From e61279186465b18b849620f8a487310e86d4bb62 Mon Sep 17 00:00:00 2001 From: Dvermetten Date: Thu, 5 Jun 2025 14:29:52 +0200 Subject: [PATCH 01/17] Update ubuntu version for CI tests --- .github/workflows/test.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index d1df7d6..e12beeb 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -6,7 +6,7 @@ jobs: build-test-python: strategy: matrix: - os: [ubuntu-20.04] + os: [ubuntu-22.04] python-version: [ "3.10", "3.11", @@ -30,9 +30,9 @@ jobs: coverage run -m --source=iohinspector unittest discover coverage report -m - name: Upload coverage report - if: ${{ (matrix.python-version == 3.12) && (matrix.os == 'ubuntu-20.04') }} + if: ${{ (matrix.python-version == 3.12) && (matrix.os == 'ubuntu-22.04') }} env: CODACY_PROJECT_TOKEN: ${{ secrets.CODACY_PROJECT_TOKEN }} run: | coverage xml -o cobertura.xml - bash <(curl -Ls https://coverage.codacy.com/get.sh) report \ No newline at end of file + bash <(curl -Ls https://coverage.codacy.com/get.sh) report From 9caa4fa9afec2720c6e6adc4a2289fef2679cc42 Mon Sep 17 00:00:00 2001 From: Dvermetten Date: Thu, 5 Jun 2025 14:36:48 +0200 Subject: [PATCH 02/17] Change align function to default --- src/iohinspector/metrics.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/src/iohinspector/metrics.py b/src/iohinspector/metrics.py index f88cbe2..62af415 100644 --- a/src/iohinspector/metrics.py +++ b/src/iohinspector/metrics.py @@ -7,7 +7,7 @@ import pandas as pd from skelo.model.elo import EloEstimator -from .align import align_data +from .align import turbo_align @@ -91,7 +91,7 @@ def aggegate_convergence( x_max = data[evaluation_variable].max() x_values = get_sequence(x_min, x_max, 50, scale_log=True, cast_to_int=True) group_variables = free_variables + [evaluation_variable] - data_aligned = align_data( + data_aligned = turbo_align( data.cast({evaluation_variable: pl.Int64}), x_values, group_cols=["data_id"] + free_variables, @@ -340,7 +340,7 @@ def aggegate_running_time( f_max = data[fval_variable].max() f_values = get_sequence(f_min, f_max, 50, scale_log=scale_flog) group_variables = free_variables + [fval_variable] - data_aligned = align_data( + data_aligned = turbo_align( data, f_values, group_cols=["data_id"] + free_variables, @@ -564,7 +564,7 @@ def get_data_ecdf( x_values = get_sequence( x_min, x_max, 50, scale_log=scale_xlog, cast_to_int=True ) - data_aligned = align_data( + data_aligned = turbo_align( data.cast({eval_var: pl.Int64}), x_values, group_cols=["data_id"], @@ -615,7 +615,7 @@ def get_trajectory(data: pl.DataFrame, else: max_fevals = traj_length + min_fevals x_values = np.arange(min_fevals, max_fevals + 1) - data_aligned = align_data( + data_aligned = turbo_align( data.cast({evaluation_variable: pl.Int64}), x_values, group_cols=["data_id"] + free_variables, From 27435e1f04ce2b457c6ccffff43c84c23c40dab2 Mon Sep 17 00:00:00 2001 From: Dvermetten Date: Wed, 18 Jun 2025 13:13:06 +0200 Subject: [PATCH 03/17] Resolve error when using polars>=1.0 in aggregations (Fixed-target) --- src/iohinspector/metrics.py | 35 +++++++++++++++++++---------------- 1 file changed, 19 insertions(+), 16 deletions(-) diff --git a/src/iohinspector/metrics.py b/src/iohinspector/metrics.py index 62af415..9d1df93 100644 --- a/src/iohinspector/metrics.py +++ b/src/iohinspector/metrics.py @@ -7,7 +7,7 @@ import pandas as pd from skelo.model.elo import EloEstimator -from .align import turbo_align +from .align import turbo_align, align_data @@ -91,7 +91,7 @@ def aggegate_convergence( x_max = data[evaluation_variable].max() x_values = get_sequence(x_min, x_max, 50, scale_log=True, cast_to_int=True) group_variables = free_variables + [evaluation_variable] - data_aligned = turbo_align( + data_aligned = align_data( data.cast({evaluation_variable: pl.Int64}), x_values, group_cols=["data_id"] + free_variables, @@ -340,7 +340,7 @@ def aggegate_running_time( f_max = data[fval_variable].max() f_values = get_sequence(f_min, f_max, 50, scale_log=scale_flog) group_variables = free_variables + [fval_variable] - data_aligned = turbo_align( + data_aligned = align_data( data, f_values, group_cols=["data_id"] + free_variables, @@ -352,23 +352,26 @@ def aggegate_running_time( max_budget = data[evaluation_variable].max() aggregations = [ - pl.col(evaluation_variable).replace(np.inf, max_budget).mean().alias("mean"), + pl.col(evaluation_variable).mean().alias("mean"), # pl.mean(evaluation_variable).alias("mean"), - pl.col(evaluation_variable).replace(np.inf, max_budget).min().alias("min"), - pl.col(evaluation_variable).replace(np.inf, max_budget).max().alias("max"), - pl.col(evaluation_variable) - .replace(np.inf, max_budget) - .median() - .alias("median"), - pl.col(evaluation_variable).replace(np.inf, max_budget).std().alias("std"), + pl.col(evaluation_variable).min().alias("min"), + pl.col(evaluation_variable).max().alias("max"), + pl.col(evaluation_variable).median().alias("median"), + pl.col(evaluation_variable).std().alias("std"), pl.col(evaluation_variable).is_finite().mean().alias("success_ratio"), pl.col(evaluation_variable).is_finite().sum().alias("success_count"), ( - pl.col(evaluation_variable).replace(np.inf, max_budget).sum() - / pl.col(evaluation_variable).is_finite().sum() + pl.when(pl.col(evaluation_variable).is_finite()) + .then(pl.col(evaluation_variable)) + .otherwise(max_budget) + .sum() + /pl.col(evaluation_variable).is_finite().sum() ).alias("ERT"), ( - pl.col(evaluation_variable).replace(np.inf, max_budget * 10).sum() + pl.when(pl.col(evaluation_variable).is_finite()) + .then(pl.col(evaluation_variable)) + .otherwise(10 * max_budget) + .sum() / pl.col(evaluation_variable).count() ).alias("PAR-10"), ] @@ -564,7 +567,7 @@ def get_data_ecdf( x_values = get_sequence( x_min, x_max, 50, scale_log=scale_xlog, cast_to_int=True ) - data_aligned = turbo_align( + data_aligned = align_data( data.cast({eval_var: pl.Int64}), x_values, group_cols=["data_id"], @@ -615,7 +618,7 @@ def get_trajectory(data: pl.DataFrame, else: max_fevals = traj_length + min_fevals x_values = np.arange(min_fevals, max_fevals + 1) - data_aligned = turbo_align( + data_aligned = align_data( data.cast({evaluation_variable: pl.Int64}), x_values, group_cols=["data_id"] + free_variables, From 9afb207bb28b6134bb4b663829eee1831790032e Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Fri, 25 Jul 2025 11:52:09 +0200 Subject: [PATCH 04/17] initial commits --- .vscode/settings.json | 11 + aux/aggregated_result.csv | 42 + aux/aligned_data.csv | 251 ++ aux/ecdf_data.csv | 42 + aux/selected_data.csv | 23 + aux/test_data/HC.zip | Bin 0 -> 18923 bytes aux/test_data/HC/IOHprofiler_f1_Sphere.json | 30 + .../HC/IOHprofiler_f2_Ellipsoid.json | 30 + .../HC/data_f1_Sphere/IOHprofiler_f1_DIM2.dat | 243 ++ 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src/iohinspector/data_processing/aocc.py | 59 + src/iohinspector/data_processing/ecdf.py | 93 + .../data_processing/normalise_objectives.py | 67 + src/iohinspector/data_processing/utils.py | 51 + src/iohinspector/metrics.py | 390 -- src/iohinspector/plot.py | 5 +- src/iohinspector/plot/__init__.py | 0 src/iohinspector/plot/plot_convergence.py | 77 + src/iohinspector/plot/plot_running_time.py | 1 + .../test_aggregate_convergence.py | 80 + .../test_aggregate_running_time.py | 92 + tests/data_processing/test_aocc.py | 75 + tests/data_processing/test_ecdf.py | 70 + .../test_normalise_objectives.py | 77 + tests/data_processing/test_utils.py | 103 + tests/test_align.py | 141 + tests/test_data/algorithm_A.zip | Bin 0 -> 1566 bytes tests/test_data/algorithm_B.zip | Bin 0 -> 1570 bytes 47 files changed, 6055 insertions(+), 392 deletions(-) create mode 100644 .vscode/settings.json create mode 100644 aux/aggregated_result.csv create mode 100644 aux/aligned_data.csv create mode 100644 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src/iohinspector/plot/__init__.py create mode 100644 src/iohinspector/plot/plot_convergence.py create mode 100644 src/iohinspector/plot/plot_running_time.py create mode 100644 tests/data_processing/test_aggregate_convergence.py create mode 100644 tests/data_processing/test_aggregate_running_time.py create mode 100644 tests/data_processing/test_aocc.py create mode 100644 tests/data_processing/test_ecdf.py create mode 100644 tests/data_processing/test_normalise_objectives.py create mode 100644 tests/data_processing/test_utils.py create mode 100644 tests/test_align.py create mode 100644 tests/test_data/algorithm_A.zip create mode 100644 tests/test_data/algorithm_B.zip diff --git a/.vscode/settings.json b/.vscode/settings.json new file mode 100644 index 0000000..e9e6a80 --- /dev/null +++ b/.vscode/settings.json @@ -0,0 +1,11 @@ +{ + "python.testing.unittestArgs": [ + "-v", + "-s", + "./tests", + "-p", + "test_*.py" + ], + "python.testing.pytestEnabled": false, + 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130825.1063182969 +52 22781.2660147740 +100 8704491.9686724935 diff --git a/aux/test_data/algorithm_A/IOHprofiler_f1_Sphere.json b/aux/test_data/algorithm_A/IOHprofiler_f1_Sphere.json new file mode 100644 index 0000000..a0161a5 --- /dev/null +++ b/aux/test_data/algorithm_A/IOHprofiler_f1_Sphere.json @@ -0,0 +1,20 @@ +{ + "version": "0.3.18", + "suite": "unknown_suite", + "function_id": 1, + "function_name": "Sphere", + "maximization": false, + "algorithm": {"name": "algorithm_A", "info": "algorithm_info"}, + "attributes": ["evaluations", "raw_y"], + "scenarios": [ + {"dimension": 2, + "path": "data_f1_Sphere/IOHprofiler_f1_DIM2.dat", + "runs": [ + {"instance": 1, "evals": 100, "best": {"evals": 32, "y": 1.3890992608930737, "x": [1.3252401375294385, -0.6679529765776291]}}, + {"instance": 1, "evals": 100, "best": {"evals": 62, "y": 0.1598690444518747, "x": [-0.13070165373855414, -1.2699173109283857]}}, + {"instance": 1, "evals": 100, "best": {"evals": 82, "y": 0.010068665100971203, "x": [0.23868848681454136, -1.2561455096951435]}}, + {"instance": 1, "evals": 100, "best": {"evals": 59, "y": 0.07535832882928815, "x": [0.029503936684615262, -1.3164784172552446]}}, + {"instance": 1, "evals": 100, "best": {"evals": 75, "y": 0.8278888460769416, "x": [0.9179632861322782, -1.7776434978790148]}} + ]} + ] +} diff --git a/aux/test_data/algorithm_A/data_f1_Sphere/IOHprofiler_f1_DIM2.dat b/aux/test_data/algorithm_A/data_f1_Sphere/IOHprofiler_f1_DIM2.dat new file mode 100644 index 0000000..5ed655f --- /dev/null +++ b/aux/test_data/algorithm_A/data_f1_Sphere/IOHprofiler_f1_DIM2.dat @@ -0,0 +1,32 @@ +evaluations raw_y +1 4.6705811572 +5 2.0741274259 +8 1.4186758054 +32 1.3890992609 +100 13.7076614579 +evaluations raw_y +1 38.2074957799 +3 31.7413875568 +5 8.4248961094 +10 5.6138868386 +16 2.5678295652 +23 0.7047566406 +62 0.1598690445 +100 24.0740622712 +evaluations raw_y +1 0.0999932311 +82 0.0100686651 +100 4.8617888738 +evaluations raw_y +1 9.7966603128 +2 7.6662875705 +14 1.3270750791 +39 1.1044300058 +59 0.0753583288 +100 19.6072478206 +evaluations raw_y +1 25.8387900554 +2 1.2497534144 +20 0.9884225642 +75 0.8278888461 +100 7.2371657867 diff --git a/aux/test_data/algorithm_B-1/IOHprofiler_f2_Ellipsoid.json b/aux/test_data/algorithm_B-1/IOHprofiler_f2_Ellipsoid.json new file mode 100644 index 0000000..ffd014e --- /dev/null +++ b/aux/test_data/algorithm_B-1/IOHprofiler_f2_Ellipsoid.json @@ -0,0 +1,20 @@ +{ + "version": "0.3.18", + "suite": "unknown_suite", + "function_id": 2, + "function_name": "Ellipsoid", + "maximization": false, + "algorithm": {"name": "algorithm_B", "info": "algorithm_info"}, + "attributes": ["evaluations", "raw_y"], + "scenarios": [ + {"dimension": 2, + "path": "data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat", + "runs": [ + {"instance": 1, "evals": 100, "best": {"evals": 87, "y": 11609.7739768967, "x": [0.29516344267328076, 0.3391906862763969]}}, + {"instance": 1, "evals": 100, "best": {"evals": 13, "y": 657.5361823281316, "x": [1.6206599386195037, 0.42232886548718795]}}, + {"instance": 1, "evals": 100, "best": {"evals": 81, "y": 178.62805438778878, "x": [-1.7835969473295243, 0.4350536967521812]}}, + {"instance": 1, "evals": 100, "best": {"evals": 58, "y": 30.53158226973449, "x": [0.6183284472467516, 0.4428117524884234]}}, + {"instance": 1, "evals": 100, "best": {"evals": 43, "y": 23.94795041556928, "x": [-2.9256749775245927, 0.4507827499735342]}} + ]} + ] +} diff --git a/aux/test_data/algorithm_B-1/data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat b/aux/test_data/algorithm_B-1/data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat new file mode 100644 index 0000000..c062494 --- /dev/null +++ b/aux/test_data/algorithm_B-1/data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat @@ -0,0 +1,40 @@ +evaluations raw_y +1 3528166.0406847419 +4 744814.7493350349 +8 37276.0601619882 +42 21571.0841027235 +43 16160.6522549923 +87 11609.7739768967 +100 12812972.6885809544 +evaluations raw_y +1 15364893.2870349139 +2 4984270.1343410257 +4 40617.2399955599 +7 929.8770978985 +13 657.5361823281 +100 10063638.7089125942 +evaluations raw_y +1 2017251.6716084427 +3 510774.6558958815 +15 63089.7385168056 +16 11364.9563005321 +58 3117.4638045791 +81 178.6280543878 +100 195055.3690568440 +evaluations raw_y +1 10846545.5767801087 +2 2759110.7893186668 +4 1184995.7843317564 +10 23636.8911983180 +32 10168.1942744350 +58 30.5315822697 +100 5304411.0058515267 +evaluations raw_y +1 17706967.6324726678 +2 10410791.1098473761 +3 7602089.6820298862 +5 999728.8128686354 +10 165506.9318883194 +14 1573.0257767019 +43 23.9479504156 +100 10079048.2146880087 diff --git a/aux/test_data/algorithm_B/IOHprofiler_f1_Sphere.json b/aux/test_data/algorithm_B/IOHprofiler_f1_Sphere.json new file mode 100644 index 0000000..dceb8b0 --- /dev/null +++ b/aux/test_data/algorithm_B/IOHprofiler_f1_Sphere.json @@ -0,0 +1,20 @@ +{ + "version": "0.3.18", + "suite": "unknown_suite", + "function_id": 1, + "function_name": "Sphere", + "maximization": false, + "algorithm": {"name": "algorithm_B", "info": "algorithm_info"}, + "attributes": ["evaluations", "raw_y"], + "scenarios": [ + {"dimension": 2, + "path": "data_f1_Sphere/IOHprofiler_f1_DIM2.dat", + "runs": [ + {"instance": 1, "evals": 100, "best": {"evals": 37, "y": 0.29456573867088964, "x": [-0.17052431245760946, -0.8171497899997968]}}, + {"instance": 1, "evals": 100, "best": {"evals": 24, "y": 0.3519490828283901, "x": [0.42243360688378573, -0.5883164714400362]}}, + {"instance": 1, "evals": 100, "best": {"evals": 51, "y": 0.48023489188889634, "x": [-0.33373309604302204, -1.5258715637042277]}}, + {"instance": 1, "evals": 100, "best": {"evals": 62, "y": 0.446875155274288, "x": [0.8803554890888989, -0.9264757429433876]}}, + {"instance": 1, "evals": 100, "best": {"evals": 53, "y": 0.03062066834897717, "x": [0.4222045538424135, -1.2006493498974602]}} + ]} + ] +} diff --git a/aux/test_data/algorithm_B/data_f1_Sphere/IOHprofiler_f1_DIM2.dat b/aux/test_data/algorithm_B/data_f1_Sphere/IOHprofiler_f1_DIM2.dat new file mode 100644 index 0000000..f52aff4 --- /dev/null +++ b/aux/test_data/algorithm_B/data_f1_Sphere/IOHprofiler_f1_DIM2.dat @@ -0,0 +1,33 @@ +evaluations raw_y +1 5.6274529163 +2 2.0751885414 +37 0.2945657387 +100 15.7624012302 +evaluations raw_y +1 11.9763916365 +3 0.6855510894 +10 0.3961235617 +24 0.3519490828 +100 37.6045678832 +evaluations raw_y +1 15.8275848238 +5 10.7151568141 +6 4.6825960131 +22 1.8375898614 +51 0.4802348919 +100 2.7173100090 +evaluations raw_y +1 18.0985016267 +3 7.2030475703 +32 2.4516207358 +39 1.3300836641 +62 0.4468751553 +100 7.9788187616 +evaluations raw_y +1 16.1975708999 +2 11.5814621723 +5 9.7435745645 +6 4.7534918694 +10 0.4365425564 +53 0.0306206683 +100 4.4659419085 diff --git a/aux/try.ipynb b/aux/try.ipynb new file mode 100644 index 0000000..396bd6a --- /dev/null +++ b/aux/try.ipynb @@ -0,0 +1,3411 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "id": "680015a1", + "metadata": {}, + "outputs": [], + "source": [ + "import iohinspector\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "7c8ac34d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape: (30, 11)\n", + "┌─────────┬──────────────┬──────────────┬──────────────┬───┬──────────┬────────┬───────┬───────────┐\n", + "│ data_id ┆ algorithm_na ┆ algorithm_in ┆ suite ┆ … ┆ instance ┆ run_id ┆ evals ┆ best_y │\n", + "│ --- ┆ me ┆ fo ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ u16 ┆ u32 ┆ u64 ┆ f64 │\n", + "│ ┆ str ┆ str ┆ ┆ ┆ ┆ ┆ ┆ │\n", + "╞═════════╪══════════════╪══════════════╪══════════════╪═══╪══════════╪════════╪═══════╪═══════════╡\n", + "│ 1 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 1 ┆ 1 ┆ 1000 ┆ 47.150496 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 2 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 2 ┆ 2 ┆ 1000 ┆ 41.120049 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 3 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 3 ┆ 3 ┆ 1000 ┆ 36.072013 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 4 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 4 ┆ 4 ┆ 1000 ┆ 31.407138 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 5 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 5 ┆ 5 ┆ 1000 ┆ 25.438597 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ 26 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 11 ┆ 11 ┆ 1000 ┆ 0.036231 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 27 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 12 ┆ 12 ┆ 1000 ┆ 0.049588 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 28 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 13 ┆ 13 ┆ 1000 ┆ 0.080143 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 29 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 14 ┆ 14 ┆ 1000 ┆ 0.008005 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "│ 30 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 15 ┆ 15 ┆ 1000 ┆ 0.009005 │\n", + "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", + "└─────────┴──────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴───────────┘\n" + ] + }, + { + "ename": "AttributeError", + "evalue": "module 'iohinspector' has no attribute 'data_processing'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[3], line 10\u001b[0m\n\u001b[1;32m 7\u001b[0m selection \u001b[38;5;241m=\u001b[39m manager\u001b[38;5;241m.\u001b[39mselect(function_ids\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m1\u001b[39m], algorithms\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRandomSearch\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m 8\u001b[0m df \u001b[38;5;241m=\u001b[39m selection\u001b[38;5;241m.\u001b[39mload(monotonic\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, include_meta_data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,)\n\u001b[0;32m---> 10\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43miohinspector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata_processing\u001b[49m\u001b[38;5;241m.\u001b[39maggregate_convergence(df)\n\u001b[1;32m 11\u001b[0m result\u001b[38;5;241m.\u001b[39mto_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maggregated_result.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28mprint\u001b[39m(result)\n", + "\u001b[0;31mAttributeError\u001b[0m: module 'iohinspector' has no attribute 'data_processing'" + ] + } + ], + "source": [ + "manager = iohinspector.DataManager()\n", + "data_folders = [\"test_data/RS\"]\n", + "manager.add_folders(data_folders)\n", + "\n", + "manager.overview\n", + "print(manager.overview)\n", + "selection = manager.select(function_ids=[1], algorithms=['RandomSearch'])\n", + "df = selection.load(monotonic=True, include_meta_data=True,)\n", + "\n", + "result = iohinspector.data_processing.aggregate_convergence(df)\n", + "result.to_csv(\"aggregated_result.csv\", index=False)\n", + "\n", + "print(result)\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3da32d5c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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raw_yalgorithm_namevariablevalue
3500.003647RandomSearchERT12270.000000
3770.943782RandomSearchERT53.133333
3781.159419RandomSearchERT37.533333
3791.424324RandomSearchERT25.466667
3801.749754RandomSearchERT19.066667
3812.149540RandomSearchERT17.266667
3822.640669RandomSearchERT13.333333
3833.244012RandomSearchERT12.466667
3843.985206RandomSearchERT8.066667
3854.895750RandomSearchERT4.933333
3866.014336RandomSearchERT4.200000
3877.388497RandomSearchERT3.733333
3889.076628RandomSearchERT3.400000
38911.150465RandomSearchERT3.400000
39013.698134RandomSearchERT3.066667
39116.827897RandomSearchERT2.600000
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3550.010204RandomSearchERT2857.000000
3560.012535RandomSearchERT2230.000000
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3610.035073RandomSearchERT2181.400000
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None None \n", + "13 20.0 RandomSearch 23.0 None None None \n", + "14 23.0 RandomSearch 23.0 None None None \n", + "15 27.0 RandomSearch 23.0 None None None \n", + "16 31.0 RandomSearch 23.0 None None None \n", + "17 35.0 RandomSearch 23.0 None None None \n", + "18 41.0 RandomSearch 23.0 None None None \n", + "19 47.0 RandomSearch 23.0 None None None \n", + "20 54.0 RandomSearch 23.0 None None None \n", + "21 62.0 RandomSearch 23.0 None None None \n", + "22 71.0 RandomSearch 23.0 None None None \n", + "23 81.0 RandomSearch 23.0 None None None \n", + "24 93.0 RandomSearch 23.0 None None None \n", + "25 107.0 RandomSearch 23.0 None None None \n", + "26 123.0 RandomSearch 23.0 None None None \n", + "27 141.0 RandomSearch 23.0 None None None \n", + "28 162.0 RandomSearch 23.0 None None None \n", + "29 186.0 RandomSearch 23.0 None None None \n", + "30 213.0 RandomSearch 23.0 None None None \n", + "31 245.0 RandomSearch 23.0 None None None \n", + "32 281.0 RandomSearch 23.0 None None None \n", + "33 323.0 RandomSearch 23.0 None None None \n", + "34 370.0 RandomSearch 23.0 None None None \n", + "35 425.0 RandomSearch 23.0 None None None \n", + "36 488.0 RandomSearch 23.0 None None None \n", + "37 560.0 RandomSearch 23.0 None None None \n", + "38 643.0 RandomSearch 23.0 None None None \n", + "39 738.0 RandomSearch 23.0 None None None \n", + "40 846.0 RandomSearch 23.0 None None None \n", + "\n", + " function_id dimension instance run_id evals best_y raw_y \\\n", + "0 1.0 2.0 8.0 8.0 1000.0 0.050848 25.374196 \n", + "1 1.0 2.0 8.0 8.0 1000.0 0.050848 16.547486 \n", + "2 1.0 2.0 8.0 8.0 1000.0 0.050848 13.520373 \n", + "3 1.0 2.0 8.0 8.0 1000.0 0.050848 8.487365 \n", + "4 1.0 2.0 8.0 8.0 1000.0 0.050848 4.720136 \n", + "5 1.0 2.0 8.0 8.0 1000.0 0.050848 4.562542 \n", + "6 1.0 2.0 8.0 8.0 1000.0 0.050848 4.365324 \n", + "7 1.0 2.0 8.0 8.0 1000.0 0.050848 2.460843 \n", + "8 1.0 2.0 8.0 8.0 1000.0 0.050848 2.195116 \n", + "9 1.0 2.0 8.0 8.0 1000.0 0.050848 2.149442 \n", + "10 1.0 2.0 8.0 8.0 1000.0 0.050848 1.876434 \n", + "11 1.0 2.0 8.0 8.0 1000.0 0.050848 1.747187 \n", + "12 1.0 2.0 8.0 8.0 1000.0 0.050848 1.690374 \n", + "13 1.0 2.0 8.0 8.0 1000.0 0.050848 1.658065 \n", + "14 1.0 2.0 8.0 8.0 1000.0 0.050848 1.596924 \n", + "15 1.0 2.0 8.0 8.0 1000.0 0.050848 1.570934 \n", + "16 1.0 2.0 8.0 8.0 1000.0 0.050848 1.233668 \n", + "17 1.0 2.0 8.0 8.0 1000.0 0.050848 1.176390 \n", + "18 1.0 2.0 8.0 8.0 1000.0 0.050848 1.110986 \n", + "19 1.0 2.0 8.0 8.0 1000.0 0.050848 0.955180 \n", + "20 1.0 2.0 8.0 8.0 1000.0 0.050848 0.772736 \n", + "21 1.0 2.0 8.0 8.0 1000.0 0.050848 0.557273 \n", + "22 1.0 2.0 8.0 8.0 1000.0 0.050848 0.539598 \n", + "23 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", + "24 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", + "25 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", + "26 1.0 2.0 8.0 8.0 1000.0 0.050848 0.441284 \n", + "27 1.0 2.0 8.0 8.0 1000.0 0.050848 0.370179 \n", + "28 1.0 2.0 8.0 8.0 1000.0 0.050848 0.367697 \n", + "29 1.0 2.0 8.0 8.0 1000.0 0.050848 0.249915 \n", + "30 1.0 2.0 8.0 8.0 1000.0 0.050848 0.239561 \n", + "31 1.0 2.0 8.0 8.0 1000.0 0.050848 0.166140 \n", + "32 1.0 2.0 8.0 8.0 1000.0 0.050848 0.121428 \n", + "33 1.0 2.0 8.0 8.0 1000.0 0.050848 0.116758 \n", + "34 1.0 2.0 8.0 8.0 1000.0 0.050848 0.107114 \n", + "35 1.0 2.0 8.0 8.0 1000.0 0.050848 0.080108 \n", + "36 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", + "37 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", + "38 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", + "39 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", + "40 1.0 2.0 8.0 8.0 1000.0 0.050848 0.052513 \n", + "\n", + " x0 x1 eaf \n", + "0 -0.344009 0.512334 0.201003 \n", + "1 -1.339305 1.030883 0.239653 \n", + "2 -0.852911 0.122410 0.263143 \n", + "3 0.031484 -0.732846 0.310235 \n", + "4 -0.327776 -0.388880 0.338184 \n", + "5 -0.061125 -0.570694 0.340710 \n", + "6 0.039378 -0.727321 0.350441 \n", + "7 -0.279667 -0.614688 0.390438 \n", + "8 -0.170377 -0.543626 0.403285 \n", + "9 -0.099207 -0.475165 0.405066 \n", + "10 -0.184409 -0.356682 0.413452 \n", + "11 -0.019840 -0.479648 0.415803 \n", + "12 -0.054411 -0.533827 0.432404 \n", + "13 -0.034062 -0.619582 0.436056 \n", + "14 -0.225230 -0.604956 0.438971 \n", + "15 -0.363783 -0.500821 0.439721 \n", + "16 -0.307221 -0.517126 0.471457 \n", + "17 -0.377140 -0.559536 0.486837 \n", + "18 -0.430195 -0.451153 0.490702 \n", + "19 -0.498781 -0.168115 0.502124 \n", + "20 -0.695775 -0.191861 0.523181 \n", + "21 -0.657877 -0.232111 0.541659 \n", + "22 -0.587752 -0.351059 0.547855 \n", + "23 -0.537835 -0.350695 0.553562 \n", + "24 -0.537835 -0.350695 0.553562 \n", + "25 -0.537835 -0.350695 0.553562 \n", + "26 -0.604819 -0.302447 0.561017 \n", + "27 -0.589226 -0.287474 0.591139 \n", + "28 -0.596643 -0.308843 0.593472 \n", + "29 -0.645870 -0.187600 0.635569 \n", + "30 -0.618717 -0.262432 0.637952 \n", + "31 -0.579345 -0.186999 0.655059 \n", + "32 -0.555937 -0.238782 0.684741 \n", + "33 -0.510889 -0.238044 0.688370 \n", + "34 -0.523574 -0.239427 0.693564 \n", + "35 -0.511887 -0.309281 0.727367 \n", + "36 -0.493136 -0.268471 0.744833 \n", + "37 -0.493136 -0.268471 0.744833 \n", + "38 -0.531623 -0.244816 0.764570 \n", + "39 -0.531623 -0.244816 0.764570 \n", + "40 -0.550382 -0.230939 0.780203 \n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/align.py:109: UserWarning: Sortedness of columns cannot be checked when 'by' groups provided\n", + " result_df = x_vals.join_asof(\n" + ] + }, + { + "data": { + "text/html": [ + "
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evaluationsalgorithm_namedata_idalgorithm_infosuitefunction_namefunction_iddimensioninstancerun_idevalsbest_yraw_yx0x1eaf
01RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.05084825.374196-0.3440090.5123340.433702
12RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.05084816.547486-1.3393051.0308830.444280
23RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.05084813.520373-0.8529110.1224100.450709
34RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508488.4873650.031484-0.7328460.463598
45RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508484.720136-0.327776-0.3888800.471247
56RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508484.562542-0.061125-0.5706940.471938
67RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508484.3653240.039378-0.7273210.474602
79RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508482.460843-0.279667-0.6146880.485548
810RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508482.195116-0.170377-0.5436260.489064
911RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508482.149442-0.099207-0.4751650.489552
1013RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.876434-0.184409-0.3566820.491847
1115RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.747187-0.019840-0.4796480.492490
1217RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.690374-0.054411-0.5338270.497034
1320RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.658065-0.034062-0.6195820.498034
1423RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.596924-0.225230-0.6049560.498831
1527RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.570934-0.363783-0.5008210.499036
1631RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.233668-0.307221-0.5171260.507722
1735RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.176390-0.377140-0.5595360.511932
1841RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.110986-0.430195-0.4511530.512990
1947RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.955180-0.498781-0.1681150.516116
2054RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.772736-0.695775-0.1918610.521879
2162RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.557273-0.657877-0.2321110.526936
2271RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.539598-0.587752-0.3510590.528632
2381RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.491967-0.537835-0.3506950.530194
2493RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.491967-0.537835-0.3506950.530194
25107RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.491967-0.537835-0.3506950.530194
26123RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.441284-0.604819-0.3024470.532234
27141RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.370179-0.589226-0.2874740.540478
28162RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.367697-0.596643-0.3088430.541117
29186RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.249915-0.645870-0.1876000.552638
30213RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.239561-0.618717-0.2624320.553290
31245RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.166140-0.579345-0.1869990.557972
32281RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.121428-0.555937-0.2387820.566096
33323RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.116758-0.510889-0.2380440.567089
34370RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.107114-0.523574-0.2394270.568511
35425RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.080108-0.511887-0.3092810.577763
36488RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.068726-0.493136-0.2684710.582543
37560RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.068726-0.493136-0.2684710.582543
38643RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.058300-0.531623-0.2448160.587945
39738RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.058300-0.531623-0.2448160.587945
40846RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.052513-0.550382-0.2309390.592223
\n", + "
" + ], + "text/plain": [ + " evaluations algorithm_name data_id algorithm_info suite function_name \\\n", + "0 1 RandomSearch 23.0 None None None \n", + "1 2 RandomSearch 23.0 None None None \n", + "2 3 RandomSearch 23.0 None None None \n", + "3 4 RandomSearch 23.0 None None None \n", + "4 5 RandomSearch 23.0 None None None \n", + "5 6 RandomSearch 23.0 None None None \n", + "6 7 RandomSearch 23.0 None None None \n", + "7 9 RandomSearch 23.0 None None None \n", + "8 10 RandomSearch 23.0 None None None \n", + "9 11 RandomSearch 23.0 None None None \n", + "10 13 RandomSearch 23.0 None None None \n", + "11 15 RandomSearch 23.0 None None None \n", + "12 17 RandomSearch 23.0 None None None \n", + "13 20 RandomSearch 23.0 None None None \n", + "14 23 RandomSearch 23.0 None None None \n", + "15 27 RandomSearch 23.0 None None None \n", + "16 31 RandomSearch 23.0 None None None \n", + "17 35 RandomSearch 23.0 None None None \n", + "18 41 RandomSearch 23.0 None None None \n", + "19 47 RandomSearch 23.0 None None None \n", + "20 54 RandomSearch 23.0 None None None \n", + "21 62 RandomSearch 23.0 None None None \n", + "22 71 RandomSearch 23.0 None None None \n", + "23 81 RandomSearch 23.0 None None None \n", + "24 93 RandomSearch 23.0 None None None \n", + "25 107 RandomSearch 23.0 None None None \n", + "26 123 RandomSearch 23.0 None None None \n", + "27 141 RandomSearch 23.0 None None None \n", + "28 162 RandomSearch 23.0 None None None \n", + "29 186 RandomSearch 23.0 None None None \n", + "30 213 RandomSearch 23.0 None None None \n", + "31 245 RandomSearch 23.0 None None None \n", + "32 281 RandomSearch 23.0 None None None \n", + "33 323 RandomSearch 23.0 None None None \n", + "34 370 RandomSearch 23.0 None None None \n", + "35 425 RandomSearch 23.0 None None None \n", + "36 488 RandomSearch 23.0 None None None \n", + "37 560 RandomSearch 23.0 None None None \n", + "38 643 RandomSearch 23.0 None None None \n", + "39 738 RandomSearch 23.0 None None None \n", + "40 846 RandomSearch 23.0 None None None \n", + "\n", + " function_id dimension instance run_id evals best_y raw_y \\\n", + "0 1.0 2.0 8.0 8.0 1000.0 0.050848 25.374196 \n", + "1 1.0 2.0 8.0 8.0 1000.0 0.050848 16.547486 \n", + "2 1.0 2.0 8.0 8.0 1000.0 0.050848 13.520373 \n", + "3 1.0 2.0 8.0 8.0 1000.0 0.050848 8.487365 \n", + "4 1.0 2.0 8.0 8.0 1000.0 0.050848 4.720136 \n", + "5 1.0 2.0 8.0 8.0 1000.0 0.050848 4.562542 \n", + "6 1.0 2.0 8.0 8.0 1000.0 0.050848 4.365324 \n", + "7 1.0 2.0 8.0 8.0 1000.0 0.050848 2.460843 \n", + "8 1.0 2.0 8.0 8.0 1000.0 0.050848 2.195116 \n", + "9 1.0 2.0 8.0 8.0 1000.0 0.050848 2.149442 \n", + "10 1.0 2.0 8.0 8.0 1000.0 0.050848 1.876434 \n", + "11 1.0 2.0 8.0 8.0 1000.0 0.050848 1.747187 \n", + "12 1.0 2.0 8.0 8.0 1000.0 0.050848 1.690374 \n", + "13 1.0 2.0 8.0 8.0 1000.0 0.050848 1.658065 \n", + "14 1.0 2.0 8.0 8.0 1000.0 0.050848 1.596924 \n", + "15 1.0 2.0 8.0 8.0 1000.0 0.050848 1.570934 \n", + "16 1.0 2.0 8.0 8.0 1000.0 0.050848 1.233668 \n", + "17 1.0 2.0 8.0 8.0 1000.0 0.050848 1.176390 \n", + "18 1.0 2.0 8.0 8.0 1000.0 0.050848 1.110986 \n", + "19 1.0 2.0 8.0 8.0 1000.0 0.050848 0.955180 \n", + "20 1.0 2.0 8.0 8.0 1000.0 0.050848 0.772736 \n", + "21 1.0 2.0 8.0 8.0 1000.0 0.050848 0.557273 \n", + "22 1.0 2.0 8.0 8.0 1000.0 0.050848 0.539598 \n", + "23 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", + "24 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", + "25 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", + "26 1.0 2.0 8.0 8.0 1000.0 0.050848 0.441284 \n", + "27 1.0 2.0 8.0 8.0 1000.0 0.050848 0.370179 \n", + "28 1.0 2.0 8.0 8.0 1000.0 0.050848 0.367697 \n", + "29 1.0 2.0 8.0 8.0 1000.0 0.050848 0.249915 \n", + "30 1.0 2.0 8.0 8.0 1000.0 0.050848 0.239561 \n", + "31 1.0 2.0 8.0 8.0 1000.0 0.050848 0.166140 \n", + "32 1.0 2.0 8.0 8.0 1000.0 0.050848 0.121428 \n", + "33 1.0 2.0 8.0 8.0 1000.0 0.050848 0.116758 \n", + "34 1.0 2.0 8.0 8.0 1000.0 0.050848 0.107114 \n", + "35 1.0 2.0 8.0 8.0 1000.0 0.050848 0.080108 \n", + "36 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", + "37 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", + "38 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", + "39 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", + "40 1.0 2.0 8.0 8.0 1000.0 0.050848 0.052513 \n", + "\n", + " x0 x1 eaf \n", + "0 -0.344009 0.512334 0.433702 \n", + "1 -1.339305 1.030883 0.444280 \n", + "2 -0.852911 0.122410 0.450709 \n", + "3 0.031484 -0.732846 0.463598 \n", + "4 -0.327776 -0.388880 0.471247 \n", + "5 -0.061125 -0.570694 0.471938 \n", + "6 0.039378 -0.727321 0.474602 \n", + "7 -0.279667 -0.614688 0.485548 \n", + "8 -0.170377 -0.543626 0.489064 \n", + "9 -0.099207 -0.475165 0.489552 \n", + "10 -0.184409 -0.356682 0.491847 \n", + "11 -0.019840 -0.479648 0.492490 \n", + "12 -0.054411 -0.533827 0.497034 \n", + "13 -0.034062 -0.619582 0.498034 \n", + "14 -0.225230 -0.604956 0.498831 \n", + "15 -0.363783 -0.500821 0.499036 \n", + "16 -0.307221 -0.517126 0.507722 \n", + "17 -0.377140 -0.559536 0.511932 \n", + "18 -0.430195 -0.451153 0.512990 \n", + "19 -0.498781 -0.168115 0.516116 \n", + "20 -0.695775 -0.191861 0.521879 \n", + "21 -0.657877 -0.232111 0.526936 \n", + "22 -0.587752 -0.351059 0.528632 \n", + "23 -0.537835 -0.350695 0.530194 \n", + "24 -0.537835 -0.350695 0.530194 \n", + "25 -0.537835 -0.350695 0.530194 \n", + "26 -0.604819 -0.302447 0.532234 \n", + "27 -0.589226 -0.287474 0.540478 \n", + "28 -0.596643 -0.308843 0.541117 \n", + "29 -0.645870 -0.187600 0.552638 \n", + "30 -0.618717 -0.262432 0.553290 \n", + "31 -0.579345 -0.186999 0.557972 \n", + "32 -0.555937 -0.238782 0.566096 \n", + "33 -0.510889 -0.238044 0.567089 \n", + "34 -0.523574 -0.239427 0.568511 \n", + "35 -0.511887 -0.309281 0.577763 \n", + "36 -0.493136 -0.268471 0.582543 \n", + "37 -0.493136 -0.268471 0.582543 \n", + "38 -0.531623 -0.244816 0.587945 \n", + "39 -0.531623 -0.244816 0.587945 \n", + "40 -0.550382 -0.230939 0.592223 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = iohinspector.get_data_ecdf(\n", + " df\n", + ")\n", + "print(data)\n", + "data.to_csv(\"ecdf_data.csv\", index=False)\n", + "iohinspector.plot_ecdf(\n", + " df,\n", + " y_min = 1.0,\n", + " y_max = 1.0,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "be98d83c", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n", + "thread '' panicked at crates/polars-python/src/dataframe/general.rs:351:73:\n", + "called `Result::unwrap()` on an `Err` value: PyErr { type: , value: KeyboardInterrupt(), traceback: Some(\"Traceback (most recent call last):\\n File \\\"/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/_utils/wrap.py\\\", line 12, in wrap_df\\n def wrap_df(df: PyDataFrame) -> DataFrame:\\n\") }\n", + "note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace\n" + ] + }, + { + "ename": "PanicException", + "evalue": "called `Result::unwrap()` on an `Err` value: PyErr { type: , value: KeyboardInterrupt(), traceback: Some(\"Traceback (most recent call last):\\n File \\\"/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/_utils/wrap.py\\\", line 12, in wrap_df\\n def wrap_df(df: PyDataFrame) -> DataFrame:\\n\") }", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mPanicException\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43miohinspector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43maggegate_convergence\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfree_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43malgorithm_name\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m result\u001b[38;5;241m.\u001b[39mto_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maggregated_result.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(result)\n", + "File \u001b[0;32m~/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/metrics.py:94\u001b[0m, in \u001b[0;36maggegate_convergence\u001b[0;34m(data, evaluation_variable, fval_variable, free_variables, x_min, x_max, custom_op, maximization, return_as_pandas)\u001b[0m\n\u001b[1;32m 92\u001b[0m x_values \u001b[38;5;241m=\u001b[39m get_sequence(x_min, x_max, \u001b[38;5;241m50\u001b[39m, scale_log\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, cast_to_int\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 93\u001b[0m group_variables \u001b[38;5;241m=\u001b[39m free_variables \u001b[38;5;241m+\u001b[39m [evaluation_variable]\n\u001b[0;32m---> 94\u001b[0m data_aligned \u001b[38;5;241m=\u001b[39m \u001b[43malign_data\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 95\u001b[0m \u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcast\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[43mevaluation_variable\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mInt64\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 96\u001b[0m \u001b[43m \u001b[49m\u001b[43mx_values\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 97\u001b[0m \u001b[43m \u001b[49m\u001b[43mgroup_cols\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdata_id\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mfree_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 98\u001b[0m \u001b[43m \u001b[49m\u001b[43mx_col\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mevaluation_variable\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 99\u001b[0m \u001b[43m \u001b[49m\u001b[43my_col\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfval_variable\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 100\u001b[0m \u001b[43m \u001b[49m\u001b[43mmaximization\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmaximization\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 101\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 103\u001b[0m aggregations \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 104\u001b[0m pl\u001b[38;5;241m.\u001b[39mmean(fval_variable)\u001b[38;5;241m.\u001b[39malias(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmean\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 105\u001b[0m pl\u001b[38;5;241m.\u001b[39mmin(fval_variable)\u001b[38;5;241m.\u001b[39malias(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmin\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 111\u001b[0m \u001b[38;5;241m.\u001b[39malias(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgeometric_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 112\u001b[0m ]\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m custom_op \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/align.py:58\u001b[0m, in \u001b[0;36malign_data\u001b[0;34m(df, evals, group_cols, x_col, y_col, output, maximization)\u001b[0m\n\u001b[1;32m 55\u001b[0m merged \u001b[38;5;241m=\u001b[39m merged\u001b[38;5;241m.\u001b[39mwith_columns(pl\u001b[38;5;241m.\u001b[39mlit(group[col][\u001b[38;5;241m0\u001b[39m])\u001b[38;5;241m.\u001b[39malias(col))\n\u001b[1;32m 56\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m merged\n\u001b[0;32m---> 58\u001b[0m result_df \u001b[38;5;241m=\u001b[39m \u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroup_by\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mgroup_cols\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmap_groups\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmerge_asof_group\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m output \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlong\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 61\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m result_df\n", + "File \u001b[0;32m~/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/dataframe/group_by.py:313\u001b[0m, in \u001b[0;36mGroupBy.map_groups\u001b[0;34m(self, function)\u001b[0m\n\u001b[1;32m 309\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot call `map_groups` when grouping by an expression\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 310\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[1;32m 312\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdf\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m_from_pydf(\n\u001b[0;32m--> 313\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroup_by_map_groups\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 314\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mby\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunction\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaintain_order\u001b[49m\n\u001b[1;32m 315\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 316\u001b[0m )\n", + "\u001b[0;31mPanicException\u001b[0m: called `Result::unwrap()` on an `Err` value: PyErr { type: , value: KeyboardInterrupt(), traceback: Some(\"Traceback (most recent call last):\\n File \\\"/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/_utils/wrap.py\\\", line 12, in wrap_df\\n def wrap_df(df: PyDataFrame) -> DataFrame:\\n\") }" + ] + } + ], + "source": [ + "\n", + "\n", + "result = iohinspector.aggegate_convergence(df, free_variables=[\"algorithm_name\"])\n", + "result.to_csv(\"aggregated_result.csv\", index=False)\n", + "\n", + "print(result)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3ec53f22", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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evaluationsalgorithm_namevariablevalue
1701.0RandomSearchgeometric_mean11.502018
20182.0RandomSearchgeometric_mean0.328777
20075.0RandomSearchgeometric_mean0.344017
19968.0RandomSearchgeometric_mean0.349327
19862.0RandomSearchgeometric_mean0.370701
19756.0RandomSearchgeometric_mean0.425972
19651.0RandomSearchgeometric_mean0.462630
19547.0RandomSearchgeometric_mean0.552266
19442.0RandomSearchgeometric_mean0.619678
19339.0RandomSearchgeometric_mean0.619678
19235.0RandomSearchgeometric_mean0.644307
19132.0RandomSearchgeometric_mean0.676764
19029.0RandomSearchgeometric_mean0.768394
18926.0RandomSearchgeometric_mean1.044003
18824.0RandomSearchgeometric_mean1.044003
18722.0RandomSearchgeometric_mean1.044003
18620.0RandomSearchgeometric_mean1.075136
18518.0RandomSearchgeometric_mean1.115466
1712.0RandomSearchgeometric_mean7.789763
1723.0RandomSearchgeometric_mean6.146942
1734.0RandomSearchgeometric_mean3.823311
1745.0RandomSearchgeometric_mean2.884371
1756.0RandomSearchgeometric_mean2.811844
1767.0RandomSearchgeometric_mean2.549035
20291.0RandomSearchgeometric_mean0.328777
1778.0RandomSearchgeometric_mean1.989434
17910.0RandomSearchgeometric_mean1.496137
18011.0RandomSearchgeometric_mean1.469509
18112.0RandomSearchgeometric_mean1.449580
18213.0RandomSearchgeometric_mean1.350359
18315.0RandomSearchgeometric_mean1.318729
18416.0RandomSearchgeometric_mean1.115466
1789.0RandomSearchgeometric_mean1.703058
20399.0RandomSearchgeometric_mean0.328777
\n", + "
" + ], + "text/plain": [ + " evaluations algorithm_name variable value\n", + "170 1.0 RandomSearch geometric_mean 11.502018\n", + "201 82.0 RandomSearch geometric_mean 0.328777\n", + "200 75.0 RandomSearch geometric_mean 0.344017\n", + "199 68.0 RandomSearch geometric_mean 0.349327\n", + "198 62.0 RandomSearch geometric_mean 0.370701\n", + "197 56.0 RandomSearch geometric_mean 0.425972\n", + "196 51.0 RandomSearch geometric_mean 0.462630\n", + "195 47.0 RandomSearch geometric_mean 0.552266\n", + "194 42.0 RandomSearch geometric_mean 0.619678\n", + "193 39.0 RandomSearch geometric_mean 0.619678\n", + "192 35.0 RandomSearch geometric_mean 0.644307\n", + "191 32.0 RandomSearch geometric_mean 0.676764\n", + "190 29.0 RandomSearch geometric_mean 0.768394\n", + "189 26.0 RandomSearch geometric_mean 1.044003\n", + "188 24.0 RandomSearch geometric_mean 1.044003\n", + "187 22.0 RandomSearch geometric_mean 1.044003\n", + "186 20.0 RandomSearch geometric_mean 1.075136\n", + "185 18.0 RandomSearch geometric_mean 1.115466\n", + "171 2.0 RandomSearch geometric_mean 7.789763\n", + "172 3.0 RandomSearch geometric_mean 6.146942\n", + "173 4.0 RandomSearch geometric_mean 3.823311\n", + "174 5.0 RandomSearch geometric_mean 2.884371\n", + "175 6.0 RandomSearch geometric_mean 2.811844\n", + "176 7.0 RandomSearch geometric_mean 2.549035\n", + "202 91.0 RandomSearch geometric_mean 0.328777\n", + "177 8.0 RandomSearch geometric_mean 1.989434\n", + "179 10.0 RandomSearch geometric_mean 1.496137\n", + "180 11.0 RandomSearch geometric_mean 1.469509\n", + "181 12.0 RandomSearch geometric_mean 1.449580\n", + "182 13.0 RandomSearch geometric_mean 1.350359\n", + "183 15.0 RandomSearch geometric_mean 1.318729\n", + "184 16.0 RandomSearch geometric_mean 1.115466\n", + "178 9.0 RandomSearch geometric_mean 1.703058\n", + "203 99.0 RandomSearch geometric_mean 0.328777" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "iohinspector.single_function_fixedbudget(\n", + " df,\n", + " x_min = 1,\n", + " x_max = 100,\n", + " \n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b5441187", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape: (15,)\n", + "Series: 'data_id' [u64]\n", + "[\n", + "\t16\n", + "\t17\n", + "\t18\n", + "\t19\n", + "\t20\n", + "\t…\n", + "\t26\n", + "\t27\n", + "\t28\n", + "\t29\n", + "\t30\n", + "]\n", + "shape: (1,)\n", + "Series: 'run_id' [u32]\n", + "[\n", + "\t1\n", + "]\n" + ] + } + ], + "source": [ + "print(df[\"data_id\"].unique())\n", + "df_one_run = df.filter(df[\"data_id\"] == 16)\n", + "print(df_one_run[\"run_id\"].unique())\n", + "# iohinspector.heatmap_single_run(\n", + "# df_one_run,\n", + "# var_cols=[\"x1\"],\n", + "# x_mins=[-5]*len(df_one_run[\"x1\"]),\n", + "# x_maxs=[5]*len(df_one_run[\"x1\"])\n", + "# )\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "429e1ce2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['data_id', 'algorithm_name', 'algorithm_info', 'suite', 'function_name', 'function_id', 'dimension', 'instance', 'run_id', 'evals', 'best_y']\n", + "shape: (327, 15)\n", + "┌─────────┬────────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n", + "│ data_id ┆ algorithm_ ┆ algorithm ┆ suite ┆ … ┆ evaluatio ┆ raw_y ┆ x0 ┆ x1 │\n", + "│ --- ┆ name ┆ _info ┆ --- ┆ ┆ ns ┆ --- ┆ --- ┆ --- │\n", + "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ --- ┆ f64 ┆ f64 ┆ f64 │\n", + "│ ┆ str ┆ str ┆ ┆ ┆ u64 ┆ ┆ ┆ │\n", + "╞═════════╪════════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n", + "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 1 ┆ 23.543464 ┆ 4.758863 ┆ 0.642882 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 3 ┆ 14.131865 ┆ 2.082703 ┆ 2.126997 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 4 ┆ 0.856332 ┆ 1.118578 ┆ -0.830057 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.174824 ┆ -0.096888 ┆ -1.386022 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 179 ┆ 0.17166 ┆ -0.129436 ┆ -0.996938 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 25 ┆ 1.521586 ┆ -5.0 ┆ -3.120021 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 27 ┆ 0.03135 ┆ -3.802689 ┆ -2.502291 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.029183 ┆ -3.781128 ┆ -2.828955 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 42 ┆ 0.00491 ┆ -3.831461 ┆ -2.740264 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 81 ┆ 0.004026 ┆ -3.853244 ┆ -2.736186 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘\n", + " run_id raw_y mean min max median std success_ratio \\\n", + "0 7 0.000065 inf 566.0 inf inf NaN 0.5 \n", + "1 12 0.000065 inf inf inf inf NaN 0.0 \n", + "2 11 0.000065 inf inf inf inf NaN 0.0 \n", + "3 9 0.000065 inf inf inf inf NaN 0.0 \n", + "4 15 0.000065 inf inf inf inf NaN 0.0 \n", + ".. ... ... ... ... ... ... ... ... \n", + "745 5 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", + "746 11 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", + "747 8 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", + "748 13 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", + "749 2 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", + "\n", + " success_count ERT PAR-10 \n", + "0 1 1561.0 5258.0 \n", + "1 0 inf 9950.0 \n", + "2 0 inf 9950.0 \n", + "3 0 inf 9950.0 \n", + "4 0 inf 9950.0 \n", + ".. ... ... ... \n", + "745 2 1.0 1.0 \n", + "746 2 1.0 1.0 \n", + "747 2 1.0 1.0 \n", + "748 2 1.0 1.0 \n", + "749 2 1.0 1.0 \n", + "\n", + "[750 rows x 11 columns]\n" + ] + } + ], + "source": [ + "manager = iohinspector.DataManager()\n", + "data_folders = [\"test_data/RS\", \"test_data/HC\"]\n", + "manager.add_folders(data_folders)\n", + "\n", + "\n", + "print(manager.overview.columns)\n", + "selection = manager.select(function_ids=[1])\n", + "df = selection.load(monotonic=True, include_meta_data=True,)\n", + "\n", + "print(df)\n", + "result = iohinspector.aggegate_running_time(df, free_variables=[\"run_id\"])\n", + "result.to_csv(\"aggregated_result.csv\", index=False)\n", + "\n", + "print(result)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7bf5c582", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Rating Deviation algorithm_name\n", + "0 1481.847229 6.719253 RandomSearch\n", + "1 1518.152771 6.719253 HillClimber" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "iohinspector.plot_tournament_ranking(df)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1c8dbaf3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['data_id', 'algorithm_name', 'algorithm_info', 'suite', 'function_name', 'function_id', 'dimension', 'instance', 'run_id', 'evals', 'best_y']\n", + "shape: (599, 15)\n", + "┌─────────┬────────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n", + "│ data_id ┆ algorithm_ ┆ algorithm ┆ suite ┆ … ┆ evaluatio ┆ raw_y ┆ x0 ┆ x1 │\n", + "│ --- ┆ name ┆ _info ┆ --- ┆ ┆ ns ┆ --- ┆ --- ┆ --- │\n", + "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ --- ┆ f64 ┆ f64 ┆ f64 │\n", + "│ ┆ str ┆ str ┆ ┆ ┆ u64 ┆ ┆ ┆ │\n", + "╞═════════╪════════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n", + "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 1 ┆ 8.2124e6 ┆ -0.530698 ┆ -2.494956 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 5 ┆ 3.5690e6 ┆ 0.781847 ┆ -1.365995 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 9 ┆ 143888.77 ┆ 1.231167 ┆ 0.847804 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ 7772 ┆ ┆ │\n", + "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 24 ┆ 69448.892 ┆ -1.347449 ┆ 0.709334 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ 009 ┆ ┆ │\n", + "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 102 ┆ 27086.700 ┆ -4.78153 ┆ 0.293066 │\n", + "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ 878 ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 25 ┆ 1.521586 ┆ -5.0 ┆ -3.120021 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 27 ┆ 0.03135 ┆ -3.802689 ┆ -2.502291 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.029183 ┆ -3.781128 ┆ -2.828955 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 42 ┆ 0.00491 ┆ -3.831461 ┆ -2.740264 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 81 ┆ 0.004026 ┆ -3.853244 ┆ -2.736186 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘\n" + ] + } + ], + "source": [ + "manager = iohinspector.DataManager()\n", + "data_folders = [\"test_data/RS\", \"test_data/HC\"]\n", + "manager.add_folders(data_folders)\n", + "\n", + "\n", + "print(manager.overview.columns)\n", + "selection = manager.select()\n", + "df = selection.load(monotonic=True, include_meta_data=True,)\n", + "\n", + "print(df)\n", + "result = iohinspector.aggegate_running_time(df, free_variables=[\"run_id\"])\n", + "result.to_csv(\"aggregated_result.csv\", index=False)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "08998b29", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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raw_yalgorithm_namefunction_idvariablevalue
14016.490770e-05HillClimber1ERT14496.000000
14041.134130e-04HillClimber1ERT14496.000000
14101.981660e-04HillClimber1ERT14496.000000
14153.462546e-04HillClimber1ERT4688.333333
14186.050093e-04HillClimber1ERT2686.000000
..................
15825.233434e+06RandomSearch2ERT2.800000
15859.144358e+06RandomSearch2ERT2.133333
15881.597790e+07RandomSearch2ERT1.733333
15952.791812e+07RandomSearch2ERT1.200000
15974.878121e+07RandomSearch2ERT1.066667
\n", + "

200 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " raw_y algorithm_name function_id variable value\n", + "1401 6.490770e-05 HillClimber 1 ERT 14496.000000\n", + "1404 1.134130e-04 HillClimber 1 ERT 14496.000000\n", + "1410 1.981660e-04 HillClimber 1 ERT 14496.000000\n", + "1415 3.462546e-04 HillClimber 1 ERT 4688.333333\n", + "1418 6.050093e-04 HillClimber 1 ERT 2686.000000\n", + "... ... ... ... ... ...\n", + "1582 5.233434e+06 RandomSearch 2 ERT 2.800000\n", + "1585 9.144358e+06 RandomSearch 2 ERT 2.133333\n", + "1588 1.597790e+07 RandomSearch 2 ERT 1.733333\n", + "1595 2.791812e+07 RandomSearch 2 ERT 1.200000\n", + "1597 4.878121e+07 RandomSearch 2 ERT 1.066667\n", + "\n", + "[200 rows x 5 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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evaluationsalgorithm_namefunction_idvariablevalue
8431.0HillClimber1geometric_mean17.691640
8472.0HillClimber1geometric_mean14.095624
8513.0HillClimber1geometric_mean11.517027
8554.0HillClimber1geometric_mean8.645013
8575.0HillClimber1geometric_mean7.502348
..................
991566.0RandomSearch2geometric_mean48.534221
995652.0RandomSearch2geometric_mean39.839912
996750.0RandomSearch2geometric_mean36.944067
1002864.0RandomSearch2geometric_mean27.835512
1005995.0RandomSearch2geometric_mean27.789929
\n", + "

168 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " evaluations algorithm_name function_id variable value\n", + "843 1.0 HillClimber 1 geometric_mean 17.691640\n", + "847 2.0 HillClimber 1 geometric_mean 14.095624\n", + "851 3.0 HillClimber 1 geometric_mean 11.517027\n", + "855 4.0 HillClimber 1 geometric_mean 8.645013\n", + "857 5.0 HillClimber 1 geometric_mean 7.502348\n", + "... ... ... ... ... ...\n", + "991 566.0 RandomSearch 2 geometric_mean 48.534221\n", + "995 652.0 RandomSearch 2 geometric_mean 39.839912\n", + "996 750.0 RandomSearch 2 geometric_mean 36.944067\n", + "1002 864.0 RandomSearch 2 geometric_mean 27.835512\n", + "1005 995.0 RandomSearch 2 geometric_mean 27.789929\n", + "\n", + "[168 rows x 5 columns]" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "iohinspector.single_function_fixedbudget(\n", + " df,\n", + " free_variables=[\"algorithm_name\",\"function_id\"],)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "311d1389", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (2_520, 15)
evaluationsdata_idalgorithm_namealgorithm_infosuitefunction_namefunction_iddimensioninstancerun_idevalsbest_yraw_yx0x1
f64i32strstrstrstrf64f64f64f64f64f64f64f64f64
1.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019158.635203-4.8888233.862607
2.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019148.239593-3.8185795.0
3.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019145.920072-3.6389264.993428
4.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019139.832259-3.3830654.335506
5.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019133.091874-2.6180864.776682
………………………………………
566.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
652.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
750.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
864.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
995.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
" + ], + "text/plain": [ + "shape: (2_520, 15)\n", + "┌────────────┬─────────┬────────────┬────────────┬───┬──────────┬───────────┬───────────┬──────────┐\n", + "│ evaluation ┆ data_id ┆ algorithm_ ┆ algorithm_ ┆ … ┆ best_y ┆ raw_y ┆ x0 ┆ x1 │\n", + "│ s ┆ --- ┆ name ┆ info ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", + "│ --- ┆ i32 ┆ --- ┆ --- ┆ ┆ f64 ┆ f64 ┆ f64 ┆ f64 │\n", + "│ f64 ┆ ┆ str ┆ str ┆ ┆ ┆ ┆ ┆ │\n", + "╞════════════╪═════════╪════════════╪════════════╪═══╪══════════╪═══════════╪═══════════╪══════════╡\n", + "│ 1.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 58.635203 ┆ -4.888823 ┆ 3.862607 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 2.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 48.239593 ┆ -3.818579 ┆ 5.0 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 3.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 45.920072 ┆ -3.638926 ┆ 4.993428 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 4.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 39.832259 ┆ -3.383065 ┆ 4.335506 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 5.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 33.091874 ┆ -2.618086 ┆ 4.776682 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ 566.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 652.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 750.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 864.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "│ 995.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", + "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", + "└────────────┴─────────┴────────────┴────────────┴───┴──────────┴───────────┴───────────┴──────────┘" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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evaluationsalgorithm_namedata_idalgorithm_infosuitefunction_namefunction_iddimensioninstancerun_idevalsbest_yraw_yx0x1eaf
01HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786765.310570e+06-0.3225440.6633830.249110
11RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275416.188412e+06-0.1925980.2011410.268371
22RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275414.848309e+06-1.1319300.4863600.279032
32HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786764.604357e+06-0.2060250.6570470.268522
43RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275413.281761e+06-0.698483-0.0667250.288152
...................................................
79750RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275413.813746e+01-0.607788-0.3779450.494987
80864HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786763.565133e+00-0.282064-0.4206760.566046
81864RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275412.194865e+01-0.681759-0.3773160.501213
82995RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275412.192754e+01-0.593897-0.3772140.501236
83995HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786762.978676e+00-0.212480-0.4157080.572082
\n", + "

84 rows × 16 columns

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" + ], + "text/plain": [ + " evaluations algorithm_name data_id algorithm_info suite function_name \\\n", + "0 1 HillClimber 45.5 None None None \n", + "1 1 RandomSearch 15.5 None None None \n", + "2 2 RandomSearch 15.5 None None None \n", + "3 2 HillClimber 45.5 None None None \n", + "4 3 RandomSearch 15.5 None None None \n", + ".. ... ... ... ... ... ... \n", + "79 750 RandomSearch 15.5 None None None \n", + "80 864 HillClimber 45.5 None None None \n", + "81 864 RandomSearch 15.5 None None None \n", + "82 995 RandomSearch 15.5 None None None \n", + "83 995 HillClimber 45.5 None None None \n", + "\n", + " function_id dimension instance run_id evals best_y raw_y \\\n", + "0 1.5 2.0 8.0 8.0 1000.0 2.978676 5.310570e+06 \n", + "1 1.5 2.0 8.0 8.0 1000.0 21.927541 6.188412e+06 \n", + "2 1.5 2.0 8.0 8.0 1000.0 21.927541 4.848309e+06 \n", + "3 1.5 2.0 8.0 8.0 1000.0 2.978676 4.604357e+06 \n", + "4 1.5 2.0 8.0 8.0 1000.0 21.927541 3.281761e+06 \n", + ".. ... ... ... ... ... ... ... \n", + "79 1.5 2.0 8.0 8.0 1000.0 21.927541 3.813746e+01 \n", + "80 1.5 2.0 8.0 8.0 1000.0 2.978676 3.565133e+00 \n", + "81 1.5 2.0 8.0 8.0 1000.0 21.927541 2.194865e+01 \n", + "82 1.5 2.0 8.0 8.0 1000.0 21.927541 2.192754e+01 \n", + "83 1.5 2.0 8.0 8.0 1000.0 2.978676 2.978676e+00 \n", + "\n", + " x0 x1 eaf \n", + "0 -0.322544 0.663383 0.249110 \n", + "1 -0.192598 0.201141 0.268371 \n", + "2 -1.131930 0.486360 0.279032 \n", + "3 -0.206025 0.657047 0.268522 \n", + "4 -0.698483 -0.066725 0.288152 \n", + ".. ... ... ... \n", + "79 -0.607788 -0.377945 0.494987 \n", + "80 -0.282064 -0.420676 0.566046 \n", + "81 -0.681759 -0.377316 0.501213 \n", + "82 -0.593897 -0.377214 0.501236 \n", + "83 -0.212480 -0.415708 0.572082 \n", + "\n", + "[84 rows x 16 columns]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "iohinspector.plot_ecdf(\n", + " df,\n", + " free_vars=[\"algorithm_name\"],)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f80aee6b", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "shape: (368, 15)\n", + "┌─────────┬────────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n", + "│ data_id ┆ algorithm_ ┆ algorithm ┆ suite ┆ … ┆ evaluatio ┆ raw_y ┆ x0 ┆ x1 │\n", + "│ --- ┆ name ┆ _info ┆ --- ┆ ┆ ns ┆ --- ┆ --- ┆ --- │\n", + "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ --- ┆ f64 ┆ f64 ┆ f64 │\n", + "│ ┆ str ┆ str ┆ ┆ ┆ u64 ┆ ┆ ┆ │\n", + "╞═════════╪════════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n", + "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 1 ┆ 1.5800e7 ┆ 3.262506 ┆ 4.431918 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 2 ┆ 7.4589e6 ┆ 3.215108 ┆ 3.085552 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 3 ┆ 6.4533e6 ┆ 2.499752 ┆ 2.841361 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 5 ┆ 4828.9966 ┆ 1.761925 ┆ 0.371379 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ 29 ┆ ┆ │\n", + "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 26 ┆ 1866.3556 ┆ 2.710169 ┆ 0.407752 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 25 ┆ 1.521586 ┆ -5.0 ┆ -3.120021 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 27 ┆ 0.03135 ┆ -3.802689 ┆ -2.502291 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.029183 ┆ -3.781128 ┆ -2.828955 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 42 ┆ 0.00491 ┆ -3.831461 ┆ -2.740264 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 81 ┆ 0.004026 ┆ -3.853244 ┆ -2.736186 │\n", + "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", + "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘\n", + "[[1.00000000e+00 1.57999232e+07 3.10000000e+01]\n", + " [2.00000000e+00 7.45889349e+06 3.10000000e+01]\n", + " [3.00000000e+00 6.45333527e+06 3.10000000e+01]\n", + " ...\n", + " [3.20000000e+01 2.91830493e-02 6.00000000e+01]\n", + " [4.20000000e+01 4.91001460e-03 6.00000000e+01]\n", + " [8.10000000e+01 4.02583880e-03 6.00000000e+01]]\n", + "[[1.00000000e+00 8.21240591e+06 1.00000000e+00]\n", + " [5.00000000e+00 3.56903493e+06 1.00000000e+00]\n", + " [9.00000000e+00 1.43888778e+05 1.00000000e+00]\n", + " [2.40000000e+01 6.94488920e+04 1.00000000e+00]\n", + " [1.02000000e+02 2.70867009e+04 1.00000000e+00]\n", + " [1.29000000e+02 4.72738896e+03 1.00000000e+00]\n", + " 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Select HillClimber data\n", + "hc_data = df.filter(df[\"algorithm_name\"] == \"HillClimber\")\n", + "\n", + "# Select RandomSearch data\n", + "rs_data = df.filter(df[\"algorithm_name\"] == \"RandomSearch\")\n", + "print(hc_data)\n", + "iohinspector.eaf_diffs(\n", + " hc_data,\n", + " rs_data,\n", + " x_column=\"evaluations\",\n", + " y_column=\"raw_y\",\n", + " max_y=1\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "85a93000", + "metadata": {}, + "outputs": [ + { + "ename": "ZeroDivisionError", + "evalue": "float division by zero", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mZeroDivisionError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[2], line 5\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28mmax\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m \n\u001b[1;32m 4\u001b[0m \u001b[38;5;28mlen\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m3\u001b[39m\n\u001b[0;32m----> 5\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marange\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mmin\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mmin\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mmin\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28mprint\u001b[39m(x)\n", + "\u001b[0;31mZeroDivisionError\u001b[0m: float division by zero" + ] + } + ], + "source": [ + "import numpy as np\n", + "min = 5\n", + "max = 5 \n", + "len = 3\n", + "x = np.arange(\n", + " min,\n", + " max + (max - min) / (2 * (len - 1)),\n", + " (max - min) / (len - 1),\n", + " dtype=float,\n", + " )\n", + "print(x)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "iohinspector", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.18" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/src/iohinspector/__init__.py b/src/iohinspector/__init__.py index 1b8e83b..67ecf6e 100644 --- a/src/iohinspector/__init__.py +++ b/src/iohinspector/__init__.py @@ -3,4 +3,5 @@ from .manager import * from .metrics import * from .indicators import * -from .plot import * \ No newline at end of file +from .plot import * +from .data_processing import * \ No newline at end of file diff --git a/src/iohinspector/data_processing/__init__.py b/src/iohinspector/data_processing/__init__.py new file mode 100644 index 0000000..ccbf096 --- /dev/null +++ b/src/iohinspector/data_processing/__init__.py @@ -0,0 +1,6 @@ +from .utils import * +from .aggregate_convergence import * +from .aggregate_running_time import * +from .normalise_objectives import * +from .aocc import (get_aocc) +from .ecdf import (get_data_ecdf) \ No newline at end of file diff --git a/src/iohinspector/data_processing/aggregate_convergence.py b/src/iohinspector/data_processing/aggregate_convergence.py new file mode 100644 index 0000000..3ce20cc --- /dev/null +++ b/src/iohinspector/data_processing/aggregate_convergence.py @@ -0,0 +1,72 @@ +import polars as pl +from typing import Iterable, Callable +from .utils import get_sequence, geometric_mean +from ..align import align_data + +def aggregate_convergence( + data: pl.DataFrame, + evaluation_variable: str = "evaluations", + fval_variable: str = "raw_y", + free_variables: Iterable[str] = ["algorithm_name"], + x_min: int = None, + x_max: int = None, + custom_op: Callable[[pl.Series], float] = None, + maximization: bool = False, + return_as_pandas: bool = True, +): + """Function to aggregate performance on a fixed-budget perspective + + Args: + data (pl.DataFrame): The data object to use for getting the performance. Note that the fval, evaluation and free variables as defined in + this object determine the axes of the final performance (most data will have 'raw_y', 'evaluations' and ['algId'] as defaults) + evaluation_variable (str, optional): Column name for evaluation number. Defaults to "evaluations". + fval_variable (str, optional): Column name for function value. Defaults to "raw_y". + free_variables (Iterable[str], optional): Column name for free variables (variables over which performance should not be aggregated). Defaults to ["algorithm_name"]. + x_min (int, optional): Minimum evaulation value to use. Defaults to None (minimum present in data). + x_max (int, optional): Maximum evaulation value to use. Defaults to None (maximum present in data). + custom_op (Callable[[pl.Series], float], optional): Custom aggregation method for performance values. Defaults to None. + maximization (bool, optional): Whether performance metric is being maximized or not. Defaults to False. + return_as_pandas (bool, optional): Whether the data should be returned as Pandas (True) or Polars (False) object. Defaults to True. + + Returns: + DataFrame: Depending on 'return_as_pandas', a pandas or polars DataFrame with the aggregated performance values + """ + if(data.is_empty()): + raise ValueError("Data is empty, cannot aggregate convergence.") + + # Getting alligned data (to check if e.g. limits should be args for this function) + if x_min is None: + x_min = data[evaluation_variable].min() + if x_max is None: + x_max = data[evaluation_variable].max() + x_values = get_sequence(x_min, x_max, 50, scale_log=True, cast_to_int=True) + group_variables = free_variables + [evaluation_variable] + data_aligned = align_data( + data.cast({evaluation_variable: pl.Int64}), + x_values, + group_cols=["data_id"] + free_variables, + x_col=evaluation_variable, + y_col=fval_variable, + maximization=maximization, + ) + aggregations = [ + pl.mean(fval_variable).alias("mean"), + pl.min(fval_variable).alias("min"), + pl.max(fval_variable).alias("max"), + pl.median(fval_variable).alias("median"), + pl.std(fval_variable).alias("std"), + pl.col(fval_variable) + .map_elements(lambda s: geometric_mean(s), return_dtype=pl.Float64) + .alias("geometric_mean"), + ] + + if custom_op is not None: + aggregations.append( + pl.col(fval_variable) + .map_elements(lambda s: custom_op(s), return_dtype=pl.Float64) + .alias(custom_op.__name__) + ) + dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) + if return_as_pandas: + return dt_plot.sort(evaluation_variable).to_pandas() + return dt_plot.sort(evaluation_variable) \ No newline at end of file diff --git a/src/iohinspector/data_processing/aggregate_running_time.py b/src/iohinspector/data_processing/aggregate_running_time.py new file mode 100644 index 0000000..c7b5b12 --- /dev/null +++ b/src/iohinspector/data_processing/aggregate_running_time.py @@ -0,0 +1,91 @@ +import polars as pl +from typing import Iterable, Callable +from .utils import get_sequence, geometric_mean +from ..align import align_data + +def aggregate_running_time( + data: pl.DataFrame, + evaluation_variable: str = "evaluations", + fval_variable: str = "raw_y", + free_variables: Iterable[str] = ["algorithm_name"], + f_min: float = None, + f_max: float = None, + scale_flog: bool = True, + max_budget: int = None, + maximization: bool = False, + custom_op: Callable[[pl.Series], float] = None, + return_as_pandas: bool = True, +): + """Function to aggregate performance on a fixed-target perspective + + Args: + data (pl.DataFrame): The data object to use for getting the performance. Note that the fval, evaluation and free variables as defined in + this object determine the axes of the final performance (most data will have 'raw_y', 'evaluations' and ['algId'] as defaults) + evaluation_variable (str, optional): Column name for evaluation number. Defaults to "evaluations". + fval_variable (str, optional): Column name for function value. Defaults to "raw_y". + free_variables (Iterable[str], optional): Column name for free variables (variables over which performance should not be aggregated). Defaults to ["algorithm_name"]. + f_min (float, optional): Minimum function value to use. Defaults to None (minimum present in data). + f_max (float, optional): Maximum function value to use. Defaults to None (maximum present in data). + scale_flog (bool): Whether or not function values should be scaled logarithmically for the x-axis. Defaults to True. + max_budget: If present, what budget value should be the maximum considered. Defaults to None. + custom_op (Callable[[pl.Series], float], optional): Custom aggregation method for performance values. Defaults to None. + maximization (bool, optional): Whether performance metric is being maximized or not. Defaults to False. + return_as_pandas (bool, optional): Whether the data should be returned as Pandas (True) or Polars (False) object. Defaults to True. + + Returns: + DataFrame: Depending on 'return_as_pandas', a pandas or polars DataFrame with the aggregated performance values + """ + + # Getting alligned data (to check if e.g. limits should be args for this function) + if f_min is None: + f_min = data[fval_variable].min() + if f_max is None: + f_max = data[fval_variable].max() + f_values = get_sequence(f_min, f_max, 50, scale_log=scale_flog) + group_variables = free_variables + [fval_variable] + data_aligned = align_data( + data, + f_values, + group_cols=["data_id"] + free_variables, + x_col=fval_variable, + y_col=evaluation_variable, + maximization=maximization, + ) + + if max_budget is None: + max_budget = data[evaluation_variable].max() + + aggregations = [ + pl.col(evaluation_variable).mean().alias("mean"), + pl.col(evaluation_variable).min().alias("min"), + pl.col(evaluation_variable).max().alias("max"), + pl.col(evaluation_variable).median().alias("median"), + pl.col(evaluation_variable).std().alias("std"), + pl.col(evaluation_variable).is_finite().mean().alias("success_ratio"), + pl.col(evaluation_variable).is_finite().sum().alias("success_count"), + ( + pl.when(pl.col(evaluation_variable).is_finite()) + .then(pl.col(evaluation_variable)) + .otherwise(max_budget) + .sum() + /pl.col(evaluation_variable).is_finite().sum() + ).alias("ERT"), + ( + pl.when(pl.col(evaluation_variable).is_finite()) + .then(pl.col(evaluation_variable)) + .otherwise(10 * max_budget) + .sum() + / pl.col(evaluation_variable).count() + ).alias("PAR-10"), + ] + + if custom_op is not None: + aggregations.append( + pl.col(evaluation_variable) + .map_elements(lambda s: custom_op(s), return_dtype=pl.Float64) + .alias(custom_op.__name__) + ) + dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) + if return_as_pandas: + return dt_plot.sort(fval_variable).to_pandas() + return dt_plot.sort(fval_variable) \ No newline at end of file diff --git a/src/iohinspector/data_processing/aocc.py b/src/iohinspector/data_processing/aocc.py new file mode 100644 index 0000000..4ed4db9 --- /dev/null +++ b/src/iohinspector/data_processing/aocc.py @@ -0,0 +1,59 @@ +import polars as pl +from typing import Iterable, Callable +from functools import partial + +def _aocc(group: pl.DataFrame, max_budget: int, fval_col: str = "eaf"): + group = group.cast({"evaluations": pl.Int64}).filter( + pl.col("evaluations") <= max_budget + ) + new_row = pl.DataFrame( + { + "evaluations": [0, max_budget], + fval_col: [group[fval_col].min(), group[fval_col].max()], + } + ) + group = ( + pl.concat([group, new_row], how="diagonal") + .sort("evaluations") + .fill_null(strategy="forward") + .fill_null(strategy="backward") + ) + + return group.with_columns( + ( + ( + pl.col("evaluations").diff(n=1, null_behavior="ignore") + * (pl.col(fval_col).shift(1)) + ) + / max_budget + ).alias("aocc_contribution") + ) + + + +def get_aocc( + data: pl.DataFrame, + max_budget: int, + fval_col: str = "eaf", + group_cols: Iterable[str] = ["function_name", "algorithm_name"], +): + """Helper function for AOCC calculations + + Args: + data (pl.DataFrame): The data object to use for getting the performance. + max_budget (int): Maxium value of evaluations to use + fval_col (str, optional): Which data column specifies the performance value. Defaults to "eaf". + group_cols (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["function_name", "algorithm_name"]. + + Returns: + pl.DataFrame: a polars dataframe with the area under the EAF (=area over convergence curve) + """ + aocc_contribs = data.group_by(*["data_id"]).map_groups( + partial(_aocc, max_budget=max_budget, fval_col=fval_col) + ) + aoccs = aocc_contribs.group_by(["data_id"] + group_cols).agg( + pl.col("aocc_contribution").sum() + ) + return aoccs.group_by(group_cols).agg( + pl.col("aocc_contribution").mean().alias("AOCC") + ) diff --git a/src/iohinspector/data_processing/ecdf.py b/src/iohinspector/data_processing/ecdf.py new file mode 100644 index 0000000..5d974c5 --- /dev/null +++ b/src/iohinspector/data_processing/ecdf.py @@ -0,0 +1,93 @@ +import polars as pl +from typing import Iterable +from .utils import get_sequence +from ..align import align_data +from .normalise_objectives import normalize_objectives + +def transform_fval( + data: pl.DataFrame, + lb: float = 1e-8, + ub: float = 1e8, + scale_log: bool = True, + maximization: bool = False, + fval_col: str = "raw_y", +): + """ + Helper function to transform function values (min-max normalization based on provided bounds and scaling) + """ + bounds = {fval_col: (lb, ub)} + res = normalize_objectives( + data, + obj_cols=[fval_col], + bounds=bounds, + log_scale=scale_log, + maximize=maximization, + prefix="eaf" + ) + return res + + +def get_data_ecdf( + data: pl.DataFrame, + fval_var: str = "raw_y", + eval_var: str = "evaluations", + free_vars: Iterable[str] = ["algorithm_name"], + maximization: bool = False, + x_values: Iterable[int] = None, + x_min: int = None, + x_max: int = None, + scale_xlog: bool = True, + y_min: int = None, + y_max: int = None, + scale_ylog: bool = True, +): + """Function to plot empirical cumulative distribution function (Based on EAF) + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + eval_var (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". + fval_var (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". + free_vars (Iterable[str], optional): Columns in 'data' which correspond to groups over which data should not be aggregated. Defaults to ["algorithm_name"]. + maximization (bool, optional): Boolean indicating whether the 'fval_var' is being maximized. Defaults to False. + measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. + x_values (Iterable[int], optional): List of x-values at which to get the ECDF data. If not provided, the x_min, x_max and scale_xlog arguments will be used to sample these points. + scale_xlog (bool, optional): Should the x-samples be log-scaled. Defaults to True. + x_min (float, optional): Minimum value to use for the 'eval_var', if not present the min of that column will be used. Defaults to None. + x_max (float, optional): Maximum value to use for the 'eval_var', if not present the max of that column will be used. Defaults to None. + scale_ylog (bool, optional): Should the y-values be log-scaled before normalization. Defaults to True. + y_min (float, optional): Minimum value to use for the 'fval_var', if not present the min of that column will be used. Defaults to None. + y_max (float, optional): Maximum value to use for the 'fval_var', if not present the max of that column will be used. Defaults to None. + + Returns: + pd.DataFrame: pandas dataframe of the ECDF data. + """ + if x_values is None: + if x_min is None: + x_min = data[eval_var].min() + if x_max is None: + x_max = data[eval_var].max() + x_values = get_sequence( + x_min, x_max, 50, scale_log=scale_xlog, cast_to_int=True + ) + data_aligned = align_data( + data.cast({eval_var: pl.Int64}), + x_values, + group_cols=["data_id"], + x_col=eval_var, + y_col=fval_var, + maximization=maximization, + ) + dt_ecdf = ( + transform_fval( + data_aligned, + fval_col=fval_var, + maximization=maximization, + lb=y_min, + ub=y_max, + scale_log=scale_ylog, + ) + .group_by([eval_var] + free_vars) + .mean() + .sort(eval_var) + ).to_pandas() + return dt_ecdf \ No newline at end of file diff --git a/src/iohinspector/data_processing/normalise_objectives.py b/src/iohinspector/data_processing/normalise_objectives.py new file mode 100644 index 0000000..5e64660 --- /dev/null +++ b/src/iohinspector/data_processing/normalise_objectives.py @@ -0,0 +1,67 @@ +import polars as pl +import numpy as np +import warnings +from typing import Iterable, Optional, Union, Dict + + +def normalize_objectives( + data: pl.DataFrame, + obj_cols: Iterable[str] = ["raw_y"], + bounds: Optional[Dict[str, tuple[Optional[float], Optional[float]]]] = None, + log_scale: Union[bool, Dict[str, bool]] = False, + maximize: Union[bool, Dict[str, bool]] = False, + prefix: str = "ert" +) -> pl.DataFrame: + """ + Normalize multiple objective columns in a dataframe. + + Args: + data (pl.DataFrame): Input dataframe. + obj_cols (Iterable[str]): Columns to normalize. + bounds (Optional[Dict[str, tuple(lb, ub)]]): Optional manual bounds per column. + log_scale (Union[bool, Dict[str, bool]]): Whether to apply log10 scaling. Can be a single bool or a dict per column. + maximize (Union[bool, Dict[str, bool]]): Whether to treat objective as maximization. Can be a single bool or dict. + prefix (str): Prefix for normalized column names. + + Returns: + pl.DataFrame: The original dataframe with new normalized objective columns added. + """ + result = data.clone() + n_objectives = len(obj_cols) + for col in obj_cols: + # Determine log scaling + use_log = log_scale[col] if isinstance(log_scale, dict) else log_scale + is_max = maximize[col] if isinstance(maximize, dict) else maximize + + # Get bounds + lb, ub = None, None + if bounds and col in bounds: + lb, ub = bounds[col] + if lb is None: + lb = result[col].min() + if ub is None: + ub = result[col].max() + # Log scale if needed + if use_log: + if lb <= 0: + warnings.warn( + f"Lower bound for column '{col}' <= 0; resetting to 1e-8 for log-scaling." + ) + lb = 1e-8 + lb, ub = np.log10(lb), np.log10(ub) + norm_expr = ((pl.col(col).log10() - lb) / (ub - lb)).clip(0, 1) + else: + norm_expr = ((pl.col(col) - lb) / (ub - lb)).clip(0, 1) + + # Reverse if minimization + if not is_max: + norm_expr = 1 - norm_expr + # Add normalized column with appropriate name + if n_objectives > 1: + norm_expr = norm_expr.alias(f"{prefix}_{col}") + else: + # If only one objective, use the prefix directly + norm_expr = norm_expr.alias(prefix) + result = result.with_columns(norm_expr) + + return result \ No newline at end of file diff --git a/src/iohinspector/data_processing/utils.py b/src/iohinspector/data_processing/utils.py new file mode 100644 index 0000000..8821c98 --- /dev/null +++ b/src/iohinspector/data_processing/utils.py @@ -0,0 +1,51 @@ +import numpy as np +import polars as pl + + +def geometric_mean(series: pl.Series) -> float: + """Helper function for polars: geometric mean""" + return np.exp(np.log(series).mean()) + + +def get_sequence( + min: float, + max: float, + len: float, + scale_log: bool = False, + cast_to_int: bool = False, +) -> np.ndarray: + """Create sequence of points, used for subselecting targets / budgets for allignment and data processing + + Args: + min (float): Starting point of the range + max (float): Final point of the range + len (float): Number of steps + scale_log (bool): Whether values should be scaled logarithmically. Defaults to False + version (str, optional): Whether the value should be casted to integers (e.g. in case of budget) or not. Defaults to False. + + Returns: + np.ndarray: Array of evenly spaced values + """ + transform = lambda x: x + if scale_log: + assert min > 0 + min = np.log10(min) + max = np.log10(max) + transform = lambda x: 10**x + if len == 1: + values =np.array([min]) + else: + if(max == min): + values = np.ones(len) * min + else: + values = np.arange( + min, + max + (max - min) / (2 * (len - 1)), + (max - min) / (len - 1), + dtype=float, + ) + + values = transform(values) + if cast_to_int: + return np.unique(np.array(values, dtype=int)) + return np.unique(values) diff --git a/src/iohinspector/metrics.py b/src/iohinspector/metrics.py index 9d1df93..e7dded0 100644 --- a/src/iohinspector/metrics.py +++ b/src/iohinspector/metrics.py @@ -12,215 +12,6 @@ -def get_sequence( - min: float, - max: float, - len: float, - scale_log: bool = False, - cast_to_int: bool = False, -) -> np.ndarray: - """Create sequence of points, used for subselecting targets / budgets for allignment and data processing - - Args: - min (float): Starting point of the range - max (float): Final point of the range - len (float): Number of steps - scale_log (bool): Whether values should be scaled logarithmically. Defaults to False - version (str, optional): Whether the value should be casted to integers (e.g. in case of budget) or not. Defaults to False. - - Returns: - np.ndarray: Array of evenly spaced values - """ - transform = lambda x: x - if scale_log: - assert min > 0 - min = np.log10(min) - max = np.log10(max) - transform = lambda x: 10**x - values = transform( - np.arange( - min, - max + (max - min) / (2 * (len - 1)), - (max - min) / (len - 1), - dtype=float, - ) - ) - if cast_to_int: - return np.unique(np.array(values, dtype=int)) - return np.unique(values) - - -def _geometric_mean(series: pl.Series) -> float: - """Helper function for polars: geometric mean""" - return np.exp(np.log(series).mean()) - - -def aggegate_convergence( - data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - x_min: int = None, - x_max: int = None, - custom_op: Callable[[pl.Series], float] = None, - maximization: bool = False, - return_as_pandas: bool = True, -): - """Function to aggregate performance on a fixed-budget perspective - - Args: - data (pl.DataFrame): The data object to use for getting the performance. Note that the fval, evaluation and free variables as defined in - this object determine the axes of the final performance (most data will have 'raw_y', 'evaluations' and ['algId'] as defaults) - evaluation_variable (str, optional): Column name for evaluation number. Defaults to "evaluations". - fval_variable (str, optional): Column name for function value. Defaults to "raw_y". - free_variables (Iterable[str], optional): Column name for free variables (variables over which performance should not be aggregated). Defaults to ["algorithm_name"]. - x_min (int, optional): Minimum evaulation value to use. Defaults to None (minimum present in data). - x_max (int, optional): Maximum evaulation value to use. Defaults to None (maximum present in data). - custom_op (Callable[[pl.Series], float], optional): Custom aggregation method for performance values. Defaults to None. - maximization (bool, optional): Whether performance metric is being maximized or not. Defaults to False. - return_as_pandas (bool, optional): Whether the data should be returned as Pandas (True) or Polars (False) object. Defaults to True. - - Returns: - DataFrame: Depending on 'return_as_pandas', a pandas or polars DataFrame with the aggregated performance values - """ - - # Getting alligned data (to check if e.g. limits should be args for this function) - if x_min is None: - x_min = data[evaluation_variable].min() - if x_max is None: - x_max = data[evaluation_variable].max() - x_values = get_sequence(x_min, x_max, 50, scale_log=True, cast_to_int=True) - group_variables = free_variables + [evaluation_variable] - data_aligned = align_data( - data.cast({evaluation_variable: pl.Int64}), - x_values, - group_cols=["data_id"] + free_variables, - x_col=evaluation_variable, - y_col=fval_variable, - maximization=maximization, - ) - - aggregations = [ - pl.mean(fval_variable).alias("mean"), - pl.min(fval_variable).alias("min"), - pl.max(fval_variable).alias("max"), - pl.median(fval_variable).alias("median"), - pl.std(fval_variable).alias("std"), - pl.col(fval_variable) - .map_elements(lambda s: _geometric_mean(s), return_dtype=pl.Float64) - .alias("geometric_mean"), - ] - - if custom_op is not None: - aggregations.append( - pl.col(evaluation_variable) - .map_elements(lambda s: custom_op(s), return_dtype=pl.Float64) - .alias(custom_op.__name__) - ) - dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) - if return_as_pandas: - return dt_plot.sort(evaluation_variable).to_pandas() - return dt_plot.sort(evaluation_variable) - - -def transform_fval( - data: pl.DataFrame, - lb: float = 1e-8, - ub: float = 1e8, - scale_log: bool = True, - maximization: bool = False, - fval_col: str = "raw_y", -): - """Helper function to transform function values (min-max normalization based on provided bounds and scaling) - - Args: - data (pl.DataFrame): The data object to use for getting the performance. - lb (float, optional): Lower bound for scaling of function values. If None, it is the max value found in data. Defaults to 1e-8. - ub (float, optional): Upper bound for scaling of function values. If None, it is the max value found in data. Defaults to 1e8. - scale_log (bool, optional): Whether function values should be log-scaled before scaling. Defaults to True. - maximization (bool, optional): Whether function values is being maximized. Defaults to False. - fval_col (str, optional): Which column in data to use. Defaults to "raw_y". - - Returns: - _type_: a copy of the original data with a new column 'eaf' with the scaled function values (which is always to be maximized) - """ - if ub == None: - ub = data[fval_col].max() - if lb == None: - lb = data[fval_col].min() - if lb <= 0 and scale_log: - lb = 1e-8 - warnings.warn( - "If using logarithmic scaling, lb should be set to prevent errors in log-calculation. Lb is being overwritten to 1e-8 to avoid this." - ) - if scale_log: - lb = np.log10(lb) - ub = np.log10(ub) - res = data.with_columns( - ((pl.col(fval_col).log10() - lb) / (ub - lb)).clip(0, 1).alias("eaf") - ) - else: - res = data.with_columns( - ((pl.col(fval_col) - lb) / (ub - lb)).clip(0, 1).alias("eaf") - ) - if maximization: - return res - return res.with_columns((1 - pl.col("eaf")).alias("eaf")) - - -def _aocc(group: pl.DataFrame, max_budget: int, fval_col: str = "eaf"): - group = group.cast({"evaluations": pl.Int64}).filter( - pl.col("evaluations") <= max_budget - ) - new_row = pl.DataFrame( - { - "evaluations": [0, max_budget], - fval_col: [group[fval_col].min(), group[fval_col].max()], - } - ) - group = ( - pl.concat([group, new_row], how="diagonal") - .sort("evaluations") - .fill_null(strategy="forward") - .fill_null(strategy="backward") - ) - return group.with_columns( - ( - ( - pl.col("evaluations").diff(n=1, null_behavior="ignore") - * (pl.col(fval_col).shift(1)) - ) - / max_budget - ).alias("aocc_contribution") - ) - - -def get_aocc( - data: pl.DataFrame, - max_budget: int, - fval_col: str = "eaf", - group_cols: Iterable[str] = ["function_name", "algorithm_name"], -): - """Helper function for AOCC calculations - - Args: - data (pl.DataFrame): The data object to use for getting the performance. - max_budget (int): Maxium value of evaluations to use - fval_col (str, optional): Which data column specifies the performance value. Defaults to "eaf". - group_cols (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["function_name", "algorithm_name"]. - - Returns: - pl.DataFrame: a polars dataframe with the area under the EAF (=area over convergence curve) - """ - aocc_contribs = data.group_by(*["data_id"]).map_groups( - partial(_aocc, max_budget=max_budget, fval_col=fval_col) - ) - aoccs = aocc_contribs.group_by(["data_id"] + group_cols).agg( - pl.col("aocc_contribution").sum() - ) - return aoccs.group_by(group_cols).agg( - pl.col("aocc_contribution").mean().alias("AOCC") - ) def get_tournament_ratings( @@ -300,123 +91,6 @@ def get_tournament_ratings( return rating_dt_elo -def aggegate_running_time( - data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - f_min: float = None, - f_max: float = None, - scale_flog: bool = True, - max_budget: int = None, - maximization: bool = False, - custom_op: Callable[[pl.Series], float] = None, - return_as_pandas: bool = True, -): - """Function to aggregate performance on a fixed-target perspective - - Args: - data (pl.DataFrame): The data object to use for getting the performance. Note that the fval, evaluation and free variables as defined in - this object determine the axes of the final performance (most data will have 'raw_y', 'evaluations' and ['algId'] as defaults) - evaluation_variable (str, optional): Column name for evaluation number. Defaults to "evaluations". - fval_variable (str, optional): Column name for function value. Defaults to "raw_y". - free_variables (Iterable[str], optional): Column name for free variables (variables over which performance should not be aggregated). Defaults to ["algorithm_name"]. - f_min (int, optional): Minimum function value to use. Defaults to None (minimum present in data). - f_max (int, optional): Maximum function value to use. Defaults to None (maximum present in data). - scale_flog (bool): Whether or not function values should be scaled logarithmically for the x-axis. Defaults to True. - max_budget: If present, what budget value should be the maximum considered. Defaults to None. - custom_op (Callable[[pl.Series], float], optional): Custom aggregation method for performance values. Defaults to None. - maximization (bool, optional): Whether performance metric is being maximized or not. Defaults to False. - return_as_pandas (bool, optional): Whether the data should be returned as Pandas (True) or Polars (False) object. Defaults to True. - - Returns: - DataFrame: Depending on 'return_as_pandas', a pandas or polars DataFrame with the aggregated performance values - """ - - # Getting alligned data (to check if e.g. limits should be args for this function) - if f_min is None: - f_min = data[fval_variable].min() - if f_max is None: - f_max = data[fval_variable].max() - f_values = get_sequence(f_min, f_max, 50, scale_log=scale_flog) - group_variables = free_variables + [fval_variable] - data_aligned = align_data( - data, - f_values, - group_cols=["data_id"] + free_variables, - x_col=fval_variable, - y_col=evaluation_variable, - maximization=maximization, - ) - if max_budget is None: - max_budget = data[evaluation_variable].max() - - aggregations = [ - pl.col(evaluation_variable).mean().alias("mean"), - # pl.mean(evaluation_variable).alias("mean"), - pl.col(evaluation_variable).min().alias("min"), - pl.col(evaluation_variable).max().alias("max"), - pl.col(evaluation_variable).median().alias("median"), - pl.col(evaluation_variable).std().alias("std"), - pl.col(evaluation_variable).is_finite().mean().alias("success_ratio"), - pl.col(evaluation_variable).is_finite().sum().alias("success_count"), - ( - pl.when(pl.col(evaluation_variable).is_finite()) - .then(pl.col(evaluation_variable)) - .otherwise(max_budget) - .sum() - /pl.col(evaluation_variable).is_finite().sum() - ).alias("ERT"), - ( - pl.when(pl.col(evaluation_variable).is_finite()) - .then(pl.col(evaluation_variable)) - .otherwise(10 * max_budget) - .sum() - / pl.col(evaluation_variable).count() - ).alias("PAR-10"), - ] - - if custom_op is not None: - aggregations.append( - pl.col(evaluation_variable) - .apply(lambda s: custom_op(s)) - .alias(custom_op.__name__) - ) - dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) - if return_as_pandas: - return dt_plot.sort(fval_variable).to_pandas() - return dt_plot.sort(fval_variable) - - -def add_normalized_objectives( - data: pl.DataFrame, obj_cols: Iterable[str], max_vals: Optional[pl.DataFrame] = None, min_vals: Optional[pl.DataFrame] = None -): - """Add new normalized columns to provided dataframe based on the provided objective columns - - Args: - data (pl.DataFrame): The original dataframe - obj_cols (Iterable[str]): The names of each objective column - max_vals (Optional[pl.DataFrame]): If provided, these values will be used as the maxima instead of the values found in `data` - min_vals (Optional[pl.DataFrame]): If provided, these values will be used as the minima instead of the values found in `data` - - Returns: - _type_: The original `data` DataFrame with a new column 'objI' added for each objective, for I=1...len(obj_cols) - """ - if type(max_vals) == pl.DataFrame: - data_max = [max_vals[colname].max() for colname in obj_cols] - else: - data_max = [data[colname].max() for colname in obj_cols] - if type(min_vals) == pl.DataFrame: - data_min = [min_vals[colname].min() for colname in obj_cols] - else: - data_min = [data[colname].min() for colname in obj_cols] - return data.with_columns( - [ - ((data[colname] - data_min[idx]) / (data_max[idx] - data_min[idx])).alias(f"obj{idx + 1}") - for idx, colname in enumerate(obj_cols) - ] - ) - def _get_nodeidx(xloc, yval, nodes, epsilon): if len(nodes) == 0: @@ -525,70 +199,6 @@ def get_attractor_network( return nodes, edges -def get_data_ecdf( - data, - fval_var: str = "raw_y", - eval_var: str = "evaluations", - free_vars: Iterable[str] = ["algorithm_name"], - maximization: bool = False, - x_values: Iterable[int] = None, - x_min: int = None, - x_max: int = None, - scale_xlog: bool = True, - y_min: int = None, - y_max: int = None, - scale_ylog: bool = True, -): - """Function to plot empirical cumulative distribution function (Based on EAF) - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - eval_var (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_var (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_vars (Iterable[str], optional): Columns in 'data' which correspond to groups over which data should not be aggregated. Defaults to ["algorithm_name"]. - maximization (bool, optional): Boolean indicating whether the 'fval_var' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. - x_values (Iterable[int], optional): List of x-values at which to get the ECDF data. If not provided, the x_min, x_max and scale_xlog arguments will be used to sample these points. - scale_xlog (bool, optional): Should the x-samples be log-scaled. Defaults to True. - x_min (float, optional): Minimum value to use for the 'eval_var', if not present the min of that column will be used. Defaults to None. - x_max (float, optional): Maximum value to use for the 'eval_var', if not present the max of that column will be used. Defaults to None. - scale_ylog (bool, optional): Should the y-values be log-scaled before normalization. Defaults to True. - y_min (float, optional): Minimum value to use for the 'fval_var', if not present the min of that column will be used. Defaults to None. - y_max (float, optional): Maximum value to use for the 'fval_var', if not present the max of that column will be used. Defaults to None. - - Returns: - pd.DataFrame: pandas dataframe of the ECDF data. - """ - if x_values is None: - if x_min is None: - x_min = data[eval_var].min() - if x_max is None: - x_max = data[eval_var].max() - x_values = get_sequence( - x_min, x_max, 50, scale_log=scale_xlog, cast_to_int=True - ) - data_aligned = align_data( - data.cast({eval_var: pl.Int64}), - x_values, - group_cols=["data_id"], - x_col=eval_var, - y_col=fval_var, - maximization=maximization, - ) - dt_ecdf = ( - transform_fval( - data_aligned, - fval_col=fval_var, - maximization=maximization, - lb=y_min, - ub=y_max, - scale_log=scale_ylog, - ) - .group_by([eval_var] + free_vars) - .mean() - .sort(eval_var) - ).to_pandas() - return dt_ecdf def get_trajectory(data: pl.DataFrame, traj_length: int = None, diff --git a/src/iohinspector/plot.py b/src/iohinspector/plot.py index b679dbf..35b14aa 100644 --- a/src/iohinspector/plot.py +++ b/src/iohinspector/plot.py @@ -378,6 +378,8 @@ def eaf_diffs( # TODO: add an approximation version to speed up plotting x = np.array(data1[[x_column, y_column, "data_id"]]) y = np.array(data2[[x_column, y_column, "data_id"]]) + print(x) + print(y) eaf_diff_rect = eafdiff(x, y, rectangles=True) color_dict = { k: v @@ -402,6 +404,7 @@ def eaf_diffs( if max_y is None: max_y = np.max(x[1]) ax.set_ylim(min_y, max_y) + ax.set_xlim((0,1000)) if scale_ylog: ax.set_yscale("log") if scale_xlog: @@ -794,7 +797,7 @@ def plot_attractor_network( except: print("NetworkX is required to use this plot type") return - from sklearn.decomposition import MDS + from sklearn.manifold import MDS nodes, edges = get_attractor_network( data, maximization, coord_vars, fval_var, eval_var, beta, epsilon diff --git a/src/iohinspector/plot/__init__.py b/src/iohinspector/plot/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/iohinspector/plot/plot_convergence.py b/src/iohinspector/plot/plot_convergence.py new file mode 100644 index 0000000..890d4a8 --- /dev/null +++ b/src/iohinspector/plot/plot_convergence.py @@ -0,0 +1,77 @@ +import polars as pl +from typing import Iterable +import matplotlib +import matplotlib.pyplot as plt +import seaborn as sbs +from iohinspector.data_processing import aggegate_convergence + + +def single_function_fixedbudget( + data: pl.DataFrame, + evaluation_variable: str = "evaluations", + fval_variable: str = "raw_y", + free_variables: Iterable[str] = ["algorithm_name"], + x_min: float = None, + x_max: float = None, + maximization: bool = False, + measures: Iterable[str] = ["geometric_mean"], + scale_xlog: bool = True, + scale_ylog: bool = True, + ax: matplotlib.axes._axes.Axes = None, + file_name: str = None, +): + """Create a fixed-budget plot for a given set of performance data. + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". + fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". + free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. + x_min (float, optional): Minimum value to use for the 'evaluation_variable', if not present the min of that column will be used. Defaults to None. + x_max (float, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. + maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. + measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. + scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. + scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. + ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. + file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + + Returns: + pd.DataFrame: The final dataframe which was used to create the plot + """ + dt_agg = aggegate_convergence( + data, + evaluation_variable=evaluation_variable, + fval_variable=fval_variable, + free_variables=free_variables, + x_min=x_min, + x_max=x_max, + maximization=maximization, + ) + + dt_molt = dt_agg.melt(id_vars=[evaluation_variable] + free_variables) + dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) + + if ax is None: + fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + sbs.lineplot( + dt_plot, + x=evaluation_variable, + y="value", + style="variable", + hue=dt_plot[free_variables].apply(tuple, axis=1), + ax=ax, + ) + if scale_xlog: + ax.set_xscale("log") + if scale_ylog: + ax.set_yscale("log") + + if not maximization: + ax.set_xlim(ax.get_xlim()[::-1]) + + if ax is None and file_name: + fig.tight_layout() + fig.savefig(file_name) + + return dt_plot diff --git a/src/iohinspector/plot/plot_running_time.py b/src/iohinspector/plot/plot_running_time.py new file mode 100644 index 0000000..0519ecb --- /dev/null +++ b/src/iohinspector/plot/plot_running_time.py @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/tests/data_processing/test_aggregate_convergence.py b/tests/data_processing/test_aggregate_convergence.py new file mode 100644 index 0000000..ecaf3c6 --- /dev/null +++ b/tests/data_processing/test_aggregate_convergence.py @@ -0,0 +1,80 @@ +import unittest +import polars as pl +import numpy as np +from typing import Callable +from iohinspector.data_processing.aggregate_convergence import aggregate_convergence + +class TestAggregateConvergence(unittest.TestCase): + def setUp(self): + # Create a simple test DataFrame + self.df = pl.DataFrame({ + "evaluations": [1, 2, 3, 1, 2, 3, 1,3, 1,3], + "raw_y": [30, 20, 10, 35, 25, 15, 40, 30, 20, 10], + "algorithm_name": ["A", "A", "A", "A", "A", "A", "B", "B", "B", "B"], + "data_id": [0, 0, 0, 1, 1, 1, 2, 2, 3, 3] + }) + + def test_basic_aggregation(self): + result = aggregate_convergence(self.df, return_as_pandas=True) + # Should contain columns for mean, min, max, median, std, geometric_mean + for col in ["mean", "min", "max", "median", "std", "geometric_mean"]: + self.assertIn(col, result.columns) + # Should have 6 rows (3 evals x 2 algs) + self.assertEqual(len(result), 6) + # Check that means are correct for one group + mean_a = result[(result["algorithm_name"] == "A")]["mean"].values + np.testing.assert_allclose(mean_a, [32.5, 22.5, 12.5]) + mean_b = result[(result["algorithm_name"] == "B")]["mean"].values + np.testing.assert_allclose(mean_b, [30,30,20]) + + def test_custom_op(self): + def custom_sum(s): + return float(s.sum()) + result = aggregate_convergence(self.df, custom_op=custom_sum, return_as_pandas=True) + self.assertIn("custom_sum", result.columns) + + # Check that custom_sum is correct for one group + sum_a = result[(result["algorithm_name"] == "A")]["custom_sum"].values + np.testing.assert_allclose(sum_a, [65, 45, 25]) + sum_a = result[(result["algorithm_name"] == "B")]["custom_sum"].values + np.testing.assert_allclose(sum_a, [60, 60, 40]) + + def test_maximization(self): + # Should not affect aggregation, but test for code path + result = aggregate_convergence(self.df, maximization=True, return_as_pandas=True) + self.assertIn("mean", result.columns) + + def test_x_min_x_max(self): + # Limit to a subset of evaluations + result = aggregate_convergence(self.df, x_min=2, x_max=3, return_as_pandas=True) + self.assertTrue((result["evaluations"] >= 2).all()) + self.assertTrue((result["evaluations"] <= 3).all()) + + def test_return_polars(self): + result = aggregate_convergence(self.df, return_as_pandas=False) + self.assertIsInstance(result, pl.DataFrame) + + def test_free_variables(self): + # Use a different free variable + df = self.df.with_columns(pl.lit("foo").alias("other_var")) + result = aggregate_convergence(df, free_variables=["other_var"], return_as_pandas=True) + self.assertIn("other_var", result.columns) + + def test_empty_data(self): + empty_df = self.df.filter(pl.col("evaluations") > 100) + with self.assertRaises(ValueError): + aggregate_convergence(empty_df, return_as_pandas=True) + + def test_single_row(self): + single_df = pl.DataFrame({ + "evaluations": [1], + "raw_y": [42], + "algorithm_name": ["A"], + "data_id": [0] + }) + result = aggregate_convergence(single_df, return_as_pandas=True) + self.assertEqual(len(result), 1) + self.assertAlmostEqual(result["mean"].iloc[0], 42.0) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/data_processing/test_aggregate_running_time.py b/tests/data_processing/test_aggregate_running_time.py new file mode 100644 index 0000000..a0bd92b --- /dev/null +++ b/tests/data_processing/test_aggregate_running_time.py @@ -0,0 +1,92 @@ +import unittest +import polars as pl +import math +from iohinspector.data_processing.aggregate_running_time import aggregate_running_time + +class TestAggregateRunningTime(unittest.TestCase): + + def setUp(self): + self.df = pl.DataFrame({ + "evaluations": [1, 10, 20, 1, 15, 26], + "raw_y": [1.0, 0.7, 0.1, 0.9, 0.3, 0.2], + "algorithm_name": ["A", "A", "A", "B", "B", "B"], + "data_id": [1, 1, 1, 2, 2, 2] + }) + + + def test_basic_aggregation(self): + result = aggregate_running_time(self.df, return_as_pandas=False) + self.assertIn("mean", result.columns) + self.assertIn("ERT", result.columns) + self.assertIn("PAR-10", result.columns) + self.assertTrue(result.height > 0) + + # Assert the value of success_count for A is 1 and for B is 0 + # You can use filter as shown, or use row indexing with .row or .to_dicts() + a_success_count = result.filter( + (pl.col("algorithm_name") == "A") & (pl.col("raw_y") == 0.1) + )["success_count"].to_list()[0] + b_success_count = result.filter( + (pl.col("algorithm_name") == "B") & (pl.col("raw_y") == 0.1) + )["success_count"].to_list()[0] + + + self.assertEqual(a_success_count, 1) + self.assertEqual(b_success_count, 0) + + def test_return_as_pandas(self): + result = aggregate_running_time(self.df, return_as_pandas=True) + self.assertTrue(hasattr(result, "to_numpy")) # pandas DataFrame + + def test_custom_op(self): + def my_sum(s): + return float(s.sum()) + result = aggregate_running_time(self.df, custom_op=my_sum, return_as_pandas=False) + self.assertIn("my_sum", result.columns) + + def test_maximization(self): + # Should not raise error + df = pl.DataFrame({ + "evaluations": [1, 10, 20, 1, 15, 26], + "raw_y": [0.1, 0.7, 1.0, 0.2, 0.3, 0.9], + "algorithm_name": ["A", "A", "A", "B", "B", "B"], + "data_id": [1, 1, 1, 2, 2, 2] + }) + + result = aggregate_running_time(df, maximization=True, return_as_pandas=False) + self.assertTrue(result.height > 0) + + a_success_count = result.filter( + (pl.col("algorithm_name") == "A") & (pl.col("raw_y") >= 0.9) + )["success_count"].to_list()[0] + b_success_count = result.filter( + (pl.col("algorithm_name") == "B") & (pl.col("raw_y") >= 0.9) + )["success_count"].to_list()[0] + + + self.assertEqual(a_success_count, 1) + self.assertEqual(b_success_count, 0) + + def test_with_f_min_f_max(self): + result = aggregate_running_time(self.df, f_min=0.2, f_max=0.5, return_as_pandas=False) + self.assertTrue(result["raw_y"].min() >= 0.2) + self.assertTrue(result["raw_y"].max() <= 0.5) + + def test_with_different_free_variables(self): + result = aggregate_running_time(self.df, free_variables=["algorithm_name", "data_id"], return_as_pandas=False) + self.assertIn("algorithm_name", result.columns) + self.assertIn("data_id", result.columns) + + + def test_success_ratio_and_count(self): + # Add a non-finite value + df = self.df.with_columns([ + pl.when(pl.col("evaluations") == 3).then(float("nan")).otherwise(pl.col("evaluations")).alias("evaluations") + ]) + result = aggregate_running_time(df, return_as_pandas=False) + self.assertIn("success_ratio", result.columns) + self.assertIn("success_count", result.columns) + self.assertTrue((result["success_ratio"] <= 1).all()) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/data_processing/test_aocc.py b/tests/data_processing/test_aocc.py new file mode 100644 index 0000000..c20ab5f --- /dev/null +++ b/tests/data_processing/test_aocc.py @@ -0,0 +1,75 @@ +import unittest +import polars as pl +import numpy as np +from iohinspector.data_processing.aocc import get_aocc + +class TestGetAOCC(unittest.TestCase): + def setUp(self): + # Simple dataset with two groups and two data_ids + self.df = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2, 2], + "function_name": ["f1", "f1", "f1", "f1", "f1", "f1"], + "algorithm_name": ["alg1", "alg1", "alg1", "alg1", "alg1", "alg1"], + "evaluations": [0, 5, 10, 0, 5, 10], + "eaf": [10.0, 7.0, 4.0, 12.0, 9.0, 6.0], + }) + + def test_basic_aocc(self): + # AOCC should be computed for the group + result = get_aocc(self.df, max_budget=10) + self.assertIn("AOCC", result.columns) + aocc_val = result["AOCC"][0] + self.assertTrue(aocc_val == 6.5) + + def test_multiple_groups(self): + # Add a second group + df = self.df.with_columns([ + pl.Series("function_name", ["f1", "f1", "f1", "f2", "f2", "f2"]) + ]) + result = get_aocc(df, max_budget=10) + self.assertIn("AOCC", result.columns) + aocc_f1_val = result.filter(pl.col("function_name") == "f1")["AOCC"][0] + aocc_f2_val = result.filter(pl.col("function_name") == "f2")["AOCC"][0] + self.assertTrue(aocc_f1_val == 5.5) + self.assertTrue(aocc_f2_val == 7.5) + + def test_custom_fval_col(self): + # Use a different column for fval_col + df = self.df.rename({"eaf": "custom_col"}) + result = get_aocc(df, max_budget=10, fval_col="custom_col") + self.assertIn("AOCC", result.columns) + aocc_val = result["AOCC"][0] + self.assertTrue(aocc_val == 6.5) + + def test_custom_group_cols(self): + # Use only algorithm_name as group col + result = get_aocc(self.df, max_budget=10, group_cols=["algorithm_name"]) + aocc_val = result["AOCC"][0] + self.assertTrue(aocc_val == 6.5) + + def test_aocc_with_missing_evaluations(self): + # Remove some evaluation steps to test fill_null + df = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2], + "function_name": ["f1", "f1", "f1", "f1", "f1"], + "algorithm_name": ["alg1", "alg1", "alg1", "alg1", "alg1"], + "evaluations": [0, 5, 10, 0, 10], + "eaf": [10.0, 8.0, 4.0, 12.0, 6.0], + }) + result = get_aocc(df, max_budget=10) + + self.assertIn("AOCC", result.columns) + aocc_val = result["AOCC"][0] + self.assertTrue(aocc_val == 6) + + def test_aocc_zero_budget(self): + # Test with max_budget=0 (should handle gracefully) + df = self.df + result = get_aocc(df, max_budget=0) + self.assertIn("AOCC", result.columns) + # AOCC should be nan or 0 + aocc_val = result["AOCC"][0] + self.assertTrue(np.isnan(aocc_val) or aocc_val == 0) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/data_processing/test_ecdf.py b/tests/data_processing/test_ecdf.py new file mode 100644 index 0000000..8783286 --- /dev/null +++ b/tests/data_processing/test_ecdf.py @@ -0,0 +1,70 @@ +import unittest +import polars as pl +import numpy as np +from iohinspector.data_processing.ecdf import get_data_ecdf +import iohinspector + +class TestGetDataECDF(unittest.TestCase): + def setUp(self): + # Create a simple synthetic dataset + self.df = pl.DataFrame({ + "evaluations": [1, 2, 3, 4, 5, 1, 2, 3, 4, 5], + "raw_y": [10, 8, 6, 4, 2, 18, 16, 14, 12, 10], + "algorithm_name": ["algo1"] * 5 + ["algo2"] * 5, + "data_id": [1] * 5 + [2] * 5, + }) + + def test_basic_ecdf(self): + result = get_data_ecdf(self.df, scale_xlog=False, scale_ylog=False) + algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() + algo1_eaf.sort() + np.testing.assert_allclose(algo1_eaf, [0.5, 0.625, 0.75, 0.875, 1]) + + algo2_eaf = result[result["algorithm_name"] == "algo2"]["eaf"].to_numpy() + algo2_eaf.sort() + np.testing.assert_allclose(algo2_eaf, [0, 0.125, 0.25, 0.375, 0.5]) + + def test_ecdf_with_custom_x_values(self): + x_values = [2, 4] + result = get_data_ecdf(self.df, x_values=x_values, scale_xlog=False, scale_ylog=False) + algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() + algo1_eaf.sort() + np.testing.assert_allclose(algo1_eaf, [2/3, 1]) + + algo2_eaf = result[result["algorithm_name"] == "algo2"]["eaf"].to_numpy() + algo2_eaf.sort() + np.testing.assert_allclose(algo2_eaf, [0, 1/3]) + + def test_ecdf_with_maximization(self): + result = get_data_ecdf(self.df, maximization=True) + # eaf_raw_y should be between 0 and 1 + algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() + # Assert that all values in algo1_eaf are 0 and the array is not empty + np.testing.assert_allclose(algo1_eaf, [0, 0, 0, 0, 0]) + + algo2_eaf = result[result["algorithm_name"] == "algo2"]["eaf"].to_numpy() + np.testing.assert_allclose(algo2_eaf, [1, 1, 1, 1, 1]) + + + def test_ecdf_with_custom_bounds(self): + result = get_data_ecdf(self.df, y_min=0, y_max=100, scale_xlog=False, scale_ylog=False) + algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() + algo1_eaf.sort() + np.testing.assert_allclose(algo1_eaf, [90/100, 92/100, 94/100, 96/100, 98/100]) + + algo2_eaf = result[result["algorithm_name"] == "algo2"]["eaf"].to_numpy() + algo2_eaf.sort() + np.testing.assert_allclose(algo2_eaf, [82/100, 84/100, 86/100, 88/100, 90/100]) + + def test_ecdf_with_x_min_x_max(self): + result = get_data_ecdf(self.df, x_min=2, x_max=4, scale_xlog=False, scale_ylog=False) + algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() + algo1_eaf.sort() + np.testing.assert_allclose(algo1_eaf, [2/3, 5/6, 1]) + + algo2_eaf = result[result["algorithm_name"] == "algo2"]["eaf"].to_numpy() + algo2_eaf.sort() + np.testing.assert_allclose(algo2_eaf, [0, 1/6, 1/3]) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/data_processing/test_normalise_objectives.py b/tests/data_processing/test_normalise_objectives.py new file mode 100644 index 0000000..c9b64b4 --- /dev/null +++ b/tests/data_processing/test_normalise_objectives.py @@ -0,0 +1,77 @@ +import unittest +import polars as pl +import numpy as np +import warnings +from iohinspector.data_processing import normalize_objectives + +class TestNormalizeObjectives(unittest.TestCase): + def setUp(self): + self.df = pl.DataFrame({ + "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], + "other": [10, 20, 30, 40, 50] + }) + + def test_basic_normalization(self): + normed = normalize_objectives(self.df, obj_cols=["raw_y"]) + self.assertIn("ert", normed.columns) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) + + def test_maximization(self): + normed = normalize_objectives(self.df, obj_cols=["raw_y"], maximize=True) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [0, 0.25, 0.5, 0.75, 1]) + + def test_bounds(self): + bounds = {"raw_y": (0, 10)} + normed = normalize_objectives(self.df, obj_cols=["raw_y"], bounds=bounds) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [0.9, 0.8, 0.7, 0.6, 0.5]) + + def test_log_scale(self): + df = pl.DataFrame({"raw_y": [1, 10, 100, 1000, 10000]}) + normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) + + def test_log_scale_with_zero_warns(self): + df = pl.DataFrame({"raw_y": [0, 1, 10]}) + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always") + normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) + self.assertTrue(any("Lower bound" in str(warn.message) for warn in w)) + arr = normed["ert"].to_numpy() + self.assertTrue(np.all((arr >= 0) & (arr <= 1))) + + def test_multiple_objectives(self): + df = pl.DataFrame({ + "raw_y": [1, 2, 3], + "other": [10, 20, 30] + }) + normed = normalize_objectives(df, obj_cols=["raw_y", "other"]) + arr_raw_y = normed["ert_raw_y"].to_numpy() + np.testing.assert_allclose(arr_raw_y, [1.0, 0.5, 0.0]) + arr_other = normed["ert_other"].to_numpy() + np.testing.assert_allclose(arr_other, [1.0, 0.5, 0.0]) + + + def test_column_prefix(self): + normed = normalize_objectives(self.df, obj_cols=["raw_y"], prefix="normed") + self.assertIn("normed", normed.columns) + + def test_dict_log_and_maximize(self): + df = pl.DataFrame({"a": [1, 10, 100], "b": [3, 2, 1]}) + normed = normalize_objectives( + df, + obj_cols=["a", "b"], + log_scale={"a": True, "b": False}, + maximize={"a": True, "b": False} + ) + arr_raw_y = normed["ert_a"].to_numpy() + np.testing.assert_allclose(arr_raw_y, [0.0, 0.5, 1.0]) + arr_other = normed["ert_b"].to_numpy() + np.testing.assert_allclose(arr_other, [0.0, 0.5, 1.0]) + # a is maximized and log scaled, b is minimized and linear + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/data_processing/test_utils.py b/tests/data_processing/test_utils.py new file mode 100644 index 0000000..f2d3c58 --- /dev/null +++ b/tests/data_processing/test_utils.py @@ -0,0 +1,103 @@ +import unittest +import numpy as np +from iohinspector.data_processing.utils import get_sequence, geometric_mean +import polars as pl + +class TestGetSequence(unittest.TestCase): + """ + Unit tests for the `get_sequence` function, covering various scenarios: + + - Linear and logarithmic sequences with both float and integer outputs. + - Edge cases such as minimum equals maximum, single-length sequences, and negative or reversed ranges. + - Validation of output types, uniqueness when casting to int, and handling of float precision. + - Ensures proper error handling when invalid parameters are provided (e.g., log scale with zero minimum). + - Tests for correct sequence generation with large lengths and duplicate handling when casting to int. + + Each test verifies that the output matches expected values and types using NumPy's testing utilities and standard unittest assertions. + """ + def test_linear_float(self): + seq = get_sequence(0, 10, 5, scale_log=False, cast_to_int=False) + expected = np.array([0., 2.5, 5., 7.5, 10.]) + np.testing.assert_allclose(seq, expected) + self.assertEqual(seq.dtype, float) + + def test_linear_int(self): + seq = get_sequence(0, 10, 5, scale_log=False, cast_to_int=True) + self.assertTrue(np.issubdtype(seq.dtype, np.integer)) + self.assertEqual(seq[0], 0) + self.assertEqual(seq[-1], 10) + self.assertGreaterEqual(len(seq), 3) + + def test_log_float(self): + seq = get_sequence(1, 1000, 4, scale_log=True, cast_to_int=False) + expected = np.array([1., 10., 100., 1000.]) + np.testing.assert_allclose(seq, expected, rtol=1e-6) + + def test_log_int(self): + seq = get_sequence(1, 1000, 4, scale_log=True, cast_to_int=True) + expected = np.array([1, 10, 100, 1000]) + np.testing.assert_array_equal(seq, expected) + + def test_min_equals_max(self): + seq = get_sequence(5, 5, 1, scale_log=False, cast_to_int=False) + np.testing.assert_array_equal(seq, np.array([5.])) + + + def test_len_one(self): + seq = get_sequence(2, 8, 1, scale_log=False, cast_to_int=False) + np.testing.assert_array_equal(seq, np.array([2.])) + + def test_log_min_zero_raises(self): + with self.assertRaises(AssertionError): + get_sequence(0, 10, 5, scale_log=True) + + def test_cast_to_int_uniqueness(self): + seq = get_sequence(0, 1, 100, scale_log=False, cast_to_int=True) + np.testing.assert_array_equal(seq, np.array([0, 1])) + + def test_negative_range(self): + seq = get_sequence(-5, 5, 3, scale_log=False, cast_to_int=False) + expected = np.array([-5., 0., 5.]) + np.testing.assert_allclose(seq, expected) + + def test_large_len(self): + seq = get_sequence(0, 1, 1000, scale_log=False, cast_to_int=False) + self.assertEqual(len(seq), 1000) + self.assertAlmostEqual(seq[0], 0) + self.assertAlmostEqual(seq[-1], 1) + + def test_log_scale_non_integer_len(self): + seq = get_sequence(1, 100, 3, scale_log=True, cast_to_int=False) + expected = np.array([1., 10., 100.]) + np.testing.assert_allclose(seq, expected, rtol=1e-6) + + def test_cast_to_int_with_duplicates(self): + seq = get_sequence(0, 0.9, 10, scale_log=False, cast_to_int=True) + np.testing.assert_array_equal(seq, np.array([0])) + +class TestGeometricMean(unittest.TestCase): + def test_geometric_mean_positive(self): + s = pl.Series("a", [1, 10, 100]) + result = geometric_mean(s) + expected = np.exp(np.mean(np.log([1, 10, 100]))) + self.assertAlmostEqual(result, expected) + + def test_geometric_mean_with_ones(self): + s = pl.Series("a", [1, 1, 1, 1]) + result = geometric_mean(s) + self.assertEqual(result, 1.0) + + def test_geometric_mean_single_value(self): + s = pl.Series("a", [42]) + result = geometric_mean(s) + self.assertAlmostEqual(result, 42.0) + + def test_geometric_mean_large_numbers(self): + s = pl.Series("a", [1e10, 1e12, 1e14]) + result = geometric_mean(s) + expected = np.exp(np.mean(np.log([1e10, 1e12, 1e14]))) + self.assertAlmostEqual(result, expected) + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_align.py b/tests/test_align.py new file mode 100644 index 0000000..e687a74 --- /dev/null +++ b/tests/test_align.py @@ -0,0 +1,141 @@ +import unittest +import numpy as np +import polars as pl +from iohinspector.align import align_data +from iohinspector.align import turbo_align + + +class TestAlignData(unittest.TestCase): + + def test_align_data_minimization_long(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2, 2], + "evaluations": [1, 2, 5, 1, 4, 5], + "raw_y": [10, 8, 6, 20, 18, 16] + }) + + evals = [1, 2, 3, 4, 5] + result = align_data(df, evals, group_cols=("data_id",), x_col="evaluations", y_col="raw_y", output="long", maximization=False) + expected = pl.DataFrame({ + "evaluations": [1, 2, 3, 4, 5, 1, 2, 3, 4, 5], + "raw_y": [10, 8, 8, 8, 6, 20, 20, 20, 18, 16], + "data_id": [1, 1, 1, 1, 1, 2, 2, 2, 2, 2] + }) + result_sorted = result.sort(["data_id", "evaluations"]) + expected_sorted = expected.sort(["data_id", "evaluations"]) + self.assertEqual(result_sorted.to_dicts(), expected_sorted.to_dicts()) + + def test_align_data_maximization_long(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1], + "evaluations": [1, 2, 3], + "raw_y": [5, 7, 6] + }) + evals = [1, 2, 3] + result = align_data(df, evals, group_cols=("data_id",), x_col="evaluations", y_col="raw_y", output="long", maximization=True) + expected = pl.DataFrame({ + "evaluations": [1, 2, 3], + "raw_y": [5, 7, 7], + "data_id": [1, 1, 1] + }) + result_sorted = result.sort(["data_id", "evaluations"]) + expected_sorted = expected.sort(["data_id", "evaluations"]) + self.assertEqual(result_sorted.to_dicts(), expected_sorted.to_dicts()) + + def test_align_data_wide_output(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2, 2], + "evaluations": [1, 2, 5, 1, 4, 5], + "raw_y": [10, 8, 6, 20, 18, 16] + }) + evals = [1, 2, 3, 4, 5] + + result = align_data(df, evals, group_cols=("data_id",), x_col="evaluations", y_col="raw_y", output="wide", maximization=False) + # Should pivot to wide format + self.assertIn("1", result.columns) + self.assertIn("2", result.columns) + self.assertIn("evaluations", result.columns) + self.assertEqual(result.shape[0], 5) # 3 evals + + + def test_align_data_custom_group_col(self): + df = pl.DataFrame({ + "exp_id": [1, 1, 2, 2], + "evaluations": [1, 2, 1, 2], + "raw_y": [5, 3, 7, 6] + }) + evals = [1, 2] + result = align_data(df, evals, group_cols=("exp_id",), x_col="evaluations", y_col="raw_y", output="long", maximization=False) + self.assertTrue(set(result["exp_id"].to_list()) == {1, 2}) + + def test_align_data_non_default_x_col(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1], + "steps": [10, 20, 30], + "score": [100, 90, 80] + }) + evals = [10, 20, 30] + result = align_data(df, evals, group_cols=("data_id",), x_col="steps", y_col="score", output="long", maximization=False) + self.assertTrue(result["steps"].to_list() == [10, 20, 30]) + +class TestTurboAlignData(unittest.TestCase): + def test_turbo_align_minimization_long(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2, 2], + "evaluations": [1, 2, 5, 1, 4, 5], + "raw_y": [10, 8, 6, 20, 18, 16] + }) + evals = [1, 2, 3, 4, 5] + result = turbo_align(df, evals, x_col="evaluations", y_col="raw_y", output="long", maximization=False) + expected = pl.DataFrame({ + "evaluations": [1, 2, 3, 4, 5, 1, 2, 3, 4, 5], + "data_id": [1, 1, 1, 1, 1, 2, 2, 2, 2, 2], + "raw_y": [10, 8, 8, 8, 6, 20, 20, 20, 18, 16] + }) + result_sorted = result.sort(["data_id", "evaluations"]) + expected_sorted = expected.sort(["data_id", "evaluations"]) + self.assertEqual(result_sorted.to_dicts(), expected_sorted.to_dicts()) + + + def test_turbo_align_maximization_long(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1], + "evaluations": [1, 2, 5], + "raw_y": [5, 7, 8] + }) + evals = [1, 2, 3, 4, 5] + result = turbo_align(df, evals, x_col="evaluations", y_col="raw_y", output="long", maximization=True) + expected = pl.DataFrame({ + "evaluations": [1, 2, 3, 4, 5], + "data_id": [1, 1, 1, 1, 1], + "raw_y": [5, 7, 7, 7, 8] + }) + result_sorted = result.sort(["data_id", "evaluations"]) + expected_sorted = expected.sort(["data_id", "evaluations"]) + self.assertEqual(result_sorted.to_dicts(), expected_sorted.to_dicts()) + + def test_turbo_align_wide_output(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2, 2], + "evaluations": [1, 2, 5, 1, 4, 5], + "raw_y": [10, 8, 6, 20, 18, 16] + }) + evals = [1, 2, 3, 4, 5] + result = turbo_align(df, evals, x_col="evaluations", y_col="raw_y", output="wide", maximization=False) + self.assertIn("1", result.columns) + self.assertIn("2", result.columns) + self.assertIn("evaluations", result.columns) + self.assertEqual(result.shape[0], 5) + + def test_turbo_align_non_default_x_col(self): + df = pl.DataFrame({ + "data_id": [1, 1, 1], + "steps": [10, 20, 30], + "score": [100, 90, 80] + }) + evals = [10, 20, 30] + result = align_data(df, evals, group_cols=("data_id",), x_col="steps", y_col="score", output="long", maximization=False) + self.assertTrue(result["steps"].to_list() == [10, 20, 30]) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_data/algorithm_A.zip b/tests/test_data/algorithm_A.zip new file mode 100644 index 0000000000000000000000000000000000000000..aa319acae5aa12ef94e46f61d69be8ca922963ff GIT binary patch literal 1566 zcmWIWW@Zs#00Exn3sGPOl;B}dU`WhK&o9a>$;gd&)Gw{zW?*CiNrH*c5MBm$3C)0v z-}QkRAUXi2Nz!O0r6iUl#-|y^2Nz_d7Nz1e_z#M~91I*7PBg-Au&2LAK~a8MW=?7m z$T}BKUn4!B-MBpR7iwSbL{G0)N1m4Nmag*^Qv9Bpd=k@R2`o5rdv^Tx{793(S0@}_ zfBWcXqwxO!) z*fw3>b7X)Z|zIN(f^(FlPZ+4E7>%x^>j0_B1ObiT= zD8?2OYG^Tm7W9yq*2^l+&%+h^{0)#~G*>1_ zenlKn{D1ar@jCUyp4|35?<|-5NtYd{)@?sLz*<*R*j<74!Z~UU^eHyEKSl+HtTD&(_&+a7GMZx>BQO^Se*PKh0mRCQ(-MHq!B=M2$%Yj2ncTKwbfF?+H{ne&)2BlDUc5ogbT{trq+)q7^{ 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a/.gitignore b/.gitignore index 4b4a036..6f53a16 100644 --- a/.gitignore +++ b/.gitignore @@ -3,6 +3,7 @@ __pycache__/ *.py[cod] *$py.class +aux/ # C extensions *.so From 83b373d3cb61d54620e3a8536772c338ad3a4a6f Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Fri, 3 Oct 2025 12:15:00 +0200 Subject: [PATCH 06/17] added tests --- examples/MO_Examples.ipynb | 80 +++---- examples/SO_Examples.ipynb | 76 ++++--- pyproject.toml | 2 +- src/iohinspector/__init__.py | 4 +- src/iohinspector/data_processing/__init__.py | 6 - src/iohinspector/metrics/__init__.py | 6 + .../{data_processing => metrics}/aocc.py | 0 .../{data_processing => metrics}/ecdf.py | 24 +- .../fixed_budget.py} | 13 +- .../fixed_target.py} | 2 +- .../normalise_objectives.py | 68 +++++- .../{data_processing => metrics}/utils.py | 0 .../{metrics.py => old_metrics.py} | 210 ------------------ src/iohinspector/plot.py | 11 +- src/iohinspector/plot/plot_convergence.py | 77 ------- src/iohinspector/plot/plot_running_time.py | 1 - .../test_normalise_objectives.py | 77 ------- tests/test_data/algorithm_A.zip | Bin 1566 -> 0 bytes tests/test_data/algorithm_B.zip | Bin 1570 -> 0 bytes tests/test_manager.py | 138 ++++++++++++ .../plot => tests/test_metrics}/__init__.py | 0 .../test_aocc.py | 4 +- .../test_ecdf.py | 2 +- .../test_fixed_budget.py} | 6 +- .../test_fixed_target.py} | 4 +- .../test_metrics/test_normalise_objectives.py | 162 ++++++++++++++ .../test_utils.py | 2 +- 27 files changed, 478 insertions(+), 497 deletions(-) delete mode 100644 src/iohinspector/data_processing/__init__.py create mode 100644 src/iohinspector/metrics/__init__.py rename src/iohinspector/{data_processing => metrics}/aocc.py (100%) rename src/iohinspector/{data_processing => metrics}/ecdf.py (84%) rename src/iohinspector/{data_processing/aggregate_convergence.py => metrics/fixed_budget.py} (91%) rename src/iohinspector/{data_processing/aggregate_running_time.py => metrics/fixed_target.py} (97%) rename src/iohinspector/{data_processing => metrics}/normalise_objectives.py (53%) rename src/iohinspector/{data_processing => metrics}/utils.py (100%) rename src/iohinspector/{metrics.py => old_metrics.py} (53%) delete mode 100644 src/iohinspector/plot/plot_convergence.py delete mode 100644 src/iohinspector/plot/plot_running_time.py delete mode 100644 tests/data_processing/test_normalise_objectives.py delete mode 100644 tests/test_data/algorithm_A.zip delete mode 100644 tests/test_data/algorithm_B.zip create mode 100644 tests/test_manager.py rename {src/iohinspector/plot => tests/test_metrics}/__init__.py (100%) rename tests/{data_processing => test_metrics}/test_aocc.py (96%) rename tests/{data_processing => test_metrics}/test_ecdf.py (98%) rename tests/{data_processing/test_aggregate_convergence.py => test_metrics/test_fixed_budget.py} (94%) rename tests/{data_processing/test_aggregate_running_time.py => test_metrics/test_fixed_target.py} (96%) create mode 100644 tests/test_metrics/test_normalise_objectives.py rename tests/{data_processing => test_metrics}/test_utils.py (98%) diff --git a/examples/MO_Examples.ipynb b/examples/MO_Examples.ipynb index 56502eb..b965881 100644 --- a/examples/MO_Examples.ipynb +++ b/examples/MO_Examples.ipynb @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -75,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -122,7 +122,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 3, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -140,7 +140,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -156,7 +156,7 @@ " Function(id=0, name='pymoo_ZDT1', maximization=False)))" ] }, - "execution_count": 4, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -182,7 +182,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ @@ -192,7 +192,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 35, "metadata": {}, "outputs": [ { @@ -238,7 +238,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 6, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -249,7 +249,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -258,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 37, "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 38, "metadata": {}, "outputs": [ { @@ -299,7 +299,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 9, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -324,7 +324,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 39, "metadata": {}, "outputs": [ { @@ -371,7 +371,7 @@ "└─────────┴─────────────┴────────────┴────────────┴───┴─────────┴────────────┴──────────┴──────────┘" ] }, - "execution_count": 10, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -397,12 +397,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -414,17 +414,19 @@ "source": [ "import matplotlib.pyplot as plt\n", "import seaborn as sbs\n", - "\n", + "import numpy as np\n", "popsize = 100\n", "funcname = 'pymoo_ZDT1'\n", "\n", "df = manager.select(function_ids=[0]).load(False, True)\n", "#Currently, this normalization function assumes that our function was already scaled to have all 0's as the ideal point.\n", "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", + "# df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", "\n", "#The cast-to-int is there to handle data type differences and prevent duplicate values for function evaluation count\n", "evals = iohinspector.metrics.get_sequence(10, 2000, 10, cast_to_int=True, scale_log=True)\n", "\n", + "\n", "hv_indicator = iohinspector.indicators.anytime.HyperVolume(reference_point = [1.1, 1.1])\n", "df_hv = iohinspector.indicators.add_indicator(df, hv_indicator, objective_columns = ['obj1', 'obj2'], evals = evals)\n", "\n", @@ -445,12 +447,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 41, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -482,12 +484,12 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 42, "metadata": {}, "outputs": [ { "data": { - "image/png": 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qymttmiZDhw5l5syZvf5at7a2cv/993PmmWcyYsQI/H4/oVCIfffdl2984xu8+eabO3W+/kQqUfcShq6SFzSxbWhNpFldE8Fn6BQGTfKCJkFTfhX2SIrqVqZuWZ3qzYHQYKlOFUIIIYQQQvSJH/3oR9x11104ztYTQ9TX11NfX8/ixYv561//ysUXX8w//vEP/H5/j1z7iSee4Fvf+hYtLS0dti9dupSlS5dy//3385e//IUTTzyxy+esrq5mxowZvPHGG1s9tmHDBjZs2MAzzzzDnXfeyeOPP86hhx7a5XN/8MEHXHLJJWzcuLHLx/SmpUuXcv7557Ns2bIO28vKynjiiSd44oknuO222zoEtp1Zs2YN5557Ll988UWH7Zs2beLRRx/lX//6F88++yynnHIKAJ988gnnnHMO5eXlW53nvvvu49FHH+XVV1/lyCOP7Oaz7J6//vWv3HTTTSQSHQuXvvzyS7788kseeOABXnnllR3+/O+55x5uvvlmLMva6rGmpiaamppYsWIFs2fP5oQTTmDu3LkUFBR0uY3be63Ly8t55JFHmDt3bq+91v/617+48cYbqays3OqxVatWsWrVKmbNmsX06dN59NFHCYfDXX5e/YEkZ3sZVYWQTyfk6ESTaTY2RKlsjpPnNykIesjxGu4wqaLfcBywHbAzs1IZ2xuKoa061bEh0eJWp9avhkAR5AySsVOFEEIIIYQQu83GjRtxHAdFUdhvv/3Yb7/9KCgowDAM6urq+Pzzz1m9ejXghp7Nzc288MILHSr+uuM///kPl112WTag0jSNo48+mn333ZdIJMIHH3xAWVkZ11xzDX/+85+7dM6qqiqOPvrobHsBxowZwxFHHIHH42Hp0qV8/PHHAKxcuZJp06bxyiuvcPTRR3d67lWrVnHTTTfR1NREKBRi6tSpDB48mIaGBt59990uP+9zzjmHiRMnMn/+fD755BMADjvsMA4//PCt9t1RGLZp0yZOPPFEKioqyM3N5dhjj6W0tJTa2lrefPNNmpqaALjjjjvYf//9ueiiizptW3NzM6eddhpfffUVOTk5HHfccZSWllJRUcGbb75JNBolkUhwzjnnsGjRIlKpFCeeeCLNzc0UFhYydepUCgoK2LBhA2+++SapVIrm5mbOPvtsVqxYsduCuNmzZ3P99dcDsN9++3HooYfi8/lYvnw5H3zwAY7jUFdXx1lnncWyZcu2265NmzZlfz9Hjx7N+PHjKSoqwuv10tjYyKJFi1iyZAkAb775JieeeCLz5s3D4+n87/ntvdaVlZW88cYbvfpa//GPf+QHP/hB9ouTnJwcjjrqKIYOHYplWSxZsoQFCxbgOA4vvPACxx9/PB988EGPfXmyO0iIurdSwO/R8Xt0kmmbukiS2kiCHK9BUchDjs9AUxUUlPaHuPdKx3vhah922rbjzgnlOFg4OLb7uOU4OLiP2baD7Tg4mWPTlk3acY+1bLAcG8t2sG33PLbjvuYhj06Oz8Dv0fDpOuqWofdW1am1bhd/qU4VQgghhBBC7CaHHHIIp556KtOnT6ewsHCb+7z33nt84xvfYNWqVbz00ks89thjXHbZZd2+Zk1NDddcc002oDrooIN48skn2XfffbP7OI7DX/7yF77//e/zwx/+sEvnveqqq7IBaiAQ4MEHH+Tiiy/usM+CBQu46KKLWLNmDZFIhEsuuYQvv/yS3NzcHZ77t7/9Lel0mhtuuIHf/OY3BIPB7GOpVApN2858GVv43ve+B7hdu9tC1NNPPz3bvbur7rjjDhKJBLfccgu33XZbh4Crvr6eCy64INsd+6c//SkXXnhhp8H3fffdRyKR4JprruGuu+4iFAoBYNs2y5Yt4/zzz2f58uXEYjF+9atfsXjxYlpaWrj99tu59dZbMU0ze64lS5Zw4oknUllZSVVVFX/605+47bbbduo5dtd1111HUVERDz/8MKeeemqHx959913OPPNMmpubqaio2GG7xo4dy5///GfOOecchgwZss19vvzyS775zW+yYMECFi5cyO9//3t+/vOfd9rG7b3W4FYSn3TSSb3yWr/xxhv88Ic/xHEcTNPkjjvu4Lvf/e5WAenChQu59NJLWbp0KQsXLuSHP/wh9913X6fPq7+QEFVg6ir5QRPLcogk0qyqacGr66C0C06z9+0+HLcRpirK5n06hK69kNdtvs7WJ9/RZ3hn2eG2Hs4Gx+222ZnQ1LJt0pnQ1HYy4Slty5mQ1N5cSboVp+0aCiptY66AmrkH0BQFXXXD1rpIkupIAl1V8JkaYa9J0KvjNzU8+haJ6pbVqTXLocEEf6FUpwohhBBCCCF6zY9+9KNO9zn22GN57bXXGD9+PPF4nD//+c+7FKLedddd1NXVATB48GBee+21rbpBK4rCd7/7XdLpNDfffHOn53zrrbd4+eWXs+tPPvkkZ5xxxlb7HXroobzxxhsceOCBNDU1sXHjRu65555OA750Os3VV1/NX/7yl60eMwyj0/b1tEQiwa233sqdd9651WP5+fk8/vjjjBkzhtbWVtasWcP8+fM54ogjOj3nZZddxt///vetHhsyZAh///vfmTp1KgAPPfQQAL/4xS/4xS9+sdX+EyZM4A9/+EP296RtaIHd5fXXX2fy5MlbbZ86dSp33nkn3/nOdwCYM2fOdtv1jW98o9PrTJ48mddff51x48ZRWVnJfffdx6233tppqL6j13ro0KE8+OCDHHPMMUDPvda2bXP99ddj23Z2v3POOWeb7TvwwAOz75OqqioefPBBfvrTnzJ06NAdPq/+QjpuiyxNUwj7DQoCXnRNQVMUVEVBZXNFqoNbPWk7Dpbt3tLW5lsq7ZBM2yTSNvHMLZa0iSZ6/taasGhNWEQS6eytJZ6iJZ6iObb9W1O0461xi1tD+1ure6uPuLe6dreGVvd8saRN2nIrSFUUdFXB1FR8hkbQNMjxGOT6TQoDHgqD27iF3FtBZnza3IBB2G8Q8ukEve7N59Hwmho+j0Ze0KQw6CFoGiTTDmWNUZZXNrN0UzNfVUWoao7TkkhjtZ83rK06NXeoex+thbJPYcM8qFkJsUY3oRVCCCGEEEKI3WjkyJFMmzYNcMdmbG5u7tZ5bNtm1qxZ2fXbb799h+NI3njjjeyzzz6dnvdvf/tbdvmss87aZoDaZuTIkfz0pz/Nrv/1r3/d5piw7Xm9Xn73u9912o7dpaioaIehZElJSYfXYP78+Z2e0zRN/vCHP2z38aOPPprhw4d3uEb713FL5557brZicvny5VuNfdtbvvWtb20zQG0zc+ZMdN2tVVyxYkW3f5fbhMPhbBhZUVGxzQmhttQXr/Xzzz/PypUrATj77LO3G6C2KS0t5aabbgLcauu5c+fucP/+RCpRxVYUBbxG17oMiL6j6wohXSeEjuNAImXRFE1R2xpHU1T8pkbYZ7hVqoaO18h8Z7LN6tQ17apTC0E3d3xxIYQQQgghhOiiDRs2MH/+fL766isaGxuJxWIdwsW1a9cCblf7L774gmOPPXanr7Fs2TKqq6sB0HW907E6NU3jkksu4Ve/+tUO93vrrbeyy12pILzqqqu49dZbsW2biooKVqxYwbhx47a7/8knn0xeXl6n591dzjzzTLxe7w73Oeigg7LB17p16zo957HHHktJSckO95k4cSIbNmzItqF9t/It+Xw+xowZw7Jly3Ach3Xr1jFp0qRO27GrLrjggh0+HgqFGDNmDCtWrMBxHNavX99pu6qrq5k3bx7Lli2joaGB1tbWDu+NBQsWZJcXLlzY6fn64rV+6aWXssszZszY4bXbnHDCCdnl999/v0tV4f2BhKhCDACKAl7TrVYFg7TlEE9ZbGqMYTsOHkMjYOrk+g0Cpo7P1NDVLcdOrYGWCvCEIDQIDB9oBmjm5nvVYOtBWIUQQgghhBBiax999BE/+clPeO+99zqtyGxTW1vbrWstXLgwuzx+/HhycnI6Paazbujl5eXZYBZgypQpnZ6zqKiIsWPHsnz5cgA+++yzHYaohxxySKfn3J26Eka2r/DtSrXlxIkTO92nfZA8YcKETvfPz8/fqTb0hJ58bZYuXcott9zCyy+/nB3DtzNdeW/0xWv90UcfZZf//e9/884773R6zrYJysCdhG5PISGqEAOQrikENZ0gOjgQT1tE4mnqW5NoioLXUMnxGYS8BgFTw2t4UIIlm6tT677KjtXqDtBqgKqDpoPuBSMAhjcTsLaFrMbmdZm0SgghhBBCiL3aP//5T66++uouh6dtuts1u6amJrs8bNiwLh3T2TiM7c/p8/koKirq0nlHjhyZDVE7C766es7dpSsz3bcfqzWVSvXIOdu6wXdn/660oSf01Gvz6quv8vWvf51EIrFT1+/Ke6MvXutNmzZll5988slOz7elhoaGnT6mr0iIKsRAlxmeoW2IBitTpVrVnKCyOYahafgNza1S9Rj4zRwMb7sPUscGOw1WGuwUJJohVu+uZ6/RFrQamaDV4watpm9zBWv7kFWGCxBCCCGEEGLAWrp0Kddee202QJ0wYQLf+ta3OOqooxgxYgQ5OTkduoxfeeWV2Ulu2ian2VmRSCS7vOWM4NsTDAa7fM5AINDltrTft7Pgy+fzdfm8u4PSCwUxO3vO3mhDT+iJdtXU1HDRRRdlA9QRI0Zw3XXXceyxxzJ69Ghyc3Pxer3Za91+++388pe/BLr23uiL17p9VWl3pNPpznfqJyREFWIvo2kKAU0nAOBA0rKJpWya6lsBBa+hEfTo+A0NU1fRNRVDVzFUL6bh33aRqWODlXLDVjsFiQRE68C23IuguJNbaZmKVm/YHZfVmwueHf/DZVvSljt5WdskZom0hYKCz9Twmxo+Q0NV++d/eIUQQgghhBjo7r777mwwcsopp/Dcc8/tcNzFnpgYqH0gGo1Gu3RMa2trl8/Z2b7bO28oFOrycWLge+CBB7Kh4wEHHMC77767w6EndtekWbsiEAhkn9Nnn33GQQcd1Mct6j0SogqxN1PA1FVMXQV0bNudoKqxNUWts7lrgaYq6KqKrrohq89wj3HDVRVDUzE0D5ru2f61bGtzyNpaDU3lbqWqNw9CJVsFqpbtkEhb2aA0mbaJJNK0JtLE0zbptE3Scr+JcxxwcFAAj+6ODZvrM8jxGW6oamp4dJksTQghhBBCiN3hjTfeyC7/z//8zw4DVID169fv8jULCwuzy2VlZV06prP92ne1j8Vi1NbWdrjO9rSfbKkr+4u9R/v3xs9//vNOx+7tifdGbyspKcmGqJWVlX3cmt4lIaoQIktVwefR8HnaBY4OpG2HtG2TthyaYynqWx2czKCpKgq6pqCrCqah4ssMHWBobQGrgq6rGKoGqgZ4wAyC42AnY6Saq0nXbiSpmiT1HKKeIprwE7W9JG2HtOVgOzYOoCuZwFZX8Xp1DE1FbVca6zhOpjLVpqwhhlUXRVPdMWADHp08v4Hfo+M33UpbqVYVQgghhBCi57UfI7GzyXiampr48ssvd/maBx54YHZ52bJltLS0dFoFOn/+/B0+PmTIEIqLi7OTS3344YecddZZOzymtraWr776Krt+8MEHd9LyntVfu8IL1868NyzL4oMPPujtJu2yI444Ivs7/8EHH3Daaaf1cYt6j4SoA0Dh8ocJhXJwNBNH82BrHhzNg6Oa2Hr7ew+O7sFW3f3cfXSZBEjsmOJOVKVrGhhbP2zbZAJWm2jCpjmaxsbOHOpWr2qagqmp+AwVn6mTzgwhEE9apBwP6bQJ6Sh6qgzNWYtq+Aj68nACxSj+PBQz2KXfU0VRsuO/hn1uYy3bHQO2KZqiujnhVt9qCj5TJ9xWrWq41apt48YKIYQQQgghuk9V1exyNBrF49l+j7UHH3ywRyYG2n///bOBZyqVYu7cuXzzm9/c7v62bTNnzpxOzztt2rTsZDmzZ8/uNESdPXt2duzKwYMHs99+++3Es9h17cea3V0TLomu2/K9sSPPPPPMHlHZOX36dB555BHAnVDu5z//eYffw4FEQtQBIH/ti+R4uheEOiiZ4HVzsGprnkzFYM9xr2PiaKYb8nYIdLcIfzUz0x7v5v2z9x4cRev74FfRsMycvm9HP6CqYKptQwJ05Dju+KVp260QbU2ksZwECm7lqq4qeDSNoKmiqiaQC4CSjqGlmlGaanEiHtKePCx/EZYZxjYCO/W6a6pCwKMT8OiZNjkkLZt4yqa8Icb6+lY0VLymSsCjkeczCXj0zPiqOppUqwohhBBCCLFTRo8ezeLFiwF47rnnuOKKK7a538qVK7OT5uwqVVW54oor+P3vfw+4E/Kcc8455Ofnb3P/v/zlLx0qRrfn2muvzYao//nPf3j11Vc55ZRTtrnv+vXr+fWvf93h2N1dGVpQUJBdLi8v363XFp0bPXo0S5cuBdz3xvbGD62pqeH73//+7mxat5133nnss88+rFq1ioqKCr797W/zj3/8o0u/+5FIBEVRdmritr4kIeoA8I/0qYwNwmHFFj4lhZJOoNgJVCuBYiVRrARq5t5dTqA4bZWCDooVR7Xiffws9jzJwCBaS48gMuhI4vnjezx4HggUBXfc1J08ztF9pHV3lkolHUdP1GO0VuLoHixPLml/MZaZg210rUK1Y5sUPLo7Rmr7atVE2qI5mqamJYnjgEdX8Oo6Yb+eGVtVxy/VqkIIIYQQQnTqzDPPzIaoN998M6WlpVsFj2+88QYzZ86kpaWFQCCwUxM3bc8PfvAD/vGPf1BfX09ZWRmnnHIKc+bMYZ999snu4zgO999/PzfffDMejyc7S/r2TJs2jdNOO42XX34ZgPPPP59//vOfXHDBBR32+/TTT7n44otpbGwEYNiwYdx44427/Jx21sSJE7PL//3vf2lqaiIcDu/2dohtO/PMM3nhhRcA+N///V/GjBnDZZdd1mGfzz77jMsuu4yNGzf22HujN2maxv3338+pp56KZVnMmjWLyspK7rrrLsaPH7/NYxYuXMicOXP4+9//znvvvdfh97Y/kxB1ALiPC0i1+MlNKvzkKB+HlHbhx2qntwhZE5mQNZkJWa2ebaRjZ66VzF5LtRIodsdtmwPfbbUrEwQ76Z5tWzcojo3ZWoG5+hnyVj+DZYRoLT2U1tIjaC0+GMfw93UTBwxH95LW3a4ASjqOlmhAb63aHKj6irA84W4Fqm00VcmEpJvfO8m0TTxlUdEYZ0N9FE1R8RgqflMjz28S9O6eKlVTV8nx7mwMLYQQQgghRN+56aabePDBB6mpqaG+vp5TTz2Vgw8+mP333x9FUfjss89YsmQJAKeccgrFxcXZ7sC7oqSkhL/97W9cdNFF2LbNggULGDduHMceeyz77LMPra2tvP/++2zcuBGAu+++m+9+97tAx27WW5o1axZHH300q1evJhKJcOGFF7LvvvtyxBFHYJomS5cu5eOPP8Zx3HkjAoEAc+bMITc3d5ef0846/PDDGTZsGBs3bqSiooJx48Zx8sknU1hYmK0MPOyww7jooot2e9sEXHHFFdx111189dVXJBIJLr/8cu68804OOOAAvF4vixcvZsGCBQAccMABnHLKKfzud7/r41Z37sQTT+T+++/n+uuvx7IsXn75ZV555RX2339/Jk+eTE5ODtFolIqKCr744gtqamr6usndIiHqAPD7433cs0hlTaPNrW9HuXh/kysmenYc8Kg6tqqDsWeUTPc3SiqKv2YhwYp5BKoWoCWbydn4Fjkb38JWdWKFk91AddARpH0yG2NP2TJQVRMNeDOBqq37sTxudaqjebF194bavQDS1N0hCnK2qFZtTVjUt0YyE2v1fojqNzUmD8kl7JcgVQghhBBC7BmKi4t59tlnOeuss6itrQXc6rrPPvusw35nn302s2fP5nvf+16PXfv888/nkUce4dprryUSiWBZFm+//TZvv/12dh+Px8Of//xnjj/++Oy2Hc2SXlJSwgcffMCMGTN48803AXcogpUrV2617z777MPjjz/OYYcd1mPPaWeoqsp9993HeeedRzKZpLKykocffrjDPldccYWEqH3E4/Hw/PPPc9ppp7FmzRrAnQht2bJlHfY7+uijefLJJ3nggQf6opndcs0117DPPvtw7bXXsnLlShzHYcmSJdkvTLZlwoQJ2x1yoz+SEHUAGBrSuOfEAPd/HufF1SnmLE2yqNrip1N8FPm3/22a6D7H8NM6eAqtg6eAbeGtX0awcj6BinmYrZsIVH9GoPoz+PJ+4uExtA46gtbSI0iER8s4qj3E0b1YuheLTKBqxTEi5Si2W0XtqIY71q7hxzJD2EYgG646mgeUnXtvbK5W7YUnswNVzXHW1EaYOCSMocn7WQghhBBC7BmOOuoolixZwt13383zzz+fDYwGDRrEIYccwmWXXcaZZ57ZK9eeMWMGxx57LH/+85958cUX2bBhA4qiMHToUE4++WSuu+46xo0bx8cff5w9prOq0ZKSEt544w1eeeUVnnzySd5//30qKytJpVIUFxdz0EEHcfbZZ3PZZZdhGH1bADF9+nQWLFjAvffey/vvv8+GDRuIRCLZSlnRt8aOHcvnn3/Ovffey9NPP82KFStIJpOUlpYyadIkZsyYwYUXXoim7XlDyU2bNo1ly5bxzDPP8OKLLzJv3jwqKytpbm7G7/dTUlLCuHHjmDJlCqeddhoHHnhgXzd5pyiOvIv2WM3NzYTDYT555yXCOUEA3t6Q4o/zY0TTkGMq/PhIL0cMlgq23cloKSNQ+THByo/x1i1DYfNbLOUrdCtUSw8nVjgZR5OfTa9wHBQ7tXlYCDsJjoODCrqJrZrYZg6WGcLRvdiaF6ctXO1nLNuhsjnGuNIQIwuDfd0cIcReJpVK8dJLL3H66af3+R+EQgghel88Hmft2rWMGjVqwM6u3d4DDzzAt771LQCuu+467r///j5u0d7Ftm2am5vJycnZ4XAKQuxIT3xuteVrTU1NO6xKl0rUAeb44Qb75mn8+sMoKxtsfv5ujAvGWXxjsgddZhnfLVKhoTSGhtK473loiSb8lZ8QrPwYf/VnGLFacte+SO7aF7F0H9HiQ9wq1ZJDsc1QXzd94FAUHM3E0UwgSHaE3+zYvAn0aBVGpAxQcBQts78Xy5OLbfjdilXdh615e3/SMMdx2+ZY7e4tFNtGVSDs9bOuNkrYZ5IX2M2lsEIIIYQQQgxQTz75ZHa5r7rfCyH2HBKiDkBDQip3nxjggYUJnlmZ5F/LkyyqsfjZUT5Kg/Ltzu5kecK0jDiRlhEnolhJfDVfEKz8mEDlfPR4PaFN7xPa9D6OohLL3z/b7T8VHNzXTR+YFNWtONW92O232+nMxGUxjJZGVNvGaQtiVQ+WGcA2c7B13xZDAijg2JnA09oiCM1sb1u3rex+ip1CsVNgp1CtFDhpFMdxH8fOnNNdBxWPN48Kp4A1lRaTRpRg6vI+FkIIIYQQYlc8/fTTvPHGGwB4vV7OOeecPm6REKK/kxB1gDI1hRsO8XJAicZdH8dYXmdx/asRfniEj6OHSne8vuBoJtHSw4iWHgaOjadxFYEKt9u/p3kd/rrF+OsWU7T4HyRCw7ITU8XzxoKy542FskfJTrTm37zNcVDsJIqVRIvXYbRWAg6OooLmwdY8gJIJSjeHpm3hp+K0xbQdJ6ByFCUzHqvinktRcRQVR9FANbHbbUNRUWwLLdnEkFQ1tU1rqLBGM2L4SPDkyPi6QgghhBBCbOHDDz9k1qxZ3HDDDdscbzGRSHD//fdzyy23ZLd961vfIi8vbze2UgixJ5IQdYA7ZqjBPrlu9/7l9Ta3vx/j7LEW1xzgwdQkgOkzikoibyyJvLHU7385emsVgcr5BCs/xle7CE/LRjwtG8lf+RRpTy6tJYfROugIokUH4ugDf2yifkFRcDRPZpzUULshASwUK4lqJd1VRcVRNWzFyISjmwPQngg5HU0l7SsEr00w2kTj+i/JjZcRLhwCOYPBlw+afJQLIYQQQggBkEwmefDBB3nwwQcZNmwYBx54ICUlJTiOQ3l5OR999BFNTU3Z/ffff3/uvPPOPmyxEGJPIX957wVKgyr/97UA//wywVMrkjzzVZIlNWl+PsXP4JB0C+4P0oESmsacSdOYM1FTrfirPnXHUa1cgJ5oJLzhNcIbXsPWvLSWHk7LkGOIlhyaGfNT7FaKhqP7sHTfbr6uihHII0KAsmgKb0M5nqYyN0QND4FAEZj+zs8jhBBCCCHEXmLjxo1s3Lhxu4+fcsopPP744wQCgd3YKtFb6uvrue2223b5PN/73vfYd999e6BFYqCREHUvYWgK1x7k5YBijd99HGdlg831r0a4+XAfxw2X7v39iW0EiAydSmToVLDT+OqWZLv9G9EqQuXvEip/F0v30Vp6JJEhxxAtPhhHk5/j3iDXb1Ibsam0QwzPMVESTVDxBZhByBkEwRLw5oLMbimEEEIIIfZCU6dO5c033+Sll17ik08+oaKigtra2uws8IMHD+aYY47h4osv5rjjjuvr5ooe1NzczL333rvL5zn//PMlRBXbJCHqXubIIQZ/PUXjzo9iLKm1+J8PYyysTnPdgV48unTv73dUnVjRAcSKDqB20jV4GlcSKn+fYPl7GLEacsreIqfsLSw9QOugI2kZeizRogNAlUB1oFIUCPtMKpvihHw6+f4Ctxo1GYH61dCwDvyFbnWqvxB0qVYWQgghhBB7D1VVmTZtGtOmTevrpgghBhgJUfdCxQGVu07wM3tRgieWJXlhVYqltRY/n+JjWI5MYNRvKUp2HNXaCVfibVhBsPx9guXvY8TryNn4Bjkb38AygkQGTyEy5FiihZNBlZ/pQGPqKpqqUN4QI2DqeHQVPCH3lk5ArB4iVe56eBgECsGb09fNFkIIIYQQQoheM3LkSBzH6etmiAFMQtS9lKYqfPMAL5OLdX43L8aaRptv/7eV7x3q5cSRUrnW7ykq8fzxxPPHUzvxm3jrlxEqe4/gpvfdMVTX/5fw+v+SNnNoHTyFliHHEiucCIoEqgNF2GdQ0xJnU2OUkQXBzXNY6R4IFoNjQ6IZqpaA4XW7+YcGgT9fgnUhhBBCCCGEEGInSYi6lztskM79pwb4zUcxvqi2+O28OAurLL59sBdPP81ZFAXUHpj1fMBQVOIFE4gXTKBm8jX4apcQLH+P4KYP0ZNNhNe9QnjdK6Q9uUQGH03LkGOJF4yXQHVPp0DYb1LVnCDkNSkMbvHlh6K6Y6N6cyEVhaYyaNrYcSIqYzdPjiWEEEIIIYQQQuyhJEQVFPpUfnu8n8eWJHh0SZJX16Z4dW2qr5u1QwqgqaAr7r2mKOgqaJl1XVWyy5rirrd/PLt/u8fd++2cT1Ey53W3mZrCvvka++S63ar7DUUjVjSZWNFkaiZfh692EaHydwlu+gg90Uju2hfJXfsiaW8+LYOPJjLkWOL549zATexxTF3F0DTKG6IEPBo+YzvBuOF3b3Ya4k2waSGYIbdi1fC6lamK6gbrippZ1zLfWLR7rMOy/M4IIYQQQgghhNh7SIgqALd7/8xJXiYV6/x+XoyaWP8eR8QB0jakAay2LVvu0fsCBkwu1jmwWOOAYp1RuWr/qZJVNWLFBxIrPpDqA76Nv+YLt0K14iP0eD15a54nb83zpHyFRAYfQ8uQY0nkjYX+0n7RJTlenZpInE0NMUYVBnecbao6tJ+Iqmm92+1/q7eLAtibg9RsaKpmQlTFXVcN95yaAUrmXtO3E8iqYAbc0FYIIYQQQgghhNjDSIgqOjioROeRM4NE033dku1zHIe0DZZD5t7Bsmm3zcHOPNbhcYfMfg5W27IDVvt1G9KZ/bc8f9v+aduhNQVLa9O0puCj8jQflaeBBDmmwgHFGgeW6BxQrDE8R0XpD6GkqhMtOYRoySFU2zcQqP6cYPl7BCrmYcRqyVv9DHmrnyHlK6ZlyDEkcvfBUQ0cVe9wT4f1tuV2j7cFbGL3USDP56E6kiDHZ1AU8nThGGXzRFQ74tjuzbYAB2wbsN17Kw3p5OZ9sjdn8zXaD+qu4Fa/5g53x2aVMFUIIYQQQgghxB5EQlSxFU1VCPXruaX6R0hn2Q6rGm2+qEqzsDrNohqL5qTDe2Vp3itzU+h87+ZQ9cBinUFBpe9DVdWgtfRwWksPR7GS+Ks+JbTpfQIVH2PEqslf9XS3T+2gbBWyskUQa3lyadjnHGJFk3vwSe3ddF3Bq2uUNcQIeHT8Zg+Nd6tkKk/VHvhPheO4QwlULoLGDZA3EkKl7kRYQgghhBBCCCFEPychqhDdpKkK++Vr7JevceF4D2nbYUW9xcIqi4VVaZbWWdTHHd7akOatDW6oWuRXOLBY58ASjQOLdYoDfTuupKOZtA4+itbBR6Gk4wSqPiVQ8SF6vB7FTqPYqcx927K7TuZetTuOnavgoNhJsJM7vG6g6hMipUdQO+EqUqGhvfkU9xpBr05tS4LyxhijC4No/W3IUkUBXy54c9wwteKLTJg6AoKloPfrb26EEEIIIYQQQuzlJEQVoofoqsKEQp0JhTqXTvCQtByW1VosrE6zsMpieb1FTdThtXUpXlvnho+Dg26oekCJO65qvq/vki9H9xIZcjSRIUfvxEEOONZ2w9Yt77HTBKoWEF73MsHKjwlULaBp5GnUjbsE2xPuvSe3l8j1m9RGEoS8OqU5/bS7vKKCLw+8YYg1upNc+fI2V6ZqRh83UAghhBBCCCGE2JqEqEL0ElNTOKDEDUivmASxtMOSGosvqtMsrErzVYPNpojDpkiKl9a4oerwHJUDijUOyoypmuPpb+WEW1AUUDJd97t4SLT0MBpHT6dw8T8JVn1C7toXCG18i/r9LqRp9Jk4mlQkdpeuud36NzXGCXp1gmY//ohXVPDnu9WpsQaoWAiNmTA1WCJhqhBCCCGEEEKIfqUf/4UtxMDi0xUOHaRz6CD3bdeaclhck+bzKjdYXd1gs6HZvT2/yg1VR+eq2e7/k4t0Amb/GA92V6VCw6g46hf4ar6gcPE/8DatoWjJLHLXvkTt/jOJDJkqE1R1U9CrUxtJsKkhzuiiALraz19HRQV/gTt5VbwRyj931/NGZMJU+c+UEEIIIYQQQoi+J3+dio7sFGo6gWKnoCu1hU5X6w8BVcfWTBzVBLWHJr7ZgwUMhSMGGxwx2K24a044fFnjVql+UW2xrslmTaPNmsYkT38FquKGqhMKtcywAVqfj6m6q2JFB7Dx+LsJbXyLgqUPY0SrGLTg98RWP0ftxKuJF4zv6ybukfJ8JnWtcUJenUHhftqtf0uq5oanXsutTN30GfgL3TA1UCxhqhBCCCGEEEKIPiV/lQ4ATdEk4RA7PWm9YqVQrASKFUe1koDidsvWPDhGAJtM0NnZebdbMdhxu5qOoaUTYDWjODbgZK9nqwaO5un7cNWxM2N8WuDYKI6N4rQtW2BbKNjggKPqpH0FbiVdD8jxKBwz1OCYoW6o2hC3+aLanaRqYbVFeYvNqgb39uxKt1K1yKcwocgNVfcv1BiTq6L198rDLSkqLcO/RmTw0eSt+g95K/+Nr2EFw977ES2Dj6ZuwpWkAoP6upV7FE1TCBgG5Y0xgh6dkHcP+qhXNQgUgp12w9Tyz9z13BEQLO77zwghhBBCCCGEEHulPegva7E9XkOjtjVBvt+Dup08zw1M46hWAsVKokA2uLQ8+aQ8YWzdh234sXUfqL0wHqHjtAttEyjpOFoqgppsQbOSkGzJhKvgqBqOZmKrpjtGprqTv6ptwadtuefcQRja4TBFAUUDRcVRNFA0HNXAUU33XnPb46gaRqQSo7WSlL9459vXBXleleOHqxw/3P1Z1ERtltRaLKmxWFKbZnWjTU3M4e0Nad7ekAbAq8O4fG1zsFqg7TFDADi6l/pxl9A08hQKlj1KzvrXCW36gGDFxzSOnk79fhdjm8G+buYew+fRiEUsyhpi7FMSxNjTwnVVh0CRG6ZG693K1EAh5I507yVMFUIIIYQQQgixG0mIOgAML/ATsTTqInHy/CaGkkaxEtnA1K0wdQPTtLcA2wxjGz43NO2twHRbFAVH9+LoXuzMphRsHa5aCbRkC2oygmYlIBlxg08y4apqAI4bjtpW5rGOAZGTmfAIRcmEofrmMFQzsTUTVDcMdYNSDUfRNy+reiZI1bcb1qR9RXgaVmK0lpP2FuDovdttusjfMVSNpRyW17uh6tK6NEtrLVpTsLDaYmG1Bbhh+ciwyv6FGhMKNSYW6ZQGFJR+PN6o5c2n+qAbaRx9FoVL/kGg+nPyVj9DzoY3qB93MY2jTt99v7N7uFy/262/qklnaJ6vr5vTParuVqC2hamRT9yxUvNGuN39t/fNkRBCCCGEEEII0YMkRB0A/E6UYp/Gplgz9XUJgv4Ahukn7S3E8oRx9PaBaT/8kXcariZQrXi7cLU1MwxAxzC0ffC5ORztPAztLkf3ES8Yj6178TStxTID2GZOj15jR3yGwkElOgeV6IAH23FY35SpVq21WFqbZlPEYW2TzdommxdXu0MA5HuVbKg6oUhjn1wNQ+t/oWoyPJJNU36Fv+pTChf/A0/LBooWPUB4zQvUTriK1kFHyeRTnVBVCHkMKppihLwGYV8/fP93VVuYaqUgWgutNW6YmjvcHUtVwlQhhBBCCCGEEL1oD/6LWmym4skdxNDicdjNDmubLALBMEGfp68btms6hKthIBOu9ieqQTJ3Xxzdj6dxJWq0hrSvsE/CPVVRGJWrMSpXY/o+7rb6mJ0JVN1gdWWDRX3c4f2yNO+XuUMAmBrsl++Gqm3hao6n/wRS0ZJD2FB0IDkbXqNg2aOYrRUMnn8nsYIJ1Ez8Jom8sX3dxH7Na2rEkhblDVF8ZhBT6z8/227RDAiVgpWE1iporXYnnsob4YapEqwLIYQQQgghhOgFEqIOBEMPhaJiDGBUvoPeEGVldYRUNEme3+zr1g18ikIqNBRb9+FpWIHRWkHKX9IvxmzM96kcO0zl2GFu9/dE2mFlg8XizNiqS2stmpMOi2osFtVY2eOGhVTGF2qML3CD1RE5fTxhlarRPPJUWoZMJW/lv8lb/Qy+uiUMf+dmmoceR93+V5D2F/dd+/q5sN+krjVBVVOcYfn+vm5Oz9BMCA1yw9RItXvLKYW8keDL6+vWCSGEEEIIIYQYYPbwkiQBdAjrVFVhREGAiYPDODhUt8RxHGcHB4ueYvkKiBdOJu0vwWitRLESfd2krXh0hYlFOheP9/CrqX6eOifIP08P8IPDvZw62mBYjvuRsLHF5r9rU/xpQZxrX2nlnKdb+NGbrcz6Ms688hRNCbuTK/UOx/BTv//lrD/xbzQPOwGAnLJ3GPH6tQx7+/sM+vjXFH75N3JXPk2w7F28dUvRo9VgW52ceWBTVQh5dTY1xWmI9rt67l2jmW546s+D5k1QtgBqVkIq3tctE0IIIYQQok+8/fbbfPvb3+bQQw+lqKgI0zTx+XwUFxdz6KGHMmPGDP74xz+yYMGC7eYFt99+O4qidLh9//vf36l2vPjii1ud4/jjj99tz6E7tvW8u3obOXLkNs85e/bsrfY955xzdqpdS5Ys6fL1tqe6upoHHniAc845h/Hjx5Ofn4/X62XYsGEcfvjh/OhHP+Ltt9/e5dfTtm1GjBjRoa0ff/zxLp2zv5BK1AGqNOzF1FW+qmyhojlOScjbt5WEewnbDBIv2B9T82I2r8fy5PTrGeUVRWFYjsawHI1TR7vbmhM2y+osltVaLK2zWF5nEUu3n7DKNSSkupWqBRrjCzVGhXdftWraV0jVITfTOOYsChf/A3/tIryNK6Fx5Tb3d1BJe/NI+wpJ+4ra3ReQyqxb3jxQBu73Sl5DI560KWuI4jdDePQB9lx1D+QMhmQEapZBpBIK9nHHTZXxUoUQQgghxF5g2bJlfOMb32DevHlbPZZKpYjH49TU1PDpp58yZ84cACZMmMDixYu7dP45c+bw+9//Hl3vWpT00EMPdb3xGb39HPqLl156ibq6OgoKCrq0f3deyzatra389re/5a677iIajW71eFlZGWVlZXzyySf84Q9/4PDDD+euu+7imGOO6db13nrrLTZs2NBh20MPPcQRRxzRrfP1JxKiDmD5AZOJQ8OsqGymsilGcY4XY08fD3EP4GgeEvn7Yet+PE2rUOwklje/r5vVZTkelSMGqxwx2B0CwLIdNjTbLK21WFbnBqsbm23KW9zb6+vcykav7o6tOj4Tqo4v0Mjz9u7vWyJ3H8qPvhOzZT1GayV6rAY9Voceq8GI1aLHatFjdShOGiNehxGvg4YV2zyXo2ikvQWk/W7AmvIWbA5c/Zmg1Qzv0WNuhv0GtZE4FU1xRuT79+Snsn1mEAw/ROuh/FMID4X8UeAN93XLhBBCCCGE6DWff/45J5xwAo2NjdltJSUlHHrooZSWlqIoCnV1dSxevJhVq1Zlqw3b79+ZqqoqXn31Vc4444xO921sbOT555/vd89hZwwePHinKka7GogCJJNJnnjiCW644YZO97Vtm8cee6zL525v06ZNnHbaaXz55ZfZbYqicOihhzJ69GhCoRCVlZV8/PHH1NTUADB//nyOO+44/vjHP3LjjTfu9DW3Ffg+8cQT/PGPf8Tj2bPn7pEQdYALenQmDA6zSo9Q1hClIODBa/T9WJ0DnqKSCo/AMbx46r9Cb610x+zcAysdNXXzhFVnZCasak44rKi3WFqbZmmtxfJ6i2gKvqi2+KJdteqggML+hXo2VB2dq6L3dLWqopDMGUkyZ+S2H3dstERjNmA1YjWZcLU2s60WPVaP4lgYsWqMWPV2L2WrRqaKtRDLk4eteXA0E0c1sve2ZuKoprve7jFbNXE0I/OYe29n93G3ofTue1NRIOwzqWqKk+PVyQ8M0DGTFRUChe54qc1lEK2FvNFuoKoP0OcshBBCCCH2WqlUihkzZmTDxMGDB3Pvvfdy1llnoW6jV1ZNTQ3PPvssjzzyCGvWrOn0/Pvvvz9Lly4F4OGHH+5SiDp37lzi8fhWx/fVc+iOfffdl7/85S89es599tmH9evXk0qlePjhh7sUor7++uts2rQJ6Npr2aayspKjjjoqWxWqKApXX301v/jFLxgyZEiHfS3L4sUXX+Smm25i7dq12LbN9773PaLRKD/5yU+6/PwikQhPP/10dt3n8xGLxWhoaOD555/n/PPP7/K5+iMJUfcCXkNjXGkIU1NZV9dKyGMQ9MqPfndI+0uwNS/ehq8wIxWk/MVuWLaHy/EoHDZI57BB7u+R7XSsVl1Wa7G+2aai1aGiNcUb691qVY8Go8IqPkPBoymYGtu89+hgagoebfO9p21d37ze/jhDdf+jsBVFxfLmY3nzSWxvviHbQk80bA5Vo+69EatFj7uBqxZvQLVTmK0VmK0VvfK6OoqWCVyNbLgaLTmE2v1n4ui+HrmGqbvDLpQ3xPCbOl5jzwv2u0wzIWcIJFqgajG0VELBGAgW79EVxUIIIYQQQrT3zDPPsHz5csANrd566y3Gjh273f2Lioq4+uqrufrqq1m9enWn5580aRKGYfDFF1/w3HPP0dTURDi8455ebdWIhmFwySWX8P/+3//r0+fQXxQUFDBhwgSeffZZ5s+fz4oVK9hvv/12eEz7ys6ZM2d2KdR0HIeZM2dmA1RN03j00Ue5+OKLt7m/pmmcddZZTJs2jVNOOYWPPvoIgJ///OdMmTKFqVOndun5PfXUU7S2tgJuYHzWWWfxf//3f9nnISGq2CPomso+xUE8hsrK6ggp2ybPLxVZu4PtCRMrnISncRVGSxlpby6OMUBmSM9QFYWRYY2RYY3Tx7jbIkmH5XWZULUuzbJai0gKltf33qRUbWGqqSlb3IOhumHrlo8Z2W1BTC2EoY3GVMHwK27P8ExI6yVFyGognK4lmKrDl2rCcJLoTgqdFLqdRLOTaE4KzU6i2ikUO4lipVCtBIqdQrGS7e6TqFYKxUln2684Fko6hkps83Naswl/5SdUHfID4gXje+R1CvsMaiIJyhuj5HgNdM2tENYyN0NVB9Ywop5Qpot/XaaL/zDIH+luF0IIIYQQYg/33//+N7v89a9/fYfh45bGjBnTpf2uuOIKbr75ZuLxOHPnzuWaa67Z7r6rV6/mww8/BOD000+nsLCw0/PvjufQX1xxxRU8++yzgFvZ++tf/3q7+7a0tPDMM88AcMABB3DAAQd06RqzZs3itddey67/7ne/226A2l4oFOLll19m4sSJlJWVYVkWV155JStXrkTTOu852T7wveyyyzj77LOzIeorr7xCdXU1xcXFXXoO/dGADlGTySRPPvkkc+bMYcmSJVRVVZGXl8eoUaM499xzufLKK7v0Zt4Vn332GXPnzuX111+nvLyc+vp6CgoKKC0t5cADD2TatGmcdNJJlJaW9mo7AFRVYURBAK+hsaKyhermOEUhz7ar90SPcnQv8fxx2LoPs2k1jp3E8uT2dbN6VdBUOHSQzqGDdMCD7ThsbLbZ2GKTTEPCckhYkMzcZ9fTHbe3fzy5jXu73cSBScu9tabaNvbcLI2uUOY2qtM9VQU0xQ11dVVBV8nc3PBW192e5aZi41dT+JQUPjWNT0niVdz1YruWS1sfIhitZOh7t9Aw9jzqxs0AdRermRXI85lUtySobklkNiloKmiq6rZbUzF1FY+uYugquupWsOqqgq4p6KobvO4xHx+q5lagphPQuB5aa9yxUsNDYQBUhwshhBBCiL1XeXl5dnnEiBG9co0ZM2bw4x//mHQ6zcMPP7zDEPXhhx/OLs+cOZPq6u0PmdZmdzyH/uKMM86goKCAuro6Hn30Uf7nf/5nu7nMU089lZ0MaubMmV06v+M4/OEPf8iuH3zwwdx0001dbl84HOaee+7h3HPPBWDt2rX8+9//5sILL9zhcevXr+edd97Jrl922WWMGTOGSZMmsWjRItLpNI899hjf//73u9yW/mbAhqjLly/nkksuYeHChR22V1ZWUllZyUcffcTvf/97Zs2axemnn97j16+urubmm2/e5uC/FRUVVFRU8PnnnzNr1ixuuOGGHh9nY0dKcryYmsqKqhYqmuOUhLy7bVb1vZqqkwyPxtF9eBpXokerSfuK9ppuxaqiMCKsMSLcc+N+Oo5D2oaEBSnbDVVTlkPShlQmgE3Z7v02t7U/bottKYvMMVvu52TD2nTm+mm7Y5gL7rrtuOftGOZuK9g1MrctDecvjOOhwkc4OPIO+V/9C3/Vp1Qd8gOSObv2DwtdVygMbh7U23HcScTSto1tO8TTNq0JC8txcLAB9/dUZXPFqqYqGLqCR9Pw6KobrmqZwFUDXVHRNAWjP32+6B4ID4F4E1QugkgV5I9xx1DdS96LQgghhBBiYGk/ZujatWt75RolJSWcfPLJvPTSS3zwwQesXbuWUaO2Li5xHIdHHnkEgPz8fKZPn84///nPTs+/O55Df2GaJhdddBH33XcfGzZs4O2332batGnb3LctkNY0jUsvvZTPP/+80/O/++67LFu2LLt+0003bXNc2R05++yzGT16dHa82fvvv7/TEPXhhx/OTvY1ZcqUbIXw5Zdfzo9//GPArVSVELWfKSsr42tf+1p24F1FUZg6dSpjxoyhpqaG119/nVgsRnV1NWeffTavvPIKJ5xwQo9df8OGDRx//PEd3vj77bcfkyZNoqCggGg0yurVq1m4cGH2G4XdLS9gMnFImBWVzVQ2xygOeTG0gdR/t59SFFLBwdi6D0/DCozWSlL+IlAH5Fux1ymKgqG5XfLbQr6+YtkOlkMmVHWD2rTdcd2y3RA2bZNZb7/f5kA2lTnXhmabV9b4Obf2Wn5QfAjXxx7A27SGYW/fRN3+V9A45qwem6xMUciEoDsOuW0bLNvGchzSlkMq4dBip7GcdtW/joKmKWiKgpqpXvXoGj5DxWtqeHUNU1cxNbXvcktvGMygO+lU2QLIHQZ5I8ET7KMGCSGEEEII0T3tu7M///zzLF26lP3337/HrzNz5kxeeuklHMfh4Ycf5he/+MVW+7z33nvZLOSiiy7CNLs2jODueg79xcyZM7nvvvsAN3zcVojavrLz5JNPpqSkpEvnfuutt7LLpmly3nnn7XT7FEXhkksuyQ418NFHH5FIJPB4PNs9pn0F8uWXX55dvvTSS/nJT36Cbdt88cUXfPHFF10elqC/GZDJzYwZM7IB6ogRI3j22Wc7/IBqa2u5+OKLeeONN0ilUlxwwQWsXr2a3NzcXb52U1MT06ZNy35oTJs2jbvvvpvJkydvtW8ymeTNN9+kpaVll6/bHUGPzoTBYVZVRyhriFIQ8OA1end2cOGyvHnECifjafgKo7WStC8fR/f2dbPELtBUBQ13/NWeDHQnFGr8aUGcu6oP5aO8fbk3/A/yahdQtPhBApXzqTr4JtL+3TemjKq63xIbsO3iWQCnLVR23OpWyyGRSlHfauPgVrMamaECQl4dn6Hh0TU8xm4OVlUNgiWQjkP92kwX/9HuZFTagPzPoxBCCCGEGIDOPvts7rnnHgBisRhTp07llltuYcaMGVvNwr4rvv71rxMOh2lqauKRRx7ZZoi6ZVf+rtpdz6G/OOKII9hvv/1YsWIF//73v7n33nvx+zvOnfLII49kKzt35rV8//33s8uTJ0/e6rw708Y2iUSCBQsWcPTRR29z3w8++IBVq1YBbnDbvmp18ODBfO1rX8uO0frQQw9lx0nd0wy4vxJfeukl3nvvPcD9wT3//PNMmjSpwz6FhYU8++yzTJ48mTVr1lBfX8/vfvc77rzzzl2+/g9/+MNsufNFF13EY489tt3Bd03T5NRTT93la+4Kr6ExrjSER1dZW9tKyGMQ9A64X4t+yTH8xAsn4Oh+zOa1WGYQ25SJbkRHp442GRRU+eX7MT5sCHNK/GZmjX2P8av/ib/2S4a/+R1qDrielqHH95/u6ApuJep2wmTbhqRlkUjbtDTGcXBQcIcGMDWVoEfHb24OVj2a1rsTXenezV38K75s18W/oBcvKoQQQgghRM+YNm0aZ555Js8//zwAdXV1/PjHP+aWW25h7NixHH744Rx66KEceeSRHHzwweh69/7m93q9XHjhhTzwwAOsXr2aDz74oEOoFo/HeeqppwAYO3YsRx55ZL97Djtj5cqVfOc73+ny/pdffnmH4LEzM2fO5Gc/+xktLS385z//4dJLL+3weNuwCOFwmLPPPrvL5123bl12eeLEiV0+bktbHrtu3brthqjtJ5Q644wzyM/P7/D45Zdfng1RH3vsMX73u9/tlp9hT9vzWtyJe++9N7t8xRVXbBWgtgkEAtxxxx1cdtllAPztb3/jjjvu2KUf4sKFC3nwwQcBGDZsGA888ECXZi/ra7qmMqYoiEdXWVkTIdVqkxfoWsm92EWqQSJvH2zdi6dpFWosQdpb0H/CMNEvHFCsc89Jfn7+bozyFpvzlx7Lbw6eyMkb78HXsILST+8iUDGP6gNvwDZz+rq5nVJV8Koa3naVrI4DybRNyrKpbk5gOXZmuAa3YjVgavg9Oh5dw6urmLpGj45Aoijgy3W787fWQLQe8kZA7ggwu/fNrRBCCCHE3sBxHGIpq6+b0a/4DG23T+D8+OOPM3PmTP7zn/9ktzmOw4oVK1ixYkU2kAsEAkyfPp1rr712u+Nw7sjMmTN54IEHALfqtH2o9swzz9DU1JTdr78+h67atGlTh4ypM4ceeuhOhaiXXXYZP//5z7PDI7QPUefNm8dXX30FwAUXXIDX2/Weq/X19dnlvLy8Lh+3pS2PbX/e9uLxOHPnzs2ut+/K3+bcc8/l+uuvp7W1lerqal555RWmT5/e7bb1lQEVokYiEd54443s+lVXXbXD/c877zyuu+46IpEI9fX1vPvuu7s0Nupf//rX7PINN9xAKLTnVBWqqsLwggAeQ2NFZQuVzXH8hoaqKKiqO3O3qrqTA7k3dvt/FAYsRSWVM9ydcKphpTtOaqAYlP4fwIvdZ2hI454TA/zqgygLqy2+/0ke1x/4K64qeY6CFXMIbfoAX/0yqg66kWjJoX3d3J2mKLhVp8bmZNRxIGXZJNM2tZEkVnMCFDBUt9u/z6MR9OjucZlgVVeUXfsOQtUhNAhSUahdCZHqTBf/wW73fyGEEEII0UEsZbH/ba/2dTP6laV3nILf3L1xSzAY5Omnn+all17i7rvv5o033sC27a32a21t5cknn+TJJ5/krLPOYvbs2TsVtB1zzDHZCYfmzp3LPffckx0ns60aUVGUbQZp/eU59BfDhw/n+OOP56233uKNN96goqKCQYMGAR0rO3c2kG4/ZGQgEOh2+4LBjvNFNDc3b3O/9uF5fn4+Z5xxxlb7BAIBzj333GwQ/tBDD0mI2tc+/PBDEokE4P6ADjvssB3u7/V6Oeqoo7IlxW+++Wa3Q1TLspgzZ052vTsD9/YHJTleTM3t2p9I29iOg2W5Yxs6Ntg42DbYjpOdY1wB2taUzP/aQlZVcQNaVWmbZMYNYrW2bf1p1u52nMzzc5zMc2137+BgO2BqKqbec6VwaX+RW5Ha8BVmxJ1wytGkIlhsluNRuPM4P/d8GueVNSnu/TzNhn2+zs3HHsKQz+7CjJQx5KPbaRx5GrUTv7nHj7OrKLgTULV/n7ULVhtbU9RG4oA7eZWuqWgoKKp7rIqS/fxRFNAUUFT3s0jB/fxRFHdfBfczy11WUBUdjGLU1ibUpk8gOAgnfzT4891zZz7TPLqK2k8/x4QQQgghxN7n9NNP5/TTT6empoa3336bDz/8kE8//ZTPP/+cSCTSYd/nnnuOY489lo8++minisAuv/xyfvnLX9LY2Mhzzz3HBRdcQGVlZTZbOe644xg+fHi/fg5dcdxxx/H222/36Dm3NHPmTN566y0sy+LRRx/lRz/6EclkkieffBKAUaNGccwxx+zUOUOhEA0NDYAbOHfXlq91Ts62ez22D3wvvPDC7U4mdvnll2dD1Oeff56GhoY9LvweUCHqsmXLssuTJk3qUtf8gw8+OPtGb3/8zlq8eHE2lQ+Hw4wZM4Z0Os0jjzzCo48+ypIlS2hoaKCwsJDJkydz1lln8Y1vfGOHM5v1lbyASV7AxHHcsNCyHWzHvVn25hDVymyzbdzlzH4py3ZnHbdsdzZyyyZtu48nLffeajvOdrJz8LhhLNlK17aZvTveu49Du1CzXbDZ1mYnG3h23GazOSB1H1Wy11UyIzO2tUXNJCvqFgGLG8goNMSS4ECe3+yxMNU2Q8QLJ2I3rsLTspG0J4xtdP+bIzHwGJrCzYd5GRZSefCLBM+vSrEpMpjbjr6b4SsfJm/Nc+Suexl/zRdUHvIDEvn79XWTe5YChq5iZN9z7pgAacv9zLFtByfTm8yh7TMi855vt+yw+cufzM5bzAeW2eCoKI4fs2YNyvqNxIJDSQSH4OheN0Q1NIIejRyviddU8RoaXl3r0S9YhBBCCCH6M5+hsfSOU/q6Gf2Krx9M2FxUVMQFF1zABRdcAEA6nWbevHnMmjWLhx9+mHQ6DcCSJUv42c9+lp3UqStmzpzJL3/5S8Dt0n/BBRfw2GOPYVlW9vG+fg719fXcdtttOzz/kUcemR3isa+cf/753HDDDUSjUR555BF+9KMfZQNGcIPHne0FnJ+fnz1+e13wu6LtHO3Pu6WKiopspgbb7srf5mtf+xqDBw9m06ZNJBIJnnjiCa6//vput68vDKgQdcWKFdnlESNGdOmY9t+OLF++vNvX/uSTT7LLw4YNo6ysjPPPP5/58+d32G/Tpk1s2rSJV155hd/85jc89dRTnVbM9hVFUdAUeqxa1LKdzbd2Fa5p28a2yd4nLYtk2g1E3Ju7X1tAYmWiTpW2KrLNla8KmVnSM9VnuqqiqqBntmmZMFZT1WwF2pZDFKjZoLTjutohRIWWeJqyhijVzW71c37AxOiBQRodzUMibxyOHsBsXIViJbG8e9a3M6J3KYrCheM9DAmp/OajGJ9WWtz4lsOvpl7N6NLDKfn8bszWTQx770fUj72Q+v0udrupD2C6pqD35hjUoQBKKko4vgEr0kQ8ZwRxbzEJy6GqOUF5YwxQ0DUFj+aGqWGfgd+j49Uz4aqh9dvqeyGEEEKI7lIUZbd3XRc7T9d1jjnmGI455hi++c1vcsopp2QrDR944AF++9vf4vP5unSu0aNHc8wxx/D+++/zyiuvUFNTw8MPPwyA3+/n/PPP7/Pn0Nzc3Ol4ppFIpM9D1GAwyLnnnsujjz7KokWL+Pzzz7OvJXQvkB45ciSrV68G3IK/7try2JEjR261z6OPPpoNz0ePHs2UKVO2ez5VVZkxYwZ/+MMfALeCVULUPlRXV5ddLikp6dIxpaWl2eVdSeg3btzYYf20005jyZIlAIwbN47DDjsMTdP48ssv+eyzzwDYsGEDxx9/PO+++y6HHHJIt6+9p2gLMXeWk6mATdubq2Hbh5uwuXpVzVSt7g75AZM8v0F9bpKyhhg1LT0YpqoayfDIbPd+vbWKtL8IFKluE5sdPdTg/76m8v/ei7K+2ebG11q5/diJTJr2F4q+vJ+csncoWPEEgaoFVB7yA1KhYX3d5D2XAo7pxzJ8aIkGQvWL8fmLSfuLsby52YrxtqEGogmLhmgK27FRULLDfwQ8OjlePROuatnxXGWMaSGEEEIIsbtMmTKFn/70p/z0pz8F3ImBPvnkE6ZOndrlc8ycOZP333+fdDrNj3/8Y7788ksAzjnnnN0yP0xPPIf+YubMmTz66KMA3HXXXbz88ssAHH300YwZM2anz3f00Udn5wtatGgR0WgUv3/nJ8v9+OOPs8sej4dDD9167o32XfnXrFmzU3/XfPzxx6xYsYL99ttzek8OqBC1/XgNXf0Gpf1+W473sDMaGxuzy21pvd/vZ/bs2dnS8zZvvfUWF154IbW1tUSjUS666CKWLl263XEj2iQSieyYr7B5UN9UKkUqlep22/cUGu6Yhm7PiLZuuE72znHAAqzdPDFkjkdlXLGfkpBBRWOMmuZWVEUh17/rYWrSW0g638DTsAqtpZKUvxBUo/MDxV5jdK7Kn77m5xfvx1jdaPOjN6PcfJiXaQf/kJaSIyj98j68jasY/tb3qNn/ShpGnSFh/C6yzDwULYUaa8CIVKFrHtLePNK+InRPGE334tNVwH2dHcchadkk02nqmpNUNNrZavq2MV9DPoOgqeMxNLyGgkfXeqSyXYhd1fbvi73h3xlCCCHcz3vHcbBte5sT+oiB4+STT84GkADl5eUdfuaO43RY3vL34fzzz+fGG28kHo8ze/bs7PbLLrtsq323t952jW2df1efw/Dhw7MVkjuy5XXbP+9tPd4dnb0e06ZNY8iQIZSXl/PYY49lt+/Ma9necccdl11OJpPMnTt3pytaHcfpMO/PlClTMAyjw/U+/fTTbPFgd82ePZtf//rXu3QO27ZxHIdUKoXWzd6JXf237oAKUePxeHa5s0CyTfsxSWOxWLevva3Beh999FHOOeecrbZPmzaN5557jmOOOQbbtlm9ejWPPfYYV1111Q6v8b//+7/ZcUfae+utt7r1rYLoXd0fvnl7vNDQ/aBfDGzXjoVHVqosalD57cdxviiPcurQifjG/g8HbXiQ4pbFlCz+O8r6D/h8+DXEza3HsxE7SwXaJu9qzNx2TjRzX90j7RGi97Qf60oIIcTApes6paWlRCIRkslkXzdH9KK28UTb2LbdYfb19gVcqVRqq5nZFUXhtNNO4z//+U9226BBgzj88MO32rd9VpNOp7d6vP1s8j35HLqj/fPeVlu7o/3ztyxrm+c877zzOozp6vV6Oe2007baNxqNZpe393wPOugg9t13X1auXAnA3XffzVlnnYWqdr1I44UXXmDNmjXZ9csvv3yraz344IPZ5by8vC5XzTY1NWXb9vDDD/OjH/1op9q2pWQySSwW4913393qd6Kr2r+uOzKgQlSvd/NM1F39wG//Bulq9Wpn1wY46qijthmgtn/83HPP5amnngLgySef7DREvfXWW7n55puz683NzQwbNoxp06ZRUFDQ7baLnmfZDvWtScobo9S3JjFUlVy/uWvjIdpptHgDipVATUXQkhFUKwFWEsWxAQdH1XE0E1szcVQT1L4f0FzsPr8d4fDPLxM8tSLFK2UqMcXkB4ePpn70ndjrXqJ46T8pblnCiV/9jMpJ19My9LjOTyq6znFQ01HUZATFcbANP2lfEWlvHrYnp0tV5I7jDl2SSNskUxbpduNAO447sZiuquiqisdU8Bs6PkPH0BUMTcXQFUxVRddUGX9V9IhUKsVrr73GSSedhGFITwghhBjo4vE4GzduJBgMbvU3rhhY2sbMbLPffvt1mH29fcGZYRjbnJn9qquu6hCiXnrppeTm5m61X/vfJV3Xs+dyHIeWlhZCoVC3hrfq7Dl0R/vn3b6tu6L989c0bZvnvPrqqzuEqNOnT2fYsK2HY2tfQKeq6nbb98Mf/pBrr70WgC+++IJZs2bx/e9/v0vtbWpq4tZbb82ujx49mssuu6xDlWcqleLpp5/Orv/sZz/r8vmrq6sZOnQolmWxadMmFixYwIknntilY7clHo/j8/mYOnVqtz+3uhqWD6gQNRgMZpe7WlXafr/2x+/KtYEdBqjt92kLUT/88MNO9/d4PB3e0G0Mw5A/bPoZAxjsMSnJDVAbSbCxPkpNJIFH17ofpmo6jjEIB7CBtOOgWAk3VLXiKOk4WrIFNRVBtxKQas6EqwqOqrvBqubB0QxQJFwdiDQUrj3Ix7AcjXsWxHlnY5rqaIxfHutDGzOdePGBlH56F97GlQz57A/E1r9Ma/FBxAonEc8bK0NF7DIFtCCOJ4jj2KipVnyR9dC6HssIkfaXYHnzscycHX7BoQGebXSmaAtYU5ZN2nJoTTo0xlJYdhIyHym6pqCrCoaq4jVVfIaO33SHBjB11b3PLEvIKnaG/FtDCCH2DpZlufNPqOouVYaJ3ev//u//mDx5cpeDqGg0ym9+85vseklJCQcffHCHn3n7ULPtd2JLp59+eodJtvfZZ59t7rfltrb1tq7hiqJw99139/hz6I4tw9yeeB9s7/m3N2nSJD777LPsEATDhg3bqddyS1dffTVPPvkkb775JgC33HILQ4cO5aKLLtphWyORCNOnT6esrAxwQ99Zs2Zt9e/Al19+mdra2mwbZsyY0eXXqrS0lJNOOolXXnkFgEceeYSTTz65S8dui6q6c0zsyr9Xu3rcgApR21djVlVVdemYysrK7HJ+fve7t25ZCbr//vt3esz48eOzyy0tLdlvYMTAoakKJTleCgImtZEkGxuiVDbH8WVm7t6lEENRcHQvju7FJgxACiAbrsZR03FUK46abEFNtqCloxBPopAJVzUjW7XqaKaMlTlAnD7GZFBQ5Y73oyyrs/juf1v51VQ/o3KHsnHq78lf8ST5Xz2Jr24Jvjp3DBtb8xDL359Y4SRiRZOI5+4L6oD6T8TupajYZgjbDIFtoaYieBpX4Sgqthkm5S9xJ6QyQ11+3ymKgqEp2x0rtS1kTVsOadsmErNoiKRIZ8Z1UgBVVTBUBV1zJ7Tymxo+Q8Pv0SkKenbbxHxCCCGEEKLnzJ8/nx/84AcceuihXHXVVZx33nnbnWz7448/5jvf+Q6LFi3Kbrvlllu6FRZqmrbNyYa6o6+eQ39y0EEH9di5VFXl0Ucf5fDDD6esrAzLsrjkkkt48803ue222xgyZEiH/S3L4qWXXuKmm27q0I3/V7/61TYn62o/odQJJ5zAoEGDdqp9l156aTZEffrpp7nvvvv2iDxsQP2F3H5Gr/Xr13fpmA0bNmSXx40b1+1rb3lsV6pat/wFkRB14NI1ldKwl4KgSW0kwYb6KJXNMfyGTthvoPbkzNztw9X2hcuO7VatptsC1hhqshk11YqWakWJNwAOKKo7LADK5nBHUQAFJ3OfLXtTVHdqr7bt7R7P7qsAqJnHxO5yUInOn08K8LN3Y2yK2Nz0eis/P9rPYYN06sdfSsvwE/BXfYqvdhG+2kXoyWYCNZ8TqPkcloGteYkVuKFqtHAyidx9ZHiI7lI1bE8Y2xMGO4WWjOCtX+Z+ieEJk/KXYnlysY3ALr1PNoes4Nazbi1t2dmgNZqwaIqlsGw3ZB1ZEGBUUUAmtBJCCCGE2EMtWLCABQsWcMMNNzBmzBgmTJhAYWEhuq5TU1PDwoULWbt2bYdjzjnnHL773e/2UYu31p+ew8qVK/nOd76zU8fceuutWwWUfWXQoEF89NFHnHrqqSxZsgTHcfj73//OAw88wGGHHcaYMWMIBAJUVVXx8ccfU129eaYGRVH44x//yPe+972tzltbW8uLL76YXb/00kt3um1nn302fr+faDRKNBrlqaee6nSIy/5gQIWo7Ss7Fy1aRDqdRtd3/BQ/++yzbR6/syZOnNhhPRLpfAKgLQdPDofD3b6+2DMYmsqgsI/CoIfqFrebf0VTDL+pE/b1cJi6JUXF0X1Y+hZj/zo2SjqO2la9moqhpiKAjWLbbtWqbQOWOygjoDgO4LgVdmSWcTKPO+5qdt12s1naze6oaKR9+VLp2MuG5mj8+SQ/t78fY1GNxc/fjXL9QV7OHmuSCgyiafR0mkZPB8fGbNmAr2YR/kyoqqVaCFR/RqDa/Yy0dV/HUDU8RkLV7lANLG8eljcPxUqiJlvwRmtwdC9pTx6Wv5i0JxfH6J3JAnVNRddwxxxpJ56yWFMbIZayGFsSwmfKz1YIIYQQYk/xta99jfnz53cIF1evXr3VmKHt+Xw+br31Vm699dZOc5PdoT8+h02bNnHvvffu1DFXX311vwlRAYYOHcpHH33Eb37zG/74xz8Si8VwHIf58+czf/78bR5z2GGHcdddd3Hsscdu8/E5c+ZkZ7P3+Xycd955O92uYDDI2WefzeOPPw64la0Sou5mU6ZMwePxkEgkaG1tZcGCBRx55JHb3T+RSDBv3rzs+gknnNDta48aNYpRo0Zl3/BLly7ljDPO2OExy5Ytyy7n5+cTCAS6fX2xZzE0lSG5PoqCHqpb4pTVx6hoihHIhKndGVS72xQVx/BjdSW0cTqGpW0TWrXfrnQIT9v2a/e4k8aIbMKMVmEZfiwzLFWqvSjHo/Lb4/3cvSDOf9emuPezOGUtFtcf5N08nISikswZSTJnJE1jznRD1eb1+Gu/zFSqLkZLRQhUfUqg6lMALN1PvGAC0cJJxIomkwiPkrF2d5KjmVi+AixAScfR43UY0Uoc3UfaW0DaV0jaV7Bbxqr1GholIS+bmmIkLZuxJSHCPhn/UgghhBBiT3DNNddwzTXXsHjxYt555x3mzZvH8uXLWb9+PU1NTTiOQygUorS0lMmTJzNt2jQuuOAC8vLy+rrpWQPhOfRXoVCIX//619x4440888wzvPzyyyxbtozq6mqi0SiFhYUMHjyYqVOnMn36dI4//vgdZhLtu/KfeeaZ3e5Rfemll2ZD1HfffZe1a9cyatSobp1rd1Ecx3E6323PccYZZ/DSSy8BcO211/LXv/51u/vOmTOHGTNmAG6IWVVVtUvfXvzwhz/krrvuAtxA94MPPtjh/hdeeCH/+te/ALeUuf2sdl3R3NxMOBymtrZ2qzFZxZ4lkbaobnYrU5vjaYIenRyvvnvD1N3JTmO0VmI2r0NNRkj78nC2rJAVPcpxHJ5cluQfXyYAOGyQzs+m+AgYXfgdcyzMpi1C1XRrh10sPUCscAKxwsnECidlQlXpFr7THCcz1EYLimNjefJIhkeR9hXuli8bbMehpiWB19QYWxKkOCSz8u7tUqkUL730EqeffrpMLCWEEHuBeDyeDTK6O8u1EF1l2zbNzc3k5OTs8eOZir7TE59bbflaU1MTOTk5291vwIWoL774ItOnTwfc2ew//fRTJkyYsNV+0WiUAw44gFWrVgHwk5/8hP/93//dpWuvXr2a8ePHZ8uan332Wc4666xt7jt//nymTJmSnXntmWee4etf//pOXU9C1IEnnrKobo6zsSFGczxFjscgNIDDVCUVxWzZgBEpB8d2gyLpIt6r3tuY4rfzYiQsCJkKRw7WOXqoziGlOl69i79njoWnaS2+mkyoWrfEnbSsHcsIEiuYSKzI7f6fzBkhoerOciz0WD04FqngEFKhEdhm5+Nt94S6SAIbh32LQwzN8w3YzyDROQlRhRBi7yIhqtidJEQVPUFC1F00depU3nvvPQBGjhzJs88+y+TJk7OP19XVcckll/Daa68BbhXq6tWryc3N3epc69at61BOPGvWLK688srtXvumm27iT3/6EwCBQICHH36Yc889t8M+77zzDhdccAE1NTUAHHnkkXz44Yc7/UeqhKgDVzxlUdkUo6whRiSRJsdrEPQM0DDVcdDi9ZjN6zCi1VhmEMvMkS7+vWhFvcUd70epjm7++PdocEipzpQhOkcO0Ql7duIfMbaFp2kNvtov8dcuwlu3BC0d67CLZQRJhoaTDA0lGRxCKpi5D5TK2LidUKwEeqweW/eRzBlBKjh4t3Txb4mniCTSjCoMMKowgC4TTu2VJEQVQoi9i4SoYneSEFX0hN0Zog7Iv1wff/xxDj/8cCoqKli3bh0HHnggxx13HGPGjKGmpobXX3+daNStmtJ1nblz524zQO2O3/72t3z22We89957tLa2ct555zF+/HgOO+wwNE3jyy+/5NNPP83uP2jQIObOnTswwzHRbV5DY2RhkJIcnxumNsbY1BQjx2vgN/XNY1kOBIqC5Ssg5gmTbq3EbFqLEakg7cvH0eUfbr1hv3yNh6cHWVxr8WFZmg/LU1S2OnxYnubD8jSqAhMLNY4eqnPUEINBwU7+QaNqJPL2JZG3L437npcJVVfhr1m0uVI1FcFXvxRf/dIOhzqKRipQ2iFYTQaHkAoNkzA9w9E8pIKDUJPNeOuWYsRqSOSMxPIW9OrrE/IaGJrK6poIibTNPsVBvIZUigshhBBCCCH2TgOyEhVg+fLlXHLJJSxcuHC7+xQVFTFr1qwdTgC1s5WoAE1NTVx//fXMmTNnh/sdccQR/Otf/2LYsGE73G97pBJ17xFNpqlojFPRHCeetLBsB01V8BoaXkPFow+cYENNtWI0Z7r4K5D2FkgX/17mOA5rGm0+LE/zQVmK1Y12h8dH56ocPURnylCDMbnqzn/pY6fxNK/HiJRhtpRhRsoxIuWYkTJUK7HdwywjuDlcDQ0hGRzqdmsPDMbR9tKKOMdCj9WB45AKDiWVMxzb6N1JCVOWTXVznMKQh/1KQ4S8e+lrv5eSSlQhhNi7SCWq2J2kElX0BKlE7QHjxo3j448/5oknnmDOnDksWbKEqqoqcnNzGT16NOeeey5XXXUVhYWFPX7tcDjM448/znXXXcfDDz/M+++/T3l5OZZlUVJSwpFHHsmFF17I2WefLRWookv8ps6Y4iDD8v1Ek2miSYumWIrGaIqWeIradBJVAY/uhqpeQ0PdQ3+3bCNAIn8caX8RZvN6jNYqLDOA7Qn3ddMGLEVRGJOnMSZP4/KJHiojNh+Wp/iwPM2iGos1jTZrGpM8siRJiV9hylCDo4foTCzSulYVreokcseQyB3TcbvjuDPSdwhXyzBbytFjNW71asMKfA0rOh6GSspfTKpdsJoMDiURHoVtdm9myD2GopH2F6Ok45gt69FjNSRzRpIKDuq1Lv6GplIa9lHdEmdRWRNjS0MUBj29ci0hhBBCCCGE6K8GbCXq3kAqUYVtO0RTFtFEmpZ4moZoktZkmmTaxrLB1FR8hobHUDH2xPEM7RRGZBNm83rUdJS0V7r4725NCZuPN6X5sCzNgso0CWvzY92emKoLFCvh/uwj5ZgtGzOVq27IuuV4q20cRadlyDE0jZ5OPG+/vWIoADXRhJZsJe0vIpkzole7+DuOQ11rEgXYtzTE4LBXvgjcC0glqhBC7F2kElXsTlKJKnqCVKIKIbpEVRWCHp2gR6c4xw05Emmb1oRbrdoQTdIST1MfTWLZDqqi4NXdSlWP3o1u2bubapDKGYHlK8RoXu928U+2kPblgyJd/HeHsEfl5FEmJ48yiacdPqtM80F5mnnlaZqTDq+tS/HautSuTUy1DY7mIRkeRTI8aosHHLREA2ZLWXZIADNTyWpEq8gpe5ucsreJ5+5D46jpRIYei6MN3KpJ2xPGNoLo8Tp81Q2kQkNJhobjGP4ev5aiKBQGPTTFUizd1EwsmWZUYXBgjdEshBBCCCGEENshIaoQA4iitI2TqlEADMv3k7JsokmLaDJNS8wNVFsTaepbLUDBo6v4TA2P3sWu2X3A7eI/HstXhNm8DiNSieUJYZvb/4ZI9Dyv7nblnzLUwLKdnpuYamcoCpY3n5g3n1jR5A4PeRpWkrv2RYJl7+BtXEXp53djLfknTSNOpmnU6aT9xT3Xjv5EbdfFv2kderSGZHgUqUApqD3/n/mwz8DQFFbXREimbcYUBwfUuMxCCCGEEEIIsS3SnX8PJt35RXfYtkMsZdGaTBNNpGmIpogk0sSTNpZjY2SGAPCbev8MVe0URssmPC3rUdIx0r78AV1puCfoysRURw7WGRRUyfUo5Hrb7pUeHQKgjZpoIrz+NcJrX8SI1bhtRKW19HAaR08nVnTAwO3q7zhoyWa0VCspX3Gmi39+rzzflGVT3RKnOORlbGmIoEe+lx2IpDu/EELsXaQ7v9idpDu/6AnSnV8I0WtUVSHg0Ql4dAjBSCCesogl3WC1KZqiMZaipiWBjY3P0AmYOqbeT/6jphqkwiOwfAUYLZku/qpO2pMHqlTD9YWuTky1LV6drYLVXI9Cnlch16O665ltYY/SpWDf9oRpGHs+DfueQ6DyE3LXPI+/5guClfMIVs4jGRxK4+jpNA87oVe6vfcpRcHyhLHauvjXNLgTb/VCF39DUynN8VHVEidZZjO2NER+wOzRawghhBBCCCFEfyEhqhAiOwRAXsBkaJ5bYdYST9MUTVITSdAYT5KybDyaRsDU8Rp9P56qbQZJ5O/vdvFvWoceq0FpV1jvKCqOqoFq4CgajqrjqLo7lupArULsJ0qDKufu5+Hc/TzZiam+qLZoiDs0xm0aEw6NcYeUDfE0VKYdKlutTs+r4E5m1Raqbg5Y1Q5Ba9stZKq0DjqS1kFHYrRsJHfNC+RsfBMzUkbxl3+lYOlDtAz7Go2jzyAVGtb7L8zutGUX/1it28XfX9KjXfw1VWFQjpeaSIJFZY2MLQ1RmiMTTgkhhBBCCCEGHglRhRBbMTSV/IBJfsBkREGAlkSalrhbndocS9EQs9AUlYBHx29qqH0VmCgKaX8xaW8eWrIVxU6i2GmwU6jpOIoVd+/tFGo6ClYaxbEAB1BAIROwGm7gquiZsFWTiat6yOaJqTpudxyHaBoa4w6NCdu9jzvZgDW7LbPelHBwgOakQ3PSYUMXrq0AQdMNV3M8+YQ9V1BceCHTUu9yTMvLFCQ3kbv2BXLXvkBD/gE0jJpOeshhKL0wjmhfcXQvqeAgtGQTvtpF6P7qzV38e4iiKBSHvDRGkywpbyaetBheEOifw4EIIYQQQgghRDcNnL8UhRC9QlUVwj6DsM9gSK6PWMqiOZamLpKgIZqksjmFAvhNnYCpoWt90O1fNbC8udt/3E6j2Cn3ZmXu7TSKlUS1YijpBIoVd9fTUXf/bFWrk6lq1UHVcToErSqgSmVrNyiKQsCAgKEwJNT574xlO7Qk24esmft2la0NCYfmhBu4tiTd0LUl6S7T0nYmg2f4GnACR6uLuUL7L19TPyOv/gvy6r+gbEEhTysn8aZnGnjC5HoVcjwKYVMh7FUJexRyTHe4geE56p4RFCoKlifX7eIfq8MXrycVHEYyZxiO7uuxy+T6TaLJNF9VR4inLcYUhfrPMCBCCCGEEEIIsYskRBVCdJmiKPhNHb+pUxr2kki7gWpTLEltS5K61iRp28FnaAQ8Wv+ZsTvTld9hB4GRY7cLV92gFccNWhUrgZqOo6ZjKHY6E7Ra4FgdhhDInAi3BlLJLLuPO4rqblPcxxxFyYSw7r0DHdfb9ssMSbC309S27vtAuPP9LdutWG0LVbe8udsP5PeJA7g3Xs0Z6de4QH2LoUotNzKHa+NP8VzrUcy2TuFtZ9Q2rzEooHDx/h5OHGlgantAmKrqpAPFKOkYnqbV6LEakuGRpPylPTaesN/U0VWV9XVREimbfUtC7vjLQgghhBBCCLGHk79shBDd5tE1ikIaRSEPIwtsIok0TZlJqVriKWrTSUxNJeDR8Bla/x4nUVFxNA+O5oEdZZZ22g1a7dTmENWxURwbcJfBcdczNwUHbNsNZR0Lxbbcx2wLFatdIAvQtt1xl60kKCppX4EMMbATNNWtFs3r0uSMQeBayhNXULvhPYrXv0A4spoL9He5QH+X9Z6xvOk/lXfUI6lPajQlHKqjNhWtDn/8JM6jixNcMN7ktNEmXr0f/45nOLqPZHAwWrIJb+1it4t/aDi24cdRzV0OVE29bcKpGPG0zbjSELl+mXBKCCGEEEIIsWeTEFUI0SN0TSXXb5LrNxme7yeSSNMcT1PbkqAxlqQxlkJFIeDR0NXtd/HtDznrVsWlHSi4KauRGVO13WRWTqbuNLPJwdm8LbtPpjI183/ZQQPsdiGsY4Pj4DgWphWlKFmOGanE8oSwzZweeY5iax6PF/Y9iep9TqS5YTnhNS8QKv+AEYmvuCrxFZd7HqZp5Kk0jTyViFHAS6uT/Gt5kpqYw32fJXh8SZLzxpmcuY9JwOgHv8g70qGLfy2+aA3oJo5iYutebCOAbfhwVDPz5YKJrZldrop2J5zyUd2S4MuyJkYVBjB1d/gDTVFQVQVNVdBVBVVxl/eIoRGEEEIIIYQQey0JUYUQPU5RFEJeg5A3M45q0qIlnqK+1e3yH0un+7qJPULBDX0Ud46qbALc1pkfcCfdUjaHw6qioCjukUpmu4qaXXb3IbOPQiyVw7qmIDlKFYXpCoyWTaT9BW7FrOgdikI8fzzx/PHUTrya8LpXCK97GT1eT8GKJ8j/ai6RQVO4fMRJnHn6ZP673uHJZQkqWx3+8UWCJ5cmOHusyTljTXI8/XxMUFUnHShxK6EtdzgLNdWMFq/LVlc7qKAZmQnYTGwz4IasmicTsmZuqtnhWxBFUSjJ8dIQTbK0oskd4MJxt6uqgqa47we1XZCqqwqmrqKrKqauYGgqqqKga+3CV0VBy6xrmWN11X1MCCGEEEIIIXqLhKhCiF7nMzV8pkZxjpeUZWPZOyz13KO4GWnHMFVpH6Yq7NIwBpbtUJPrZ11dgLVNuRQmN5Ebq8bRdHeGdaWfh3R7OMubR/24S6gfewHBinmE17yAv24xoU3vE9r0PqVGiKGDj+Lcw4/lpdZxPL7cYmOzzaNLkjy1IsmZ+5icv59Jvq+f/5wUDUfX2OY7s228YCuFYsXQW5tR7LYvQpRMuKq71aq6H9sI4uhuwGrrHvJNE8fnzf6uOo6D7YDtOFi2g+042DakLYdkyiYST2Nl9nEct5obBXdYDNwvFxQVN4Rtq2zNBKyG5gav7q0taHW/pHDD2rYvMtz7tmMVNRPobvF427Z+PRSJEEIIIYQQYreQEFUIsVu54UZft2LPoakKpWEv+QGTqmYfG+pyaWzMpSi5iWCkEsuTg20G+7qZA5+qExlyDJEhx2A2rSW87hWCmz5ATzQSXv9fwuv/yzVmmIsHT+HDkVP44/oxrGqCfy1P8sxXSU4bY3DROA/FgX4epm5L+/GCt+Q42TGCFTuFHq9FiVZsHtJC0UAzsFUD28zBMkM4uhdb8+LoXhxj5yuq3dB1cxDbFsa2hbC2k3bDWTIhrNsS2urD26Z8a1tuqxZXFVBRsoGroiioZCpnFdA1BV1VURXQVDek9Xt0crw6QY8uQasQQgghhBADnISoQgixBzB1lWH5fopCHsobfJTX5VPfWEZxohJvMkLaV4CjdW28SrFrkuFR1BxwPTWTvoWvbjGh8vcIbvoQPdlE3rqXOYOXOcWTz6oRR/FA0+E83TiG51ameHFVipNGGly0v8nQ0AD5JkFRcDRj+797bQGrlUSPVmFEygE3XHWHAfBieXKxDT+27sXRvNi6F9Tt//NEVRRUrWcCS6d9xStuKOs4m+8dx60GTzsOiRTYTjq7n+2AbTuYujt8SVHIQ9jnDmMi47sKIYQQQggx8EiIKoQQexCvoTGmOEhxjofyhjDVNYUYzespaq1BM91ASrr47yaqRqzoAGJFB1A9+Tr8NV8QLH+fYMWH6Il6xlW9yF28yK9yCniNI5nVcgSvrB3Df9elmDpMZ8b+HkblDpAwdXtU3e3qr/uw22+306hWEsWKYbQ0oto2jqJkxlb1YBl+bDMH2/Bng1VH8/T4zHOK4o7NunkU452XSFu0JixqIy3oqkLQq1MYdCfZy/EamLq8H4UQQgghhBgIJEQVQog9UMhrMG6QQWnYy4a6AiqqNuJvXU9eYhOOPx/b8Pd1E/cuqk605BCiJYdQbX8bf/VCQuXvEaiYhz9Zx9d5ka97XqRaLeLp5BG8sPFIvrVhFFOGGMzY38N+BQM8TN2SqmOrOrT/PXUcFDuJYiXREvUY0SrAwVFU0DzYmgfbDLlDAmSDVS+OZvbZ0wDw6Boe3f35pSybaNJidU0rCq34PTqFAZP8gEnIa+Az97KfsxBCCCGEEAOIhKhCCLEHy/WbhH151OYGKKsuprxqDeGWcoJGM1agcIfdokUvUQ2ipYcRLT0MxUrir/6MYPl7BCvnU5yu4Tr9Ba7TX2CdXcILVUdy76Yj8RePYsYEL5OL9+Kfl6K0G3s1hNW23bFQrCSqlURvrcBoKXM3qzqOauIYPtJmDo4RyI61amteUHd/YGloKmGfSthnYNkOsaTFxoYY6+uj+AyNsM/t9p/jMwiYmoyjKoQQQgghxB5kL/5rTQghBgZFUSgKecgPlFJTmMfGTaVEalaS21iB1xfE8ub2eDdo0TWOZtI66EhaBx1JtZUgULmA4Kb3CVTOZyRVfEd9lu/oz7K6YRAvvHsUr+cczbGTxnBoqQRsWYqGo/uwdF/H7XbKHRIg1YoZr0dxMlNIaSa25iHtL8byFmB5wn0yxIWW6dof9Oo4jkMsZVEbSVDZHMejqYR8OsUhLzleg6BXl3FUhRBCCLFLjj/+eN55553s+rBhw1i5ciUeT+cTed5+++388pe/BOCiiy7iiSee2OH+b7/9NnPnzmX+/PmsX7+epqYmNE0jFAoxfPhwxo4dy2GHHcaxxx7LIYccslP/rnUch3feeYfXX3+d9957j7KyMurq6ohGo+Tk5JCfn8/EiRM5+OCDOf300zn44IO7fO4t/fznP+fXv/51dv26667j/vvv3+nzrFu3jtdee4133nmHRYsWsWHDBiKRCKFQiKFDh3LUUUcxY8YMjjvuuG63VfQPiuM4Tue7if6oubmZcDhMbW0tBQUFfd0cIUQ/kUzbVDW2UlG+FmpXkaPE0XMKcbYMoUSfUdJxApXzCZW/h79qAaqdyj62wh7KR+ZRePc9jvySYRT4VEImEqp2RduQAOk4WiqKo6jYZphUcBCWJw/bDPZ1CwGIpyxaE2niaQtdUwl6dEoyFao5PgND6z/jqKZSKV566SVOP/10DEMmrxNCiIEuHo+zdu1aRo0ahdfr7evmiJ2wZYgK8Kc//Ykbb7yx02O7GqIuW7aMb3zjG8ybN6/L7ZowYQKLFy/e5mO2bdPc3ExOTg6qqjJ37lzuuOMOlixZ0uXzjx49mu9///tcc801XQqM2ziOw8iRI9mwYUN2W15eHhUVFV0+z+eff851113H/Pnzu7T/8ccfz0MPPcTw4cO73E7RuZ743GrL15qamsjJydnuflKJKoQQA4ypqwwrDFEUnsCm6kHUln+F1riBoKGhhor7pJuz6MjRvUSGTiUydCpqKkqg8mPMDe+RU/MZ+6ll7Jf+Fyz7F4uXjOR56yhe5UgS3mIK/SoFPoUCn3tfuMW9R9/Lg9Z2QwLYnjCKlUJNteCtXYKje0h7CzIVqnmZYQP6htfQ8Bqbx1FtTaT5qiqCqioETI3CoAe/R0NXVXRNQVcVdE117zPLQgghhBCdufPOO7n66qvx+3d9voTPP/+cE044gcbGxuy2kpISDj30UEpLS1EUhbq6OhYvXsyqVatoq9drv//2xGIxrrnmGubMmdNhu9/v57DDDqO0tJRwOExjYyPV1dV8+umntLS0ALBmzRq++93v8tprr/Hss892+fm89dZbHQJUgIaGBp577jkuuOCCLp1jxYoVWwWoY8eOZeLEiRQWFtLY2MiHH35IWZk7HNXbb7/NUUcdxXvvvcfo0aO73FbRf0iIKoQQA5TX0Bg9pIii/DCVFYNp2rQcvXYD/mAeij+3r5snMmzDT8uwaTBsGg3JCMrGj0itepcxsS+ZqK5jorqOW5nDp6l9eb7+KF60jqCGvG2eK2hAoV8l36tkA9ctg9Y8r7LXdB13NANLy8fygpKOoceqMVorsI0AKX8xlq8Qywz36RcLhqaS6zfJ9YNlO7Qm0qyvi2I7TnYUDlVR0FRQVQVdVdFUBa+uYeoKXkPD0NrC1kzQ2racCWClilkIIYTYO1VVVXHPPffwk5/8ZJfOk0qlmDFjRjYQHTx4MPfeey9nnXUWqrr1l7s1NTU8++yzPPLII6xZs2aH504mk0yfPp0PPvggu+3www/ntttu46STTsI0t55ENJ1OM2/ePP7xj3/w+OOPk0wmaW1t3ann9NBDD2WXfT4fsVgsu72rIWqbffbZh6uvvprLLrvs/7P333F23uWd//+6+3369D6qtiQX2XI3LrKNbAwGUwJOgmNICMlClsDuN/vdhCTLNwkhAZLfprAkkIUNBrKmheKAbcCWi2Rs3GVLsi3J0kia3uf0crffH/eZMyNbVvNI067n43Fzyl3PzDE65z3X5/rQ2dl5xDrf97nzzjv5+Mc/TqFQYGBggN/4jd/gsccek89oi5AM51/EZDi/EOJkTOUKDPbuJz/4CoaXw062oloyxH+hUisZ4gOPEevbRmxsJwrVnp8o7LfP4xfGVfw8uJyD5TjjBZ+Sd5wDTh9XgTpLCYPVatB6ZYfOFR3LZKh24KM6ebRKjkBR8M06nFgrnt2Ab8QXZP9gzw/wgwDXC/CCAM8PF9f38fyAgAAIr1tFQdVAV8KwXFNVLEPB1FRsQ8PUtFq4aurhJFjH+gAvw/mFEGJ5keH8i9fs4fxXXnllbch9Q0MDPT09xxyifLzh/N/73vf41V/9VSAMHHfs2MG6detO6Lr279/P2rVrj7rO930+/OEPc+edd9ae+9M//VM+85nPnNCxAQYGBvj4xz9OOp3mgQceOKF9crkcbW1tteD1S1/6Er/3e78HgK7r9PX10draetzjPPLII/T09PCBD3wATTv2H+V/+MMf8iu/8iu1xz/96U+5+eabT+h6xbHJcH4hhBBzri4eJbn+fMZbOhg5/DKFsUMEKBjJZmzTms5gxALhm0kyq95KZtVb0UoTxPt/QaJ/G5GJlzirtIuzSrv4oPJ/KLRsInP+ZkabrmTEtRkvBowV/SNuxwvV21KAH8BEKWCiFLBv0gfgJ684bFnp8rFLbBLmEn8jKCq+mcA3E+C7aJUskfEX8XUb16rHjbXiWfUE+sL54qipChoKxgkUzPqzQtYwaA3IFX1c38ULAnw/rHANqsftqouwqilWay8ghBBCiMXvjjvuYHJykj179jAxMcH//J//sxaSnoqf//zntfvvete7TjhABV43QIUwhJwdoP6X//JfTipAhbAq9vvf/z7PPvvsCe/z/e9/vxagrl69mo985CP8y7/8Czt27MB1Xf7v//2//MEf/MFxj3Pddded8GRR73nPe7j88strw//vueceCVEXIQlRhRBiGVFVhebGRhrq3sTE2AqyA/spTPSTDnSCSAMxy8TQpd/iQuPZDaTX3kp67a3ohRES/duI923HTu8nNvwMseFnaFUNCq2Xku3aTL77sqOGgJ4fkC4HjBUDxos+Y8WAA1Me9+532HrIYceIyx9cZnP5cqlKVXU8ux7PrkdxS+ilMYz8EL4RxY224Eaa8Kw6UBfPxyVVUVC1EwtcS47HwfE8mZLD2uY4jfH56xMrhBBCiLmjaRp/8Rd/wa//+q8D8Pd///d84hOfOOURrP39/bX7K1eunJNrBPjsZz9bu7969Wo+97nPnfKxLr744hPedvZQ/jvuuANFUfjABz7Ajh07autPJEQ9WVdffXUtRD148OCcH1+cfvJNWQghliFNU2lu7WbNhdeydtNmVrY10+iNU86NM5ouki25eJ50e1mI3GgLk2e/j94b/pGDW77M+IbfoBLvQvUd4oOP0/7U51lz3x20Pf23xAafQPGc2r6aqtAQUVnXoPGmToNbzzL5L5dG+PstUboSKuPFgD/dVuTvniySd5bX7z/QbdxoC068nUDVMbOHiY48Q3ToKcz0QdRyGpZYByTb0GhPRciWXF7om+LgWA7X8+f7soQQQggxB371V3+VCy+8EIBsNsvnP//5Uz7W7L6nPT09b/japo9z//331x7/3u/93hlpIXHo0CEefvjh2uM77rgDgNtvv702JP+FF16oBapzaXYLJc87wV5cYkGREFUIIZYzVSPS2E3zhmtYfd4VrGtLclYkjeUXmCo6jOXKFMruUsuOlgwn0cXEhvdzaMuXOHTD/2Ji3W040VZUr0Si7xE6nvhLVt93By3P/gPRkWfBP/qHtXObdL50c4xfWRc27r/vgMNH7suxY9g9ky9nYVAUfDOOE2vDibSgBA7WxMtEh58hMroDIzeA4hbn+yrnjKootCRsbENnz3CW3QMZsiXn+DsKIYQQYkFTFIW//Mu/rD3+4he/yODg4Ckda/aQ/B//+Me8+OKLb/j6ZgeZEPZiPRO++c1vMj010BVXXFFrTdDW1sZNN91U2252tepc2blzZ+1+d3f3nB9fnH4SogohhADdRGlcTWzNVbSsvpANTSbnxjJ0xRV8YDxfZjJXoeTIX0wXJEWhklrN+Lm/ycGbvsrh6/4nk2vfhWs3oLl5UocfoPOx/4/VP/0gzc//M/bYLgiOrDi0dYXfu9jm/3dDlLaYwnAh4L8/VOCfni1Rcpdpiq5qeFYdTqIDz0qglSexx14gNvQU1viL6IVR8JdG0By3dFriNkOZEs/3TjEwVcT3l+nvXQghhFgibr31Vq644goAisUif/VXf3VKx3n3u99du18sFtm8eTN/+7d/e8Qw/5O1ffv22v22tjZWrFhxysc6Gd/4xjdq9z/wgQ8csW7247vuugvXnbvPeYcPH+bBBx+sPb7xxhvn7NjizJEQVQghxAwzCs3r0FZcTrLtLLojFc5LFFjXZFMfN6m4PqPZMumCg7tcg7WFTlEo169nbOPv0nPznfRe8zmmVt+CaybRK2nqeu6l+9FPsupnH6Jp51ewJvccMUz9wladf3lrnLevDfui/mhvhY/+LM/usaURFp6qQLNwI004sXZ8zcDI9REZfZbo8LMY2V4UpzDfl/iG6ZpKRypCEMCu/jR7hjOU5Q8nQgghxKI2e6Kmr3zlKxw6dOikj3HDDTdw66231h6Pj4/zh3/4h3R3d7NhwwY++MEP8oUvfIEnn3zyhIPHw4cP1+6fc845J31Np+Kxxx5j3759ABiG8Zrq13e/+93E43EARkZGuO++++bs3H/wB39QG8K/YsWKI36eYvFYPDMlCCGEOHPsFLSdD8l2zMmDNGaHaIyZFJMpMhWf8VyFbMXBLfpEDJ2oqaPKn+UWHkWl1HQ+pabzGd34EaJjzxPv20Z84HGM0jj1+++mfv/dVKJt5Lo2k+3aTCW5iqih8F8vi3B1l8HfPVmkP+vzB1sL3LbB5IPnW5iacvxzL1WKgm/E8I0Y+C5aJYs9tpvAiOBEW3EjzXh2PSiL9z+IuqhJxPU4NF5gKlea78sRQgghxBtw4403cv311/Pwww9TqVT49Kc/zf/5P//npI9z11138cEPfpAf/vCHteeCIGDPnj3s2bOHb37zmwDEYjHe8Y538JGPfIQbbrjhdY83MTFRu59KpY57/n379vGP//iPx9zmAx/4QK3y9mhmD9F/29veRlNT0xHro9Eo733ve2vbff3rX5+TsPPrX/863//+92uPP/vZz2JZMqHnYiQhqhBCiKNTFIg1QaQeciMw0UOkOELEjNHcWkfe8cgUHSbyFSYKZRQgaupEDA2Wcca2YKkahZaLKbRczOiFHyM68iyJ/m3EBn+JWRiiYe93adj7XcrJlWQ7N5Pr2sxl7e185W1x/vnZEvcfdPjOSxWeGHD571dEWNdwAtO/L3WqjmfX41l1qG4BM3MII3sY327AibXj2o0E+umfIOF0sPRw0qmxdFhhe3Asz6qWJIa2eMNhIYQQp0kQwBIYkTGnjGj4WXqB+MxnPsM111wDhIHeJz/5Sc4+++yTOkY8HucHP/gB9957L//wD//A1q1b8f3XTkiZz+f5zne+w3e+8x3e+c53cuedd1JfX/+a7bLZbO1+LBY77vn7+/v5p3/6p2Nuc+mll75uiFoqlfjud79be/zqofzTPvjBD9ZC1B//+MdMTEzQ0NBw3Ot7PU8//TQf/ehHa4/f//73c/vtt5/y8cT8khBVCCHEsakaJNvDQDU7CBM9qNk+EpE6EvUJWlI2uZLLVKHCVMFhLF9CU1Rilo6pS+CyEAWaQb79CvLtV6C4JWJDT5Lo20Z05GmszCGszDdpeumblOrXke3czB9feC3XdCX5+6dKHEz7fOL+PLefa3L7eRa6unC+IMybI6pTHbRyBrs4hq9HcWJteJEWPCu56KpTVUWhKWGRA14ZzZF3Ata0xEnaxnxfmhBCiIXEKcBfd8z3VSwsfzIA5vGDwTPl6quv5m1vexv33XcfnufxZ3/2Z9x1112ndKxbbrmFW265hdHRUR5++GEee+wxnnnmGZ577jlyudwR2/7Hf/wH1157LY8//jiJROKIdbMf5/P5U7qWk3H33XczNTUFQF1d3etWmF5//fV0dXXR19dHpVLh29/+Nv/5P//nUzpnT08Pt956K6VSOLLnggsu4Mtf/vIpHUssDIvr07wQQoj5oxlQtwK6L4fmc8BzIN2P4ZWojxqsbopxbkeSs1uS1EVNihWP0VyJbNHF9aR/6kIV6Da5rs0MXvk/6HnrvzF80SfIN19EgIo9uZfmXV9l9c9+i9sO/n/86PztvK2ziBfAN3dX+MT9eXqmpGfmEVQDL9KIE2snUHWs9AEiw08TGX0ePT+I4pXn+wpPSUvcYiRb5vneKfpl0ikhhBBi0fnMZz6DUq2O/c53vnPETPGnorm5mdtuu42///u/Z9u2bUxOTrJ9+3Z++7d/G12fqdfbvXs3f/qnf/qa/WdXd6bT6eOe7/rrrycIgtcsK1euPKHrnT2U/7bbbnvd4fSqqvIbv/EbR93vZAwODnLTTTcxNDQEwJo1a/jpT39KMpk8peOJhUEqUYUQQpwcIwLNZ0OiFaYOQ7oPilMQa8TSTay4SWPMpOC4ZEsuY7kymaKDj8/MOP+gej+AQKk9rVTvKIQjoBTCdeHj6tqZzWe2O2KdgqKA+up9lQU1qmpB8s04mZVvIbPyLWilSeIDj5Lo205k4kWiYztZNbaTf1Y0els28aWpK/iPyUv42M99PrjR4rb1JppUpc5QFHwzjm/GUbwKWnkSozCMZyRwYm24kSZ8M7lo3pS6ptKeMkkXHXb3p0kXKqxpjmMb0tZBCCGWPSMaVl6KGUZ0vq/gNS6++GLe85738IMf/ADf9/nUpz7Fj370ozk7vq7rXHPNNVxzzTV8+MMf5uabb65Vpn7lK1/h85//PJFIpLb97PDzpZdemrPrOJqhoSF+/vOf1x7fcccdx9z+Ax/4AJ///OcBePLJJ3n55ZfZsGHDCZ9vfHycm266if379wPQ3t7OAw88QHt7+ylcvVhIJEQVQghxauwktJ4HyQ6Y6IHcEKg6RBtQVJ2YGS7NcZt82cXxfYIAAgIIwA8CpmvZgiBc/OpflL0gqD32g9nrw2N41dnkAz88nl/dHsAn3IZget30/bD5/Uy/1ukgd9bDadUwVp2+Xw1pa2EsYGgqlrF0B3R4dj3pNbeSXnMremGERP824n3bsdP7WZF5hs+qz/AXtsH93kX8x86r+KPeS/ivVybpSkqo9mqBZuJGmiDwUZ0c1tQ+zMwhXLsBN9aGZzcQaOZ8X+YJSUUMbEPl8HiBTMllbXOc5oRMjCCEEMuaoiyooevi9X3605/mRz/6Eb7vc/fdd/PUU09x2WWXzfl5rrrqKv7kT/6EP/mTPwHCfqRPPfUUmzdvrm1z7bXX8q//+q9AGHIePnyYFStWzPm1APzbv/0bnjczeuq66647qf2//vWv89nPfvaEts1kMtx8883s3r0bgKamJh544AFWr159UucUC5OEqEIIIU6dokC0Aew6yI/AxEHIDIEZDSekUhQ0FZKR0/PPTS1cpRrI1oLYMDANqK6r9rz3q+vDfasBLTOB7fQxPX8mzPX9AK96Hi/wCfwwxC04LiVHIRUxlvxEWm60hcmz38fk2e/DyPaS6NtGon8bZq6ft2tP8nbtSbL5CA88cCljq67jggsvQdWkb+ZrKCq+mcQ3kyhuCb00FlanmgncWAdupBHfTBz/OPPM0jU66iKM5yu80D/FqoYYKxqjMumUEEIIscCdd9553H777fzbv/0bAP/jf/wPfvazn52Wc731rW+thagQDm+f7frrrz/i8be//W3+8A//8LRcy6kOyZ/2b//2b/zVX/0Vqnrszzr5fJ5bbrmFZ555BoBUKsVPf/pTzj333Dd0frFwSIgqhBDijVNVSLRBtBGyQzBxIBzmH6kD6/SFQmFVqI8a+GHKqRmcqURzsuBweDzPWK5MQ8ziOJ+plgwn0c3EOb/BxIbbsdIHiPc9QqxvG4nSGO9RtsPh7aR7E+Q7r8FbdR2lxnMX3YRKZ0Kg27i6DYGHVslhT7yMr1u4kWbcaAuu3RhO6rZAKYpCU9yiUHHZN5IlU3JY0xwP/6gghBBCiAXrz//8z/n2t7+N67r8/Oc/Z9u2baflPLZtH/H41T1IV61axVve8pbaMPsvf/nLfOITn3jNfm/Us88+y65du2qPL7vssuOGodOeeeYZXNelr6+PrVu3ctNNN73utqVSiXe+85384he/ACAajXLPPfdwySWXvLEXIBYUCVGFEELMHc2Aum6INUOmHyYPwVQfxBpmekMFAQRe9dZ/1f1jLVDro6oo1MbsK1q1r6QCXgV0KwxujcjrXuZcqI8aWHqC3okC4/kyqYiBqS+jsFBRKNetpVy3lvHzfgtr/CXGX3yYFeO/oJEMqb77oO8+HLuJYssmSvXrKNWvo5xcFbZ9ECFFw7NSeFYKxS2i5wcxcv24kSacRBeu3bSgw9SoqWPpWjiJXMllTXOMjlQEVfrjCiGEEAvS2rVr+dCHPsRXvvIVIKxGffOb3zzn53n++eePeHy0ofqf/OQnayFqT08Pn/zkJ/mHf/iHOb2O2VWoGzdu5MknnzzhfW+99VZ+8pOf1I7zeiGq4zi8973v5cEHHwTCwPjuu+/m6quvfgNXLhYi+RYjhBBi7hk2NK6FeAtMHoZMHxQmw3WKAqhh9ary6kUD1QRNB9UIQ1lVD28VNQyTFG3WfXXmPkApE1bClqYgPxZeh5UAfW7/oj0tamrVyXWKDKSL2LpG3F6G/7QqKuWm84hvPo9d6f/E/Y8/zQW5R3mr9hTJ0hjG4QdIHn4AAF81KdedFYaqDesp1a/HjTQvmgmWTqdAj+DqEfBd9NIkenEMN9qCE+8Me6ou0IpeTVVoS0Zqk05lig6rm+JEzIUb/gohhBDL2ac+9Sm+8Y1vUC6X2b59O47jHHP7v/u7v+OCCy7gxhtvPKHjFwoF/vqv/7r2uLW1lU2bNr1mu+uuu44PfehDfO1rXwPgH//xH0kkEvzlX/7lib+YY3Ach7vuuqv2+HgTSr3aHXfcUQtRf/jDH5LNZkkkjhxl53ket99+O/feey8QTrD13e9+94R/VmJxWYbf9IQQQpwxVgLazoNUB7iVo4eftfB0+v4bCNPsFKS6oJKD4tRMoJobA8M6LYGqoSmsaIgSMTV6JwpM5irUxcxlmwl2pAzueMuV/GDvxbzphRyXsYuL1X1sUvazSd1P0i8QmXiRyMSLEE5YSkZN0W+fzXh8HbnUOtzGs0nEEtTbChFjGf4gVR032gy+g14aRy+O4ERacRJdeHbDgg1TUxGDiKFxeKJIplqV2hy3UJbrfwxCCCHEAtXd3c1HPvIRvvCFLwDwy1/+8pjbP/nkk/y3//bfuPTSS/nQhz7Ee9/7XlpbW4+67RNPPMHv//7vs3Pnztpzf/RHf/S6Q+g/97nPsXfv3tow+M985jPcf//9fOpTn+Kmm27CNI8++eZLL73EP/7jP9LX1/e6133vvfcyNjYGhK2I3v/+9x/zdb7aO9/5ThKJBNlslkKhwPe+9z1++7d/u7Y+CAI+/OEP8+///u8AqKrKN7/5Td75znee1HnE4iEhqhBCiNMvUn/mzqUoYVhqJcJAtZwNg9TsUBisuqPVCtVkOPR/jk7ZkrCwdY1DE3lGcyUaoha6tjzDI01VuG2DxeXtOne9eBn35S7lrpLPVMmj0x+sBqqvcKG6n3OUwyT9NMnC01B4GkbA36uwP+hgh7+WXcpZ9BhnMWGvIhXRqbMV6m2FBlut3a+31TBw1VlagZ1q4EZbUDwHvTiKXhzFjTTjJLqrYerCe62mrtKRspnIV3ihL82qxiiddVGpShVCCCEWmD/5kz/hq1/9KoVC4YT3efrpp3n66af52Mc+xtq1aznvvPNoampC13VGR0fZsWMHPT09R+zznve8h49//OOve0zTNPnZz37G7/zO7/Dtb38bCIPYd7zjHUSjUS677DLa29upq6ujVCoxOjrK7t27OXjw4BHHWbt2LRdddNERz80eyr9582a6u7tP+LUCRCIR3vOe9/CNb3yjdrzZIeqXvvSlI86xdu1aHn30UR599NETOv4Xv/jFk7oeMf8kRBVCCLF0KQrYyXBJdc8KVAehmAavHFamWok5CVSTEZ2zWxL0ThYYzZZI2Aa2sXzDo5UpjT9+U7T2OAgCim6KydJ6Jks+T5cCHiqUsDP7aczto7O4j9XOPtoY5Wyln7PVfm5jG/hQzJvszK3meX8tO/yzeMhfSz9NzJ5IzNagzlboTKhc3KpzSZvO6joVdQGGjScj0AzcWCuKV5kJU6OtYZhq1S24MFVRFBqrk069MpKnf6pIyjZpjJskbJ2YpWNoC7OaVgghhFguWltb+cQnPsHnPve54267ZcsWnnzyySMC0v3797N///7X3ScSifDHf/zH/PEf/zG6fuzoKRKJ8K1vfYt3v/vdfPrTn+bFF18EwrYAjzzyyDH3XbduHR/96Ef52Mc+dkTV6vj4OPfcc0/t8ckO5Z+933SIun37dnp6eli9ejUAIyMjR2y7b98+9u3bd8LHlhB18ZEQVQghxPJwtEC1OAm5aoWqV5mTQNU2VFY3xbB1jYGpIo4bkIjIP7cQhmtRA6JGGHSGDGBTdYEsUChNYk/uRRvfgzGxl3h6LxGvwOXKHi5X99SON6Gk2BWcxTPeWp7yzuIFbw1D+ShDeY9nhjy+8nyZOkvhkjadS9o0Lm7TaYws3vAu0MxqmFpGLwzNhKnxLjwrteDC1KipEzE0io7HVKHCcLaEpihETI2GmEl91CRu60QNTSaiEkIIIebBH/7hH/KlL32JdDp9zO1+93d/l9/93d9l165dPPLII/zyl7/k5Zdf5tChQ6TTaYIgIJFI0NbWxgUXXMANN9zAbbfdRn39yY1G+7Vf+zVuu+02HnnkER544AG2bdtGf38/4+PjFItFkskkDQ0NnHPOOVx22WXceOONXHnllUc91re+9S0qlQoQTvT0vve976SuZdqb3/xm2tvbGRwcJAgCvv71r/Pnf/7np3QssfgpQRAE830R4tRkMhlSqRRjY2M0NjbO9+UIIcTiFARQzlR7qA5CKR32bzUjYMZPOVANAhjPV+idKFB2PeqjFq/TCkocT+Bj5PqxJ/diT+7BntiDlTmIEnhHboZCNtLFAWsDP3cv4q6pc5hyj/z9rUqp1VBVZ2Ozhq0v3vBOcUvopUkC1cCJteHEO/Ctujk9h++5HNzxKKs2XYOqvfE/BrieT9HxKFQ8PN/H1FVilk5z3CIRMYhb+rKu3hZCiPlWKpVqlXa2fXom5hRimu/7ZDIZksnk6/ZMFeJ45uL/t6bztXQ6TTKZfN3tpDRGCCHE8qYo4YRUdgrqVsxZoKoo0BQ3sQyV3vEC4/kS9RELfRGHdvNGUXES3TiJbrIrtoRPeWWsqf1hqDq5F3tiD0ZxhGSxl03FXjZxP/+vaTLUvInHtYv5Xn4TT0wmOZj2OZiu8P09FQwVzm8OK1QvbdNZs8iG/ge6jRNvR3FLmNlejMIQTqwjDFPN1//wN590TSWhqSRsA4CyGwaqe0dyAEQMjVTECIf+WwYxS0OXof9CCCGEEGIBkBBVCCGEmDY7UE11h4FqaQoyg9Uh/04YqFoJ0I4+U+irJSydtS1x+icLDGVKxE2DiCWVdm9UoFmUGs+l1Hhu7Tmt2gYgOvIssaEnMYqjdEw+yXt5kvcC+dZ1vBS9lPvci/nxWAcjRXhu2OO5YY//Ux36f1GrVqtUbYoujvBuJkwtYmYOYeQHcWKdOPF2fDMx35d3TJauYeka9YAfBJQcj4l8haFMEU1RiZk6DXGDuqhJ3NKJmtrSmjxMCCGEEEIsGjKcfxGT4fxCCHGG+P6RgWopDb4DihZWp+p2eKu+fjjq+zCcLdE3WQAU6iLG7DmRxFwLAsxMD/HBJ4gNPYk9dWSTfyfSwlDjZTyuXsrd2fU8OwpF98hDrEyGQ/8vbtO4oEUnskiqiFWngFaeItBtKrEO3HgnvhE7pWPN9XD+k+F4PsWKR8Hx8AMfS9eIWzpNcZOEbRC3dSxd/iAhhBBzSYbzizNJhvOLuSDD+YUQQoiFRFUhUhcuqRVQTkM5F05OVUqDUwxvAw8UtRqsWqBZoBm1Q7SnbGxDo3ciz1iuTENM+qSeNopCJbWGidQaJja8H604Tmz4KWKDTxAdfR6jOEJ33z10cw/v1aPkVlzM3til/KxyIY+ORtgz4XMo43MoU+EHe8FQ4bymcOj/JW06Z9Uv3KH/vhHFN6KoTh5r6gBmfohKvBMn1k5gROf78k6YoakYEZVkxCAIAsquT6HssTcfDv2PmhqpqEFDzCJu6cQtHU0mqBJCCCGEEKeJhKhCCCHEyVBViNSHC4QzSLllcAphmFrJhxWrlXwYtPouoIBugm5Tb5pYLQl6JwqM58ukIgamLknq6eZFGsmseiuZVW9FcUtER58nNhRWqerlKVIDj3IZj3KpolJsOJfxTZfzS+0SHpps4Zkhl+FCwI4Rjx0jHv/6Qjj0/4aVBm9bY7C6bmFWQ/pGDN+IoVZy2JP7MHL9YW/ZWBuBHpnvyzspiqJgG1pt0inPD4f+j2YqDEyV0DWFmKnT3RClLWlLmCqEEEIIIeachKhCCCHEG6EoYNjhMptbmQlWnWIYrFYrV6OewxozIOZ4DGV8HCtKLBoNjyVOu0C3ybdfQb79Cgh8rMl9xKuBqpU5SHR8F9HxXXTzr7wr3kVuzeUcTF3GQ8WzeHo44Plhl6lywA/3Vvjh3gobGjXetsbg+hUGUWPh/Q59M07FiKE6OayJlzGyfVQSK3BjrQT64hyqqakKMUsnZoUfZR3PJ1dy2dk3xVgqwqqmGKmIMc9XKYQQQgghlhIJUYUQQojTQTfDJVI385zn1oJVwy3SWZzCGh9lcGyKfH6cVEQHVSPQLXzNIlDNY/ZZFXNAUSk3rKfcsJ7xcz+Inh8mNvQk8aEniIztxMz10fBKHw38gAvNJPnWS8lceTmPBhfwk0M6j/e7vDzu8fK4x5eeK3H9irA69ZzGBTYBkqLgmwl8I47qZLEnXsLPHiLQLHw9gq/bBLpNoBrVRSdQTZRF0jnf0FTqYyZxT2c4U2KqUGFlY5SOuqhUegshhBBCiDkhE0stYjKxlBBCLAG+z2R6ip6hMTKZLC1mGcvNoXol8CoogR9upzAr3JoJulAkIDpdVCdPdORZYoNPEBt+Gs3J1db5qkGu81p6u97OjyZWcd8Bh76sX1u/KqXy1jUGN64ySFkL8HcUBKhuAcV3wHdRfHfmvYZCoKig6riBxoujPus7k6hmjEAPw/3pkDVQdQItfD8upPdiruSSLlVoilusborRGLfm+5KEEGJRkImlxJkkE0uJuXAmJ5aSEHURkxBVCCGWjmLF45WRHAPpAnW2QUzzULwSqueg+BUUt4zq5FDdIopXQQkcFM8BAsLQSwmDVW1WwKrKcOY543tEJl4MA9WhJzDzg7VVxfr1TK15B780ruTeg7Ct16HshesMFa7q1HnbWpOLWrUFOxnVa/geSuDiuw4vDVU4tylAVzyU6R6/QIACmk6g6NUw1Q6rqPXoEe9Fz0zMy3vR8wPGc2VQobsuyorGaK2nqhBCiKOTEFWcSRKiirlwJkNUGc4vhBBCLAARU+Oc9gRRU6NnLE9ZU6mP1eG/esMgQPGdcPEqKF65GrKWUJ08qltEc0u16sLqTq+pYA00AxQJlE6YqlFs2kixaSNj538Ya3IvdQd+QqJ/O5HJPUSe2cOtVh2bV72NgXPfyv3DCe47UGHfpM8jvS6P9Lq0xRRuXm1y8xqD5ugC/6KgagRo+IoJVPAiDfDqyZoCP3yP+S5K4KI6WZTyBErggc901ooTbaVcv47AiJ7Rl6CpCi1Jm2LF48BYjol8hdXNMZrjFqpMPCWEEEIIIU6SVKIuYlKJKoQQS08QBIxky+wbyZEvuygEhP9QK6iKgqYoaOqsRVHQteo6VQmDLa8SBqteBcV3UL1yGLBW8tUAtgK+gxIEEECgabiRRglVT4FWmiR18KekDt6HXpoAIFA0ch1XM7XmVnYpZ3Nfj8PWgw55J9xHVeDSNp23rTW4skNHX8CBnucH7OmdZH13/anNeO97GIVhPKuBUsN6fCs19xd5AoIgYCJfwfF92qsTT8UtqSUQQohXk0pUcSZJJaqYC1KJKoQQQixTiqLQmrRJ2DrFiofnBzh+gOcFVDyPkuNR8XwqboDrh8/5lQDPBy8IqqGrAhioijkTshoKWlxBx8MIHLTARQ/CoFUvjGDmhqjEWqQFwEny7HomNryfiXW3ER94jLoDPyEy8SKJ/m0k+rfRnFrLxWvewUfO38y2QYX79ju8MOrx5KDLk4MudZbCW1aHk1F1JZdgiK1qOLE29MIIkbGdlOvX40abz/hlKIpCY9yi4vr0TxWYLFRY3RSjLWmja/KlTQghhBBCHJ+EqEIIIcQCFDV1oubr/zMdBAGeHwapbjVkdX3/iMdl16suYejqBQEVHzxfx/d1vMBCARQ9TlIJSEwM4MebMcwoUgxwklSdXNdmcl2bsab2kzrwExJ9j2Cn92M/9480mV+jfeVbeOubbuGg28hPexx+3uMwWQr47ssVvvtyhY3NGm9bY3Btt4GtL9zq1JOmqLixNrTiGPb4Lsr+OpxYB8xDf1hTV+lIRUkXHXb1ZxjLllnVFKMuap7xaxFCCCGEEIuLDOdfxGQ4vxBCiBMVBNVwdTp49fza44rrkysUqQzvRZ/qoajFcbQIKAqGqmJoCoamYmhqrc+lOD61kiF18Oekeu7BKI4CEKCSb7+SqTXvINtwPk8Mevz0gMOTgy5+9RNZRA+H+1/RoXN5h069PX+J9hsezv8qajmN6happNZSSa4Cdf6qb13PZzxfQVcVVjRG6aqPYury1wMhxPI2PSx21apVRCKR+b4cscTJcH4xF4rFIgcPHpTh/EIIIYSYG4qiVMPQ19mgIUrQcTmV0Sac4ZcpE1DSYuQrHsWKS6Hi4fgOQRCgKSqGXg1XVRVNk2T1aHwzyeS69zF59nuIDT5J3YEfEx17gfjgY8QHH6OcXEnD6ndwzVU3MFqJ87Meh58eqDCUD9je57K9L5wYbEODyhUdBld06JxVr6LMQwXnXPGtFKgG9tQ+FK9CpW4tgTY/VaC6ptKatMmVXfYMZRnPV1jVGKMpbi7qn7EQQrwR00GW779makshhFiQpv//6kwE8VKJuohJJaoQQog5FwSQ7oPRl4EAYs14PlSqbQHKrkfR8ciXPSquT8Xz8YNwKnZdVTFUpRqwqvMxWnvBMzOHSPXcQ/Lwg6heCQDPiJFZcRNTa95BJdrKvgmfJwYcfjngsm/yyC+xjRGFK9rDKtWL2nQip3nY/1xXok5TvDJ6YRwn1ka5YT2BPr/VTp4fTjzlBwFd9RFWNsaImEuwR60QQhyH7/vs3buX5uZm+Y4pTjupRBVzYXx8nNHRUdatW3fK76MTrUSVEHURkxBVCCHEaZMbgeEXwSlCovWo/Ssrnl/ttxouubJLsexR8X0czycgQEXF1FT0atWqrinSEgBQKzmSh7eS6vkJZn4QgACFQuulTK15B4WWTaBojBd9nhxweWLA5Zlhl5I7cwxDhU2tGpe3G1zZodMWn/svH6crRAXAdzEKI3hWA6WG9WGV6jwrOR7juTKpqMHqpjgtCQt1rl+3EEIscH19fTiOw+rVq+f7UsQSJyGqmAs9PT0YhkFXV9cpH0NC1GVAQlQhhBCnVXEShndDcQoSbSfUv9L3oex5VNxwYquS45EruZQ9v9aHdTpc1dWwxYCuLePK1cAnOvwMdT0/ITb8TO1pJ9JEtvsGMt1bcBLhB8KKF/DCiMcTAy6/HHAYyh/5EW5VSuXydp0rO3TObdLmJPQ8rSEqQOBjFEbw9RilhvV4kaa5P8fJXlIQMFVwKLoenXURVjZGSdjGfF+WEEKcMZlMhv7+flasWEEsFpvvyxFLmISo4o3K5/McPnyYzs7OY4afxyMh6jIgIaoQQojTrpyDkZcgOxgGqdqphUmOH+BMV616PmXHo1DxKTkujhfgzOq9NrstgK6qLJfP1Eaun9SBe0j2Pojm5GrPF+vXk12xhWznZnwzDoRB3+GMXw1UXXaPebWJqQASZjg51ZUdBpe26yStUwtAT3uIWqUXxwCFcv16nFj7USufzzTH8xnNlomYGqsao3TURdC1ZfJmFEIsa77v09fXR6FQoLu7W4JUcdpIiCreiHw+T29vL9FolK6urjf0HpIQdRmQEFUIIcQZ4ZRgdA9MHYJ4M+inNuvl0Xg+VKqVqxXPo+L4FByPYtnD8X1cL8DHhyDsuaprSq01wFKd0ErxHGJDT5A4vJXYyDMoQRgw+6pBvv1KMiu2UGi+6IjK4Gwl4OnBcNj/k4Mu2crMxztVgXMbNa7oDKtUVyZPfHKqMxWiAmjlNIpbolJ3FpXEihOqfD4TMkWHbNmhNWnTkrSxdBVLV7ENDUNCVSHEEjUdpObzeWzbJplMYts2qrq4JzgUC4vv++RyOeLxuISo4riCIMD3fUqlEplMhlKpRCwWe8MBKkiIuixIiCqEEOKM8RwYfwXG90MkBdWKyNPF98Oeq44XVq5WXJ982aXoeGHlqufj+QGKEqChouth9ape7b+6VGilSRJ9D5M8vBUrc7D2vGvVk+m+geyKLVSSK4/Yx/MDXhoPh/0/MeDSkz5ycqrWqMIVnTpv6jDY1KqhHyMcPZMhKoDqFNDKaSqJFVTq1hJo5mk/54nw/IDxfBnXDydRMzQFUwuD1IStEzV1LCN8bOlhH2AJGYQQi910wJXJZMjlckh0IOZaEAQUi0UikYj8uylOmKIoxONxksnknAXwEqIuAxKiCiGEOKN8HyYPwtgeMGyw6874JQRBGK5WPD9sD+D5FCsehYpHxfWr1as+EUMnbutn/PpOmyDASh8gcfgBEn2PoFcytVWlurPJrHgz2a7r8M3Xfugbzvu1QPW5YRdnVqaaMOGqToPN3ToXteoYrwqgz3SICqB4ZfTCOE6sjXLDegI9ckbOe6KCIMD1A8ruzHvQq/b6NaoBqqmpJGyduGVgGyqWrmEZYQWrfEkUQixGvu/jui6+7x9/YyFOkOM4bNu2jc2bN2MY0n9cHJ+qqui6PueVyxKiLgMSogohhDjjggDSfTD6MhBArHm+r6hmOlwtlD36J4uUHI+6qLmkKlMB8B1iQ0+T7N1KbOgplMADIFB08m2Xk1mxhXzrJaC+NkQuugE7hsNA9Rd9LlPlmY+BMSMMVK/t1rmkTcfUlHkJUQHwXYz8CJ7dQKlxw1HD4YXIma6eroar05WrmqJg6AqWrhGzNBKWjm3oYWuAash6Rn++QgghxALgOA733nsvt9xyi4SoYl5JiLoMSIgqhBBi3uRGYPhFcIqQaF0QEwHNlq+49E+WGMuViJsGEWth9Neca1o5TbzvEZKHt2Kn99eed606sl3XkVmxhUpqzVH39fyAXaMe2/ocHu11mSjNfCSM6vCmToOruzQSTo6Nq85wiAoQ+BiFEXw9RqlhPV6k6cyefw55flALVqcrphVAoRquahpRK2wNYBsathGGrZa+NN+3QgghBEiIKhYOCVGXAQlRhRBCzKviJAzvhuIUJNoWzERA01w/YDRbpn+qiO8HpCImS3nOAjN9kGTvVhK9D6GXp2rPl1JryHZvIdt9HZ5Vd9R9p/uoPtLr8mivw1hx5uOhpQZc2Wlw3QqDy9p1bP0MhqlBgF4aBxTK9etxYu0LLrB/I/ygGq66YQWr4/v4AagoREyVhG3QGDeJWzpxS0eXiayEEEIsIRKiioVCQtRlQEJUIYQQ866cg5GXIDsYBqnawvsAnCm69E0WmCo6JG0Dy1jiQZTvER15luThB4gNPYHquwAEika+9dJwuH/bZaAe/XflBwEvj3ts63XZ1uswWpj5qGhrcFmHznXdBpe360SMMxNoauU0ilukUnd2OJGWsrR/h54fUHLCXr+O76EpKlFToy5mUB81iVk6cVNHlRYAQgghFjEJUcVCISHqMiAhqhBCiAXBKcHoHpg6BPFm0O35vqLXcLyAwXSRwakSmqqQihiwDPIntZIl0beNZO9W7Mm9tec9M0mu7QpKDRsoNaynkugG5bWVxK7nc/9LUxxyIvyiz2UoP/Ox0dTgsnadzd0GV3ToxE5zoKo6ebRSmkpqFeW6ta8bAi9FrudTrIaqnu9j6CpRU6cxZpKKGMQsnaipyaRVQgghFhUJUcVCISHqMiAhqhBCiAXDc2F8H4zvh0gKzPh8X9FrBAFMFiv0TxbJllzqIyb6mRyaPs+MbC/Jw1tJ9j6IXpo4Yp2vRyjVnU2pYT2l+g2U6tfh2fVHTCylKrBv0mdbr8P2XoeB3MxHSEOFS9t1ru3SeVOnQdw8PT9XxSujF8Zx4h2U69cRLMDA/kyouGGoWnRc/AAsXSVuhaFqImIQt8LeqkIIIcRCJiGqWCgkRF0GJEQVQgixoPg+TB6EsT1g2GDXzfcVHVXJ8RmYKjCcLWPrGnH7tbPYL2mBR3T0eSKjL2BP7sWe3IvqlV6zmRNtpVi3jkNKN4nVF+HWryXQzPAQQcD+KZ/tvQ7bel36sn5tP12FS9rCQPWqLoPEXAeqvouRH8GLNFJqWI9vvv4H3eUgCALKrk+x4lF0PBQFbEMjFTFoiIX9VGOWjqkv7RYIQgghFh8JUcVCISHqMiAhqhBCiAUnCCDdB6MvAwHEmuf7io7K92E8X6ZvskjJ9aiPmGja8qlKPULgYWZ6sSdfDkPViZcxs70oHPkRMVB0ynVrKNWvD5eG9TjRNgLgYDqsUN3W63I4MxOoGiq882yT3zjPmtswNfAx8sP4RoJSw3q8iHwOmuYHYT/VYsWj5ProqoJtatRHDOpiM5NUadJPVQghxDyTEFUsFBKiApVKhe985zt861vfYvfu3QwPD1NfX8/q1av5lV/5FX7rt36LpqamOTvfnXfeyYc+9KGT2ufDH/4wX/3qV0/pfBKiCiGEWLByIzD8IjhFSLQu2BnV8xWX/skS4/kSMdMgYsoQaADVKWBN7cUafxl3YDfNpQPolfRrtnPNJOX69RQb1lOuX0+pfh09Bbs2KdXBdBioJkyFO84zufUsE2OuwuogQC+OgapRql+PG21bsO+z+eT5AcWKR8Fxcb0AXVeI6joNcYPGuEV91JRAVQghxLyQEFUsFCcaoi7Z8Wsvv/wy73//+9mxY8cRzw8NDTE0NMTjjz/O3/7t3/K1r32NW265ZX4uUgghhFiq4i2gGTC8O6xM1XTQTNAt0Kxw3QIQM3XWNMeIWxoDUyWKFY+6qIm6zEc++0aUYvMmco0XsicyyfquOqzSCPbkHuyJPdiTe7DS+9ErGfThp4gNPwVAgEJXoovL6tfzsQ3redpfz9/ubeFg2udLz5X5j1cc/tOFFm/q1N/4JEiKghttRitPYY/tolJXxom1EqgGqEv2I+5J01SFuK3X2lY4nk+h4nF4osDhiQJ1UZP2lE1jzJI/IgghhBBCHMOS/ITZ19fHli1bGBgYAEBRFDZv3szatWsZHR3lgQceoFgsMjIywrvf/W5++tOf8uY3v3lOr2HDhg1s2bLluNtdddVVc3peIYQQYsGI1EPHRZAfg0oeSmlwS1DOg++G26hqGKrqVhiyzkO4qqsKHXUR4pZB32SB8XyJpG1iGcs8SZ1NUXBjbeRibeS6rguf8hzM9AHsyT1EJvdgTezBLAxhZXuxsr2kDj/A24FrO67h26t/m39+KUJ/1ufPHi1yQbPGRy+yObvhjYd2nlWHquaxJ17CzPQQqCaBauAbUXw9SqBbBKpBoJr4mkmgGaAujBB/PhiaSiqikooYuJ5PpuSyqz9NzNJpTdi0JC2StoEq1alCCCGEEEdYkiHq7bffXgtQV65cyd13382FF15YWz82Nsav//qvs3XrVhzH4bbbbmP//v3U1dXN2TVcccUVfPGLX5yz4wkhhBCLkhkLl2luBdwiOKVqoJqDciZ8XM6F4WoQhJWr08Gqbp2RysJkROcsM85QusTgVImSo5CKGCBZ0lEFmkG5YT3lhvVMD/TXylPVStW92JMvExnbSXLgUT48uoObN/0OX0pfzff3Orww6vGxn+e5cZXBhy6waI6+scDaN2JUdBvFc1B8F8UrojtZlMCFQAECAkUB1agGqga+HsE3YgSaRaCFIWugmbX1y6E1gK6pNMRMgsAgX/HoGc9zeLJAY8ykPRWhPmZg6VKdKoQQQggBSzBEvffee9m+fTsApmny4x//mI0bNx6xTVNTE3fffTcXXHABBw4cYGJigr/5m7/hr//6r+fjkoUQQojlQzfDxU4d+bxbDkNVpxSGrOXpytUylLPge+F2qjbTEkA35zxcNTWV7voocUunf7LIaK5MfcRE15d+oDYXPKuOfPsV5NuvAMCaeoWW576AnT7Ayuf/gU+1PML73vyf+dK+OrYecrj/oMO2Xof3bTD5tQ0WEeMN/JwVjUDXeN1m/4EXBqy+i+KX0Ut5KAyh+AEoYSsCNJ1AMQi0V4WsqhEGrJqFr52ZUP9MUhSlNuFUxfWZzDsMZ8okbJ2OlE1jwiJhzUELBiGEEEKIRWxpfQIE/umf/ql2/zd/8zdfE6BOi8VifPrTn+aOO+4A4F/+5V/49Kc/ja4vuR+JEEIIsfDp1SH9s8PVIACvEk5O5c6qXK2Fq5mZcFXTq71WzTccrioKNMRMIqbG4FSR4WwZW9dqPSXFiSvXnUXvdX9H/Ss/pOHlu4iNPMfF47/P5875IL88+218eYfD7jGP/7u7wn37HX5ro8VbVhunZ6IjRSPQNALNOvr6wJ8VsjpopQJ6YRglCIAAUKqVqia+HsGzkgR6BF+zwnBVt5dEmwBTV2lOWPhBQLbksmc4hzWepzFu0ZayaYia6Jq0uhBCCCHE8rOkvg3kcjm2bt1ae/yhD33omNu/973v5aMf/Si5XI6JiQm2bds2571RhRBCCHGKFGUmXJ0tCGYqV91SGLKWc1CuhqulDAQe4Tj8IDyOqodVrKr+quX1hypHDI1VjXHitkH/ZJGxalWqNlezyy8Xqs7kutvIdVxFy3P/i+j4Lpp3fYUb67ex8bKP82Cmk6/sKDGYD/i7p0r8aF+Fj2yyubjtDH9MVdRqtal59PWBj+I7KJ6D6mTQSmPVgJWZSlXdxjMS+Ea0FqyGlazmomsPoCphO4tUxKDkeIxkygylSyQjBp11ERpiJjFrSX2VEEIIIYQ4piX1yeexxx6jXC4DYaXpZZdddsztbdvmTW96E/fffz8ADz74oISoQgghxEKnKGDY4TLb7HDVc8B3wttaH9ZCWNnqOhAUw3WBf+RxXxWyqqpGS0wnasXpnygyni8TtwyZxfwUOPFO+q/5a5IHf0bT7q8RmdzDyof/K+9adxtX3nwbdx8I+L+7yxyY8vmjhwtc0aHzuxdarEwtkJ+1olb7p7421A/7sJZRnDxGaRIl8CEIqr1WjTBQNeN4RpxAt6vVq2HAuhjCVdvQsA0Nzw/IlBx2D6SJmBotCYvWZIS6iExEJYQQQoilb0mFqC+99FLt/saNG09oaP7FF19cC1Fn7/9GTU1N8b3vfY/du3eTTqdJJpN0dHTwpje9iY0bN0pPKSGEEGKuvV64Opvvz4SrvgOeW72tzApbi9XH5XCiK98lHvistXzqnDJDGYccGvFEHVjRM/bylgRFJbP6beTbLqPl+S8RH3qCxj3fIj7wC+646BO8ZfU6vrm7wo/3VXhiwOWpQZe3rzX44PkWdfYCHUKuKGFYqh1lKL/voHpO2IM1n8Wotp8IFBU0E1818c0EvhGvVa1O36IsvNerqQr1UZP6qEmh4tI3WaR/skRd1KCjWp1qGwsk9BZCCCGEmGNLKkTds2dP7f7KlStPaJ8VK1bU7r/88stzdi133303d99991HXnX322fzRH/0Rv/3bvy1hqhBCCHEmqSqoR2kR8Gqzw1avAr6L7jm0+g5WNk/fyBhTU8NEMqOYiSYUO3Zmrn+J8CJNDF7xP4gPPErzC/+ClT1M17b/TnzNO/j9Cz7Iu86K8ZXnyzzW7/LjVxy2HnK4/VyL96wzMRdTOwXVwFcN4FVhu++h+BVUrxL2XfX7AAhQQQ/DVc+qwzeT+EYMX48Q6Mf448A8iJo6UVPH8XwyRYcX+qaIWzptKZvmuE0yIhNRCSGEEGJpWVIh6vj4eO1+a2vrCe3T1tZWuz8xMTHn13Q0+/bt43d+53f40Y9+xLe//W1iMfniJYQQQiwoxwhb6+oh2uEzPj7G2MABMuO9GJlR7EQzakT+TT9hikKu81oKzRfSvPOrJHsfpP7Aj4kPPkFk08f4i2sv4flhly/vKPHKpM9Xny/zk1cqfPhCm+u6F3lAp2oEagRPjxz5fOCheA6KV8bID6BkewlQQLfxjBie3YBvRPH1cDlWT98zxdBUGuMWQRCQK7vsH81xaKJAUyyciCoVMbB0dXH/voQQQgghWGIhai6Xq92PRCLH2HLG7O1m73+qVqxYwW233caWLVvYuHEjzc3NeJ5HX18fW7du5Qtf+EKt4vUnP/kJt99+Oz/84Q9R1eMP2SqXy7WerwCZTAYAx3FwHOcNX7sQQgghTowCNDXUU193MZOTK5kYPER2ohclM4YZa8CIxuf7EueE5wdH3J6Wc+gJBi76f0h3Xkfb8/+EURyh8/E/I911Axec/zt84cYEWw+53LmzzFA+4K8eK/L9RpX/dKHNuU3zHyLOrWp4r1ow3R0g8FDdMko5i54fRQF8zcTXLHwriWek8I0IwQKoVo0ZCjHDpOx6jKbzDE7msA0VQ9OIWRpxU8c2NUxdxdJVTE1F1xZe2wIhhBBnxnSOIXmGmG8n+h5UgiA4fZ+Kz7AtW7bw4IMPAvCpT32KT3/608fd58EHH2TLli0AaJqG67qnfP6pqSmSyeQxA9FKpcJHP/pRvva1r9We++Y3v8kdd9xx3OP/+Z//OX/xF3/xmufvuusuolHpySaEEEKIxU3zSpwz+O+sGb0fhYCynuCFrg8wUHcFZV/hoQGFrQMqFT+saryo0efWFT6NC2ukuxBCCCGEWEQKhQK33357bU6j17OkQtS3v/3t3HvvvQD80R/9EZ/73OeOu899993HLbfcAkA8HiebzZ7WawTwfZ/rr7+e7du3A3D++eezc+fO4+53tErU7u5uBgcHaWxsPG3XK4QQQogTl01PMDV0kOxoL065iBZtwI4lFsMk7K/h+QGv9E9xVmcd2hmcfd2eeJn257+Ale0FINt6OcMX/B5upInxos/Xd1W4v8chAAwV3n22ya+fYxIzF+EPeS5MV6t6ZVQ3/KwYqAa+vvCqVQH8IMDxfBw3vK14Pl71K4muKpiaiqGrxC2NuGVg6hqWroTVq7p2Rt+LQgghTh/Hcbj//vu56aabMIyjTNAoxBmSyWRoamo6boi6pIbzx+MzQ+eKxeIJ7TN7u9n7n06qqvJnf/Zn3HjjjQDs2rWLvr4+urq6jrmfZVlY1mt7sxmGIf+HI4QQQiwQDU2tNDS1UsysY3JwP+nhQxRHxyHaSDSWQFtMEyNVaapyRoMrp+kceq//AvV7v0vD3u+RGH6S6EM7GT/vQ2ir3sp/vyLCe9aZ/O8dJZ4b9vjengo/7amwZZXJ29YYrKlbasP8j0cHTQdi+NVnFK+C5pUwisOouX4CRSHQI/hGFNeqDyesMuL4RhSUMzukXgV0HSJHmd/NrYaqjhcwlvcZzBZRAAUFQw8D1qipE7c1bEPD0jXilk7EXG6/cyGEWDok0xDz7UTff0sqRJ1djTk8PHxC+wwNDdXuNzQ0zPk1vZ7NmzdjGEat78JLL7103BBVCCGEEItHJFlPJHkpTZ1rmRrqYXLoIIWxCTyrnlg8ia4vvjD1TAo0g4lzfoNc5zW0PPcFIpN7aHn+n4n3bWPkoo9zVn0nn78+ypODLv+yo0xvxudHeyv8aG+FdQ0qb11jcsMKg/gyrU4NNJNAM/HNajVF4KG4ZVQnh1Ucr25j4Otx3EgDvpnAMxIEeoT5LJvWX6dPqh8EVFwfx/OZKlQYzQZ4gY8CpKImG9oS1EXNM3/BQgghhFg2llSIun79+tr9Q4cOndA+hw8frt3fsGHDnF/T6zEMg6amJgYHBwEYGxs7Y+cWQgghxJljxutpOauexo7VTA0dZGroILnJw2SMFLFYEsuQiXWOpZJcSd/mv6HuwE9ofPEbRMd3seLB32diw+1MnvUerugwuLRN55khl58ecHh8wGXvhM/eiRJffq7EtV0Gb1tjsLFFQ12MPRXmiqIRGFE8I4o3/ZRXRnWLWFP7gTB49fUYbrQZ34jjmfEwVF0AVEXBNsLq09mCIGA0V2b3QIZz2pM0xCRIFUIIIcTpsaRC1HPOOad2f+fOnbiui64f+yU+++yzR93/TMjn87X7sVjsjJ5bCCGEEGeWFq2ncU09De2ryAyHYWom3cu4liQaTYbDkZdxxndMisbU2neRa7uSlue/SGzkOZpe/Drx/u2MXPQJynVncXmHweUdBlMlnwcOOvz0gMOhjM/WQw5bDzm0xxRuXmNy82qDpqgE1wCBZuFpFp5VB0EwE6pO7g3X6xaekcCzG/HMOL4RXxA9VWdTFIWWhM1ItsTugTQb2pI0J47SJ0AIIYQQ4g1aUhNL5XI5mpqaapMvPf7441x55ZWvu325XKa5ubk2mdTWrVt585vffEau9cCBA6xdu7b2+KmnnuLSSy89qWNkMhlSqRRjY2MysZQQQgix2BSnyI0eJD18kKlsgawSx4okiFn6gpmEyvMD9vROsr67fuFM5hMEJHofpHnnV9GcLIGiMnnWe5jYcDuBZs3aLODlCY+fHXB46JBDwQ2fVxW4pE3nbWsMruzQMRZhj9ozIghQvBKqW5yZrEqP4JoJvEhjtZ9q7Iif+Xwbz5VRFDinPUlLcmGFvUIIIV7LcRzuvfdebrnlFumJKubVdL627CaW2rJlC/feey8Ad9555zFD1B/84Ae1ALWhoYHNmzefkesE+Nd//dfa/VQqxaZNm87YuYUQQgixAETqiK/YRLx5JY1jh8mMHGIiO8xEKYZhxYlbOqoUTL6WopBdsYVCy8U07/zfJPq307Dv+yR7H6KUWosT76QS78SJd3J+vINzLm3kIxfZbO8Nq1N3jno8Nejy1KBLylK4cZXBW9cYrErJxERHqE5E5emRcPh/4KO6JbTyJEZhBABfj+BZKTy7oTb8H3X+vgQ3xi0m8xVeHMjgBQHtqYXRikAIIYQQS8OSqkQFuOeee3jHO94BhLPZP/PMM5x33nmv2a5QKHDhhRfyyiuvAPDJT36Sz372s6d83lwuRzweP6FtH3vsMbZs2UKpVALgIx/5CF/+8pdP+pxSiSqEEEIsIcVJKhO9ZEYOMZ7Okq/46FaUSCQGhgXKmQ/5FmQl6qvEBp+g5fl/Qi9NHHW9r9lU4h1huBrrYFhv56HJFr432MzB0kw7pQ2NGm9dbXD9SoOYsTBf64ISeKjudKVqBV9VCfQonlWHZ9fjGTF8Iw7qma/ZmCpUqPg+61sTdNZFUBZKabcQQogjSCWqWChOtBJ1yYWoEM58v337dgBWrVrF3XffzQUXXFBbPz4+zvvf/37uv/9+IKxC3b9/P3V1da851sGDB1m9enXt8de+9jV+67d+6zXb3XnnnfzzP/8zv//7v8+73vUuUqnUa7YplUr87//9v/nkJz9JsVgEoK6ujhdffJH29vaTfp0SogohhBBLUHGKSjHLxMQEY6ODFPNZoqpL1FBA1Qg0C1+3w2HUyuktVV0MISqA4pawJ1/GzA1g5Pprt0ZhCCXwX3e/kp7kMG3sLLex32+jJ2inX2mnu6uLN6+Ns7FZkwDuRPleNVAtoPgugaKFoaqZqPVS9TWTQDMJVLP6/j19P9tM0aHoeKxrjdPdEJXfoxBCLEASooqFYlkO55921113cfnllzM4OMjBgwfZtGkT1113HWvXrmV0dJQHHniAQqEAgK7rfPe73z1qgHqynnrqKX7zN38TXdfZsGEDGzZsoL6+Hs/z6O/v5/HHHyeTydS2j0Qi3H333acUoAohhBBiiYrUYUbqaGvopn7V+YxMTDEwOsFoPkdSKZIkh+aWUEpTAASKWg2oLALNPO3B6kIU6DbF5k0UmzcducJ3MQrDmLn+arjajzEdsJbGsd0M68iwTtsLswt9h6F/qJEBtR0l2UljWxdG42qKTefPS2XloqBq+GYc36yOzPJdVLeIXhpDKQxCtWwjUHVQDXzVwK9Wqwa6VXv/zlXAmowYqIrCnuEsfhCwoiGGuoD/ECCEEEKIhW9Jfgrs6uriwQcf5P3vfz87duwgCAIefvhhHn744SO2a25u5mtf+xpbtmyZ0/O7rsuuXbvYtWvX625z+eWXc+edd3LOOefM6bmFEEIIsXRYukZ3SyPN9XUMZ0r0ThQYKTvU6T5J3Qkr/yoZtHIazS2glCYhgEDTqqGUddor/hY0Vcep9kd9NcUtYuQGMfNHBqxapg/Ty9OpjNMZjEN6F6TDfTJqip3xa3il8Qbc+jXU2yr1tkK9rRI1kGrH2VQd30zgkzjyed9B8RwU3zlGwKrPClhtAtXE162TDljjdjhJ297hHJ4Pq5skSBVCCCHEqVuSISrAhg0beOKJJ/j2t7/Nt771LXbv3s3w8DB1dXWsWbOGX/mVX+FDH/oQTU1Nc3K+97///axbt47HHnuMX/7yl+zfv5+xsTHGx8fxfZ9UKsXq1au58sored/73sc111wzJ+cVQgghxNJnGxorG2O0JGyG0kX6poocLmqkokni8c6ZmdSdAqpbRKukUctpNCcfBquEAZWvWwSaTaAayzdYrQr0CJW6NVTq1rxqRYBayRBM9dPTe5iJ4T4SpQEuU1+m2U9zdeYers7cw0v7u/mBdy0/8q5mlHpMDeothXpboc5WabBn3Y8otXXLPnBVDQLVIABe02jBd1G8CorvoJXGMQpDMwGrooFmzgpYYwR6pBaw+nr0qFXCMSsMUveNhBWpa5rjC7o1hRBCCCEWriXZE3W5kJ6oQgghxPJUqLgMTBXpnypSqHg0RE2i5qsCpMBHdYso1T6VWjmDWsmgeiUUzwk30Qx8zcbX7aMGUIulJ+rpdjjjsWu4TOPEc5w79TAbi09h4ALgBQrb/Qv4vnctP/cvpYx53OMdK3CttxVWpVRWJNXlG7Qeje+i+E4tZFV8F6X6NSZQDQLNxrOSeFYKX4+GIeusqtWS4zGeL7OqMcZZLXF0bfm1vRBCiIVGeqKKhWJZ90QVQgghhFjKoqbOWS0J2lIRBiaLDKSLTBUr1EcsIma1uaei4hsxMGJ4gJNg1uQ/RRS3gFaeQqtk0YsTKIE7q79qdeIqAcCKpMaKZBS4Griaw5Uc8f7tJHsfJDLxEtdrz3O99jyOFqWn/ip2JK5nl7qByXLAZGlmmSr5FFyoeDBcCBguHLUeE4DGiMLFrToXtWpc1KbTFFnmoZ+qE6g6gR55zSrFc1C8EnphCCPbDyoEmo2vRXAjDfhGnKgRRYlaHBrP4wcBZ7cmMCRIFUIIIcRJkErURUwqUYUQQggBkCk5DEwWGUwXqXgBDVET29COvyOA76A6+Wp/1Sx6aQrVK6C4ZTw/YNekzTmtBoppgypVIq9m5PpJHH6QZO9DGMWR2vNOtJVM95vJrNiCG2urPV9yp0NVn6lSwETpyMfjxYB9kx7Oq7LVFUk1DFXbNC5s1omZUqX6ugIfxSujuiVUrwy+T6AZBFqEkh5n1I3Q0tjAms4WLDu27FtbCCHEfJFKVLFQnGglqoSoi5iEqEIIIYSYLV1w6J8qMJgp4fsB9VETSz/BMHVarb9qnqCc45X9Bzm3RUcPyii+E1a4aha+Xq1WVaSaD4DAJzK2i0TvgyQGfoHqFmurio3nkuneQq7zmrA6+DjKbsDuMY/nhl2eG3bZO+Ez+wO7qsCGBo2L2jQuatU5p1HD1CQIPJbpalXVLeG7ZaaKHnXJBF0tjVjJFrASYEbBiIEmg/WEEOJMkBBVLBQSoi4DEqIKIYQQ4tWCICBddOibLDKUKUEA9VETUz/5sNP3XA7ueJRVF1yJHlTCiaucHHpxAtUrongl8AMCTa+GqhECTb4EKW6J+ODjJA4/SHR0B0o1AvVVk3z7lWRWvJlC80WgnljAnSkHPD8SBqrPDnv0Z48sU7U12NgSBqoXt+qsrlNRpbrymDzXYyqTockO6E6qWBphpbURATsFkXowY2BEw+fk5ymEEHNOQlSxUEhPVCGEEEKIZUhRFOqiJqmIQUddhL7JAiOZMgANMfPU+kCqejgBlRl+qKykgnC4tJOvTlqVDieuKqdRvAooSjhjumYT6Payq1YNdJts9w1ku29AK46R7H2YRO9WrGwvif5tJPq34Vr1ZLuvJ9O9hUpq1TGPl7QUru02uLY7/II5nPfDQHXI5blhj6lywFODHk8NekCZOkthU+tMqNoWX14//xOh6Rr1dfWM5Es4ZZNVjTEimgdOCXLDkO4N37e6HQap0cYwVNUt0MyZWwlXhRBCiGVDKlEXMalEFUIIIcTx+H7ARKFC30SB0VwZVVFoiJonNDt5rRJ10zWoxxvi7LthX1Unj+rk0cuTqE4BxSkQ6CaemVreVapBgDX1CsneB0n0PYJWydRWlVJryHZvIdu1Gc+uP8nDBhxM+zw77PLskMcLoy4l98htOuJKGKi26Wxq0UhaEqpO830Yz5dIRUxWNUWJmbPe54EPbgmcIrhhb1UUBTQDVBN0Ixz+byXCULUWsNrhrSo/ZyGEOBapRBULhQznXwYkRBVCCCHEifL9gLF8mb6JImO5MrqqYuoqmqKgqqAqSnUBTVVQFOXkQtSjUNwSWnkSIzeAVppACXw8K3lCfUGXNN8hNvwMycNbiQ09hRKEqWegqBRaLiHbeS2Flk14dsNJH9rxAl4e98JQddjj5XEPf9anfQU4q17lkjad61YYrK1TUZZ5NWUQwHi+TNzSWdUUI2Ed470eBOA74E0vlfDx9M9Y1cIAVTPAjIeLYYNmgW5Wb60TbuUghBBLmYSoYqGQEHUZkBBVCCGEECfL8wPGcmWG0iWKjofvB/hBgDd9G4QFeAEBge9SOvAM1upLUDR9JmSdDlxV5ZghbE3go5Wn0AsjGIVhFKeAb0TxzOSyD5PUSoZE3zaSvQ9iT+49Yl05uZJC8yYKLRdTbDwvbI1wkvJOwM6RMFB9btjlYPrIfqrdSZUbVhjcsFKnK7GMfxcBTOQrRE0tDFLtU+x65rthsOrNClqD6s9c0cLq1eneq2Y8nMxqOljVrbCKdZn/NyGEWD4kRBULhYSoy4CEqEIIIYR4ozx/VoDqB3hBgOeFt5WKw1Pbt7LpqhtA1XA8H8cLqrfh/WOFsBCgKioJWydaHSatOAX00hhGth+tkiFQNTwzeUoB4VJjZHtJ9j5MdOQZrKn9tQmpAHxVp9RwLoWWTRSaL6JctyYM5U7SeNHn2SGXX/S7PDng4szKVM+uV7lhpcF13QYtsWU4FL0apJqGypqmOKnIHE8f4bszwao/XcU6HbAqYQWrGYdU50wPViGEWMIkRBULhYSoy4CEqEIIIYQ4nU7ky82xQljPDxjPlRnNlik6HjFTJ2EbaKoCvotemkDPD6IXx1H8Cp6ZwDfiMlkPoJbTREefJzq6g+jIcxjF0SPWe0aCQvOFFFouotByEW605aTPka8E/KLf4aFDDs8OHznsf2Ozxg0rDK7t1qmzl1egOpmvYGgqq5pi1EfP0Jf6wA/D1UoOKoUwQI23QaIVIvVSnSqEWJIkRBULxYmGqHP851UhhBBCCLGcaKoShqKvozVpkyu7jOfKDE6VGM4U0TWVVMSAaAtupBm1kkEvjmLkhzByA/i6hWelwmHPy5Rvpch1bSbXtRmCACM/QHTkOaIjzxEZewHNyZIYeJTEwKMAVGIdYaDavIli8wUn1Hc2Ziq8ZbXJW1abTJV8tve6PHTYYeeoV1u++Cxc3Kpxw0qDqzsNYubSD7jrYybpgsOB0Ryrm2I0xMzTf1JFnRnSH2kAJw9TB8Ml0iDVqUIIIcQCICGqEEIIIYQ4reKWTtzSaU9FmCxUGEqXGMuXcd0KSdsgZiXxrRROvAu9NIGRHwirUwHXTBIY0fl+CfNLUXDinaTjnaTXvAN8F3tybxiqjj6HPbkXMz+A2TNAXc89BIpKqX59tZ/qRZTq14F67I/9dbbKrWeb3Hq2yUje55HesEJ136TP00MeTw95/INa4vIOnRtWGFzZoWPpSzdQTUUNskWXA6N5vCCgOW6duZMrysykVL4LpTQM7Agfx1ulOlUIIYSYJzKcfxGT4fxCCCGEOJ1O1zC7IAjIFF1GsiWGMiXyZZeIoZO0dXRNDSeiKk2iF4YxiiOoThHPjOGZiVPqA7rUqU6eyOgLtaH/Zn7giPWeHqHYdEHYT7XlYpxYxwm3TOjLeDx0OKxQ7c3MNFCN6HBVZzgh1SVtOvoxqpEXs1zJxfF9VjZEaUnY89dpIgjC6tRSJnxcq05tCienEkKIRUiG84uFQobzCyGEEEKIBUlRFFJRg1TUoLshyliuzGC1OlVBIWkbRCKNeJFGnMoKtOI4Rr4fIz8STkRlpQi0M1gZuMD5Rox8x5vId7wJAL0wUhv6Hx19Hs3JEh96gvjQEwA4keZw2H/TRopNG3Gjza977K6kxgfO17jjPJMDUz4PHXZ4+JDDcCFg6yGHrYccEqbC5m6d61cYbGzWjtneYbGJ2zr5ksvBsQLpoottqBiail5tY6GpKqoKuqqgqyqaoqCejhays6tTPQfKGRh8HoyYVKcKIYQQZ4hUoi5iUokqhBBCiNPpTFaIeH7AZKHCcLrEaK5MqeIRtw0Sto6qKOA76MVx9PwQemkcxXPwrGTY+1Mmonp9gYc1dYDo6HNER3YQGX8RJXCP2MSJtlKoBqphqHrsSaqCIOClcY+HDrk80uswWZr5OtFgK1y/wuCGlQbrG1SUJfK7KTkeJcfH8wMCAiAAFAhAnQ5UlXDRNQVDV7H0MHDVVAVdVVAVBU1TagGsrqhvLHCdrk4tpsOeqpF6qU4VQiwqUokqFooTrUSVEHURkxBVCCGEEKfTfH25yZYcxnNlBqZKZMsuhhpORGXqKgQBaiWNXhjByA+jujl8PYJnJo/b91OA4paIjO8Kh/+P7cSa2o+Cf8Q2TqSlGqieT6FpI2609XWDas8PeH7E46HDDo/2OuScmXVtMYXzmnRW1amsSamsrtNoiihLJlgFIAh/Bn4Q4AUBnhfgU33OD/BrgSsQKGHgqswKXTUFU1cxNQVT11CVsFJbUUBBQVWA2n0FheqvQgFVATVcieq7UM6guiUUM4qSbEeNt6BEG6Q6VQixYEmIKhYKGc4vhBBCCCEWpYRtkLANOuqiTOQrDKaLjOcreH4QTkRlpvCtOpzECvTSOEa2H704hhL4YcLkA9WcLlCUsEoPpXpfA0UhUFRAnXU/XFfbXjkdY7LnX6DbFFovpdB6KeOA6hSwJ14kMraLyNhO7Kl9GMURjN6tJHu3AuHw/2LT+RQbN1Js3ogTbauFqpqqcHGbzsVtOh+/xObpIZeHDzk83u8ylA8YyjtwaOb8CRNWpTTW1KmsTmmsrt5GjEUarCqgaQoaCgbAsTKAAPwAPN/HC8KQtewGFCteGLoS1Apcj9ip9mauBqzV84ZB68xzimKgBDqqV8DsewFUFc9K4cY78CONKGYUVVFI2DoddRFsQ8JVIYQQ4mRIiCqEEEIIIRYkU1dpS9m0Ji3SRYeRTJmhTImBtEPU0EhGLIJ4J060Da2SRvEdCPwwTA288Nb3UHwXJXCq98PHBC5KEIDvoRJA4BGmXD7gh+tqwiArUPVqP1Zzfn4gp4FvRGuhKoDiFIhMvBRWq47txJ7ch1Ecxeh9iGTvQwA4dmOtUrXYtLE2UZWpKVzVaXBVp0HRDXhhxGX/pE9P2qNnyqc365OtwM5Rj52jHjBTttoeU1hdp7G6WrG6uk6lM64uqf6qtepRVT1m1npM1SAWwA/C0LXWYKB6Hy2OY8QJvApqOYuZfwFXj1GONFOxmxhU44xky6xpjtEct5ZWZbAQQghxGkmIKoQQQgghFjRFUaiLmtRFTbobooznywxMFRnJlsJ1EQPbbji5gwYBBNXA1A8D1PDWnxXE+iiBB0GA4rvoxVG04jhK4OKZS7Mfa2BEKbReQqH1EqA6/H/ipZlK1cm9GKVxjL6HSfY9DIBrN1Bs2kihsRqqxjuJ6ApXdBhc0TFz7IoXcDjj0zPl0ZMObw9M+UyUAgbzAYN5l8f6Z7Y3NViZVGvh6ppquFpvL80q4RNSDWKhOpR/+smjikA0AkGA5eRJVgYI3EE8Pc5U1mLfaIx0Yx2dTfVEo3HQbU7PrFhCCCHE0iAhqhBCCCGEWDQipkaXGaUtaTNZcBjOlBjLlhnPV0hYOvHpiaiOZ3poPxqBGtYFHm+iACfeiVZOoxVHMPJDGPmBJd+PNdBtCi0XUWi5CAhDVXvyZSJju8KeqpN70EsTJPoeIdH3CACuVV8d/n8+5eRKnHgnnlWHqSmcVa9xVv2Rw8gzZZ+eKZ8D1YrVnimPg2mfkgf7Jn32TR7Zs7XOUmptAFbXqVzRoS/vYPV4FAXfjOObcfAdVLdIo5LGLY6Q2e/i9Om01CVpSMZRrQTYKTDsMFSdXiRcFUIIISREFUIIIYQQi4+uqTQnLJoTFpmSw1i2zEC6xGC6iK1rpCIGujbHwY+i4Nl1ePZr+7ECeGaSwFjas6IHuk2xeRPF5k1MAIpXxp7YQ2RsZ7VSdQ96eZJE/3YS/dtr+3l6DCfeQSXeiRPvnHXbQdKKcGGryoWtM19N/CBgMBfUWgH0THkcSPsMZH2mygHPDXs8N+wBYKhw8xqD29ZbdCQk7Dsm1cA3jXAqsQgkA8iWyuxPl0iXM7THc0TVajmwooJugmaBlQA7OROqGpHweQlXhRBCLCMSogohhBBCiEUtaRskbYPO+gjjuQr9U0XG8mUUFFIR47RMoBPoNs50P9byFHphGKM4glKewjeieGaiWum6tAWaRbH5AorNFwCgeBXsyT1ExnZhT7yEmetHL4yguXm0qX3YU/tecwzXbjhKuNpJZ6yVzoTBNV0z25bcgEPpsM/qgSmfXaMu+yZ9fvKKw737HTZ36/zaOdZrql3F61AgEbFwTZORQoV0VqM9ZdOcsNDxwauAV4bcMGT6woasqga6BZoZBqtWAvRI+JwRCUPWJdbmQgghhAAJUYUQQgghxBJh6RoddRFakzaThQpD6RKj2RLj+TJJ2yBu6XM/iY6q4UUa8SKNOM5KtMIYRn4AIz9CoGphdapuz+05F7BAM6uTTm2sPad4FYz8IEauHzPXX70dwMj1o1fS6KUJ9NIEjO088liKihNtOyJYjcQ7icU7WN/QCIpCEAS8MOrxnZcqPDXo8vDhcLmkTePXzrHY1KLJxEknQNcUmhIW+ZJLz1iOTNGhoy5Cwo6EwehsvhcGq14FskOQ7q3OvabOCldTEG+BWItUqwohhFgyJEQVQgghhBBLiqYqNMUtGmMm2XKUkUyJoXSJgXSRiKGTihinZdZ334jhp2I4iY4wGMwPo5fGUEoTeGYc34iHQdMyE2gmleRKKsmV5F+1Tq3kjgxX8wO1x6pXxswPYOYHYPipI/bzNbsarnbQmFjBVevWsHfdCr7Rk+ThXo9nhjyeGSqwrkHl18+xuKpTPy2/86UmZuvYhsZUwSFbcmlN2rSlbAxt1s9O1UCNwqtbV8wOVzP9Ybgab4OG1RA9yYnfhBBCiAVIQlQhhBBCCLEkKYpSG+rfVR9lLFdmYKrISLaEqpy+of6oBm60FTfSglrJoBfHwomockMEuolnpgg0Y+7Puwj5Zpxyw3rKDeuPXBEEYc/Zo1SvGoUhVK+End6Pnd5f26UDuFaPkWtdyfPuCn4+1cXOyRX8zS+6aUxE+NUNJjeuMjA1CVOPRdMUGuImpYpH72SBTCmsSq2LGMcepT87XLUJw9TcMBTGINkF9SvCof9CCCHEIiUhqhBCCCGEWPJsQ6OrPkpb0maiOtR/LFdmolAmaZnErNMw7FtR8K0UFSuFk+hCK01g5IfQimMogY9nJvCNmPSPPBpFwY004UaaKDZfeOQ638HID1fD1T6szEGsdA9mtg/NzZOaepHNvMhmHdDBDxR6ym28tGMFD+9cQVPnWs5ffzZmokV+9sdgmxqmrpEpOuwdztJWrUq19BOsptZMSLaDU4SJA2GgWr8Skp1gLJ8WF0IIIZYOCVGFEEIIIcSyoWsqLQmb5rhFpugyki0xlCkxkHaIGhrJ0zTUP9As3Fg7brQVrZxGL4xiFIbQcoP4ho1nJkGVj+YnRDVwEl04iS7gipnnfQczOytUTfdgZXrQy1OsVQZZyyDwBPQD/VBUYzipVfh1qymnwqWSWLGsetgej6pCXcyg4vr0TxXCXqn1Eeoj5om3OjUiUNcF5SwM74Z0fzjEP9EOmrznhRBCLB7yr5YQQgghhFh2FEUhFTVIRWeG+vdXh/prqkJdxMQ80Yq7kzqximfX49n1VJLd6MVxjNwARnGUAAXPShHokeMfR7yWalBJraaSWk22+4ba01ppMgxTp3qYGjyANtXDSr+fiJ8nMrkbJnfXtg1QceIdlJOrwlA1tZpychVupHlZV62aukpz3CZTctk3nKUlYdGeihAxT6IdhpUAMw7FSRjYAfF+qF8NsWaZfEoIIcSiICGqEEIIIYRY1iKmRndDlPaUzUS+wmC6xFi+jOsFpGyDmHV6PjIHeiSsqIy1o5UnMfJD6MVR1OIknhnDMxPLciKquebZ9RTsemi5GHUdeEHAt/uK/HJ3D2bmIOeohzlXPcQF2mGSQQYz14eZ6yMx8OjMMYwE+bbLyXZtptC8Kez/udwokIzouK7GcLZEuujSWR+hMWahnejbVFHCSabsJBQmoP+ZcMh/3UqZfEoIIcSCJyGqEEIIIYQQVIf6J22aExbposNIpsxgpsjUVIWYqR9RmRoE1dva/0BQvXPEutr2wZHPzdomXJcAO4GmtWOUxkmUh7BLAyimjWelQJWJqOaKqihc2R3liq5z2TW6nu+8XOGvB1wAmpniHQ19vKupnzX+IazMQcxsL5qTJdm7lWTvVlwzRa7zGrKd11JqPHfZBd26rtAUt8mVXPaP5pgqOLTX2SRO5o8Nqg7xFnDLkBmA3CjUdUOqG6z46bt4IYQQ4g2QEFUIIYQQQohZFEWhLmpSFzXpaogwli0zkC5R8fxw/cyGtcfTzyko4dPKzCbTW6mqMrOdEi4q6hGPoQHfb2Cq2ImfG63OSD+EqSmokXp0O7acR5XPKUVR2Niis7FFp2fK4zsvVXjocB1fm6jjaxPnc3a9yq+dY3Fte0A0vZdE/3bi/Y+iV9LU9dxDXc89OJFmcp3Xku3aTDm1dlkN+Y/bOranMZ4vky05tKdsmpM2xsn0FNYtSHZApQDjr0BmKJx8KtUZrhNCCCEWECWY/rO4WHQymQypVIqxsTEaGxvn+3KEEEIIscQ4jsO9997LLbfcgmEs70pI1/PxgoDpGHQ6K5sJRY8MSKefO1UV16dY8ShUKhSnRsmP9xJkhvAqJRwjjmImMQ0VU9fQteUT3J1uw3mff99T4b79Fcpe+FxHXOW2DSZXd+nUmwHR0R0k+rcTG3gMzS3U9q3EO8l2bibbtRkn0T1Pr2B+FMseuYpDfdSkoy5KKnKKtTqlDJTSEKkPJ5+Kt8nkU0IsYfI5QywU0/laOp0mmUy+7nYSoi5iEqIKIYQQ4nSSLzcLRxAElHJTlCYHcSYOU8xNkvNMiloch7A/p6lpmLqCqWkyT88blC773L23wo/2OWQrM1+XOhMqG5s0zm/WuKDB56z8syT6txEbehLVr9S2K6XWkOvaTLZzM260ZT5ewhnn+5AuVFBUaEva1MdNbF1DP5nKVIDADyefckoQb56ZfGoZVfkKsVzI5wyxUJxoiCp/1hNCCCGEEGKBUxSFSKKeSKIe2tdAfhR38jCV7DgVzyevJsm4KiXHp1Cu4OGjoWLq1UVTZ/UhEMeTslQ+uNHmtnMs7ttf4Wc9Dj1TPv3ZcPlpjwNAY2QjG5s3cdE6hxt4mjWT24mNPIedPoCdPkDT7jspNpxLtmszuY6r8ez6eX5lp4+qQn3cpOR49E4VGMyUsDSVmKWTsHVsQ8c2VCz9OAm/okK0EXwXCuOQH4dkJ9SvCCtUhRBCiHkilaiLmFSiCiGEEOJ0kgqRBc73wpApMwi5YXDLlI04ZSVGyfPJl11yZZey4+N4HiigqxpWNVTVpA3ASclVAnaPuewc9dg56rF3wsP1j9wmbsAVjUXeYz3JFaVf0JTejTI94RgqheYLyXVtJtf+JnxzaU+g5HoBFdej7IatMAAsXSNiqiQtg4ilYevhcszKabccvs81M5x4qq4bzNiZeRFCiNNKPmeIhUIqUYUQQgghhFjKVC2c4TzWHPaRzI1gZfqxykMkzSg0pPCJUXY9Sq5PyfHIllzyFZd00cHHJ6LrRC1dRkqfgLipcEWHwRUd4Rf9shvw8oTHrlGPnaMuL4555BzYOhRhK9cB19GtTfBb8Se5mcfoKr9CbPQ5YqPP0fz8P1FovZRs13XkWy8j0O35fXGnga4p6JpOtDo/lO9DxfMolH2mCmEvWV1VsA2NuKUTt3RsQ8M2NIzZAX9t8qk8jO2F7CDUrwqfk8mnhBBCnEESogohhBBCCLGYKQpE6sKlrhvyozDVB9lhVFUjEqknErUAg/YUOH5AqeIxVXAYz5cZz5fRFIWYpWMeb6i1qLF0hQtbdC5s0QELzw94Zcpn12hYrbpr1KO33MBfpt/KX/JWVipD3Kr9kvcZj7HK7yM++Evig7/E12xy7VeQ67qOfMvFoC7Nr2iqCraqYRsAOgTgeD5l12ckU2YoKKEqCqY+uwWAhm2o2LqGYsbAiEI5DUM7IdMPDWvCyaekCbAQQogzYGn+Cy2EEEIIIcRyZESgbgUkOsIh0Om+MFT1XbCTYMYxVAXDDkOq1pRFtuQynquQLlZIFwMihkbU1CWXOkmaqrC+QWN9g8Z714eTgfVmfXaNerww4rFrtJ0vFt7NF913s145zDu1x7hVfZwVjJLse4Rk3yNUjBS5FTeQXXEjldSq+X5Jp5cChq5izArufR/Krkem6DCeLwEKpqZiGSop2yBi6thmHDuRQC9NQv+zkOoMJ5+K1M3bSxFCCLE8SIgqhBBCCCHEUqPpkGgNh/uXpiA7DJmBMFQ1Y2CnQNUwNZXGmElD1CRXcckUHMZyZSbyJTRFJWZLdeqpUhSFFUmNFUmNW9aGz43kw1B159havje6ir9N/xqblP1hoKo9TrOTpmH/j2jY/yP6rTX0tW5BP+t6ksnU/L6YM0RVIWJqREwNMCCASrVadWCqhB/4aJpanbDKJmVaJCZ6sfNjULcqnHxKhvgLIYQ4TSREFUIIIYQQYqlSlHBG80j9rKH+vZAdqo6vToERRVEgYekkLJ2WpE225DCer5AuOKQLFSKmLtWpc6AlpvLmmMqbV4V9VTNln11jG9k5ci4/GP0AHenneI/6CFvUZ+ksH6Dz8AHKh77GduUSnku+GaftItY1mayr14gYy6CRrQKmrh4R5E9PWDWRrzCa9TH1OHWFMg3pF4imh7BazoJ4qwzxF0IIMeckRBVCCCGEEGI5MGPhkuwMh/pnByE/BvlxMKNgJUEzMDSFhphJfdQk74TVqeO5ChOFMiph71TLkIBqLiQtlas6Va7qNAAbx7uOnvS1fHV4kobBh7kk+xBnc4gbeYIbM08wlK7nhy9ew5f86/ASXWxo0FjfqLGhUWNVSkVXl36wesSEVQGUXI/xismIrxLPjZAaHiTWspJY2zrsRP18X64QQoglREJUIYQQQgghlhPNgERbuJSzUJgIh/rnxwAfzARYcRRFJW7qxE2d5mp16kSuwlTRIVOqYBs6MalOnVOGprCuQWNdQxOc8z7gfewZ24/6yv10jj5CmzfJ7+k/5vf4Mc8Uz+Z7h6/jX3uuJEsUU4Oz6rUwWK2Gqx1xBUVZwsGqQnXyKQ0Ck5JjMVQqoR3YiznQR7TlLJJtq0kl4tKWQgghxBsmIaoQQgghhBDLlZUIl1QXFKfC4f7ZIUgPgG6E1alGBENVaIiGvVMLFY90sdo7tVqdGrWqQZaYc2rTWmhay4D3YWJDT5I8/ADRkWe4RN3HJeo+/sL4Bvf7l3GXex2Pj53Li2Nebd+EqbC+QQ2rVavBar29RMNEBWxTwzZjBIkYTj5NrvcFxoZ7URrWUN/SSUPcJhUx0LUl+jMQQghxWkmIKoQQQgghxHKnahBrDJeG1eFw/8wgFCfCClUzBnYSVJ2oqRE1NZoTFtmSy2S+zGTBIVtysPVwvaYt4erHeRJoBrnOq8l1Xo1WmiDR+xDJww9gZXt5h/oL3mH+gqzRxGOR6/m2s5lH001kKwFPD3k8PTQTrJ7bqPH2swyu6zaw9KX5e1IUMOMpzFiCeGGC8vjzjGYG6YuvwI430JK0aIiZJCMG2jJogSCEEGJuSIgqhBBCCCGEmKFbkOyARHt1uP84ZPohNwqBH4apZhxdVaiPGtRHDYoVj3QprE6dKjpAQMzUw+pUyajmnGc3MHX2e5k661ewpvaSPPQAib5tJJwxbnb+nZv5d/Lt5/NK45vZpl7BzrTJnnGPwxmfF8c9Xhz3+NKzJW5abfL2tQYrU0u0ilhR8WNNmHaFjuIYbiHHlNfJ/kILPbpF3NZpS1rURU2StoEqgaoQQohjkBBVCCGEEEII8VqKEgamdhLqVkBxEnIjkB0OQ1XNDNfpNhFTI2JqNMdtMiWHyUJYnZrLu7XDaYqCroWTH+mqgqaq0k/1jVIUyvXrGa1fz9jG3yE2+EuShx4gOrqD2PguLhzfxUbNJtt5DZnLb2Qgeg4/7XG5d3+F4ULAD/dW+OHeChubNd6x1uSabh1zCVYRB5qJE+9AreRoKr5CvT9JwVjBlFPPy0NZdE0lFTFoS9okIwZJW1/avWSFEEKcEglRhRBCCCGEEMemahBrCpeG1eFkVNmhsErVqw73txJoqj5Tnep4lBwf1/OpuD5l16Po+FQ8n0rFx/NdfAIIQFGmg1UlnH1drc40LznWCQs0i1zXdeS6rkMvjJLofZDk4Qcw84OkDj9A6vADtMba2dB8IR85bxUvuN18Z6iTh4ZMdo567BwtknpO4S2rDW5Za9CVWHrVqb4Zxzci6KVJ4hMvYMU7cRIrKGs2uZLL7oE0ph4Gqq3JsH9q3JJAVQghREhCVCGEEEIIIcSJMyKQ6gyH/JczkJ8e7j8SrreTYMSIGBqRo0w25fgBrufjegGO5+NUQ9ai41NyPFwvoOQ4uH4Q7hDMVLFqKtVqVqliPRY32szk+l9jct2vYo/vJnl4K4mBRzHzg2GoCrQBbwFKqRZ6tJU8lu/imUo3z+xZwfdfbuPCVoO3rzW5qlPHWErVqYqGG2lC8cqY2V6M4jhaYiVmvJ36WJSK65MtOoxm09i6Rn3MZEVDlPqYOd9XLoQQYp5JiCqEEEIIIYQ4eYoCdipcasP9h8MwtdAPuglmHDQDVD3cHjBUBUPVwHjtIYMAHD8MVl2PWshacjxKrkdlOmj1XXzfr1aqzlSuShXrqygKpabzKTWdz+gF/4nY8DNY6f1Y6R7MzEGM4hh2aYRzGOEcnuLD1ZywGJjsmezi5SdX8BN9Jam2NWxcfxbN9an5fT1zKNCs6hD/LPbki3iFYSqpVRBppjFuAVByPEazZSbzFVY2RulqiGJokt4LIcRyJSGqEEIIIYQQ4o3RdIg3h0ulAMUJyAyGE1NVcuA7UC0sRVHD7VVj1q0BihrOqq6pmK8TVHk+uH7YEqBWyer6FB2P4nGqWHVVQauGrMuxijXQI+Q6ryHXeU3tObWSxcocxEz3YGUOhuFq9jARr8wm5QCb1APhhkPhMqY0UkyuItKyBie1ikpyNZV4Z9juYZHyzQS+EUUvTmCP7sCJd+IkVuKbcWxDwzY08mWXPcNZJgoV1jTFpSpVCCGWKQlRhRBCCCGEEHPHjIZLshPcMngV8JzqbRmcEjiFcPGc8LHnQOCH+yuEwaqqz1SxVm81FTRVxdJfm4IGAbj+dIuA4Igq1mLFC3uxOj6e99perGEV60zQulz4ZoJi00aKTRtnngw8jPwQVroHI91DfvgAduYgrcEoTcE4pMch/czMMVSDSmIFldRqyslVlFOrKKfW4JvJeXhFp0jRcKPN1SH+fRjFccrJlTjxDlANYpaObWiM58s83zslValCCLFMSYgqhBBCCCGEmHuKAoYdLkcTBLPC1emgtQxuBZx8WNHqVcKwtVQNWYMgDFkVbSZgrVayKmrYu9PQjl4VOR2wTlewVqZ7sVZ8yo5H2fPIV4JjtwlYDgGrooXVmPFO6LwGzoUKsHcyy849rzA1eICV3mHOUQ+xXukl5pex0/ux0/trhwhQybdfydTaWyk2nl9r5bDQhUP821ErGezxFzEKI1SSq3AjTWiqQkvClqpUIYRYxiREFUIIIYQQQpx5ihL2TdWPEUJ57qtC1mo1a6UYBq1uKax2LWfBd2f2m90mQDNANdBVDf11erH6ftiLdXabgEq1TcD0ZFdFx8HzfUDBUFVMPWw7sFwqV9vqE7RdeREVbxO/6HP5i/0VXhhx6FZGOUc5zCXWYa6N9rHaP4RdHCI++BjxwccoJ1cxteZWsl3XEeivE6gvML6ZxDdi6MXx6hD/DpxEN76ZlKpUIYRYxiREFUIIIYQQQixMmh4uRI++3vdnglW3MnO/nIdKvno/96p2AUotWJ0OWVXVwNJfv02A4/uU3TBYLVU8smWXYsUj7Tj4QRismpqGqSkYSzxYNTWFG1Ya3LDS4HDG4979Nj/vaeVnxcugCJoC72sd4LeNn3P2+MNYmYO07vhfNO2+k/Sqm0mvvgU32jLfL+P4FA032lId4t8bVqUmunHinWh6RKpShRBiGZIQVQghhBBCCLE4qSqox2gZ4LlhkOpVqiFrtSdrJV+tZHXC+7MnvlJV0MyZNgGaganp4WRXFhALN3O8gJLrUXZ8ihWPXMWhVPEpVBx8AhTA0DRMPQxYl+JkViuSGh+9SONDGy229Trcs99h95jHd4Y6+A6/Rad5G/9v/TbeUvoZsfIIDfv+nfp9P1hUQ/3DIf4dqE4ee3IfRn6YSnIlTqyVmGXUqlJ39E6ysjFGt1SlCiHEkiUhqhBCCCGEEGJpqlWyxl67LghmWgVMB6xuGZwiVHLhrVOEUhp8Lwz7IvVgRACq/Vd1Etb0ASNhsOp4lF2fYsUlV3YpOT6FcqUarCqYmoqxxIJVS1e4abXJTatNeqY8ft7j8OAhh/5SjP9n+G2o3Mxt0ef4T9bPWFvc9aqh/u8k230dgWYd/0TzyDdiVPQoWiWNPbYLIzdAJbUSIs21qtS9w1kmpSpVCCGWLAlRhRBCCCGEEMuPooBuhcvR8jvfqwas1UrW7DBkB6EwEYap5mtbDNSCVQDCEK3i+ZQdn5Lrha0ASi5l91XBqq5iaAqWri30wszjWl2n8ZGLNH7nQosdIx4PHHR4tM/hO4VL+E7hEtYpvfyX2P28xdtWHer/BZp2f21xDPVXFDyrDs9MoJcmiYzuwIm24yRWELPrsA2NsVyZHcWwKrWrPop5lBYRQgghFicJUYUQQgghhBDi1VQN1Eit8pR4C9R1Qbo/DFOLExBpOGqYOpuphRNQJWZ99ar1V3U9irOC1Vy5DAFYhkZE19D1xZuoaqrCJW06l7TpfMK1+f+zd9/hcV5l+se/b50+I426ZFnuJXGcxKkE0hNKQtvQEhZIyLLA0hZYltB7J9SlhfJLgF3IsixLKCGkQ3pz3EvcbVm9Te8zvz8mEQlxizwqtu/Pdc2VkXTe9xwptjy69Zzn3N9d5I5deR7r6+SdyauJ8Fout+/mn9zbaC4MHllb/Q2Loq8Ro1TASfdhZ4YoBDsohGbREg6oKlVE5CilEFVERERERORQ+Oqrj8hTYWpPtTLVXw/uPloG7MdTh1g9FaxWKtWK1XS+RDJbZCyTJ5kvUMxUsE0Tr2vitS2YoZniwfhsgwvnOFw4x2EkU+bu3QVu32ly3ehL+VHxEi40V/JPzp8501h/RG31r1gOhUArRjGDG9uBne4nH+oiGGzFG/aNV6XOjlZ7paoqVUTkyKYQVURERERE5Lnw1VUfdbMg3gPxvZAZBW8EPKHnfDvD+FuwWu936Cj7SBeLpHMlxtIFkrkiyWwWw6hu+fc5FpZ1ZCaqUZ/JZYs9XLbYw65YiTt2Fbhj52lcnj6VRcYerrRu5VX2PXiPoK3+FdtHIeTDzMfxjm6glOohH5lDS7CZVKHCloEEY5k8cxuDRFWVKiJyxFKIKiIiIiIiMhHeSPUR7vhbmBrrnnCY+hTThKBrE3RtmkMecsUyqXyxWqWaKhDLFChTwTFNvI6FxzaPyCrVrojF1cstrjrBw7rBErfvnMcX9vwTX86+jtdaf+FK61Y6n7bVP9l+JmPzXk624fgZudW/7IYpO0Gs3Bi+wTUU/c1Yodl4Q/UMpfLEVZUqInJEU4gqIiIiIiJyOLzh6iPSAfHeapA61l19nyd02IFftUrVJep3aa+rkMmXSOWLjKbzpHMlErkCBgY+x8Tr2JhHWD5nGgbLm22WN9u86xQvD/X4uH3nK7iw9yWcy0qusv7M8631hHruJ9RzP5nQHOLzX0589gVgzrAfaQ2TkjdKqVzEzgzhywxhB9tpC3WSqPhVlSoicgSbYf/iiIiIiIiIHKE8IWgKQbj9b2Fq7KkwNVyT6knbNAh5bUJem5aQl2yxRDpfIp6pVqiOpvNUKOOxbLyOiXOEVTy6lsHZnQ5ndzrEc17+svsFfH7XGRSHd3KldSuXWffgS+zEt+rbuJt/y9iKd1JsOn66l/1spk0x0IJRzOIm9uBkBrGDnfj87QymCqpKFRE5AilEFRERERERqSVPEJoWQqQdEn0wtvvJMDUEnkjNtqIbBvicao/UhoBLoVwhnSuRyhUYTRdI5YsUsxUsw8DnWHgcaybugt+vsMfkZQtdXrbQpSexlDt2LeCVO67gnOydvN3+PQ2Z3dTfdw33+i6gf+lVHD+rHsucWZ9gxfZSCLZj5pN4Rp/ASfXhCXcRsxrYMpBgNJ1nXpOqUkVEjgQKUUVERERERCaDG4CG+RBqe2aY6glV+6bWONF0TIOIzybis2mL+EgXnjycKlMgmS2STOUwMQj7HOwj7GCq9pDJG5d5eMPxLWwaeS1f234xp+79GZdxFy/I3MnIYw/zrcdez3DHhZzb5eGEJmtGBaplN0jZCWDlY/iG1uL4GgkEZ9OXgtXZAp31fjrq/fhca7qXKiIi+6EQVUREREREZDK5fmiYB+GnhanxvdWQ1RsBo/bbuQ0DAq5NwLVpevJwqnS+xFAyx3Ayh2WahL3OEdc/1TAMljbYLG1oonTK+7lr+4tYtPl7dBR282l+yMPdf+FjO65myDObszttzpvtcFyjhTkTSnANg5KnjpITws6OEBxeRZe/jZi3na2DZfoSObqiflojXhzrCPsfIyJyDFCIKiIiIiIiMhUcH0TnVitTk/0wuhNiT4apvrpJCVOfUj2cyiTidWgIuPTGsgynsvgcm6DHhhmQMT5Xlmkwa8Ey0vO+zcDW31G/6Reczmb+6H6EnxRfwre2XMZNW7w0+gzOne1w7mybJVELY7oDVdOi6G/CKOVx0n00ZIcI+ZoZyzSwoSdIX9xPV9RPY9CDOYOqaUVEjnUKUUVERERERKaS44X6Lgi1Phmm7qqGqY6v2k/V9k7a1KYJ0YBLyOcwnMzRG8symMgS8jl4nSN0K7lpE1t0GalZZ9O09kcEe+/n7fYfeI37IJ8svIk/ZE7lfzfn+d/NeVoDBud0Opw322FBvTmtgWrFcikEWjGKGdxUD830UO/WMZRrYm2inqb6CLOjfur86pcqIjITKEQVERERERGZDrYH6mZD8MkwNdED2TikhsBywA2C469571So9k9tDXuJ+BwGEzn641lSuSIRn3vE9Ut9StHfRO8ZH8Hf9wjNa35AQ7qf71hf55roaXzLvoo/9NfTl6rwq015frUpT3vQ5LzZ1S3/cyLTF6hWbB9F2wflInYuRntxmHw+wGCqgbUjTbQ0tTCrwY/f1Y/vIiLTSd+FRUREREREppPtQl0nRGZBPgnZGKQGIT0KmbHqNn83UH2Yta0W9TkWs6N+6v0uffEsw8kctmkSOgL7pT4l3XoauxpPIPrEr6jf8hs6Y4/wFWsN/7bscm7xXcqd3fBwT5GeZJlfbMjziw15ZodNzntyy//s8DRV5Jo2JV8DpUoFq5CkI7+H7FgPg2N1jA6209bWQWt9CNc+Qv/HiIgc4RSiioiIiIiIzASGAZ5Q9RGZBYXMk4HqMKSHqtWqlUr1oCo3AFbttnmHvDYBN0hDwKUnljni+6VWbC/Dx72JeOf5NK/6Lv7hdbRt+imvD93FRSe+g9HTj+eBniJ/2V3gkd4iu+NlfrYux8/W5ZhXZ3Luk1v+20PTEFgaBmU3RNkNYReztOfGyAwN0Du8leHGLtraOmmK1mOpX6qIyJRSiCoiIiIiIjITOb7qI9QKpUI1UM2MQbIP0iNQKlb7q7qB6rjDNN4v1eswlMzRF8symMwR8tpHbL/UQqiTvS/4IqE9d9G47id4ErvpvPdDRGZfRPD4N3NBV4RUvsL9ewvcvbvIY31Fto+V2T6W4/q1OY5vtPjnkzwc3zg9PzpXbC9F24vjK9GYi5PpW0v3wBbGGmfT0tFFXbQJ40gtGRYROcIoRBUREREREZnpLAcCjdVHdC7k4tX+qcn+v1Wr2s6Tgaq/2gJgghzLoC3ipc7vMBDPMZDIks6VCPucI7NfqmGQmH0BqdbTaNzwU8I7/0x49+0Eeh9k6Pg3Q9fFXDzX5eK5LvFchfu6C9y9u8CqgRLrh0q89/Y05822ecuJXloC0xRYmhZlXz0ebx1OLkmmfwu7hrYRa2ynqWMegfrW6p8RERGZNEf1r6zy+Tw///nPueSSS+jq6sLr9dLW1sZZZ53Ftddey9DQ0JSu5/3vfz+GYYw/5syZM6Xzi4iIiIjIUcC0wFcP9V0w6zSYfSZ0rKgeUFUsQLy3+sjGoFyc8DQ+x6Krwc+S1jD1AZexTJ5YukC5XMPPZQqV3RADJ72L7nO+Si48F6uQpGXVfzDrng/ixnYAEPYYvGS+y5fPD/BfLw/y4nkOBnD37iJX35zk+jVZMoXK9H0ShoHpDRFono0bbGRooIedq/9K79q7yA1shVxy+tYmInKUMyqVyjT+CzB5Nm3axBVXXMGqVav2O6a5uZnrr7+eSy65ZNLX8/DDD/O85z2P8tNecXR1dbFz584J3zMejxOJRBgaGqKhoaEGqxQREQ25U74AANdQSURBVBH5m0KhwM0338wll1yC46jCSeSIUMhUK1TTw9XDqfIpqJSr2/09wQn3US2XYTSTpzeWIZ4p4HdsAt4jeGNjuUTd9j/QsOk/MYsZKobJ2LyXM7zk9VQc/zOGbh0t8YPHs6weKAEQ9Rq8ebmHF851MI3pr8xNZ3PkUzHCVpbGunrqmjuxIu3VoF1b/WUG0+sMmSmeytdisRjhcHi/447KELW7u5szzjiDnp4eAAzD4JxzzmH+/PkMDg5y++23k8lkAHAch1tuuYULLrhg0tZTKBQ45ZRTWLt27TPerxBVREREZjL9cCNyhCsVqoFqdgwSvdUqxXIBTLu65d/xPect4IVSZbxfaqZQIux18DhHblBnZYZoWvsjQj33AVDwNTJ4wltJtT2vetDXkyqVCvfvLfLDVVl6ktUfoRfUm7z9ZC8nNk9/mFypQCJbpJSN02DnaAp5CEVbMCKd1RYQtme6lyjyLHqdITPFoYao0//dfhK8/vWvHw9Qu7q6uOmmmzjxxBPHPz40NMTll1/OHXfcQaFQ4DWveQ3btm2jrq5uUtbz5S9/eTxAff3rX88vfvGLSZlHRERERERknOVAoKH6qH+yj2ouUT2cKjNSrVYtF8GwwPWB7Tto2DbeL9Xn0J/IMZjIkspxxPZLLfka6Tv9w8T7H6Vp9Q9w0320P/wFUi2nMrD87RQDrUC1MOf5sxxOa7O5aUue/1yfY+tomQ/cmebsWTb/fJKXtuD0hcmGAWGfTcmtZyhTYDhRoCXbS/NoH75QPYQ7INgM3v2HAyIicmBH7q8M9+Pmm2/mnnvuAcB1XX7/+98/I0AFaGxs5KabbmLevHkAjIyM8JWvfGVS1rNp0yY+97nPAfCP//iPXHzxxZMyj4iIiIiIyH6ZJvjqoK4T2k6ArufD7OdB+wqo6wLDrvZQjXVX+6lmRqGYrZY47oPPtZjT4GdxyzP7pR6p+xzTLaey+8LvMrzodVQMm0D/o3Td8Q6im36Jmf9bn1HXMnjNEg8/vTTIyxY4mAbc013kn25O8qNVWVL56f0CWJZBNOgS8PnoKYTYkArSM5Yh37se9jwEAxurIbqIiDxnR12I+t3vfnf8+ZVXXskJJ5ywz3GBQIDPfOYz429fd911FIsTb7q+L5VKhbe85S3kcjnq6+v5+te/XtP7i4iIiIiITIhlV0PVSAe0Hg9dZ1VD1Y5TITqv2js1l4R4D8T2VqtWC+lnhaphn82CpiCLWkJ4HJOhZJZUtrY/V02ViuVh5Lg3suuC75BuXI5ZztOw6b+Yc+ubaVz3/7AyfzuYuM5r8p5TffzgRQFWtFgUyvCrTXmu+mOSP2zNUypPb5jq2iaNIQ+ObbMzZbEpE2YwZ1Ic3Ardj0DfumpQfqSm3iIi0+CoClGTySR33HHH+NtvfvObDzj+Va96FcFgEKhWo/71r3+t6Xq+//3vc9991d46X/3qV2lubq7p/UVERERERGrCtKpbvcNt0LwEZj8Zqs46FRoXgxOoHlqV6K2GqqkhyKehUsY0oSHgsqQ1zNzGIBVgKJFlNJUnWyjBEZbTFUKz2Pv8z9N76gfJhbuwihnqt/6Gube+heaV38JJ7BkfO7fO4kvn+fncOT46QyZjuQrfejTLv/w5xcq+6Q+Tfa5FU9BLsQxbRitsyYYZLbpURnfCnoerYWp6RGGqiMghOKp6ot5///3kcjmgWml62mmnHXC81+vlec97HrfddhsAd955Z80OmNqzZw8f+tCHADj77LO5+uqra3JfERERERGRSWea4AlWH6FWqCyohqj5ZLVCNT1U/e9T1Yy2i+P6aQv5qPM7JLNFRtMFErkCyVwBCxOfa+F1LDgSWqcaBslZ55DsOBt//6NEt/wa3/B6IrtvI7L7NpKtZzK66FVko0sxDIMz2h1OabX5/dY8P1+XY0eszDV3pzmz3eZtJ3mYFbam8XOBkNcm4NrEMnliGWgMRmjxVQjFdkO8G0JtEJkF/oZnHKglIiJ/c1SFqBs3bhx/fsIJJ2DbB//0VqxYMR6iPv36w/WOd7yDRCKB67pcd911GPqHSEREREREjlSGAa6/+gg2Q8O8J0PVVDVYTQ1XD67K9uMrl/HZLk31frKESObLxNJ54tkiQ6kcBgZ+x8LrWjM/rzMM0q2nkW49De/IRuqf+F+CfQ+OPzINxzOy8NWkW07FNg3+YZGHC7tcfr4+x++35Hmwp8gjvUVesdDlDcs8hNzp+4RNE+oDLsVihcFkjrG0SXO4jiYf+OI91V64wWaom10NU82jauOqiMhhO6pC1M2bN48/7+rqOqRrZs+ePf5806ZNNVnHjTfeyB/+8AcArrnmGpYuXVqT+4qIiIiIiMwYjq/6CDRC/Rwo5qqhai5R7aGaieEt9OMFGoNecmEfqZL95CFURYZTOQzA51h4HXvGZ3bZ6FJ6z/wYTmIP9Vt+Q3jPXfiG19MxvJ5cuIvRBa8iMescwh6bd67w8rIFDj9cleOhniK/eSLPbTsLvGmZh5cucLDN6QtTbdugMeghWyjRPZJm2LVpjdTT6DVwUv2Q7K+GqZHO6v9bcxqraEVEZpCjKkQdHh4ef97S0nJI17S2to4/HxkZqcka3vOe9wCwaNEiPvrRjx72PUVERERERGY821N9+KNQ3wWFbDVQzcUhOYAnn8RTzBJ1TfI+H6myj3geRtN5RtLVtmxe28LvzuxAtRDqZGDFvzK89B+p3/Y7Ijv/hCe+i9aVX6dh488ZW/BKYl0vYnbYy+fO8fNob5HrVmXZGSvz3ZVZfr81z9tO8nB6uzOtn4fXsfDaFslckR1DSYZ9Dm2RBupdMNNDkOiDYBPUdYG/sXoYmYjIMeyo+i6YTCbHn/t8vkO65unjnn79RL3vfe9jcHAQgB/84Ad4PJ7DvudTcrnceM9XgHg8DkChUKBQKNRsHhERERFg/PWFXmeIyMRY4KmrPkKdUEiP91E1MiMESzGCRpGmgEOq4iFVthlLlxhO5qhQwWtbeBwL25qZe/5Lngb6j3szgwtfQ93OPxHd/juczCBNa39EdNONjM69lNG5L+XklgjfvdjPn7YX+Pn6PLvjZT761wyntub55xM9dEWmt9LT51p4bItktsCmdJxowENzqJ6Qt4KRHIX4YDUYj3QqTJWa0usMmSkO9c/gUfXdL5vNjj93XfeQrnl6yJnJZA5r/ltvvZWf//znAFx55ZWcf/75h3W/v/fFL36RT3/60896/1133YXf76/pXCIiIiJPeap/vIjI5Mg/+TiCeS/CXHIOnSP3sqD/ZoL5ARqfuJG6Lb9hd8M5bG1+CQs9TXxoOdzabfLXPoNH+0qs7EtxVkuFizvK1NWu/uawDI2meeJZ7x188iFSe3qdIdMtnU4f0rijKkT1er3jz/P5Q/tH+OmVnYdavbovqVSKt73tbQA0NDRw7bXXTvhe+/PhD3+Y97///eNvx+NxOjs7Of/882loaKj5fCIiInJsKxQK3HbbbVx88cU4zvRuOxWRo1wxD/kEZBOQHoRcklIhS7ZYIVl2GC3YpIomxXIZj2XjdUwcewbu+e96Fd2VVxLqfYDolv/FF9vKvKHbmTt8J/H2sxlZ8CpOnjuXNybK/HhNjvv3Frm33+DBQZOLuhxeu8SlPTT9n1ehWCaWzeOxLVpCHhqCHlyzDNk45DPgq6seQBVoAvvQCphE/p5eZ8hM8dRO74M5qkLUYDA4/vxQq0qfPu7p1z9XH/3oR9m5cycAX/va12hsbJzwvfbH4/Hssz2A4zj6hiMiIiKTRq81RGTSOQ74AhBphcoCyKdwcgm82THqUkO055JksmlSJYORvE2i4JDIGXhtG58707b826RnnU264wX4hlZT/8T/Ehh8nMjevxDZ+xdSzSsILnw1n37BCaweKPHTdTnWDpa4ZUeBW3cWOKfT5vKlHubXT982f8u18Lo+MrkS3WNZYpkirREv9YEG7EAZsmMwsAZ89dUwNdgCjveg9xXZF73OkOl2qH/+jqoQ9enVmP39/Yd0TV9f3/jzaDQ6oXlXrlzJf/zHfwBw/vnnc+WVV07oPiIiIiIiIsc8wwBPsPoIt0G5hJlLEMglCKSHaUqPkk4nSOfL9JdDxDNlypTx2vbMOpTKMMg0nUSm6SQ8Y1up3/K/BPfeR2BgJYGBlWTrFhJc+GpOvOBM1g1VuHFjnod6ity9u/o4vc3miuNcljVN34/tPo+F17VIZotsHUxSl3Rojfio8zVg+OohG4Pe1eCNVMPUUCs4E9/hKSIykx1VIerixYvHn+/ateuQrtm9e/f48yVLlkxo3jVr1lAul8fvd+aZZ+537FOHTgH09vY+Y+zHP/5xLr300gmtQURERERE5KhkWtXt4746qOvEKOYIZOMERrcTjfeTCoWIlXyMpHKMpHMYgN+18ToWxgwpUM3VLaDvtGtwjuulbuv/Ed51O96xLbQ98kXygXYiC17JCWddwNZEgBs35vjrniIP91YfJzRZXHGch1NbLYxp+IQMA0I+m0DZJpbJE88kaAi6tES8hHz14K2rhql9ayHWDc3HQUDt5kTk6HNUhahLly4df7527VqKxSK2feBPceXKlfu8fqK2bdvGtm3bDmlsPp/noYceGn/76QGriIiIiIiI7IPtgWAT+OqwfLsIj2wnbGZobWsima8wls4zli4wlMxhG0a1mtKZvq3xT1cItDF44jsYWfJ6Itt+T92OP+Kmemhe/T0aNvyM6JwXs+jkl7LrhHp+tTHPbTsLrB0ssfYvaRbUm1y+1MMLZtlY5tSHqaYJ9QGXQrHMYDLHWLpAS9hDU8iL11dXrUZNDUDvKmheCuH2KV+jiMhkOqpC1LPOOguPx0MulyOVSvHoo48esCo0l8vx4IMPjr99wQUXTMUyRURERERE5HBZDjQuqPblHN6Ck+yl3h+lvjFArlgmmSsyksoTzxRIZIu4lonftWbEgVQlTx0jx72R0YWvIrz7Duq23YSb7iO65dfUb/0/GjvOZv6iV/LGZfP43815/rg1z9bRMp+7P8OskMnrlrpc2OXgTEMvWMc2aQx6yBZK7BlNM5TK0xbx0hD04ARbID0CPauhmIO6LmZOfwURkcNzVH03CwaDXHjhheNv33DDDQcc/5vf/IZEIgFU+6Gec845E5r3qquuolKpHNLj+uuvH7+uq6vrGR+76qqrJjS/iIiIiIjIMSvQAO0roGkp5FOQ6MNjVmgIuCxsDnJcW5gFzUECHotUvshgIkciW6RUqkz3yqk4fmLzX8aui6+j5/SPkmk4HqNSItx9N7Pvfi8nPfYR/q3lcf7zZT7ecLxLyIXuRJmvPZzlyj8k+c3mHJni9HweXseiKeiFCmwfTLK5L85wKk/ZGwVPAPrXw9BmKBWmZX0iIrV2VIWoAO94xzvGn99www2sX79+n+PS6TSf+MQnxt9+61vfetCt/yIiIiIiIjID2S40LYSOU8BbD/EeyKcB8LkWzSEPS1rDLGkLM7cxgGMZxDIFhhI5UtkiTx5xMX0Mi1T78+g++8vsPu+bxGedR8Ww8A+vo/3hz7P8nnfwHv9t/OIlNm89yUPUazCYqfD9x3O88fdJ/mt9jkR+GsJUA4Jem4aAl2y+zBP9CbYOJomVfVT8DTC0BfrXQSEz9WsTEamxoy5EvfTSSzn77LOB6nb9l770paxZs+YZY4aHh3nlK1/J1q1bgWoV6jXXXLPP++3cuRPDMMYfB6tuFRERERERkWkSaISOk6FpCeQSkOyHSjUhNQwIeWzaIl6Oa4uwpC3MrHofGDCSzjGSzJPNl2CaC1RzdQvoP/UD7HjhTxhZ+GpKThA31Uvz2us47o438/bif/HLizL866le2gIGsVyFG9bmeMPvEvxoVZaRzNQnwqYJEb9Dnc9lNJVnU1+cHbEiKU8jjO2B3tWQjU/5ukREaumoLL38xS9+wemnn05vby87d+7kpJNO4txzz2X+/PkMDg5y++23k05Xfytp2za/+tWvqKurm95Fi4iIiIiIyOGzPdC06MleqVshtre65d/xjw+xTIj4bCI+m9aIj0Su8OSBVEWSqSyWYRLw2LjT2D+15Gtk+PirGFl8+d/6pqZ6iG79DfXbfkt7+wv4h7NewZ8T8/jlxhw7Y2V+tSnP/z2R58XzHF6zxENbcGrXb1sG0aBLvlimL5ZlNGXRHKynOT6Ip7gKWo6rBt0iIkegozJEnTVrFnfeeSdXXHEFq1atolKpcPfdd3P33Xc/Y1xTUxPXX3/9M/qoioiIiIiIyFEg2ATeMIzsgNEdkEtWAzzjmcGiYxlE/S5Rv0uuWCaR/duBVLFMnoBr4/dM34/OFdtLbN6lxOa+hED/o9Rt/S3+oTWE9v6V0N6/8qboUl66/BXcWTmVX2wssXG4xO+3FvjjtgLnz3a4/DiXORFrStfs2iZNIS+ZfIk9Y1mGnQAduTHqCo/jtB4H4fZqabCIyBFkyv4leOrk+3/4h3/g3e9+96TPt2TJEh566CFuvPFGfvnLX7J+/Xr6+/upq6tj3rx5XHbZZbz5zW+msVG/BRMRERERETkq2R5oWgz+KAxtrfZK9TeA49vncI9t4gm6NARcMoUSY+k8ffEcg4ksdT4XZxorUzFMUq2nk2o9HXdsO/XbbiLU/Rd8IxvpGNnI5f4WXjTvZdx/3AX87AmLlf0l7thV4I5dBc7qsPmnEz3MDk9tmOpzLXyORTJXZGvGR302TUv6USKzlmE2zK32ARAROUIYlUplSjq+mKaJYRi8853v5Nvf/vZUTHnUi8fjRCIRhoaGaGhomO7liIiIyFGmUChw8803c8kll+A4znQvR0Tk8BSy1YrUkZ3V8G4fVan7ksoX6Y9lGUzkMQ2DsM+ZMdmflR0hsv2P1O38E1a+2nO0ZPuId72QlQ2Xcv32Ou7tLgJgm/C6JS5XHOfBY099FWi5DIlsgXI+QaOVJdq5mMis4zBsd8rXIjODXmfITPFUvhaLxQiHw/sdN0O+9YuIiIiIiIhMIsdbPXCqYwW4gWqv1EM4NT7g2sxtDLKoNUTAYzGcypLMFqdgwQdX8kYZOe6N7HjR9fSf9C5yoU6sYob6bTdxwcNv5/vut/ifs/ZwRrtNsQz/tSHPW29J8ljf1K//qcOnQqF6hsshdm1Zy44NDxFP6MApETkyHJU9UUVERERERESexTAg1PK3XqljuyCfBH/jAXt0GgbU+x2CXpvhZI7esSyDiSwRnzuth089pWJ5iM95MfGuF+IfeJy6bb8lMPA4oZ77OK3nPm6oX8w9y17Dh7ceR0+ywofuTnP+bJu3n+wl6pv6w6fqIiHyeQ+x3p2MxZLUzzmR1pYWfO7UthsQEXkupv+7vYiIiIiIiMhUcnzQvBTaTwbbB7FuKGYPfplp0Br2sqQ1RFvERzJXZDSZp1yegjUfCsMk3XIKPWd9ll0XfIdY1wspmw6+0c28cOvn+Ev087yvazumAXftLnL1zUl+vzVPeWq6/D2D67oEm2fjL44xuOUhVj+xlT0jaQqlmfLFFBF5JoWoIiIiIiIicuwxDAi1wqxTIToP0qOQHoZDCBR9rsWchgCLW0KEfA7DqVx1i//UZ5H7lQ/PYeDk97DzRdczsuAyyqZLcGQ9/9r/MR5o+wYXR7pJFeDbj2Z57+1pto+Vpn6RholV10GTt0JwaB3btm7i8V0j9MezlMoz6IspIoJCVBERERERETmWOT5oOb5alWp5IL4XirmDXmYYUOd3WNgSZEFzEMOAwUSWbGEawsgDKHnqGF52NTsv/iGxOS+mYpi0jDzCD3PX8MeWH7DQHmDjcIl/+XOKH67KkilOcXhpGBT9Tfh9Hmbnt1Ee3sHq3SOs2xtjOJljis7CFhE5KIWoIiIiIiIicmwzDAi3QccpUD+3WpF6iFWptmnQHPKwpDVMR72fbKHESDJPsTSzwr+Sr5GBk97Frgu/T6LjbAwqHB/7K392PsAP635GtBLjfzblecvNSR7YW5j69XkiVDwhWrPbmVXYxXA8yeN7xtjYGyeenfr1iIj8PYWoIiIiIiIiIgCu/29VqaZT7ZWaTx/SpV7HpKvBz+KWMPUBl7F0jkRmZm3xBygEO+g77Rp2n/dNUs0rMCtFXpi9hQf87+MT3v8hk07xiXsyfOreNIPpqe1PWnYCFP0N+JO76cxto94usmckw+O7Rtk6kCCTn1lVviJybLFrcZMLLrjgkMf+3//9H+vWrTvgGMMwuOOOOw53WSIiIiIiIiLPjWFAuB28ERjZCYkeyIyCrw7cwEEvD/tsAp4g9QGHvrEsg8ksIY+Dd4adPJ+rW0DPWZ/BN7iGhg0/xTe6mav5P17nv41v51/ODd0v5J/6ilx1godXLHSxTGNK1lWxPBQCzTipPupKebwNS0hU/GwdSNIXz9EV9dMW8WJbqgkTkallVGrQYMQ0TQzjwN9Qn5rmUMYZhkGppN8wHUw8HicSiTA0NERDQ8N0L0dERESOMoVCgZtvvplLLrkEx3GmezkiItMjG4N4T7VXaiFTDVc9oUO6NFcsMxDP0h/PUSiXqfO52NbUhJHPSaVCoPdBGjb+DE9iDwBDRpSv5l/Fr0vnMLfe4b2n+ljcMIVBcKWMkx6gbAfIRhdT9DYQzxZJ5Qu0hn3MbQoQ9urfpiOZXmfITPFUvhaLxQiHw/sdV7Nf3VQqlQM+nus4ERERERERkWnnjUDzUug8AxoXQ6kIY92QjR+0Z6rHNumM+lncGqIx6GEskyeWLhxKq9WpZRik2p/H7gu+Q9/J76Xga6KxMsKXnR9xm+eDLIw9wLtvS/KdxzKk8lO0eMOk4G/BKOfwDa3FTfUS8do0B730x7Os2j1G92iaUnmmfTFF5GhVkxC1XC4f9AHVKtR3vetdBx2rKlQRERERERGZUTwhaFoEnadXQ9VyudozNRs7aJga8trMbwyyqCWExzEZSubI5Gbgz72GRaLrInZddB2Dy/6ZohtmntHL991vcZP7MYa2reTqm5P8ZXdhaoqgDIOir5GKaeMZXo8b34ltVGiL+DANg3V7Y6zviZHMFSd/LSJyzFMTEREREREREZFD5QlC4wKYfQa0LKseHBXrhswYVPZ/EJNpQkPAZXFriK6on0K5zFAiR7E48yopK5bL2IJXsOviHzO85PWUbR/LzR38l/tF/qP0OX7/wFo++tcMvcmpOXiq5IlQdkN4Rp/AM/oERilHxOfQHPLSM5Zh1Z4xemMZyqpKFZFJpBBVRERERERE5Lly/dAwrxqmtp4AhgmxvZAeOWCY6lomHfU+FreFaAp5iGULjCTzFIpTE0g+F2XHz8iS17Pz4h8zOv8VlE2b51vrucnzCa4e+ipf/NNmbtyQozgF4WXZ8VP0RXHjO/ENrMbKjuBYJu0RH+VyhbXdMTb1xcnkZ2CFr4gcFRSiioiIiIiIiEyU44PoXJh9JrSfBJZbPYgqPQzl/Qd6QddmflOQxa0h6gMuqXyRoUSuGgLOsILKkifC0An/zK6Lfkh89kVUMHmJ9Qh/sD/Iog3/wSdv2cW6wcnfUl+xPBSCbZiFOL7BVbixnRiVEvV+l2jAZfdIhtV7xhiIZ3XmiojUnEJUERERERERkcNle6BudvUAqraTwPZCvBdSQ1Ded8BoGFDvd1jYHGRJa5iOeh/FcoXBZI5Etkh5hhWnFv3N9K94L7sv+A+SrWdiGRVeZ9/Nz3PvY/gv1/HjhwbITXZ7AsOk6G+mbHnxjGzCO7QOM5/AY1u0R7xkCyXWdMfY0p8kW1BVqojUjj3dCxARERERERE5atgu1HVCqBWSAzC2GxL9YDngj4L57B/DDaN6+FTIa9Mc8jKWyTOYyDGSymKZJiGPg20b0/DJ7Fs+3EXvmR/DO7KJunU/JTSylrfYf6K35yE+PvRBXveCpcyJWJO6hrIbpGx7cdL9WPk4+boFFAKtNAQ9ZAsltg8lGcvkmdcUpDHomdS1iMixQZWoIiIiIiIiIrVmORDpgFmnQccK8EaqoWpyAEqF/V7mdUxaw16WtIVZ1Bom4nOI5woMJXNkZ1i/z2x0CX1nf4G9Z32GuLeDNmOEb+U/yf/cdi83b8tP/pZ606YQbAMDvENr8Yxswihm8ToWbREfyWyJ1d1jbB1IkJ+BPWdF5MiiEFVERERERERkslg2hNufDFNPAV8UUoOQ6INSfr+XOaZBQ8BlUUuIpa1hWsNe8uUyg8ksyZm01d8wSDevYPCCrxFrOJGAkeP71rWMrvwtn78vTSo/+b1JS546ir4onvgufAOPY6cHMQ2DppCHoGuzdSDF2r1jjKb2//UWETmYKQ1R1dhZREREREREjkmmVd3i33FKNVANNENqGOJ9UMzt9zLDgLDPZm5jgONaw8xtCGKbBiPpHGOpAsXSzPg5u+wGGXj+pxnreiGWUeFTzs+4oO/HvPOWGBuHp+bQqXywDbOUwTu4GndsK0Ypj9+1aQ17GUsXWL1njJ1DSYqlmZJAi8iRZMp6ou7YsQOAcDg8VVOKiIiIiIiIzCymCcFm8DdCZgRie6pVqeUS+OvB8e/3Up9r4XMtGoMeYpnqFv9YukCFCgGPjdeZ3D6kB2XaDJ70bgrBWTSuv54r7duYXRjgvbe/m1cvr+e1S1xMYxJ7uxomRV8jZiGNZ2wLVi5Orm4eeOpoDnlJ5ops6kswli4wtylIxOdM3lpE5KgzZSFqV1fXVE0lIiIiIiIiMrOZJgQawd8AdaMQ74FEL6RGwBcBN1gtQ90HxzJoDLpE/S6JXJHhVJaRVIFEtoDPsQl47P1dOvkMg7GFl1EItNL66LWcz2puND7NP63+dx7va+FDz/NR753cTbFlx0/Z8mBnBvEPxslF5lMItBP02Hhtk8Fkjli2wLzGIO11Pixz5hzaJSIzl3qiioiIiIiIiEwXwwB/FFqXQefp0LQISkWI74XsGFT2v/XcNCHis5nXGOS4tjBd0QCGAcOpLLH09G71T7WfRffZX6boqWepuYebPB+nOPAEb7slxWN9k7+9H9OiGGilbNp4h9bjHdmIWUhhWyatYR+2YbKhN876nhjJ3BSsR0SOeApRRURERERERGYCbwSaFsPsM6BlGWBCrAfSw9Xt/gfgdy066n0c1x5mQVMIv2sRyxQYSebJFaanB2iufiF7zv06ufAcmowYv/J8ljPyD/Ghu9P8eHWWYnnyQ96yG6bob8JJduMbWIWd6oNKhbDPoSnooXcsy6rdo/SMZShPwXpE5MilEFVERERERERkJnEDEJ0LnWdA+4lge6tb/ZMDUCoc+FLLpCnkYXFrmMWtIRqCLtlCiaFEbloqU4v+Jvac/RVSLafiJc8P3G/ydut3/PfGHO+7I01vcvID3orlUAi0QaWAd2gNntEtGKUcjmXSXuejUoF1e2Ns6ouTzqsqVUT2bdJ6om7dupX+/n5GR0dJJBKEw2Gi0Sitra3MnTt3sqYVEREREREROTo4XqibDaE2SA1WD6FKDVZbAPiiYHv2e6llQr3fod7vkMgV6YtlGUzkCLgWfs+UHY8CQMXx03PGx2la92Pqtv+eDzk3stDq40PDV/P2P5d4/2k+zp09yYc8GQYlbxSjmMWNbcPKjZGrX0DJG6XO7+Ivltk1kiaWKTCvKUhzyIMxbY1lRWQmqtl3zkqlwq9+9StuvPFG7r33XkZGRvY7tqmpibPPPpsrrriCyy67rFZLEBERERERETn6WA6E2yHYUt3aH+uGZH91i7+/Hhz/AS8PeWz8jUGCHpuesQwjyTx1fhdzKvemmhaDy99GPthO05of8Srzbhb4B3lj+l/53P2wsq/Iv6zw4rUnN7is2F4KwVbszDC+wVXkw/PIh2bh2jYdER+j6QJrumN0Rf10Nfrx2NakrkdEjhw1+Zb5pz/9iSVLlvD617+e3/3udwwPD1OpVMYfwDPeHhgY4De/+Q2vec1rOOGEE7jjjjtqsQwRERERERGRo5dpQbAZ2k+ubvWvnwP5NIx1Qy4Blf1v17dMaIt4WdQSIuxzGE5lyRYO3Gd1MsTmvYyeMz9O2fZxYnk9t4c+RZfRz83bC7zr1hQ7xqZgTYZF0d9M2fLiGdmEd2gdZj6BYRhEAy51PoftQ0nWdscYS+cnfz0ickQ47BD161//Oi9/+cvZunXreGD69w70/vXr1/OSl7yE733ve4e7FBEREREREZGjn2GAPwqty6DzdGhaBKUixPdCdgwq++8zGvLaLGgJ0lkfIFsoMZrKHyh7nRTp1tPYc/ZXKPiaaC70cGvgE1zg3cyueJl33ZbiD1vz+80RaqnsBikEmnHS/fgGVuEke6BSxutYtIZ9jKULrN4zxp6RtA6dEpHD287/i1/8gg984AMA471CGhsbednLXsYZZ5zB4sWLiUQiBINBEokEsViMTZs28dBDD/GHP/yBoaEhDMOgWCzy7ne/m+bmZl796lcf/mclIiIiIiIicizwRqqPyCxI9Ff7psZ6wPWBt65avfp3HNOgM+oj5LXpHkszlMwS8bm49tTt789H5rLn3K/R/uBn8Y5t4cfG5/mP6Nv5xshZfOvRLCv7i7z/NB9Bd5L7kpo2hWAbVm4M79BazNwY+cg8LNtLS9hLPFNgQ0+M+JO9Un2utveLHKuMygR/vdPd3c0JJ5xALBYDIBwOc+211/KmN70J13UPen0ul+OnP/0pH/zgB0kkElQqFaLRKGvXrqWtrW0iSzrmxONxIpEIQ0NDNDQ0TPdyRERE5ChTKBS4+eabueSSS3CcST7wQ0REaqOQhdQAjO2GzChYLvjqq31V9yFXLNMXy9IXy2KZBhGfA1N4npJRzNL62NcJ9t4PwD0Nr+WqnldQqhi0+A0+cpaP4xqn5iAso5TDSQ9R9NaTj8yl6GsCwyRfLDOYzFHnd1jQHKQxuP8DveTQ6XWGzBRP5WuxWIxwOLzfcRP+NdPXv/51YrEYhmHQ1dXFypUrectb3nJIASqAx+PhrW99K4899hidnZ0YhsHo6Cjf+MY3JrokERERERERkWOb44W62dWeqR2ngK8OUoOQ6INS4VnDPbbJ7KifhS1BPLbJQDJLsTh1W9crtpfe0z/EyMJXAXD28K/466zr6PIX6E9XeN8daW7ckKM8Bdv7K5aHfLANs5jGN7AK3+Bq7PQgrgXtES+ZfIk13WPsGExSLO2/ZYKIHJ0mFKLmcjl+9rOfAeA4Dr/+9a+ZN2/ehBYwf/58fv3rX+M4DpVKhRtuuIFC4dnf2EVERERERETkEFkOhNuh41SYdRr4G6thamoQys88vMkwIBpwWdASpC3sZSybJ5ktTt1aDZPh499M/0nvpmJYdAz+lT9GvsTLZqUpV+Ana3J8+O40I5kpCC4Nk6KvkYK/ESs7jHfwcbyDa7CzwzQGHPyOzeb+BOt74iRzU/g1EpFpN6EQ9fbbb2dkZATDMHj961/PKaeccliLOPXUU7niiisAGB4e5o477jis+4mIiIiIiIgI1Z6owWboWAHtK8ANQbwX0iPPOoDK51jMaQiyoCkIwFAyR6k0dVWp8TkvYu9Zn6ZkBwiObuRr6Y/xueVDeC1Y2V/ibbekeKR3ioJL06Hob6bkbcDODOIbWIl3aB3hcoyWoIe+WJZVe8boi2Wn5BAsEZl+EwpRH3300fHn73rXu2qykKff5+GHH67JPUVERERERESEapgaboNZp0L7SdVeqbG9kI3B00JA04SmkIdFrUEaAh5G0nnSU1hxmWk6iT3nXkvB34Kb7uOKHR/mv07dyrw6k7FchY/8Jc1XHswQz01NcFmxHIqBFkreKHa6H9/ASoKj6+n0ZikXy6zdG2NLf5J8Udv7RY52EwpRH3vsMQBCoRArVqyoyUJWrFgx3rz16SGtiIiIiIiIiNSI5UBdZ3WLf+sJ1QA1thfyyWcMC7g285oCzG0MUChXGEnmKU9RTlgIdbLn3K+TiS7FKqRYsebT/HzxfbxykYsB3LazwD/dnOQvuwtTVgVasdwnw9Q6nHQfvv7HaMtuocFMsW0wwdq9Y8TSak0ocjSbUIi6fft2DMPg5JNPrtlCDMNgxYoVVCoVtm/fXrP7ioiIiIiIiMjfcbwQnQudp0PTYijmqmFqITM+xDYN2iJeFreECPtshlNZsoXSAW5aOyVPhL3P/zyJWediVEp0rP4PPuH5Jd+40MvscLUq9XP3Z/jkvRmG0lNXBVqxPBQCrZQ8YZzkXupHVjO3uIPE6BCrukfpHk1TLmt7v8jRaEIhaiwWA6C5ubmmi2lqanrG/UVERERERERkErkBaFoEs06H+jmQS0C8pxqqPinktVnQHKKzPkCmUGIsVWAqCkArlkvfKR9geHH1DJXolv/lou1f4brzK7zxeBfbhAf2FvmnPyX5/dY85SnsTVqxvRSCbZTcIN7UXroy6wmOPcHmHXvY1BefsrBZRKbOYYWo9fX1NV1MXV3dM+4vIiIiIiIiIlPAG4bWZdVt/uF2yIxCog/K1X6ojmXQGfWxsDmEz2MylMxOTR9Qw2Bk6T/Sd8q/UTZtgr0PsuCv7+Gt7Tv43gsDLGmwSBfg249m+cCdafbEpza8HA9TnQAN+b3MTm9geMdq1m7bw3Ayd/AbiMgRY0IhaiqVAsB13Zou5qn7PXV/EREREREREZlC/ii0nQQdp4K/EZIDkBqEcjWcrPc7LGwO0RbxkcgWiWeKMAUFoInO8+k++yvkA204mUFm3XsNp/T9im9e4OEdKzx4bVg7WOJtt6T4xfocxSneUl+xfRSC7RgeP7PKPdg9j7Jl3aPs6umjWNKhUyJHgwmFqFPVuFlEREREREREpphhQLAJOlZA+wpwgpDohfQIVCp4bJM5DQEWtgRxLBhMZikWJz8nyNUvYs953yI+6zyMSpmGTf/F7Ps/xms6E/zoxUFObbUolOH6tTneeWuKzSNTv6W+4vgphjoIh4LUpXcxsPEetm5cSSoxNuVrEZHamlCIKiIiIiIiIiJHOdOCcBt0nlatTjUdiHVDNoZBhYaAy8KWEM0hL2OZHMlscdKXVHb89J/6AfpWvJ+y7cM/vI7Zd76b+fGH+MK5fq4500vYNdg+VuY9t6W47vEs2SkIeJ+9zgBWtJNwIECmewM7Hr+LoZ3rqOSSU74WEakN+3AuTiQS7N69u1ZrIZFI1OxeIiIiIiIiIlIDlgN1nRBoqlakjuyshqn+enxukHmNQcI+h72jGYaSWeq8HmzbmNQlJWZfQDa6mNZHv4p3bCvtD3+esbmXcvGyqzmlNcD3V2a5a3eRX2/Oc193gfee5mNF62FFIBNiekMEW0KkEmPsfeJxskO7ae5ciFvfAa5/ytcjIhNnVCawN980TQxjcr4hVioVDMOgVNJJdgcTj8eJRCIMDQ3R0NAw3csRERGRo0yhUODmm2/mkksuwXGc6V6OiIjMFPkUjHVDbDcUc9U+qo6PdL5Ez1iGoWQOx7IIe22Y3CwVygUaN/yc+q2/ASAX7qLv1A+SD3fxUE+Bbz2aZTBdjT1eNNfhbSd7CbmTvah9y+VLpJOjNFhZWpqbCLbMrx7iZXumZT3TTa8zZKZ4Kl+LxWKEw+H9jjvs7fyVSqVmDxERERERERGZ4dwANC+GztOhfg5k4xDvxW8WmdcYZGFLCNc2GExmyRUm+VAl02Fo2dXsfd6nKXrq8MR30Xn3+wjv+BNntNn8+CVBXr7QwQD+vKPAP92c5K97CtOSQXhci0hdI4NmI9sGUwxtfYzCzodgbA+UClO+HhF5biYcok5G8KkgVUREREREROQI4Y1Ay/HVMDXcBqkhzEKChoDLopYQHXV+0oUio8k85UnOUtMtp7D7/P8g1bwCs5ynZfV3aXv4iwQrSd59io+vX+inM2wymq3w2fsyfOreDEPpSV7UPpgmNIS8lN0wW3IhtvaOMPjEQ+R2PgTxXihrV67ITDWhhiA7duyo9TpERERERERE5EhjGNXt/N666mNgI1RKeLx1dDX4ifgcesYyDKeyBF0Hn8eatKWUvPX0PO9T1G39LY0bfkaw9348Y1voO+XfWNa0jB+8KMAvNuS4cUOe+/cWWTWQ5K0nennJfAdzkloW7k/QaxPw2KRyLlsyOSJ7emka7ifcNAtv83zwN1S/tiIyY0woRO3q6qr1OkRERERERETkSGWa1a39pg0DGyA9DP4G6vwOAY/NYCJLbyxLKlmkzudiW5MUEBomYwsvI9O0nNZHvoyb6mXWvR9hZMnljCx6HVed4OXcToevP5xh00iZbz6a5c5dBd53mpdZ4ckLePe5VKMapgY9Nsmch22ZDOEdO4gO9hBp6cLfPBd89VO6JhHZv8PuiSoiIiIiIiIigmFAXSe0Lq++nRwAwLEM2ut8LGoN0RDwMJrOkcwWYRI7+uXqFrD7vG8R77wQgzINm37BrPs+gp0eYG6dxTcvCvAvJ3vwWrBmsMRbb0lx44YcxfI0tBl8MkxtDIcoBlrYlXbYvnUT3Wv/SmrPWsglpn5NIvIsClFFREREREREpHbCbdB6IlgeSPTCk+efhDw285uCLGgOgQGDySyF4uT1Ja04fvpPeR99p/wbJduHb3g9s+96D4Ge+7FMg8sWe/jhS4KsaLEolOEna3K869YUT4xMU19SA/wem4a6COVQO90pg+2b17B79d0k9m6CQmZ61iUigEJUEREREREREam1YBO0LQc3BPEeqFTDUsuE5pCHJS0hWsNe4tkisXSByTxnOtF5PnvO/zbZuoVYhSTtD3+B5lXfwShmaQuafOk8Px88w0vINdg2Vubdt6W4YU12eqpSn+RzLRrq6yHSQV+yxM4Nj7Bz1V3Ee7dSKeambV0ixzKFqCIiIiIiIiJSe/5oNUj1Nzzr5HmfazG3MciiliAex2QomSVbmLwK0EKgjT3nfIWRha8GILLzFjr/8n7c+E4Mw+DiuS4/uSTAebNtyhX4rw153ndHmp7E5FXKHgqvY1EfbcCIdDKYyLBz3QPsWPUXRnt3Ui4Wp3VtIseaCR0s9ZTHH3+cTKZaTj5v3jxaW1ufNeZTn/oUP/vZzw7pfpdddhnXXnvt4SxJRERERERERGYKb6QapPavr1akhtuqh09RbaEaDbgEPDYD8Sx98SzpXIk6v4s5GSVfpsPw8VeRaTqRlse+jiexm86738/QCW8hNucl1HtNPnqWn+fPKvDNRzJsGi7x9j8neecKLy+c62AYk3QY1iHwuBaeaDP5QoGx2DCJkXvxNbQT7VhItKkd05raQ7FEjkUTDlHXr1/PaaedRqVSoaGhgXXr1u1z3PDwMDt37gQ44DecSqXCt771La666iqWLVs20WWJiIiIiIiIyEziBqD1BDAsiO+FUAtY7viHPbZJZ9RP2OfSM5ZmOJUl4Nr4PYdV97Vf6eaT2X3Bf9Cy8psE+h+lefX38A+spP/k91B2w5w32+G4BosvPZhh7WCJax/O8khvkX89zUfInb4gFcB1HNyGVor5AqnRAVIjfQw1dNDQsZBoYyuWpQ3HIpNlwn+7PvOZz1AuV8vav/Wtb9Hc3HzA8YZhUKlU9vsAKJfLfOELX5jokkRERERERERkJnJ81SC1fi4kBqCYfdaQiM9mQUuIuY1BipUKQ8kcxdLk9CUteeroOfOTDC77ZyqGTbD3QWbf9R58Q2sBaA6YfPV8P1cv92AZ8Jc9Rd72pySrB2bGFnrbdQg2duCLNJMb3svutX9l4+oH6B8YoFCa3hYEIkerCf1aJx6Pc9NNN2EYBosXL+aKK644pOuuv/76/X7si1/8Ik888QS//e1vicViRCKRiSxNRERERERERGYi24XmpWCYMLIdAlFw/M8Y4pgGbREvIZ9N71iWoWQOj20R8thQ6yJQw2BswSvINC6j9dGv4Cb30nHvRxlZ/FpGFl+BZVpccZyHFS02X3ggQ0+yzL/fmeZ1S13etMyDY01vVSqA5XrwN3VSzmXIj+xg98he+hvn0NQxn4b6elxblakitTKhEPUPf/gD+XwewzB473vfe8jXXXnllfv9mOM4vOENbyCXy/G73/2ON77xjRNZmoiIiIiIiIjMVJYNzUvAcmB4S/WwKU/oWcOCrs38xiB1Poe9YxkGkzkiPmdSQsFc3Xx2n/dNmtb8kMju22jYfCOB/sfoO+X9FEKdLG6w+MGLAnzv8Sy3bC9w48Y8K/uLfPhMH7PCM6MXqenx4fV04c2lyA1toXtkD33RuTR1zKW5PqIwVaQGJvS36P777x9//vKXv7wmC/mHf/gHfD4fAA899FBN7ikiIiIiIiIiM4xpQeNCaD4O8inIxvY9zISmkIfFrSHaIh6S2SJj6QKVSdjhX7F9DKz4V3pP/XdKTgDv2BZm3/Ue6rb8BiolfI7Bv53u4xPP9xFy4YmRMv/y5xR/2pYfb1E4I3gCeBo6qfd7cIc20LPuHjZs28FIKj/dKxM54k0oRH388ccBWLp0Ka2trTVZiM/nY/ny5VQqFR577LGa3FNEREREREREZiDDgPo50HI8FHOQHtnvUJ9jMachyMLWIF7XZCiRpVicnOAyOetcdl3wXVItp2CWCzSt/3/MuudDOMm9AJzd6XDdi4Oc1GyRLcHXH8nymfsyxHMzqA+pYVDxRnAbOmlwCpR61rB+2062DSTJF2fQOkWOMBMKUXfv3o1hGMybN6+mi3nqfj09PTW9r4iIiIiIiIjMMIYBdbOhdTlQgeTAAYdG/S6LmkO0RryMZXIks5NzyFPJ10jPmZ+i/6T3ULJ9+EY2Mvuu9xDZ9juolGnym3z5fD//fKIH24R7u4u89ZYUK/tmxqFT4wyTcrCZqFsimtjK9r29rOkeU1WqyARNKEQdGxsDoKWl5aBjFy5cyLnnnss555xz0LGhULUPyujo6ESWJSIiIiIiIiJHmnAbtJ4IlguJXg60X99jm8xpCDKvKUi5UmEkmac8GcWVhkF8zgvZfcF3STedhFnK0bz2h3Tc+xHsVB+mYfDapR6+dVGAzpDJcKbCh+5O86NVWfKlGbS9Hyj6mwmQoquwg2RsjFV7RlWVKjIBEwpRC4UCAOVD+E71nve8h7vuuou77rrrkO+bz+u3IiIiIiIiIiLHjGATtJ0IbujJIHX/eYNpQkvYy6KWECGvzXAqO2mBYNHfzN6zPsvAie+gbHnxD6+j6853EdlxM1QqLIpafPdFAS6d71ABfrUpz7/enmJ3vDQp65kQw6Dgb8bNj9JZ3EHILLBlIMma7jGGk7npXp3IEWNCIWpDQwMAw8PDNV3MU/eLRqM1va+IiIiIiIiIzHD+KLQtB18U4j1QPnAQGfLaLGgJ0hbxkcgWJm17P4ZBbO4l7LrgO6QblmGWsjSv/h4d938cOz2AzzZ472k+Pv0CH2HXYOtomXf8OcXvt86gQ6cMk0KgFSszRH1yK21+iKULrO4eY+tAglxxBoW+IjPUhEPUSqXCpk2barqYjRs3AtDY2FjT+4qIiIiIiIjIEcAbgdYTINjyZJB64GDUtUzmNASY3xwEYCiZm5zt/UAx0MreF3yBwRP+mbLlwT+4itl3vovwrluhUuGsWQ7XvSTAihaLXAm+/WiWT9yTYSw7Q7bNGyYFfwtOqg//2GZaAgYB12brQIo13TFVpYocxIRC1OXLlwOwZcsW9u7dW5OFdHd3s2XLFgzDGL+/iIiIiIiIiBxjPMFqkBrugHgvlA7c8s8woCnoYWFrkHq/y1AyS64wScGlYTI2/xXsPv/bZKJLsIppWh7/Nu0PfhorM0yjz+SL5/l5+8keHBMe7CnytltSPNo7Qw6dMi3ygRacVC+e0S347QqtYS/xTIFVqkoVOaAJhagXXnjh+PPvfve7NVnI0+9zwQUX1OSeIiIiIiIiInIEcnzVILV+DiT6oXjwKsmgazO/KcjsqJ9Urkg8U4RJ2k1fCHbQffaXGTz+zZRNm0D/o3Td+Q5Ce+7CBF612MN/XBygK2wykq3w4b+k+f7KGXLolGlTCDTjJLrxjG7BokRzyEvQtZ/slRpjSFWpIs8yoRD1JS95Ca7rAvCd73yHrVu3HtYinnjiCb7zne8A4Loul1566WHdT0RERERERESOcLYLzcdBdD4kB6GQPugljmUwq97PgpYgllnd3l+arODSsBhb+Cr2nPdtsnULsQopWh/7Gm0Pfx4rO8r8eovvvjDAyxc6APzmiTzvvi3FztgMqPQ0HYr+Rtz4Ljxj26Bcwu/atEd8xDPVXqlb+lWVKvJ0EwpRW1tbufrqq6lUKiSTSS655BK6u7sntIA9e/Zw6aWXkkqlMAyDN7/5zbS0tEzoXiIiIiIiIiJyFLFsaF4CTYshMwb55EEvMQxoCLgsagnREPQwks6RzU9eGJgPz2bPOdcytPQNVAybYO+DdN35ToJ778FjG7z7FB+fPdtHncdg+1iZd96a4rdPTP+hUxXLpehrwBPfgRvbDpUypmGMV6VuG0yyes8YQ8nctK9VZCaYUIgK8LGPfYyGhgYMw2Dr1q0sX76cn/zkJ+TzB+5V8pR8Ps+Pf/xjTjzxRLZv3w5ANBrlYx/72ESXJCIiIiIiIiJHG9OChgXQtBRySUiPHNJlftdiXlOA2dEAmWKJsXRh0rb3Y1qMLr6c3ed9nVx4LlY+TtsjX6b1kS9j5mKc2eHww5cEOK3NJl+C767M8oE702wdnd5Kz4rtpeCtxxPbjhvfBU+GpX7Xpi3iI5ktsWrPGFsHkmQLqkqVY5tROYxfJ9x55528+MUvplQqUalUMAyDaDTKK17xCs444wyWLl1KXV0dgUCAVCrF2NgYGzZs4OGHH+amm25iZGRk/LcZjuPw5z//mfPOO69Wn9tRLx6PE4lEGBoaoqGhYbqXIyIiIkeZQqHAzTffzCWXXILjONO9HBEROdZVKpDohcHN1a39wZZqwHoIRtMFukfTJLIF6v0ebMuYvHWWC0Q3/zfRJ36FUSlT9NQxcOI7SbU/j0qlwk1bCvxodZZ8CQzgkvkOV53goc474Tq3w2YW0lj5GNm6JRTCs6vlvE/K5EuMpHNEAy5zG4M0Bl0M4/C/fnqdITPFU/laLBYjHA7vd9xhhagAv/3tb7nqqqtIJBIA42HqwTw1rlKpEA6H+elPf8orXvGKw1nKMUchqoiIiEwm/XAjIiIzUmYMhjZXD5wKNoHtPbTLCiX2jmYYSOQIujY+z6EFsBPlGd1Cy8pv4EnsBiA+63wGl7+NshukP1XmR6uy/GVPEYCAA2843sMrFro4kxnwHoCZT2IWUuSiSymEZj3jY+VKhZFUnlK5wuyon9kNfrzO4X399DpDZopDDVEP+9ccr3zlK3n44Yc555xzxqtKn/7fv3/8/cfPO+88HnnkEQWoIiIiIiIiInJwvjpoO6l64FRqGLJjh3aZYzG3McjcxgD5UpnRZJ7JbPWZq1/InvO+ycjCV1PBJNx9F113vgN/3yO0BEw+9nw/X7/Az4J6k1QBrluV4623pHhwb2FaepCW3SBlx4dndDN2qvcZHzMNg8agh7DXYftQklV7xhhMqFeqHFtqUiu+aNEi7rrrLh544AGuvPJKZs+evd+/SJVKha6uLq666ioeeOAB7rzzThYuXFiLZYiIiIiIiIjIscD2QPNSaFsO5VJ1m3+lfNDLLBPaIl4WtoTwey2GklkKxYNfN1EVy2X4+KvoPucr5IMd2NkROh78NM0rv4VZSHFCs813Lg7w/tO81HkMuhNlPn5Pho/8Jc2u2NT3IC27YSqWi3dkE3a6/1kf97kWbREfmXyJ1XvG2NKvXqly7Djs7fz7s2fPHnbv3s3IyAiJRIJQKEQ0GqWrq4tZs2Yd/AZyUNrOLyIiIpNJ2+xEROSIkB6p9klNDUKwuRqwHoJcsczesTT98Rxe2yLotSd1mUYxS8PGn1O37XcYVCh66hg6/moSneeDYZAqVPjF+hy/eSJPsQymAS9f6PLG4z2EPVO7xd/KjmIAmYbjKfka9zkmWygxnMpR53dZ1BIiGnCf0xx6nSEzxZT1RJ3J8vk8//3f/80vf/lL1q9fT39/P/X19cydO5fLLruMq666isbGfX8zmIihoSHuu+8+Hn74YdauXcu2bdvo6ekhmUziOA719fUsW7aM8847jze96U10dHQc1nwKUUVERGQy6YcbERE5YhQyMLQVxnaBNwye0CFdVi7DYDJL91iGYrFCnd/FnOTznbxD62h5/Nu4qR4AMtHjGFj+dvJ18wDYmyjzw1VZ7t9b7Zcacg2uPMHDS+c7WObUhal2ZoiKYZNtPIGSt36fY8qVCkPJHB7H4oT2CBH/ob9e0OsMmSmO+RB106ZNXHHFFaxatWq/Y5qbm7n++uu55JJLajLnS1/6Uv74xz8e0liPx8OHP/xhPv7xj2NO8Du0QlQRERGZTPrhRkREjijlEozthqEtQAUCTc84Zf5AEtkie0bSjGXyRHwurj25SapRKlC37bdEN9+IWcpRwSQ29yUML30jZTcIwMq+It9/PMvOWLXdwJyIyb+c7GVF6+RWzD6dnR6gYvnINB5P2VO333H98Swhr82yjggBz6GtT68zZKY41BB16v7mTaHu7m4uvPBCenqqv9UxDINzzjmH+fPnMzg4yO23304mk2FgYIBXvvKV3HLLLVxwwQU1XUNjYyNLly6lq6uLYDBIOp1m69atPPzwwxSLRXK5HJ/61KfYvn07P/3pT2s6t4iIiIiIiMgxx7QgOhfcIAxugngPhFrAPHj0EfLaLGgJ0juWpTeWwbEsQl77UDPY56xiOYwueg2JWefRuP7/Edp7D3U7/khw770MH38l8dkXsaLV5gcvCvDHbQVuWJtjZ6zMNXenOavD5q0neekITXLJLFD0NWGnB/AObyTbuIyyu+8K3+aQh95Ylif6EyxtC+N1rElfm8hUm1Al6mc+85nJWMszfOITn5jwteeccw733HMPAF1dXdx0002ceOKJ4x8fGhri8ssv54477gAgGo2ybds26urqDmvN1157LaFQiAsvvJAFCxbsc0x/fz/ve9/7+OUvfzn+vv/5n//h1a9+9XOeT5WoIiIiMplUISIiIkesfAqGnoCxPeCPghs4pMsqFRhO5emNZUhkC/gcm4Bn8sLUp/gGV9G05jo8iT0AZOoXM7j87eTqqwdxx3MVfr4+x++25ClXwDbhskUurz/eQ8CZ5MVVKjipPkqeerKNx1N29v21LJUr9MUzzKr3s7g1hGMdOOTV6wyZKSZ1O79pmhiT/B2kVJrY6W4333wzl156KQCu6/Loo49ywgknPGtcKpVi+fLlbN++HYAPf/jDfOELX5j4gp+DSqXCRRddxJ133gnARRddxG233fac76MQVURERCaTfrgREZEjWqkIIztgeCvYDvgP/efmQqnCSCpHXyxLKl/C51gEPTZMZhRSLlK37Xc0bP4lZjFDBYP4nBcxdNybKLvVYGdXrMQPHs/yaF81M6nzGFy93MML505yv9RKuRqk+hrJNBxPxfbtc1ihVGYgkWVuY5CFzUHMA6xJrzNkpjjUEHXCtd+VSmXSHofju9/97vjzK6+8cp8BKkAgEHhGRe11111HsVg8rLkPlWEYvPnNbx5/+/HHH5+SeUVERERERESOGZYNjQug/SQwbIjvhfKh/dzvWAYtYS9L2sLMbQyAUT2AKp2bxNzAtBlbeBk7L/wB8VnnYVAhsvMW5tz2NiI7boZKia6IxRfO9fO5c3zMCpmM5Sp8/ZEs77otxdqBSVybYVIItGBlhvCObMIoZvc5zLFMGgIedgwl2TWcOuyMR2QmmVBP1HPOOWfSK1EnIplMjm/RB54RVO7Lq171Kt7+9reTTCYZGRnhr3/9a817o+5PU1PT+PNEIjElc4qIiIiIiIgcUwwDwm3V7fxDT1T7pAYawdl3JeXf89gmbREv9X6X4WSOgUSOwXiWkNfB605O38+Sr4H+Uz9AbM6LaV7zAzzxnTSv/h7hXbcyuPztZKNLOKPdYUWLzU1b8vzn+hxbR8u8/84053ba/PNJXloCk9Av1bAo+FtwU31UMMg1LKVieZ41zOtY1Ptdtg6mcB2LjrpD+1qLzHQTClHvvvvuGi+jNu6//35yuRxQrTQ97bTTDjje6/XyvOc9b3wr/Z133jllIeqGDRvGn8+ZM2dK5hQRERERERE5JnnD0Lq8GqaObIdiFnz1h365Y9JR7yMadBlKVMPURKJQDVMn6RClbOMydp/3LSI7/kjDxv/EO7aVzr9+gNjsixg+/irw1PHqJR4umuNww9ocf9pe4C97ijzQk+Q1S1xet9SDz65xAZxpkQ+04KR6wbTJRheD+eyt+H7XplCq8ERfHMcyaA55a7sOkWkw+Ue5TaGNGzeOPz/hhBOw7YNnxCtWrNjn9ZOpp6eHa6+9dvztiRwqJSIiIiIiIiLPge1C0xJoOxEqQLwPys/tPBafY9EZ9bOkLURHnZ9cocxQIke+WJ6cNZsWsfkvZ9dF1xGffREAkd2303X724hs/z2US9R5Td57mo/vvTDAic0W+RL81/o8V/8xyZ07C7XfUm/aFALNOIluPKNb9tsiIeJzMDB4oi/BWDpf2zWITIOjKkTdvHnz+POurq5Dumb27Nnjzzdt2lTzNT0lnU6zYcMGvva1r3HyySfT09MDwNKlS/nQhz40afOKiIiIiIiIyJMMAyKzoOPkaiVqvAeKued8m4Br09XgZ3FbiJaIh3S+yFAyR2GSwtSSt57+Fe9lzzlfJRuZj1VI0bzmOmbf/a94h9cDML/e4qvn+/nE8320BgyGMhW++GCGLz+YJVOsdZDqUPQ34sZ34Rnbvt8wuiHoIVsos6kvQXIy+8mKTIGjKkQdHh4ef97S0nJI17S2to4/HxkZqdla7r33XgzDGH8EAgGOP/54PvCBDzAwMADAJZdcwv33308oFKrZvCIiIiIiIiJyEL766oFT0XmQGoJsfEK3CXls5jYEWdIapinoIZErMpLMU6x1aPmkbHQpe877OgMnvoOSE8QT30nnPdfQ8ujXsLIjGIbB2Z0OP7kkyJXLPJgG3LGrwHtuS7En/tyqbg+mYrkUfQ144tvxjG3BKO07jG4OeYhlCmzui5Mt1HYNIlNpQj1RZ6pkMjn+3Oc7tMbFTx/39OsnU319Pd/73ve4/PLLn9N1uVxuvOcrQDxe/SZfKBQoFAo1XaOIiIjIU68v9DpDRESOThbULwTLB8PbINcHgaZqtepz5HVMZkf91PtdBhI5RlN5TCDoc7CtWh/MbTLS9RJirWfRtOnnRHbdSrj7LgJ9DzK0+PWMzn0plmlzxXEuy5pMvvBAlp2xMu+6NcX7TvNydueze5hOfCkeSm499tgOnFySfN18yu6zC8Wa/Db9Y2ksyixqCeFYpl5nyIxxqH8Gj6oQNZvNjj93XfeQrvF4/naSXCaTqdla2tvbeec73wlApVIhkUiwefNmVq5cyejoKFdccQU//OEP+cEPfsCiRYsO6Z5f/OIX+fSnP/2s99911134/f6arV1ERETk6Z46hFNEROTot7emd+sfrentni36j9R5nsfy7p9Rn95Oy/qf4Nt2C2tnvZGh0HG4wPuOh58+YbEtYfD5B7KctzPNy2eXsWq6N9kHo0noWX3AUbuefDydXmfIdEun04c0zqjUvMPw9Ln00ku5+eabAbjmmmv40pe+dNBr/vSnP3HJJZcAEAwGSSQSk7rGnp4ePvrRj3LDDTcA1arUu+++m+XLlx/02n1VonZ2dtLb20tDQ8NkLVlERESOUYVCgdtuu42LL74Yx6lh1YqIiMhMlM/AyDYY2wP+OnADh3W7chlimTwDiRyxTB7HtAh6HczJaKxYKRPZfRtNG3+Kna/mGvH2sxk4/mqKvkZK5Qo3rM3zP5urBzwd12jxkTO9NPpruxgrO4pRypMPd1EIzwbzma8fcsUSw6k88xuDdEQcbr/9dr3OkGkXj8dpbGwkFosRDof3O+6oqkQNBoPjzw+1qvTp455+/WRpb2/n+uuvJxwO8+1vf5vR0VEuv/xy1q5di2VZB7zW4/E8o3L2KY7j6BuOiIiITBq91hARkWOC44BvOfjDMPQEVPLgP4yCJQuaHS/RoIexdIH+eJaxTB6PbRHy2hPpGnDAyZJzX0y64/k0bPxPIjv+RLjnHgIDj9J7+kfJNJ/EW0/2cnyTxVceyrBhqMS7bkvz0bN8nNRSw2jIH4ViBn9iO4VShnzdAsru37IWn2UTNSx2jWVx7WqAq9cZMt0O9c/fUXWw1NOrMfv7+w/pmr6+vvHn0Wi05mvany9+8Yvj6fbGjRv505/+NGVzi4iIiIiIiMg+mBY0zIf2k8GwId6z35PnD5VtGjQGXRa1hljYHMS1DYaSWZLZ2p9WX3ZDDJ74L+w57xtk6hdjFTO0P/gpAj33A/D8WQ7fe2GQeXUmY7kK19yd5sYNOco13KRcsX0U/K046T58g6ux0wPP+LjftQm4NtsGJ3cnsEitHVUh6uLFi8ef79r191029m337t3jz5csWVLzNe2P3+/nrLPOGn/7vvvum7K5RUREREREROQAQq3QcTIEGqtBanHfJ88/F45p0BTysKQ1zLymanXmYCJLsVT7Lou5uvnsfcGXSLSfhVku0vbwlwjvvBWAjpDJty4K8MK5DuUK/GRNjk/ekyGRr+E6TItCoA3KebyDa3BjO6D8t9A45HWwjWokNZrO125ekUl0VIWoS5cuHX++du1aisWD/1Zn5cqV+7x+KtTX148/Hx4entK5RUREREREROQAvBFoPRHq50JqCHK1qZx0LIPWsJfFrSGaQ17G0rlJqUqtWA59p11DrOuFGJRpWfVt6rb8LwBe2+ADp3t532leHBMe7Cnyjj8n2Tp6eFW3z2AYlHwNlN0AnpHNeIc3YBT+doBPXaB6IPjW/iSJ7KGdji4ynY6qEPWss84a7xmaSqV49NFHDzg+l8vx4IMPjr99wQUXTOr6/l5vb+/486lsJSAiIiIiIiIih8DxQstx0HI85NPVMLVGW9/9rsW8xiDzm0MADCVyta9KNSwGTno3IwtfBUDT+utpWH8DVCoYhsEl812+dVGA1oBBX6rCe25L8adtta0MLTsBCoEmnFQPvsHVWJlnFpElcgU29yXI5GsY4IpMgqMqRA0Gg1x44YXjb99www0HHP+b3/yGRKL6m6RoNMo555wzmct7huHhYR544IHxt6e6ClZEREREREREDoFpQXRutU+q5UKi97D7pI7f2oTmkIfFrSEaQx5GJ6Mq1TAYPv7NDB1/FQDRLb+medV3oFL9HBZGLb73oiBnttsUyvD1R7Jc+1CGXLGW2/sdCoE2zGIa39BqnPguqJQBaA55GUzmeKI/Qb5Yrt2cIjV2VIWoAO94xzvGn99www2sX79+n+PS6TSf+MQnxt9+61vfim1P/ES6kZGRQx5bLpd517veRS5X7ani8Xh46UtfOuG5RURERERERGSShVqqQWqgqWZ9Up8yXpX6ZK/UoWTtq1JHF76a/pPeTQWTyK4/0/rIVzFK1W30Idfg02f7uHq5B9OAP+8o8J7bU+xN1DDUNAyK/ibKlhfv8Ebc0c0AmIZBa8hLTyzD1oEEpXLte8SK1MJRF6JeeumlnH322UB1u/5LX/pS1qxZ84wxw8PDvPKVr2Tr1q1AtQr1mmuu2ef9du7ciWEY44/9Vbf+7Gc/47TTTuNnP/sZ8Xh8v+tbs2YNl1xyCTfeeOP4+/793/+dhoaG5/JpioiIiIiIiMhU84ah7USIzqtpn1QAy4SWsJdFrUEagx7GMvmaV6XG57yIvtM+SNm0CfXcS9uDn8EoZoBqmHnFcR6+dJ6fOo/B9rEy77w1yf3dte1XWnaDFP2NeBLd1XmzMWzLpDnoZfdImh1DSSo1apkgUksTL72cwX7xi19w+umn09vby86dOznppJM499xzmT9/PoODg9x+++2k09VmxrZt86tf/Yq6urrDnvfRRx/lyiuvxLZtlixZwuLFi6mvr8cwDIaHh1mzZs14cPuUV73qVXzyk5887LlFREREREREZArYHmg+DtwADG2BYhb8jWAYNbl9wLWZ1xgk5LXpGcsylMxR53OxrdrcP9nxAkpOkPaHPkdg8HE67vsYPc/7FGW32pv15Bab778owGfvz7BhqMQn783w2iUlrl7uwTJrs4aK5ZIPtMJoDN/wWoqVhRBoI+r3sH0whWuZzG4I1GQukVo5KkPUWbNmceedd3LFFVewatUqKpUKd999N3ffffczxjU1NXH99dc/o4/qRD11oBVAsVhk3bp1rFu3br/jQ6EQn/rUp/jXf/1XLMs67PlFREREREREZIqYZrVPqhuAgY2Q6IFgC5i1iVksE1rDXoJem57RapDqdywC3trcP9N8Et3P/zwdD3wS3+hmZt1zDXvP+iwlX3WXbKPf5GsX+Pnx6hz/uznPrzbl2TxS4iPP8xH11WhTs1G9T9kw8Q6tw8wnMCJzKXkcnhhI4toWrRFvbeYSqYGjbjv/U5YsWcJDDz3ET3/6U1784hfT2dmJ67o0Nzdz5pln8pWvfIUNGzZw6aWX1mS+f/mXf2Hz5s1897vf5U1vehOnnHIKTU1NOI6D4zg0NDSwbNky3vCGN3DDDTfQ09PD+9//fgWoIiIiIiIiIkeqYDN0rIBAC8R7q1Wptby9azO/Kci8pgAlKgwlc5Rq1Cs1F11M99lfpuiN4knspvOeD+Ike8Y/bpsGbz/Zy8fO8uGzYfVAiX/5c4q1A7VtMVD2RCh663FjO/AOrSNsVCtRN/fFGU7Wru+syOEyKmo0ccSKx+NEIhGGhobUU1VERERqrlAocPPNN3PJJZfgOM50L0dERGTmKuarW/vHdoIbrPZOrbFErkjvWJahZJaAa+P31KYq1U7103H/x3BTvRQ9dew96zPkI/OeMWZPvMRn7suwM1bGNOAtJ3p49WIX4zBaGJTKFTbvGWVxZ321TUClhJMepGx5ydUvordUh8e1WNYRIeLT6xCZPE/la7FYjHB4/393j9pKVBERERERERGRKWG70LwUWo6HUh6SA1DjmrWQx2ZeU4C5jUGK5QrDNapKLQZa6D77K+TCc7FzY8y658N4h9c/Y0xn2OLbFwe4sMuhXIEfrsrxmfsypPI1/BwNi0KgFajgHVpDR3E3mWyGJ/oTpPO1rX4VmQiFqCIiIiIiIiIih8s0oX4OtJ0Ejh/iPVCubfhnmwZtES+LWkLU+11GMzkyudJh37fkraf7BV8k03AcVjFFx/2fwN/3yDPG+GyDa8708p5TvDgm3Ntd5J23pdgxdvjz//1aSp4Invg2Zue2MTY6zBN9CXLF2s4j8lwpRBURERERERERqZVgE7SfDKHWap/UQqbmU4S8NvObg8xpCJIvlxlJ5imXD++eZTfI3ud9hlTLqZilHO0PfY5g91+eMcYwDF620OUbFwZo9hvsTZR5920p7u8uHN7kf6di+yj4W3Ez/czJPcHIwB629CcplA7zkxQ5DApRRURERERERERqyROE1uXQuBDSI5CN1XyKp6pSF7eEiPgdhlNZMvnDq9as2F56zvgY8VnnYlRKtD56LZHtf3zWuMUNFt9/UYDT2ixyJfjMfRnu2VPbIBXTohBow6oUmJ3dzPCu9WzpiylIlWmjEFVEREREREREpNZsF5qWQNtyKBUg2V/zPqnw9KrUAPlSDapSTZv+U/6NsbkvxaBC85rvE930y2etPewx+ezZfi7scihV4HP3Z7h7d42DVMOg5GvA8IToKOxmZMdqtvaOUFSQKtNAIaqIiIiIiIiIyGQwDKibDe0rwAlMSp9UAMc0aK/zsbglRNjnMHK4VamGyeDytzG8+AoAGjb9F41rfwSVZ4aXlmnw72d4uXhO9cCpLz6Q4c6dNQ5SgbITgGAjrcVeRnasYmvPoIJUmXIKUUVEREREREREJlOgATpWQKht0vqkQrUqdUFLkNnRAPlimdHUYVSlGgYjS/+RgRPeCkD99t/RsvIbzwqBLdPgA2d4efG8apD65Ycy3LYjf5ifybNVLA+VcAstpQFGtq9k294BSuXaV/aK7I9CVBERERERERGRyeYGqlv7GxdBZhQyY5MyjWMadNT7WNQSIuS1GU7lyBYmXpUam/9y+la8n4phEt5zF20PfwGjlHvGGNMweN9pXl66oBqkfvWhLLdsr32QiulQCbfTRIyx7Y+wY89eBakyZRSiioiIiIiIiIhMBcuBpsXVQ6cqlUnb3g8Q9tksaA7RWe8jnS8RSxdggnljYvYF9J7+UcqmS7DvYdrv/yRmIfWMMaZh8J5TvLxioUMF+NrDWf64dTKCVAvCbdQbaUa2PcKu3bsUpMqUUIgqIiIiIiIiIjJVDAPqOmHWKRBshXgfZOOTMpVjGcyq97OwJYjHMRlM5igWJxY4ptrOYO9Zn6Fk+/EPr6Pj3o9g5caeMcYwDN65wstli1wAvvlolpu2TEKQapgY4TYiTonhrY+we+dWygpSZZIpRBURERERERERmWreCLSdCK3LoFyYtKpUw4Co32Vhc4jWsIexbJ5kdmLzZBuXsfcFX6DoRvDGtjHrnmuw0wN/N5/B20/28Nol1SD1O49l+c3m3L5ud3gMAzPUQtjrMLztUXZv30hZh03JJFKIKiIiIiIiIiIyHSwbonOh4xQINFcPncolJmUqr2MypyHI/KYgFWAomZvQoVO5ugV0n/MVCr4m3OReZt3zQZxE9zPGGIbBW070cPnSapD6/cdz/M+mSQhSATPYQMAfYmTbSrq3rqVcmnj/V5EDUYgqIiIiIiIiIjKdfPXQfhK0LINirrrFv1z7MNA0oTnkYWFLkKjfZTiVndChU4VgB93nfJV8cBZOZohZ930EJ9X7jDGGYXD1cg9vOL4apP5wVY4bN0xOkGoHInhCUYZ3rWHvlpVUipPQQkCOeQpRRURERERERESmm+VAw7wnq1Kj1e39+eSkTBXy2MxrDtJZHyBbKDGWKlB5ji1Fi75Gus/+MrnQbOzsCB33fmSfW/uvPMHLlcs8APxkTY7/XDc5QarrD+GEmxnatZG9TzxGpZCZlHnk2KUQVURERERERERkpvBHoe1kaFoK+TQkJqcq1TENOqM+FjSH8LomQ8ksheJz299f8kTY+/zPkw924GQG6bjvo1iZoWeNe8MyD1cvrwapP12X46drs1Sea2p7CDxeP05dG4N7ttC7+REquckJoeXYpBBVRERERERERGQmsV1oWggdp4K37smq1PSkTFXvd1jUEqIt4iWWLZB4jodOlbz17H3+5yn4W3BTvcy672NY2dFnjbviOA9vPakapP7n+jw/XZd/ztWvh8Lj8WJHOujv2U3fEw9TyYzVfhI5JilEFRERERERERGZiQIN0LECGhdDLg7JAajU/gR6j109dGpBcxCD6qFTpdKhJ5xFXyPdz//Ck4dNddNx/8cwc7FnjXvNEg//cnI1SL1xY57f7TYnpSLV63WxIu309fUysPkhKsnBms8hxx6FqCIiIiIiIiIiM5XtgebF1apUNwSxvTAJ/T4NA5qCHha1BmkIeBjN5MjkD72NQDHQwt7nf56iN4onvouO+z+BuY+erpct9vCuU7wA3Nlj8sPVuUkJUn0eByvUTs/QGINbHoF478EvEjkAhagiIiIiIiIiIjNdsOnJqtSFkIlBapDJ2A8fcG3mNQXoigbIF8uMJg99230h2E738z9P0Y3gjW2j/YFPYhae3YbgFQtd3n1KtSL1/54o8L2VkxSkem3MUDPdI2kGtzwMo7sm5WsmxwaFqCIiIiIiIiIiRwLHC01LqmGq7YNYNxSzNZ/GNg3a63wsbAkR8NoMJbPkD/HQqUKok73P/xwlJ4RvdDPtD34KYx9rvHS+y+XzShjAb7fk+fZjWcqTEHD6PTZmoIFdiQpD21fC0FYo174lghz9FKKKiIiIiIiIiBwpDANCLTDrVIjOh/QopIcnpcIy4rNZ2BKko85PMlskninCIUyTj8xl7/M/S8kO4BveQPuDn8Eo5Z417nktFd5/uhcD+MPWAt98ZHKC1IDXxvJG2JmyGd61FgY2QqlQ83nk6KYQVURERERERETkSOP4oOU4aD8ZTBfie6H47KDycLmWyeyonwUtQSwThlJZiodw6FSubgE9Z32asu3DP7SGtoe/gLGP4PLiOQ7XnOnDNOBP2wt87eEspXLtg9Sg18Zyg+zMeBnp3gj9G6BQ+ypeOXopRBURERERERERORIZBoTbYNYpUDcHUkOQHql5VaphQEPAZXFLiMagl7FMnlS2eNDrstEl7D3zk5QtD4H+x2h95MtQfvZ1F85x+PDzqkHqrTsKfPWhyQtSTcfH9myQ0Z4t0L8O8qmazyNHJ4WoIiIiIiIiIiJHMjcALcdXq1INC+I9UMrXfBqfazGvMcjcxgClSoWRZP6g7UWzjcvoOePjlE2HYN+DtD56LZRLzxp33myHj53lwzLgjl0FvvRgZvKCVNvDtmyE0f490LMasrGazyNHH4WoIiIiIiIiIiJHOtOESEe1V2qkE5KDkBmr+TSWCa1hL4taQoR9NsOpHLnCgZPUTPNJ9J7+ESqGTajnXloe/yZUnn3N2Z0On3i+D9uEu3cX+fwDGYqTEKSGvDamZbMtF2JsZAB6VkFquObzyNFFIaqIiIiIiIiIyNHCE4TWE6DtxOohUPG+STl0KuS1WdAcorPeRyKbP2iQmm49jd7TPkjFMAnvuYvW1d/dZ5B61iyHTz7fh2PCPXuKfO7+DIVD6MH6nNfvszEMi23ZEGOJOPSugnhvzeeRo4dCVBERERERERGRo4lpQl0ndJwE3lB1e/8+ttAfLscy6KjzM6veTzxbIF88cJCaaj+LvlM+QAWTut23ckL3f+4z4D2zw+HTZ/txTLivu8hn7suQn4QgNeyzqWCwLRNgLFOo9khN9Nd8Hjk6KEQVERERERERETka+eqh7SQINj0ZpB78MKjnyjShvc5PR52PeDZP4SBBanLWOfSv+FcqGMwbup2mDf9vn0HqaW02nz3Hj2vBgz1FPnvf5Gztj/gdKmXYnvJUg9SBDZPSBkGOfApRRURERERERESOVp4gtC6vVqbGe6GYq/kUlgmz6v20hr2MZfIUD1I1mph9IX3L3wFAw7bfEt34n/scd0qrzeeeFqR+/eEs5UloTRDxO5TKFbalvQzHYlT610M+XfN55MimEFVERERERERE5Gjm+KD5eIjOg9QgFDI1n8IyoTMaoDXsZTR98CA1NufFrJn1BgAanvhv6jf/9z7Hndxi8/GzfJgG3LazwI9X1z4EBqjzO5gYbEn56enZS6FvAxTzkzKXHJkUooqIiIiIiIiIHO1sF5qXQsMiyIxCLlH7KUyDzoYAzSEPo+kcpYMEqTuaXsjAcW8GoHHjz6nb8pt9jjuzw+EDp3sB+J9Nef574+QEqUGvTcjnYXchzO4dW0j2boTygdsTyLFDIaqIiIiIiIiIyLHAtKBxITQfB7kkZMdqPoVjGnQ1BGgKeRlJ5w6aQY4suIzhJf8IQNP6/0dk+x/2Oe7iuS5vO8kDwI9X57hl++RUibq2STQUYIgwu7asY2D3JioKUgWFqCIiIiIiIiIixw7ThPo50HoClIqQGqr5FI5lMDvqpzHoZTiZPXiQuvhyRha9FoDmNT8gvPPP+xz36iUeXrfUBeAbj2S5f2+hput+imlCNBKm6ETYu3U1O7ZvIX+QA7Pk6KcQVURERERERETkWGIY1YOmWpeDYUOiD2p8YJPHNulq8BMNehhOHSRINQyGl76R0fmvBKB51XcI7blrn0P/abmHF891KFfgc/dlWDNQrOm6n84fiuDz+RneuYaN23YQz05OaCtHBoWoIiIiIiIiIiLHolALtJ8IbhDiPVCpbbWlxzaZ0xCg3u8ynMoeOKc1DIaW/RNjcy/FoELLY98guPfefQwzeO9pXs7qsCmU4eP3pNk2Wqrpup/OCkSJek3yvetYt72b3liGSo0DZzkyKEQVERERERERETlW+aPQdiL4GyDWA+XaVnZ6nWqQGvG5DKdycJAgdXD524jNvhiDMq2PfpVA74PPGmaZBh95no8TmizSBfjwX9L0JCZvu3050ESTncM3uoUNuwfZ0p/U9v5jkEJUEREREREREZFjmTdcDVLDbRDvhVJtD23yuRZzGwMEPfYhBKkmAye/i/is8zAqJdoe/hL+/kefNcxjG3z2bD/z6kxGsxU+dHeKkcwkBZuGQSHQTLQ8QktuJzsGYqzviWl7/zFGIaqIiIiIiIiIyLHO9VcPm6rrgkQ/FLM1vb3ftZjbFCDgsRlJ5Q8SpFr0r3gfifbnY1SKtD30BXyDq541LOAafPFcP20Bg95UhQ//JU0yP0lb7Q2Lgr+ZYKaX2fQxGM+yes+YtvcfQxSiioiIiIiIiIgI2B5oOR4aFkBqGPKpmt4+6NrMaQjgdUzGUgepdjUt+k79d5Ktp2OW87Q/8Bn8/Y89a1jUZ/Kl8wLUew22j5X5xD1pcsXJCTUrlkPRV48vsZ3Z1jCVCqzbG9f2/mOEQlQREREREREREamybGhaUn1kY5CN1/T2Ia/N3MYgjnMIkZRp03fah/8WpD74WQI99z9rWHvI5Avn+vE7sHawxBceyFAqT1KQavsoOQE8Y1toYow6n8P2oZS29x8DFKKKiIiIiIiIiMjfmCY0zIeWZVDIQHqkprcP+2y6on4A4ukDB48Vy6H39I+QaH9BdWv/I18itOfuZ41bUG/x2bP9OCbcv7fINx/JTto2+7IbpoKBZ/QJ/OUkrWEvg4kca/aM0RebvHlleilEFRERERERERGRZzIMqO+qHjgFkByo6e0jfqc6jQnxTPHAg02bvlP/nXjnBRiVMi2PfY3wrlufNWx5s83HzvJhGnDLjgI/WZOr6ZqfruRrwCim8Y5sxi5naYv4KFdg7d4YWwe0vf9opBBVRERERERERET2LdxWDVJtL8R7ocZVll1RPxUqJLIHC1It+le8l7E5L8GgQsvj3yay/ffPGnbWLIf3neYF4L835vmfTZMXpBb9zVi5ETwjm6FcoN7vUudz2Dao7f1HI4WoIiIiIiIiIiKyf4HGapDqjUC8B8qlmt26PuAypyFAqVwmebAg1TAZPPEdjM5/BQDNa66jfsuvnzXsxfNc3nKiB4Afrspx646DHGI1UYZJwd+Mk+rDM7YNKmW8jqXt/UcphagiIiIiIiIiInJgvrpqkBpsfjJIPUjg+Rw0BqtBar5UJnXQINVgaNlbGF70uuq1628guvG/nlUh+9olLq9e7ALwtYezPLB3kqpCTZuivwE3thM3vhsAyzS0vf8opBBVREREREREREQOzhOE1uVQ11nd2l+s3Vb5ppCHOQ1+csUymdxBKl0Ng5Hj3sjQcW8CoGHzL2lcf/0zglTDMPjnkzxcPMehXIHP3Z9h3WDtgt+nq1geSt4I7tgW7FTf+Pvr/S4Rr7b3Hy0UooqIiIiIiIiIyKFxvNCyDKLzIDkIhXTNbt0c8jK7wU+6UCKbP3jLgNFFr2XwhH8GoH7rb2ha8wOo/K3i0zQM3n+6lzPbbfIl+Nhf02wfq10rgqcrOwEqlot3dDNWdmT8/T5X2/uPFgpRRURERERERETk0FkONC+FpsWQGYN8sia3NQxoDXuZHfWRzBfJFg4eeI7NfwX9J72LCgZ1O/5I8+PfhsrfrrNNg4+e5WNZo0WqAB++O01vcnK21pe89VAu4BnZjPm0r8nTt/ev2xtj90jtgmeZOgpRRURERERERETkuTEt/n97dx4mVXXnf/xzb+1Vve/dNDSbgihqNICAiAY1BjUx8WcmLhNj4sTEbJpN4y5GTUycMZMxxiRuo3GcbOMSzeKGgoKCiCv7Dr2vte/1+6OkpKXpru6u7qab9+t5eLzV99zzPbfg4bl+OPcclR0mlR8hhbpyNiPVMKTqQpdqi9zyh2OKxPoOPL0Tz1DT8d9VSqYKdz6nqtV3dluz1Wk1tOQktyYVmmoPp3T10qA6wkMTpMZd5bJEu+To2Cgj0X25g2K3XR6HVZua/WroCg1JfQwdQlQAAAAAAAD0n2FIJZOkssOlQHvO1kg1DGlckUu1xW75IrGsNmXyjT9FjbN+qJRhUf6el1X9+k9kJD5cgzTfbui2k92q8hiq9yd1zUtBBaJD8Fq9YSjmqZQt2CR756b9NuDKc1jlsJja0OhTqz93a8pi6BGiAgAAAAAAYGAMQyqdkg5T/c1SIjebJ5mmVFPkVk2hS95wVLEsglT/uBNVP+c6JU2b8hpXqvq1W2TEw5nzZS5Tt5/sVpHD0OaOpG5cHlQ0MRRBqkUxd4Xs3t2ye7d32/BKkorcdqVS0vpGn7pCbDY1WhCiAgAAAAAAYOBMS3p91KIJkq9xv9mXA2Uxpdpit6oKXOoMRRXPIvAMVs1S/dwblbQ45Gleo5oVN8nYZ6mB2nyLblvoltsqvdWc0G0rQkokcx+kpiw2xV3FcnRtkc2/Z7/zZXkOhaMJbWj0KhDJzfeFoUWICgAAAAAAgMGx2KTy6VJ+teRrklK5WXPUYkq1JW6V5zvVEYx+dFJnj0Llx2rPvCVKWF1yt72rca9e322jp8NKLLp5gVs2U3pld1y/WB1WKpuO+ylldSlh88jRuVHWYMt+5yvyHeoIxLSxyZfVJloYWYSoAAAAAAAAGDybU6qcIblL0zNScxRM2kxD44vdKnTZ1BGIZnVNuPRI7Zl/qxK2PLk6NmjcK9fKjHRlzh9badWP5rpkGtLftsZ0/9tDsz5p0l6glCRHx4Zu9SXJMAxVFjjV5A1rc7NfscTQbHaF3CBEBQAAAAAAQG7YPekg1VEg+Zty1q3TZmpCiVt2qylfKLvX3yPFh2v3ibcrbi+Us2uLapf/SJZwe+b8gvE2fefjTknSY+ui+tP6oQlSE64yGfGgnO0bZMRD3c5ZTEMV+U7t7ghqa0tAySFYWgC5QYgKAAAAAACA3HEWSpVHShanFGjNWbf5TqsmlLoVSyYVjmb3+nu0cJJ2L/iJ4s4SOXw7Vbvs6m6v1i+eYtclMx2SpHvXRvTQO0Pzan/cXSFLuE2O9g1SsvtmUjaLqVKPQ9ta/drRFhiS+hg8QlQAAAAAAADklrskPSNVkkKdOeu21GPX+GKXfJGYYvHsXn+P5Y/X7gU/VcxVIXugXrXLrpIt0JA5f/4Muy460i5JeuS9qO58Pax4rmeEGqZinkrZAg1ydG7bb6kDp82iYrddm1sC2tMZOkAnGEmEqAAAAAAAAMi9/Eqp4ggpFpYivpx1W1ngUnWhU52hqJJZLiMa81Rr94KfKuqpkS3UnA5SfbskpdcmvXimU1d83CnTkP6xLaYblgUViuU4SDWtirtKZfduk82/Z7/TbrtVbptFG5t8avaGc1sbg0aICgAAAAAAgKFRME6qmJ4OUWPBnHRpMaVxxW6VeBxqD0SkLLPOuLtcuxf8VJH8CbKG21W77GrZu7Zmzp851a6bTnTJYZFWNST0vRcC6gjndrOnlNWphM0tR9fmbuuz7lXgsslimNrQ5Mt6Ey0MD0JUAAAAAAAADA3DkIrqpNLDpEC7FM/N5k12S3qjqTyHVZ3BWN8XfCDhLNbuE29XuHCKrNEu1S6/Ro6OjZnzc8fZ9PNPeFToMLSpI6lvPxvQLm92669mK+kolJJxOTo2yughWC7x2BWNJbWh0SdfOPt7w9AiRAUAAAAAAMDQMU2pdIpUMknyN0uJ3ASDbrtF40vcMkzJH45nfV3SUag9829VqHiaLDG/xr1yrZxt72XOTy+16BenelSTZ6gxkNIVzwX1fmv2/Wcj7iqXJdIpR+dmKbl/3+X5DnnDMW1o9CmU5SZaGFqEqAAAAAAAABhapkUqnyYVjZd8TVIyN8FgkdumCSVuReIJRWLZv3qftOdpz7xbFCybKUs8pHGv3iBX89rM+XH5pu461aNpJaa80ZR+8GJQr+7O4axQw1DMXSGbf4/s3u37bTRlGIYqC5xq9Ue1scmnaJabaGHoEKICAAAAAABg6FlsUvkRUn5VOkjNkfI8h8YVueQNRxVPZL8ZVMrmVv0JNypQcZzMREQ1r90ie+eHa6QWO0397BMeza62KpqQbn4lpKc25XCdUtOquKtE9q6tsgYb9z9tGKrMd6ihK6TNzT4lkjne6Ar9QogKAAAAAACA4WFzSpUzJFdx+nNq8MGgYUjVRS6V5zvVEYz2q8uU1amGOdcrUP6xdJD6+q0yI12Z8y6roSULXPrUZJuSKek/3wjrvrfCSuVg3On6LqWsTjk7NskS7tzvvNViqjzPqV0dQW1r8eesLvqPEBUAAAAAAADDx+6RKo9IHwdactKl1TQ0ocStQpet37vapyw2Nc76oaKeatmCTape9dNuyw1YTENXznLqi0c5JEmPrYvqjtfCivVj1mtvEo4iKRFJbzQVD+933m41VexyaGtrQDvb99+ICsODEBUAAAAAAADDy1GQ/q9pl4JtuenSampCqVt2qylvqH8bQSXt+WqYc62SFqfcrW+r7L37u503DEP/epRD35vtlGlIz22P6bqXgwrEchOkxt3lsoTbD7jRlMtuUb7Tpk3NfjV0hXJSE/1DiAoAAAAAAICRUTFNSialHl5lH4h8h1V1pW4lUsl+72ofLZioxuO/K0kq3vKE8ne+sF+bMybbdcsCl5xWaU1TQt99PqDWUA42fTJMxd3lsvl2y+7d0eMyB3kOqxwWUxsbfWr1RwZfE/1CiAoAAAAAAICRkVcpVRwhRUNS1J+TLks8do0vdisQiSnWz13tAzXz1Hb4v0iSKtb+Uo6OTfu1mV1j088/4VGRw9DWzqS+82xAO7r6F9j2JGWxKeEs+mCjqZ433ipy25VMSRsafeoKxQZdE9kjRAUAAAAAAMDIKayVyqdLYa8Uy82r6pX5TlUVOtUZiirZz4mi7UdcKH/lLJnJmKpfv1WWcMd+baaVWPSfp3k0Lt9UczClK58P6N2W/i0h0JOkza2UxS5Hx6ZuG1ztqyzPoVA0oQ2NXgUig6+J7BCiAgAAAAAAYOQYhlQ8USqZml4fNT74V9VNU6ot9qjU41B7ICL1Z+lSw1TTx7+vaF6tbKFWVa/6SY/rlFbnmfrFqW4dUWqRLyr98MWglu0a/OzQhLNYZiIkZ+emHjeakqTyfIfaA1FtbPIpHBv8LFj0jRAVAAAAAAAAI8s0pbKpUvEkyd/cY2jZXzaLoQklbuU5reoIRvt1bdLmUf2ca5WwuuRqe0/l7/y2x3aFDlN3nOLW3HFWxZLSLa+E9H8bBx8Cx9zlsgZbZO/aIiX3D0lNw1BVgUtN3rA2N/sVS+RgXVb0ihAVAAAAAAAAI8+0SGWHS0XjJW9Dj+Fhf7nsFk0o8chiGvKH+xfMxvLHq+n470uSirY9rYLt/+yxndNq6Mb5Lp011aaUpF+tiei3a8NK9rA5VNYMi2Luctl9u2X37eqxicU0VJHv1O6OoLa2BJRMDqIe+kSICgAAAAAAgIOD1S6VHyHlV0m+Rik1+BmWhS6rxpe4FYknFYn1c6Op6jlqm36hJKn87V/J2b6+x3YW09C3j3fqkpkOSdIf1kf1kxUhRRMDDzZTFrsS9nzZu7bIGmzusY3NYqrU49C2Vr92tAWUGkxwi16N6RA1Go3q4Ycf1uLFi1VXVyen06nq6mrNmzdPP//5z9Xa2przmtu3b9dvf/tbXXTRRTrmmGNUXFwsm82mkpISHX300brsssv00ksv5bwuAAAAAADAmGBzShUzJFeJ5GuSchAMluc5NK7IKV8kqng/g832af8if/Vcmcm4ql+/TZZwe4/tDMPQBUc69MM5TlkM6cWdcV37UlD+6MDHn7TnKWWY6Y2mor4e2zhtFhW77drcEtCeztxszIX9GakxGlGvX79e559/vtauXXvANhUVFXrggQe0ePHiQdd788039bWvfU2vv/56Vu1PPvlkPfTQQ5owYcKAa3q9XhUWFqq1tVWlpaUD7gcAAKAnsVhMzzzzjBYvXiybzTbSwwEAAGNIVs8ZoU6p4S0pHpLyKgddM55MaXtrQM3esMrynTKM7K81YkGNf/n7cvh2KlQyXXvm366U5cDPR6sb4lrySlChuDSx0NRtC90qdw9wLmMqJVugSXFXmcJlRyplcfTYzBuKKZpI6MiaQlUUOAdW6xC0N1/r6upSQUHBAduNyZmou3fv1qJFizIBqmEYWrhwob785S/r7LPPlsvlkiQ1NzfrnHPO0QsvvDDomhs2bNgvQD388MP1uc99Tl/96lf1+c9/XrW1tZlzS5cu1dy5c7V169ZB1wYAAAAAABhzXEVS5VGSaZOCbYPuzmoaGl/iVpHbrvZA/zZ/StncaphznRI2j1zt61X+9j29zpD9eLVV/77IoxKnoe1dSX3n2YC2dQ5wjVfDUMxTLmuwSfbOrQdc4qDAZZNpmNrQ5FNHoH8baaFvYzJEveCCC1RfXy9Jqqur05tvvqmlS5fqvvvu05NPPqmdO3dq0aJFktL/8nHeeeeps7MzJ7WnTp2qn/zkJ9q9e7c2bNigP//5z7r33nv1v//7v9qxY4fuu+8+ud1uSVJ9fb0uvPBC1qsAAAAAAADoiac0/Wp/Ii5F/YPuzmE1Nb7ULYfNIm+onxtN5dWo8eM/VEqGCnf8U4Xb/9Zr+6nFFv3iVI/GF5hqCaV05fMBvdXUv5oZhkVxd5nsvp2yHWCjKUkq8dgVjSf1Xn2Xmr3hgdVCj8ZciPrMM89o2bJlkiS73a6nnnpKxxxzTLc2ZWVleuKJJzR58mRJUnt7u+64445B1a2urtYDDzyg9evX66qrrtK4ceP2a2Oapr785S/rkUceyfxs5cqV+uc/e97dDQAAAAAA4JBXUC2VHSYFO6XE4GdY5jusqitxK5FKKhTp3+zQYOXxaptxsSSp/O175Wx9t9f2VXmm7lrk0ZFlFgVi0o9eCuq1+tiAxp2yOJSw58nRtUWW0IH3+anIdyqRlN6p79LOtoCSSSbv5cKYC1HvvvvuzPHFF1+smTNn9tjO4/FoyZIlmc/33nuv4vEB/muApIULF+pLX/qSLBZLn20/+9nPavbs2ZnPTz/99IDrAgAAAAAAjHnFE6WiCZK/+YCvs/dHiceu8cVuBaIxxeL966/jsHPlG7dARiqh6lU/kbWXQFOSChyGfnqyW/NrrYolpZuXh/RG48AyqKQ9X5Lk6NgoMxY4YLsSj11uq1XrG33a3OxXLDH47+xQN6ZCVL/fr+effz7z+ZJLLum1/bnnnqu8vDxJ6dmoL7/88pCOb1/z58/PHG/fvn3Y6gIAAAAAAIw6piU9G9VVkg5Sc6Ay36mqQpc6QzEl+5MxGoaaPvYdRQomyhrpVPVrt8roY4asw2rounkuzRuXDlJvXBbUW80DC1LjzlJZol45Ojb2WjfPaVWx266trX6ta/AqFB3gmqyQNMZC1FdffVWRSHphYI/Ho1mzZvXa3ul0au7cuZnPudhgKlvGPlvAJRL8IQYAAAAAAOiV3S2VT5dMqxTuGnR3pinVFrtV6rGrPRiW+vHWe8rqVP2c65Sw5cvZuUkVa+/udaMpKb2x1bXzXJpVbVUkIV33clDvtw4gSDUMxdyVsgaaZO/a3mtdp82iynyn6jvDere+S12hgS0lgDEWoq5bty5zPHPmTFmt1j6vOe6443q8fqi98847mePx48cPW10AAAAAAIBRy1MqlR0uRQNSPDLo7mwWQxNK3Mpz2Pq9o33cU6WG2VcpJVMFu55X4dan+rzGbjF043yXPlZpUTieXiN1Q/sAJteZFsVdJbJ7t8nm39NrU6vFVHWhU13BmN7Z06VmHxtODcSYClE3bNiQOa6rq8vqmgkTJmSO169fn/Mx9WTnzp3dZr2eeuqpw1IXAAAAAABg1CscLxXVpV/rTw7+7V6X3aIJJR5ZraY6g/2bqRkqP1atR31ZklT+7u/kanm7z2scVkM3L3BrZrlFwZj0o6UBbeno/32krE4lbG45OjfJEm7vta1pGKoscCoeT+rdPV3a1R5Qqo+Zs+huTIWobW1tmePKysqsrqmqqsoct7f3/gcuV7773e9mXuGfMGGCzj777GGpCwAAAAAAMOqZZnp91PxKyd+Uky4LXVZNKvPIahrq8Ef79Wp/55TPyFt7ioxUMr3RVKDvMbmshm45ya3ppRb5otLVS4Pa0dX/IDXpKJRSifT6qLFgn+1L8xxyWi1a15DecCrOhlNZ6/t991HE7/dnjl0uV1bX7Ntu3+uHykMPPaQ///nPmc+33367HA5HVtdGIpHMmq+S5PV6JUmxWEyxGGtaAACA3Nr7fMFzBgAAyLXBP2eYUtEUKRiQfG2Su3jQY8pzWFRX4taOtoBafREVe+yS0fd1ktRwzDdk9+2Us2uLql+7VTtO/KlSVmev1zgt0o8XuHT1S0Ft7kjqBy8G9fNT3BqX3785jwlHmWyBRlnbNylSMi29ZmwvPDZDFpna0tSlQDiiqeV5ctgs/ao5lmT7Z3BMhajh8IdrOtjt9qyu2TfADIVCOR/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" ] @@ -527,7 +529,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ @@ -541,12 +543,12 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 44, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -572,12 +574,12 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 45, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -603,34 +605,34 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 46, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohi/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n" ] }, { "data": { - "image/png": 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" ] @@ -658,14 +660,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Further analysis\n", + "# Further metrics\n", "This tutorial is a work-in-progress, more examples will be added in future releases. " ] } ], "metadata": { "kernelspec": { - "display_name": "iohi", + "display_name": "iohinspector", "language": "python", "name": "python3" }, diff --git a/examples/SO_Examples.ipynb b/examples/SO_Examples.ipynb index aad801d..83129d5 100644 --- a/examples/SO_Examples.ipynb +++ b/examples/SO_Examples.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -114,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -137,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -154,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -201,7 +201,7 @@ "└─────────┴──────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴───────────┘" ] }, - "execution_count": 4, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -219,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 23, "metadata": {}, "outputs": [ { @@ -235,7 +235,7 @@ " Function(id=1, name='Sphere', maximization=False)))" ] }, - "execution_count": 5, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -261,7 +261,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 24, "metadata": {}, "outputs": [], "source": [ @@ -271,7 +271,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 25, "metadata": {}, "outputs": [ { @@ -318,7 +318,7 @@ "└─────────┴───────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴──────────┘" ] }, - "execution_count": 7, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -329,7 +329,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 26, "metadata": {}, "outputs": [], "source": [ @@ -338,7 +338,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 27, "metadata": {}, "outputs": [], "source": [ @@ -349,7 +349,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 28, "metadata": {}, "outputs": [ { @@ -379,7 +379,7 @@ "└─────────┴───────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴──────────┘" ] }, - "execution_count": 10, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" } @@ -404,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 29, "metadata": {}, "outputs": [ { @@ -451,7 +451,7 @@ "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘" ] }, - "execution_count": 11, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -470,7 +470,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -490,12 +490,12 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 31, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -505,28 +505,28 @@ } ], "source": [ - "#Note: we filter the data by function ID here. This is equivalent to doing the subselecting before loading the performance data. \n", + "#Note: we filter the data by function ID here. This is equivalent to doing the subselecting before loading the performance data. \n", "data_singleft = iohinspector.plot.single_function_fixedtarget(df.filter(pl.col(\"function_id\") == 1))" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 14, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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" ] @@ -554,12 +554,12 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 33, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -581,12 +581,12 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 34, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -601,12 +601,20 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 35, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/align.py:109: UserWarning: Sortedness of columns cannot be checked when 'by' groups provided\n", + " result_df = x_vals.join_asof(\n" + ] + }, { "data": { - "image/png": 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" ] @@ -628,12 +636,12 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 36, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -657,7 +665,7 @@ ], "metadata": { "kernelspec": { - "display_name": "venv", + "display_name": "iohinspector", "language": "python", "name": "python3" }, @@ -671,7 +679,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.12" + "version": "3.10.18" } }, "nbformat": 4, diff --git a/pyproject.toml b/pyproject.toml index edcc61f..05c4001 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "iohinspector" -version = "0.0.5" +version = "0.0.6" authors = [ { name="Diederick Vermetten", email="d.vermetten@gmail.com" }, { name="Jacob de Nobel", email="jacobdenobel@gmail.com" }, diff --git a/src/iohinspector/__init__.py b/src/iohinspector/__init__.py index 67ecf6e..7bdd748 100644 --- a/src/iohinspector/__init__.py +++ b/src/iohinspector/__init__.py @@ -1,7 +1,7 @@ from .align import * from .data import * from .manager import * -from .metrics import * +from .old_metrics import * from .indicators import * from .plot import * -from .data_processing import * \ No newline at end of file +from .metrics import * \ No newline at end of file diff --git a/src/iohinspector/data_processing/__init__.py b/src/iohinspector/data_processing/__init__.py deleted file mode 100644 index ccbf096..0000000 --- a/src/iohinspector/data_processing/__init__.py +++ /dev/null @@ -1,6 +0,0 @@ -from .utils import * -from .aggregate_convergence import * -from .aggregate_running_time import * -from .normalise_objectives import * -from .aocc import (get_aocc) -from .ecdf import (get_data_ecdf) \ No newline at end of file diff --git a/src/iohinspector/metrics/__init__.py b/src/iohinspector/metrics/__init__.py new file mode 100644 index 0000000..a12b9f3 --- /dev/null +++ b/src/iohinspector/metrics/__init__.py @@ -0,0 +1,6 @@ +from .utils import (get_sequence) +from .fixed_budget import (aggregate_convergence) +from .fixed_target import (aggregate_running_time) +from .normalise_objectives import (normalize_objectives, add_normalized_objectives, transform_fval) +from .aocc import (get_aocc) +from .ecdf import (get_data_ecdf) \ No newline at end of file diff --git a/src/iohinspector/data_processing/aocc.py b/src/iohinspector/metrics/aocc.py similarity index 100% rename from src/iohinspector/data_processing/aocc.py rename to src/iohinspector/metrics/aocc.py diff --git a/src/iohinspector/data_processing/ecdf.py b/src/iohinspector/metrics/ecdf.py similarity index 84% rename from src/iohinspector/data_processing/ecdf.py rename to src/iohinspector/metrics/ecdf.py index 5d974c5..44cad57 100644 --- a/src/iohinspector/data_processing/ecdf.py +++ b/src/iohinspector/metrics/ecdf.py @@ -2,29 +2,9 @@ from typing import Iterable from .utils import get_sequence from ..align import align_data -from .normalise_objectives import normalize_objectives +from .normalise_objectives import transform_fval + -def transform_fval( - data: pl.DataFrame, - lb: float = 1e-8, - ub: float = 1e8, - scale_log: bool = True, - maximization: bool = False, - fval_col: str = "raw_y", -): - """ - Helper function to transform function values (min-max normalization based on provided bounds and scaling) - """ - bounds = {fval_col: (lb, ub)} - res = normalize_objectives( - data, - obj_cols=[fval_col], - bounds=bounds, - log_scale=scale_log, - maximize=maximization, - prefix="eaf" - ) - return res def get_data_ecdf( diff --git a/src/iohinspector/data_processing/aggregate_convergence.py b/src/iohinspector/metrics/fixed_budget.py similarity index 91% rename from src/iohinspector/data_processing/aggregate_convergence.py rename to src/iohinspector/metrics/fixed_budget.py index 3ce20cc..48ebb16 100644 --- a/src/iohinspector/data_processing/aggregate_convergence.py +++ b/src/iohinspector/metrics/fixed_budget.py @@ -55,17 +55,16 @@ def aggregate_convergence( pl.max(fval_variable).alias("max"), pl.median(fval_variable).alias("median"), pl.std(fval_variable).alias("std"), - pl.col(fval_variable) - .map_elements(lambda s: geometric_mean(s), return_dtype=pl.Float64) - .alias("geometric_mean"), + pl.col(fval_variable).log().mean().exp().alias("geometric_mean") ] if custom_op is not None: aggregations.append( - pl.col(fval_variable) - .map_elements(lambda s: custom_op(s), return_dtype=pl.Float64) - .alias(custom_op.__name__) - ) + pl.col(fval_variable).map_batches( + lambda s: custom_op(s), return_dtype=pl.Float64, returns_scalar=True + ).alias(custom_op.__name__) + ) + dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) if return_as_pandas: return dt_plot.sort(evaluation_variable).to_pandas() diff --git a/src/iohinspector/data_processing/aggregate_running_time.py b/src/iohinspector/metrics/fixed_target.py similarity index 97% rename from src/iohinspector/data_processing/aggregate_running_time.py rename to src/iohinspector/metrics/fixed_target.py index c7b5b12..27495c3 100644 --- a/src/iohinspector/data_processing/aggregate_running_time.py +++ b/src/iohinspector/metrics/fixed_target.py @@ -82,7 +82,7 @@ def aggregate_running_time( if custom_op is not None: aggregations.append( pl.col(evaluation_variable) - .map_elements(lambda s: custom_op(s), return_dtype=pl.Float64) + .map_batches(lambda s: custom_op(s), return_dtype=pl.Float64, returns_scalar=True) .alias(custom_op.__name__) ) dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) diff --git a/src/iohinspector/data_processing/normalise_objectives.py b/src/iohinspector/metrics/normalise_objectives.py similarity index 53% rename from src/iohinspector/data_processing/normalise_objectives.py rename to src/iohinspector/metrics/normalise_objectives.py index 5e64660..bdc88ad 100644 --- a/src/iohinspector/data_processing/normalise_objectives.py +++ b/src/iohinspector/metrics/normalise_objectives.py @@ -10,7 +10,8 @@ def normalize_objectives( bounds: Optional[Dict[str, tuple[Optional[float], Optional[float]]]] = None, log_scale: Union[bool, Dict[str, bool]] = False, maximize: Union[bool, Dict[str, bool]] = False, - prefix: str = "ert" + prefix: str = "ert", + keep_original: bool = True ) -> pl.DataFrame: """ Normalize multiple objective columns in a dataframe. @@ -22,7 +23,7 @@ def normalize_objectives( log_scale (Union[bool, Dict[str, bool]]): Whether to apply log10 scaling. Can be a single bool or a dict per column. maximize (Union[bool, Dict[str, bool]]): Whether to treat objective as maximization. Can be a single bool or dict. prefix (str): Prefix for normalized column names. - + keep_original (bool): Whether to keep original objective columns names. Returns: pl.DataFrame: The original dataframe with new normalized objective columns added. """ @@ -58,10 +59,69 @@ def normalize_objectives( norm_expr = 1 - norm_expr # Add normalized column with appropriate name if n_objectives > 1: - norm_expr = norm_expr.alias(f"{prefix}_{col}") + if keep_original: + norm_expr = norm_expr.alias(f"{prefix}_{col}") + else: + idx = list(obj_cols).index(col) + 1 + norm_expr = norm_expr.alias(f"{prefix}{idx}") else: # If only one objective, use the prefix directly norm_expr = norm_expr.alias(prefix) result = result.with_columns(norm_expr) - return result \ No newline at end of file + return result + + +def add_normalized_objectives( + data: pl.DataFrame, + obj_cols: Iterable[str], + max_vals: Optional[pl.DataFrame] = None, + min_vals: Optional[pl.DataFrame] = None +): + """Add new normalized columns to provided dataframe based on the provided objective columns + + Args: + data (pl.DataFrame): The original dataframe + obj_cols (Iterable[str]): The names of each objective column + max_vals (Optional[pl.DataFrame]): If provided, these values will be used as the maxima instead of the values found in `data` + min_vals (Optional[pl.DataFrame]): If provided, these values will be used as the minima instead of the values found in `data` + + Returns: + _type_: The original `data` DataFrame with a new column 'objI' added for each objective, for I=1...len(obj_cols) + """ + + return normalize_objectives( + data, + obj_cols=obj_cols, + bounds={ + col: (min_vals[col][0] if min_vals is not None else None, + max_vals[col][0] if max_vals is not None else None) + for col in obj_cols + }, + maximize=True, + prefix="obj", + keep_original=False + ) + + +def transform_fval( + data: pl.DataFrame, + lb: float = 1e-8, + ub: float = 1e8, + scale_log: bool = True, + maximization: bool = False, + fval_col: str = "raw_y", +): + """ + Helper function to transform function values (min-max normalization based on provided bounds and scaling) + """ + bounds = {fval_col: (lb, ub)} + res = normalize_objectives( + data, + obj_cols=[fval_col], + bounds=bounds, + log_scale=scale_log, + maximize=maximization, + prefix="eaf" + ) + return res \ No newline at end of file diff --git a/src/iohinspector/data_processing/utils.py b/src/iohinspector/metrics/utils.py similarity index 100% rename from src/iohinspector/data_processing/utils.py rename to src/iohinspector/metrics/utils.py diff --git a/src/iohinspector/metrics.py b/src/iohinspector/old_metrics.py similarity index 53% rename from src/iohinspector/metrics.py rename to src/iohinspector/old_metrics.py index 0156174..b960ebc 100644 --- a/src/iohinspector/metrics.py +++ b/src/iohinspector/old_metrics.py @@ -9,216 +9,6 @@ from .align import align_data - - - -def get_sequence( - min: float, - max: float, - len: float, - scale_log: bool = False, - cast_to_int: bool = False, -) -> np.ndarray: - """Create sequence of points, used for subselecting targets / budgets for allignment and data processing - - Args: - min (float): Starting point of the range - max (float): Final point of the range - len (float): Number of steps - scale_log (bool): Whether values should be scaled logarithmically. Defaults to False - version (str, optional): Whether the value should be casted to integers (e.g. in case of budget) or not. Defaults to False. - - Returns: - np.ndarray: Array of evenly spaced values - """ - transform = lambda x: x - if scale_log: - assert min > 0 - min = np.log10(min) - max = np.log10(max) - transform = lambda x: 10**x - values = transform( - np.arange( - min, - max + (max - min) / (2 * (len - 1)), - (max - min) / (len - 1), - dtype=float, - ) - ) - if cast_to_int: - return np.unique(np.array(values, dtype=int)) - return np.unique(values) - - -def _geometric_mean(series: pl.Series) -> float: - """Helper function for polars: geometric mean""" - return np.exp(np.log(series).mean()) - - -def aggegate_convergence( - data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - x_min: int = None, - x_max: int = None, - custom_op: Callable[[pl.Series], float] = None, - maximization: bool = False, - return_as_pandas: bool = True, -): - """Function to aggregate performance on a fixed-budget perspective - - Args: - data (pl.DataFrame): The data object to use for getting the performance. Note that the fval, evaluation and free variables as defined in - this object determine the axes of the final performance (most data will have 'raw_y', 'evaluations' and ['algId'] as defaults) - evaluation_variable (str, optional): Column name for evaluation number. Defaults to "evaluations". - fval_variable (str, optional): Column name for function value. Defaults to "raw_y". - free_variables (Iterable[str], optional): Column name for free variables (variables over which performance should not be aggregated). Defaults to ["algorithm_name"]. - x_min (int, optional): Minimum evaulation value to use. Defaults to None (minimum present in data). - x_max (int, optional): Maximum evaulation value to use. Defaults to None (maximum present in data). - custom_op (Callable[[pl.Series], float], optional): Custom aggregation method for performance values. Defaults to None. - maximization (bool, optional): Whether performance metric is being maximized or not. Defaults to False. - return_as_pandas (bool, optional): Whether the data should be returned as Pandas (True) or Polars (False) object. Defaults to True. - - Returns: - DataFrame: Depending on 'return_as_pandas', a pandas or polars DataFrame with the aggregated performance values - """ - - # Getting alligned data (to check if e.g. limits should be args for this function) - if x_min is None: - x_min = data[evaluation_variable].min() - if x_max is None: - x_max = data[evaluation_variable].max() - x_values = get_sequence(x_min, x_max, 50, scale_log=True, cast_to_int=True) - group_variables = free_variables + [evaluation_variable] - data_aligned = align_data( - data.cast({evaluation_variable: pl.Int64}), - x_values, - group_cols=["data_id"] + free_variables, - x_col=evaluation_variable, - y_col=fval_variable, - maximization=maximization, - ) - - aggregations = [ - pl.mean(fval_variable).alias("mean"), - pl.min(fval_variable).alias("min"), - pl.max(fval_variable).alias("max"), - pl.median(fval_variable).alias("median"), - pl.std(fval_variable).alias("std"), - pl.col(fval_variable).log().mean().exp().alias("geometric_mean") - ] - - if custom_op is not None: - aggregations.append( - pl.col(fval_variable).apply(custom_op).alias(custom_op.__name__) - ) - dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) - if return_as_pandas: - return dt_plot.sort(evaluation_variable).to_pandas() - return dt_plot.sort(evaluation_variable) - - -def transform_fval( - data: pl.DataFrame, - lb: float = 1e-8, - ub: float = 1e8, - scale_log: bool = True, - maximization: bool = False, - fval_col: str = "raw_y", -): - """Helper function to transform function values (min-max normalization based on provided bounds and scaling) - - Args: - data (pl.DataFrame): The data object to use for getting the performance. - lb (float, optional): Lower bound for scaling of function values. If None, it is the max value found in data. Defaults to 1e-8. - ub (float, optional): Upper bound for scaling of function values. If None, it is the max value found in data. Defaults to 1e8. - scale_log (bool, optional): Whether function values should be log-scaled before scaling. Defaults to True. - maximization (bool, optional): Whether function values is being maximized. Defaults to False. - fval_col (str, optional): Which column in data to use. Defaults to "raw_y". - - Returns: - _type_: a copy of the original data with a new column 'eaf' with the scaled function values (which is always to be maximized) - """ - if ub == None: - ub = data[fval_col].max() - if lb == None: - lb = data[fval_col].min() - if lb <= 0 and scale_log: - lb = 1e-8 - warnings.warn( - "If using logarithmic scaling, lb should be set to prevent errors in log-calculation. Lb is being overwritten to 1e-8 to avoid this." - ) - if scale_log: - lb = np.log10(lb) - ub = np.log10(ub) - res = data.with_columns( - ((pl.col(fval_col).log10() - lb) / (ub - lb)).clip(0, 1).alias("eaf") - ) - else: - res = data.with_columns( - ((pl.col(fval_col) - lb) / (ub - lb)).clip(0, 1).alias("eaf") - ) - if maximization: - return res - return res.with_columns((1 - pl.col("eaf")).alias("eaf")) - - -def _aocc(group: pl.DataFrame, max_budget: int, fval_col: str = "eaf"): - group = group.cast({"evaluations": pl.Int64}).filter( - pl.col("evaluations") <= max_budget - ) - new_row = pl.DataFrame( - { - "evaluations": [0, max_budget], - fval_col: [group[fval_col].min(), group[fval_col].max()], - } - ) - group = ( - pl.concat([group, new_row], how="diagonal") - .sort("evaluations") - .fill_null(strategy="forward") - .fill_null(strategy="backward") - ) - return group.with_columns( - ( - ( - pl.col("evaluations").diff(n=1, null_behavior="ignore") - * (pl.col(fval_col).shift(1)) - ) - / max_budget - ).alias("aocc_contribution") - ) - - -def get_aocc( - data: pl.DataFrame, - max_budget: int, - fval_col: str = "eaf", - group_cols: Iterable[str] = ["function_name", "algorithm_name"], -): - """Helper function for AOCC calculations - - Args: - data (pl.DataFrame): The data object to use for getting the performance. - max_budget (int): Maxium value of evaluations to use - fval_col (str, optional): Which data column specifies the performance value. Defaults to "eaf". - group_cols (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["function_name", "algorithm_name"]. - - Returns: - pl.DataFrame: a polars dataframe with the area under the EAF (=area over convergence curve) - """ - aocc_contribs = data.group_by(*["data_id"]).map_groups( - partial(_aocc, max_budget=max_budget, fval_col=fval_col) - ) - aoccs = aocc_contribs.group_by(["data_id"] + group_cols).agg( - pl.col("aocc_contribution").sum() - ) - return aoccs.group_by(group_cols).agg( - pl.col("aocc_contribution").mean().alias("AOCC") - ) - - def get_tournament_ratings( data: pl.DataFrame, alg_vars: Iterable[str] = ["algorithm_name"], diff --git a/src/iohinspector/plot.py b/src/iohinspector/plot.py index 99eb368..76f9da1 100644 --- a/src/iohinspector/plot.py +++ b/src/iohinspector/plot.py @@ -9,14 +9,11 @@ from matplotlib.patches import Polygon, Rectangle import seaborn as sbs -from .metrics import ( - aggegate_running_time, - get_sequence, - aggegate_convergence, +from .old_metrics import ( get_tournament_ratings, get_attractor_network, - transform_fval, ) +from .metrics import aggregate_running_time, aggregate_convergence, get_sequence, transform_fval from .align import align_data, turbo_align from .indicators import add_indicator, final @@ -66,7 +63,7 @@ def single_function_fixedtarget( Returns: pd.DataFrame: The final dataframe which was used to create the plot """ - dt_agg = aggegate_running_time( + dt_agg = aggregate_running_time( data, evaluation_variable=evaluation_variable, fval_variable=fval_variable, @@ -139,7 +136,7 @@ def single_function_fixedbudget( Returns: pd.DataFrame: The final dataframe which was used to create the plot """ - dt_agg = aggegate_convergence( + dt_agg = aggregate_convergence( data, evaluation_variable=evaluation_variable, fval_variable=fval_variable, diff --git a/src/iohinspector/plot/plot_convergence.py b/src/iohinspector/plot/plot_convergence.py deleted file mode 100644 index 890d4a8..0000000 --- a/src/iohinspector/plot/plot_convergence.py +++ /dev/null @@ -1,77 +0,0 @@ -import polars as pl -from typing import Iterable -import matplotlib -import matplotlib.pyplot as plt -import seaborn as sbs -from iohinspector.data_processing import aggegate_convergence - - -def single_function_fixedbudget( - data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - x_min: float = None, - x_max: float = None, - maximization: bool = False, - measures: Iterable[str] = ["geometric_mean"], - scale_xlog: bool = True, - scale_ylog: bool = True, - ax: matplotlib.axes._axes.Axes = None, - file_name: str = None, -): - """Create a fixed-budget plot for a given set of performance data. - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. - x_min (float, optional): Minimum value to use for the 'evaluation_variable', if not present the min of that column will be used. Defaults to None. - x_max (float, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. - maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. - scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. - scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - - Returns: - pd.DataFrame: The final dataframe which was used to create the plot - """ - dt_agg = aggegate_convergence( - data, - evaluation_variable=evaluation_variable, - fval_variable=fval_variable, - free_variables=free_variables, - x_min=x_min, - x_max=x_max, - maximization=maximization, - ) - - dt_molt = dt_agg.melt(id_vars=[evaluation_variable] + free_variables) - dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) - - if ax is None: - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) - sbs.lineplot( - dt_plot, - x=evaluation_variable, - y="value", - style="variable", - hue=dt_plot[free_variables].apply(tuple, axis=1), - ax=ax, - ) - if scale_xlog: - ax.set_xscale("log") - if scale_ylog: - ax.set_yscale("log") - - if not maximization: - ax.set_xlim(ax.get_xlim()[::-1]) - - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - - return dt_plot diff --git a/src/iohinspector/plot/plot_running_time.py b/src/iohinspector/plot/plot_running_time.py deleted file mode 100644 index 0519ecb..0000000 --- a/src/iohinspector/plot/plot_running_time.py +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file diff --git a/tests/data_processing/test_normalise_objectives.py b/tests/data_processing/test_normalise_objectives.py deleted file mode 100644 index c9b64b4..0000000 --- a/tests/data_processing/test_normalise_objectives.py +++ /dev/null @@ -1,77 +0,0 @@ -import unittest -import polars as pl -import numpy as np -import warnings -from iohinspector.data_processing import normalize_objectives - -class TestNormalizeObjectives(unittest.TestCase): - def setUp(self): - self.df = pl.DataFrame({ - "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], - "other": [10, 20, 30, 40, 50] - }) - - def test_basic_normalization(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"]) - self.assertIn("ert", normed.columns) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) - - def test_maximization(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"], maximize=True) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [0, 0.25, 0.5, 0.75, 1]) - - def test_bounds(self): - bounds = {"raw_y": (0, 10)} - normed = normalize_objectives(self.df, obj_cols=["raw_y"], bounds=bounds) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [0.9, 0.8, 0.7, 0.6, 0.5]) - - def test_log_scale(self): - df = pl.DataFrame({"raw_y": [1, 10, 100, 1000, 10000]}) - normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) - - def test_log_scale_with_zero_warns(self): - df = pl.DataFrame({"raw_y": [0, 1, 10]}) - with warnings.catch_warnings(record=True) as w: - warnings.simplefilter("always") - normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) - self.assertTrue(any("Lower bound" in str(warn.message) for warn in w)) - arr = normed["ert"].to_numpy() - self.assertTrue(np.all((arr >= 0) & (arr <= 1))) - - def test_multiple_objectives(self): - df = pl.DataFrame({ - "raw_y": [1, 2, 3], - "other": [10, 20, 30] - }) - normed = normalize_objectives(df, obj_cols=["raw_y", "other"]) - arr_raw_y = normed["ert_raw_y"].to_numpy() - np.testing.assert_allclose(arr_raw_y, [1.0, 0.5, 0.0]) - arr_other = normed["ert_other"].to_numpy() - np.testing.assert_allclose(arr_other, [1.0, 0.5, 0.0]) - - - def test_column_prefix(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"], prefix="normed") - self.assertIn("normed", normed.columns) - - def test_dict_log_and_maximize(self): - df = pl.DataFrame({"a": [1, 10, 100], "b": [3, 2, 1]}) - normed = normalize_objectives( - df, - obj_cols=["a", "b"], - log_scale={"a": True, "b": False}, - maximize={"a": True, "b": False} - ) - arr_raw_y = normed["ert_a"].to_numpy() - np.testing.assert_allclose(arr_raw_y, [0.0, 0.5, 1.0]) - arr_other = normed["ert_b"].to_numpy() - np.testing.assert_allclose(arr_other, [0.0, 0.5, 1.0]) - # a is maximized and log scaled, b is minimized and linear - -if __name__ == "__main__": - unittest.main() \ No newline at end of file diff --git a/tests/test_data/algorithm_A.zip b/tests/test_data/algorithm_A.zip deleted file mode 100644 index aa319acae5aa12ef94e46f61d69be8ca922963ff..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1566 zcmWIWW@Zs#00Exn3sGPOl;B}dU`WhK&o9a>$;gd&)Gw{zW?*CiNrH*c5MBm$3C)0v z-}QkRAUXi2Nz!O0r6iUl#-|y^2Nz_d7Nz1e_z#M~91I*7PBg-Au&2LAK~a8MW=?7m z$T}BKUn4!B-MBpR7iwSbL{G0)N1m4Nmag*^Qv9Bpd=k@R2`o5rdv^Tx{793(S0@}_ zfBWcXqwxO!) z*fw3>b7X)Z|zIN(f^(FlPZ+4E7>%x^>j0_B1ObiT= zD8?2OYG^Tm7W9yq*2^l+&%+h^{0)#~G*>1_ zenlKn{D1ar@jCUyp4|35?<|-5NtYd{)@?sLz*<*R*j<74!Z~UU^eHyEKSl+HtTD&(_&+a7GMZx>BQO^Se*PKh0mRCQ(-MHq!B=M2$%Yj2ncTKwbfF?+H{ne&)2BlDUc5ogbT{trq+)q7^{ 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normed = normalize_objectives(df, obj_cols=["raw_y", "other"]) + arr_raw_y = normed["ert_raw_y"].to_numpy() + np.testing.assert_allclose(arr_raw_y, [1.0, 0.5, 0.0]) + arr_other = normed["ert_other"].to_numpy() + np.testing.assert_allclose(arr_other, [1.0, 0.5, 0.0]) + + + def test_column_prefix(self): + normed = normalize_objectives(self.df, obj_cols=["raw_y"], prefix="normed") + self.assertIn("normed", normed.columns) + + def test_dict_log_and_maximize(self): + df = pl.DataFrame({"a": [1, 10, 100], "b": [3, 2, 1]}) + normed = normalize_objectives( + df, + obj_cols=["a", "b"], + log_scale={"a": True, "b": False}, + maximize={"a": True, "b": False} + ) + arr_raw_y = normed["ert_a"].to_numpy() + np.testing.assert_allclose(arr_raw_y, [0.0, 0.5, 1.0]) + arr_other = normed["ert_b"].to_numpy() + np.testing.assert_allclose(arr_other, [0.0, 0.5, 1.0]) + # a is maximized and log scaled, b is minimized and linear + + def test_add_normalized_objectives_basic(self): + df = pl.DataFrame({ + "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], + "other": [10, 20, 30, 40, 50] + }) + normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"]) + self.assertIn("obj1", normed.columns) + self.assertIn("obj2", normed.columns) + arr_obj1 = normed["obj1"].to_numpy() + arr_obj2 = normed["obj2"].to_numpy() + np.testing.assert_allclose(arr_obj1, [0, 0.25, 0.5, 0.75, 1]) + np.testing.assert_allclose(arr_obj2, [0, 0.25, 0.5, 0.75, 1]) + + def test_add_normalized_objectives_with_bounds(self): + df = pl.DataFrame({ + "raw_y": [1.0, 2.0, 3.0], + "other": [10, 20, 30] + }) + min_vals = pl.DataFrame({"raw_y": [0.0], "other": [0]}) + max_vals = pl.DataFrame({"raw_y": [10.0], "other": [40]}) + normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"], min_vals=min_vals, max_vals=max_vals) + arr_obj1 = normed["obj1"].to_numpy() + arr_obj2 = normed["obj2"].to_numpy() + np.testing.assert_allclose(arr_obj1, [0.1, 0.2, 0.3]) + np.testing.assert_allclose(arr_obj2, [0.25, 0.5, 0.75]) + + def test_add_normalized_objectives_single_objective(self): + df = pl.DataFrame({"raw_y": [1, 2, 3]}) + normed = add_normalized_objectives(df, obj_cols=["raw_y"]) + self.assertIn("obj", normed.columns) + arr = normed["obj"].to_numpy() + np.testing.assert_allclose(arr, [0, 0.5, 1]) + + def test_add_normalized_objectives_no_min_max(self): + df = pl.DataFrame({"raw_y": [5, 10, 15]}) + normed = add_normalized_objectives(df, obj_cols=["raw_y"]) + arr = normed["obj"].to_numpy() + np.testing.assert_allclose(arr, [0, 0.5, 1]) + + def test_transform_fval_basic(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df) + arr = res["eaf"].to_numpy() + # log10(1e-8) = -8, log10(1e8) = 8 + # normalized = (log10(x) - (-8)) / (8 - (-8)) = (log10(x) + 8) / 16 + expected = [np.abs((np.log10(x) - 8) / 16) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_maximization(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df, maximization=True) + arr = res["eaf"].to_numpy() + expected = [(np.log10(x) + 8) / 16 for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_minimization(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df, maximization=False) + arr = res["eaf"].to_numpy() + expected = [1 - ((np.log10(x) + 8) / 16) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_linear_scale(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df, scale_log=False) + arr = res["eaf"].to_numpy() + expected = [1-(x - 1e-8) / (1e8 - 1e-8) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_custom_bounds(self): + df = pl.DataFrame({"raw_y": [0, 5, 10]}) + res = transform_fval(df, lb=0, ub=10, scale_log=False) + arr = res["eaf"].to_numpy() + # For minimization, 0 maps to 1, 10 maps to 0 + expected = [1 - (x / 10) for x in [0, 5, 10]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_column_name(self): + df = pl.DataFrame({"score": [1, 10, 100]}) + res = transform_fval(df, lb=1, ub=100, scale_log=True, fval_col="score") + arr = res["eaf"].to_numpy() + expected = [1- (np.log10(x) - np.log10(1)) / (np.log10(100) - np.log10(1)) for x in [1, 10, 100]] + np.testing.assert_allclose(arr, expected) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/data_processing/test_utils.py b/tests/test_metrics/test_utils.py similarity index 98% rename from tests/data_processing/test_utils.py rename to tests/test_metrics/test_utils.py index f2d3c58..9482304 100644 --- a/tests/data_processing/test_utils.py +++ b/tests/test_metrics/test_utils.py @@ -1,6 +1,6 @@ import unittest import numpy as np -from iohinspector.data_processing.utils import get_sequence, geometric_mean +from iohinspector.metrics.utils import get_sequence, geometric_mean import polars as pl class TestGetSequence(unittest.TestCase): From e12d82c7093604f431703dc73c88a27da3fcaf3a Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Thu, 16 Oct 2025 10:32:24 +0200 Subject: [PATCH 07/17] all tested --- examples/MO_Examples.ipynb | 61 +- examples/SO_Examples.ipynb | 68 +- src/iohinspector/__init__.py | 5 +- src/iohinspector/metrics/__init__.py | 9 +- src/iohinspector/metrics/attractor_network.py | 113 +++ src/iohinspector/metrics/eaf.py | 53 ++ src/iohinspector/metrics/ecdf.py | 30 +- src/iohinspector/metrics/fixed_budget.py | 2 +- src/iohinspector/metrics/fixed_target.py | 2 +- .../metrics/normalise_objectives.py | 127 --- src/iohinspector/metrics/ranking.py | 84 ++ src/iohinspector/metrics/trajectory.py | 45 + src/iohinspector/metrics/utils.py | 133 ++- src/iohinspector/old_metrics.py | 234 ----- src/iohinspector/plot.py | 868 ------------------ src/iohinspector/plots/__init__.py | 16 + src/iohinspector/plots/attractor_network.py | 122 +++ src/iohinspector/plots/eaf.py | 205 +++++ src/iohinspector/plots/ecdf.py | 86 ++ src/iohinspector/plots/fixed_budget.py | 79 ++ src/iohinspector/plots/fixed_target.py | 87 ++ src/iohinspector/plots/multi_objective.py | 93 ++ src/iohinspector/plots/ranking.py | 186 ++++ src/iohinspector/plots/single_run.py | 50 + tests/test_metrics/test_attractor_network.py | 52 ++ tests/test_metrics/test_eaf.py | 74 ++ tests/test_metrics/test_ecdf.py | 10 + .../test_metrics/test_normalise_objectives.py | 162 ---- tests/test_metrics/test_ranking.py | 51 + tests/test_metrics/test_trajectory.py | 66 ++ tests/test_metrics/test_utils.py | 179 +++- tests/test_plots/__init__.py | 0 tests/test_plots/test_attractor_network.py | 26 + tests/test_plots/test_eaf.py | 50 + tests/test_plots/test_ecdf.py | 31 + tests/test_plots/test_fixed_budget.py | 33 + tests/test_plots/test_fixed_target.py | 33 + tests/test_plots/test_multi_objective.py | 187 ++++ tests/test_plots/test_ranking.py | 138 +++ tests/test_plots/test_single_run.py | 81 ++ 40 files changed, 2428 insertions(+), 1503 deletions(-) create mode 100644 src/iohinspector/metrics/attractor_network.py create mode 100644 src/iohinspector/metrics/eaf.py delete mode 100644 src/iohinspector/metrics/normalise_objectives.py create mode 100644 src/iohinspector/metrics/ranking.py create mode 100644 src/iohinspector/metrics/trajectory.py delete mode 100644 src/iohinspector/old_metrics.py delete mode 100644 src/iohinspector/plot.py create mode 100644 src/iohinspector/plots/__init__.py create mode 100644 src/iohinspector/plots/attractor_network.py create mode 100644 src/iohinspector/plots/eaf.py create mode 100644 src/iohinspector/plots/ecdf.py create mode 100644 src/iohinspector/plots/fixed_budget.py create mode 100644 src/iohinspector/plots/fixed_target.py create mode 100644 src/iohinspector/plots/multi_objective.py create mode 100644 src/iohinspector/plots/ranking.py create mode 100644 src/iohinspector/plots/single_run.py create mode 100644 tests/test_metrics/test_attractor_network.py create mode 100644 tests/test_metrics/test_eaf.py delete mode 100644 tests/test_metrics/test_normalise_objectives.py create mode 100644 tests/test_metrics/test_ranking.py create mode 100644 tests/test_metrics/test_trajectory.py create mode 100644 tests/test_plots/__init__.py create mode 100644 tests/test_plots/test_attractor_network.py create mode 100644 tests/test_plots/test_eaf.py create mode 100644 tests/test_plots/test_ecdf.py create mode 100644 tests/test_plots/test_fixed_budget.py create mode 100644 tests/test_plots/test_fixed_target.py create mode 100644 tests/test_plots/test_multi_objective.py create mode 100644 tests/test_plots/test_ranking.py create mode 100644 tests/test_plots/test_single_run.py diff --git a/examples/MO_Examples.ipynb b/examples/MO_Examples.ipynb index b965881..7f38e21 100644 --- a/examples/MO_Examples.ipynb +++ b/examples/MO_Examples.ipynb @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 57, "metadata": {}, "outputs": [], "source": [ @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 58, "metadata": {}, "outputs": [], "source": [ @@ -75,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 59, "metadata": {}, "outputs": [ { @@ -122,7 +122,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 32, + "execution_count": 59, "metadata": {}, "output_type": "execute_result" } @@ -140,7 +140,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 60, "metadata": {}, "outputs": [ { @@ -156,7 +156,7 @@ " Function(id=0, name='pymoo_ZDT1', maximization=False)))" ] }, - "execution_count": 33, + "execution_count": 60, "metadata": {}, "output_type": "execute_result" } @@ -182,7 +182,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 61, "metadata": {}, "outputs": [], "source": [ @@ -192,7 +192,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 62, "metadata": {}, "outputs": [ { @@ -238,7 +238,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 35, + "execution_count": 62, "metadata": {}, "output_type": "execute_result" } @@ -249,7 +249,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 63, "metadata": {}, "outputs": [], "source": [ @@ -258,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 64, "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 65, "metadata": {}, "outputs": [ { @@ -299,7 +299,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 38, + "execution_count": 65, "metadata": {}, "output_type": "execute_result" } @@ -324,7 +324,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 66, "metadata": {}, "outputs": [ { @@ -371,7 +371,7 @@ "└─────────┴─────────────┴────────────┴────────────┴───┴─────────┴────────────┴──────────┴──────────┘" ] }, - "execution_count": 39, + "execution_count": 66, "metadata": {}, "output_type": "execute_result" } @@ -397,12 +397,12 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 67, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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RSZMm7XH81772NbKysjqcd38544wzkpXBezJjxoxk8FVcXNzhnMccc0yy8nBPDj74YEpLS5Nr2Lkqckcej4exY8eyfv16TNOkuLiYQw45pMN17Kvzzjtvr19PS0tj7NixbNy4EdM0KSkp6XBdtbW1fPLJJ6xfv56mpiYCgUC7343ly5cnH69atarD+frivX799deTjy+66KK93nu74447Lvn4gw8+4Hvf+16nrhMRERERERHZWVMgSklDgJrWCF6HjaJMzz6fudMZClGlx3z88cf88Ic/5P333++wInO7+vr6bt1r1apVyccHHXQQ6enpHV5z+OGH7/XrFRUVyWAW4Kijjupwzry8PCZMmMCGDRsAWLFixV5D1EMPPbTDOfenzoSRO1b4dqba8uCDD+5wzI5B8pQpUzocn52d3aU19ISefG/WrVvHrbfeyhtvvNGpNn3o3O9GX7zXH3/8cfLx888/z7vvvtvhnNsPKIO2rS9EREREREREuiocS1DeGKSsKUjCgCGpLuy2/ddkPyhD1O0nQ3/66acsX76cTz/9lM8//5xYLAbA3LlzWbJkyaC7d1/6+9//zpVXXtnp8HS77rZm19XVJR8PHz68U9cMGzas03N6PB7y8vI6Ne+oUaOSIWpHwVdn59xfOnPSvcPx371Etv8c7+uc29vguzO+M2voCT313rz11lt8/etf79SevDvqzO9GX7zXlZWVycfPPPNMh/PtrKmpqcvXiIiIiIiIyIHLMExqWsOU1AfxhaJkeZ14nfs/0hx0IepLL73ExRdfTDAYPKDu3ZfWrVvH1VdfnQxQp0yZwne+8x2OPPJIRo4cSXp6eruW8csvv5zHHnsMIHk4TVf5/f7k490daLM7Ox/ktLc5tx+m1Bk7ju0o+PJ4PJ2ed3/ojXL3rs65P0ruu6Mn1lVXV8cFF1yQDFBHjhzJNddcwzHHHMOYMWPIzMzE7XYn73X77bfz85//HOjc70ZfvNc7VpV2Rzwe3+c1iIiIiIiIyIGhORSjpCFAdXMYl91GUcb+ad3fnUEXovp8vj4LMfvy3n3pnnvuSQYjJ510Eq+88spe913siYOBdgxEO/ueBwKBTs/Z0dg9zbvzCelyYHvooYeSoeO0adN477339rr1xP46NGtfpKSkJF/TihUrmDFjRh+vSERERERERAabSDxBZVOIksYg0bhBbqoLx35s3d+dQReibpefn8/s2bOTH2+99Rb33nvvoL93X1i0aFHy8R133LHXABWgpKRkn++Zm5ubfFxeXt6pazoat2OrfSgUor6+vt199mTHw5Y6M14OHDv+bvzkJz/pcO/envjd6G35+fnJELW6urqPVyMiIiIiIiKDiWma1LVGKG4I0BiIkeFxkJPi6utlAYMwRD355JMpKSlhxIgR7T6/dOnSQX3vvrTjHokdHcbT3NzM559/vs/3nD59evLx+vXraW1t7bAKdNmyZXv9+tChQxkyZEjycKmPPvqIM888c6/X1NfX8+WXXyafz5w5s4OV96z+2govbbryu5FIJPjwww97e0n77PDDD0/+zH/44YeccsopfbwiERERERERGQxawzHKGoNU+MI4rBYKM9xY+1Hu0bd1sL2goKBglxDzQLh3X7Ja//tj1FFr/cMPP9wjBwNNnjyZIUOGAG2H3zz77LN7HW8YBgsXLuxw3vnz5ycfP/roox2Of/TRR5N7VxYVFTFx4sQOr+lJO+41u78OXJLO68rvxksvvTQgKjtPP/305OO///3vhMPhPlyNiIiIiIiIDHSxhEFJQ4CVpT5KG4NkeR3kpLr6VYAKgzBElf1vzJgxycevvPLKHsdt2rQpeWjOvrJarVx22WXJ57fffjuNjY17HP+nP/2pXcXonlx99dXJxy+++CJvvfXWHseWlJTwf//3f+2u3d+VoTk5OcnHFRUV+/Xe0rHO/m7U1dXx3e9+d38saZ+dc845jBs3DoCqqiquu+665KFyHfH7/V3ab1hEREREREQGL9M0qfdHWF3mY31VCzaLhaGZXlx2W18vbbcUoso+O+OMM5KPv/e97+02eFy0aBHz5s2jtbW13Wn2++J//ud/yM7OBtr2Oz3ppJPYvHlzuzGmafLAAw/wve99D5er4z005s+f3649+dxzz+Wf//znLuM+++wzTjjhBHw+HwDDhw/npptu2odX0z0HH3xw8vG///3vfT45XXrWjr8bv/rVr3jyySd3GbNixQrmzp1LWVlZj/1u9CabzcaDDz6Izdb2H7VHHnmE0047jfXr1+/xmlWrVnHrrbcyfPhwtm3btr+WKiIiIiIiIv1UMBpnY3Urq0p9NIdiFKR7SPc4+npZezXo9kSV/e+WW27h4Ycfpq6ujsbGRk4++WRmzpzJ5MmTsVgsrFixgrVr1wJw0kknMWTIEJ544ol9vm9+fj5/+ctfuOCCCzAMg+XLlzNp0iSOOeYYxo0bRyAQ4IMPPqCsrAyAe+65hxtvvBFo32a9s0ceeYSjjz6aLVu24Pf7Of/88xk/fjyHH344TqeTdevWsXTp0mT1XUpKCgsXLiQzM3OfX1NXHXbYYQwfPpyysjKqqqqYNGkSX/va18jNzU1Wxc6ePZsLLrhgv69N4LLLLuP3v/89X375JZFIhEsuuYQ777yTadOm4Xa7WbNmDcuXLwdg2rRpnHTSSdx11119vOqOnXDCCTz44INce+21JBIJ3njjDd58800mT57M1KlTSU9PJxgMUlVVxerVq6mrq+vrJYuIiIiIiEg/EE8YVLeEKW4I4g/HyUlx4nb0z8rTnSlElX02ZMgQXn75Zc4880zq6+uBtuq6FStWtBt31lln8eijj3LzzTf32L3PPfdcnnjiCa6++mr8fj+JRIIlS5awZMmS5BiXy8Uf//hH5s2bl/zc3k5Jz8/P58MPP+Siiy5i8eLFQNtWBJs2bdpl7Lhx43jqqaeYPXt2j72mrrBarTzwwAOcc845RKNRqqurefzxx9uNueyyyxSi9hGXy8Wrr77KKaecwtatW4G2g9B2rto8+uijeeaZZ3jooYf6YpndctVVVzFu3DiuvvpqNm3ahGmarF27NvkPJrszZcqUZPW4iIiIiIiIHFiaAlGKGwLUtERIddkpynAPqAOzFaJKjzjyyCNZu3Yt99xzD6+++moyMCosLOTQQw9lwYIF7Vqbe9JFF13EMcccwx//+Edee+01SktLsVgsDBs2jK997Wtcc801TJo0iaVLlyav6ahqND8/n0WLFvHmm2/yzDPP8MEHH1BdXU0sFmPIkCHMmDGDs846iwULFuBw9G25+emnn87y5cu5//77+eCDDygtLcXv93d6n0rpXRMmTGDlypXcf//9vPDCC2zcuJFoNEpBQQGHHHIIF110Eeeff36yPX4gmT9/PuvXr+ell17itdde45NPPqG6upqWlha8Xi/5+flMmjSJo446ilNOOYXp06f39ZJFRERERERkPwvHEpQ1BilrCmIYkJ/mwm4beDuMWswDJGm5/fbbk4cazZ07t12l4kC5dyQSIRKJJJ+3tLQwfPhwmpub91pZuSfhcJht27YxevTodqe8D1YPPfQQ3/nOdwC45pprePDBB/t4RSLSVQfan1siIiIiIiIDVcIwqW0NU1wfoDkUI8vrxOvsf/WcWyrqOPuI8R3mawMv9j2A/epXvyIjIyP5MXz48L5e0oDyzDPPJB/3Vfu9iIiIiIiIiMhg1xyMsaaimS/Km4nFTYoyPP0yQAWobg51apxC1AHktttuo7m5Ofmx/cAk6dgLL7zAokWLAHC73Zx99tl9vCIRERERERERkcElEk+wpdbPyrImalvD5Ka6yEpx9su9T2MJg8c/LubXb27o1HiFqAOIy+UiPT293ceB7qOPPuKqq65i1apVu/16JBLhnnvu4cILL0x+7jvf+Q5ZWVn7aYUiIiIiIiIiIoObYZjUtoRZWepjU60fl91GQboHRz/d+3RjdSs3P72Sf35WjtHJjU77Zx2tSCdFo1EefvhhHn74YYYPH8706dPJz8/HNE0qKir4+OOPaW5uTo6fPHkyd955Zx+uWERERERERERk8GgNxyhpCFLVHMJhtVKY4cbaDytPoa1S9h9LS3l5VQWGCZleB2fPHs3t93R8rUJUGTTKysr2usXBSSedxFNPPUVKSsp+XJX0lsbGRn7605/u8zw333wz48eP74EViYiIiIiIiBw4YgmDSl+I4oYA4ahBbqoLp71/Vp4CrKtq4b5Fm6jwte2BOm9iHlfNGUNdo69T1ytElQHt2GOPZfHixbz++ut8+umnVFVVUV9fT0tLC+np6RQVFTFnzhy++c1vMnfu3L5ervSglpYW7r///n2e59xzz1WIKiIiIiIiItJJpmlS749S0hCgwR8hze0gO9PV18vao3AswROflPDq6kpMIDvFyfXzxnHY6GwA6jo5j0JUGdCsVivz589n/vz5fb0UEREREREREZFBLRCJU9oYoKIpjNViIT/dg83aP1v3Ab4o93Hf4s1Ut4QBOOGgIXx7zhhSXV2PRBWiisiANGrUKEyzk7s/i4iIiIiIiEi3xRMG1S1hiusD+CNxclJcuB22vl7WHgWjcR77uITXv6gCIDfVxQ3zx3HoyO4fNK4QVURERERERERERHarMdDWul/TEiHVZacow4Olnx4cBbCqzMcfF2+itjUCwMlTCvjW0aPwOvctBlWI2oHi4mJGjx6dfP7II49w+eWX992CREREREREREREelkomqCsMUiZL4hpQEG6u1+37gcicf7+4Tb+va4GgCFpLm46bjzThmf2yPyDMkQ99dRTqaysbPe56urq5OPly5czffr0Xa57/fXXKSoqGrD3FhERERERERER2RcJw6Tmq9b9lnCMbK8Lj7P/tu4DLC9p5P53NlPvjwJw+iGFXHrkqB5d96AMUdetW0dJSckevx4IBFi9evUun49GowP63iIiIiIiIiIiIt3VHIxR3BCgujmEx9n/W/f94TgPf7CVRRtqASjMcHPTceM5eGhGj99rUIaoIiIiIiIiIiIi0jnhWIKKphBljUFihkFemhuHzdrXy9qrZdsauP+dLTQGo1iAM6cVseCIkb124NWgDFGLi4t7bK6ungDek/cWERERERERERHpLYZhUuePsK0+gC8YJdPjJMfl6utl7VVLKMZf39/Ku1/WATA008PNx4/noML0Xr3voAxRRUREREREREREZM9awjFKG4JU+kI4bVYKMzxY+3HrPsCHm+v587tb8IViWC1w9oyhXHjYCFz23t+zVSGqiIiIiIiIiIjIASIaN6j0BSlpDBKOGuSmunDa+3frvi8Y5c/vbeXDzfUADM/2csvx45mQn7bf1qAQVUREREREREREZJAzTZN6f5TihgAN/ggZbifZmf27dd80Td7fVM9f3ttCSziO1QLnHjqcb84evt/3bFWIKiIiIiIiIiIiMogFInFKGgNUNoWxWiwUpHuwWft3635TIMoD727mk62NAIzK8XLz8RMYNyS1T9ajEFVERERERERERGQQiicMqprDFDcECETi5KS4eu30+p5imibvbKzjofe34o/EsVktXDBrOOceOqzHq0+tER+pTes6NVYhqoiIiIiIiIiIyCBimiaNgbbW/brWCKkuB0MzvX29rA41+CP86Z3NLC9pAmBsXgo3Hz+B0bkpPXofSzyEo7UMp78Cr7+sU9coRBURERERERERERkkQtEEZY1BynxBMBgQrfumafKf9TX87YNtBKMJ7FYLFx02gm/MHNazazdiOPxVOFtLsUVbibuzSNjcnbpUIaqIiIiIiIiIiMgAlzBMalrCbKsP0BqKkZ3iwuPs3637ALWtYf60eDMry3wATMxP46bjxzMiuwcrZ00De6gOZ3MJtnADhjOVaGoRWDof0CpEFRERERERERERGcB8wSglDUGqmkN4nXaKMj1YuhAQ9gXDNHlrbTWPfFhMKJbAabNy8eEj+Pr0oT1afWoLN+FoKcERrMGwOYilFoCl6+GyQlQREREREREREZEBKBxLUN4UpKwxSMKAIWnuHj98qTdUN4f54+JNfF7RDMBBhencfNx4hmZ5euwe1lgAR2sFDn85mHHinlxMm6Pb8ylEFRERERERERERGUAMw6S2NUJxQwBfMEqW14nX2f9jPsM0ee3zKh77uJhI3MBpt3LZkSM57ZCiHqs+tSSi2P1VOFtLsMaCxD1ZmPZ9D2f7fzQtInu1ZMkSrrvuOmbNmkVeXh5OpxOPx8OQIUOYNWsWF110EXfffTfLly/HNM3dznH77bdjsVjafXz3u9/t0jpee+21XeaYN2/efnsN3bG7193Zj1GjRu12zkcffXSXsWeffXaX1rV27dpO329Pamtreeihhzj77LM56KCDyM7Oxu12M3z4cA477DC+//3vs2TJkn1+Pw3DYOTIke3WunTp0n2aU0RERERERPasJRxjTWUzn5f7iMQMCjM8AyJArfSF+NGLX/DX97cSiRscXJTOny6cwZnTeqh930hgD1TjqV2Bu2kdptVKLK2oRwJUUCWqyIC1fv16rrjiCj755JNdvhaLxQiHw9TV1fHZZ5+xcOFCAKZMmcKaNWs6Nf/ChQv57W9/i93euT8mHnvssc4v/iu9/Rr6i9dff52GhgZycnI6Nb477+V2gUCA3/zmN/z+978nGAzu8vXy8nLKy8v59NNP+d3vfsdhhx3G73//e+bMmdOt+73zzjuUlpa2+9xjjz3G4Ycf3q35REREREREZPeicYNKX5CShiDhuEFeqmtAtO4nDJNXV1fyxCclRBMGboeVy48azSkHF2DtiX1bTRNbpAlHS+lX+546iaUUgqVn3xuFqCID0MqVKznuuOPw+XzJz+Xn5zNr1iwKCgqwWCw0NDSwZs0aNm/enKw23HF8R2pqanjrrbc47bTTOhzr8/l49dVX+91r6IqioqIuVYx2NhAFiEajPP3001x//fUdjjUMg3/84x+dnntHlZWVnHLKKXz++efJz1ksFmbNmsWYMWNIS0ujurqapUuXUldXB8CyZcuYO3cud999NzfddFOX77m7wPfpp5/m7rvvxuVydet1iIiIiIiIyH+ZpkmdP0JxfYDGQJQMt5PslIHx962yxiD3LtrExppWAKYPz+SG+ePIT3f3yPzWqB9HaxmOQCWYBjFvLlg7v++pJR6isLRzeYZCVJEBJhaLcdFFFyXDxKKiIu6//37OPPNMrNZd/5Wlrq6Ol19+mSeeeIKtW7d2OP/kyZNZt24dAI8//ninQtRnn32WcDi8y/V99Rq6Y/z48fzpT3/q0TnHjRtHSUkJsViMxx9/vFMh6ttvv01lZSXQufdyu+rqao488shkVajFYuHKK6/kZz/7GUOHDm03NpFI8Nprr3HLLbewbds2DMPg5ptvJhgM8sMf/rDTr8/v9/PCCy8kn3s8HkKhEE1NTbz66quce+65nZ5LREREREREduWPxCltCFDhC2O3WihI9/ToyfW9JWGYvLCynIXLSoklTLxOG1ccPZqvTc7H0gPVp5ZEBIe/CmdrKZZ4kLg7G9PetWDWU/8F+SvuIdRU3anx/b/mV0Taeemll9iwYQPQFlq98847nHXWWbsNHwHy8vK48soreffdd1myZEmH8x9yyCFMmzYNgFdeeYXm5uYOr9lejehwOLjwwgv7/DX0Fzk5OZx66qlAW8Xnxo0bO7xmx8rOSy+9tFP3MU2TSy+9NBmg2mw2nnrqKf7617/uEqBu//qZZ57J6tWrOfLII5Of/8lPfsJ7773XqXsCPPfccwQCAaAtML722mt3+zpERERERESka2IJg9KGACtLmyhrCpLldZCb6hoQAWpJQ4D/fW41j39cQixhcujILP504UxOmlKw7wGqkcAeqMJTswJX4wYMq41YalGXAlRLPEze6j8z7IPbcARriDgyO3WdQlSRAebf//538vHXv/51JkyY0Olrx44d26lxl112GQDhcJhnn312r2O3bNnCRx99BMCpp55Kbm5uh/Pvj9fQX2x/L6GtsndvWltbeemllwCYNm1aMszuyCOPPMJ//vOf5PO77rqLb37zmx1el5aWxhtvvMGwYcOAtgrVyy+/nEQi0an77hiULliwoF3o++abb1JbW9upeURERERERKSNaZo0+CN8Xu5jfXULViwUZXhx2W19vbQOxRMGz3xayi3PrGJzrZ8Ul41bjh/Pz06fTF7aPm4/YJrYQvV46j/HU/c5FiNKLLUAw5nWpWk89V8wYvENZG77FwC1Q09ky7Tvd+pahagiA0xFRUXy8ciRI3vlHhdddFHyQKmOgr8dv97Zysn98Rr6i9NOOy25f+qTTz6Z3Nt1d5577rnkYVBdqUL93e9+l3w+c+ZMbrnllk6vLyMjg/vuuy/5fNu2bTz//PMdXldSUsK7776bfL5gwQKmTZvGIYccAkA8Hu/23q4iIiIiIiIHomA0zsbqVlaW+fAFYuSneUj3dH5/z760tc7P//xzNU8uLSVumBw+Opv7L5zJ8Qfte/u+NdqCq3EdntqV2MINxLx5JNxZXTo4yhIPk/f5Xxj2wW04g9VE3bmsnf7/qJ9xI8PyOy4GA4WoIgPOji3v27Zt65V75Ofn87WvfQ2ADz/8cI/3MU2TJ554AoDs7GxOP/30Ts2/P15Df+F0OrngggsAKC0t3et2BNsDaZvNxsUXX9yp+d977z3Wr1+ffH7LLbfscVuEPTnrrLMYM2ZM8vmDDz7Y4TWPP/54MhA+6qijkhXCl1xySXKMWvpFREREREQ6ljBMKnwhVpT6KK4PkOF2MCTdPSBa92MJgyeXlvC9f65ma32ANJed/zlxAj8+9SByUvet+tQSD+P0bcFbuwJnaxkJVwZx7xCwdu2IJ3f9Gka8cyOZW9sOkKobeiKfH3EPaeOOZFx+Kunuzs2nEFVkgNmxnf3VV1/t9MFDXbW9EtI0zT1Wo77//vvJEPSCCy7A6XR2au799Rr6ix2rSvf0Xu5Y2fm1r32N/Pz8Ts39zjvvJB87nU7OOeecLq/PYrG028v2448/JhKJ7PWaHV/HjsHpxRdfnAxxV69ezerVq7u8HhERERERkQNFUyDKF+U+1lQ0YxomRZke3I7+37oPsKmmle8+s4pnPi0jYZgcNTaH+y+eybyJQ/at+tSI4/BX4K1ZgavpSwyrs8v7nkJbCJu7vfo0UEXMncu6aT+hevoNjBk2hOFZXpy2zkejClFFBpizzjor+TgUCnHsscfy29/+tl2LfE/4+te/TkZGBkCy2nRn3Wnlh/33GvqLww8/nIkTJwLw/PPPJ1v2d/TEE08kKzu78l5+8MEHycdTp07F6/V2e43bRSIRli9fvsexH374IZs3bwbagtvzzz8/+bWioiKOP/745HNVo4qIiIiIiOwqHEuwuaaVVWVN1PujDEl1kel19sjJ9b0tGjd47KNi/ve51ZQ0BsnwOLj15EncdspBZHk7V1y1W6aJPViHp241nvovwIwRSy3CcKZ2eart1adZW1/Fgkn90BNYdcQf8Iw9ggn5aWR7nXT1re5a/auI9Ln58+dzxhln8OqrbWXoDQ0N/OAHP+DWW29lwoQJHHbYYcyaNYsjjjiCmTNnJvc27Sq3283555/PQw89xJYtW/jwww85+uijk18Ph8M899xzAEyYMIEjjjii372Grti0aRM33HBDp8dfcskl7YLHjlx66aX8+Mc/prW1lRdffHGXdv3tQXVGRka7kLkjxcXFyccHH3xwp6/b2c7XFhcXt/t+72jHYPS0004jOzu73dcvueSS5EFX//jHP7jrrrv2y/dQRERERESkvzMMk9rWCMX1AZqCUbJTnHidA+fvSxuqW7hv0SbKmkIAHDs+l+8cO5aMfdy71Rppxtlahj1QCRYrUW8+WLtekWuJh8lZ/wSZW17BgknMncvmSVcTKZzN6CwvOSldD0+3GzjfJekXTNMkFOvcyd0HCo/Dtt//peipp57i0ksv5cUXX0x+zjRNNm7cyMaNG5OBXEpKCqeffjpXX3018+fP7/J9Lr30Uh566CGgrep0x1DtpZdeorm5OTmuv76GzqqsrOT+++/v9PhZs2Z1KURdsGABP/nJT5LbI+wYon7yySd8+eWXAJx33nm43Z1vUWhsbEw+zsrK6vR1O9v52h3n3VE4HObZZ59NPt+xlX+7b3zjG1x77bUEAgFqa2t58803O71froiIiIiIyGDVHIpR0hCgujmMy25jaKZnQFSeAkTiCZ78pJRXVldgmJDpdXDdvHEcOSZnn+a1xEM4/BU4W8uwJKLEPdmYtu7tpepuWEf+intwBioBqB92AlvHXkJ2Vg6jMj14nPu2TYJCVOmSUCzB5J++1dfL6FfW/eKk/f6vRqmpqbzwwgu8/vrr3HPPPSxatAjDMHYZFwgEeOaZZ3jmmWc488wzefTRR7sUtM2ZM4cxY8awdetWnn32We677z5crrY/zLZXI1oslt0Gaf3lNfQXI0aMYN68ebzzzjssWrSIqqoqCgsLgfaVnV0NpFtbW5OPU1JSur2+1NT27REtLS27HbdjeJ6dnc1pp522y5iUlBS+8Y1vJIPwxx57TCGqiIiIiIgcsCLxBJVNIUoag0TjBrmpLhxd2Iuzr62tbOa+RZuobA4DMH9iHlcdM4Y09z5UnxoxHIEanC0l2KItxN2ZGJ7uBbK7Vp/msHnSNYQKZjMy001uqpueeLsHzndMRHZx6qmn8u9//5vq6mqeffZZbrnlFo455phdAjGAV155hWOOOaZd6NYZ2wNSn8/HK6+8AkB1dXWyXXvu3LmMGDGiX7+Gzpg7dy6maXb64/LLL+/yPbYHpIlEgieffBKAaDTKM888A8Do0aOZM2dOl+ZMS0tLPg4EAl1e03Z+v7/d8/T09N2O2zHwPf/88/d4mNiOwfqrr75KU1NTt9cmIiIiIiIyEJmmSW1LmNVlPjbW+HHZbRRmeAZMgBqOJfjre1u47YUvqGwOk53i5KenT+Z7J07sfoBqGtiDNXhrVuKuXwMkiKYWYTi6VxTkbljHiHduImvLy1gwaRx2PCsP/wPWEUcwoSCV/PSeCVBBlajSRR6HjXW/OKmvl9GvePrBqXl5eXmcd955nHfeeQDE43E++eQTHnnkER5//HHi8TgAa9eu5cc//jH33Xdfp+e+9NJL+fnPfw60tfSfd955/OMf/yCRSCS/3tevobGxkZ/+9Kd7nf+II45gwYIFPbLW7jr33HO5/vrrCQaDPPHEE3z/+99vFzBecsklXW7lyM7OTl6/pxb8ztg55Nx5n1OAqqqqZHgOu2/l3+7444+nqKiIyspKIpEITz/9NNdee2231yciIiIiIjKQtIZjlDUGqfCFcVgtFGa4sQ6Q1n2Az8t93Ld4EzUtEQBOnJzPFUePJtXV/SjRFvbhaC3FEazCtDqIpeaDpXuZiiURIWfdE2R+FZ7G3NlsnXQtrUNmMSzTzZB0N3Zrz77fClGlSywWy4Da8PhAZbfbmTNnDnPmzOHb3/42J510UrLS8KGHHuI3v/kNHo+nU3ONGTOGOXPm8MEHH/Dmm29SV1fH448/DoDX6+Xcc8/t89fQ0tLS4X6mfr+/z0PU1NRUvvGNb/Dkk0/yxRdfsHLlyuR7Cd0LpEeNGsWWLVsAWLNmTbfXtvO1o0aN2mXMk08+mQzPx4wZw1FHHbXH+axWKxdddBG/+93vgLYKVoWoIiIiIiIy2MUSBlW+EMUNQYLROLmpLlz2vi++6qxgNM6jHxXzxppqAPLSXNwwfxwzR3R/Wz1LLIiztRxHoByLESfuzsW0dX8rAHfDevJX3oPTXwFA47Dj2DTmctLSM5mQ5SXd0zu51cCoHxaRbjvqqKP40Y9+lHweDof59NNPuzTH9nAvHo/zgx/8gM8//xyAs88+u107eW/pidfQX+wYlP7+97/njTfeAODoo49m7NixXZ5vx8O+vvjiC4LBYLfWtXTp0uRjl8vFrFmzdhmzYyv/1q1bsVgse/3YHqBun3/jxo3dWpuIiIiIiEh/Z5om9f4Iq8t8rKtqwWaxMDTTO6AC1BWlTdywcGUyQD3l4AL+dOGMbgeolkQUR0sJ3prPcDVvIWH3Eksp6HaAaklEyF3zN4a9/wOc/gri7my+nP5jNk++gaIhuYzPT+t6gBoLgdG5A9QVooocAE4++eR2z6uqqrp0/fnnn588Mf7RRx9Nfr6nWvk7Y2+vYdSoUR3uYbrjuvvS8ccfz9ChQwH4xz/+QSwWA7r/Xs6fPz/5OBqN8txzz3V5DtM0WbhwYfL5UUcdlTxAbLvPPvuMtWvXdmuN2+0YwoqIiIiIiAwWwWicjdWtrCr10RyKUZDuId2zD4cu7WeBSJz7Fm/iZ6+spa41Qn66izvOOpjr5o3rXjeyaWAPVOOpXYW7cT2mBaKpRZgOb7fX6G5cz4h3biZr84tYMGkadhyfHfYHIkMPY/yQNIZne3HYuti+H2yEkA9yOlfQpL5skQPA9gB0u50Dso5kZGRw5pln8uyzzyY/V1RUxAknnNAj6+uMfX0N/YXVauXiiy/mrrvuSn7O7XZz/vnnd2u+uXPnMnHixGSV57333suCBQuwWjv/b2QvvfQSW7duTT6/5pprdhmzYwCanZ3N+PHjOzW3z+dLru2JJ57gjjvu6NLaRERERERE+qt4wqC6JUxxQxB/OE5OihN3Pzg3pSuWFzfyp3c20xCIAnD61EIuPWIUHmf3Xoct3ISjpQRHsAbD5iCW0v19T+GrvU/X/4PMzS9hwSDuyqZ48rXU5xxKfrqLokwPLnsX/45pxKG1BpwpUDQdzM4daqUQVeQAsHr16nbPR4wY0eU5Lr300nYh6sUXX7xfw7CeeA39xaWXXtouRD3jjDPIzMzs1lwWi4X//d//5aqrrgJgxYoV3HPPPXzve9/r1PXNzc3cdNNNyedjxozhnHPOaTcmFou1q1T98Y9/3On5a2trKSoqIpFIUF5ezuLFi/dr+C4iIiIiItIbmgJRihsC1LRESHXZKcpwd/mg4L7UGo7x8PvbWLyxFoDCDDc3Hz+eKUUZ3ZrPGgvgaC3D4a8EM07MmwvWfavGdTduIH/FPTj95QD4hh3HxjGX4k7JZHy2l2yvky6/5bEgBBogrRDyJoA7A1paOnWpQlSRAeYPf/gDU6dO7XQQFQwGufPOO5PP8/PzmT59epfve/LJJ7fbh3TcuHFdnmO7vnoN/cWUKVNYsWJF8pCm4cOH79N8V1xxBQsXLmTx4sUA/OAHP2Do0KFccMEFe73O7/dz6qmnUl7e9h8km83GI488gs3W/l8JX3vtNerr64G2StoLL7yw02sbMmQIJ554Im+++SbQVtGqEFVERERERAaqcCxBWWOQsqYghgH5aS7stoHVbffJ1gYeWLKZpmAMC/D16UO5+PAR3aqitSQi2P3VOFtLsMaDxN1ZmPbOHWS95zmjZK9/kqzt1afubEomX0Nt1kzy0twMzfLg6U7Fb7ABEjHInQDZY8Du7NLlA+u7LCIsW7aME088kdmzZ/PAAw9QU1Ozx7FLly5l7ty5fPHFF8nP3Xrrrd2qILXZbMyaNSv50d3KSei719CfzJgxI/le5ufn79NcVquVJ598kmHDhgGQSCS48MILufrqq6moqNhlfCKR4NVXX2XatGl89NFHyc//8pe/5Nhjj91l/I6t/McddxyFhYVdWt/FF1+cfPzCCy/Q2trapetFRERERET6WsIwqWoOsbK0iS11flKcdvLT3QMqQG0OxfjtWxv4v9fX0xSMMSzLw13nTuXbc0Z3PUA1EtgDVXhqVuBuWodptRFLLdrnANXVuJER79xE9uYXsGDQPGw+Kw//Ay1DDmPskDTG5KZ2PUA14tBSARY7FE6DvIldDlBBlagiA9by5ctZvnw5119/PWPHjmXKlCnk5uZit9upq6tj1apVbNu2rd01Z599NjfeeGMfrXhX/ek1bNq0iRtuuKFL19x2223JQ6L6WmFhIR9//DEnn3wya9euxTRN/vrXv/LQQw8xe/Zsxo4dS0pKCjU1NSxdupTa2trktRaLhbvvvpubb755l3nr6+t57bXXks93DEQ766yzzsLr9RIMBgkGgzz33HN861vf6t4LFRERERER2c+ag7GvWvfDuO02ijI8A6p1H+DDzfU8+O4WmkMxrBb4xoxhXHjYCJxd3U/UNLGFG3G2lmIP1mLYXcRSCsGyb2GyJREle8M/yNr04ld7n2ZRNuVaqrJmkpvqZmiWm5TuHHK1vX0/vaitAtWd3u01KkQVGWCOP/54li1b1i5c3LJlC1u2bNnjNR6Ph9tuu43bbrsNu73vf+3742uorKzk/vvv79I1V155Zb8JUQGGDRvGxx9/zK9//WvuvvtuQqEQpmmybNkyli1btttrZs+eze9//3uOOeaY3X594cKFxGIxoO17sPN+qZ2RmprKWWedxVNPPQW0VbYqRBURERERkf4uEk9Q3hiirClILGGQm+rCMYAqTwF8wSh/fncLH25pAGBktpebjx/P+Py0Ls9ljbbiaC3H4a8AzB7Z9xTA1bSR/BX34GotA6Bl6Dy+HPctcKczOtNDXpoLu7UboXWwAeJRyJsE2aPBtm9r7fs0RUS65KqrruKqq65izZo1vPvuu3zyySds2LCBkpISmpubMU2TtLQ0CgoKmDp1KvPnz+e8884jKyurr5eeNBheQ3+VlpbG//3f/3HTTTfx0ksv8cYbb7B+/Xpqa2sJBoPk5uZSVFTEsccey+mnn868efP2+i+oO7byn3HGGaSldf0/tNBWwbo9RH3vvffYtm0bo0eP7tZcIiIiIiIivckwTOr9EbbWB/AFY2R4HOSkuPp6WV1imibvbarnL+9toTUcx2a1cO6hw7hg1vAuB8GWeBhHoApnaymWePirfU/d+7xGSyL2VfXpC19Vn2ZSfvB1VGbOJMvrZFiWlzR3N6JLIw7+GnCkQtEUSCug6ydQ7Wa9pmma+zyL9ImWlhYyMjJobm4mPb3r5cjhcDgZZLjd+/7DLyLS2/TnloiIiIiI9KbWcIyShiBVzSEcVitZKU6sA6x1vzEQ5YElm1m6rRGAMbkp3Hz8eMbkpXZtIiOOI1iLo6UYW6SFhCsdw9nFOfbA1fTlV9WnpQC0DJvL5rFXkHClUZDuoSDTjaM71afRYFsFahfa9zubr6kSVUREREREREREDmixhEGlL0RxQ4BwtK11v8v7hfYx0zRZvKGWhz7YSiCSwG61cMHs4Zw7c1jXDsAyTWzhBpwtpdhDdRh2N7HUgn3e9xS+qj7d+BRZm57HYrZVn1Yech3lGTNJ9zgYlukl09uNtnvThFAjxGM91r6/M4WoIiIiIiIiIiJyQDJNk3p/lJKGAA3+CGluB9mZA6t1H6DeH+H+dzazvKQJgHFDUrn5uPGMyk3p0jzWaAuO1jIc/kqwWIh588DaM/Ghq2kT+SvuTlaftg6dy+bxVxC1pzE0w01BhhtXd4JrIw6tNeBK69H2/Z0pRBURERERERERkQNOIBKntDFARVMYq8VCfroHW3dayPuQaZr8e10Nf/9wG8FoAofNwkWHjeTsGUO79Fos8TAOfwVOf1nbvqeeHExbz4TJbdWnC8na9Fyy+rT64OsozTyUNJedkVkesrzO7uWe0SAEG9va9/MmtAWpvUQhqoiIiIiIiIiIHDDiCYPqljDF9QH8kTg5KS7cDltfL6vLalvC/PGdzawq8wEwMT+Nm48fz/Bsb+cnMeI4gjU4m0uwRptJuDIwUrN7bI0u3+a26tOWEgBahx7LtolXErCmUJDmoijTi9vRjepT02zb+zQR/6p9f1SPt+/vTCGqiIiIiIiIiIgcEBoDba37NS0RUl12ijI8WAbYwVGGafLmmmoe/aiYUCyB02ZlwREjOHNaF6pPTRN7qA5nayn2UD0Jh5dYalGPtcG3VZ8+Tdamf7ZVnzozqJ56HWUZs3A7bIzL8pCT4sLanW1Wd2zfLzgEUvN7pX1/ZwpRRURERERERERkUAtFE5Q1BinzBTENKEh3D7jWfYDq5jD3Ld7EFxXNAEwuTOem48YzNMvT6TmsER/O1nLsgUqw2Ih688Hac5W4u1afHkPxxKtotaSQl+ZiaKYHr7Ob94sGvmrfH9rr7fs7U4gqIiIiIiIiIiKDUsIwqfmqdb8lHCPb68LT3QCvDxmmyb8+r+Lxj4uJxA1cdiuXHTmK06YWYu1kFaYlHsLRWobTX4ElESPuyca0OXtwkTGyNzxN9g7VpzVTr6UsczYOu5UxmR7yUt3YulN9ur1934hD3kGQPRps+zfWVIgqIiIiIiIiIiKDji8YpaQhSHVzCI9zYLbuA1Q0hbh38SbWV7UAMHVoBjceN56CDHfnJjBiOALVOFtKsEVbibuzMDw5PbrGturTe3C1FANt1adlk66iGS9ZXidDMz2kubsZQxpxaK0GVzoUTIW0/J5beBcoRBURERERERERkUEjFE1Q3hSkvClI3DDJS3Pj6Fb5Y99KGCYvr6rgH0tLiSYMPA4b3zp6FCdNKehc9alptO172lyCLdyA4Uwl2oP7ngJt1acbnyX7y2exmAniznRqpl5HReZhWKwwIsPDkAw3ju5undCufX8iuFJ7bu1dpBBVREREREREREQGvHjCoLolTHFDEH84RpbXidc5MKOv0sYg9y3axMaaVgCmD8/kxvnjGJLeuepTW9iHo7UUR7AK0+oglloAlp7dxsDl2/LV3qfFALQWzaF88tU0mR4y3HaGZXnJ8HTz/TdNCNaDYcCQyZA1ar+37+9sYP4kiYiIiIiIiIiIAKZpUu+PUtIQoN4fIWUAt+4nDJMXVpTz1LJS4oaJ12nj23NGc+JB+Z16PZZYEGdrOY5AORYjTtydi2lz9Owid1N9Wjf1WiqyjyBhmAzLclOQ4cbZ3erfRAz8teDOgNwJfda+vzOFqCIiIiIiIiIiMiC1hGOUNwap9IWxWKAg3YOtu63jfay4PsC9izaxuc4PwKyRWVw/fxy5qa4Or7UkotgDVThbSrHGAsTdmZgOb4+v0enbSsGKu3G1bAOgtegoKqdcQ0PCS5rDytAsD1keZ/d3DIj6IeSDjGGQM75P2/d3phBVREREREREREQGlHAsQZUvRGljkHDMICfVicves+3q+0s8YfDPz8p5dnkZccMkxWXjO8eMYf7EIR1XnxqJtn1PW0qwRRpJONOIpRb27L6nAEac7C+fJXvjM1jMBAlnOrVTr6Eq50iiCYPCTBeFGV7cjm5Wn5omBOra/nfIZMgc2eft+zvrX6sRERERERERERHZg4RhUtsapqQhiC8YI8PtIDul40rN/mpLnZ97F21iW30AgMNHZ3PdvHFkpzj3fqFpYos04WgpxRGswbA5iaUUgqXnD9ByNm8lf8U9uJu3AuAvPIrKQ66hwfDitloYm5NKboqr+7ltIgatNeDJbDs8KnVIj629JylEFRERERERERGRfq8xEKW0IUBNSxi3w05hhrtzp9T3Q7GEwdOflvHcZ2UYJqS57Vxz7FiOGZ/bYfWpNerH4S/H4a8A0yDmzQVrD+97Cl9Vn/6T7I1P71B9ejXVOUcRiifIS3MzLNODx7kPFcBRPwR9kDmsbf9TZ0qPLb+nKUQVEREREREREZF+KxiNU9YYosIXxDAgL82No7uHFvUDX9a0cu+iTZQ2BgE4elwu1xw7hkzv3qtPLYkIDn8VztZSLPEgcXc2pt3dK2t0Nm/7qvp0CwD+wiOpOuRa6o0UXBYLY/NSyU110+1vw/b2fYD8KZA5ot+17++sf69OREREREREREQOSLGEkdz31B9JkO117lvVYx+Lxg2eWlbKiyvLMUzI9Di4Zu5Yjh6Xu/cLjQT2UC3O5mJskWYSrjSM1KLeWWSy+vQZLGachCON2mnXUJd3NP5onJwUJ0VZHtJc+xAptmvfnwSpeT22/N6kEFVERERERERERPoNwzCpD0QoaQjS4I+Q6nJQlOHu+JClfmxDVQv3Lt5EeVMIgLkT8rjqmDFkePbShm+a2MKNOFtLsQdrMewuYqkFvbLvKYCzuZj8FXfvUH16BNWHXE+DkYItYTIqJ4Uh6W7s1n34PkRaIdQMmcMhd3y/bt/fmUJUERERERERERHpF5pDMcoag1Q1h7FbLRSke7DtS2jXx8KxBP9YWsLLqyoxgWyvk+vmj+Xw0Tl7vc4abcXRWorDXwWYxLx5YO2lGM+Ik7XpOXI2PP1V9WkqdVOvoS5/Dq2RBJkeO8OyvKR79uH+yfZ9S1v7ftZIsA6sqmKFqCIiIiIiIiIi0qfCsQTlTUHKm0JE4ga5KS6c9oG77ynAmopm7lu8iarmMADHTRrCVXPGkOrecxxniYdxBCpxtpZhiYWIe3pv31MAZ0sx+Z/tUH1acAQ1066n0UzFiBkMz/JQkOHBYduHIDsR/ap9P2tAte/vTCGqiIiIiIiIiIj0iYRhUtMSpqQhQHMoRqbHSU6Kq6+XtU9C0QSPf1zMv76oAiA31cn188cxa2T2ni8y4jiCNTibS7BGm0m4MjDSsnpvkUbiq+rThTtUn15NQ8GxNIdjpLmtDMvykuXdy3YDnZFs3x/5Vfu+t2fW3wcUooqIiIiIiIiIyH5lmiaNgSiljUFqWsJ4HXaKMjwDet9TgNXlPv64eBM1LREATpqcz7eOHk3Kng5iMk3soXocraXYQ/UYdjex1CLoxffB2VJC/op7cPs2AeAvOJzaadfTRDqxSILCDA9FmR5c+1IJvGP7fsHBkDliwLXv70whqoiIiIiIiIiI7Df+SJyyxgAVvjCYkJ/mxm4b2K37wWicRz4s5s211QAMSXNx43HjmT48c4/XWCPNOFvLsAcqwWIl5h3Su0GjkSBr8/Nkb3gKq/Hf6tOmwrk0haJ4nTAyJ5WcFOe+ZbiJKPhr/9u+n5LbYy+hLw3sn1CRA9S8efOwWCzJjxEjRhCJRDp17e2335687pvf/GaH45csWcJ1113HrFmzyMvLw+l04vF4GDJkCLNmzeKiiy7i7rvvZvny5Zim2aXXYZomS5Ys4Sc/+Qlz585l7NixZGZm4nQ6yc3NZcKECXzjG9/gjjvuYMWKFV2ae2c/+clP2r1n1157bbfmKS4u5qGHHmLBggVMmzaNrKwsHA4H2dnZTJ06lauvvpp33313n9YqIiIiIiIyGEXjBiUNAVaWNlHSECTD7SA/feAHqCtKmrj+qZXJAPXUQwr544Uz9higWuJhnL7NeGtX4PBXkHBnEe/lANXZUsrw9/6X3HWPYzXi+AsOo+T4B6jKOwZfKMqQNDcT89PITd3HADXSCv46yBgBRTMHTYAKYDG7mnpIv9HS0kJGRgbNzc2kp6d3+fpwOMy2bdsYPXo0bnfvbVIsPW/evHm7BHX33nsvN910U4fX3n777fz85z8H4IILLuDpp5/e7bj169dzxRVX8Mknn3R6XVOmTGHNmjWdGvvss8/yi1/8grVr13Z6/jFjxvDd736Xq666Cper83vkmKbJqFGjKC0tTX4uKyuLqqqqTs+zcuVKrrnmGpYtW9ap8fPmzeOxxx5jxIgRnV6ndEx/bomIiIiIDDyGYVLnj1DSEKAxECXN5SDds497bfYD/kicv3+wjf+srwGgIN3NjceNY+qwzN1fYMRwBGpwtpRgi7YQd2diOFJ6d5FGgqzNL5C94R9fVZ+mUHfId/AVzacpHMNttzE0y0NuigvrvmTZptHWvm+xQc64AdW+39l8Te38IoPEnXfeyZVXXonXu++bNK9cuZLjjjsOn8+X/Fx+fj6zZs2ioKAAi8VCQ0MDa9asYfPmzckK1B3H70koFOLb3/42CxcubPd5r9fL7NmzKSgoICMjA5/PR21tLZ999hmtra0AbN26lRtvvJH//Oc/vPzyy51+Pe+88067ABWgqamJV155hfPOO69Tc2zcuHGXAHXChAkcfPDB5Obm4vP5+OijjygvLwfaKniPPPJI3n//fcaMGdPptYqIiIiIiAwmzcEYJY0BqpvDOG1WCtI92KwDe99TgGXbGrl/yWYaA1EswBnTirjkiJG4HbsJDk0De6geZ0sJ9lA9CWcK0V7e9xTaqk/zV9yd3Ps0kD+bmuk34LdmEghHyUlxU5TlJtW5j/FgPNLWvu/NHlTt+ztTiCoySNTU1HDffffxwx/+cJ/micViXHTRRclAtKioiPvvv58zzzwT627+Waquro6XX36ZJ554gq1bt+517mg0yoknnsiHH36Y/Nxhhx3GT3/6U0488UScTucu18TjcT755BP+9re/8dRTTxGNRgkEAl16TY899ljyscfjIRQKJT/f2RB1u3HjxnHllVeyYMEChg4d2u5rhmHw6KOPcuONNxIMBqmsrOTiiy/mo48+GvCbo4uIiIiIiHRFKJqgvClIRVOImGGQm+rCMcDb9gFawzH++v5WlmysA6Aow81Nx49nSlHGbsdbIz6cLaXYg9VgsRFNKej9Ck0jQdbmF8ne8GRb9ak9hbqp36F56HH4QjFsGIzKSSUvzYV9XwPtcAtEWiBrNOSOA4enZ15DPzTwf3pFDnBHHHFE8vFvf/tbWlpa9mm+l156iQ0bNgBtgeM777zDWWedtdsAFSAvL48rr7ySd999lyVLlux17ptuuqldgPrjH/+YpUuXctppp+02QAWw2+3MmTOHRx55hG3btvGNb3yjS6/H7/fz/PPPJ5//4Q9/SD5+6623qKmp6dQ8hYWFPPLII2zYsIFbb711lwAVwGq1csUVV/Dkk08mP/fJJ5/w73//u0trFhERERERGajiCYPypiArSpvYUufH47RRkO4ZFAHqx1vque6pFSzZWIfVAmfPGMp9F87YbYBqiQVxNn2Jt3YljkAVCXc2cW9erweojtYyhr//fXLXPYrViBPIn0XJ8fdTVziPhmCEdI+diflpFGa49y1ANQ1orW47RCr/YMifPKgDVFCIKjLgLViwgIkTJwLQ2NjI73//+32ab8fA7+tf/zoTJkzo9LVjx47d49feffdd/vKXvySf33zzzdxxxx1dWltRURHPP/88d911V6evef7555OVq6NHj+bqq69m+vTpQFuV6z/+8Y9OzTN37lwuv/xybLaO/4N39tlnc9hhhyWfv/baa51er4iIiIiIyEBkmib1/giry32sqWjBMEyKMjx497VVvB9oDsW4660N3PnGBnzBGMOzPNx1zjSuOHo0Lnv7vyNaElEcLSV4a1fg9m3BsHuIpRZi2nZfONRjzARZm55jxDs34W76koQ9heoZt1Bx+M9oMDIIxRIMz0ph3JA00tw90L7fXAGujLbDo7JHD5j9T/eFQlSRAc5msyUPigK4++67aWho6PZ8FRUVyccjR47cp7Xt6M4770w+Hj16NL/+9a+7PdfMmTM7PXbHVv4FCxZgsVi45JJLdvv1nnT00UcnHxcXF/fKPURERERERPqD1nCM9VUtrCr14QvGKEh3k+l1DvhtzUzT5P1NdVz/1Are31SP1QLnHTqMey6YwcSCtJ0GG9gD1XhqV+FuWIeJSTS1CMOx7+eWdMTRWsaw935A7tpHsRoxAvmHUnL8/TQMPY76QASPy8r4IWkMz/bgsPVA+36gvq19f+gMSMnpmRcxAChEFRkEzj//fKZNmwZAa2srv/nNb7o9145t+9u2bdvntW2fZ8cK12uvvXa/nKxeUlLSbouBBQsWAHDRRRclK0o///xzVq1a1eP33vH/LCQSiR6fX0REREREpK9F4gmK6/2sKG2itDFIhsfBkDT3oDg4qikY5VdvbOCutzbSHIoxKsfL78+bzqVHjsJpbx+n2cJNuOs+x1O3GkvcTyy1AMOV0esHR2EmyNz0PCPeuQlP00YSdi81M26m8vDbaTQz8IfjDM30Mn5IGllexz7ea4f2/YKDIX/KoG/f35lCVJFBwGKx8Mtf/jL5/E9/+hNVVVXdmmvHlvxXX32VdevW7fP6dt4r9YILLtjnOTvjiSeewDRNAA4//PDk1gQFBQWceOKJyXG9UY36xRdfJB8PHz68x+cXERERERHpKwnDpLo5zMpSHxuq/TitNoZmend/Mv0AY5omSzbWcv0/VvDx1gZsVgvfnD2cP5w/nXFDUtuNtcYCuBo34qldiT1US9yTS8KTC5befx+2V5/mrX2krfp0yKGUHv8AjUNPoDYQwWm3MD4/lRHZXlz2fYz/4hFormxr3x96KGSNgj2cmzKYDcpXnEgk+Pzzz/nb3/7Gtddey6xZs3A628rILRYL8+bN6/U1RKNRnnjiCU499VRGjhyJ2+2msLCQo446it/97nfU19f3+hrkwHLGGWdw+OGHAxAKhfi///u/bs1z1llnJR+HQiGOPfZYfvvb37Zr8++q999/P/m4oKCAESNGdHuurnj88ceTj3ds4d/5+VNPPUU8Hu+x+5aWlrJ48eLk8xNOOKHH5hYREREREelLTYEoayqa+bzcRziaoDDDTeq+7rHZTzT4I9zx2np+/58vaY3EGZOXwh/Om8bFh49sdzCWJRHB0VyCp+YznM3bSDhTiKcUYNr2sdqzM8wEmZte2Kn69CYqj7wdnyUTXzhKYbqb8flpZKc4970YNtz8Vfv+qLb2fW92T7yKAWlw/JTv4KWXXuLiiy8mGAz22Ro2bNjAhRdeuEuLcHV1NdXV1Xz88cf89re/5ZFHHuHUU0/tm0XKoHTHHXckKywfeughvv/973d5X9P58+dzxhln8OqrrwLQ0NDAD37wA2699VYmTJjAYYcdxqxZszjiiCOYOXMmdnvHf4yUlpYmHx900EFdWk93ffTRR2zatAkAh8OxS/XrWWedRWpqKn6/n9raWt544w3OOOOMHrn39773vWQL/4gRI3psXhERERERkb4SjMYpbwxR7gtiGJCb6moXLA5kpmmyaEMtD3+wlUAkgd1q4ZuHjeCcGUOx7/gajQT2UB3OlmJskSYSzjRiaUX7bZ2O1nLyV96Dp3EDAIEhM6mdfiNhVy4+fxS3w8a4vFRyUlz7XihqGuCvAZsTCg6BjOEHZPXpjgZdiOrz+fo0QC0vL+f444+nsrISaGuzPvbYYxk7dix1dXW8/fbbhEIhamtrOeuss3jzzTc57rjj+my9MriccMIJzJs3jyVLlhCNRvnFL37B3/72ty7P89RTT3HppZfy4osvJj9nmiYbN25k48aNPPHEEwCkpKRw+umnc/XVVzN//vw9ztfY2Jh8nJmZ2eH9N23axL333rvXMZdcckmy8nZ3dmzRP+WUU8jNzW33da/XyznnnJMc99hjj/VI2PnYY4/x/PPPJ5//6le/wuVy7fO8IiIiIiIifSGWMKhuDlPSGMQfipGV4sTrHDxxUl1rhPuXbOazkiYAxg9J5ebjxzMyJ+W/g0wTW6QJZ0sJ9mAths1JLKUQLPspVDQTZG5+mZz1T2I1oiTsXuoPvpKWkScSjCYIBKPkpbkoynST0hPfm3gE/LWQkgd5Ew/o6tMdDZ6f+p3k5+cze/bs5Mdbb73VYSjTEy666KJkgDpy5Ehefvnl5IE/APX19Xzzm99k0aJFxGIxzjvvPLZs2dKpYKlfME2I9V1I3S85vL2/WXQX3HHHHcyZMwdoC/R++MMfMn78+C7NkZqaygsvvMDrr7/OPffcw6JFizAMY5dxgUCAZ555hmeeeYYzzzyTRx99lKysrF3Gtba2Jh+npKTs8vWdVVRUcP/99+91zKxZs/YYoobDYZ599tnk851b+be79NJLkyHqq6++SmNjI9nZ3f+Pw/Lly7nmmmuSzy+88EIuuuiibs8nIiIiIiLSV0zTpM4fobQhSEMgQorTQVGmp90hugOZaZr8e10Nf/tgG6FYAofNwsWHj+Ss6UPbHYxljfpxtJbhCFSCaRDz5oJ1P7Ttf8XhryB/xT14GtcDEBgyg9rpNxF15+ELRLHbLIzOTfnqQK8euGHYB9EgZI+BnHHg6P1DoQeKQReinnzyyZSUlOyy5+LSpUt7/d6vv/56cu9Hp9PJq6++yiGHHNJuTG5uLi+//DJTp05l69atNDY2ctddd3HnnXf2+vp6RCwId+6/UvUB4UeV4Ow4GNxfjj76aE455RTeeOMNEokEP/vZz3jqqae6Ndepp57KqaeeSl1dHUuWLOGjjz7is88+Y+XKlfj9/nZjX3nlFY455hg+/vhj0tLS2n1tx+eBQKBba+mKl19+GZ/PB7RVvu6pwnTevHkMGzaM8vJyotEoTz/9NNddd1237rlt2zbOOOMMwuEwAFOnTuXPf/5zt+YSERERERHpSy3hGKUNQaqaw9gsFvLTPO2CxYGupiXMn97ZzKoyHwCTCtK46fjxDM/yJsdY4mEcgSqcrWVY4kHi7mxM+34MFM0EmVteJWfd419Vn3q+qj79GuGYQWsgTHaKi6GZHtJ6Yk9a04DWWrA72tr304cd8O37Oxt078b+PLRmZztWzl122WW7BKjbpaSk8Itf/CL5/C9/+UuPHmojcscddyT/dfCZZ55pd1J8d+Tl5XHeeedx9913895779HU1MT777/PFVdc0W5P1LVr1/LjH/94l+t3rO7cHm7uzbx58zBNc5ePzu7vumMr/3nnnbfHdnqr1crFF1+82+u6oqqqihNPPJHq6moAxowZw5tvvkl6enq35hMREREREekL4ViCLbV+VpY0UeELkeV1kJfmGjQBqmGavPZ5JTcsXMGqMh9Ou5VvzxnNr78x9b8BqpHA4a/EU7sCV+NGDKudWGrRfg1QHf4Khr1/G3lrHsZqRAnkzaD0uPtpHnkSTYEY4XiCEdkpjB2S2jMBajwCzRXgyYSimZA5QgHqbgy6StS+4vf7WbRoUfL5t771rb2OP+ecc7jmmmvw+/00Njby3nvvDYy9UR3etspL+S+Ht+Mx+9nMmTM5++yzeeGFFzAMg//3//4fL730Uo/Nb7fbmTNnDnPmzOHb3/42J510UrIy9aGHHuI3v/kNHo8nOX7H8HP9+vU9to7dqa6u5t///nfy+YIFC/Y6/pJLLuE3v/kNAMuWLWPDhg1MmjSp0/draGjgxBNPZMuWLQAUFhby9ttvU1hY2I3Vi4iIiIiI7H8Jw6SmJUxpQxBfKEqGx0l2yuA626GqOcR9izaxprIFgClF6dx03HiKMr/6u6tpYgs34Gwtwx6owXB4iKUW7L99TwFMo636dP3jWBMRDLuHuoO/TcvIk4jETVr8YTI8ToZmesj09tCWAmrf7zSFqD3ko48+IhKJAG2VprNnz97reLfbzZFHHsl//vMfABYvXjwwQlSLpV+1rsue/eIXv+Cll17CMAxefvllPv300w5/LrvjqKOO4kc/+hE/+tGPgLb9SD/99FOOPfbY5JhjjjmGv//970BbyFlaWtprFeNPPvkkiUQi+Xzu3Llduv6xxx7jV7/6VafGtrS0cNJJJ7F27VqgbbuOt99+m9GjR3fpniIiIiIiIn3BNE2agjFKGwLUtITxOOwUZQyefU+hLSD+1+eVPP5JCdG4gdth5bIjR3HqIYVYv3qd1mhL276n/kqwWIilDAHr/o3MHP5K8lfeg6dhHQDBvOnUzLiJuGcIzaEYCcNkaKaXwkw3zp7Y/NRIgL8O7E4omArpQ1V92gG9Oz1kx+q6Qw45pF2L857MnDlzt9eL9IQpU6a0O9ToJz/5Sa/d6+STT273vKqqqt3zefPmtXv+9NNP99pautuSv92TTz6520O0dhYIBDj11FP57LPPAMjIyODNN99k8uTJ+3R/ERERERGR/SEQibOxupWVZU00BKIMSXOTleIcVAFqeVOQ2174nIc/2EY0bjB1WAZ/vHAmp08twmqxYImHcfq24K1dgbO1jIQrg7h3PweopkHmlpcZ8c6NeBrWYdg91Ey7noqjfknImUtdaxiXw8r4glRGZHt7JkCNh6GlErxZUDQDMocrQO0EVaL2kI0bNyYfd3bfxh0r8TZs2NDjaxK5/fbbefrpp4nH4/z73//mvffe65X7uN3ty/133oN01KhRnHTSSbz11lsA/PnPf+amm27a5bp9tWLFCtasWZN8Pnv2bKyd/A/BZ599Rjwep7y8nEWLFnHiiSfucWw4HObMM8/kww8/BMDr9fLaa69x6KGH7tsLEBERERER6WXRuEF1c4iSxiCBSJycFBduh62vl9WjonGD51eU88/PyoglTDwOG1ccPZqTpuS3hcRGHEewBmdzCdZoMwlXBkZqdscT97C26tN78TS0dTcG86ZRM/0m4t58WiNxIvEEBZluijK8uB09FHKGfBANQPZYyB0H9sG1bUNvUojaQxoaGpKP8/PzO3VNQUFB8nFjY2OPr0lk7NixfOtb3+Khhx4C2qpRe2PbiNWrV7d7vrtW/dtuuy0Zom7bto0f/vCH3HPPPT26jh2rUA855BCWLVvW6WvPOOMM/vWvfyXn2VOIGovFOOecc1i8eDHQFhi//PLLHH300fuwchERERERkd5lGCb1/gjFDQGaAlFSXQ6GZva/Mz721fLiRv7y3laqW8IAzByRyfXzxzEkzQ2miT1Yh6O1FEeojoTdQyy1qG3rwv3JNMjY+i9y1z2W3Pu0fsq3aB51CnEDmvxhPE4744akkuN19UyRqJEAf21baFo4Te373aAQtYdsP1QHaHegzt7sOG7H6/ckEokk912Ftv0YRTry//7f/+Pxxx8nEonw/vvvE4vF9jr+D3/4A1OnTuWEE07o1PzBYJA777wz+Tw/P5/p06fvMm7u3Llcc801/PnPfwbg3nvvJS0tjV/+8pedfzF7EYvFeOqpp5LPOzpQamcLFixIhqgvvvgira2tpKWltRuTSCS46KKLeP3114G2A7aeffbZTr9XIiIiIiIifaE5GKOksW3fU4fVSn66B5t18LTtA9S0hHno/a0s3dZWpJad4uTKOaOZMy4Xi8WCNdL81aFRVWCxEPXmg3X/V+A6AlUMWXEv3oa2Lspg7lRqZtxMPCWfQDhOKJ4gL83N0EwPXmcPrS8ebtv/NHUI5E0ET1bPzHuAUeTcQ8LhcPKx0+ns1DU7tjyHQqEOx//qV78iIyMj+TF8+PCuL1QOOMOHD+fqq69OPv/kk0/2On7ZsmWceOKJzJ49mwceeICampo9jl26dClz587liy++SH7u1ltv3WML/b333tuuYvOOO+7giCOO4LXXXiMaje7xPuvXr+eaa66hvLx8j2Nef/116uvrAbBYLFx44YV7HLs7Z555ZjI0DQaD/POf/2z3ddM0+fa3v81zzz0HgNVq5YknnuDMM8/s0n1ERERERET2l3AswebaVlaWNlHdHCYnxUVOqmtQBaixhMEzy8u47qkVLN3WiM1q4RszhvLgxTM5Znwe1kQYp28z3toVOPwVJNxZX+17up8DVNMgY8urjFh8A96GNRg2N7XTrqPi6DuIevJp8EdIYDI6N4Uxuak9F6CGmiDQ0Na+XzRDAeo+UCVqD9lxb8e9hUE72rGqtDPVq7fddhvf+973ks9bWloUpEqn/OhHP+Lhhx8mGAx2+prly5ezfPlyrr/+esaOHcuUKVPIzc3FbrdTV1fHqlWr2LZtW7trzj77bG688cY9zul0OvnPf/7DFVdckTxcaunSpZx++ul4vV5mz55NYWEhmZmZhMNh6urqWLt2LcXFxe3mGTt2LDNmzGj3uR1b+Y899tgu/254PB7OPvtsHn/88eR8V1xxRfLrDz74YLt7jB07lg8++IAPPvigU/P/6U9/6tJ6REREREREuiueMKhpjVBSH6AlHCPL6yTHOfj2vlxR0sRf3ttCZXNbYdshQzO4Zu5YRmR7scTD2FsqcLaWY4u2EHdnYXhy+mSd9kA1+Svu2an69CbiKQWEogn8kbaAuyjLQ5qrh6K6ZPu+G4qmt7XvD6JDw/qCQtQekpqamnzcmarSncfteP2euFyuXQ7sEemM/Px8brrpJn796193OPb4449n2bJl7QLSLVu2sGXLlj1e4/F4uO2227jtttuw2/f+x4rH42HhwoWcddZZ/OIXv2DdunVAW/Xnu+++u9drJ0yYwDXXXMP111/fruK7oaGB1157Lfm8q638O163PUR9//332bZtG6NHjwagtra23dhNmzaxadOmTs+tEFVERERERHqbaZo0BKKUNgSpbY3gddooyvC0HaY0iNS2hvnbB9v4aEvb+TTZXidXzBnNseNzsSbCOJqLcfjLsUb9GM4Uon2x7ym0VZ9ue53ctY9iTYQxbO62vU9Hn4JhWvH5o9isFkblpDAk3Y29pyqEt7fvp+VD7kTwZPbMvAc4hag9JCfnv/+asbf25x1VV1cnH2dn7/9T4OTA8oMf/IAHH3yQ5ubmvY676qqruOqqq1izZg3vvvsun3zyCRs2bKCkpITm5mZM0yQtLY2CggKmTp3K/PnzOe+888jK6lpLwAUXXMB5553Hu+++y9tvv817771HRUUFDQ0NhEIh0tPTyc7O5qCDDmL27NmccMIJHHHEEbuda+HChckKcJfLxbnnntultWx33HHHUVhYSFVVFaZp8thjj3H77bd3ay4REREREZH9yR+JU9oYoLIpjAUoSHcPqrZ9aGvdf2lVBc98WkYkbmC1wBlTi7jo8BGkWKI4WopxtJZjjflJOFOJpRb2WfWlPVBN/sp78da3bX8XzD3kq71PCwjHErSGI2R6HAzN8pLh6cF4LtQEsRDkjofsMW0HSUmPUIjaQyZOnJh8XFJS0qlrSktLk48nTZrU42uSwWvJkiVdviYrKwufz9fp8QcffDAHH3ww119/fZfv1VlWq5X58+czf/78fZrnhhtu4IYbbtjn9dhsNiorK3f7tdtvv12BqoiIiIiI9DuReIIqX4jSxhChWJxsrwu3Y/8fmNTbVpf5ePDdLVT42rp6pxSlc82xYxmTbmIPluD0V2CNBYi70on1VeUp7Kb61PVV9empmFhpDsYwTJPhWR7yM9w4bT10XJGRAH8N2L1QOE3t+71AIWoPOeigg5KPv/jiC+LxeIdtzStWrNjt9SIiIiIiIiIie2MYJrWtEYobAviCUdLdDooyvH29rB7X4I/w8Afb+GBz20HCmV4HVxw9muNGuXEEK3DWVmGNBYm7MoinDe3TtbZVn96Ht/5zAII5B1Mz8xbiKQVE4wbNoTBpbgfDsrxkehw9l3HGQhCoV/t+L1OI2kOOOuooXC4XkUiEQCDA8uXL99h6DG2HSu14Svpxxx23P5YpIiIiIiIiIgOcLxilpCFITUsYp81KYYYH6yCrOownDF5ZXcnCT0sJx9pa9087pJAFM7LJitXhqKvEEguTcKX3eXiKaZBR/Ca5a/6+Q/Xp5TSPPg2w0hqKE00kKMxwU5TpxWXvoepTgGBj2x6oueMheyzYnR1fI92iELWHpKamcvzxx/P6668D8Oijj+41RH3hhRdobW0F2vZDPfbYY/fLOkVERERERERkYApFE5Q1BqnwBUkYkJvqwtFT7eD9yBflPh58bytljUEADipI49qjhjDJ3YzDtwpLIkrClYHh7vvzZeyBmq/2Pv1v9WntzJuJpRQST5j4QmE8DjvjctLISXH2XPWpEYfWGnCkQOF0SO/DLQwOEApRe9B1113XLkS98cYbmTJlyi7jgsEgP/3pT5PPv/Od73TY+i8iIiIiIiIiB6ZYwqCmJUxxQxB/KEZWihOvc/DlCI2BKH//cBvvflkHQIbHwRWzh3BSUQBXaD2WlihxVyamJ6eDmfYD0ySj+A1y1z6CNR5qqz6dfBnNY04HixV/OE44Ficvzc3QTA8eZw/uU5ts3y+EvAngzui5uWWPBt8/V/Sw4uJiLBZL8uPRRx/d49jTTjuNY445Bmhr1z/99NP5/PPP241paGjgrLPOYvPmzUBbFeqtt97aa+sXERERERERkYHJNE3qWiOsLvOxtrIZTCjK9Ay6ADVhmLy0qoJrnvyMd7+sw2qB0ydn88gpHs7M3IbbX0nCkUIstQjT0ff7vtqDtQz96CcMWf0A1niIUM4USuf/keaxZ5IwLNT7I5jAmLxUxuSm9myAGmyEkA9yJ7QdIKUAdb8ZXL91Xzn11FN3OWG7uro6+Xj58uVMnz59l+tef/11ioqK9uneTz31FIcddhhVVVUUFxczffp05s6dy9ixY6mrq+Ptt98mGGwrR7fb7Tz77LNkZmbu0z1FREREREREZHBpCccobwxS6QtjsUB+mgebdfC1a6+tbObP726huKEtK5mY5+bm6TYOcldiiRltlad2dx+v8iumSXrxm+St/Xuy+rRh8qX4xpwBFiuhSIJALEZOipuiLDepPRl2b2/fd6ZA0fS2KlS17+9XgzJEXbduHSUlJXv8eiAQYPXq1bt8PhqN7vO9hw0bxuLFi7nwwgtZtWoVpmmyZMkSlixZ0m5cXl4ejzzyCMcff/w+31NEREREREREBodwLEGlL0RZY5BwzCAn1YnL3oOVjP1EUzDKIx9u452Nba376S4b3z7EzukFTVgtJgl3FqbN1cer/C97sJb8lffhrVsFQChnMjUzbiaWOhTDAF8gis1mYVROKnlpLuw9GXjHghBoUPt+HxuUIWpfmzRpEkuXLuXpp59m4cKFrF27lpqaGjIzMxkzZgzf+MY3+Na3vkVubm5fL1VERERERERE+oGEYVLbGqakIYgvGCPD4yA7pf+EiD0lYZi8/kUVTy4tIRhNYAFOG2PnyvEtZDgtJNxZxG396IR50yS95C1y1/wN2/bq04MuxTe2rfo0HEvQGo6T5XUwLMtLmruHo7ZgAyRibe372WPA3o/emwPMoAxRi4uLe2yuUaNGYZpml69zOp1ceumlXHrppT22FhEREREREREZfBoDUUobAtS0hHE77BRmuLEOwlbt9VUtPPjuFrbVBwCYkGXlewcHmJhlIeHKIW5z9PEK27MHaxmy8o+k1K0EIJQ9mZqZbdWnpgnNgRimxWR4loeCDA8OWw9+z4w4+GvAkQKFk9W+3w8MyhBVRERERERERKS/C0TilDUGqWgOYRqQl+bGYRt8Z4D7glEe+7iYt9fXApDmgKsmRTh1FJiebOLW/hWe7lJ9anW27X069gyw2IjGDZpDUdI9DoZmesny9vD6t7fvpxe1VaC603t2fukWhagiIiIiIiIiIvtRLGFQ5QtR2hjEH0mQ7XX27Anu/UTCMHlzbTVPfFJMIJIA4NThMb4zxSQlPQvT2v9iKXuwjiGr/khK7QoAQtkHUTPzFmKpQ8GEllCcWMKgMMNDUaYHl72HQ+9gA8SjkDsRcsZAP6vOPZD1v59WEREREREREZFByDBM6v0RShqDNPgjpLocDM309PWyesXG6lYeXLKJLfVBAManJ7h5msHEwkyw9sPA2DRJL/kPuWsexhYPflV9egm+sWeCxUY8btIUipDqsjMqN5Vsr7Nnu+uT7fupUDQF0grUvt/PKEQVEREREREREellzaEYZY1BqprD2K0WCtI92HryBPd+ojkU4/GPtvDv9fUApNpNrphscOrENGy2/hlD2UP1bXuf1n4GQCh7EjUzbiGWNgwAfzhOOJ6gIN1NYaYHj6OHQ+BosK0CVe37/Vr//OmV/ao7B2eJiPQF/XklIiIiIgNNOJagvClIeVOIaNwgJ8WFs6dbwPuBhGHy9tpyHvukjNaIAcBJIwy+PSOVLE8/jZ9Mk/TS/5D7xQ7VpwctwDfu623VpwkTXyiK225jXF4qOSkurD35rTNNCDVCPAZ5kyB7tNr3+7F++lMs+4P1q998wzD6eCUiIp2z/c8ra4/+PxcRERERkZ4XTxjUtkYoaQjQHIqR6XGSk+Lq62X1is2VDTz47ha+bIgCMCbd5MZZXg4e0n8DwV2qT7MmUjPzu8nq02AkTiCaIDfVxdAsNynOHo7QjDi01oArTe37A4RC1AOY3W7HYrEQDodJSUnp6+WIiHQoHA5jsViw2/WfLxERERHpn0zTpDEQpbQxSG1rBI/DRlGGB8sgDMj8/lae/Ggzr38ZwARS7CaXHeLizPGu/rtVgWmSXvr2V9WnAQyrg4aDLklWnxoG+IJR7DYLo3NTGJLmxtbTNRzJ9v2hkDehLUiVfk9/Cz2AWa1WUlNTaWlpIScnp6+XIyLSoZaWFlJTU1WJKiIiIiL9kj8Sp6wxQIUvDCYMSXVh7/EEru+Z0QDvfL6Nv61ooiXaFpYeP9LOd6a7yfb039drC9WTv+pPpNQsB7ZXn95CLG04AOFogtZIjCyvi2FZHtLcPRybmWZbeJqIq31/AFKIeoBLT0+noqKCQCCgalQR6dcCgQDhcFj/6CMiIiIi/U40blDVHKKkIUgwGicnxYW7pw8f6gessQDFZWXc/3Ed65osgIVR6VZunOVm6pB+HDGZJmmli8j74qFk9WnjQRfTNO5ssNgwzbbqU4sFhmelUJDpxtHTlbQ7tu8XHAKp+WrfH2D68U+47A+pqamkpKRQVlbG8OHDFaSKSL8UCAQoKysjJSWF1NTUvl6OiIiIiAgAhmFS52/b97QxECXd7WBoprevl9XjrNFWwk0VPLG8lle2WTCw4LHDZYe4+Pp4J/b+2rrP9urT+0mp+RSAcNYEqmd+N1l9Go0bNIeiZHicDM30kOnthcrQaACCjWrfH+AUoh7grFYrw4YNo7y8nNLSUtxuN+np6bjdbqxW66Dcs0VE+j/TNDEMg3A4TEtLS3Lv5mHDhqmVX0RERET6BV+wbd/T6uYwTpuVwgwP1kH2d2hrtAVbaxXvbKzmL2ss+KJt/198/gg735nhJrcft+5jmqSVLSbvi79iiwUwrHYaJy1oqz612sCE5lCMhGEyNNNLYaYbZ09vvbC9fd+IQ95BX7XvK4obqPSdk2SQ6vf7aWlpoa6uDtM0+3pZIiJYLBZSU1PJycnRXqgiIiIi0i+EognKm4KUNwWJGya5qS4cg2zfU2vEhyNQTUllFfeutrKmqW1rghHpVm481M30/H4cJ5km3trPyFn3BO7mLQCEM8dTM/O7RNNHABCLG/hCMdJcdoZmecjyOnu+s96IQ2s1uNKhYCqk5ffwDWR/68c/9bI/Wa1W0tPTSU9PxzAM4vE4hmH09bJE5ABmtVqx2+0KTkVERESkX4gnDKpbwpQ0BGkNx8jyOvE6B1GsYprYIs3YAxVEmmv4y3p4cZsTA3Db4ZIpLs6e4MRh67/Vtp66z8lZ/ySexnUAGHYPjRMu+G/1KdAajhOJJyhId1GU6cXt6IW/b7Rr358ILm1JNhgMot926SlWqxWn09nXyxARERERERHpc6ZpUu+PUtoYoK41SorTRlGGZ/Bsf2ea2CI+HP4KbIFa3i4zeXC9i6ZI25fnDrdz9Qw3ed7+W9zgatxI7von8NatAsCwOmkeczqN48/BcGUAEE+Y+IJR3E4b44akkuN10eP1GqYJwXowDBgyGbJGqX1/ENF3UkRERERERERkN1rDMcoag1T6wlgsUJDuxtaPD1HqEtPEFm7E4a/AHqxlW4vJPWu9fF7ftr3fsDQrNxzq5tCC/hsdOZu3krP+SVKrlwFgWuw0jzqJxgnnk/DkJMcFwnFC8QS5aS6GZnrwOm09v5hEDPy1X7XvT1T7/iDUf38TRERERERERET6QCSeoLIpRGlTkHDUICfVicveC8FbXzCNtvC0tRx7qI5AzOQvW9N4YVMCwzRx2eDiKS7OmejE2U9b9x2t5eRs+AdpFe8DYGKlZcRxNE68kHjKf8NLw4CmYASH3cro3BTyUt30yva1UT+EfJAxDHLGq31/kFKIKiIiIiIiIiICJAyTutYIxQ0BfMEYGW4H2Zmuvl5WzzAN7KEGHP5ybKE6TNPC23XpPLg6TmM4AcCcYXauneFmSEr/bN23B2rI2biQtNLFWGg7x6V16LE0TLqIWNqwdmP94TihWIKcFCdFWR7SXL0QgZkmBOra/nfIZMgcqfb9QUzfWRERERERERE54DUFopQ2BqlpCeOy2yjMcGMdDPueGgns4Xoc/krsoVpMi42t0Sz+uDLOqtoYAEWpba37swv7Z0xkCzWQ/eWzZBS/hcWMA+AvOJyGgxYQzRjdbmwsbuALRfE47IzJSyE31YW9N7ZgSMSgtQY8mW2HR6UO6fl7SL/SP387RERERERERET2g2A0TnljiHJfEMOA3FQXjl7p+d7PjDj2UH3bnqehekyrjRZ7Dk+uN3h+Y4SECU4bXDTZxXmT+mfrvjXSTPam58jY+hpWIwpAIG8GDQctIJI9sd1Y04TmUIyEYVKQ7qYgo5f2PoW29v2gDzKHQe4EcKb0zn2kX1GIKiIiIiIiIiIHnFjCoLo5TElDAH8kQbbXiae3Qrf9yYhhD9XjbCnDFmnCtDmIenJ5rwL+vDJMfajt4Kgjh7a17hem9r/A2BoLkLn5RbK2vIw1HgIglD2ZhsmXEMo9ZJfx4WiC1kicdI+dogwPWV4nvVJEvL19HyB/CmSOUPv+AUTfaRERERERERE5YJimSZ0/QmlDkHp/hFSXg6IMN5aB3rpvxHAE63C0lmOLNGHYHMS8Qyjzw58+CbOipm3f04IUC9fPdHPEUEcfL3hXlniYzK2vkLXpBWwxPwDhjLE0TL6E4JBD2TkZjSdMmkNR7DYrw7O85Ge4cPZWFXG79v1JkJrXO/eRfkshqoiIiIiIiIgcEJpDMcoag1Q1h7FZLBSke7D1xn6Z+5ElEcUeqsPRUoo92kzC7ibmHULIsPLUFxGe2xglboDDChdOdnH+JCcue/96zZZElIziN8j68p/YIz4AImkjaDhoAYHCI3cJTzGhNRInHIuTm+qmMMNNmrsXI65IK4Sa1b5/gFOIKiIiIiIiIiKDWjiWoKIpRFlTkEjcIDfFhdPe/9rYu8KSiGAP1uJoLcMWacZweImm5GNi5cOKOA+uCFIbbGvdP6zQzvUz3RSl9bPXbMRJL32b7I1P4wjVAxD1FtB40MW0DjsWLLturxCNGzSHYnidNsYPSSM7xUWvbWG7c/t+1kiwDoItH6RbFKKKiIiIiIiIyKCUMExqWsKUNgTxhaJkeJzkpLj6eln7xBIPYw/W4GytwBprxrB7iaUWgsVKeWuCB1YE+bSqrXU/32vhuplujhxq71/bFZgJ0srfI3vDUzgDVQDEPLk0TvwmLSNOAOuucZVhQHMoimlCYYabggw3HkcvBpqJ6Fft+1lq3xdAIaqIiIiIiIiIDDKmadIYiFLaGKSmJYzX0XbgUL8KErvIEg/hCNTg8JdjjfoxnCnEUtrC03Dc5Ol1YZ7dECX2Vev++ZOcfHOyC3d/at03TVKqPiZn/ZO4WksBiLsyaZpwHs2jTsG0OXd7WTASJxCNk+lxUpjpIdPj6J2Do7ZLtu+PhNzx4PT24s1koFCIKiIiIiIiIiKDRiASp6wxSEVzCNOA/DQ39l7r9+59llgQR7AGR2s51pifhDP1q8rTthTxo4oYD64IUx1oa92fVWDj+kPdDEvrR23npom39jNy1j2Bu3kLAAlHKk3jz8E35gxMu3u3l8UTJr5QFKfdyqicFPLS3DhsvZieJtv3LVBwMGSOUPu+JClEFREREREREZEBLxo3qGoOUdoYJBCJk5Piwt2b7d69zBoLYA9U4/BXYIsFiLvSiKUWJcPTKr/BAyvCfFIZByDPa+HaGW7mDOtfrfueus/JWf8knsZ1ABh2D01jv45v7FkYztTdX2RCSzhONJEgN9VFYaabVGcvR1iJKPhr/9u+n5Lbu/eTAUchqoiIiIiIiIgMWIZhUu+PUNwQoDEQJc3lYGjmwG2/tkZbsQeqcQYqscaCxF0ZRHcIT6MJk2fWR1m4LkLMALsVzp3o5KIpLjz9qHXf1bSR3HVP4K1bBYBhddI85nSaxp9DwpWxx+vCsQSt4RhpLgcjc9LI9jqx9nYhcbJ9f4Ta92WPFKKKiIiIiIiIyIDUHIxR0higpiWMw2qlIN2Dzdp/gsSusEZbcPircQQrscTCJFzpxNOGthuztDLG/Z+FqfqqdX9mflvr/oj0/lNx62zeRs76J0mtXgqAabHTPOokGiecT8KTs8frDAN8wShWKwzL8pKf7sZl7+X01DTa2vctNrXvS4cUooqIiIiIiIjIgBKIxKlqDlHeGCJmGOSkuHAM0H1PrREfjkA1jkAVlkSUhCsDw53dbky13+DBlWE+qmhr3c/1WLhmhptjh/ef1n1Hazk5G/5BWsX7AJhYaRlxHI0TLySekr/Xa/3hOOF4nEyPi6JMDxme/RBXqX1fukghqoiIiIiIiIgMCP5InOrmEJW+MMFonCyvkxynq6+X1XWmiS3SjD1QiSNYjSURJe7KxNypUjOaMPnnhrbW/UgCbBY4Z6KTBVNceBz9Izy1B2rI3riQ9NLFWDAAaB16DA2TLiaWNmyv18biBs3hKG67ndG5qeSmurDvj0ricAtEWiBzZFv7vsPT+/eUAU8hqoiIiIiIiIj0ay3hGNW+MFXNIUIxgwzPAN331DSxRXw4/BXYg7VYjBhxdyamZ9cqyE+r4vzpszCV/rZgctoQGzce6mZkRv9oN7eFGsj+8lkyit/CYrZVyPoLDqPhoAVEM8bs9VrThJZQjLhhkp/mpiDDg9e5H16XabRVn1rtkK/2fekahagiIiIiIiIi0i81h2JU+UJUt4QJxxJkepxkpwzQytNw43/DU4y2ylO7e5ehtQGDP68M8355WzCZ7bZw9Qw380f0j9Z9a6SZ7E3Pk7H1X1iNKADBvOnUH3QJkeyJHV4fjiZojcRIczsYk+khy+tkv7yseKQtQPXmQt5ESNnz/qwiu6MQVURERERERET6DdM0aQ7FqGwOUdMcJho3yfQ6yBmQ4anRFp62lmMP1QEmCXcWpm3X1xJLmDy/Mco/1kYIJ8BqgbMnOLnkYBcp/aB13xoLkLn5RbK2vIw1HgIglH0QDQddQihvaofXJxJt31eb1cLwrBTyM1w499c+tuEWiLRC1mjIHaf2fekWhagiIiIiIiIi0udM08QXjFHhC1HTGiaRMMn0OMlNHYDt1qaBPdSA3V/xVXjKV+Gpc7fDV1S3te6Xtba17h+S19a6Pzqz71+7JR4mc+urZG16HlvMD0A4YywNky8hOORQOiwjNdv2sg3HE+SkuCjMcJPm3k9x1I7t+wUHQ8YIsA7MA8ik7ylEFREREREREZE+YxgmTcEoFb4Qta0RTLMtPHU7+j5A7DIjgT1cj8NfiT1Ui2mxkXBnY9ocux1eFzT4y8ow75a1te5nuS18Z7qL40c6+rx135KIklH8Bllf/hN7xAdAJG0EjZMuxl90VMfhKRCNGzSHYnicNsbmpZKT4mK/FJ+aJkSaIdwKKXlt7fve7P1wYxnMFKKKiIiIiIiIyH5nGCYNgSiVvhB1rREAMr0OXPaBGJ7GsYfq2/Y8DdVjWm3EPLlg3X14GjdMXvwyyuNrIoTjba37Z453ctnBLlKdfdy6b8RJL32b7I1P4wjVAxD1FtB40MW0DjsWLB1/fwyj7eAowzQpzHBRkOHBs79C8UgrhHzgSoeCQyC9COwDcCsI6XcUooqIiIiIiIjIfpMwTBoCESqbQtT5o1iALK8Tp30AtlkbMeyhepwtZdgiTZg2BzFvXlv7+B6sqmlr3S9paWvdn5xr46ZD3YzN6uPw2EyQVv4e2RuewhmoAiDmyaVx4jdpGXHCXl/TjkKRBP5ojAyPk6JMD5kex/45OCoWhGATONyQNwkyhoHTux9uLAcKhagiIiIiIiIi0uviCYOGQJTypiAN/ig2q4WcFCeO/XW4UE8yYjiCdfx/9v48Tq66zPv/X6fqnFP70nt3kk5ngSzEALKDAygYFVFUEhCQDDiMIzpfnVHncY/ec889v9l0dJwZvUcddEajwyYOoIggGhYRRPbVkIWsne5O77VXnTrr74+TNIlA6O5UdVcn1/Px4GH1SdX5fKoTk+53X9f10Qp9BI1xXFXHirZD4I2D0NGKy3eeM3io12/dT4cU/vikEGsWawRms3Xf84jt+y0tm28iVOgFwA6lySy7jNyii95wjuvvsx2PbMVEDwZY1BKjLRFGC87A+7KrUB7zQ96mxZDuhnCy/uuKY46EqEIIIYQQQgghhKgby3EZK5rszZTJlEy0YIC2eAh1DoanimOiVkbQCntRq1kcNYwV6zhseGq7Hne9YvLfL1Up72/df99xGteuDpOYzdZ9zyM6/AwtL99IOLcDAEeLkTl+Ldkl78dTJ3mCvQcFw6bqOLTGQ3SmwiRCMxA3uTaURv35p8l5kO6RuaeiriREFUIIIYQQQgghRM2ZtstosUpfpkymbBEKBmhPhAkGZnnm5zQoThW1PIxW2EuwmsfVIpixjjedD/rSsM2/P2OwK+e37q9o8Vv3j2+e3db9yOhLtGy+kcjYywC4aoTM0g+QXfpBXD0+6ftULZe8YRIPqXS3xGmJhgjUOxt3Hahk/ArUeAc09fiHR83yQVzi6CchqhBCCCGEEEIIIWqmajuMFk32jpfJli0iWpCOuRqe2gZqeQi90E/AyuGqUax4JyiHTwrHKy7/+UKV+3dbACR1v3X/3Utmt3U/lNlKy8s3ERt5DgA3oJNbcjGZ49fhhFKTvo/rQq5sQgDmp6N0psKE6j3T1vPAyIJZgkgLdKzyQ9TDVAELUUsSogohhBBCCCGEEOKIGZbDSKFKf6ZCtmIS1VQ6k3M1PK2globRi3sJmEVcPYYV63rT8NRxPe7ebrHhJYOyBQrw3qUaf3RiiGRo9sYX6LldtGy+ifjgEwB4ikpu0bsYX3Y5TqR1SvcqGTYV2yYd0elKRUhHtXps+VBGHowchFPQdRIkuiA4A+sKcRAJUYUQQgghhBBCCDFthuUwlDfoy1QoGBYxXaUrFZndw5KmSbHKaOUhtEIfAauIo8ex4l2TahXfNGrz/5422Jn1W/eXNQf49KkRlrfMXqWkVuijZcstxPsfQcHDI0Bh4QWMLb8CO9Y5pXvZtn9wVEgLsqglTmsihFbvgNws+a37WsyvPE3OA22Ss1qFqDEJUYUQQgghhBBCCDFlZdNmOG/QlzUoGjbxkMq8VARlDoanAauEWhpEK/YTtErYoQRWfN6kwtOM4fLdF6r8Ypffup/Q4Y9ODHPREm3WqnDV8jDNW24h2fsgCn6oW5h/LmMrrsJKdE/pXp4H+YqF7bq0JUJ0pcPE9DrHSbYB5TEIhqDlOEh1Q2jys1qFqAcJUYUQQgghhBBCCDFpparNYM5gIFehZNokdI15qfDcDE/NAmppEL00QMAqY4dSmJMMTx3X454dFhteNCj6+SnvWaLxxyeFSM1S637QGKd5622kdv8CxbMBKHaewdjKqzFTS6Z8P8NyKBgWibDG4nSMpohe34OjHAtKY/4chFQPpLshkq7jgkJMnoSoQgghhBBCCCGEeFPFqs1grkJ/tkLFdEiFdeYl52jlqZlHKw6ilQdQLAMnlMROzJ/06zeP2fz70wavZPwqz+OaAnzq1DAntM5OzBKo5mh+5Q5SO39GwDUBKLedzNjKqzGaV0z5fo7jkatYBALQ3RSlPVnng6NcG8rjfoia6IKmHoi2TCrMFmKmSIgqhBBCCCGEEEKIN5Q3LAazBvtyFSqWSyqi0ZwOzfa2piVQzaGV9qGV9qE4Jk4ohRtunvTrc1W/df/nO/3S07gGHz0xzMVLZ6d1P2CVSG//CekdPyFoVwCoNK9kbOV6Km0nTv2Gnh+WVyyHlph/cFQyUsfoyHP9madmBWJt0LwIYu3Ut9xViOmREFUIIYQQQgghhBCvkStb7MtVGMwZVB2HdESnOTYHw1PPI1jNoZYG0MqDKI6JHUrjRVomfQvH9bhvp8V3X6xSMD0A3rXYb91vCs984KfYBumdd9P0yh0ErSIARmopYyuvptxx2rQqOE3bJVcxiWgqS9titMRDqPUKhj0PqjkwChBpgvkrIN4JQYmpROOSP51CCCGEEEIIIYQAwPP8Nu6BbIWhvIFpe6SjGi36XA1Ps2jFftTyMIprYYfTeJHWKd1m65jDvz9TYeu437q/JO237r+lbeYjFcUxSe6+j+ZtP0KtZgGoJroZX/ERivPOAWXqga7r+gdHuZ5HVypMZzJCRA/WeOcHqRagkoVQAjpXQ3IeqHPwz5c45kiIKoQQQgghhBBCHOM8zyNT3h+eFgwcx6MpqhOO1zFMqxfPI2iMvxqe4vqVp2p4SrfJVz2+96LBvTssPCCqwbWrQ1xynD7zrfuuTbL3fpq33oZWGQHAjHYyvuIqCt3ngzK936eK6VAybZJhja50mKaIXr8xpFbFn3uqhaFtBaQWgB6t02JC1J6EqEIIIYQQQgghxDHKdT0yZZP+bIXhQhU8SEU0wtpcDE/dQ8JT8HDCTXjBqVU5up7HL3Za/NcLVfL7W/ffuUjjYyeFaI7McOu+55Do+zXNW25BL+0DwAq3ML7iSvIL3wmB6cU6tuORrZjowQAL9x8cpQXrlJ7aVSiP+XttWgTphRBO1mctIepIQlQhhBBCCCGEEOIY47oeYyWTgWyFkUIVgHRUI6TOzfBUrYyhFvtR91dp+uGpPuVbvTLu8O/PGGwecwBYlPJb909sn+H4xPOI7fstLZtvIlToBcDWU2SWXU5u8UXTem/+faFQtalaNi3xMF3pMIlQnd6ba/vhqev6LfvpHohO/hAvIRqNhKhCCCGEEEIIIcQxwnE9xkpV+jMVRotVAig0x3S04Bw8Dd11UI1RtOIAamUYTwnihJvxgtqUb1UwPb7/ksHPtlu4HkRUuGZ1iA8cr9fvcKXX43lEh5+lZfONhLPbAXC0GJnj1pJd+n48NTLtW1ctl3zFJBZSOa49QXMsRF1+210HKhm/AjXe7lefRlshMAf/jAlxEAlRhRBCCCGEEEKIo5ztuIyVTPoyZcaKJsGAQkssNCfD04BV8g+MKu0jWBnDCwSxIq0QmHp46noeG3f5rfvZqt+6/46FKn/y1jCtM9y6Hx79Ha2b/5vI2Mv+3tQImSWXkD3uQ7h6fNr3dV3IlU08BeY1RelMhglrdXhvngdGFqpFPzTtWAXxDgjMwepmIV6HhKhCCCGEEEIIIcRRynJcRotV+jIVxotVdDVIWzyEOsfCU8WpEjQyqJVRVGMUxTZwgzpWtG3ac0F3ZPzW/U2jfuv+wqTfun9yx8xGJaHMNlpevpHYyHMAuAGN3OKLySy7DCeUOqJ7lwybsmXTFNXpSkVIRbT6HBxl5MHIQTgFXSdBogvUaY4cEKJBSYgqhBBCCCGEEEIcZUz7QHhaJlO2CAUDdCQjM3+q/JFwbYLVnD/vtDJMwCrhBYI4WhwvPP3ZmiXT4/u/q/LTV0xcD8IqrF8V4kPL9PodrvQ69NxuWjbfRHzwcQA8JUhu0bsZX3Y5TqT1iO5t2/7BUSEtyOLWOK2JEFo9fu/NMlTGQYv5lafJeaBNf+SAEI1MQlQhhBBCCCGEEOIoUbUdRgp+5WmuYhJWVToS4bkTnnouATOPamRQS4MErTx44OgJrFgHKNOvoPU8jwf2WHzn+SoZw2/dP79b5eNvDdMWnbnKXK3YT8vmm4n3P4KCh0eAwsILGFt+BXas84ju7XmQr1hYrktbIkRXOkxMr0P0Y1ehPArBELQcB6kFEErUfh0hGoiEqEIIIYQQQgghxBxnWAfC0zK5ikVUV+lIzJ3K04BZ9OeclgcJVHMoro2rRbAi7TWZqbkr67fuvzTit+4vSAT4/04Nc2rnzMUianmY5i23ktz7AIrnAlCYfy5jK67CSnQf8f0Ny6FgWCTCGovTMZoieu3PcnIsPzz1FEh2Q9NCiDTVeBEhGpOEqEIIIYQQQgghxBxlWA5DeYO+TIWCYRHTVbpSEQJ1GXxZW4ptEKxmUcvDqMYYil3FVUM4oRResDbzNEuWx42/q/Ljbftb94PwkVUhLl2uo89Q637QGKd5649I7b4PxbMBKHacztjK9ZjpJUd8f8fxyFUsAgHoborSngwTUmucnro2lMf9EDXRBU09EG2hPgNWhWhMEqIKIYQQQgghhBBzTNm0GcoZ9GcrFKo2iZDGvFQEpdFDLddCNbIEjTHU8jBBu4wbUHH0BF6kpWbLeJ7HQ702337OYHx/6/4fLFD5xFvDtMdmpnU/YOZp2nY76V33EHCqAJTbTmJs5XqM5hU1WaNo2FQsh+aYzrxUhGSkxjGP50IlA2YFYm3QvAhi7dS+xFWIxichqhBCCCGEEEIIMUeUqjaDOYOBXIXS/vB0fqOHp55LsJrfH5wOETQLoCg4Whwz1lXzasY9OYdvPGPw/LDfuj8v7rfun941MxFIwCqR3v4T0jt+QtCuAFBpXsHYyj+k0nZiTdawbJdsxSSiqSxti9ESD6HWcnSD50E1B0bBb9eftxwSnRDUareGEHOMhKhCCCGEEEIIIUSDKxjWRHhaqTqkInpjV556HgFr/5zT4j4CZh7Fc3C1KFa0NnNOf1/F8rhpU5U7tpo4HuhBuOqEEJetmJnWfcU2SO/8GU2v3EHQKgBgpJYytvJqyh2n1SQs9jzIVSxc16MzGaYrFSGi1/hzaRahnIVQHDpXQ3IeqKHariHEHCQhqhBCCCGEEEII0aDyhsVg1mBfrkLZckhHdJqbGjfQ8uecZlBLQ6jVDIpTxVXDOOEmvDpVMXqex6/32tzwnMFoxW/dP3u+yiffGqYzXv+2c8WxSO7+Oc3bfoRazQJQTXQzvuIjFOedA0pt9lAxHYpVm2REZV46QlNEr20Rr1WB8hhoEWhbDqn5oMdquIAQc5uEqEIIIYQQQgghRIPJlS0GcmWGclWqzv7wNNaY4animASrWYKVUbTKKIpVxgtqNZ9z+nr25v3W/WeH/Nb9zpjCn54S5qz5M9B27tokex+geesP0SojAFjRDsZWXEWh++2g1KZC1HY8chUTNRhgYXOU9mQIPVjDcNiu+odGKQFoWgzpbginand/IY4SEqIKIYQQQgghhBANwPM8smWLfbkKg3kDy/FIRzRa9AYMT12HoOnPOdVKwwSsAp6i4OoJ3FDt55z+vortccumKrdvNbFd0AJw5QkhLl+hE1Lr3LrvOST6HqF5y83opX0AWOEWxpdfQb5nDQRqFLV4UKjaVC2blniYrlSYRLiGMY5r+5WnrgvJLkj3+PNPG3VEhBCzTEJUIYQQQgghhBBiFnmeR6ZsMZCtMFQwcByPpqhOWKv93NAj4nkErAJBI4NWGiJg5lA8B0ePY8Xaa1Z5eThF0+OeHSY/3mYytr91/4wulT89Jcy8RJ1b9z2P2L7f0rL5JkKFXgBsPUVm2WXkFr8XL6jXbCnTdsmVTaIhlePaEzTHQtSs+NR1oJLxK1DjbX71abQVAvUffSDEXCYhqhBCCCGEEEIIMQtc12O8bDKQrTCcrwKQimgNF54qdgXVyKCWhwhWMwRsE0eLYEeaITAzp7XvK7rcuc3kvp0mhu1f64gqfPLUMGfPU+t7wJbnER1+lpbNNxLObgfA0WJkjltLdun78dRIzZZyXchVTDygKx2hKxUhrNUo3PQ8MHJQLUC0GdpPgERnXQ75EuJoJCGqEEIIIYQQQggxg1zXY6zkh6cjBT88bYrq6GrjVAL6c04zr845tSt4QR1Hi2NHwjO2j5dHbW7favKbPhvXLzxlUSrAuuU67+jR0IP1bT0Pj/6O1s03EhnbBIAbDJNd+gEyx30IV4/XdK1y1aZs2qQiOl3pCOmIVrvO+moBKll/1mnXSZDoArV2lbNCHAuO6hDVNE1uu+02br31VjZt2sTQ0BBNTU0sXryYSy+9lGuvvZbW1ta6rP3www9z00038cgjj7Bv3z5M06Srq4sTTzyRD3/4w1x22WWo6lH96RdCCCGEEEIIcRDH9RgrVunPVhgtVgmg0BzT0Wp5SNCRcB2CZs4PTssjBKzi/jmnSdxQesZmZTqux2P9fnj68qgzcf3UziDrloc4tTNY38pTIJTZRsvmG4kNPweAG9DILb6YzLJ1OKF0TdeyHY9sxURXAyxqjdOaCKEFavT+zLJ/aJQe8ytPU/NBq13lrBDHEsXzPG+2N1EPW7Zs4corr+T5559/w+e0t7ezYcMG3vve99Zs3bGxMdavX8/Pf/7zwz7v1FNP5aabbmLFihXTXiufz5NKpcjlciSTyWnfRwghhBBCCCFE/diOy1jJpC9TZqxoogYCpKNaY4SnnkfAzBM0smjlfQSqeRQ8HD2Oq8X8E9tnSMXy+MUuizu3VtlX8qMKNQAX9GisW66zOF3/tnM9t5uWLTcR3/c4AJ4SJNfzLsaXfxgnUuMiLA/yho3pOLTGQ3Slw8T1GhVb2VX/0KiABuluSC2AUKI29xbiKDPZfO2oDFH7+vo488wzGRgYAEBRFM477zyWLl3KyMgI999/P5VKBQBN07jvvvu44IILjnjdTCbDWWedxbZt2yauLVmyhLPPPptwOMyOHTv4zW9+g2VZAHR0dPD444+zaNGiaa0nIaoQQgghhBBCNC7LcRktVunLVBgvVtHVIOmIhtoA4WnAKhGsZlFLQwSrWRTHxNUiOHqidqfLT9JoxeWubSb37DApmP61hK7w/uM0LjlepyVS/8+XVuynZcstxPt+jYKHR4BC9zsYW3Eldqyz5usZlkPBsEiENLrSEZqjem3OdXIsKI+Cp0ByHjQthEhTDW4sxNFrsvnaUdlPftVVV00EqD09Pdx1112cdNJJE78+OjrKFVdcwQMPPIBlWVx22WXs2LGDdDp9ROted911EwFqOBzmO9/5DuvXrz/kOTt27ODKK6/kqaeeYmhoiLVr1/L000/XvRVBCCGEEEIIIcTMMG0/PO0dL5OrWISCATqSEYK1atGeJsWpEjQyqJVRVGMUxTZwgzpOKIEXDM34fnZkHO7YavJQr4Xt+tfmxQOsXa6zZrFGRK3/50stD9O85VaSex9A8fxNFOb9AWMrP4KV6K75egcOjlIUWNAUpSMZJlSLWbiu7bftO5Z/WFTTIoi2zNgIBiGOBUddJeq9997LxRdfDICu6zz99NOsXr36Nc8rlUqceOKJ7Ny5E4AvfOELfPGLX5z2us888wynnXbaxMe33HILV1555es+N5vNctJJJ9Hb2wvATTfdxEc+8pEprymVqEIIIYQQQgjROKq2w0jBrzzNVUzCqkoqos1ueOraBKs51MoYamWYgFXCCwRxtDieFp3x7Xiex1P7bO7YavLs0KvzTle3BVm3XOfMeeqMfL6CxjjNW39Ecs99BFwbgGLH6YytXI+ZXlKXNYuGTcWyaY6F6EpFSEVqUNfmuVDJgFmBWKsfnsbbIVD/0QdCHC0aqp2/UCjQ19dHJpPBtm3OO++8uq118cUXc++99wLwsY99jO985ztv+Nybb76Zq6++GoDm5maGhoamfdjT5z//eb785S8DcOKJJ/LCCy8c9vnf/va3uf766wE4/fTTefLJJ6e8poSoQgghhBBCCDH7DMthOG/Ql6lQMCwiuh+eBmarCtBzCZh5VCODWhokaOXBA0dP4GrRGZ1zeoDpeDyw2+KOrSZ78n7FZ0CB87pV1i4PsaJlZkK/gJmnadvtpHfdQ8CpAlBuPZGxE9ZjNK+sy5qW7ZIz/FC9Kx2mNR5CPdKg2POgmgcj77frNy3yK1CDWk32LMSxZNbb+QuFAjfccAM333wzv/vd7ziQ1SqKgm3bhzx3eHiYr371qwCsXr36NS3wk1UsFnnggQcmPv7oRz962OevXbuW66+/nmKxyPj4OL/+9a+nPRv1iSeemHg8mYOqDlTLAjz11FP09vaycOHCaa0thBBCCCGEEGLmVUyH4cKB8NQmpgfpTEVmLTwNmEWC1SxaeZBANYfi2rhaBCsye5WJuarL3a9Y3PWKSbbq5wJRFS5aqvOhZTodsZkJdANWmfT2H5Pe8ROCtn9GSqVpOWMn/CGVtpPe5NXT43mQr1jYrkdHIkxnKkJUr8Hvg1mEcsY/KKpzNSS6QAsf+X2FEIdVlxD14Ycf5iMf+Qj79u0D4M2KXdvb23nggQd4/vnnSafTfPjDH0bX9Smv+9hjj1Gt+j9JisVinH766Yd9fjgc5uyzz2bjxo0APPjgg9MOUYeGhiYe9/T0vOnz58+fTzAYxHGcibWvvfbaaa0thBBCCCGEEGLmlE2boZxBf7ZCsWoTD2nMS4Vn5awLxTb8A6LKw6jGGIpdxVVDOKEUXnDq31fXyt68P+90424Lc3/XfltE4UPLdd67RCemz8znSrEN0rt+RtO2OwhaBQCM1BLGVq6n3HFa3WaGGqZDoWqTCKssSUdoiupHvpRV8eeeqiFoXQ7pBaDHarJfIcSbq3mI+uijj/Ke97wH0zTxPA9FUVi5ciXZbHYiVH09H//4x7n++uvJZrNs3LjxkErNydq8efPE49WrV0+qNf+UU06ZCFEPfv1UTXUqgqIoh/wDu2nTpmmvLYQQQgghhBCi/orVV8PTsmmTCGnMS0VmPjx1LVQjS9AYQy0PE7TLuAEVR0/gRVpmdi8H8TyPF0ccbt9i8vjAqx2oxzcFWLcixHnd6pG3sU+S4lgkd99H87bbUKtZAMz4AsZWXk1x3jl1G2lgOx65iokaCNDdFKUjFUIPHuFajgmlMX/PTYsg3Q3hVE32K4SYvJqGqIZhcMUVV0xUg15zzTV88YtfpKuri0996lN885vffMPXrl27lk9+8pN4nsf9998/rRB169atE48nUw0KHNJCv2XLlimveUBbW9vE6w8cGHU4/f39h4w1OJIAVwghhBBCCCFE/RQMi8GcwUCuQqXqkIroMx+eei7Ban5/cDpE0CyAouBoccxY16yewm67Hr/ea3P7liqvZNyJ62fNU1m3QufEtuDMfa5ch2Tv/TRv/SFaZQQAK9rB2IqrKHS/HZQ6jTXw/JC9Ytm0xsN0pcIkwkcYubg2lMfAdSHZBekef/7pLP5eC3Esq2mI+t3vfpeBgQEUReETn/gE3/jGNyb92paWFo4//ni2bdvGs88+O631x8bGJh53dHRM6jWdnZ0Tj8fHx6e1LsCpp57KI488AsB9993HF7/4xcM+/8DhV1NZu1qtTgTU4A++FUIIIYQQQghRH7mKxdD+8NSwHNIRneam0MxtwPMIWPvnnBb3ETDzKJ6Dq0WxorN/AnvJ9Lh3p8mPt5mMlP3uTD0I71qscekyne7kDO7Pc0n0/ZrmLTejl/wuWDvczPjyK8j1rIFA/Q5cMm2XXMUiogc5rj1BSyzEERWfei5UMmAZEG+D9CKItUFg5g8EE0K8qqYh6t133w1AIpHgn/7pn6b8+hNOOIGtW7eyffv2aa1fLBYnHkcikUm95uDnHfz6qfrABz7A1772NQCee+45br/9dtatW/e6zy0UCq/5/BQKhTdd40tf+hJ/+7d/O+09CiGEEEIIIYQ4PM/zyFdsBnJlhnJVqo4fnrbEZi489eecZlBLQ6jVDIpt4GoRnHATXgOcvj5UcvnxNpOf7zAp72+wTIcUPnC8zvuP10iFZjDs8zxi+35Ly5abCeX3AGDrKTLLLiO3+CK8YP1+31zXPzjK9Ty6UmE6U2Ei2hEEx54HRg6qBYg2Q9tKiHdAsG5nggshpqCm/0986aWXUBSF8847j3g8PuXXNzc3A5DNZqe1vmEYE48nezBVKPTqX6iVSmVa6wK8/e1v521vexu/+c1vALj22muxbZsrrrjikOft3r2bj3zkI+zcufOQ65NZ+wtf+AKf/exnJz7O5/N0d3dPe89CCCGEEEIIIXye55EtW+zLVRjMG1iOR1NEp0WfmfBUcUyC1SzByihaZRTFKuMFtVmfc3qwrWMOt2+t8uu9Nu7+Y0F6kgHWLte5cJGGHpzJ8QYe0eFnadl8E+HsKwA4aozM8ZeSXXoJnjq5wqrpqlQdiqblj3ZIR0hHtCPrsq8WoJL1Z512nQSJLlBn72AwIcRr1TREPdBOP3/+/Gm9/sCMFNd13+SZry8cDk88Nk1zUq85uD1+stWrb+Smm27i9NNPZ3R0lFKpxJVXXslf//Vfc9ZZZxEOh9mxYwePPvoolmURjUY599xz+cUvfgH41btvJhQKHRL6CiGEEEIIIYQ4Mp7nkSlb9GfLDBeqOI5HU1QnfCQVhZPlOgRNf86pVhomYBXwFAVXT+CGZnfO6QGO6/H4gM3tW0x+N+pMXD+lI8ja5Tqnd6kzOhtWsQ3iA78htfvnRMb9c0ncYJjs0g+QOe5DuPrUC7qmwnY8shUTPRhgUUuMtkQY7UjCY7MM5XHQo37laXoBaPUNgIUQ01PTEDUWi5HNZqdd0Tk4OAj481Gn4+Dq18nu4eDnTad69mCLFi3iscceY+3atbz00ksAbN++/TXjCTo6Orj55pu56667JkLUdDp9RGsLIYQQQgghhJg81/UYL5v0ZyqMFPzimlREq3946nkErML+OaeDBMwciufg6HGsWHv9Dj6aIsP2+OUuizu2mgwU/UInNQDvWKixdrnO0qaZnHfqEc5sIblnI4n+RwjY/vfxbkAjt/i9ZJZdhhNK13kPUDBsqo5DazxEZypMInQEkYpdhdIoBHVoWQrpbgi9eXGVEGL21DRE7erqIpPJ8PLLL0/5tZ7n8fjjj6MoCosXL57W+geHr0NDQ5N6zYHgFl4dJ3Akjj/+eJ5//nl+9KMfcfvtt/Pkk08yMjJCKBRiyZIlXHrppVx//fW0trby3e9+d+J10pYvhBBCCCGEEPXnuB7jJZP+TJmRookCNEV1dLW+czwVu4JqZFDLQwSrGQK2iaNFsCPNdT30aKrGKy53vWJy93aLgun37Mc1eN9xOh84Xqc1OnPzToNGhsTeB0nt2Yhe7Ju4bsa6yPesId99Ic4MjDqoWi55wyQR0uhuidMSDU3/jCfHgvIoeAqkuqFpIUSaarpfIUR91DREPffcc3n55Zd59tln2b17N4sWLZr0a++44w5GR0dRFIW3v/3t01p/+fLlE4/37Nkzqdf09vZOPF6xYsW01v19gUCAK6644jXzUH/fpk2bJh6ffvrpNVlbCCGEEEIIIcRrOa7HWLFKf7bCaLFKAIWWmI52RMeoH54/5zTz6pxTu4IX1HG0OHYk/OY3mEG7sg63bzV5aI+FtX/CXldM4dLlId69WCOizVDLvmsTG3qG5J6NxIaeRPH8zbjBEMV5f0CuZw1Gy6oZGXXgupAtmygBmJ+O0pkKE5pu2O46UBn3Q9R4B6R7INbaECMbhBCTU9MQ9bLLLuPb3/42nufxqU99irvvvntSrxsYGODTn/404M9FvfLKK6e1/sqVKycev/TSS9i2jaoe/i0+++yzr/v6estms2zevHni43POOWfG1hZCCCGEEEKIY4XtuIwWTfoyZcZLJmogQEssVL/w1HUImjk/OC2PELCK++ecJnFD6YYKzTzP45lB/7CoZwZfnXd6QmuQdct1zpmvEgzMzH61wl6SezaS3PsgajU7cb3SvIL8wjUU55+Lq0VnZC8AJcOmYtukIzrz0lFSkWnGJ57rHxhllv3QtGkRxNsh0BhjG4QQk1fTEPWCCy7g/PPP5+GHH+bee+/lsssu44YbbjjsjNOf/exnfPKTn2RwcBBFUVi3bh0nnHDCtNY/55xzCIVCVKtVSqUSTz/9NGedddYbPr9arfL4448fsv+Zcuedd2JZFgAnnHACp5566oytLYQQQgghhBBHO8txGS1W2TteJlMy0dUgbfEQaj3CU88jYOYJGlm08j4CZh7F8/bPOe0AZeZa4CfDdDwe2uPPO92V8ys9Awq8bYHKuuU6J7TWNCp4Q4pVJtH/CMnejROHRAHYoTT57gvI96zBSszs6Dvb9shUqkQ0lUUtcVoTIbTpBMmeB9U8GHm/XX/eMkh0QrBxRjcIIaam5n8z3njjjZxxxhkMDQ1x5513cs8993DhhRfS1/fq/JLPfOYzDA4O8thjjx1yffHixdxwww3TXjsej3PhhRdy7733AvD973//sCHqnXfeSaFQAPx5qOedd960156KarXKP/7jP058fP3118/IukIIIYQQQghxtDNtl5H94Wm2bBFWA3QkI3WpqAxYJYLVLGppiGA1i+KYuFoEO9IKgZkJIqciX3W5e7vFT18xGTf8eadhFd6zROfSZTpd8RkIez2P8NgmUr33E+9/hIDjH+rlKQFKHaeT71lDqeO0Gf/8eR7kKxa269KeCDMvHSGqT7Na1CxCOQN6AjpXQ6ILtMYa3yCEmDrF8zyv1jfdvHkza9euZcsW/ydJymHaFQ4sv2rVKn76059O+1CpA+655x7e9773ARAKhXjmmWdYtWrVa55XLpc56aST2L59OwCf//zn+dKXvnREa0+G53lcd911bNiwAYC3vOUtPPvss2ja1H8alc/nSaVS5HI5kslkrbcqhBBCCCGEEHNG1XYYKVTpG6+QM0wiqkoyotU8PFWcKkEjg1oZRTVGUWwDN6jj6gm8YKima9VKf8Hljq1VNu6yMPZ37bdGFD64TOfipTpxvf4t+8HKKMm9D5LcsxG9tG/iuhlfQK5nDYXuC3DCs3PAkmE5FAyLRFhjXjpCU0Sf3sFRtgGlMVBD/qFR6W7QYzXfrxCitiabr9UlRAU/pPyXf/kXvvnNbzI8PPyGz0un0/z5n/85n/vc54jFavOXy3nnnccjjzwCwKJFi7jrrrs48cQTJ359bGyMK6+8ko0bNwJ+FeqOHTtIp9Ovudfu3bsPCXY3bNjAtdde+7rr/vKXv+Q3v/kN11xzDUuWLHnNr+/YsYM/+7M/45577gEgEonw8MMPT/tQKQlRhRBCCCGEEMc6w3IYzhv0ZSrkDYuorpKKaARqOXvUtQlWc6iVMdTKMAGrhBcI4mhxvBmc0zkVnufxuxGHO7aaPNZvc+Ab/6XpAOtW6JzfraEF6xyeuhbxfU+S7N1IdOhZFPYfEqVGKMw/l3zPGoymFbM2J9ZxPHIVi2BAoSMZoj05zYOjHNMPT5UAJOdD00IIp2q/YSFEXcx6iHqAbds8/fTT/Pa3v2VgYIBcLkcsFqOjo4MzzzyTt73tbei6XtM1+/r6OOOMM9i3z//plqIonH/++SxdupSRkRHuv/9+yuUyAKqqct9993HhhRe+7r2mEqL+8Ic/nDgUa9myZaxevZqWlhYKhQJbt2495BCrcDjMT3/6U9asWTPt9ykhqhBCCCGEEOJYVTEdhgsGezMVioZNPKSSCKu1C089l4CZRzUyqKVBglYePHD0hH/AUYPNOT3AcT0e6bO5fUuVrePuxPUzulTWrdA5uT142G7RWtDzu0nu2Uhi70OoZn7ieqVlFbmFayjOfxueGqnrHg7Lg2LVxrAdmqM689IREuFpjA9wbSiPg+tAvMM/NCra3FCHhwkh3txk87W6DxlRVZWzzjrrsLNJa23BggU8+OCDXHnllTz//PN4nsevfvUrfvWrXx3yvLa2NjZs2PCGAeqR2LZtG9u2bXvdXzvttNP49re/zSmnnFLzdYUQQgghhBDiaFY2bQZzBgPZCsWqTTykMS8VrlkwGDCLBKtZtPIggWoOxbVxtQhWpLFPVC9ZHvftNPnxVpOhsl8rpQVgzSKNS5fr9KTqu/eAWSTR/2uSezYSzr4ycd0ON5NfeCH5he/Eis+v6x4mw7RdshWTqK6ytC1OSyzElM8a81yoZMCqQLwd0osg1sb0ZgAIIeaKxpt0XSMrVqzgiSee4Ic//CG33normzZtYmhoiHQ6zZIlS7j00kv56Ec/Smtra83WfN/73sePf/xjHnjgAZ544gn27dvHyMgIkUiErq4uzjjjDC677DIuuugiAvKXqxBCCCGEEEJMWrFqM5irMJA1KJs2ybDGvFSkJuGpYhv+AVHlYVRjDMWu4qohnFAKL1jbzslaGy65/OQVk3t2mJQt/1oqpHDJcRrvP16nKVzH7z09l8joSyT3bCQ+8BgB1/QvKyrFrjPIL1xDuf2UhgifXdc/OMr1POalwnSmIkS0Ke7L88DIQbUI0SZoW+lXoAaP2mhFCHGQurfzi/qRdn4hhBBCCCHE0a5gWBOVpxXLJRXWiE+n9fr3uRaqkSVojKGWRwjaJdyAiqMnZrfVfJK2jTvcsbXKw702zv7v6rsTAdYu13nnIo2QWr+WcrU8TLL3AZK996OVhyauVxMLyfe8i0L3O3BCjTMTtFJ1KJoWqYjfup+OaFPvuK8WoJKFUBKaevzZp2pjB+xCiMlpmHZ+IYQQQgghhBBiqnIVi33ZCoN5A8NySEd0mmOhI7up5xKs5vcHp0MEzQIoCo4Wx4x1NfwsS9fzeGLA5vYtJi+OOBPXT24Psm6FzuldNZwJ+3sUxyS273H/kKjh51H2H1XlqFEKC84n37OGavr4hvoc2o5HtmKiBwP0NMdoT4anfpiWVYbSOOhRv/I0Nd9/LIQ45tQ1RH366ad58skn2bVrF/l8HsuyJvU6RVH47ne/W8+tCSGEEEIIIYRoQHnDoi9TZihnYNoe6ahGy5GEp55HwNo/57S4j4CZR/EcXC2KFW3sOacHVG2Pjbst7txqsrfgHxYVVODtCzXWLtc5vrl+7yGU3eEfEtX3K4JWceJ6ufVE8j1rKHadjaeG67b+tHhQMGyqjkNrPERnKkwiNMX4w65CaRSCOjQvgaaFEErUZ79CiDmhLiHqj370I/7qr/6KnTt3TvseEqIKIYQQQgghxLHDdT0GchV2jpSomA5NUZ3W+PTDQX/OaQa1NIRazaDYBq4WwQk34QW1Gu68fjKGy12vmPxsu0Wu6ld+xjS4eKnOB5fptEXrM+80YOZJ7H2YZO9GwrlXv6+3Im3kF76T/MILsWOddVn7SFUtl7xhEg+pdLfEaY5O8eAox4LyGHhAqhvS3RBtrtd2hRBzSM1D1M9//vP88z//MwDTHbdaq1MVhRBCCCGEEEI0vrJps3OkRH+mTCykMS89vZmkimMSrGYJVkbRKqMoVhkvqPlzTiMtNd51/ezJOdy+1eSB3RaWX3hKZ0zhQ8t03rNEJ6rV4XtmzyE68gLJPRuJ7fstAdcGwA2olLrOJt+zhnLbSaA0ZuWu60KubEIA5qejdCTDhLUppKeuA5VxP0SNd0C6B2KtDTWeQAgxu2oaot5333185Stfmfi4ubmZiy++mLe85S00NzejqjKCVQghhBBCCCGEz/M8RgpVdowUyVUs2hNhtCmVDQKuQ9D055xqpWECVgFPUXD1BG6o8eecHuB5Hs8N+eHpU/vsiesrWoKsW67zBwtUgoHavxe1NEiy936SvQ+gVUYmrhupJeR71lBY8HZcvbHb2EuGTdmyaYrqdKUipKZycJTnQSXjzz6NtkLTIojPjTEPQoiZVdNU8xvf+AbgV5Jedtll/Nd//RfxeLyWSwghhBBCCCGEOApUbYc9o2V6x8uoAYV5qcjkuxI9j4BV2D/ndJCAmUPxHBwthhVrb9hqyddjOR6/6rW4favJzqxfdqoA5yxQWbdcZ1VrsObdmoptEN/3W5J7NhIdfXHiuqPFKSx4+/5DopbWdM16sG3/4KiQFmRxa5zWRAhtKkGzkQMjD+E0dJ0EiS6YI6MehBAzr6Yh6lNPPQVAZ2cnP/jBDwiFjvDkRCGEEEIIIYQQR53xksmOkSJjxSotsRBhbXKhp2JXUI0ManmIYDVDwDZxtAh2pBkCcyv8Kpge92w3+ckrJmMVfxReOAjvXqLxoWUh5idqPO/U8whlXyG155fE+35N0C77l1Eot59MfuEaSl1n4QX12q5bB7btUTAsXDzaEiG60mFi+hTiDbME5XHQE9DxFkjOA63BDscSQjScmoaohUIBRVF4xzveIQGqEEIIIYQQQohD2I5LX6bM7tEyjuvRmYy8aYu6P+c08+qcU7uCF9RxtDh2ZO4FX/uKLnduNblvl4mxv2u/OazwwWU6Fy/VSYZqW3UarOZI7H2IZO9GQvk9E9etaMerh0RF22u6Zr0YlkOxahNQFJpiOq0JnXRYJzDZvNk2oDQGaghal0FqAYSke1YIMTk1DVEXLFjAjh07iEajtbytEEIIIYQQQog5rmBY7BwpMZivkAzrxEOH+XbUdQiaOT84LY8QsIr755wmcUPpOTPn9GCbRm1u32LyWL+Nu/8M5sWpAOtW6LxjoYYWrOF7ch2iw8+S2rOR2OCTKN6BQ6J0ivPOId/zLiqtbwGlxtWu9eBBqWpTNm1CWpDOZIiWWJhEWJ38HwPHhNK4/+cm3QPpboik67lrIcRRqKYh6sknn8z27dvZvn17LW8rhBBCCCGEEGKOcl2PwbzBjpEiZdOhPR5GfYPDoxTbQC0Po5UGCJh5FM/D0eNYsY65Efj9Hsf1+E2/H55uHnMmrp/eFWTd8hBv7ajtvFOt2D9xSJRqjE9cN9LH+4dEzT8PV58blZeu64enhm0T0VUWtsRojulE9SnMu3Vtv23ftSHe6R8aFW2ekyG8EGL2KZ7nebW62a9+9SsuuOACNE3jlVdeYeHChbW6tXgd+XyeVCpFLpcjmUzO9naEEEIIIYQQ4hAV02HXaJG+TIWIFiQdff15m4pTRS0Po+f3ErByuGoUR09AoKZ1PzOmbHn8YpfJnVtNBkv+t9xaAC7s0Vi7QmdRqnYHXyl2hXj/b0j1biQytmniuq0nKXS/g/zCNZipRTVbr95sx5936rgu8bBGeyJEOqoTUqcQonsuVDJgGRBvg/QiiLUx+b5/IcSxZLL5Wk3/RXr729/OJZdcwk9/+lP+8A//kF/84hcyG1UIIYQQQgghjkEjhSo7RopkSyatiRAh9bXB4WvCUy2GFeuak1WnAKNllx9vM7lnh0nJ8q8ldYX3H6dxyfE6zZEavS/PIzy+hWTvRhL9jxCwK/5lApQ7TiXXs4ZS5+lz6rCtquVSrFooKKSjGm2JEMmIhvomM3MP4XlQzYFRgEgTtK3wK1CDczOMF0I0lpr/TXLrrbeydu1a7rvvPk477TS+9KUvcdFFFxEM1u4nbUIIIYQQQgghGpNpu/SOl9g9ViaoKMxLR17Tsn60hafbMw63bzH5Va+Fs7/Xc34iwNrlOmsWaYTV2rSPB40Mib0PktqzEb3YN3HdjHWR71lDvvsCnEhrTdaaER6UTZuSaaMHg7QnQrTEwyRC6tSLRqsFqGQhlITO1ZCc5x8gJYQQNVLTdv4DPM/jH/7hH/ibv/kbFEUhEomwbNkyUqnUpOa9KIrCAw88UOttHXWknV8IIYQQQgjRSLJlkx0jRUYKJk1Rjah+aN3OgfBUK+wlaPrhqaMn52R46noeT+3z550+P/zqvNPVbUHWrdA5a55KoBazN12b2NDTJPdsJDb0FIrn+peDIYrzzyW38J0YLavm1JxP14WSaWNYDhEtSGtcpymuE9enUedllaGcAS0CqYWQmg+6HHYthJi8WWnnP+ArX/kKX//611EUBc/zKJfLvPDCC5N6red5NR2sLYQQQgghhBCivhzXoz9TZudoCdvx6EyGCR7Uhu2HpyNohV6CZh5Xi87ZylPT8bh/t8UdW016836gGVDgvG6VdStCLG+uTRemVthLas9GEnsfRK1mJ65XmleQX7iGwvxz8bS5FRbajkexamO7LvGQyrx0jHREJ6xN48+BWQYj648saFoM6W4IS3GREKJ+ah6i/vEf/zEbNmx4zfU6FLwKIYQQQgghhJhlxarNzpEiA1mDZFilJfbqHE7FMfdXnu4PT9UIVqxzToanWcPl7u0WP33FJFv1v7+NqvDepTofWqbTHjvy9xSwysT7f01yz0Yima0T1+1Qmnz3BeR71mAluo94nZlm2i5Fw8YDUhGVtkSMVFRDm8q8UwC7CtW8/79aFFLdkFoA0ea67FsIIQ5W0xD11ltv5Xvf+95EBery5cu5/PLLWb16NU1NTaiqDHMWQgghhBBCiKOB53kM5atsHylSNCzaE2G0oB8kHhKeVnP7K0/nZnjam3e4c6vJxt0W5v6u/faowoeW6Vy0VCemHWEnpecRHttEas9G4gOPEnCq/mUlQKnjDPI9ayh1nAqBOfb9tAcVy6FkWqiBAC1xnZZ4iFRYm9q8U9f2552aJQjq/oFRiS4/ONVjddu+EEL8vpr+Lfyd73xn4vFnPvMZ/vmf/5nAlKdBCyGEEEIIIYRoZIblsHu0xN5MmVAwyLyUf3jUq+HpXoLVrB+exude277nebww7HDHVpPHB+yJ68uaA6xbHuK8bvWQcQXTEayMkux9kGTvRvTSvonrZnwBuZ53Ueh+B0646YjWmA2eB6WqTcWyCWsq89NRmmL+vNNJT+7zXKgW/fBUCfht+u2L/OA0nJpT81+FEEePmh4slU6nKRQKLFq0iFdeeUUC1DqTg6WEEEIIIYQQM22sWGXHSJHxkklLLERYC/rhaWUELd87EZ46odScC09t1+PhXps7tlZ5JePPO1WAs+errF2us7oteERneCiORWzwCZK9G4kOPYfC/kOi1AiF+eeS71mD0bRiToaEzv55p6bjEtdV2pIh0lGNiDaFGbFm2W/Xdx3Q45DohFgrhNMQnGOVuEKIOWNWDpayLAuAc889VwJUIYQQQgghhDiKWI5L71iZPeMl8BS6UhGCroVaHNwfnuZwtcicrDwtmh737jD5yTaTkYpfZxQKwrsWa1y6TGdB8sgOi9Jzu0n2biS59yGCZn7iernlLeR71lCc9zY8NXxEa8wWy3YpGDYeHsmwRk8ySjqiowUnGQQfmHNqGaBH/Vb9eIdfdaqG6rt5IYSYgpqGqPPmzWPnzp0y+1QIIYQQQgghjiK5isXOkSJDeYN0RCeuuqilgd8LT+fezNPBosuPt5n8fKdJZX/XflNY4QPH67zvOI1UaPrvJ2AWSew/JCqcfWXiuh1uJr/wneQXXogVn3+kb2HWGKZD0bQJBhSa4zqt8RDJsEZwMp+yiTmnZX/Wa7QJ2lb6805D8brvXQghpqOmaefZZ5/Njh07ePnll2t5WyGEEEIIIYQQs8B1PQZyFXaMFDFtl864StgYQhvfS9DI7g9PO0A5skrNmbZ5zOb2LSaP9tm4+wfcLUoFWLtc54IeDX2yVZS/z3OJjL5Ics9G4gO/JeCa/mVFpdh1BvmFayi3nwKBufX5OuDgeachLUhnMkxrPEQ8NIl5p57rHw5l5P1xBaEktJ/gB6ihFFM7bUoIIWZeTWeiPvroo5x33nkEg0GeffZZVq9eXatbi9chM1GFEEIIIYQQ9VI2bXaOlOjPlIlr0OJl0Qq9E+GpE0rOqfDUcT1+O+CHp5tGnYnrp3QEWbcixGmd0593qpaHSfY+QLL3frTy0MT1arKH/MJ3Ueh+uz8jdo5yXShWbaq2TVRXaU+EaIrqRPRJ/P5bZT84dR3QY/vnnLbJnFMhRMOYbL5W0xAV4DOf+Qxf//rXOeGEE3jooYdoa2ur5e3FQSREFUIIIYQQQtSa53mMFPzDo/KlMvOCBaLlPtRqFkcN7z8wau6EpxXb4xc7LX68rcpA0f/2Vw3AOxZqrFuhsyQ9vfeiOCaxfb8lued+oiPPo+Df21GjFBacT77nXVTTx83JQ6IOsG2PgmHh4JEIq7QnwqQiGiH1TapG7arfrm9VQIv4h0PFO/12fW1uzn4VQhy9ZuVgKYB/+Zd/IRKJ8OUvf5nVq1fzV3/1V6xdu5Z58+bVeikhhBBCCCGEEDVUtR32jJbZO5ojWh1jqTuItj88NWNzq21/rOLyk20m9+wwKfhd9SR0eN9xOpccr9MamV77eCi7neSejST6fkXQKk1cL7ee6B8S1XX2nD0k6gDDcihWbQKKQlNMpzWhkwxrqIHDBMKuDdWi/19Qg0ga2pZDpFnmnAohjgo1rURdsmTJxOP+/n4sy5poh0ilUqRSqUm1RyiKwo4dO2q1raOWVKIKIYQQQgghamW8ZLJzKENxtJ92Z5iYk5uTlac7sw63bzF5qNfCdv1r8+IKly4P8a7FGhF16pWhATNPYu/DJHs3Es7tnLhuRdomDomyY521eguzw/NHOJRMB10N0BLTaImFSYQPM+/U88As+lWn4M85Tc6DaLPMORVCzBmzUom6e/fuQ0LSA489zyObzZLL5d70Hp7nTXsOjRBCCCGEEEKIqbEdl77RHAP9veiFPhYqBdAjc6ry1PM8nh50uH1LlWeHXp13uqo1yLoVOmfPUwkerorydW/qEB1+nmTv/cT2/ZaAawPgBlRKXeeQ71lDue3EOfM5eiOu6x8WZdg2EV2luylKc1wjph8mLrDKfnBqW36VaXoRxNv9dn2ZcyqEOErV/G+3wxW21nj8qhBCCCGEEEKII1Aoldm7dw+Fwe00e0X0cAQn3DlngkHT8Xhwj8UdW0125/yy04AC5y5QWbtCZ2XL1L/lVUuDJPdsJLn3AbTK6MR1I7WUfM87KSx4O66eqNl7mC2241E0bGzXIR7WmN8UJx3V33jeqWP6B0RZhj/XNN7h/xdpljmnQohjQk1D1F27dtXydkIIIYQQQggh6sC1LYb39TLUuxWnNEZLLI4X7cKZI+Fpvupy93aLu14xyRh+sU5EhYuW6HxomU5nfGpt5IptEB94jGTvRqKjL01cd7Q4he53kF/4TqrppTV9D7OlarkUqxYKCqmoRlsiRjKiob1epe6BOadmCQJBv9K0bbn/v6G5HyQLIcRU1DRE7enpqeXthBBCCCGEEELUkmNTyQwwuGcr2bFBVD1KtLUbLzA3wtO+vMMd20w27rKo7u/ab4sofHCZznuX6sT1KbTsex6h7DZSezYS7/s1QbvsX0ah3P5W8j1rKHWeiRfU6/BOZpgHFdOhaFrowSDtiRDNsRDJsPbasaUHzzn1PAinoG2FP+c0nJY5p0KIY5YMKxFCCCGEEEKIo51j4xWHyO7bzvC+fvKOSiw9H03XZntnb8rzPF4acbh9q8nj/TYHhsQd3xRg3fIQ5y1UD39q/O8JVrMk9j5Ecs9GQoXeietWtINczxoK3RdgR9tr/C5mh+v6h0VVLIeIFqS7KUpTXCf+evNOrQpU8+DYoMUOmnOahmDj/zkRQoh6kxBVCCGEEEIIIY5Wjg2lYazRXYwMDzBY8nBDbaTTYWjw83xt1+ORvTa3b62ybdyduH7WPJV1y3VObA9O/lBi1yE2/AzJPRuJDT6J4vllrG5ApzjvbeR71lBpfQsoR0eVpe14FKs2tusS11WWtMVIR3TC2u+9P8f0K07NMmgRiLVDotNv19cis7N5IYRoUBKiCiGEEEIIIcTRZn94SmYPxcwQ+4ouI06SRDJEWGvs1v2S5XHvDpOfbDMZLvt1p3oQ1izSuHS5zsLk5PevFfv3HxL1IKoxPnHdSB9PruddFBech6vFav4eZotpuxQNv1o3FVFpS8RIRTS04EFhs+uAWYDq/jmn4TS0HO+36+txmGwwLYQQxxgJUYUQQgghhBDiaDERnvbilEYYrcBeI4ZDgJaE3tDjLB3X48fbTG7cVKVs+dfSIYVLjtd5/3Ea6fDkNq/YFRL9j5Ls3Uhk7OWJ67ae3H9I1BrM1KI6vIPZY5gOxaqNGlRojuu0xv15p8EDnzLPA6sERgE8F8JJaF0OsRaZcyqEEJNU0xB1yZIlNbmPoijs2LGjJvcSQgghhBBCiKOeY0NpBLJ7oDRKxQ3SV00wUraJ6UFSocaun9mTc/jqkwZbxvw2+4XJAGuX61zYoxFSJ1EZ6XmExzeT3LORRP8jBBzDv0yAcsep5HrWUOo8HQJHz2xPz4NS1aZi24RVlXnpCM0xnXhIfbWY1Kr47fqOCVoc0gv3zzltkjmnQggxRTX9l3T37t2Tn0mzn+d5E48VRcHzvCnfQwghhBBCCCGOSa4DxeGJ8NQLaIwpzewtVjFMm6aojhps3O+vbNfjts0mN2+qYrkQVeHjbw3zniUagUl8Xxg0xkn2PkiydyN6sX/iuhmbR75nDfnuC3AiLfV8CzPO2T/v1HIdoprK4pY46ahG5MCYBsfyD4iyKqCGIdrqzzmNNsucUyGEOAI1/3HkwaHoZB0IT6fzWiGEEEIIIYQ45hwcnpbHIKBSjbQzkDcZypfRg0Fa46GGPjxqe8bhq09U2JH1D406o0vlz08P0xZ9k9Zy1yY2+BTJ3o3Ehp5G8fzXu8EQxfnnkutZg9F8wlE329OyXQqGjYtHMqzRk4iSimrowYD/58HI+nNOlSBE0v6c00gThBJH3edCCCFmQ01D1F27dk3qea7rksvleOmll/jRj37EPffcQzgc5pvf/CYXXHBBLbckhBBCCCGEEEePA+FprhdKoxBQId5OxvDoHy2Tr1ikIjq62rgzLk3H4+ZNVW7bbOJ4kNAVPnlKiAt7tMN2Jer5XpK9G0nsfQi1mp24XmleSX7hGgrz/wBPi87AO5hZhuXPOw0GFJpiOm2J/fNOlf1zTksFwPMPhZI5p0IIUTeK1wDln/fccw8f/vCHsSyLH/3oR3zgAx+Y7S3NCfl8nlQqRS6XI5lMzvZ2hBBCCCGEEPXiOofMPCWgQrQZiyCDWYPBfAU8hVRUa+iiw81jNv/yhMGevF89em63yqdODdP0BodGBawy8f5fk9yzkUhm68R1O5Qmv/BC8gvfiZXonpG9z6j9807Llk1IDdIc8w+LiodUFMcAI79/zmnMn3Eqc06FEGLaJpuvNUSICnDjjTdyzTXXkEqleOmll1iwYMFsb6nhSYgqhBBCCCHEUe4NwlMCKoWqTX+mwnipSiKsET4wE7MBGbbHD16qcuc2E9eDdEjhU6eFOa/7dUI/zyMy9juSezYSH/gNAafqX1aClDpPJ79wDaWOU/3PxVHGdaFYtTFtm4iu0hYP0RTTiQZdf86pWd4/57TFn3MaaQL96Ku+FUKImTTnQlSARYsWsXfvXr7whS/wD//wD7O9nYYnIaoQQgghhBBHqYPD0+KIX2G4Pzx1XRgpGvRlK1i2S1M01NCd2y8M2/zrkwYDRb/69MIejU+eEiIZ+r1Nuw7J3gdoeuV/0Ev7Ji5XE91+u373O3DCTTO59Rlj2x6FqoXjeSTCKu2JMKlQgJBbhmrRn3MaTkFqHkSaZc6pEELU0GTztYb60d0555zDD3/4Q376059KiCqEEEIIIYQ49kyEp73+7NOgBomOiarLiuXQn6kwUjAIayot8dAsb/iNlS2P/3rB4O7tFgCtEYU/Pz3MmfN+r/rU84gNPknLyz8gVOgFwFEjFOefR75nDUbT8qM2MDww7zSAQjqq0RbXSaoWqjkOxoE5p8sg1uqHqIHGrTYWQoijXUOFqAfS3t7e3lneiRBCCCGEEELMINfx2/WzvVAcek146nkwXjbpz5QpVm2aoiHUYOMGi0/ts/naUxWGy37j43uXaPzJyWFi+qF7Do9tpvXlDUTGXgbA0RKML7+c3KKL8NTwjO97RnhQNm1KpoOuBuhIhmgJQYIyATsHgRikul+dc6rqs71jIYQQNFiIunPnTgAcx5nlnQghhBBCCCHEDHDdgypPhyCo+uHZQQcEmY7LvqzBYM5ADQZoi4ehQfPTgunx7ecMfrHLrz7tjCl85vQIp3Qe+q2nVthL68v/TXzfbwFwgyGySy8hc/w6XC024/ueCa4LJdOmajuE1SDdKZ0WtUKUEiihg+acNsucUyGEaEANE6Ju3ryZhx9+GEVR6O4+Ck9XFEIIIYQQQogDDg5PS8N+m/bvhacAuYpNX6ZMrmKSiujoauMOP32sz+LrTxuMGx4K8IFlOn+0OkREezXxDRrjtGy5heSeX6J4Lh4B8j3vZGzFVTiR1tnbfB3ZjkfRsLFch0QoyPyEQ1Owgq4GIZyGZJc/7zaUPGrHFgghxNGgIULUjRs38rGPfQzLslAUhXe/+92zvSUhhBBCCCGEqL0D4Wlur195GghCrO014antegznDfqzFTwXWuPhhs3XsobLN581+FWvDcCCRIDPnRHmLW2vfrsZsMo0vXIH6R0/IeBUASh2nsnYCddgJhfOyr7rzbRdioYNnkeTbtOmG8T1IFokCYlFEG2FSFrmnAohxBxR0xD1j/7ojyb9XNu2GRsb44UXXmDfvldPXoxGo/zFX/xFLbclhBBCCCGEELPLdaF80MzTNwhPwW/57s8YjJUMYrpGRG/MkM3zPB7ea/ONZwxyVY+AApet0Fm/KkRI3Z/4uhapXT+neesPUc08AJXmFYyu+ihGy6pZ3H2deP7hXyXTQvMs2tUqLSGPeCJJIL4E4h0y51QIIeaomoao3//+91Gm8eNRz/OHjcdiMW6//Xbmz59fy20JIYQQQgghxOz4/fBUCbxheOq6MFaq0pepYNgOTZEQwQY9PGqs4vL/njZ4rN+vPl2cCvC5MyMsb94f+Hou8f5HaH35v9HKQwCY8QWMnvCHlLrOPura1j0PSlUbo2oQx6BHt0gm4sRTC/x2/UgT6EfnrFchhDhW1Lyd/0AgOhWJRILLL7+c//N//g89PT213pIQQgghhBBCzKxDwtNhPzR8g/AUwLBcBrJlhgpVwmqQ1nhohjc8OZ7n8ctdFjc8Z1C0IKjAR1aFuGKljrY/8I0MP0/rpg2EczsAsENNjK38CPmFa4661nXH8SgaJm61QDJQZX4sRDLdSrhlgcw5FUKIo0xNQ9QNGzZM+rmappFMJlm0aBErV64kGDy6/jEVQgghhBBCHIMmwtP9M08VBWItEHz99m3Pg0zFpD9ToWDYNEV0VLUxQ7ehksvXnqrw9KADwPFNAf7izAhL0v73cnp2J60vbyA2/BwAjhohc/w6sks/gKeGZ23f9WBaDqVSEc3Kk9IVmtqaSbYuR092yJxTIYQ4StU0RL3mmmtqeTshhBBCCCGEmBtcF8pjB7XtHz48BbAcj8FchYGcQVBRaIuHoAHzU9fzuGe7xX++YFCxQQvANatDrFuuEwwoqKUhWjbfSLLvVwB4ikp28UVkll+BE0rN7uZrrFopUy1m0TBpTSRJLzieVNsCgrFmUBuzelgIIURt1LydXwghhBBCCCGOGa8JT3nT8BSgYNj0ZcpkyhaJsEpYa8zKxf6Cy78+WeHFEb/69ITWIH9xRpjuZJBANUfzth+R2nUPAdefjVpYcD6jK9djxzpnc9s15Tk21WIWyyig6WFa2zpp6lxIoqkNJRSf7e0JIYSYIRKiCiGEEEIIIcRUTTM8dVwYLhj0Zys4jkdLLEQgMDNbngrH9fjxNpPvv1Sl6kA4CH90UohLjtNR3SrpbXfQtO12gnYZgHLbSYyu+ijV9HGzvPMa8VyoljCKWSzXQ4010b70OJra5hFLNsucUyGEOAZJiCqEEEIIIYQQkzXN8BSgbDr0ZyuMFKrE9CCpyOsfMjXb9uQcvvqkwZYxv/r05PYgnz0jQlfUI9n7S1q23IxqjANgpJYwtupaym1vPSqCRcUqQyVPyahiqlHCLUuZ1zGPptZ2Qrq06wshxLFMQlQhhBBCCCGEeDOe54enmT2vzjyNTm4OpufBaKlKX6aCYTo0RXXUYOMFjrbrcdtmk5s3VbFciGrw8ZPDXLRYJT70JC1P/IBQYS8AVrSDsZVXU1hwPigNWEo7BYpjEjDz2EaZnKNjR1pILJxPV0cnLakkwUDj/V4JIYSYeVMOUf/oj/6oHvs4hKIofPe73637OkIIIYQQQghxWAfC09xeyO8DJh+eAlRtl4FsmaF8FV0N0ppozGrG7RmHrz5RYUfWBeCMLpU/Pz1Md2UrrY9uIDL+MgCOlmB8+YfJLb4YL9iYlbST4joErQIBs0TJCZInhpJaTLq1nY6WVtJRDeUoqKwVQghRO4rned5UXhAIBGbkHxPHceq+xlyXz+dJpVLkcjmSyeRsb0cIIYQQQoijxyHh6aB/Ldo0pRPYM2WLvkyZgmGRiujoauNVbJqOx82bqty22cTxIKErfPKUEO9pHqRt838T3/c4AG4wRHbpJWSOX4erxWZ519PkuQSsMkGzgOsp5L0IOa0VPdVOR2sb7akI8ZA0awohxLFmsvnatP6FmGLuOmXyEz8hhBBCCCHErPA8KI9Drnfa4anlegxmDfblKyieQms83JDjQjeP2fzLEwZ78n716bndKp9dVWLJ7h+QfOGXKJ6LR4B8zzsZW3EVTqR1lnc8PYpdIWgWUFwHKxhhODiPit5ENNXK0pYErfEQYS0429sUQgjR4KYcom7YsKEe+xBCCCGEEEKI2VOD8BSgULXpz1QYL1VJhLWGDOcM2+MHL1W5c5uJ60E6pPC5t7pcXL6D9CM/IeBUASh2nsnYCddgJhfO8o6nzp9zWiBgV/G0MCW1hfFgE7beRHMqwdJ0hOaYjhpsvOpgIYQQjWnKIeo111xTj30IIYQQQgghxMx7TXjqTWnm6QGOC6NFg75sBct2aYmFCTRgPvfCsM2/PmkwUPSrT9/TA3/V/ABdL/8I1cwDUGleweiqj2K0rJrNrU6d6xC0igSsEl5Aw9GTZCJLGCeKFk7SngzRmYqQjmgE5LAoIYQQUyQDX4QQQgghhBDHnonwtA8KA/7H0whPASqWQ3+mwnDBIKqpJOONd3hU2fL4rxcM7t5uAdAW9vi3JU9z5uAtaENDAJjxBYyecA2lrrNoyPkDr8fzCFglglYR8HC0JOXUMrJKgrwXJRbWWJwK054MkwzP4YOwhBBCzDoJUYUQQgghhBDHDs+DSgaye484PPU8GC+b9I2XKZk2TdEQarDxwsen9tl87akKw2X/bIvPzN/Mx6xbiO7cAYAdamJs5UfIL1wDgcYbP/B6Dsw5Dbg2jhrDTPRg6E2MuzGqXoBURGNVOkJrPEREnxvvSQghRGOTEFUIIYQQQghx9HtNeOpCtGVa4SmA6bjsyxoM5gzUYIC2eBgaLD8tmB7ffs7gF7v86tPzorv5cuJHdI09D4CjRsgcv47s0g/gqeFZ3OnkKI5FwMz7c07VEHakHTvaTimYJGsG8FxojmmsSEdpietoMu9UCCFEDdU9RC0UCvz2t7/l2WefZXR0lEKhQCKRoLW1lVNOOYWzzz6bRCJR720IIYQQQgghjkU1Dk8BchWbvkyZXMUkFdHR1cYL6x7rs/j60wbjhke3Msy/Nd3BaeVHIAeeopJd/F4yyz+ME0rN9lYP7+A5p4qKG05jpI/H1lMUiJA3THQvQGcqTGcqTHNUl3mnQggh6qJuIWpvby9/93d/xy233EK1Wn3D54XDYa666ir++q//moUL596pj0IIIYQQQogGdEh4ug88Z3/b/vQrLm3XYzhv0J+t4LnQGg833OjQrOHyzWcNftVr00SeL0fvYp23kWDZBqCw4HxGV67HjnXO8k4P4+A5p56HoyeoNi3HCTVh6QkKVZdixSKquyxpje+fd6qiNNpvhhBCiKOK4nmeV+ub3nnnnVx33XXk83kmc3tFUUgmk3zve9/jQx/6UK23c9TK5/OkUilyuRzJZHK2tyOEEEIIIcTsOxCe5vogP1CT8BSgaNoMZAxGiwbxkNZwczY9z+PhvTbfeMagWjW4Tr2PT2l3E/bKAJTbTmZ01bVU08fN8k4PL2CVCBpZXC2GHW3HjrTihFLYXpBcxaLquCRCKvObIrQlQkR1mVAnhBDiyEw2X6t5iHrfffdxySWX4DjORIDa3NzMGWecwaJFi4jFYpRKJXbv3s1TTz3F2NgYiqLgeR6apnH33Xfzrne9q5ZbOmpJiCqEEEIIIcR+E+FpP+T7wbUh1nLE4anrwmipSn+mgmE7NEV0gg12eNRYxeX/PW3wRH+VdcFf8xfa7bSRAcBILWFs1bWU20+Z5V0enuJYqJVRvKCOmViIFZ+Pp4ap2g7ZsoWHR1NUZ35ThJZYqCFHKAghhJibJpuv1fTHduVymeuuuw7b9ltFFi1axJe//GU+9KEPoaqvXcpxHH784x/zl3/5l+zatQvLsrjuuuvYtm0bkUikllsTQgghhBBCHI0ODk8LA+BYNQlPAQzLZSBbZqhQJawGaY1Pf45qPXiexy93WdzwXIWznWe4T7+N4wP9AFjRDsZWXk1hwfmgNHDg6LkEjQwBx8SKdWEme3BDKcqmTTZXQQ0qtCdDdKUiNMd0gjLvVAghxCypaYi6YcMG9u3bh6IonHrqqfzyl78knU6/4fODwSDr1q1jzZo1rFmzhqeffpqBgQE2bNjAJz/5ySPej2ma3Hbbbdx6661s2rSJoaEhmpqaWLx4MZdeeinXXnstra2tR7zO6/ntb3/LjTfeyOOPP87u3bspFApEIhE6Ojp461vfygc/+EHWrl1LKNRYX4gJIYQQQggxJ7xeeBptBu3IizE8DzIVk/5MhYJh0xTRUdXGCu+GSi5fe6qCO7SZDdotnK5vA8DRk4wv+zC5xe/FC2qzvMvDC5hFgtUcTihNpXkldrSdsuWSyVaI6AF6mqN0psKkIprMOxVCCDHratrOf9FFF/GLX/wCVVXZvHkzS5cunfRrt2/fzsqVK3Fdl3e96138/Oc/P6K9bNmyhSuvvJLnn3/+DZ/T3t7Ohg0beO9733tEax1sbGyM6667jrvuuutNn7t06VJ+8IMf8La3vW1aa0k7vxBCCCGEOCZVMpDt88NT14ZIU03CUwDL8RjMVRjIGgQDCqmIBg2U37mexz3bLe5/YQd/ptzGu4NP+9eDOtmlHyBz/DpcLTbLuzw8v3V/DC+o+a37iQWYaIyVqqgBhfnpKPOaIsRDMu9UCCFE/c3KTNTu7m4GBgY4//zzefDBB6f8+gsvvJCHHnqI+fPns3fv3mnvo6+vjzPPPJOBgQHAP7jqvPPOY+nSpYyMjHD//fdTqVQA0DSN++67jwsuuGDa6x1QqVQ455xzDglu29raeOtb38qCBQsYGRlh06ZN7Ny5c+LXo9EoDz74IGeeeeaU15MQVQghhBBCHFMOmXlqQaQ2lacHFAybvkyZTNkiGdYIaY3VBt9fcPn+4/28K/cjPhz8FUHFwyNAvuedjK24CidSny67mnmd1n1LS5Ipm9iuS0cyzMLmKOmoPts7FUIIcQyZlZmoo6OjABx33PROfFy6dCkPPfTQxH2m66qrrpoIUHt6erjrrrs46aSTDtnnFVdcwQMPPIBlWVx22WXs2LHjsKMHJuPLX/7yRICqKAp///d/z2c/+9lD5rt6nsdtt93G9ddfTy6Xo1wu87GPfYwXX3zxiNYWQgghhBDiqDURng6Aa9Y8PHVcGC4Y9GcrOI5HSyxEoIHyU8f1uHdzhsiWO/mPwL1EVBOAQueZjJ9wDWZy4Szv8M35rft5nLDfum9F2shXXUqFCs2xED3NUVrjIQIy81QIIUSDqmmIGolEME2TYrE4rdcfeN2RHCp177338sgjjwCg6zp33303q1evPuQ5ra2t3HXXXZx44ons3LmT8fFxvvKVr/DFL35x2usCfP/73594/OlPf5q/+qu/es1zFEXhiiuuQFVVLrvsMgBeeuklXnrppdfsUwghhBBCiGNancNTgLLp0J+tMFKoEtODfvt+A+nNGGz77d1cW72D5qD//VIutYL8iR/FaFk1y7t7cwe37lebjsdKLKDkBMnkq8TDGid0pehMhdGCDZRaCyGEEK+jpv9SzZs3D8/zJkLMqfA8j0cffRRFUZg3b9609/DNb35z4vE111zzhsFkLBbj7/7u7yY+/va3v41t29NeN5/Ps2fPnomPr7zyysM+/4Mf/CDRaHTi423btk17bSGEEEIIIY4qlSwM/g72PgXZ3RCKQXJ+TQNUz4ORYpWtQwVGC1WaojrRBprBaTsOL/72fpb96hN8wvwBzUqR8dB8+s/43wy//Z8bP0D1XIKVMdTKKFask3L7KRTji+kvulRMh+Pa4py6sInu5qgEqEIIIeaEmv5r9Y53vAOAgYEBvvGNb0zptf/xH/9BX18fAG9/+9untX6xWOSBBx6Y+PijH/3oYZ+/du1a4vE4AOPj4/z617+e1roH1j5YU1PTYZ+vquohcxZc15322kIIIYQQQhwVJsLTJyGz+6DwNPpmr5ySqu2ye6zIjuEingetiRBqsHHayDM7nyH4sz9n7dDX6FZGGFea2HHCJxl797cozzsHGvyk+oBZRCsO4qkRKm0nUWpexaAZIlM2mZ+O8NaeJo7rSBDRg7O9VSGEEGLSahqiXn311ROPP/vZz3LDDTdM6nX/+Z//yWc+85mJj9evXz+t9R977DGq1SrgV5qefvrph31+OBzm7LPPnvh4OodhHdDW1kY4HJ74eNOmTYd9/sjICMPDwxMfHzyzVQghhBBCiGNKJQuDm6DvqVfD01Ttw1OATNli21CBfTmDZFgjEW6c6tPA+Hb4xf/mjBf/hmXeLopehCc7r2Lsvd/BXfZeCDR26Kg4FlpxkIBTpdq8jHLbyYwozQwWTNJRjZO606yal2y4kQlCCCHEZNQ0RD3zzDO5/PLL8TwP27b50z/9U0499VT+/d//nWeeeYbR0VEqlQqjo6M8++yzfOMb3+D000/n+uuvx7IsFEXh8ssvn9ZJ9QCbN2+eeLx69WpU9c2/IDrllFNe9/VTpWkaF1100cTH//AP/0C5XH7D5//lX/7lRPXphRdeyLJly6a9thBCCCGEEHPSIeHpLj80rVN4arkee8crvDJcwDBdWuNhNLUx2sjV0iCR33yFpb/+c46vvIjpBbkv8l62Xfgdms66quZzYGvudVr3x8ML6S+6qAGF1QtSnLQgTVsihNLgVbRCCCHEG6n5j12/973vsWvXLp566ikAnn/+ef78z//8sK/xPA+A008/ne9+97vTXnvr1q0Tj3t6eib1moULXz3JcsuWLdNeG+CLX/wiGzdupFgs8uyzz3LiiSfy13/917ztbW9jwYIFjIyM8OKLL/JP//RPPProowCccMIJbNiw4YjWFUIIIYQQYk4xcpDtg8IA2FWINEGstW7LFao2/ZkK46UqibBGWGuMis5ANUdqy22kd92Lin8+w73e2yitvpqTj+ue5d1NTsAsEqzmccJpKs0rKWotjJdtwprD8e0J5jdFGubzLYQQQhyJmoeo0WiUX/3qV3zuc5/jO9/5zqRmfQYCAT7+8Y/z1a9+lUhk+j9lHRsbm3jc0dExqdd0dnZOPB4fH5/22gArVqzgN7/5De9///vp7e1lx44dXHvtta/73HQ6zfr16/nHf/xHEonEEa0rhBBCCCHEnGDkIbt3xsJTx4WRokF/toJlu7TEwgQaoPhUsQ3SO35KatvtaI7fvfaI8xYeal/PxWesJBlqgE2+CcWxUCujeGqIavMyKpEuxgwFz3Hobo6woDlKMixt+0IIIY4edRkAFIlE+Na3vsVf/MVf8J//+Z88+OCDPP/881iWNfEcTdM4+eSTueCCC/jYxz7GkiVLjnjdgw93mmwYe/Dzfv9wqOk48cQT2bZtG//1X//FX/7lX1IqlV73ee9+97u58sorpxSgVqvViZmvAPl8/oj3K4QQQgghRN3ZVcj1+fNOrUrdw1OAiunQn60wXDCIairJeKiu602K65Ds3Ujz5lvQqn4Bxya3h28FruLss8/gynlzIHT0XILGOAHHwop1YSQWMu5EMco27ckQ3c1RWmK6tO0LIYQ46tR1ivqSJUv40pe+NPFxLpejWCwSj8dJpVI1X88wjInHuq5P6jWh0KtfTFUqlSPew+joKP/rf/0vbrrpJizLorOzk3POOYfW1lay2SxPPPEEe/bs4bbbbuO2227jT/7kT/jWt75FMPjmLS5f+tKX+Nu//dsj3qMQQgghhBAzwnWhOATjO6A8DpE0RJvruqTnwXjZZO94mbJp0xQNoQZnOdDzPGKDT9Dy8g8IFfYCsNdt46v2Zdg95/Oxt0aJ6Y0fOh7aur+ITKCJvOGSjgZY1pmmPREmGGj89yGEEEJMx4weRZlKpeoSnh4QDocnHpumOanXHFzZeSSjBABeeeUVLrjgAvr6+giFQnzjG9/g4x//+CEHXHmexw9/+EOuv/568vk83/nOdwgGg3zrW9960/t/4Qtf4LOf/ezEx/l8nu7uuTErSQghhBBCHGMqWf+wqFw/qCH/wCilvm3qpuOyL2uwL2egBQO0xcMwy5leeOxlWjd9n8j4ywCMe3G+YX+IjaE1/H/nJDmlc0a/JZsWxTFRK2MTrfuFUCejBkR1hRWdcbrSEUKqzD0VQghxdGv8f7GnIB6PTzyebFXpwc87+PVTZds2l156KX19fQDccMMNrzsPVVEUrrzySlpbW3nXu94FwH/8x39w7bXXcsYZZxx2jVAodEjlrBBCCCGEEA3HMvy5p9nd4JgQb4Pg5LrEjkSuYtOXKZOrmKQiOro6u3NFtcJeWjf9gPjg4wBU0PmufRHfsd/PhcvSfPPEEBG1was2D7Tuu37rfjnWzYgdQbGhpyVMd3OMeOio+pZSCCGEeEM1/Rdv9erVrF+/nquuuooFCxbU8taT0tLSMvF4aGhoUq8ZHByceNzcPP3WojvuuIPf/e53ACxfvpxrrrnmsM9fs2YN73znO7n//vsB2LBhw5uGqEIIIYQQQjQs1/Fb98d2QCUD0frPPQWwXY/hvH94lOdCazzMbI7jDFbGaNlyC8k9G1FwcVG4zX47X7PXoiVa+dszwrylrfGDx4Nb90uJRYx4KUwLOvbPPW2KajL3VAghxDGlpv96b9q0iS984Qv87//9vznvvPP4wz/8Q9auXTtjp88vX7584vGePXsm9Zre3t6JxytWrJj22vfdd9/E43e84x2T+oLiggsumAhRn3766WmvLYQQQgghxKwqj8P4LigOzljrPkDRtBnIGIwWDeIhjYg+ey3lAatE0yt3kN5xFwHHHxn2oHca/2h+mF3M57KVOutXhQg1ePXpoa37yxkLtpG3A6SjGitaYrQlQjL3VAghxDGp5j8C9TwPz/N4+OGHefjhh/nTP/1T3ve+97F+/XouuuiiSR2gNF0rV66cePzSSy9h2/Yh80hfz7PPPvu6r5+q/v7+iccHV8QeTmvrqz+Zz+Vy015bCCGEEEKIWWFVINML2T3g2hBrg2D9T5h3XRgtVenPVDBsh+ZoiOAsHR6lOBapXffSvO02gmYegK3qcv6q9GGe9lawOBXg/50ZYXlzg88MPaR1fx65yHxG7QjxYJAT2qJ0piKzPiJBCCGEmE01DVFvuukmbr75ZjZu3Iht24A/c/T222/n9ttvp6WlhSuuuIKPfOQjnHnmmbVcGoBzzjmHUChEtVqlVCrx9NNPc9ZZZ73h86vVKo8//vjExxdccMG01z74UKrx8fFJvWZsbGzicTqdnvbaQgghhBBCzCjXgcI+GNsJRhaizaDHZmRpw3IZyJYZKlQJq0Fa47N0ZoDnkuj7NS2bb0Qr+6PExkPz+f+VL+enxmmoAYU/XBXiipU62iwFvJN1cOt+Id7DoJtEJciS1igLmiNE9cYfPyCEEELUW01/lHjVVVdxzz33MDAwwNe//vWJoPRAdero6Cjf/OY3Oeecc1i+fDl///d/z86dO2u2fjwe58ILL5z4+Pvf//5hn3/nnXdSKBQAfx7qeeedN+21Fy5cOPH4oYcemtRrHnzwwYnHxx133LTXFkIIIYQQYsaUx2HgOf8/14LUghkJUD0PxssmrwwXGMxXSYd14uHZCfeiw8/R/avP0PnMV9HKQ1T1Zm6I/Amn5/6Jn1qns6w5yLfeFWP9W0INHaAqjolW3EfANSmnl7E3egKDXpqOVJS3LmxiWWdCAlQhhBBiP8XzPK+eC+zYsYObbrqJW265hVdeeeXVhQ+aGXrWWWexfv16Lr/88iM63Angnnvu4X3vex/gn2b/zDPPsGrVqtc8r1wuc9JJJ7F9+3YAPv/5z/OlL31p2uveddddfPCDH5z4+L//+79Zv379Gz7/wQcffE3g+2aHUf2+fD5PKpUil8uRTCanvGchhBBCCCEmzSz7bfvZXr+fPt4KgZkJ2CzHY1+uwr6sQTCgkIpoMAvZZCi7g5ZN3yc28hwAjhrht80f4tMD72TcDqMF4JrVIdYt1xt7buhBrftmdB5j+nzyhGmOhehpjtIaDxFo5P0LIYQQNTTZfK3uIerBnnrqKW688UZ+9KMfMTw8/Oom9geqmqbxnve8h/Xr17N27dppr3PeeefxyCOPALBo0SLuuusuTjzxxIlfHxsb48orr2Tjxo2AX4W6Y8eO122p3717N4sXL574eMOGDVx77bWveZ5t26xatYpt27YBEA6H+bd/+zc+9rGPHTIH1vM8/ud//oc/+ZM/mZiD2t3dzSuvvEIoNLVWJAlRhRBCCCFE3Tn2/tb9HVDNQ7QF9OiMLV8wbPaOl8lWLJJhjZA283M51dIgLZtvJNn3MACeotK/4CL+cvwSfjPmV+Guag3yuTPCdCcbe/bpq637TeQi3Qx7SeIRPzztTIXRgjL3VAghxLGlIUPUA1zX5Ze//CU333wzP/nJTyiVSof8eiAQmJipOh19fX2cccYZ7Nu3D/BD2vPPP5+lS5cyMjLC/fffT7lcBkBVVe67775DqkIPNtkQFeCJJ57gggsumLg3QFdXF+eccw6tra3kcjkef/xxdu/ePfHroVCI+++/nz/4gz+Y8vuUEFUIIYQQQtSN50F5DMZ3QWEQQjEIp0GZmQpFx4XhgkF/toLreqQiOoEZzvcC1RzNW28jveteFM///iQ3/3xuCV3O17Y2UXUgHITrTgpzyfEagRn63EyH4piolTE8NUQp0s2A0ooeCrMgHWF+U5SI3tjhrxBCCFEvDR2iHqxcLvOTn/yE733vexMzQhVFwXGcI7rvli1buPLKK3n++eff8DltbW1s2LCBiy+++A2fM5UQFeDJJ59k/fr1ExWph7N48WJuvPFG3va2t73pc1+PhKhCCCGEEKIuzBKM74ZcL+BBrG3GWvcByqZDf7bCSKFKXFeJhGY24FNsg/SOn9L0yu0Ebb9Aotx2Mi/1/CF/s3k+W8b871VObg/y2TMidMUbuHrzoNb9amQe+4Kd2FqCzlSY7uaoPxpBCCGEOIZNNl+b9SnhzzzzDL/+9a95/vnnURSFWmW6K1as4IknnuCHP/wht956K5s2bWJoaIh0Os2SJUu49NJL+ehHP0pra2tN1jvgjDPOYNOmTfz0pz/lJz/5CU8//TQDAwMUi0VisRgdHR2ceuqpXHLJJaxbtw5Nky9ahBBCCCFEg3AsyA/A+E4wi37rvhaZseU9D0ZLVfoyFQzToSmqo87kwUyuQ7J3Iy1bbkE1xgEwUksYXnkt3xtbxc2PVbFch6gGHz85zEVLtEPOemg0B1r37XATw/p8soEm2pJhFjbHaI3rDb13IYQQotHMSiXqyy+/zE033cStt95Kb2/vIb/meR6qqmKa5kxva86RSlQhhBBCCFETngelUcjshOIwhOIQSs1Y6z5A1XYZyJYZylfR1SCJ8AzWe3gesX2P0/ryD9CLfQBY0Q7GVl7Nc7E/4KtPVtmRdQE4c57Kn50Wpi3auNWnB7fuZ0ILGAm0kojF6GmN0ZEIocrcUyGEEGJCw1WiDgwMcOutt3LTTTfx4osvTlw/OMM9+eSTufrqq7nqqqtmaltCCCGEEEIc26oFyOyB7F4IKJDonNHWfYBM2aIvU6ZgWKQjOpo6cyFfeOxlWjdtIDK+GQBHTzK+7MOMLLyIm7a43PZYBceDhK7wp6eEuaBHbdwKzoNa94vhToaCXajRFMc1RZnfFCGsydxTIYQQYrrq+tVRoVDg9ttv5+abb+bhhx/Gdf2f3h4cnHZ3d/ORj3yEq6++mhNOOKGe2xFCCCGEEEIcYJuQ7/cPjjJLEG8FNTyjW7Bcj8Gswb58BcVTaI2HZ6z4VSvspXXTD4gPPg6AGwyRXfoBMsevZVM+xL/cb7An73//cm63yqdODdMUbtwKzgOt+6aeZkifRzXcyrymKAuaoyTDMkJMCCGEOFI1D1Ft2+bee+/lpptu4mc/+xnVahU4NDhNpVKsW7eOq6++mvPPP7/WWxBCCCGEEEK8Ec/zW/bHd/ot/OEEpBfM+DYKhk1/tsJ4qUoirM1YlWSwMkbLlltI7tmIgotHgHzPOxlbcRUlrYUfvFTlzm1lXA/SIYVPnxbm3O7GDSH91v1RnGCYofAScno7bU1JVjZHaYnJ3FMhhBCiVmoaon7iE5/gf/7nf8hkMsChwammaVx00UWsX7+e97///ei6XsulhRBCCCGEEG/GyENmN+T6IBCEZJf/vzPIcWGkaNCfrWDbHi2xMIEZKPAMWCWaXrmD9I67CDh+oUex8yxGV12DlejmhWGbf32yxEDRrz595yKNT7w1RDLUoNWnB7XuZ7UORvX5xFPNrG6J0p4IEwxIeCqEEELUUk1D1G9/+9soinJIeHrOOedw9dVXc/nll9Pc3FzL5YQQQgghhBCTYVch1w+ZXWBVINYKamjGt1ExHfqzFYYLBlFNJRmvf4Wn4likdt1L87bbCJp5fx/NKxld9VGMlhMoWx7/9XSFu7dbALRFFP7s9DBnzmvc6lO/dT9HWU0zpC8hmOzkuJYYXekIIVXmngohhBD1UPN2fs/zWLZs2cSc08WLF9d6CSGEEEIIIcRkuC6UhmFsJ5RHIZKG6MwXNlRtl9FCleFCFcO2aYqGUIN1rpT0XBJ9D9Oy+Sa08hAAZnwBoydcQ6nrLFAUntpn87WnKgyX/SKQi5dqfOykMDG9Mas4D7TuW0qIQX0J1XgXXc1JuptjxEMzexiYEEIIcayp6b+0n/rUp7j66qs5/fTTa3lbIYQQQgghxFRVsn7rfr4fghqk5oMys63ppuMyVjQZzBtUTJuYrtIar//hVdHh52jZ9H3CuR0A2OFmxlZcRX7hGggEKZge336uwi92+dWnnTGFz5we4ZTOBg0i97fuK47FSKCdQnQBLS1trGyO0hTVZO6pEEIIMQNq+lXCddddB8CLL77IqlWrCAallUQIIYQQQogZZVch0wvZ3eBUITrzrfuW65EpmQzlDApVi4im0hYPQ52zvlB2Oy2bfkBs5DkAHDVC5vh1ZJd+AE/1w9vH+iy+/rTBuOGhAB9cpvPRE0NE1MYMIg+07ucCKcZDS4g0z+OE1gRtiZDMPRVCCCFmUE1D1JNPPhlFUejp6WHnzp21vLUQQgghhBDicFwXioMwtgMqGb91P9Y6o1uwXY9M2WQob1AwLEKqX3la70JJtTRIy+YbSfY9DICnqGQXv5fx5R/GDaUAyBou33zW4Fe9NgDdiQCfPSPMW9oas/r0QOt+BZ1hdTFq0wKWtqXpTEXQ1QY97EoIIYQ4itX0KwZN07Btm7POOquWtxVCCCGEEEIcTiUD47ugsM+vOp3h1n3HhVzFZDBnkK2Y6MEgzdEwgTpvIVDN0bz1NtK77kXx/HA0v+B8xlaux451Av6ZDQ/vtfnGMwa5qkdAgctX6Kx/Swi93nNZp8NzUI0Mjm2xT2nFSvbQ1d7BguYIUb0xA18hhBDiWFDTf4U7Ozvp6+sjHo/X8rZCCCGEEEKI12NVILsXsnvAMf3K06A+Y8u7LuQMi+G8wXjZRA0EaInVPzxVbIP0jrtoeuUOgnYZgHLbyYyuupZq+riJ541VXP7f0waP9fsB6+JUgM+dGWF5c2OOHQuYBQJGnnElQTG6lKb2BSxsiZOOztzvqRBCCCFeX01D1BUrVrB371727NlTy9sKIYQQQgghDuY6UBiE8Z1+FWq0eUZb9z0P8obNcMFgvGiiAOmIjlrvyk7XIdm7kZYtt6Aa4wAYqaWMrbqWcvtbD9qfxy93WdzwnEHRAjUAV50Q4oqVOloDVp8qjkmwPErR1cmEFhFtW8TKtjSt8RABmXsqhBBCNISahqiXX345Gzdu5NFHH2VsbIyWlpZa3l4IIYQQQghRHn+1dV8LQ2oBdR86epCCYTOcNxgtmeBBMqyh1vtQJs8jtu9xWl/+AXqxDwAr2sHYyqspLDj/kNEFQyWXrz1V4elBB4BlzQH+4owIi9MNWH26v3XfNE2GAi0E2payuLODzlQYLShzT4UQQohGonie59XqZoZhcNppp7F582Yuu+wyfvjDH9bq1uJ15PN5UqkUuVyOZDI529sRQgghhBD1ZJYh2+u37rvO/tZ9bcaWL5o2I/kqo8UqtuuRDGszcsBReOxlWjdtIDK+GQBHTzK+7MPkFr8X76D373oe92y3+M8XDCo2aAG4ZnWIdcv1hjzFPmAW8Mo5xkjgpBfR3rmQ+c0xInoDhr1CCCHEUWyy+VpNK1HD4TC3334773nPe/if//kf8vk8X/va11i2bFktlxFCCCGEEOLY4dh+1en4TjDyfuu+Hp2x5Sumw0ixynChiuU4JEI6Ia3+4alW2Evrph8QH3wcADcYIrv0A2SOX4urxQ55bn/B5V+frPDiiF99uqo1yOfOCNOdbLxAUnGqBMpj5Kwg5dhS0l2LWdCWJhWZuUBcCCGEEFNX00rUv/u7vwNgdHSUG264Acfxv4g58cQTOfXUU2lrayMSiUzqXv/3//7fWm3rqCWVqEIIIYQQRzHP29+6vxOKQ35wGk7PWOu+YbmM7g9PDcshEVYJa/UPJYOVMVq23Exyz/0ouHgEyPe8k7EVV+FEDp376rgeP95m8v2XqlQdCAfhupPCXHK8RmAGRxxMiuegVjKUDIOc1k608zgWdHbSGtdRGm2vQgghxDFksvlaTUPUQCDwmi8APM+b1hcFBwJY8cYkRBVCCCGEOEqZJRjfDbm9gAuxNgjUtInsDVVtl/GSyWDeoGLaxHWNSKj+4WnAKtH0yh2kd9xFwKkCUOw8i9FV12Alul/z/D05h68+abBlzP++4a0dQT5zeoSueOPNEg2YBaxShixJgq3HMW9BDx3JMKrMPRVCCCFm3ay084Mfmk7m2uHIT2KFEEIIIcQxybGhMABjO8As+q372sy07luOx3ipylDeoFh1iGhB2uJhqPOX5opjkdp1L83bbiNo5gGoNK9kdNVHMVpOeM3zbdfjts0mN2+qYrkQ1eDjJ4e5aInWcN9HKE4VrzDKuB3ETS+jbf5S5remZqSiVwghhBC1VdMQ9W/+5m9qeTshhBBCCCGODZ4HpVHI7ITCMITikJw/I637tuuR2V95WjAsIppKazxU/6U9l0Tfw7RsvgmtPASAGV/A6AnXUOo663Xf+/aMw1efqLAj6wJw5jyVPzstTFu0wSo6PQelNE6xYmBEu0gvOp55nR0kwzL3VAghhJiratrOL2aWtPMLIYQQQhwFqkXI7IbsXggoEG2ZkdZ9x4VsxWQwZ5A3LPRgkHhIJTADeWR0+FlaNn2fcG4nAHa4mbEVV5FfuAYCr63SNB2PmzdVuW2zieNBQlf401PCXNCjNl71abWAURinFEwR7VpG1/weWuKhhtunEEIIIXyz1s4vhBBCCCGEmATHglyfP/vULEK8FdRw3Zd1XcgZFkN5g0zZRA0EaI6GZiQ8DWW307rp+0RHngfAUaNkjl9HdukleG/w3jeP2fzLEwZ78n716bndKp86NUxTuLGqTxWnipUbpujqqK0nsHDhUtrTSYIBCU+FEEKIo4GEqEIIIYQQQswkz4PSCIzthNIwhJOQXjAjy+YqFsOFKuMlk4ACTRGdYLD+IV+wmqNl0wZSvff7e1FUsovfy/jyD+OGUq/7GsP2+MFLVe7cZuJ6kA4pfPq0MOd2N1hLvOfgFscolg1IL6C9exmd7e2EVJl7KoQQQhxNJEQVQgghhBBiphh5yOyB3F6/bT0573Xb12utYNgM5Q3GiiYAqYiGOgPhKZ5Lcs8vad30fYJWEYD8gvMZW7keO9b5hi97YdjmX580GCj61afvXKTxibeGSIYaq/rUreQxCuNYkWaSx53IvPmLiMvcUyGEEOKoVNcQ1TAM7rvvPh599FH27t1LJpPBcRweeOCBQ57neR6VSgUATdPQNPnCQwghhBBCHEVsE/L9ML4TrDLE2kAN1X3ZQtVmtGAwWjRxXI9kWENTZyaI1LM7aX/hm0QyWwGoJhczfPInMZpXvuFrypbHf71gcPd2C4C2iMKfnR7mzHkN9v2BXcXIDlJVwsTmnUj3wqU0JWIy91QIIYQ4itUtRP3qV7/KV77yFcbGxiaueZ73ul9YjI+Ps3DhQgzD4Mwzz+Sxxx6r17aEEEIIIYSYOa7rt+yP7YTyKIRTkKp/637ZdBgpVBkpVLEcl2REQ5+h8FSxyrRsuZn0jrtRcHHVCGMrPkJ2yfsPW3X71D6brz1VYbjsn3t78VKNj50UJqY3UDDpOlTzI1SrJnpLD90LV9Da2ipzT4UQQohjQM1DVMuy+OAHP8h9990H+MHpm2lpaeGaa67hhhtu4IknnmD79u0cd9xxtd6aEEIIIYQQM8fI+YdG5fsgqM1I637FchgtmAwXDaqWQyKskYrOUBWn5xEf+A1tL30H1RgHoDDvDxhZ/cc4kdY3fFnB9Pj2cwa/2OVXn3bGFD5zeoRTOhtr8phVymIUMgQTbXQsWUF710J0TeaeCiGEEMeKmn9l8olPfIKf//znAITDYa655houuOACbrnlFu666643fN3VV1/NDTfcAMC9997Lpz/96VpvTQghhBBCiPqzq5Drg8wusA2Itta9db9qu4wV///s3XmUXWWd7//3OWfvMw81V+YZSEImBFRsBwS0VWwbUVFwAFFs1Iv28t5et/u31u3fvbfvau/w69vi3K0CyqQ4oi2iMqktTgwBEubMqSQ115n3vH9/7FAESCpJpYaT4vNai5VTu/az93NSxcquT32/z2PTX7Fpuh75lEmxMHMt8GZtH92PfpXcwEMAOLn5DG64mkbvmROOu3+vy7UPWIxYITHgolOTfHhDiozROpWdvmNhjR0gTGZpX34GvUtWks1kZ3taIiIiMsOmNER98MEHuf7664nFYixcuJBf/OIXrF69GoBf//rXE459zWteQ6lUolKp8Jvf/EYhqoiIiIicXIIAav0wsg0aI5Bpg2zntN7S9UOG6zYHyhYNxydrJujOp2GGMsiY79D+zPdpf/o24oFLEDcYPeU9jJ76bsLEkYPjMSvgSw9Z3LfbA2BxIc5nXplmXXfrVJ8Gvo9VHsD3PXK9K+hdspq29un9eoqIiEjrmtKnlOuvv3583dMbb7xxPEA9Vps2beJXv/oVTzzxxFROS0RERERkejVHYXQnlPuiqtPSQohN3xqkbhAyVnc4ULGoWS5p06A7n5qx8BQgO/Aw3Y98hWR9HwCN7k0MbPw4bn7hEceEYciv9nh88UGLsh0Sj8Elq5N8cF2KZKJFqk9DaFZH8ZqjpNvmsXDJGjp6FhFPzMyasiIiItKapjREvffeewFYt24db3jDG457/KJF0SL7fX19UzktEREREZHp4VowthvGdkVt/PluSCSn7XZ+AKMNh/6KRbnpkjYSdObTzOSm8InmMN1bvk6h7zcAeOkOBtd9lNrC1zHRRIaaAV98wOK3fVH16fJSnP/4qgyndbTOuqK21cAZ68fMFph3ytl0L1qBmUzP9rRERESkBUxpiLpv3z5isRhnnHHGpMbn83kA6vX6VE5LRERERGRqBT5UD8DI9qgKNdsOuSNvnnTCtwtgzHLoL1uMNRzMRILOXIr4TBZHBj5tO/6NjiduIuE1CYkztuJCRtZ8gMDMHXGYH4T8+FmHGx61aXhgxOGytSnetyaJ2SLVp57r0Sj3Y8ZCuhadSvfS08gU2md7WiIiItJCpjREtSwLiDaUmoxarQY8H6aKiIiIiLScxgiM7IDqfjDT09q6H4Yw1nQZrNqM1G0SsTjt2RSJGQ4fUyNP0fPIl0mXtwFgtZ/KwMZPYLetmnDcU8M+1z7Q5JnRAIDVnQk+c3aa5W2tUX0aBFAvD5Nwa7R39NK1dA3FroUTVtSKiIjIy9OUhqjd3d309fVx4MCBSY1/8sknx68jIiIiItJS3CaM7ora9wMP8j2QMKflVmEIVcujv2oxUnMAKGWSGDMcnsadGl2P30Bx58+JEeKbOYbWXkFl2ZshduQgtO6EXPeYxU+ecQmBvAkf2ZjmbStN4q0QUIZQa9QJa0PkC3k6V55Fx4LlxIwjb4YlIiIiL29TGqKuXr2avXv38rvf/Q7f90kkjv03zHv27GHz5s3EYjHOPvvsqZyWiIiIiMjkBX5UdTq8DawyZDshmZ2221Vtj8GKxVDdIQygmDYxjBkOHsOQwp576NpyHYZTBqCy+DyG1l2Jn2qbYFjIfbs9vvqwxYgVAnD+UpO/OiNFe7o1NmZq2g5OZYCsGadz+Wl0LjoVI1ua7WmJiIhIi5vSEPUtb3kLd911F0NDQ3zrW9/iwx/+8DGP/S//5b/g+z6xWIw///M/n8ppiYiIiIhMTn0YRndE65+aGSgtmrZW77rjMVCxGa45uEFAMW2SNGY+eExWdtH9yFfIDm8BwC4sZnDjJ2h2rZ9w3N6qzxcesHio3wdgUSHOp85Kc0bvlP7IMWmOF9CojJAJ6szrXkDX0jWk2+apdV9ERESOyZQ+0VxxxRX8wz/8A5VKhc985jOsX7+es84666jj/vt//+9861vfIhaLsWDBAt73vvdN5bRERERERI6PU4/a9kd3Rb31hV6IT08Y2HR9hqo2A1Ub2/MppE1K5vQsEzCRmGfR8dS3aX/2h8RCnyCRYuS0Sxld9ZcQP/J8HD/kO0843Pq4jRuAGYf3n57iPauTJFtg4yjfD6nUaiTtEbpLJTqXvJJC9zIwkrM9NRERETmJTOmTYEdHB//jf/wPrrnmGiqVCq973ev45Cc/yaWXXopt2+PnVSoV9u/fz29/+1u+8pWv8NBDD41/7p//+Z8xZ+GhUUREREQE34PqPhjeDnYFcp1gTk/rvu0FDNds+is2TcejkDYpZmbnOTi3//d0P/ovmM1BAGrzXsXghr/Cy/ZMOO6hAx6ff9CirxptHHXmvATXnJlhYWH2W/fDEKpNG+qDdGYMOlauoW3hKcTSxdmemoiIiJyEYmEYhlN90b/+67/m85//PLEXtcY8d6sjHf/7v/97/ut//a9TPZ05q1KpUCqVKJfLFIt6GBQRERGZtDCExjCMbIPqAKTykC5NS6u34wcM1xz6KxYNxyOXNMimZqfl3aj30/3Yv5A/8EcA3Ew3gxuupj7/VROOG2kGfPVhi3t3ewB0pGN84hVpXr/YeMmz/mxo2B52fYxSrEFn70LaF60hUehR676IiIi8xLHma9PytPa5z32ODRs28J/+039ibGwMiILT5x6oXpzbtrW18c///M9cfvnl0zEdEREREZEjs2tR2355d/Rxcd60tO67Qcho3aG/bFG1XTKmQXc+DbOR6wUu7c/+iI6nvk3ctwljCUZXvZOR095HaKSPOMwPQn66zeW6Ry3qLsRj8I5VSa5YnyKXnP2A0vECqrUqeb/M4vY2OhZvINWxBBLqdBMREZETMy2VqM+p1Wpcd9113HHHHfzud7+jWq2Ofy6VSvHKV76St7/97fzVX/2VKiknQZWoIiIiIifAd6HSByM7oiA11xltHjXFvCBktBFVnlYtl5RhkE8Zs1YUmRl6jO5HvkyqugeARuc6Bjd+Aqe4ZMJxz4z4XPtAk6dGotb9UzvifPqsDKd2JKZ9zkfj+SGVhkXKHaUzE6dz4SqyvasgVZjtqYmIiEiLO9Z8bVpD1Ber1+uUy2VyuRylUmmmbjtnKUQVERERmYQwhPogjGyP/kzlId025bfxAyg3HQ6ULcaaDslEgkLaJD5Ly4Um7DG6tlxHcc89AHjJEkPrrqS6+LwJ29zrbsgNj9n8+BmHIISsCVduSPP2lSaJ+OxWn4YhVJouoVWmy7Do6F1EccGpxPJq3RcREZFjM6vt/EeSy+XI5XIzeUsRERERkefZVRjZCeU9EE9AYX705xQKAihbLgMVi5GGgxGP05lLz1p4ShhQ2nknnY9/k4RbJyRGedlbGF57OUEyf+RhYciv93h8+SGLESuquzh3icHVZ6TpzMzyxlEh1GwP26rTTpXurnZKCzaRaF+k1n0RERGZFrOzgr2IiIiIyEzynOdb990G5LrASE3pLcIQKpbHQNVipOYQA9oySYzE7FVEpsa20fPIl0iPPg2AVVrJwMZPYHecNuG4fdWALz7U5E/7fQAW5ON86qw0Z86b/R8fLNen2rQp+mUW5k3a56/F7F6h1n0RERGZVjP6FFSr1ahWqxQKBfL5I//WW0RERERkSoQh1Aaeb91Pl6C0cMpvU7U8BioWQ3UHQiimTQxj9sLTuFun44mbaNv+U2IE+EaG4TUfpLz8wgkrbx0/5LtPOtzyuI3jgxmH961J8r61KZKzGAZDtO5puemQ9GosTTp0LFxApvdUyHWrdV9ERESm3bSGqDt27ODrX/869957L5s3b8a27fHPpVIpNm3axBvf+EY+8pGPsGLFiumcioiIiIi83FjlqHW/0hcFh8UFU966X3M8Bis2QzUbLwgppk2Sxiy2uoch+b5f073lGxjWCADVha9ncP1H8dMdEw7d3O/x+Qcs9lSjjaPO6E3wqTPTLCrO7sZRQQAVyyV0m/QmqnR1d1CYvxFKat0XERGRmTMtG0vVajX+5m/+hq997Ws8d/nD3SZ28DfGsViMj370o/yf//N/KBTUhnOstLGUiIiIyGF4NpT3wugOcK1pad1vOj6DNZuBqo3r+xRSSVLm7K4Tatb66HnkK2QHNwPg5BYwuPHjNHrOmHDcqBXwr5tt7trpAtCejnH1pjRvXGqMP6/PioPrnlquTSc1uvMmpd4VxDuXqXVfRFwq234AAL94SURBVEREpsyx5mtTHqIODg5ywQUXsGXLlsMGp0ecSCzG2rVrufvuu+np6ZnKKc1ZClFFREREDhEEUOuHkW3QGIFM25SHbZYbMHQwPLVcn0LKIJ2c3UrNmG/T/vR3aX/me8QDjyBuMnrqJYye8i7CRPKI44Iw5GfbXL7+iEXNhRjw9lUmV25Ik0/Obnu85fpULZc8DeanHNp6FmF2rVTrvoiIiEy5Y83XprSdPwxDLrroIh577LHx31qfeeaZfOhDH+Kcc85hyZIl5HI56vU6e/bs4Xe/+x033ngjf/rTnwDYunUr73znO/ntb387ldMSERERkbmuORZVnpb7oqrT0kKITV1lqO0FjNQdDlQsmq5H3jTpLkxtdetkZPsfpPvRr5Ks7weg3nMmgxuvxs3Nn3DctlGfax+weGI42jhqVXucT5+VYXXn7AbCnhcyZjmkcFlmVOlo7yDds0Gt+yIiIjLrprQS9cYbb+Tyyy8nFothmiZf/vKXufLKK4867oYbbuDqq6/GcRxisRg33HADH/zgB6dqWnOWKlFFRETkZc+1YGwPjO0E34la9yeovjzuy/shI3Wb/opFzfbJmAnyKSMq25xFieYQ3Y99jcK+qPjAS3cwuP5j1Bb82YSVmg035FtbbH74tEMQQtaAy9en+MtTkiTis/emggDKTYcw8KN1TwtJ8t3LoX2pWvdFRERkWs1KJepNN900/vpYA1SAK664gjAM+chHPjJ+HYWoIiIiInJEQQC1AzC8DZqjkG2PAtQp4gUhowcrT6uWS8Y06MqnZr+TPPBp2/5jOp+8hbjXJIzFGVvxFwyvfj+hmT3isDAM+W2fx5cftBhsRjUUr19s8PEz0nRlZ3MjLKjaHpbr02U06c24FLsWEutYodZ9ERERaSlTWok6f/58+vv7Wb58Odu2bTvu8atWrWL79u309vayf//+qZrWnKVKVBEREXlZaozAyI4oRDVSkGmfstZ9P4CxpkN/2aJsuSQTUeVpfHb3jAIgPfwEPY98iVRlJwDNjtUMbPwETmnFhOMO1AK+9JDF7/d5AMzLxbjmzDSvXDC77fFNx6dmu+QTPgvNOqW2NozOFWrdFxERkRk1K5WoY2NjxGIxXvOa10xq/DnnnMP27dsZGxubymmJiIiIyFzgNqPW/dGdELhRpeIUhW1BAGXLpb9iMdpwMOJxOrKplghP406Frq03UNr1CwB8s8DQ6VdQWfqmCcNj1w/5/lMON221sX0w4nDJ6iSXrU2RMmavwtPxAipNl2QiZFmqTlfOJNl5mlr3RUREpKVNaYja29vLnj17SKUmt8j+c+N6e3uncloiIiIicjILfKjuh+HtYI1BtgOSuSm5dBhCuekyULUZqTvEY9CeSZJItEAbeRhQ3H03XVuvJ+FUACgvuYDh0z+MnypNOPTRAY/PP2CxqxIAsLEnwTVnpllamr2No8IQxhoOYQjzUxY9KZds+3zoWBktxaDWfREREWlhUxqibty4kd27d/P4449PavwTTzxBLBZjw4YNUzktERERETlZNUZgZDtUD4CZiVq9pyhsq1oe/RWL4ZoDQCljYrRCeAokKzvpeeTLZIaj52q7uJSBjZ/A6jx9wnFlO+Brm21+vsMFoC0V42ObUlywzCQ2iyGl6wWMNR3akiELkzWKhTZiHcvVui8iIiInjSkNUS+//HJ+8pOf8Mc//pGHH36YM84445jHPvzww/z+978fv46IiIiIvIw5DRjbBWO7o177Qi/Ep+bRtWp7DFUthmoOfhBSTJuYRgv07QMxr0nnk7fStu1HxMKAIJFmePVljK18x4TvPwhDfr7d5WuP2FSdaMuDC1eaXLkhTTE1u8FwzfKwXJdFyTrzCkmSHadC+zJI5Wd1XiIiIiLHY0o3lgK46KKL+PGPf8zKlSv55S9/ybJly446ZteuXVxwwQVs27aNt7/97fz4xz+eyinNWdpYSkREROYc34ta90e2g1WGbCckj7zr/PFoOD6DVZvBmo3rBRQzJskWCU8JQ3L7f0f3Y1/DbA4CUJt/DoPrP4aX7Z5w6I4xn2sfsNg65AOwoi3Op89Ks7ZrSusljlsQwGjDJo3LolSdjs5e4t2nQL5XrfsiIiLSMmZlYymAm266iSuuuIIf/OAHbNiwgf/4H/8jH/zgB1mx4qW7hu7YsYMbb7yR//t//y/VapWLL76YG264YaqnJCIiIiKtLgyhMQwjO6LW/VRuylr3LTdgsGozULOwXZ9C2qSUaZ0WcqN+gJ5H/4Vc/58AcLO9DGy4msa8sycc1/RCbtpi8/2nHPwQ0gZcvi7FO09NkojPbkhpuwGVpk13vMr8UpJ87+lR9amZmdV5iYiIiEzWlFainnfeeeOv77//fhzHGV97qauriyVLlpDNZmk0GuzZs4fBwei37GEYkkqlOOecc44+4ViMu+++e6qmfFJTJaqIiIjMCU4dRnZCeTcQQq57Slr3bS9guGbTX7Fpuh75lEkmOXsbK71YzHdpe/YHdDz1HeKBQxgzGD3lXYyc+h5CIz3h2Pv7XL70oMVAI3qUf+0ig4+fkaYnN8uVtWG01qxv11mYqtPduxCz59Toa6rqUxEREWlBx5qvTWmIGo/HD7tg/XO3OPRzhzt2NGEYEovF8H3/BGc6NyhEFRERkZOa70JlX9S679Si1v0pqFR0/ZDhus2BskXD8cmaCXIpA1oow8sMPkLPI18hWdsLQKNrAwMbP45bWDzhuIF6wJcesri/zwOgNxvjP5yZ5tULZ7+y1vdDRutNCkGZhW0Z2uavIta5AozUbE9NRERE5IhmrZ1/okz2cJ+b4iVZRURERKTVhSHUh2B0O9QGog2GigtPuFLRDULG6g4HKhY1yyVtGnTnUy0VniasUbq2fIPi3vsA8FJtDK37CNVF5074/r0g5AdPOdy4xcbyIRGD96xOctnpKTLG7L9By/Vp1MrMSzTpXbSQ7Pw1kOua7WmJiIiITJkpDVHvvffeqbyciIiIiMw1dhVGd8HYHojHoDDvhFv3/QBGGw79FYty0yVtJOjMp1urezz0Ke34GZ2P30jCqxMSo7z8bQyv+SBBcuJd6rcMelz7gMXOcgDA+u4EnzorzbJSCyxNEMJYw8K0hlhcyNCz7AyMjuVgJGd7ZiIiIiJTakpD1De84Q1TeTkRERERmSs8Byp90cZRTh3yXXCUdT+PJghgzHLoL1uMNRzMRILOXIr4LC8L+mKp0WfoeeTLpMeeAcBqW8XAxk9it58y4biKHfD1R2x+tt0FoJiM8bFNKd683DyuJbGmi+eHVMojtMXqdC9aSseiNZDrnO1piYiIiEyLKW/nFxEREREZF4ZRy/7I9qiFP12AtkUnfMly02WgajNSt0nE4rRnUyQSsx8sHiru1Oh84kZKO+4gRohv5Bhe+yHKy98CsSNXkYZhyC92uHztEZuyHS199ZYVJldtTFFMtUZC3Gw6uLV+egpZ5i09i0y3qk9FRERkblOIKiIiIiLTw6pErfvlPRBPQHF+9OckhQd3fu+vWozUHABKmSRGi4WnhCGFvffRteUbGPYYAJVF5zK07iP46fYJh+4q+1z7gMVjg9FGqstKcT59Vpp13a3x2B6GUB0bIelVWDB/CT3L15PIdcz2tERERESm3ZQ+jf2n//SfuOqqqzjttNOm8rIiIiIicjLxHCjvhdEd4DajDYZOcIf2qu0xWLEYqjuEARTTJkYLbKj0YmZ1Dz2PfIXs0KMAOPlFDGz8OM3ujROOs7yQm7fafPdJBz+EdAI+sC7Fu05LYsRb4326jkNzdD/5XI7eU86mbf5KSJizPS0RERGRGRELwzCcqovF43FisRjnnHMOV111FZdccgmZTGaqLi8vUqlUKJVKlMtlisXibE9HREREXu6CAOoDMLwdGkOQaYNU4YQuWXc8BqsOQ1UbNwgopk2SRmu0tB8q5ll0PH0b7c/8gFjoEcSTjJz2XsZWXUx4lKDxD/tcvvigxYF69Fj+6gUG/+HMNL251nmfzcoofrNMW+9i5q9YT7qotU9FRERkbjjWfG1aQtTnFAoFLr30Uj7ykY9w1llnTdVt5CCFqCIiItIyrDKM7ITK3qg6MdsJscmHgE3XZ6hqM1C1sT2fQtokbbbAbvSHkT3wJ3oe/Spmox+Aeu9ZDGy4Gi83b8Jxg42ALz9k8e97PQC6szH+wyvSvGZR61R3Bp5Lc3Q/cTNDz7K19CxaSdxonfmJiIiInKhZCVEvv/xyvv/979NoNJ6/wcFQdf369Vx11VW8//3vp62tbapu+bKmEFVERERm3Xjr/nbwLMieWOu+7QUM12z6KzZNx4vC02RrhqdGY5Dux/6V/P7fAeBmuhhc/zHq88+B2JFb8P0g5EfPOHzzMZumB/EYvOu0JB88PUXGbI3WfQC/MUajMkqmawkLVq6n1K7qUxEREZl7ZiVEBahWq9xyyy1cd911/OlPf3r+RgcfJFOpFO9617v4yEc+wrnnnjuVt37ZUYgqIiIisyYMoT4Iw9uiP0+wdd/xA4ZrDv0Vi4bjkUsaZFOtsZnSSwQebdt+TOeTtxD3LcJYnLGVFzG8+lJCY+KlrB4f8rj2AYvtYwEAa7sSfPqsNCvaWicojvku1uh+rHiGjsVrWLR0Fcmkqk9FRERkbpq1EPVQW7Zs4etf/zo333wzw8PDz9/0YKC6YsUKPvKRj3DFFVcwb97E7U6T4TgO3/nOd7j11lvZunUr/f39tLe3s3z5ci6++GKuuOIKurq6puRe9913H2984xsnPf7666/niiuuOK4xClFFRERkVtg1GN0JY7shnoha9+OTCwHdIGS07tBftqjaLhnTIJ8yoHUKMl8gPfw4PY98iVRlFwDNjrUMbPwETmnZhOOqTsg3HrG4Y5tLCBSS8NGNad6ywiQ+QdXqjGuMUq2ViZUWsWD5Onq6u16wXJeIiIjIXNMSIepzXNflhz/8Iddddx133XUXQRD95v25B7JEIsHb3vY2PvrRj/K2t72NePzEF9F/8sknufTSS9m8efMRz+np6eH666/nbW972wnf70RD1J/97Ge85S1vOa4xClFFRERkRvkeVPdF1ad2DfJdYKQndSkvCBltRJWnVcslZUThaavmdXG7TNfW6yntvgsAP1lk6PQPU1ly/oRrv4ZhyN27XP7lYZsxO3rsftMyk49tStGWbp2No2K+i1/tp+wnyS9YzeKlKylkJ/e1FRERETmZtFSIeqg9e/Zw3XXXccMNN7Br167nJ3LwiXn+/PlcccUVXHnllaxYsWJS99i7dy+vetWr2Ldv3/i1X//617Ny5UoGBwe56667aDabAJimyZ133sl55513Qu/rmWee4dprrz3m83/xi1/wzDPPANDb28vevXsxjONrWVOIKiIiIjOmPgwj26F6AFL5qH1/EvwAyk2HA2WLctPBTCQopE2m4Hfo0yMMKO76JV1bbyDhVgEoL30zQ6dfQZCc+Plrd8XnCw9YbB7wAVhSjPOps9Js7GmhZQrCkIQ1Rr1eo5GdR/eStSye34OZaNUviIiIiMjUatkQ9VC//OUvue666/jRj36EbdvPTyoWIxaLce655/Lxj3+ciy66iETi2FvEXv/61/Ob3/wGgKVLl3L77bezcePG8c8PDQ3xvve9j7vvvhuAjo4Otm3bNmMbXvm+z6JFizhw4AAAn/nMZ/inf/qn476OQlQRERGZdm4TRnfB2C4IA8h1Qfz4Q8AggLLlMlCxGGk4GPE4xVYOT4FkeTs9j3yZzMiTANjFZQxs/CRW55oJx9leyK2P23znSQcvgGQCPnB6ineflsRMtE6pbcy3idUGGfZSGN2nsnjZSrqLE6/pKiIiIjLXHGu+Nqu/Bn/d617H/v37eeqpp9i8efN4NWoYhoRhyL333su9997LsmXL+Id/+Acuu+yyo17zjjvuGA9Qk8kkP/nJT1i/fv0Lzunq6uL2229nw4YNbN++nZGREf73//7f/OM//uPUv8nD+PnPfz4eoAJcfvnlM3JfERERkWMWBFDdH1WfNkejdU+T2eO+TBhCxfIYqFqM1BxiQFsmidFCYeKLxdwGnU/eTNv2nxALAwIjw/Dq9zO24i+Ouvbrn/Z7fOGBJvvrUZ3C2fMNrjkzzfx8C6XFYUjCHsVuNhk259G2ZDUrFnaTTbZQhayIiIhIi5mVStQHHniAb3zjG3z729+mUqmMHw/DkGQyyWtf+1r++Mc/UqvVnp9oLMYll1zCLbfcMuHi9hdeeCF33HEHAFdddRX/+q//esRzb775Zj7wgQ8AUTVqf3//cbfUT8Z73/tebrvtNgDOOOMMHnrooUldR5WoIiIiMi2aYzC6Ayr7wEhBpoPJLFZatTwGqxaDNQdCKKZNDKN1w1PCkPy+39L12NcwrWhT1OqCP2No/VV4mYk3Ix1qBnz1IYtf7fEA6MzE+OQr0rx2kdFSGzPFPItEc5gRL4NdWs7CJctZ1JEnEW+dOYqIiIjMpJZr5x8dHeXGG2/kG9/4Blu2bAGi0PQ5p5xyCldddRVXXHEFXV1dNBoNvv3tb/PFL35xfHOoWCzG5z73Oa655prD3qNWq9HV1TW+NMD999/POeecc8Q5WZZFd3f3eFh79913n/DaqEczNjbG/PnzsSwLgM997nN8+tOfntS1FKKKiIjIlPJsKO+Nqk89G/LdkEge92VqjsdgxWaoZuMFIcW0SdJooUrMwzDr++l+5KvkBh4EwMnOY3Djx2n0njnhOD8I+fGzDjc8atPwIB6Di05Jcvn6FFmzhYLJMCRhjeC7Dv3xHtK9q1ixoIeO3PF/fUVERETmkpZp5//lL3/JN77xDW6//XYcxwGeD09TqRQXX3wxH/vYx3jDG97wgnHZbJYrr7ySK6+8ki984QvjQeN11113xBD1/vvvHw9Qc7kcZ5999oRzS6fTnHPOOfzyl78E4J577pn2EPW2224bD1BN0zymJQpEREREplUYQm0AhrdBYyjaNCo3ceXl4TQdn8GazWDVxvF9CqkkKbO1w9OY79L+zPdof/o24oFLEDcYPeU9jJ76bsJEasKxTw37XPtAk2dGAwBWd8T59NkZVrUf+1r+MyHmWZjNYcqxAiPZFfQsWMKK7gJps7XmKSIiItLKpiVE3b17N9dffz033HADu3fvBl5Ydbp69WquuuoqLr/8cjo6Oo56vWuuuYbbbruN3/72tzz99NNHPO+JJ54Yf71+/fpjas1/xSteMR6iHjp+unzzm98cf/22t72N7u7uab+niIiIyBHZVRjZCeU90XqfpYUQO77g0w9gsGaxf8yi6foUUgbFjDk9851CmYHN9DzyZZL1fQA0ujcxsPHjuPmFE46rOyHXPWbxk2dcQiBnwkc2pnnbCrO12uLDAMMaIfQ99iUW4LUt45QF3cwvpom30jxFRERETgJTGqJ+5zvf4brrruPuu+8eD02f+zOdTvPud7+bj33sY7z2ta897mtv2LCB3/72t+NVnIfz1FNPjb9eunTpMV13yZIl46+ffPLJ457X8XjmmWe4//77xz/WhlIiIiIya3wPKntheAe49ajy1Ji48vJw6o7HvjGLoZpNxkjQXTj+a8y0RHOY7i3foND3awC8dAeD6z5KbeHrJlz7NQxD7t3t8S8PW4xY0TPu+UtN/uqMFO3p1qq4jXlNjOYITaPE/vQiSl0LWNtTpJRt/XBbREREpBVNaYh66aWXEovFXlB1evrpp3PVVVfxoQ99iLa2tklfO5k8+npNw8PD4697e3uP6brz5s0bfz0yMnL8EzsO3/rWt8Zfd3Z2cuGFF07r/UREREQOqz4EI9uiFv5UPqo+PU5BAMN1m72jTSzXpy2bxEi0eHVj6FPa/lM6n7iRhNckJM7YigsZWfMBAjM34dC9VZ8vPGDxUL8PwKJCnGvOTPOKeS22o30YYDSHIQwZTC6hkl3E4u52lnXlWn5dWhEREZFWNuVPfWEYkslkuOSSS/jYxz424cZOx+Oyyy5j06ZNE57z3AZRAJlM5piue+h5h46famEYctNNN41/fNlllx1TMHwo27bH13yFaOFbERERkWPmNGBsF4zuAkIozIP48T8ONl2f/WNN+qs2aSNB10lQfZoafYqezV8mXd4GgNV+KgMbP4HdtmrCcY4f8p0nHG593MYNwIzDZWtTXLImSbLFQuOY28CwxnBS7fQlFmIWezi9p0BvMUVsggpbERERETm6KQ1RN2zYwFVXXcUHPvABSqXSVF6as88++6gbRR3a6n+sAWUq9fxDf7PZnNzkjsGvfvUrdu7cOf7xZFr5P/vZz/Lf/tt/m8JZiYiIyMtC4EN1f7RxlFWGXCeY2eO+TBjCSMOhb7RB1fboyKQwjNYO5+JOjc7Hv0lp553ECPHNHENrr6Cy7M0Qm3hjpYcOeHz+QYu+arRx1JnzElxzZoaFhRar6Az9qPqUOOX8cvrjvfS0F1nZk6eQVvu+iIiIyFSY0hB18+bNU3m545ZOp8dfO45zTGMOrew81urVyTh0Q6l169Zx5plnHvc1/u7v/o7PfOYz4x9XKhUWL148JfMTERGROao5CsPboxDVzEBp0YTrfh6J7QXsG2vSX7ExE3F68mlo5fw0DCnsuZeurddh2GMAVBafx9C6K/FTbRMOHWkGfPVhi3t3ewB0pGN8/BVp3rDYaLmKzrhbJ2GN4WW66DcW0kx1sLIzx5LOLGaixcJeERERkZNYiy3idGLy+fz462OtKj30vEPHT6VGo8H3v//98Y8nu6FUKpV6QeWsiIiIyBF5NozuhrGd4DuQ74HE5KoSRxsue0cbVC2XUibZ8mtrJiu76X7ky2SHtwBgFxYzuPETNLvWTzjOD0J+us3lukct6i7EY/COVUmuWJ8il2yt8JTgYPVpPE69tIq9dFPK5dnQk6OnkD76eBERERE5LnMqRO3s7Bx/3d/ff0xjDhw4MP66o6NjyucE8IMf/IBqtQpAIpHg/e9//7TcR0RERIQggPoADD8LjRHItkOua1KXcv2QA+Um+8oW8ViMrnx6MkWsMybmWXQ89W3an/0hsdAnSKQYOe19jK66COITB8jPjPhc+0CTp0ai1v1T2uN8+uwMp3VM3PI/G+JOjYRTwct0M5pewnCYZ2FbhpU9ObLJOfV4LyIiItIyJvWUdd555031PF4gFotx9913H/e40047bfz1rl27jmnM7t27x1+vXr36uO95LA5t5X/zm9/M/Pnzp+U+IiIi8jJnVWBkB1T2RlWnpYUQm1zVaKXpsXe0wVjTpZA2SJutFyYeKrf/D3Q/+i+YzQEAavNeyeD6v8LL9U44ru6G3PCYzY+fcQhCyJpw5YY0b19pkoi3WGIc+BjNQYibNNtOY3+si3giyZruHIvas603XxEREZE5ZFIh6n333Tdt60GFYTjpa69Zs2b89WOPPYbneRjGxG/xoYceOuz4qbJ3717uueee8Y+vuOKKKb+HiIiIvMz5LpT3RgGq24gqT43JLQHkBiGDFYt9YxZ+ENKZSxFv4e59ozFA96P/Qv7AHwBwM90Mbria+vxXTTguDEN+vcfjyw9ZjFghAOcuMbj6jDSdmdZ7w3GnSsKu4uV6qeaW0u+m6cgmWdVToCN3bBuqioiIiMjkTbrfJwzDqZzHlHjNa15DKpXCtm3q9ToPPPAAr371q494vm3b/P73vx//eDoqbG+66SaCIGoLa2tr4x3veMeU30NERERepsIQ6kMwsg1qA5AuRtWnk1S1PfaNNhmu2+RTJplkC1efBi7tz95Ox1O3EvdtwliC0VXvZOS09xEaE68Juq8a8MWHmvxpvw/AgnyMa87McNb8FmyFDzzM5hBhIonVsYYho4eGB0s6M6zoyrd8hbCIiIjIXDGpJ8X/9//9f4/pvDvuuIM//elPxGIx/v7v/34ytzou+Xye888/nzvuuAOAG264YcIQ9dC1Sjs6Onj9618/5XM6tJX/ve99L+m0FvoXERGRKeDUYWQnlHdDLAbFBRCfXKDmBzBYs+gba+J6AZ25dEtXn2aGHqP7ka+QqkbLMjU61zG48eM4xaUTjnP8kO8+6XDL4zaOD2Yc3rcmyfvWpkgmWq8VPu5UMJwaTnYeVmEZ/W4aMxZj7YI8C0oZ4mrfFxEREZkxsXAaS0qvueYavvSlLxGLxfB9f7pu8wI//elPefvb3w5Eu9k/+OCDnH766S85r9FosHHjRp599lkA/vZv/5bPfvazUzqXP/7xj7zqVc+3kv3ud7+bMNQ9XpVKhVKpRLlcplgsTtl1RUREpIUFPlT2wfA2cKqQ7QQzM+nLNRyfvrEmQzWbjJEgl27BasyDEvYYXVuuo7gnWirJS5YYWncl1cXncbQdrzb3e3z+AYs91ahD6IzeBJ86M82iYgtWcgYuZmOI0MhgF5dRTfUy3PTpLqRY1V2glJ14kywREREROXbHmq+1cI3B5Fx44YW87nWvA6J2/be//e08+uijLzhneHiYiy66aDxA7ejo4D//5/982Ovt3LmTWCw2/t8NN9xwzHM5tAr11FNPndIAVURERF6GGiOwbzPsfwQIoLhw0gFqEMBg1eapA1WGqjZtmWTrBqhhQHHHz1h619UU99xDSIzysrew64KvUl1y/oQB6qgV8L9+3+Rv7m2wpxrQlorxd6/O8L/OzbZkgJqwy5j1QdzcfBo9mxgw5jFmh6zoyrNuYUkBqoiIiMgsadEn5RNzyy238MpXvpL9+/ezc+dONm3axBve8AZWrlzJ4OAgd911F41GAwDDMLjttttoa2ub0jk4jsO3v/3t8Y8vv/zyKb2+iIiIvIy4FozthtGdEHhQ6IX45B/jmq7P/rEm/VWbtJGgqzC5TahmQmpsGz2PfIn06NMAWKUVDGz8JHbHaROOC8KQn21z+fojFjUXYsDbV5lcuSFNPtl6bfAx38VoDhIYWazu9TRTPQw0PHJJWL+wRG8xNW0bu4qIiIjI0c3JEHXRokXcc889XHrppWzevJkwDLnvvvu47777XnBed3c3119/Peeff/6Uz+Hf/u3fGBkZASAej/OhD31oyu8hIiIic1wQQK0fhp+F5ihkOyCZm/TlwhBGGg59ow1qtk97JolhtGYwF3cbdDxxI23bf0qMAN/IMLzmg5SXX3jUtV+3jfpc+4DFE8PRclIr2+L89dkZVne2XuUpYUjCKRN3m7j5RTjFZdRIM1p3mFdMs7InTyGt6lMRERGR2TYnQ1SA1atX84c//IFvf/vb3HrrrWzdupX+/n7a2tpYsWIFF198MR/+8Ifp6uqalvsf2sp/3nnnsWjRomm5j4iIiMxRVvngxlF7wEhBaSHEJr8Sk+0F7Btr0l+xMRNxuvOpqDyz1YQh+b7f0L3l6xhW9Avp6sLXMbjuo/iZzgmHNtyQb22x+eHTDkEIGQOuWJ/iL09JkmjBTZhivoPRHCIw81hd63GyvYw0PLzQ45SeAks6s5iJObf6loiIiMhJac6GqADJZJIPfehDJ1QFumzZMiaz99btt98+6XuKiIjIy5jnQKUPRraD14RcVxSinoDRhsve0QZVy6WUSZI0WjOYM2t9dD/6VXIDDwPg5BYwuPHjNHrOmHBcGIb8ts/jyw9aDDaj57bXLTb4xBlpurIt+F7DkIQ9RtyzourT0nLseIaBikVbJsmKnhw9hfRsz1JEREREDjGnQ1QRERGRk0YYQn0QhrdFf6ZL0cZRJ8D1Qw6Um+yvWMTCGF359NE2sZ8VMd+h/env0v7M94gHLkHcZPTUSxg95V2EieSEY/fXAr70kMUf9nkAzMvFuObMNK9c0Jot8DHfxmgMEyQLNLs34mV7qNkB5brNgrYMq3ryZJN6RBcRERFpNXpCExEREZltdi3aNGpsD8TjUFxw1HU/j6bS9Ng72mCs6VJIG6TNFlwPFMj2P0j3o18lWd8PQL3nFQxuuBo3v2DCca4f8v2nHG7aamP7YMThktVJLl2bIt2K67yGIQl7lLhv4xSX4BSX4RsZhmo28RismV9gUXu2JZcdEBERERGFqCIiIiKzx/egui+qPrVrkO8C48TauL0gZKBisW/Mwg9COnMp4i3Y0Z5oDtH92Ncp7Pt3ALx0B4PrP0ZtwZ9xtHLZRwc8Pv+Axa5KAMCG7gSfOivN0lJrBsUxz8JsDuOlSjTbV+Nle3H8kMGxJh35JCu783TmT2zJBhERERGZXgpRRURERGZDYyQKT6sHIJU/uHHUiVUhVm2PfaNNhus2+ZRJJtmCoWLg07b93+h88ibiXpMwFmdsxV8wvPr9hGZ2wqFlO+Brm21+vsMFoC0V42ObUlywzCTWiusUhAEJa4RY4GOXluMUlxIaGcpNl4bjsaQzy4rufMtWCYuIiIjI8xSiioiIiMwktwmju2BsFwQBFOdB/MQeyfwABmsWfWNNXC+gM5duyerT9MgT9Gz+MqnKDgCaHasZ2PgJnNKKCccFYcjPt7t87RGbqhNtHHXhSpMrN6QpplowPAViXhOzOYKXasPuXImX6cYPYahiYRox1i4osqCUIa72fREREZGTwqSe2P/7f//vx3TeH//4x+Me85y///u/P67zRURERFpaEEDtQFR92hyFbCckJ668PBYNx6dvrMlQzSZjJCi2YFt43KnStfUGSrt+DoBvFhg6/QoqS98EsYnT3h1jPtc+YLF1yAdgeSnOp89Oc3pXi9YChAFGcxjCALu0Eqe4hNBIY7k+w3Wb7kKKVd0FStnW3PhKRERERA4vFoZheLyD4vH4tLdM+b4/rdefCyqVCqVSiXK5TLFYnO3piIiIyJE0x2B0B1T2gZGCTMcJt+4HAQzXbfaONrFcn7ZsEiPRYlWNYUhh9910bb0Ow6kAUF5yAcOnfxg/VZpwaNMLuWmLzfefcvBDSBvwoXUp3nlqEqNFqzdjbgPDGsVPd+KUluNluiAWY7ThYHs+SztyLO3KkjLUvi8iIiLSKo41X5v0r/Ankb0es5Zc00pERETkeHkOlPdEAapnQ64LEskTvqzlBuwba9BftUkbCboKrVd9mqzspOeRL5MZfhwAu7CEgU2fxOo8/ahj7+9z+dKDFgON6HnzzxYZfOKMND25FlyjACD0o+pTYthtK3GLSwkTKfwgpL/SJJdMsG5hiXnFtJ5zRURERE5SkwpRX//61+sBUERERORIwhBqAzCyHeqDkGmL2ven4LIjDYd9o02qtkd7JolhtNYzWcxr0vHkrbRvu51Y6BMkUgyvvoyxlX951LVfB+oBX3rI4v4+D4DebIxPnpnmnIWt2/oedxskrDH8dAd220r8TPR1bjgeow2HecU0K3vyFNKt+x5ERERE5OgmFaLed999UzwNERERkTnCrsHIDqjsjdb7LC6A+Im3b9tewP6yRX/ZIhGP0Z1PQSvlp2FIbv/v6H7sa5jNQQBq889hcP1VeNmeCYd6QcgPnnK4cYuN5UMiBu9eneT9p6fItFhIPC70MRpDEEtgt5+CW1hMmEgShiEjdQcvDFnVk2dpZw4z0aIVtCIiIiJyzFp0RX4RERGRk4zvQaUPhreDU4N8d7T+6RQYbbj0jTWoNF1KmSRJo7VCOaMxQPcjXyHf/ycA3Gwvgxv+ivq8Vx517JZBj2sfsNhZDgBY15XgU2elWd7WuuuGxp0aCaeMl+nBKS3HT3cA4PoBgzWLYtpkbU+e7nxK3VsiIiIic4RCVBEREZETVR+GkW1Q7Yd0HtoWTcllXT/kQLnJ/opFLIzRlU+f6H5UUysMKO24g67Hv0ncaxLGDEZPuZiRUy8hNNITDq3YAV9/xOZn210AiskYV21K8eblJvGWepOHCHyM5hDEDez21bj5hYQH17it2R7lpsuCtgwru/PkUnrMFhEREZlL9HQnIiIiMlluE0Z3wuguIIDivKOu+3msKk2PvrEGow2XQtogbbZWZaZZ3UPvw18gMxJtHNXsWEv/GdfgFhZPOC4MQ36xw+Vrj9iU7WjjqLcsN/nophSlVGtV2B4q7tRI2GW83Dyc4nL8dBsAQRgyVLOJx2D1vDyLO3Ik4i0aAouIiIjIpClEFRERETlegQ/VAzC8Dawy5DrAzE7Jpb0gZKBisW/MIghDOnMp4q2ULQYu7c98n46nvk088AiMDENrr6C8/K3RGrAT2FX2ufYBi8cGfQCWleJ8+qw067pb+JE08DCbQ4SJJFbHWtzCAohHm0Q5XsBg1aI9l2RVT57O/NQs3yAiIiIiraeFn1hFREREWlBzNFr3tLofzDSUFjJVPfZV22PfaJPhuk0+ZZJJtlb1aWr0KXof/gKpyk4A6r1nMbDxE0fdOMryQm7eavPdJx38EFIJ+OC6FO86LYnRwlWbcaeCYVdxc/OwS8sJUm3jn6s0XWq2y5LOLCu68y1XKSwiIiIiU0shqoiIiMix8GwY3Q1jO8F3IN8DCXNKLu0HMFiz6Btr4ngBHdkUiUTrhIsxz6LziRtp2/YTYgR4ySJD6z9GddEbjhog/2GfyxcftDhQj1r3X73A4JOvSDMv30rltS8SuJiNYUIjRbNzLW5+4fgyDX4Qte+biRinLyyxoJQh3sJBsIiIiIhMDYWoIiIiIhMJQ6j1R637jWHItEGua8ou33B8+saaDNVsMkaCrhZrCc8MbKZ38xcwG/0AVBady+D6qwhSpQnHDTYCvvyQxb/v9QDozsT45JlpXrPQaOkd6+N2mYTbwM324rStIEgWxz9nuT7DdZuufIpVPXnasslZnKmIiIiIzCSFqCIiIiJHYldhZCeU90DCONi6PzUVlEEAww2bvaNNLMenLZvEaKHq07hTo2vL1yntvgsAN9PNwKZP0ug9a8JxfhDyo2ccvvmYTdODeAzedVqSD56eImO2zvt7sZjvYjQHCYwsVufpuLn5EH++RX+04WB7Piu68iztypIy1L4vIiIi8nKiEFVERETkxXwXynthZAe4jajy1Ji6ClHLDdg31qC/apMyEnQVWqj6NAzJ7/st3Y9+FcMeIyRGecXbGVrzQcKjbJ71+JDHtQ9YbB8LAFjbmeDTZ6dZ0dbagWPCHiPuNnFzC3BKywmShfHP+UHIQNUim0ywbmGJecV0S1fSioiIiMj0UIgqIiIi8pwwjFr2R7ZBtR/Sxaj6dAovP9pw6BttUrU92jNJDKN1ArlEc5ieR79Cfv/vAbALixnY9CmszjUTjhtuBty4xeaObS4hUEjCRzemecsKk3gLB44x38FoDkfVp13rcLPzXlB92nA8RhsO84ppVvTkKaanZg1cERERETn5KEQVERERAXAaMLoTxnZFHxfnj28mNBVsL+BA2eJA2SIRj9GdT0Gr5IthQHHXL+jach0Jr0EYSzBy6nsYPfW9hBNsnjVqBXznCYefPOvg+NGxNy0zuWpTivZ0C28cFYZR9aln4eYX4hSXESTzh3w6ZKTu4AUhq3ryLO3MYSZa+P2IiIiIyLRTiCoiIiIvb4EP1f3RxlFWOWrdNzNTeovRhkvfWINK06WUSZI0WieQM2v76Nn8BbJDjwFgtZ9K/6ZP4ZSWHXFMxQ747pMOP3rGwYr2jWJtZ4IrN6bY2NPaj5cx346qT80Cze4NeNneF6xz6/oBgzWLYtpkbXee7kJK7fsiIiIiohBVREREXsYaI9G6p9V9YGahtAimMDBz/ZAD5Sb7KxaxMEZXPj2Vlz8xgU/7th/S8cQtxAOHIJFieM2HGFv5dogdfg3TmhPy/adsfvCUQ+NgeHpqR5zL16U4e77R2mFjGJKwR4n7Nk5hMU5x+UvWeK3ZHuWmw4K2DCu78+RSelQWERERkYieDEVEROTlx7VgbA+M7Yw2kcr3wgRt65NRaXr0jTUYbbgU0gZps3U2V0qObaf34WtJl7cBUO8+g4FNn8TLzTvs+Q035IdPO3zvSZuaGx1b0RaFp+csbPHwFIh5FkZzhCBZpNm1Gi/b84Lq0yAMGa45xGIhq+cVWNSexVD7voiIiIgcQiGqiIiIvHwEAdT6o42jGiOQbY/a96eQF4QMVCz2jVkEYUhnLkW8RfK4mG/T8eSttD/7A2JhgG/mGVx/FdXF5x22AtfyQn78jMN3nnCoOCEAS4pxPrQuxesWGy29aRQQVZ9aI8QCF6e4FKe0jNB44VINjhcwWLVoyyU5pSdPZz41S5MVERERkVamEFVEREReHqxK1Lpf2QuJJJQWvqAacSpUbY99o01GGjY50ySTap3q08zQY/Q8/AWS9X0AVBe8lsENf4Wfbn/JuY4f8m/POnz7CYdRKwpPFxbifPD0FOcuMUjEWzw8Jao+NZvDeKk27M61eJmelwTFlaZLzXZZ0pllRXe+paqFRURERKS1KEQVERGRuc13obwXRraD24wqT42prTb0AxiqWfSNWdieT3smRSLRGkFj3K3TtfV6SjvvBMBLdzCw8RPU57/6Jee6fsid211uedxmqBmFp/NyMd5/eoo3LTNPivCUMMCwRiDwsUvLcYrLCI30C07xg5Chmo2ZiHH6whILShniJ8N7ExEREZFZoxBVRERE5qYwhPpQ1LpfG4R0Mao+nWINx6dvrMlg1SJjGnS1UDt4bv8f6HnkS1GoCJSXvYWh0z9MYOZecJ4XhPxyh8vNW236G1F42p2JcdnpKf58uYnZIoHw0cS8JkZzBD/djlNagZfpfkn1qeX6DNdtuvIpVvXkacsmZ2m2IiIiInIyUYgqIiIic49Th5GdMLYb4jEozof41LZqBwEMN2z2jjZpOh7t2RRGi4SNCWuU7sf+lULfbwBwcgsYOOMaml3rX3CeH4Tcs8vlpq02+2pReNqRjnHp2hRvW2mSbJH3c1RhgNEchjDEbluJW1jykupTgNGGg+35LOvMsbw7R8pQ+76IiIiIHBuFqCIiIjJ3BD5U9sHwNnCqkO0EM3P0ccfJcgP2jTXor9qkjATdhZcGdrMiDCnsuYfux75Gwq0RxuKMrrqYkdWXEiaer5ANwpBf7/H41mM2e6oBAG2pGO9dk+Ttq5KkjZMkPAXiboOENYaf7sBuW4Gf7nxJ9akfhAxULTLJBOsWlphXTBNr9U2xRERERKSlKEQVERGRuaExEq17Wj0AySwUFx52x/kTEYZRNWPfaJOq7dGWMTGNqd2carKM+gF6Nn+J3ODDAFillQyc8SnstpXj54RhyG/7ovB0RzkKTwtJuGR1ir88JUnGPImCxdCPqk+JY7evwi0sfkFQ/JyG4zHacJhXTLOiJ08xbc78XEVERETkpKcQVURERE5urhW17Y/ujCpRC70Qn/pHHNsLOFC2OFC2SMRjdOdT0AqZY+jTtu0ndD5xI3HfJognGVl9GaOr3jm+hEEYhvxhn8c3t9g8OxqFp1kT3n1aiotPS5I7mcJTos2yEtYYfrYbu7gcP9P5knPCMGSk7uAFIat68iztzGEmWiPwFhEREZGTj0JUEREROTkFAdQORK37zVHIdkAyd/RxkzDacOkba1BpupQySZItUn2arOyk5+EvkBl9CoBG13oGNv0H3Hy0gVYYhjx4wOebW2yeHPYByBjwzlOTvHt1ikLy5ApPCQ5Wn8bj2O2nHqw+fenGUK4fMFizKKRM1vbk6S6k1L4vIiIiIidEIaqIiIicfKxy1Lpf7gMzDaWFEJv6YNP1Qw6Um+yvWMTCGF359FSvEDApMd+l/enb6Hj6u8RCD9/IMrTuSipL3zz+9/DIgMc3H7N5bDAKT1MJ+MtTklyyJkkp1Roh8PGIOzUSTgUv041TWoGfbj/seTXbo9x0WNCWYWV3nlxKj7siIiIicuL0VCkiIiInD8+B8l4Y3Q6eBfluOEwl4lSoND36xhqM1B2KGZO02Ro7uaeHn6Bn8+dJVfcAUJv/agY2fHy8pX3rUBSePtwfhadmHN6+Ksn71iTpyJx84WlUfToIcRO7fTVOYSHEX7quaRCGDNccYrGQ1fMKLGrPYqh9X0RERESmiEJUERERaX1hCPXBqHW/PgiZNsi+dB3MqeAFIQMVi31jFn4Q0pVPE2+BLC7mNuh6/FuUdvyUGCFeqo3BDVdTW/BnEIvx1IjPNx+z+NP+KDw14vDWFSaXrk3RnW2BNzAJcadKwq7i5XqxS8sJUm2HPc/xAgZrNm1Zk1N68nTmX7rBlIiIiIjIiVCIKiIiIq3NrkWbRo3tjjZKKi4Y3zBpqtUcj32jFsN1i5xpksm2RvVptv8BejZ/CbM5CEBlyQUMrvsIQbLAttFozdPf9XkAxGPw5uUm71+bYl7+5AxPCTzMxiChkcLqWINbWHjEzcIqTZea7bKkI8vyrjyZZGt8zURERERkblGIKiIiIq3J96C6L6o+tWuQ7wIjPT23CmCoZtE3ZmF7Pu2ZFInE7C9+GrfLdD/2dYp77wXAzfbSv+kamj2b2FX2+eafGvxmz/Ph6XlLTT5weoqFhZM0PAXiTgXDqeFk5+GUlhOkSoc9zw9Chmo2ZiLG2gUlFrZliMdn/2smIiIiInOTQlQRERFpPfXhaOOo6gFI5aFt0bTdquH49I01GaxaZEyDrlZoBQ9D8n2/pvvRf8FwKoTEGVv5DobXfIA9DZMbf9fg3l0e4cHTz11i8IHTUywtncRVmIGL2RgiNDI0O9bi5hccsfrUcn2G6zZd+RSrevK0ZadnXVwRERERkecoRBUREZHW4TZhdBeM7YIwgOK8IwZpJyoIYLhhs3e0ieV6tGdTGC1QfWo0Bul55Mvk+v8EgF1cRv8Z17DTPIWbHrS5a2ed4GB6+meLDC5fl2J520kcngIJu0zcqePmF+CUlhEki0c8d6zhYHk+yzpzLO/OkTJO7vcuIiIiIicHhagiIiIy+4IAqvuj6tPmaLRpVDI7bbez3IB9Yw36qzYpI0FXLg2znZ+GAaUdd9D1+DeJe02CuMHIae/j6QXv5OYnA+7cXsM/GJ6+akEUnp7ScXIHiDHfxWgOEhhZrO71uNl5R1zv1g9CBqoWmWSCdQtLzCumicVm+4smIiIiIi8XClFFRERkdjXHYHQHVPaBkYLSIpimcCwMYbTh0DfapGp7tGVMTGP21w81q3voffgLZEYeB6DZsYan1vwHrt/dwx0/s3GD6LxX9Ca4fH2KtV0n+SNcGJKwx4h7Fm5+EU5xGUEyf8TTG47HaMOht5hmZU+eYtqcwcmKiIiIiChEFRERkdni2VDeG1WfejbkuyExfWtb2l7AgbLFgbJFIh6jO5+a/erTwKP9me/T8dStxAOPwMiw+5QP8cX6+fz4Pg/HdwHY0J3givUp1vec/I9uMd/BaA4RmHmsrvW4uXkQO3yQHYYhI3UHLwhZ1ZNnaWcOMzH7obeIiIiIvPyc/E/iIiIicnIJQ6gNwPA2aAxBpg1yXdN6y9GGS99Yg0rTpZRJkmyB6tPU6DP0PnwtqcpOAMrdZ/Hl9Ef45mMlLM8DYG1nVHl6Rm/i5G9df3H1aWk5gZk74umuHzBQtSikTdb25OkupE7+vwMREREROWkpRBUREZGZY1dhZCeU90RrX5YWHrEKcSq4fsiBssX+ShNC6Mqnp2ulgGMW8yw6n7yZtmdvJ0aAmyzyw7YP81/3vZKGF03u1I44l69LcfZ8Y04EhzHfxmgMEyQLNLs34mV7Jvy6122PsuWwoC3Dyu48uZQeWUVERERkdumJVERERKaf70FlLwzvALceVZ4aqWm9ZdXy2DvaYLThUEibpM3Z34QpM7iZ3oe/gNnoB+DRwuv55Nhl7KlEu9GvaIvC03MWzo3wlDAkYY0QDxyc4hKc4jJC88gbhoVhyFDNgVjIab0FFrVnMdS+LyIiIiItQCGqiIiITK/6EIxsi1r4U/mo+nQaeUHIYNWmb6yJ74d05tLEZzmHizs1urZ8ndLuuwAoG138P+6V/HRwEwBLinE+tC7F6xYbxOdCeEpUcWs2h/FSJZoda/CyvRNuGOZ4AYM1m7asyaqePF356Q3ZRURERESOh0JUERERmR5OA8Z2weguIITCPIhP76NHzfHYN2oxXLfImSaZzOxXn+b7fkv3o1/BsMcIifEd3sQ/1N5LnQwLC3E+eHqKc5cYJOJzIzwlDEhYI8QCD7u0PKo+NdITDqk0Xaq2y5KOLMu78mSSs/91ExERERE5lEJUERERmVqBD9X90cZRVhlynTBBC/dU8AMYqln0jVnYnk97JkUiMbuhZKI5TM+jXyW//3cA7GAB/9H+GA+FpzIvF+Pq01O8aZk5d8JTIOY1MZsjeKk27M6VeJnuCatPgzBkqGaTiMc4fUGRhW1Z4nPo70NERERE5g6FqCIiIjJ1mqMwvD0KUc0MlBZNGKJNyS0dn71jTYaqFmnTmP028DCkuOsXdG25joRXxyPBl7x38CXvIkqZJJ8+PcWfLzcxZznknVKhj9EcgTDELq3EKS45avWp5foM1Wy6CilWdedpzyVnaLIiIiIiIsdPIaqIiIicOM+G0d0wthN8B/I9kDCn9ZZBAMMNm72jTSzXoy2bwpjlYNKs7aN78xfJDT0KwOZgBf/Z/RiDqaVctSHF21aaJOdSeEq03mvCruCnO3BKy/EyXUcNzscaDk3XZ3lXjmVduZbY9EtEREREZCIKUUVERGTyggDqAzD8LDRGINsOua5pv63lBuwrN+iv2KSMBF25NMxmNhn4tD37Q9qfuAUjdGiGSf4/7xJ+YLyV92xM8xerkqSNuRWeEngYzSGIm9gdp+LmFxEmJq4m9YOQgapFJplg3cIS80tpYnNkIy0RERERmdsUooqIiMjkWBUY2QGVvVHVaWkhxOLTesswhNGGQ99Yk2rTpS2bxDSm955HkxzbRu6P19LV2A7Ab/x1/GPsI5xz+hK+eUqSjDn3QsKEXSbh1nGzvdil5QSptqOOaTo+w3WbeaU0K3vyFNPTW6ksIiIiIjKVFKKKiIjI8fFdKO+NAlS3EVWeGtO/DqntBRwoWxwoWyTiMboLs1x96tnYD97Civ0/JEHAWJjjf4cfwDj1TXz2tBS55NwLT2O+g9EcJjAyNDvX4ebmQXzix8kwDBltuLh+wCk9eZZ05kjOcvAtIiIiInK8FKKKiIjIsQlDqA/ByDaoDUC6GFWfzoCxhkvfWJNy06GUSc5qCBeGIXueeZTTnvgip4T7AfhZ8CoeWvZR3nX6PIqpuReeEoYkrBHigYObX4hTXEaQzB91mOsHDFZt8mmDNfNLdBdSat8XERERkZOSQlQRERE5OqcOIzuhvDvaNKi4AOLTvxmQ64dR9WmlSRhCVz59tD2LptXWfWWSD9/A29xfAtAftvOz3qs4/RWv5ZL03KyujHlNzOYIXqqNZscavGzPMS3bULc9ypbDvFKGVT15cik9doqIiIjIyUtPsyIiInJkngO1fhjeBk4Vsp1gZmbk1lXLY+9og9GGQyFtzuoO7o8PeWx96Ld8uP4N5sdGALg//yaSr/wwf1Ysztq8plXoYzSHgRh2aSVOcQmhkT76sDBkqOZALOTUngKLO7IYibkZMIuIiIjIy4dCVBEREXkpqxK17pf3RK9TOSguZCbKQL0gZLBq0zfWxPdDOnNp4rOUwT014vOjR/q5aOQ6/p/E7yEGA8Y8BjZdQ/eijbMzqRkQd2oknDJ+phu7uBw/03lM41w/YKBq05Y1WdWTpys//WvlioiIiIjMBIWoIiIiEvE9aAxD9QDUB8BtQqoAxfkz0roPUHM89o1aDNctcqZJJjM71afbx3y++ajFvAP38n/Mm2hP1PCJs2/pO7E3XEYqMUfDwcDFbAwRGins9jU4hYUQN486zPUDKk0X2/NZ1J5lZXeeTHL2KodFRERERKaaQlQREZGXO7sGjSEo74XmGMTjkG6DXNeMTcEPYKhm0TdmYXs+7ZkUicTML366q+zzrS022/fu5x+Nr/P65GMAVAsrGD3zU9htq2Z8TjMiDEk4ZeJOAzc3D6e0nCBVmnBIEIbUbY+q5ZFIxGjPmpxaKtBbTJOIa/MoEREREZlbFKKKiIi8HAU+NEejqtPaAXAakMxBoRfiM/t40HR8+saaDFYt0qYxKy3ge6s+N21xuG+XzYcSP+crydvIxWz8eJLR1ZcxuuqiGf97mSkx38ZoDhOYeazu9bjZeRNWHtueT6Xp4fgB+bTByp4cXfkUxbRJXOGpiIiIiMxRc/OnARERETk8p3Gw6rQvClEJIV2KNoyaYUEAww2bvaNNLNejLZvCmOHq0/21gJu32vxyp8sq9vC95Nc4I/4sAI3OdQyccQ1ufuGMzmnGhAEJa4RY4OEUluAWlxKYucOe6gchNdujbnuYRozOfIreYpr2nEnKUNu+iIiIiMx9ClFFRETmuiAAawxq/VA5AE4VklnId89adaXlBuwvN+iv2CQTCbpyaZjB/HSgHnDL4zZ3bndJhC6fNm7nk8btGPj4RpahdVdSWfpmiM3NXeXjboOENYqfbscuLcfL9Bx20zDL9ak0XbwgoJA2ObU3T0c+RTFtEJuBTcZERERERFqFQlQREZG5yrWijaIqe6E+AviQKkJp0WEDs5kQhjDadOgbbVJturRlk5jGzAWVw82Abz/u8NNtDm4Ar4g9zeeyX2dJsBeA2rxXM7DxavzMzK0HO6MCH6M5BLEEdvspuPlFhEb6Baf4QUjFcmk4HmkjQXcxxbximrZskuQMfq1ERERERFqJQlQREZG5JAwPVp0OQmVfVHWaSEKuI/pzFjl+wP4xiwNli0Q8Rndh5qpPx6yA7zzh8ONnHRwfslj8U+G7/IV7J7EgxEu1MbjhamoL/mzWAubpFneqJOwKXrYHp7QcP93xgs83nGiTqCAMKWZMlnYW6cglKaTNWZqxiIiIiEjrUIgqIiIyF3jOwarTfVAfhMCDVAGKC1qiJX2s4dI31qTcdCimk6TMmZlTxQ757pM2P3rGwfKiYx8sPcbfhl8n5wxG5yy5gMF1HyFIFmZkTjMt5rsYzSFCI43VuRY3vwDiUTDq+gFVy6Pp+mTMOAva0nQX0rRnTYzE7H/fiIiIiIi0CoWoIiIiJzOrDPUhKO8FuwoJAzJtYMz8DveH4wYhB8YsDlSahCF05dMzUuhZd0K+/5TN9592aLjRsTPbavx/uZtZPvyraG7ZXgY2/QcaPWdM/4RmQxiSsMeIexZubj5OaRlBskgYhtRtj6rlEo/FKGVNVnTn6MglyaX0aCgiIiIicjh6UhYRETnZ+F5UdVrdH1Wdehak8lCYB/HW2Sm9annsHW0w2nAopE3S5vTPremG/PBph+89ZVN1omMrSjH+64I/8Zq+b2AMlwmJMbbyHQyv+eBL1gOdK2Kehdkcxk8WaXZvwMv24gZQqdnYnk82ZbC0M0t3IU0pY5KIz80lDEREREREpopCVBERkZOFXYtC0/JesCvR2p3pNsi11iZIXhAyWLXpG2vi+yGduTTxae4Mt7yQnzzr8J0nHMp2CMCSYpyPn1rlLwb/lfyOPwFgF5fSv+lT2B2nTe+EZksYYDSHIQywS8uxCkuo+SbVsk0iEaM9a3JqqUBHLjkjobaIiIiIyFwxp0NUx3H4zne+w6233srWrVvp7++nvb2d5cuXc/HFF3PFFVfQ1TW9P3g+9NBD3Hbbbdx111309fUxMjJCZ2cn8+bNY9OmTbzxjW/kTW96E/PmzZvWeYiIyEkq8KExArV+qB0ApwHJHOR7IN56/4zXHI99oxZDNYt80iSTmd6gzvFDfrrN4duPO4xYUXi6IB/nQ6ebXBTcRfcTN5DwmgRxg9FT38vIqe8eXw90rom7dRJWGT/dQTW/hJGwDacekk/Dyp4cXfkUxbRJXFWnIiIiIiLHLRaGYTjbk5gOTz75JJdeeimbN28+4jk9PT1cf/31vO1tb5vy+w8MDPCZz3yGm2+++ajnfvKTn+SLX/zicd+jUqlQKpUol8sUi8XJTFNERFqV04DGEJT7oDkaHUuXIJmd3XkdQRDAYM2ib8zC9nzaM0kSiekL61w/5M4dLrdstRlqRo8y83Ix3n96igs7DzD/0S+SGX4cgGbHGgY2XYNTXDJt85lVgYfRHCLAYDS1kGGzFzOVpjOXoreYpj1nkjJUdSoiIiIicjjHmq+1XgnLFNi7dy/nn38++/btAyAWi/H617+elStXMjg4yF133UWz2WRgYICLLrqIO++8k/POO2/K7r97927OPfdcduzYMX7stNNOY/369XR2dtJoNNi2bRubN2+m0WhM2X1FROQkFwRgjUH1QPSfWwczA/nulqw6fU7T8ekbazJYtUibBl356dvUyg9CfrnT5eatNgfqUXjanYlx2ekp/nxpjJ7tP6DjV7cSDzwCI8PQ2g9RXn4hxObmTvNxu0zQrDIY76SWX0y62M0ppTSd+RTFtEFsJnbxEhERERF5GWjdn8hOwGWXXTYeoC5dupTbb7+djRs3jn9+aGiI973vfdx99924rst73vMetm3bRltb2wnfu1wu88Y3vnE8QH3jG9/I5z73OTZs2PCScx3H4Z577qFarZ7wfUVE5CTmWlHVaaUP6iOAD6kiZBYyI1vZT1IYwnDdYe9og6br0ZZNYUxT9akfhNy72+XGLQ77agEAHekYl65N8baVJoXKs/T+5lpSlZ0A1HvPZGDjJ/GyPdMyn9kWug5O5QDNMIXfdhrZniUsa8vTlk2SNOZmYCwiIiIiMpvmXDv/HXfcwYUXXghAMpnkgQceYP369S85r16vs2HDBrZv3w7A3/3d3/GP//iPJ3z/q666iq9//esAvPe97+Xmm28mkZieFjq184uInMTCMKo6rQ1G4alTAyMVtewnkrM9u6OyvYB9Yw36KzbJRIJC2oBpyE+DMOQ3ezy+ucVmTyUKT0upGO9dk+QvViXJYNP55M20PXs7MQL8ZJHB9VdRXXRuSwfQk2U5Hm51CHwbo30xbYtW097eQSE9N9d5FRERERGZbsear825EPXCCy/kjjvuAKJA81//9V+PeO7NN9/MBz7wAQA6Ojro7+/HMCZfnLt582bOOOMMABYvXszWrVspFAqTvt7RKEQVETkJec7BqtP9UB+EwINUIfrvJAj9whBGmw59o02qTZe2bBJzGiofwzDk/j6Pb22x2T4WhaeFJLxndYqLTkmSMWNkBh+h5+EvkGwcAKCy6A0Mrf8Yfqo05fOZTb4fUnd8XKtG3hsj195FccEaSj2LTui5RUREREREXqZrotZqNe6+++7xjz/84Q9PeP673vUurr76amq1GiMjI/z6178+obVRv/rVr46//uQnPzmtAaqIiJxEwhDsCtSHoLwX7CokTMi0RdWnJwnHD9g/ZnGgbJGIx+gupKe8+jQMQ/643+Obj9k8MxqFp1kT3n1aiotPTZJLxog7Nboevo7Srl8A4Ga6Gdj4CRrzzp7aycymEJquT93xiIUB7ZTpKJjk5p1BtndltFauiIiIiIjMmDkVot5///3Ytg1ALpfj7LMn/mEqnU5zzjnn8Mtf/hKAe+65Z9Ihqu/73HrrreMfv+td75rUdUREZA7xXWiMQHVf1Lbv25DKQ3H+SbfR0VjDpW+sSbnpUEwnSZlTO/8wDHmo3+ebj9k8MewDkDbgnacmefdpKYqpKK3N9/2W7ke/imGPRvNafiFDay8nNLNTOp/Z4vkhddvD9X3SpsHCjEd7vEG2fRGJrlWQ6zopKpZFREREROaaORWiPvHEE+Ov169ff0wtbq94xSvGQ9RDxx+vLVu2UKlUACiVSqxcuRLP87jxxhu56aab2Lp1K6Ojo3R1dbFhwwbe8Y53cOWVV5JKnTwVSCIicozs6iFVp5Uo9Eq3gdk92zM7LuHBasjhmsOBSpMwhK58esozvEcHPG54zOaxwSg8TSXgHackuWR1krZ0FNYmrBF6HvkK+f2/A8DJL6L/jE9hda6d2snMgjCEpuPRcHzi8RjFtEFXxqQYjJFKpaFjI5QWg9H6a+WKiIiIiMxVcypEfeqpp8ZfL1269JjGLFmyZPz1k08+Oel7/+lPfxp/vXjxYvbu3cu73/1u/vjHP77gvH379rFv3z7uvPNO/uf//J9873vfO2rFrIiInAQC/2DV6QGo94PbhGQO8j0QP3n+uQ1DsFyfqu0x1nCpWC6O51NImaSTU7tR4uNDUdv+Q/1ReGrG4cJVSS5dk6QjEx+fUHHXL+jach0Jr04YSzByyrsZPe29hCfBBlwTcb2Auu3jBgGZZIJF7RnaMia5oE7cq0LbAuhcAZn22Z6qiIiIiMjL3snzU90xGB4eHn/d29t7TGPmzZs3/npkZGTS996zZ88LPn7rW9/K1q1bAVi9ejVnn302iUSCRx99lIceegiA3bt3c+655/LrX/+aM888c9L3FhGRWeQ0oo2ixvaCNQrEIF2CbOdsz+y4NB2fmu0xejA4df0AIx4nm0xQykztzu9Pj0Rt+3/c7wFgxOEtK0wuW5uiO/v8MgFmbR89m79IduhRAKy2U+g/41M4peVTOp+ZFATQcDyaroeZiFPKJunIJSlmDJKhC7X+aMmH+RuhuADiUxtci4iIiIjI5MypELVWq42/zmSObcOFQ887dPzxGhsbG3+9ZcsWALLZLDfccAPvec97XnDuvffeyyWXXMLQ0BCNRoP3vve9PP744ySTE1fU2LY9vuYrML58gIiIzLAggOZoVHVa6wenBsnsSVd1+uLg1PF8zHiCbGrqg1OA7WNReHp/XxSexmPw5mUm7z89xbz8IWusBj5t226n88mbifs2QSLF8JoPMLbyHRA7OUNFxwuoWx5+GJBNGizpyFHKmuSTBjGCqIrZd6F9GXQsj4JUERERERFpGSfPT3rHwLKs8ddHCySfc+iapM1mc9L3rtfrLzl200038c53vvMlx9/4xjfy4x//mNe+9rUEQcC2bdu4+eab+fCHPzzhPT772c/y3/7bf5v0HEVE5AS5VlR1WumD+ggQQLoImUUnzWY/hwanVcvFPhicZqah4vQ5u8o+N26x+dWeKDyNAectNfnguhQLCy/coCo5tp3ezZ8nPfYsAI3ujfRvugYvN+/Fl215h1adJhMJ2vNJOnNJCmkTM3Hw+8VpQGM4atmftx7yvSfN95KIiIiIyMvJnApR0+n0+GvHcY5pzKGVncdavXq0ewOcc845hw1QD/38xRdfzPe+9z0AvvOd7xw1RP27v/s7PvOZz4x/XKlUWLx48aTnLCIixyAMo6rT+sHw1K6CmYZcB5wka3I23YPBaT0KTh3PxzgYnBanKTgF2Fv1uWmLw727XYIwOvaGxQYfXJdiaemFFaUx36HjqVtpf+b7xMIA38wxtO6jVJZccNKFipbr07B9AkLyKYPlpTzFjEEuechjV+BBfTCqrO06NapANdNHvKaIiIiIiMyuORWi5vPPt74da1XpoecdOv5E7g1MGKAees5zIer9999/1PNTqdQLKmdFRGQaec7BqtN9UYAaeJAqQOnkqDqdreAU4EAt4KatNr/c+Xx4+mcLDT60PsWKtpe246eHttC7+Qska30AVBf8GYMbrsZPnzwbKvl+SN3xcTyfpBGnu5CkPZeikDYw4i/6frEqYJWh0AsdqyB3cq2fKyIiIiLycjSnQtTOzud/COnv7z+mMQcOHBh/3dHRMSX3Bli7du1Rx6xZs2b8dbVapVqtUigUJj0HERE5QWEIdiUKTct7o7DLSEKmDYzW/yXWc8HpWMOl0oyC00Q8HgWnaTPqo59Gg42AWx63+dk2F/9gePrK+QaXr09xasdLw9O426Bz6/W07fwZAF66g4ENH6e+4JzpnehUCaO/87rjESNGPp1gYXuOUtokkzzM2q2+G1WfGumodb+0CBLTG2iLiIiIiMjUmFMh6mmnnTb+eteuXcc0Zvfu3eOvV69ePel7v3jssVS1vjgwVYgqIjJLfDdal7K6H2qD4NvRxj6lBRCLH338LLLcgKrtRsHpwYrTRGzmglOA4WbAtx93+Ok2BzeIjr2iN8Hl61Os7Tr8o0buwB/pfuTLmM0hAMpL/5yh0z9MkGz9DZU8P6Rue7i+T9o0mF9K055NkU8ZJA737fLckhBuE0oLoWMFpEszPm8REREREZm8ORWiHlrZ+dhjj+F5HoYx8Vt86KGHDjv+eK1bt+4FH9dqtaOOqVarL/i4VNIPVCIiM8quPl91aleiwDRdArN7tmc2IcsNDm4O5bw0OE3NTHAKMGYFfOcJh58862D70bH13QmuWJ9iQ8/h//1N2GN0P/qvFPp+DYCTm8/Apmtodm+YmUlPUhhC0/FoOD7xeIxi2qArn6WYMUkZEwTtnhV9j6WKsGATFOZD/DBVqiIiIiIi0tLmVIj6mte8hlQqhW3b1Ot1HnjgAV796lcf8Xzbtvn9738//vF555036XsvX76c5cuXs2PHDgAef/xxLrzwwgnHPPHEE+OvOzo6yOVyk76/iIgco8CHxghUD0DtQFQdmMpHu6K3cLh12OCUOJnUzAanABU75LtP2vzoGQfLi46t6YzC0zN6E8QOt2ZsGFLYcw/dj32dhFsljMUZXfVORlZfRpho3aUSXC+gbvu4QUAmmWBRe4a2bJJc0iA+UZFyGEThaRhA+3LoWA5J/TsvIiIiInKymlMhaj6f5/zzz+eOO+4A4IYbbpgwRP3BD34wXg3a0dHB61//+hO6/8UXX8w//dM/AfCjH/2Iv/mbv5nw/B/96Efjr0/03iIichRO/WDVaR9Yo0AsqjrNdc32zI7oueB0rOFQsTxsz5u14BSg7oR8/ymb7z/t0HCjY6e0x7l8fYpXzjcOH54CRr2fnke+RG4g6v6wSisYOONT2G2rZmrqxyUIoOF4NF0PMxGnlE3SkUtSzBgkD9uv/yJOPQrqs13QuRLyPSfFZmQiIiIiInJksTAMw9mexFT66U9/ytvf/nYg2s3+wQcf5PTTT3/JeY1Gg40bN/Lss88C8Ld/+7d89rOfPaF7b9u2jTVr1uC60U+Wt99+O+94xzsOe+4f//hHXvOa1+D7Uf/jj370I/7yL//yuO5XqVQolUqUy2WKxeIJzV1EZE4KgmgtyuoBqPWDU4NkNgpP4635e0TbO1hxWn8uOPVJECOTSpA2EjMenAI03ZAfPu3wvadsqk50bEVbnA+tS/GahUcOTwl92rb/G52P30jctwjiJiOrL2N01Ttb8u/f8QLqlocfBmSTBp35FKWsST5pHFsGGnhQG4oqmtuXQfvSk2JDMhERERGRl7NjzdfmXIgKUVXnb37zGwCWLVvG7bffzoYNz6+1Njw8zKWXXsovf/lLIKpC3bZtG21tbS+51s6dO1m+fPn4x9dffz1XXHHFEe/913/911x77bUA5HI5vvWtb3HxxRe/4Jxf/epXvOc972FwcBCAV7/61dx///1H/iH0CBSiiogcgduMNooq740qAsMAMiUwcy1ZEfhccDpWdyhbHpbrY8RmNzgFGLUCfr7d5XtPOZTt6HFhSTEKT1+32CA+wd9lsrKLnoc/T2b0KQAanesYOOMa3PzCGZn7sTq06jSZSFDKmnTmkhTSJmbiOP7irXK0xm5+XlR9mu2YvkmLiIiIiMiUOdZ8rfXKQKbALbfcwitf+Ur279/Pzp072bRpE294wxtYuXIlg4OD3HXXXTQaDQAMw+C22247bIA6Gf/rf/0vHnroIX7zm99Qr9d517vexZo1azj77LNJJBI8+uijPPjgg+Pnz58/n9tuu+24A1QREXmR53ZArw1AdX8UaJnpqF0/Yc727F7icMFpIhYjm0xQyKdmLTj1g5AHD3j8bLvL7/o8/IO/al2Qj8LTc5cYJOJHnlzMd2l/+jY6nv4usdDDN7IMnf5hKsv+PNq4q0VYrk/D9gkIyacMlpfyFDMGueRxPhr5DtQGwczCvPVQXASJOfl4JSIiIiLysjYnn/IXLVrEPffcw6WXXsrmzZsJw5D77ruP++677wXndXd3c/3113P++edP2b1TqRQ/+clP+PjHP86tt94KRBtIHbqJ1HNe9apX8d3vfpfFixdP2f1FRF52PPtg1WkfNIaijaPSRSgtarmq0+eC03LDodz0sDyfOLMfnALsrwX8fLvDL3a4DDafb1JZ3RHn7auSXLDMnDA8BUiPPEnPw58nVd0NQG3eqxjY+HH8TGusO+v7IXXHx/F8kkac7kKS9lyKQtrAOMp7e4kwhOYIuBaUFkcbR6XVFSIiIiIiMlfNyRAVYPXq1fzhD3/g29/+Nrfeeitbt26lv7+ftrY2VqxYwcUXX8yHP/xhurqm/ge7UqnELbfcwtVXX823vvUt/v3f/52+vj5836e3t5dXv/rVXHLJJVx00UWqQBURmYwwjNqn60NQ6QOrAkYSMu0ttwal7QXUbY+xpkO58cLgtCs3u8Gp44f8+16PO7c7PNzvjx8vJGNcsMzkrStMlrcljnqdmNek8/Fv0bb934gR4qXaGNzwV9QWvHb2g+wQmq5P3fGIESOfTrCwPUcpbZJJHv29HZbbjL730m2wcG3Uwh9vnSpbERERERGZenNyTdSXC62JKiIvO74bVZ1W90ct1L4NqTykii3VKn644DRGjFwyQdqcvTVOn7Nt1OfO7S5373LGN4qKAWf0JnjbyiTnLDRIHuN6oNn+B+nZ/CXM5gAAlcXnM7j+IwTJ2f13yfND6raH6/ukTIP2rEl7NlrrNDHZb5XAj77/wgDalkabRyWzUzltERERERGZYS/rNVFFRGSOsatR5V95b1SBGk9Apg2M7tme2bgXB6dN1yMei5NNJujMpWa9ILPuhNyz2+XO7Q5PjwTjx7uzMd6y3OTPVyTpzR17uhh3KnQ/9jWKe+4FwM32MrDpkzR6XjHlcz9WYQhNx6Ph+MTjMYppg658lkLaJG2eYMhuV6E5Brlu6FwVrbU7219UERERERGZMQpRRUSkNfletOZk9QDU+qMW6lQeCvOiELUFOP7za5yONTws1yN2MDjtyqdnPWMLw5DHBqOq01/vcbEPduwbcThnocFbVyR5RW/iqGudvuii5Pt+Tfej/4rhlAmJMbbyHQyv+QChkZmeN3IUrhdQt33cICCTTLCoPUNbNkkuaZx4l33gRVXPCRN61kLbkmjpCBEREREReVlRiCoiIq3FqR+sOu0DaxSIQ6YYVf61gOeDU5exhot1sOI0k0zQ2QLBKcBIM+AXO13u3O7SV32+6nRZKc5bVpicv9SkLX386aLRHKJ785fI9/8JALuwhP4zPo3dcdqUzf1YBQE0nKji10zEKWWTdOSSFDMGyUn3679IcwzsGhQXQOeKaM1dERERERF5WVKIKiIisy8IoDl6sOr0QBSkJrOQ74H47P9TdcTg1Gyd4NQPQv643+Nn213+sM8jOLjiecaAc5eYvGWFyZrOxOQ2NAwDSjvvpHPr9SS8JmHMYOS09zJy6rshbk7tGzkKxwuoWx5+GJBNGizpyFHKmuSTxtR9HTw7CvKTOViwEYoLW6b6WUREREREZsfs/2QqIiIvX8/tcl7pg8ZItGFPphRV/M1yMvmC4LTpYrk+cWItFZwC7K36/Hy7yy92uIxYz+8VubYrwVtXmLxhsUnGnPxkzeoeejd/kczwVgCaHasZ2PQpnOKSE577sTq06jSZSNCeT9KZizaJMo9xA6xjEobRxlG+E20c1bEMUoWpu76IiIiIiJy0FKKKiMjMCsOo6rQ2AJX94NTATEft+omZrWp8MdcPo+C06TDaeFFw2gKbQz3H9kJ+s9flZ9tcHh30x4+3pWJcsCyqOl1amnzlZMyzyO//HcXdd5EZfJQYIUEizdDayymveBvEZqYq03J9GrZPQEg+ZbC8lKeYMcglp+HxxW1AfTgK8HvXQb6XE19QVURERERE5gqFqCIiMjM8O6ryK/dBYwgCH9JFKC2c1arTwwWnMSBrGi0VnAI8M+Lzs+0O9+xyqbvRsXgMzpxn8NYVJq9eYEy+MjMMSQ9vpbj7bgr7/p241xz/VG3eKxnccDVetmcK3sXEfD+k7vg4nk/SiNNdSNKeS1FIGxjHswHWsQp8qA8CMeg6FdqXgjk7G2SJiIiIiEjrUogqIiLTJwzBKke7m1f3gVWJdjbPtIORmrVpPRecVpouow2H5sHgNGMm6MimWqoAseqE3L3T5c7tDtvGnt8kal4uxp8vT/Lm5SY9uclP2Kj3U9xzD4Xdd5NsHBg/7mTnUV1yPpXF5+Hlek/oPRxVCE3Xp+54xIiRTydY2J6jlDbJJKex6tWuRptH5Xugc1XLbF4mIiIiIiKtRyGqiIhMPd+Nqk4r+6IqP8+BdAFKCyA2OwnlyRScBmHIIwM+d253+M0eD/dgdmrG4c8WGbx1RZJNvQnikyyTjXlN8vvup7j7brJDjz5/XyNDdcFrqSw5H6vz9GmvEPb8kLrt4fo+KdNgXjFNezZa6zQxnV8P342WkzDTUet+2+JZX0pCRERERERam0JUERGZOlbl+Y2irHK0o3mmDYz0rEzHDUJqlkfVchmpt3ZwCjDUCPj5Dpefb3fYX39+k6gVbXHessLk/KUmxdQkJx0GZA626+f7/p24b0WHidHs3kBlyQXU5p9DOM1fqzCEpuPRcHzi8RjFtEFXPkshbZI2p/kLEoZgjYHTgMJ86FwZfX+KiIiIiIgchUJUERE5Mb4HzZFok6j6ALhNSOWhMC8KUWfY4YJTgIzRmsGpF4T8fp/Hndtd/rTfIziYnWZNeOMSk7euTHJqe5zYJKtCjfoBirvvprjnHsxG//hxJzefypILqC5+44ysdep6AXXbxw0CMskEi9oztGWT5JLGzHxNPDtaViJVgAWbohB1Fr4/RURERETk5KQQVUREJsepR1Wn5T3RupKxBGSKs7Ku5KHB6ejB4DSkdYNTgD0Vnzu3u/xih8uY/XzV6fruBG9dYfK6xSZpY5Lt+m6Dwr7fUth9N9nhLePHfSNLbeHrqCy5AKtj9bS36wcBNByPputhJuKUskk6ckkKaYOUMUNflDCIlpbwPehYHv2XzM3MvUVEREREZM5QiCoiIscu8KE5CtUDUOuP2qKTGSj0Qnxm/0lxg5D6iypOnwtO21s0OG16Ib/e7fKz7S5bh/zx4+3pGG9ebvKW5SaLipOsjgwDMkOPUdx9F/l99xP37egwMRo9m6gsuYD6/FcTJqZ/Qy/HC6hbHn4YkE0aLOnIUcqa5JPGdOe2L5pIHRojkO2Aeasg3zvtwbGIiIiIiMxNClFFROTo3ObBqtO+qHWfENKlKJyayWmchMFpGIY8NRLws20O9+12aXjR8XgMXjnf4K0rTF65wMCITy7cM2v7KOy5h+LuuzGbg+PHnfwiKkvOo7r4PLzM9FcHH1p1mkwkaM8n6cxFm0SZiRkOLgMv+n6NxaF7NbQtiTaREhERERERmSSFqCIicnhBEG3CUxuI1jt1qmBmonb9GdzJ3HtBq75Lw/UIgXQLB6cAFTvgrp1R1enOcjB+fEE+xltWJHnTcpOuzOQmH3cb5Pv+neKeu8gMPz5+3Ddy1BYdbNdvP21Gqi4t16dh+wSE5FMGy0t5ihmDXHKWHjGsMtjVqOq0c9WMB/0iIiIiIjI3KUQVEZEX8uyoiq+yDxpDUQt/ugilRTPWCu0FIXXbp9J0DganPiFhywenQRjy0AGfO7c73N/n4R7MTpMJeN0ik7euMFnfkyA+mb/H0CczeLBdf//vDmnXj9PoOYPKkvOpz3/VjLTr+35Iw/GxPZ+kEae7kKQ9l6KQnnxF7YlPyoH6IBhZ6F0HpcWQ0GOOiIiIiIhMDf10ISIiEIZRBV9tECp9USWfkYRMOxjTH8rBocGpy1jDoe4cGpwmWzY4BRioB/x8h8vPtzv0N57fJOqU9jhvWZHkvKUm+eRk2/X7KO6+m8KeezCbQ+PH7cJiqkvOp7LojfiZzhN+D0cVQtP1qTseMWLk0wkWtOcopU0yyVnc5T4MoyUmPBuKC6FjRbTUhIiIiIiIyBRSiCoi8nLmuy+sOvUcSBegtCBaT3KaHTY4DUPSZusHp44f8rs+jzu3Ozx4IFqbFSBvwnnLTN66Ismq9smFi3G3Tr7vNxR3301m5Inx476Zo7roXCpLzsduO2VGKoM9P6Ruezi+T9o0mFdM056N1jpNzPbX57m1etMlmL8GCvNp6W8aERERERE5aSlEFRF5ufHsaNfy5lhUdWqVIZ6ATBsY07/5zguC06YTrad5MDhty5gkZnoTouO0s+xz53aXu3a6lO3nq0439SR4y4okr11kkDIm166fHdhMcc895Pb9jnjgRIeJ0+h9BZUlF1Cf90rCRHKq3soRPbdJlOV5xGNximmDpfkshbRJ2myBkDLwoTEcTbRjJXQsh2R2tmclIiIiIiJzmEJUEZG5zm1GoaldhcYI2JXoWOhDMg+FeVGIOo38AOp2tDnUSMMZ34gobSQonQTBacMNuW+3y53bXZ4Y9sePd2ZivHm5yVuWJ1lQmFy4aFb3HGzXvxfTGh4/bheWUFlyAdXF5+KnZ2ZzpEM3icqaCRa15WjLmuSSRusUeDo1aIxCrhs6V0Z/ztBavSIiIiIi8vKlEFVEZC4JwygwdepR2FQfjF67zehzRjKq2Et1Q3x6/wk4fHAakDaMkyI4DcOQx4d97tzmct8eF8uLjidi8OoFBm9daXLWPIPEJDZSijs1Cn2/prD7bjKjT40f980C1UVvoLL0AuzSyhlu1w9IGXE680k68kkKKROzlb5GgRet2ZswoXsNtC+ZsfV6RUREREREFKKKiJzMAj8KS506WJWoxdltgGdFAZyRBiMTterPwBqnJ3twCjBqBdy1M6o63V0Jxo8vKsR56wqTNy03aU9P4u8y8MkOPkxx993k9v+eeOACEMbi1HvPorLkAhq9ZxMmzKl6K0cUhtCwPZquTzwWo5A2WJzPUJztTaKOxBoDqwbF+dHGUdmZqcwVERERERF5jkJUEZGTie8+H5o2x6Jdyd0m+A7EEmCmIZWHbOeMtTj7B9fPrDRP3uDUD0IePOBx53aX+/s8/INLnaYT8PolJm9dYXJ6V4LYJP5Ok5XdFPbcTXHPvRjWyPhxu7gsatdf9Ab8dPtUvZUJ2W5A3fYIwoBM0mBRe4a2bLK12vUP5dlRNbWZh/kboLgQEnp0ERERERGRmaefREREWplrPd+a3xiJNoFym1FrcyIB5sEq0xnYbOhQzwWnVctluB4Fp34YkDENihkT4yQITgH21wJ+vsPhF9tdBpvPbxJ1Wkect65Icu5Sk5w5mXb9KoW9v6a4+y7SY8+MH/eSRaqL3kB1yQXYpRUz1q7fcHxszyNpJOjIJ+nMJSmkW6xd/1BhePAXBBaUlkDnCkgVZntWIiIiIiLyMqYQVUSkVYRh1Irv1MGuRa35dg28RvS5hBmFpvmuaV/P9HCOFJymT7Lg1PFD/n2vx53bHR7uf36TqEIyxgXLoqrT5W2TaGkPfLIDD1HcfRe5A38gHkSLqIaxBPXes6ksOZ/6vLMgPjPt+k3Ho+H6xImRTxssbM9TTJtkW7Fd/1BuA+rDkGmHnrWQn0drlsmKiIiIiMjLiUJUEZHZEgTgHtwEyqpCYyj62LMPbgKVikLTdC/EZyf4CgKoO8+vcVq3fYIgJGUmTqrgFGD7mM/Ptrncvcuh6jx//BW9Cd66MslrFhokJ/F+kpWdFHffTWHPvRj22Phxq7SC6pLzqS46Fz9VmoJ3cHSOF1C3PHxC0maChW0Z2jJJ8qkWbdc/VOBH/w+EIXSdAu3Lou9/ERERERGRFqAQVURkpvjeIZtAlQ9uAtWMQtNYLFrP1MxApmPG1jM9nOeC05rtMVy3Xxicpk+u4LTuhNyz2+XO7Q5Pjzy/SVR3NsafLzf58+VJ5uWPP12M2+WoXX/P3aTHnh0/7iVLVBefS2XJ+TilFVPyHo7GP9iub/keyXiC9nySjlySQtogmWj15PQguxqt8Zvvgc5VM7qmr4iIiIiIyLFQiCoiMl0852Bo+v+3d+dxcpV1vse/Z62qrurqNSvZwRBUcJtAWGQLAuLGwKAkbgSvO16d61V0hkHgiswF54oIOnpRoqPg4Og1oixCEEFZBJUBMYEhISQhe7rTW21nu3+c6urudKeXpLfqfN6vV7/61Klzqp5T6YTDt3+/5+ksLwLVWp7P1CsvApWSktm44nSCDRScBmFczVhtwWkURXp2d6B7N3p6eIunYrlj3zalE4+w9dZFrt44w5JljvCaQl/pnX9UdvNapXf8QUbU3a5vq2vm8XG7/ow3jctUC1EkFUqBujxfpgylk5ZmV0u7fm+BFy8cZbnSjNdKdXMke3zn9wUAAACA4SBEBYDR4uUHXgQqCuL5TO2UVNMYb08CvYPTlq6SOot+HJza1RecSlJLPtSvN3m6b6OnrR09Vafzs6bOXeTorAWO6pMjr8x02zaW2/Ufkl1qq+wv1B+l9rnL1THnVIXj2a5f9OWHkVLldv26crt+tRSdSiqnwPukUk6qnSU1HRkvkAYAAAAAkxQhKgAcjCgqB6bdoemeeBEoLx8/X1kEatqELAK1vyiSSkGooheqGAQqlAK1F3x1lXz5QfUGp0EY6Q/bfd270dPj23yFUbw/aUunz4sXiTqmyZIxwtZwq9im2q0PqXbzWiXbNlb2+4l6dcw9Q+1zl6tUt2AUr+TAgiBSzgtU8Hw5lqn6mp52/YRdTclpmV+UOndLiYw063VSdvaEzfkLAAAAAMM18f9nDwDVIAx6AtNCe3k+01x5PlNJdjKuNE3VS8bEBltBKBX9QEU/VNEPlC8F6iz6KgWhPD9SpEiGDLmWqdpE9QWnkvRKR6h7N5b065c8tRSiyv5XN1l665GOTpvrKOWMtF3fU3rHU3G7/s4nZUTxPAChaatr5glqn3eWctPfOD6BXyTlvUBdJV+GDKUTlmbVZZRN2apx7OqcLjQK4783gR8vGtW4MA5SAQAAAKAKEKICwEACr2cRqHyblC8vAhWU4pDUScUB0AQvgFMKQhX9UCU/VNEL1FkMlC/FgakfRlIkWYYhxzaVsCxlXHPyr9J+AEU/0iNbPd2zwdMzu4PK/rqEobcscHTuIkfz60YYcEaREm0bVbv5AdVu/a3sUnvlqUL9q9Q+76y4Xd+tHa3LGFTJD5UrBvKjQEnb1qy6pOpTrmqTTnW16++vlIsD1JpGaeZRUmYGC0cBAAAAqCqEqAAgSV6hp9I03xovBOXlpdCXrO5FoOombBGoMOwdmAbKe4E6C378OAgVRqEkQ45pyrEMZdxyhekUyKn+qyXQPRtLevBlT11evM+Q9DezLL11katls205I6ymtQqtqt36kLKb1yrRvqmy3082qn3uGeqYu1yl7LzRu4hBhKGUK/nKl3w5tqm6GlcN6Rplk051tuv3FvrxwlGGJTUvjitQneREjwoAAAAARowQFcDhJ4p6FoEqdsQVcsVOyc/Fz1XmM22ekPlM/TBS0Q9U8uPvXQVfOS9QqRyYSqq04zu2oZTjyKrClvzBdJQird3k6d6NJW3Y17NI1IwaQ+cucnX2QkfT0yMLGI3AU3rHH1S7Za3SO5+SEcWvG5qOumYtU/u85cpNe8O4tesXyu36kpRO2Fo4LaPalK10tbbr76/QHi+uVjtDajxKSjdN9IgAAAAA4KARogKY+sJQ8sqLQBU64kWgvK64+lSKq0udlJScMa4L3HQv9lTy4wrTgheoqxgo7/nyglB+EEqGZBmmHMtU0rFUm3SmRsA2gDCK9MyuuOr0kS2+vHJ26pjSyXNsvXWRq9fPsGSO5AOIIiXaNij7ctyub3kdlafyDUerY95ydRxxqkJ3fObm9PxQXaVAfhAo6diakU2qviZeJMo2p8gfbFCKq0/tlDTzWKluTvyLCQAAAACoYoSoAKaewO+Zz7TQJuVb4jkZ/WI8D6OTjEPTVOO4zcsY7r/YUzkwLfqhPD9UqHhxJMc05VqmMlW64NPB2JMLdd9Lnu7bWNL2rp5FohbWmXrrkY6Wz3eUTYys6tQqtKp2y2+U3fyAEh2bK/vjdv0z1T5vubzauaN2DYOptOt7gRzLUG3SUVO6RtnUFGjX7y2K4qkwvLxUd4TUuCieAgMAAAAApgBCVADVzy+VQ9POeC7T7iAn9HsWgUpmx20+Uy+IVAwClby4wrSz6CtfDFQKQ3lBKCmSKVOOHc9fmnbdql3s6WD5YaTHt/m6d6OnJ7f7CsvZaY0tnTHf0VsXuVrcaMoYQchtBCWld/xB2c1rVbPrj73a9V11zT6x3K7/unh+zrFWbtfPlQKFipRxbS1oqlFtylHGnSLt+r35Balrj5TISrNfL9XO1mH3Qw0AAABgSiNEBVB9uuczLXVKuZa42tTLS1EQz2Hq1MSrgI9xC3F3O37RC1UMAhVKgTpLvgpeWG7Hj2RIssuLPaUcS3VJZ0os9nSwtrQHunejp1+/5Glfsafq9Nhpls5d5OjNcx2l7BG26+97QdnND5bb9TsrT+Ubj1H7vOXqPOLNCp30aF7GAfl+pK6Sr1K5XX9a1lVDTUKZpC1nqrTr9xaFcXgaBlLDQqlxoeSOz2cNAAAAAOOJEBXA5BZF5cC0OzTdIxW7JC8XP19ZBGramC4CFezfjl8K1Fn0VQpCeX6kSHFg6liWHMtQ8jBqxx9K3o/08GZP92709Jc9QWV/Q9LQWxY4OneRo7nZkVWHWvm9ym79jWo3r1WiY0tlv5dqVkd3u37miFG7hsH0tOv7si1TtUlb89M1qk06SjpTuBqz1BX/EqOmWWo6UspMH7fpMQAAAABgvBGiAphcwqAnNC20xSGN11Wez1SSnYwXrEnVxa36Y6AUxG34JT9U0QvUWQyUL8WBqR9GiiLJNgw5tqmEZSnjmnQu7yeKIj3fEurejSX95mVPuXgRepmGdPwsW29d5Oj42SNbTMkISkpvf7zcrv9nGSq361sJdc46Ue3zzlJ+2rHj167vx/PaRoqUdmzNa0yrLuUok5iC7fq9hb7UuSdehG3aMVLDvHGbKgMAAAAAJgohKoCJFXg9i0Dl26T83rg1PyjFIamdlBIZqaZp1KvcwrB3YBov9tRZ8OPHQagwCiUZsk1TrmUo7dpyLPOwbscfSnsx1AObPN2z0dOmtrCyf3bG0DkLXZ290FFzzQgS5yhSsvV5ZTc/oMwrj8jyuipP5Zterfa5Z6nziFMUOjWjeRkH5AeRuoq+vDCUa5uaXuuqPu2qNulMzXb9/RXapEKHVDszrj6taZzoEQEAAADAuCBEBTC+vEJPa36+NQ5lSrm4us2yyotA1Y16ZZsfRir6gUp+/D1X9NVVClQqB6aSZMiQa3XPX+rIoh1/WMIo0p93Brp3Y0m/3+rLK2enriW9eY6jty5ydOx0S+YIQnA7v0e1Wx5UdvODcju3VvZ7qWlqn7dcHXPPlJeZPdqXMqDudv2C78s0TNUmbDXX1qg2aSvljEPV62QQlKTO3fF8w7OOlbJzJItbCAAAAACHD/4PCMDYiaL9FoHaG1ex+bn4ucp8ps2jNp9p92JPJT+uMK2043t+ebGnUJG6F3sylXQs1Sadqd1+PUZ2dYW67yVP920saWeuZ5GooxpMvXWRqzPnO8q4I2jX9wvKbH9ctVvWqmbX0zIUv2ZoJdQ5++S4Xb/5tWM2jcP+Cl6gXDFQGIWqcW3NqU+rvsZR2rUPj+kb/GI893ApF1eB182NF45KZid6ZAAAAAAw7ghRAYyeMIznLy11xWFpbk/82CvEz9tuudJ0Rjyf4ii8XTEIVPTiatJcyVdXMV78yfPL7fiGIcc05VqmMiz2dMi8INJj23zds6GkP+4I1B2dph1p+QJHb13k6qiGEfzZRpGSLeuU3bw2btf3c5Wnck2vVce85eqYfbKicWzXz5UClfxArm2qKeOqMeOqNuHImeo/O2FQDk27ypXhruSmpeY5Uqo+XkDqsEiPAQAAAKA/QlQABy/we+YzLbbHlaZePg5NDUNyknFommo85PlMvUo7fqiiF6qr6CtXDFQKQ3lBKCmSIVOuHbfjp12XvGcUbWoLdO9GTw9s8tRW7Kk6ff10S+cucnXKHFsJewTt+rldqt3yG2U3r5Xbta2y36uZofa5Z6p93nL56Zmjeg0HEkVSrugr7wUyDUOZpK05DUllk45S7hRu148iyS9Pr+EV4oDUSUvZI+K5ThO1kltLcAoAAAAAIkQFMBJ+qdciUK3xl5ePF4cyy/OZJmqldPNBv0XvdvyCH6hQCtVZ8lTw4rA0CCNJkWzDKs9dailLO/6YyHmRfrs5XiRq3d6gsr8pZejshY7OXehqdu3wA7a4Xf8xZTc/oNTuZ3q16yfVecQpap+3XPmm14xbu37RC5Ur+vK72/UbUqpLucokpnC7fuCVq8XzUhTGv+hIZqWmo6RENv77a7sTPUoAAAAAmHQIUQEcWJ/5TFviRaC8vBQF8RymTiquWLOcg3r5IJRKfqCCH6rkB8qVAnUWfZWCUL4fKVQkQ5JjxYFpknb8MRdFkdbtDXTPBk8PbfFU8OP9liEtm23r3EWOls6yZQ13JfooUnLvc3G7/rbfyfLzladyzcepfd5ydc4+SZGdGoOr6a+7Xb/o+3JtSw0ZV01pV7XJKdquH4U985oGpfjvrZuWGhfFLfqJ2nixKH4LAQAAAACDIkQFEIuiOGwpdpZD0z1SsUvy8/stAjXtoBaB8oJIBT+Q54cqdC/2VPLlBZG8MF7O3ZIhxzaVsCxlXHPqVgNOQq2FUA9s8nTvRk+b28PK/jm1ps5d5OgtCxw1pob/B2Lndim7ea1qtzwot2t7ZX+pZqY65i1X+9wz5adnjOo1HEgUSfmSr5wXyFTcrn9EQ0bZpKOaqdiu37tFX4pb9NPT4grx7mrTUZiTGAAAAAAOJ4SowOEqDMpVpl1SsUPqKi8C5RclQ5KdlOyUlKobUXt1FElFP27HL/qB8l6gzoIf7wtChVHcwm2bplzLUI1rybGc+D0xroIw0h93+Lp3o6dHX/EVlKc6TVjSqXMdvXWRo9dOs2QMs0rR8PPKbHtU2c1rVbPnmcr+0E6pY3bcrl9oes24VT2W/FBdBV+BIiUdS0fUp1SfcpVO2LKmUkAf+nGlaakrrjy1E5KbkRoW9oSmTnKiRwkAAAAAVY0QFThcBF6v+UzbpHx5EaigFIekdjJu861pGnbI5VcWe4q/54q+ukrx4k+lIK5mNGTItczy/KWOrKnYMl1F2ouh1u8N9OzuQGs3edqd71kk6uhGU+cucnXGPEdpd7jt+qFS3e36r/xOZhBXP0YylJ92nNrnnaXOWScqsscnxAvK7foF35drWapPu2rKuKpN2nKnSnIaReUF3LrieYoNM/67Wz9fqmkoLwiVoUUfAAAAAEYRISowFYVBOWTJxy36+dbyfKY5KfAlq7wIVLIurlobhp7q0lBFL1BXKVCu5MsLQvlBKMmQZRpyLFNJx1Itiz1NuFIQ6cXWQOv3Bnq+Jf6+rTPqc0yta2j5grjqdFH98Fu87a4dym5eq+yWB+Xkdva8Z3qW2uedpY65Z8ivmT5q1zKoSMqXAnV5vgwZyiQtzW7IqDZpq8axp8bPoV/smdtUiv/+phrjNv1Ebfx1kHMTAwAAAACGRogKVDu/FM9bWglM26Rie1xh6hfjY7rnM003DzmfaRhKxSBQ0YurSfPlxZ6KfijPDxVGoWQYckxTrmUq45YXe5oKQVUVC6NIr3TEVabry4Hpxn2h/LD/sXNqTR3daOmE2bZOnmPLHWZ1sOHlVLvt96rdvFY1e/9S2R/YNeo84s1qn3eWCo1Lxrddv+jLDyOlHEuz61Kqr3GVmQrt+mFQDk274nZ9y42rTZvnxL/8SNRKbs1EjxIAAAAADhuEqEC1iKJ4wZjuCtNSl1TYF3/3i3HQIsWBqZ2IQ5YhWvO9Sjt+qKIXB1K5YqBSGMoLQsVN2aZcO27HT7suiz1NEq2FODB9fm+gdXsDvdASqNPrf1x9wtCSJktLmiwd3Wjp6CZLtcNt1Zfidv09z8bt+tt+LzOIg/lIhnLTX6/2eWepa9YyRdbwKpoPVRBEynmBCp4vxzJVX+OqMR236yfsKv7hrPz9zkmlvGSa8YJQ2SOkmsZyaFor/gICAAAAwMQgRAUmo97t+H5eKnTEgalfiL+iKA5H7UR5EZn0oK28USSVgrgdv+AHKpRCdZY8Fbw4LA3CSFIk27BkW4ZSjqUs7fiTRsGP2/LXlUPT9XsD7cxF/Y5zLelVDVYlNF3SaGlG2hj2wlC9OV3bVbt5rbKb18rJ767sL2XmqH3emeqYe6b8VPMhXdewRVLeC9RVitv10wlLs+oyqk3ZSldzu37gxfOalvLx33knKSWzUuORPQtC2e5EjxIAAAAAIEJUYOINpx3ftOKw1EnGrbzmwHNXBqHkBWHlq3c7fikI5fuRQkUyJNlmXGGaTJTb8TEpBGGkLd1t+eWvl9pChftlpoakeVkzrjBtsnRMk6UFdaZs8+D/LE0vp8wrv1N2ywNK7f1rz5jstDrnlNv1G44e13b9XDGQHwVK2rZmZpNqqHGVSdqHdJ0TJgp75jUNSvHUGm5aalwopcoLQjk1LAgFAAAAAJMQISowXkbUjp88YDt+FMXhkheG8vxIpXI7fq4UquDF80P6QaRQ8WSYlkw5dvf8pRbdwJPMnnxPW/76clt+zu9/XGPS0DHlwHRJk6XFjZbSziiEbVGg1O5nld38gDLbH+vVrm8qN/0Nap+3XF2zThi3dv0wlHIlX3kvkGMZyqYcNWZqlE061dmu7xelUqfkFeLHTjpeDCrdXF4QKnvAX4oAAAAAACYPQlRgLPRux/dyUrFTKrTGgcow2/G9IJLnhZXAtOSF5bkgg/i5IFQYxos8GTJkm4Ycy1DSsWQnTMLSSSjvRXqhpWfhp+f3Btqd79+Wn7Slxb3b8pssNacOri1/QFEot2Orarf+VrVbHuzTrl+snauOecvVPucMBamm0Xm/IccjFcrt+pKUTthakK1Rtsapvnb90I8rTb0uKSi36LsZqWFhT4u+k5zoUQIAAAAARogQFThUfikOSrsXhRlBO34QSqUgkFeK5IUllfy4/T7vxdWlfhjK79XHbZtmJSytcRxZtOFPWkEYaVNbqOdb4rlM1+8NtLm9f1u+aUgL6kwd3RiHpcc0WZqXNWWNUru6EZTkdmxWYt9GJdo2KtG+UW7bS7L8fM9YnbQ65pyu9nnLVax/1bi1k3t+qK5SID8IlHBszcgmVV8TLxJVNe36UVT+ZUm5otyw4l+K1M3rtSBUhhZ9AAAAAKhyhKjAcA3Yjt8aV535hbj6VOrXjh9GRlxJGoRxZWneU8kvqqvkq+iFlfb7SKEUGbJMQ7ZlyjENJe3yfKXkL5NaFEXanYsqFabr9wb6r5ZAhaD/sdNqDC1p7KkwfVWDpdRotOVLMkvtSrS9pMS+DfH39o1yO7bIiMJ+x4amo/y016l93lnqmnm8Imt8FjDav12/NumoKV2j2qSjpFMl5dN+sWduU0lyUlKyQcpM66k2HWShNwAAAABA9SFEBQYywnb8yGmSb9gqBYFKfiTfC1XMh8qVuuL2+7BnUSdFkmEYcspBacoxab+vMl2lSM93B6YtcVt+S6F/W36NIx3daOnoRqsyn2lTahT+oKNIdm5nXFla+XqpT1t+b4FTq2L9IhXrur8WqpSZEy9sNB4iqeAHyhUDhYqUcW3Nb4zb9TNuFbTrh0H874CXkwJPsty42rR5TlxZnqiV3JqJHiUAAAAAYAwRogIjaMf3raQ8MyMvMiuVpfkuX12lnPwgqrTfR4pkyJBjxm3ZCctSxiUorUZ+GOmlffHiT+v2Bnq+JdCW9lD7R6aWIS2qN+OFn8qVpnOzpsxDTAiNwJPb8XIlKE20dbfj5wY8vpSepWLdQhXrFqlUDk39ZP8FysaD70fqKvkqBYESjqVpWVcNNQllkracydyuX6k6z8ULQhlGvCBU7exeLfq14i80AAAAABw+CFFx+BhmO35oOvJMV6UoJc+qVSmMVCgFynUEKgUl+UFRXtjTHm2Vq0pty1DSceK5HCdxPoQDi6JIO7qiSkv++pZAL7YGKg3Qlj8zbfRZ+OmoeksJ+9D+4M1SRyUo7f6K2/H7DyA0bZVq5/etLq1bqNBJH9IYDlVPu74v2zJVm7A1L1Oj7GRv1w+8eF7TUi6+CKc8JUfDop5qU3t8pjwAAAAAAEw+hKiYmoZox4/CUF4keYajkhLylFExNJX3QhVK5fb7oKhQBSmSzO6g1DRU45qyLWfytyBjSO3Fnrb858tt+fuK/dvyM47iCtPywk+LGy01JA8hEOzTjt8Tmh64HT/TKyyNv0q149iOPwwFL1BXMVCkSDWOpXmNadWlHKVde3IWbEZhz7ymQSn+LN201LhIStaXq03TLAgFAAAAAJBEiIqpYJB2fK9UkB+G8kJLJcOWFznqCtPK+5IfRPLCUEHgS4YvQ3FIapuGko7FPKVTTCmItLHclt9dZfpKR/8Fl2xTOrLe7KkybbR0RK0p42DDtNCT275FybYNciuh6Uuy/K4BD/dqZvQLTP1U86QM8/wgUlfRVykIlXBMTcu4asi4qk06k7Nd3y/GFeh+XooUt+inp0np5p4WfYv/LAIAAAAA+uP/FlE9DtCOHxRz8ot5eV5JfhipJEv50FEusFSI0vLDSH7YXV0YyTZC2ZbR035vTcKwB4ckiiK90hkHps/vDbV+r68N+0J5/TNTHVFrVuYwPbrJ1JH1ltyD/JkwS539qkvjdny//xgNW8Xs/Mr8pcW6RSplFyh0Mwf13uOlu12/4Psyjbhdf24mpWzKUcqxJnp4fYV+XGnqdUlBEC8E52akhgVSIhsHp05yokcJAAAAAKgChKiYnPZrx4+KHSp1tsor5uSX8vKDQCU/Ui50lA8teYYjL6pVqDgls2TK7p6n1I6/M0/p1LWvEFba8rtb8ztK/Y/Lun3nMT260VI2cRA/GFEkO7er19ylL5Xb8XcNeHjgpFWsO7JvYFo7RzKdkb/3BCl4gXLFQGEUKuXamlOfVn3NJGvXj6LyvxldcdWpYcUt+XXzpFSDlMzG1aeTZsAAAAAAgGpBiIqJ16sdv5Tvkp9rlde1T55XkF/Mq1AKVQgNleSoKEe+kZRMW4bi1nvHMZSwTKVN2u8PB0U/0ov74vlL15VD0x1d/ecxdUzpVQ3dFabxXKYz08bI2/JDT27Hlp7q0n0blGh/SZY3WDv+wv3a8adNynb8ofhBpFwpUMkP5NqmmjKuGtPldv3JUsEdlOJq01L5z8NJSckGKTOtp9rUqp6wGgAAAAAwORGiYvyU2/GDYk6lQqdKuU75uRb5hU4V8zkVS568IFBJtjzDVWi6Cs162ZYl24nb72tNU9ZkCW8w5sIo0pb2sFJdun5voI37QgX9M1PNzfa05S9psrSwzhxx0GeWOpVof6lSXeq2bVSiffMg7fjzVKpb1BOaZhdO+nb8oUSRlCv6ynuBTMNQJmlrTkNS2aSjlDsJ2vXDIP6li5eTfC8OSBMZqXmxlKwrz21aM9GjBAAAAABMMYSoGBOh76tU7FIp36VSoVNeV7v8rlYVCl3yinkFYSg/kALTUWglZNhpWYmEHLO7qpT2+8NRSz6sLPrUHZzmvP7HNSSNSjv+MeXvaXcEPzBRJDu/u1c7fhyaOrmdAx4e2Om+1aX1i1SqnVtV7fhDKXqhckVfgSKlHEtzGlKqS7nKJCa4Xb8yF3JO8gpxRa9TI2Vm9loQKiOZkyDgBQAAAABMWVM6RC2VSvr3f/933XHHHXruuee0c+dONTQ0aOHChbrgggt0ySWXqLm5edTeb/Xq1Vq1atWIzvnQhz6kW2+9ddTGMJ6iKJIXRCoW8yrlu+QVcyrlO5Vvb5Gfa1PgFxSWigqjSJFhKbITspyUrFStLNtW2jKrscMZoyTvR/qvljgoXbc3bs/fletfYpq0pFc1xkHpknJb/rSaEbTlh365Hb/v/KWW1zng4V5qejks7QlN/ZrpVdmOP5Tudv2i78u1LTVU2vVtudYEJqeBF89rWsrFIaqdiMPShkXxvKaJ2ngfAAAAAADjZMqGqOvXr9eKFSv09NNP99m/Y8cO7dixQ4899phuuOEG3XbbbTrvvPMmZpBVwg9CFf1QJS9QsZiTl+9UPtelfFe7onyrolJOoVeQEfoyDEOm7cqwk7KSdUrUJmXSfn/YC8JIm8tt+d2VppvaQoX7ZaaGpPl1ZtySXw5NF9SZsszh/QyZXpfc7rlLu1vyO16WGQ7Ujm+pVDuv19ylcWha7e34gwlDqegHKvqhvCCUZRhKJy0d0ZBRNumoZqLa9aMwXhCq1BXPcWra8YJQDQvjBaEStfHjKRhkAwAAAACqw5QMUbdu3arly5dr27ZtkiTDMHTqqafqyCOP1O7du/XAAw8on89r165dOv/883XvvffqzDPPHNUxLFmyRMuXLx/yuJNOOmlU3/dghWGkUhCq6IVxyFLylM93KtfZIb+YU1RoV1RokxkUZAYlWUYk27JkOgmZyZTM2nrJmpI/TjgIu3O9AtO9gV5oDVTon2OqOWX0LPzUaOlVjZZqnGEEZVEkO79nv3b8jYO049dUgtJSOTQt1c5TNMUXHAqCSCU//iWIFwayDFOubaou5SibslXj2EonbE1I0alfjENTPy9Filv009N6tejX8m8KAAAAAGDSmJL/h7py5cpKgDp//nytWbNGr3vd6yrP79mzRxdffLHWrl0rz/N00UUXacOGDaqvrx+1MZxwwgm6+eabR+31RkMUlYNSP6wEK/mSr1wur0KuS0GpS2EpL6PYJsfrkB16cgxfSUOybEdmMqXIrlNkuZLB/IOI5bxIL7QEfapM9+b7t+WnbOnoxjgw7a40ba4ZRnoX+nI7tvabv9TyOgY83EtN61dd6tfMOCyqGP0gUskPVPRC+QplyZTrmKpPO8omU0o5tlKuNeIFt0ZF6Mft+V6XFARxO76bkermSak6KZGVnOT4jwsAAAAAgGGYciHq3XffrUceeUSS5Lqu7rrrLh177LF9jmlubtaaNWt03HHHaePGjWppadH111+vr3zlKxMx5FHn9QlKAxW9QJ1FX50FX0EpL7/UpaiYlxXk5JbalYgKykSeHDOUZRoybFdhIqHIqlVkupXwKZzg68LEC8JIL7X1VJk+3xLo5bZQ+0empiEt7G7LL3/NrR26Ld/0cnJ7zVuaaNs4SDu+WW7H75679EgV6xYqdGtH8YonNz+IVPTi9vwwimSahhK2qaaMq9qUo5RjKelacoY5HcKoiqK4yrTUFVedGlbckl83r1eLfkYTu2oVAAAAAADDM+VC1FtuuaWy/cEPfrBfgNotnU7rmmuu0fve9z5J0re//W1dc801su3q+0h2tRfU5tvqLPrqKvoq+KG8Ukmhl5fpF2QFeSWCnGqCTjkqyok82UakyDAVJVxFVkqhVS+ZtoKJvhhMGlEUaWdX1Gfhp/9qDVQc4IdkRo1RqTA9psnSkQ2WUvYgwV0UyS7sjUPS3vOXdm0f8PDATlXa8LtD07gd3x2lq60Ovh+pUJ7TNFIkyzSUtCxNy7qqTThKOpZSriV7IkJTKZ7PtJSTvFw8z6lTIyUbpMy0uNI0UStN8SkUAAAAAABTU/UlhoPo7OzU2rVrK49XrVo16PEXXnihPvaxj6mzs1MtLS16+OGHR31u1PHwly27VJtslRuWlFBRtUGnkkGXnKgkM/SkSIosS5GTUGilFVmuPNrxsZ/OUhyY9p7LdF+xf1t+2onb8rsrTI9utNSYGqSaMPTldm7tU12aaHtJVql9wMPjdvyFvVryF8mvmS4Zh1/FoleediMOTUPZpqmkY6khnVA6Ebfmp+wJmtNUksIgDky9nOR7cUDqpqXGI3tVm9ZM0OAAAAAAABg9UypEffTRR1UsFiXFlaZLly4d9PhkMqkTTzxR999/vyTpwQcfrMoQdWHur8qGlowoLhGMLEehlVBo1Sro1Y4PdPOCSBvLbfnPlwPTLR39J2ywDGlRvVmpMD26ydKcWlPmAX6mDC+nRPtLlaA00bZRbvvLcZi/n7gdf66K2XJ1af0iFbMLFSbqRv16q0KkXnMWBwojybEMJR1LTZmkalxbKddUciJDU0ny8uXgtBD/2+LUSJmZUk1THJomaiWTX9IAAAAAAKaWKRWirlu3rrJ97LHHDqs1/41vfGMlRO19/qHat2+ffvKTn+i5555TW1ubstmsZs+erRNPPFHHHnusjFEMNiPTkp9qlMwp9ceJURJFkbZ3RpVFn9bvDfRiayBvgEluZ2eMPlWmRzVYcgdahCiKZBX27ldduvGA7fihnYqD0my5urT+8GzH76M7NPVCFYP4FyCOZSrpmJqWSakmYcdzmtrWxE4bGvrxvKalcou+nYiD0oZFUrLcom8nJnCAAAAAAACMvSmVuj3//POV7fnz5w/rnHnz5lW2169fP2pjWbNmjdasWTPgc6961at0+eWX69JLLx2VMDVy0gSoh7kwitSSj7SjK9T2zlA7uiLt7Aq1oyvUS/tCtZf6t+XXuoaWNJla0mhV5jOtSwyQ1oVBuR2/V3Vp20bZB2rHTzb1mr80Dky9mhmHZTt+b1EkFf1AJT9SyQ8kRXJtS0nH0rTahNJJS6ny4wktHo/CuNq01CX5pfjflkRaaljQq0U/TYU7AAAAAOCwMqWSt71791a2Z8yYMaxzZs6cWdluaWkZ9TEN5L/+67/03/7bf9PPf/5z/fjHP1Y6nR6X90X1iqJIbcV4oacdXaG2d4Xa0RmHpDu6Iu3qCgesLO3mmNKRDeUK03Kl6eyM0S/EN/y8Em2byoHphnixp/aXZYal/mMyTJUyc/rMXVqqW6jgcG3H3093aFr0QnlhIMmQa5tKOZZmZhOqSdhKOqaS9gSHppLkF8uhaV6SIdkpqaZZSjfH1aZurWRNqf9cAAAAAAAwIlPq/4o7Ozsr26lUaljn9D6u9/kHa968ebrooou0fPlyHXvssZo2bZqCINDWrVu1du1a3XTTTZWK11/+8pdauXKl/t//+38yh9GvWywWK3O+SlJ7+8CVgKhOXV5UCUZ3doXa3tX3cd4f/HzTkKbXGJqZNuOvTPx9Tq2pRfWmnN5t+VEkq9DSp7o00bZRTtd2GepftRpayX6LPZWy8xRZtHF3C0Op5Acq+KH8IJRhSK5tKZO0VZdKKelYqnEtuZY5wZWmkRQUJb8QV5wGQdyO72akunlSqi6uNnWG928oAAAAAACHgykVohYKhcq26w5vrsVEoicEyufzh/T+559/vj7wgQ8MGIguXrxYixcv1oc+9CF97GMf02233SZJ+sUvfqHbb79d73vf+4Z8/euuu05XX331IY0RE6foR9qZ664gjStKe1eTdgzQcr+/plTvkLTXdtrUtBpDljnQ/KWBnM6tSu7bILdXaGqX2gZ8Dz/Z2CcsLdYtlJeeddi34+8vDHtXmoYyDUMJ21RdylE2ZStpW0q5lhL2BH5uvQNTvygF5STeTkh2shyadrfoZzSxk68CAAAAADB5TakQNZlMVrZLpf7txwPpXdk53OrVA6mvrx/yGNd1deutt+rFF1/UI488Ikn63//7fw8rRP3iF7+o//E//kflcXt7u+bOnXvQ48Xo8sNIu3P7h6OhdnTG+1oKQ4ekWdfoG45mukNSQzPSZr9FnoygJKuwR3ahRXZbi6xCS7xdaJFVaJVdbJHTtUNmUOz3XpFMlWrnVCpMS+XANEjUj9ZHMqUEQaSSH6rgB/LDUJZhyrVN1dXEoWnKsZVyTbnWBAWRQwWmtU1Ssk5yauIqU6eG0BQAAAAAgGGaUiFqJpOpbA+3qrT3cb3PH0umaepLX/qSzjrrLEnSX/7yF23dulVz5swZ9LxEItGnchbja7DFm3Z0htqdjxQOkZPW2NLMjKkZ6Z5wdGbG1Kx0vK/GiUNSIyjGIWh3ILq7RfaW3gFp+bs3vCkoQivRvx2/dp4iOzn0yYcpP4hU9AKV/FBBFMWVpo6pxrSr2qStGtdW0rH6TpMwXoYMTMtzmRKYAgAAAAAwKqZUiNrU1FTZ3rlz57DO2bFjR2W7sbFx1Md0IKeeeqocx5HneZKkdevWDRmiYmwNtnjTznJgOtjiTVK8gNP+rfYzyhWls9KGsmZRTmlf34rRfS2yd/SqHi3sleV1DXvcoekoSDbKTzbKTzYoSDbJTzbITzYpSDbIq5khLz1TMqxD/ISmNj+IVCiHpqHi0DRpm2qudZVJOko5lpKuJWegKRPGUr/A1FO8+BOBKQAAAAAA42VKhahHH310Zfvll18e1jmbN2+ubC9ZsmTUx3QgjuOoublZ27dvlyTt2bNn3N77cDZWizcdkSpqjrVPTdonp9Aiu9Aqq7BXdler7L17ZRVbZedbZPkjCUddBeUwNA5FGythaU9o2qjQyWjil3evPr4fqeAHKvqhoiiUZZlKWpamZxPKJGwlXUspx5I9nqEpgSkAAAAAAJPSlApRjznmmMr2s88+K9/3ZduDX+Kf/vSnAc8fD11dPYFaOp0e1/eeqkpB7zlJo17zkh7c4k1zU0UtSuzTXLtNs4xWNUStcoutPZWk2+PWesvPDXuMoZWQn2hQkGqUn+gfigaVcDRNODqKSn6okh+q6AeKFMk2TSUdSw3phDIJR0nXVMq2NW5TmvYOTL2CFPoiMAUAAAAAYHKaUiHqSSedpEQioWKxqK6uLj311FNatmzZAY8vFot6/PHHK4/PPPPM8RimJGnjxo1qb2+vPJ49e/a4vXc1G63Fmxaki1qS3KdFiTbNtfdplrlPzVGrsmGr3GK5knTvXln+8ObWlcrhaL9AtHclaZOCRAPh6HiIpFIQqtgdmkaSa5lKOKaaMimlE7aSThyajksuOVRgmp3TE5i6NZKdIjAFAAAAAGASmVIhaiaT0fLly3X33XdLklavXj1oiPqzn/1MHR0dkuL5UE899dRxGackfe9736ts19XV6fWvf/24vfdktv/iTTv3qyYdavGmtPKaZ7fq6FSbjky0aZ69T7PMVjVrn+qDVtX4cUhq5vPSMPPR7nC0e47R/StGu7dDu4ZwdKJEUrG70jQIpCiSY8ft+NMybjk0tZS0rbHPJvsFpkG8n8AUAAAAAICqNaVCVEn6xCc+0SdE/dSnPqXXvOY1/Y7L5XK68sorK48/8pGPDNn6P5jOzk5lMplhHfvoo4/qX/7lXyqPL7744kN672oSRZHaS1GlcrR78aZ4lfsDLd4UKaO8phv7tMho1Sxrn45092mes0+zzX1qVqvqw1alvVbZYSE+xSt/DSK0kgcMRPuGoynC0UkmiqSiH6johfKCUDLiStOUY2lGNqFUIg5Qk7Y1tn903YGpV4hDUwJTAAAAAACmJCOKoqH7n6vMqaeeqkceeUSStGDBAq1Zs0bHHXdc5fm9e/dqxYoVuv/++yXFVagbNmxQfX19v9fatGmTFi5cWHl822236ZJLLul33OrVq/XNb35Tl112md71rneprq6u3zGFQkHf+c539IUvfEH5fFwGWV9fr7/+9a+aNWvWiK+zvb1ddXV1+tMj9yiTmTxzqnYv3rSzXEF64MWbItUqr+lGq6Yb+zRdrZphtGqGEQeks8x4X324T25UGPb7B3aq/wJMiQb5qbid3k81yU80KHJqxuT6MfrCUCoF5dA0DCQZcm1TNY6lupSjlGsr5VhK2ObYhaZDBaapBilRK7npeA5TAlMAAAAAACa97nytra1N2Wz2gMdNyfLH22+/Xccff7y2b9+uTZs26fWvf71OO+00HXnkkdq9e7ceeOAB5XLxQkC2bevOO+8cMEAdqSeffFIf/OAHZdu2lixZoiVLlqihoUFBEOiVV17RY4891mce1FQqpTVr1hxUgDqRhl68KVRWOU0z9mmG0arp2qfXGa16S/nxNHefZputmqZ9Sqo48JtEkoK+uwK7pleVaIOCAVat95ONiuzUmH8GGFthKJX8QAU/lB+EMgwpYVvKJG3VpVJKOpZq3Dg0HRNDBaZ1cwlMAQAAAAA4jEzJEHXOnDl68MEHtWLFCj399NOKokgPPfSQHnrooT7HTZs2TbfddpuWL18+qu/v+77+8pe/6C9/+csBjzn++OO1evVqHXPMMaP63qPhgIs3dYTqynXIKbZWwtEZRquOMfbptHI16Qy1anpin1JGadjvF9jpPnONHqi9PrKTY3jVmEhhKBW9QEU/rjQ1DVMJ21RdylE2ZSvlxAtBjUloGkVxUOoX+wemTkpKTyMwBQAAAADgMDclQ1RJWrJkiZ544gn9+Mc/1h133KHnnntOO3fuVH19vRYtWqQLLrhAq1atUnNz86i834oVK7R48WI9+uijevzxx7Vhwwbt2bNHe/fuVRiGqqur08KFC7Vs2TL93d/9nU455ZRRed+D0W/xps5Q7Z3t8jpbZOT2yi3FAel0o1VHGq06sTscNfYpaXhSYnjvEzjpnhA00Sg/1aig/N1PNCjobqsnHD3sBEEUz2nqh/KjUJZMuY6p+rSj2mRKNY6tpGvKtUY5rIzCclg6SGDaPYcpgSkAAAAAACibknOiHi4ONCd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" ] @@ -447,12 +447,12 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 68, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -466,7 +466,7 @@ "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", "hv_indicator = iohinspector.indicators.anytime.HyperVolume(reference_point = [1.1, 1.1])\n", "\n", - "df_hv = iohinspector.plot.plot_indicator_over_time(\n", + "df_hv = iohinspector.plots.plot_indicator_over_time(\n", " df, ['obj1', 'obj2'], hv_indicator, \n", " evals_min=10, evals_max=2000, nr_eval_steps=50, free_variable='algorithm_name'\n", ")" @@ -484,12 +484,12 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 69, "metadata": {}, "outputs": [ { "data": { - "image/png": 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qymttmiZDhw5l5syZvf5at7a2cv/993PmmWcyYsQI/H4/oVCIfffdl2984xu8+eabO3W+/kQqUfcShq6SFzSxbWhNpFldE8Fn6BQGTfKCJkFTfhX2SIrqVqZuWZ3qzYHQYKlOFUIIIYQQQvSJH/3oR9x11104ztYTQ9TX11NfX8/ixYv561//ysUXX8w//vEP/H5/j1z7iSee4Fvf+hYtLS0dti9dupSlS5dy//3385e//IUTTzyxy+esrq5mxowZvPHGG1s9tmHDBjZs2MAzzzzDnXfeyeOPP86hhx7a5XN/8MEHXHLJJWzcuLHLx/SmpUuXcv7557Ns2bIO28vKynjiiSd44oknuO222zoEtp1Zs2YN5557Ll988UWH7Zs2beLRRx/lX//6F88++yynnHIKAJ988gnnnHMO5eXlW53nvvvu49FHH+XVV1/lyCOP7Oaz7J6//vWv3HTTTSQSHQuXvvzyS7788kseeOABXnnllR3+/O+55x5uvvlmLMva6rGmpiaamppYsWIFs2fP5oQTTmDu3LkUFBR0uY3be63Ly8t55JFHmDt3bq+91v/617+48cYbqays3OqxVatWsWrVKmbNmsX06dN59NFHCYfDXX5e/YEkZ3sZVYWQTyfk6ESTaTY2RKlsjpPnNykIesjxGu4wqaLfcBywHbAzs1IZ2xuKoa061bEh0eJWp9avhkAR5AySsVOFEEIIIYQQu83GjRtxHAdFUdhvv/3Yb7/9KCgowDAM6urq+Pzzz1m9ejXghp7Nzc288MILHSr+uuM///kPl112WTag0jSNo48+mn333ZdIJMIHH3xAWVkZ11xzDX/+85+7dM6qqiqOPvrobHsBxowZwxFHHIHH42Hp0qV8/PHHAKxcuZJp06bxyiuvcPTRR3d67lWrVnHTTTfR1NREKBRi6tSpDB48mIaGBt59990uP+9zzjmHiRMnMn/+fD755BMADjvsMA4//PCt9t1RGLZp0yZOPPFEKioqyM3N5dhjj6W0tJTa2lrefPNNmpqaALjjjjvYf//9ueiiizptW3NzM6eddhpfffUVOTk5HHfccZSWllJRUcGbb75JNBolkUhwzjnnsGjRIlKpFCeeeCLNzc0UFhYydepUCgoK2LBhA2+++SapVIrm5mbOPvtsVqxYsduCuNmzZ3P99dcDsN9++3HooYfi8/lYvnw5H3zwAY7jUFdXx1lnncWyZcu2265NmzZlfz9Hjx7N+PHjKSoqwuv10tjYyKJFi1iyZAkAb775JieeeCLz5s3D4+n87/ntvdaVlZW88cYbvfpa//GPf+QHP/hB9ouTnJwcjjrqKIYOHYplWSxZsoQFCxbgOA4vvPACxx9/PB988EGPfXmyO0iIurdSwO/R8Xt0kmmbukiS2kiCHK9BUchDjs9AUxUUlPaHuPdKx3vhah922rbjzgnlOFg4OLb7uOU4OLiP2baD7Tg4mWPTlk3acY+1bLAcG8t2sG33PLbjvuYhj06Oz8Dv0fDpOuqWofdW1am1bhd/qU4VQgghhBBC7CaHHHIIp556KtOnT6ewsHCb+7z33nt84xvfYNWqVbz00ks89thjXHbZZd2+Zk1NDddcc002oDrooIN48skn2XfffbP7OI7DX/7yF77//e/zwx/+sEvnveqqq7IBaiAQ4MEHH+Tiiy/usM+CBQu46KKLWLNmDZFIhEsuuYQvv/yS3NzcHZ77t7/9Lel0mhtuuIHf/OY3BIPB7GOpVApN2858GVv43ve+B7hdu9tC1NNPPz3bvbur7rjjDhKJBLfccgu33XZbh4Crvr6eCy64INsd+6c//SkXXnhhp8H3fffdRyKR4JprruGuu+4iFAoBYNs2y5Yt4/zzz2f58uXEYjF+9atfsXjxYlpaWrj99tu59dZbMU0ze64lS5Zw4oknUllZSVVVFX/605+47bbbduo5dtd1111HUVERDz/8MKeeemqHx959913OPPNMmpubqaio2GG7xo4dy5///GfOOecchgwZss19vvzyS775zW+yYMECFi5cyO9//3t+/vOfd9rG7b3W4FYSn3TSSb3yWr/xxhv88Ic/xHEcTNPkjjvu4Lvf/e5WAenChQu59NJLWbp0KQsXLuSHP/wh9913X6fPq7+QEFVg6ir5QRPLcogk0qyqacGr66C0C06z9+0+HLcRpirK5n06hK69kNdtvs7WJ9/RZ3hn2eG2Hs4Gx+222ZnQ1LJt0pnQ1HYy4Slty5mQ1N5cSboVp+0aCiptY66AmrkH0BQFXXXD1rpIkupIAl1V8JkaYa9J0KvjNzU8+haJ6pbVqTXLocEEf6FUpwohhBBCCCF6zY9+9KNO9zn22GN57bXXGD9+PPF4nD//+c+7FKLedddd1NXVATB48GBee+21rbpBK4rCd7/7XdLpNDfffHOn53zrrbd4+eWXs+tPPvkkZ5xxxlb7HXroobzxxhsceOCBNDU1sXHjRu65555OA750Os3VV1/NX/7yl60eMwyj0/b1tEQiwa233sqdd9651WP5+fk8/vjjjBkzhtbWVtasWcP8+fM54ogjOj3nZZddxt///vetHhsyZAh///vfmTp1KgAPPfQQAL/4xS/4xS9+sdX+EyZM4A9/+EP296RtaIHd5fXXX2fy5MlbbZ86dSp33nkn3/nOdwCYM2fOdtv1jW98o9PrTJ48mddff51x48ZRWVnJfffdx6233tppqL6j13ro0KE8+OCDHHPMMUDPvda2bXP99ddj23Z2v3POOWeb7TvwwAOz75OqqioefPBBfvrTnzJ06NAdPq/+QjpuiyxNUwj7DQoCXnRNQVMUVEVBZXNFqoNbPWk7Dpbt3tLW5lsq7ZBM2yTSNvHMLZa0iSZ6/taasGhNWEQS6eytJZ6iJZ6iObb9W1O0461xi1tD+1ure6uPuLe6dreGVvd8saRN2nIrSFUUdFXB1FR8hkbQNMjxGOT6TQoDHgqD27iF3FtBZnza3IBB2G8Q8ukEve7N59Hwmho+j0Ze0KQw6CFoGiTTDmWNUZZXNrN0UzNfVUWoao7TkkhjtZ83rK06NXeoex+thbJPYcM8qFkJsUY3oRVCCCGEEEKI3WjkyJFMmzYNcMdmbG5u7tZ5bNtm1qxZ2fXbb799h+NI3njjjeyzzz6dnvdvf/tbdvmss87aZoDaZuTIkfz0pz/Nrv/1r3/d5piw7Xm9Xn73u9912o7dpaioaIehZElJSYfXYP78+Z2e0zRN/vCHP2z38aOPPprhw4d3uEb713FL5557brZicvny5VuNfdtbvvWtb20zQG0zc+ZMdN2tVVyxYkW3f5fbhMPhbBhZUVGxzQmhttQXr/Xzzz/PypUrATj77LO3G6C2KS0t5aabbgLcauu5c+fucP/+RCpRxVYUBbxG17oMiL6j6wohXSeEjuNAImXRFE1R2xpHU1T8pkbYZ7hVqoaO18h8Z7LN6tQ17apTC0E3d3xxIYQQQgghhOiiDRs2MH/+fL766isaGxuJxWIdwsW1a9cCblf7L774gmOPPXanr7Fs2TKqq6sB0HW907E6NU3jkksu4Ve/+tUO93vrrbeyy12pILzqqqu49dZbsW2biooKVqxYwbhx47a7/8knn0xeXl6n591dzjzzTLxe7w73Oeigg7LB17p16zo957HHHktJSckO95k4cSIbNmzItqF9t/It+Xw+xowZw7Jly3Ach3Xr1jFp0qRO27GrLrjggh0+HgqFGDNmDCtWrMBxHNavX99pu6qrq5k3bx7Lli2joaGB1tbWDu+NBQsWZJcXLlzY6fn64rV+6aWXssszZszY4bXbnHDCCdnl999/v0tV4f2BhKhCDACKAl7TrVYFg7TlEE9ZbGqMYTsOHkMjYOrk+g0Cpo7P1NDVLcdOrYGWCvCEIDQIDB9oBmjm5nvVYOtBWIUQQgghhBBiax999BE/+clPeO+99zqtyGxTW1vbrWstXLgwuzx+/HhycnI6Paazbujl5eXZYBZgypQpnZ6zqKiIsWPHsnz5cgA+++yzHYaohxxySKfn3J26Eka2r/DtSrXlxIkTO92nfZA8YcKETvfPz8/fqTb0hJ58bZYuXcott9zCyy+/nB3DtzNdeW/0xWv90UcfZZf//e9/884773R6zrYJysCdhG5PISGqEAOQrikENZ0gOjgQT1tE4mnqW5NoioLXUMnxGYS8BgFTw2t4UIIlm6tT677KjtXqDtBqgKqDpoPuBSMAhjcTsLaFrMbmdZm0SgghhBBCiL3aP//5T66++uouh6dtuts1u6amJrs8bNiwLh3T2TiM7c/p8/koKirq0nlHjhyZDVE7C766es7dpSsz3bcfqzWVSvXIOdu6wXdn/660oSf01Gvz6quv8vWvf51EIrFT1+/Ke6MvXutNmzZll5988slOz7elhoaGnT6mr0iIKsRAlxmeoW2IBitTpVrVnKCyOYahafgNza1S9Rj4zRwMb7sPUscGOw1WGuwUJJohVu+uZ6/RFrQamaDV4watpm9zBWv7kFWGCxBCCCGEEGLAWrp0Kddee202QJ0wYQLf+ta3OOqooxgxYgQ5OTkduoxfeeWV2Ulu2ian2VmRSCS7vOWM4NsTDAa7fM5AINDltrTft7Pgy+fzdfm8u4PSCwUxO3vO3mhDT+iJdtXU1HDRRRdlA9QRI0Zw3XXXceyxxzJ69Ghyc3Pxer3Za91+++388pe/BLr23uiL17p9VWl3pNPpznfqJyREFWIvo2kKAU0nAOBA0rKJpWya6lsBBa+hEfTo+A0NU1fRNRVDVzFUL6bh33aRqWODlXLDVjsFiQRE68C23IuguJNbaZmKVm/YHZfVmwueHf/DZVvSljt5WdskZom0hYKCz9Twmxo+Q0NV++d/eIUQQgghhBjo7r777mwwcsopp/Dcc8/tcNzFnpgYqH0gGo1Gu3RMa2trl8/Z2b7bO28oFOrycWLge+CBB7Kh4wEHHMC77767w6EndtekWbsiEAhkn9Nnn33GQQcd1Mct6j0SogqxN1PA1FVMXQV0bNudoKqxNUWts7lrgaYq6KqKrrohq89wj3HDVRVDUzE0D5ru2f61bGtzyNpaDU3lbqWqNw9CJVsFqpbtkEhb2aA0mbaJJNK0JtLE0zbptE3Scr+JcxxwcFAAj+6ODZvrM8jxGW6oamp4dJksTQghhBBCiN3hjTfeyC7/z//8zw4DVID169fv8jULCwuzy2VlZV06prP92ne1j8Vi1NbWdrjO9rSfbKkr+4u9R/v3xs9//vNOx+7tifdGbyspKcmGqJWVlX3cmt4lIaoQIktVwefR8HnaBY4OpG2HtG2TthyaYynqWx2czKCpKgq6pqCrCqah4ssMHWBobQGrgq6rGKoGqgZ4wAyC42AnY6Saq0nXbiSpmiT1HKKeIprwE7W9JG2HtOVgOzYOoCuZwFZX8Xp1DE1FbVca6zhOpjLVpqwhhlUXRVPdMWADHp08v4Hfo+M33UpbqVYVQgghhBCi57UfI7GzyXiampr48ssvd/maBx54YHZ52bJltLS0dFoFOn/+/B0+PmTIEIqLi7OTS3344YecddZZOzymtraWr776Krt+8MEHd9LyntVfu8IL1868NyzL4oMPPujtJu2yI444Ivs7/8EHH3Daaaf1cYt6j4SoA0Dh8ocJhXJwNBNH82BrHhzNg6Oa2Hr7ew+O7sFW3f3cfXSZBEjsmOJOVKVrGhhbP2zbZAJWm2jCpjmaxsbOHOpWr2qagqmp+AwVn6mTzgwhEE9apBwP6bQJ6Sh6qgzNWYtq+Aj68nACxSj+PBQz2KXfU0VRsuO/hn1uYy3bHQO2KZqiujnhVt9qCj5TJ9xWrWq41apt48YKIYQQQgghuk9V1exyNBrF49l+j7UHH3ywRyYG2n///bOBZyqVYu7cuXzzm9/c7v62bTNnzpxOzztt2rTsZDmzZ8/uNESdPXt2duzKwYMHs99+++3Es9h17cea3V0TLomu2/K9sSPPPPPMHlHZOX36dB555BHAnVDu5z//eYffw4FEQtQBIH/ti+R4uheEOiiZ4HVzsGprnkzFYM9xr2PiaKYb8nYIdLcIfzUz0x7v5v2z9x4cRev74FfRsMycvm9HP6CqYKptQwJ05Dju+KVp260QbU2ksZwECm7lqq4qeDSNoKmiqiaQC4CSjqGlmlGaanEiHtKePCx/EZYZxjYCO/W6a6pCwKMT8OiZNjkkLZt4yqa8Icb6+lY0VLymSsCjkeczCXj0zPiqOppUqwohhBBCCLFTRo8ezeLFiwF47rnnuOKKK7a538qVK7OT5uwqVVW54oor+P3vfw+4E/Kcc8455Ofnb3P/v/zlLx0qRrfn2muvzYao//nPf3j11Vc55ZRTtrnv+vXr+fWvf93h2N1dGVpQUJBdLi8v363XFp0bPXo0S5cuBdz3xvbGD62pqeH73//+7mxat5133nnss88+rFq1ioqKCr797W/zj3/8o0u/+5FIBEVRdmritr4kIeoA8I/0qYwNwmHFFj4lhZJOoNgJVCuBYiVRrARq5t5dTqA4bZWCDooVR7Xiffws9jzJwCBaS48gMuhI4vnjezx4HggUBXfc1J08ztF9pHV3lkolHUdP1GO0VuLoHixPLml/MZaZg210rUK1Y5sUPLo7Rmr7atVE2qI5mqamJYnjgEdX8Oo6Yb+eGVtVxy/VqkIIIYQQQnTqzDPPzIaoN998M6WlpVsFj2+88QYzZ86kpaWFQCCwUxM3bc8PfvAD/vGPf1BfX09ZWRmnnHIKc+bMYZ999snu4zgO999/PzfffDMejyc7S/r2TJs2jdNOO42XX34ZgPPPP59//vOfXHDBBR32+/TTT7n44otpbGwEYNiwYdx44427/Jx21sSJE7PL//3vf2lqaiIcDu/2dohtO/PMM3nhhRcA+N///V/GjBnDZZdd1mGfzz77jMsuu4yNGzf22HujN2maxv3338+pp56KZVnMmjWLyspK7rrrLsaPH7/NYxYuXMicOXP4+9//znvvvdfh97Y/kxB1ALiPC0i1+MlNKvzkKB+HlHbhx2qntwhZE5mQNZkJWa2ebaRjZ66VzF5LtRIodsdtmwPfbbUrEwQ76Z5tWzcojo3ZWoG5+hnyVj+DZYRoLT2U1tIjaC0+GMfw93UTBwxH95LW3a4ASjqOlmhAb63aHKj6irA84W4Fqm00VcmEpJvfO8m0TTxlUdEYZ0N9FE1R8RgqflMjz28S9O6eKlVTV8nx7mwMLYQQQgghRN+56aabePDBB6mpqaG+vp5TTz2Vgw8+mP333x9FUfjss89YsmQJAKeccgrFxcXZ7sC7oqSkhL/97W9cdNFF2LbNggULGDduHMceeyz77LMPra2tvP/++2zcuBGAu+++m+9+97tAx27WW5o1axZHH300q1evJhKJcOGFF7LvvvtyxBFHYJomS5cu5eOPP8Zx3HkjAoEAc+bMITc3d5ef0846/PDDGTZsGBs3bqSiooJx48Zx8sknU1hYmK0MPOyww7jooot2e9sEXHHFFdx111189dVXJBIJLr/8cu68804OOOAAvF4vixcvZsGCBQAccMABnHLKKfzud7/r41Z37sQTT+T+++/n+uuvx7IsXn75ZV555RX2339/Jk+eTE5ODtFolIqKCr744gtqamr6usndIiHqAPD7433cs0hlTaPNrW9HuXh/kysmenYc8Kg6tqqDsWeUTPc3SiqKv2YhwYp5BKoWoCWbydn4Fjkb38JWdWKFk91AddARpH0yG2NP2TJQVRMNeDOBqq37sTxudaqjebF194bavQDS1N0hCnK2qFZtTVjUt0YyE2v1fojqNzUmD8kl7JcgVQghhBBC7BmKi4t59tlnOeuss6itrQXc6rrPPvusw35nn302s2fP5nvf+16PXfv888/nkUce4dprryUSiWBZFm+//TZvv/12dh+Px8Of//xnjj/++Oy2Hc2SXlJSwgcffMCMGTN48803AXcogpUrV2617z777MPjjz/OYYcd1mPPaWeoqsp9993HeeedRzKZpLKykocffrjDPldccYWEqH3E4/Hw/PPPc9ppp7FmzRrAnQht2bJlHfY7+uijefLJJ3nggQf6opndcs0117DPPvtw7bXXsnLlShzHYcmSJdkvTLZlwoQJ2x1yoz+SEHUAGBrSuOfEAPd/HufF1SnmLE2yqNrip1N8FPm3/22a6D7H8NM6eAqtg6eAbeGtX0awcj6BinmYrZsIVH9GoPoz+PJ+4uExtA46gtbSI0iER8s4qj3E0b1YuheLTKBqxTEi5Si2W0XtqIY71q7hxzJD2EYgG646mgeUnXtvbK5W7YUnswNVzXHW1EaYOCSMocn7WQghhBBC7BmOOuoolixZwt13383zzz+fDYwGDRrEIYccwmWXXcaZZ57ZK9eeMWMGxx57LH/+85958cUX2bBhA4qiMHToUE4++WSuu+46xo0bx8cff5w9prOq0ZKSEt544w1eeeUVnnzySd5//30qKytJpVIUFxdz0EEHcfbZZ3PZZZdhGH1bADF9+nQWLFjAvffey/vvv8+GDRuIRCLZSlnRt8aOHcvnn3/Ovffey9NPP82KFStIJpOUlpYyadIkZsyYwYUXXoim7XlDyU2bNo1ly5bxzDPP8OKLLzJv3jwqKytpbm7G7/dTUlLCuHHjmDJlCqeddhoHHnhgXzd5pyiOvIv2WM3NzYTDYT555yXCOUEA3t6Q4o/zY0TTkGMq/PhIL0cMlgq23cloKSNQ+THByo/x1i1DYfNbLOUrdCtUSw8nVjgZR5OfTa9wHBQ7tXlYCDsJjoODCrqJrZrYZg6WGcLRvdiaF6ctXO1nLNuhsjnGuNIQIwuDfd0cIcReJpVK8dJLL3H66af3+R+EQgghel88Hmft2rWMGjVqwM6u3d4DDzzAt771LQCuu+467r///j5u0d7Ftm2am5vJycnZ4XAKQuxIT3xuteVrTU1NO6xKl0rUAeb44Qb75mn8+sMoKxtsfv5ujAvGWXxjsgddZhnfLVKhoTSGhtK473loiSb8lZ8QrPwYf/VnGLFacte+SO7aF7F0H9HiQ9wq1ZJDsc1QXzd94FAUHM3E0UwgSHaE3+zYvAn0aBVGpAxQcBQts78Xy5OLbfjdilXdh615e3/SMMdx2+ZY7e4tFNtGVSDs9bOuNkrYZ5IX2M2lsEIIIYQQQgxQTz75ZHa5r7rfCyH2HBKiDkBDQip3nxjggYUJnlmZ5F/LkyyqsfjZUT5Kg/Ltzu5kecK0jDiRlhEnolhJfDVfEKz8mEDlfPR4PaFN7xPa9D6OohLL3z/b7T8VHNzXTR+YFNWtONW92O232+nMxGUxjJZGVNvGaQtiVQ+WGcA2c7B13xZDAijg2JnA09oiCM1sb1u3rex+ip1CsVNgp1CtFDhpFMdxH8fOnNNdBxWPN48Kp4A1lRaTRpRg6vI+FkIIIYQQYlc8/fTTvPHGGwB4vV7OOeecPm6REKK/kxB1gDI1hRsO8XJAicZdH8dYXmdx/asRfniEj6OHSne8vuBoJtHSw4iWHgaOjadxFYEKt9u/p3kd/rrF+OsWU7T4HyRCw7ITU8XzxoKy542FskfJTrTm37zNcVDsJIqVRIvXYbRWAg6OooLmwdY8gJIJSjeHpm3hp+K0xbQdJ6ByFCUzHqvinktRcRQVR9FANbHbbUNRUWwLLdnEkFQ1tU1rqLBGM2L4SPDkyPi6QgghhBBCbOHDDz9k1qxZ3HDDDdscbzGRSHD//fdzyy23ZLd961vfIi8vbze2UgixJ5IQdYA7ZqjBPrlu9/7l9Ta3vx/j7LEW1xzgwdQkgOkzikoibyyJvLHU7385emsVgcr5BCs/xle7CE/LRjwtG8lf+RRpTy6tJYfROugIokUH4ugDf2yifkFRcDRPZpzUULshASwUK4lqJd1VRcVRNWzFyISjmwPQngg5HU0l7SsEr00w2kTj+i/JjZcRLhwCOYPBlw+afJQLIYQQQggBkEwmefDBB3nwwQcZNmwYBx54ICUlJTiOQ3l5OR999BFNTU3Z/ffff3/uvPPOPmyxEGJPIX957wVKgyr/97UA//wywVMrkjzzVZIlNWl+PsXP4JB0C+4P0oESmsacSdOYM1FTrfirPnXHUa1cgJ5oJLzhNcIbXsPWvLSWHk7LkGOIlhyaGfNT7FaKhqP7sHTfbr6uihHII0KAsmgKb0M5nqYyN0QND4FAEZj+zs8jhBBCCCHEXmLjxo1s3Lhxu4+fcsopPP744wQCgd3YKtFb6uvrue2223b5PN/73vfYd999e6BFYqCREHUvYWgK1x7k5YBijd99HGdlg831r0a4+XAfxw2X7v39iW0EiAydSmToVLDT+OqWZLv9G9EqQuXvEip/F0v30Vp6JJEhxxAtPhhHk5/j3iDXb1Ibsam0QwzPMVESTVDxBZhByBkEwRLw5oLMbimEEEIIIfZCU6dO5c033+Sll17ik08+oaKigtra2uws8IMHD+aYY47h4osv5rjjjuvr5ooe1NzczL333rvL5zn//PMlRBXbJCHqXubIIQZ/PUXjzo9iLKm1+J8PYyysTnPdgV48unTv73dUnVjRAcSKDqB20jV4GlcSKn+fYPl7GLEacsreIqfsLSw9QOugI2kZeizRogNAlUB1oFIUCPtMKpvihHw6+f4Ctxo1GYH61dCwDvyFbnWqvxB0qVYWQgghhBB7D1VVmTZtGtOmTevrpgghBhgJUfdCxQGVu07wM3tRgieWJXlhVYqltRY/n+JjWI5MYNRvKUp2HNXaCVfibVhBsPx9guXvY8TryNn4Bjkb38AygkQGTyEy5FiihZNBlZ/pQGPqKpqqUN4QI2DqeHQVPCH3lk5ArB4iVe56eBgECsGb09fNFkIIIYQQQoheM3LkSBzH6etmiAFMQtS9lKYqfPMAL5OLdX43L8aaRptv/7eV7x3q5cSRUrnW7ykq8fzxxPPHUzvxm3jrlxEqe4/gpvfdMVTX/5fw+v+SNnNoHTyFliHHEiucCIoEqgNF2GdQ0xJnU2OUkQXBzXNY6R4IFoNjQ6IZqpaA4XW7+YcGgT9fgnUhhBBCCCGEEGInSYi6lztskM79pwb4zUcxvqi2+O28OAurLL59sBdPP81ZFAXUHpj1fMBQVOIFE4gXTKBm8jX4apcQLH+P4KYP0ZNNhNe9QnjdK6Q9uUQGH03LkGOJF4yXQHVPp0DYb1LVnCDkNSkMbvHlh6K6Y6N6cyEVhaYyaNrYcSIqYzdPjiWEEEIIIYQQQuyhJEQVFPpUfnu8n8eWJHh0SZJX16Z4dW2qr5u1QwqgqaAr7r2mKOgqaJl1XVWyy5rirrd/PLt/u8fd++2cT1Ey53W3mZrCvvka++S63ar7DUUjVjSZWNFkaiZfh692EaHydwlu+gg90Uju2hfJXfsiaW8+LYOPJjLkWOL549zATexxTF3F0DTKG6IEPBo+YzvBuOF3b3Ya4k2waSGYIbdi1fC6lamK6gbrippZ1zLfWLR7rMOy/M4IIYQQQgghhNh7SIgqALd7/8xJXiYV6/x+XoyaWP8eR8QB0jakAay2LVvu0fsCBkwu1jmwWOOAYp1RuWr/qZJVNWLFBxIrPpDqA76Nv+YLt0K14iP0eD15a54nb83zpHyFRAYfQ8uQY0nkjYX+0n7RJTlenZpInE0NMUYVBnecbao6tJ+Iqmm92+1/q7eLAtibg9RsaKpmQlTFXVcN95yaAUrmXtO3E8iqYAbc0FYIIYQQQgghhNjDSIgqOjioROeRM4NE033dku1zHIe0DZZD5t7Bsmm3zcHOPNbhcYfMfg5W27IDVvt1G9KZ/bc8f9v+aduhNQVLa9O0puCj8jQflaeBBDmmwgHFGgeW6BxQrDE8R0XpD6GkqhMtOYRoySFU2zcQqP6cYPl7BCrmYcRqyVv9DHmrnyHlK6ZlyDEkcvfBUQ0cVe9wT4f1tuV2j7cFbGL3USDP56E6kiDHZ1AU8nThGGXzRFQ74tjuzbYAB2wbsN17Kw3p5OZ9sjdn8zXaD+qu4Fa/5g53x2aVMFUIIYQQQgghxB5EQlSxFU1VCPXruaX6R0hn2Q6rGm2+qEqzsDrNohqL5qTDe2Vp3itzU+h87+ZQ9cBinUFBpe9DVdWgtfRwWksPR7GS+Ks+JbTpfQIVH2PEqslf9XS3T+2gbBWyskUQa3lyadjnHGJFk3vwSe3ddF3Bq2uUNcQIeHT8Zg+Nd6tkKk/VHvhPheO4QwlULoLGDZA3EkKl7kRYQgghhBBCCCFEPychqhDdpKkK++Vr7JevceF4D2nbYUW9xcIqi4VVaZbWWdTHHd7akOatDW6oWuRXOLBY58ASjQOLdYoDfTuupKOZtA4+itbBR6Gk4wSqPiVQ8SF6vB7FTqPYqcx927K7TuZetTuOnavgoNhJsJM7vG6g6hMipUdQO+EqUqGhvfkU9xpBr05tS4LyxhijC4No/W3IUkUBXy54c9wwteKLTJg6AoKloPfrb26EEEIIIYQQQuzlJEQVoofoqsKEQp0JhTqXTvCQtByW1VosrE6zsMpieb1FTdThtXUpXlvnho+Dg26oekCJO65qvq/vki9H9xIZcjSRIUfvxEEOONZ2w9Yt77HTBKoWEF73MsHKjwlULaBp5GnUjbsE2xPuvSe3l8j1m9RGEoS8OqU5/bS7vKKCLw+8YYg1upNc+fI2V6ZqRh83UAghhBBCCCGE2JqEqEL0ElNTOKDEDUivmASxtMOSGosvqtMsrErzVYPNpojDpkiKl9a4oerwHJUDijUOyoypmuPpb+WEW1AUUDJd97t4SLT0MBpHT6dw8T8JVn1C7toXCG18i/r9LqRp9Jk4mlQkdpeuud36NzXGCXp1gmY//ohXVPDnu9WpsQaoWAiNmTA1WCJhqhBCCCGEEEKIfqUf/4UtxMDi0xUOHaRz6CD3bdeaclhck+bzKjdYXd1gs6HZvT2/yg1VR+eq2e7/k4t0Amb/GA92V6VCw6g46hf4ar6gcPE/8DatoWjJLHLXvkTt/jOJDJkqE1R1U9CrUxtJsKkhzuiiALraz19HRQV/gTt5VbwRyj931/NGZMJU+c+UEEIIIYQQQoi+J3+dio7sFGo6gWKnoCu1hU5X6w8BVcfWTBzVBLWHJr7ZgwUMhSMGGxwx2K24a044fFnjVql+UW2xrslmTaPNmsYkT38FquKGqhMKtcywAVqfj6m6q2JFB7Dx+LsJbXyLgqUPY0SrGLTg98RWP0ftxKuJF4zv6ybukfJ8JnWtcUJenUHhftqtf0uq5oanXsutTN30GfgL3TA1UCxhqhBCCCGEEEKIPiV/lQ4ATdEk4RA7PWm9YqVQrASKFUe1koDidsvWPDhGAJtM0NnZebdbMdhxu5qOoaUTYDWjODbgZK9nqwaO5un7cNWxM2N8WuDYKI6N4rQtW2BbKNjggKPqpH0FbiVdD8jxKBwz1OCYoW6o2hC3+aLanaRqYbVFeYvNqgb39uxKt1K1yKcwocgNVfcv1BiTq6L198rDLSkqLcO/RmTw0eSt+g95K/+Nr2EFw977ES2Dj6ZuwpWkAoP6upV7FE1TCBgG5Y0xgh6dkHcP+qhXNQgUgp12w9Tyz9z13BEQLO77zwghhBBCCCGEEHulPegva7E9XkOjtjVBvt+Dup08zw1M46hWAsVKokA2uLQ8+aQ8YWzdh234sXUfqL0wHqHjtAttEyjpOFoqgppsQbOSkGzJhKvgqBqOZmKrpjtGprqTv6ptwadtuefcQRja4TBFAUUDRcVRNFA0HNXAUU33XnPb46gaRqQSo7WSlL9459vXBXleleOHqxw/3P1Z1ERtltRaLKmxWFKbZnWjTU3M4e0Nad7ekAbAq8O4fG1zsFqg7TFDADi6l/pxl9A08hQKlj1KzvrXCW36gGDFxzSOnk79fhdjm8G+buYew+fRiEUsyhpi7FMSxNjTwnVVh0CRG6ZG693K1EAh5I507yVMFUIIIYQQQgixG0mIOgAML/ATsTTqInHy/CaGkkaxEtnA1K0wdQPTtLcA2wxjGz43NO2twHRbFAVH9+LoXuzMphRsHa5aCbRkC2oygmYlIBlxg08y4apqAI4bjtpW5rGOAZGTmfAIRcmEofrmMFQzsTUTVDcMdYNSDUfRNy+reiZI1bcb1qR9RXgaVmK0lpP2FuDovdttusjfMVSNpRyW17uh6tK6NEtrLVpTsLDaYmG1Bbhh+ciwyv6FGhMKNSYW6ZQGFJR+PN6o5c2n+qAbaRx9FoVL/kGg+nPyVj9DzoY3qB93MY2jTt99v7N7uFy/262/qklnaJ6vr5vTParuVqC2hamRT9yxUvNGuN39t/fNkRBCCCGEEEII0YMkRB0A/E6UYp/Gplgz9XUJgv4Ahukn7S3E8oRx9PaBaT/8kXcariZQrXi7cLU1MwxAxzC0ffC5ORztPAztLkf3ES8Yj6178TStxTID2GZOj15jR3yGwkElOgeV6IAH23FY35SpVq21WFqbZlPEYW2TzdommxdXu0MA5HuVbKg6oUhjn1wNQ+t/oWoyPJJNU36Fv+pTChf/A0/LBooWPUB4zQvUTriK1kFHyeRTnVBVCHkMKppihLwGYV8/fP93VVuYaqUgWgutNW6YmjvcHUtVwlQhhBBCCCGEEL1oD/6LWmym4skdxNDicdjNDmubLALBMEGfp68btms6hKthIBOu9ieqQTJ3Xxzdj6dxJWq0hrSvsE/CPVVRGJWrMSpXY/o+7rb6mJ0JVN1gdWWDRX3c4f2yNO+XuUMAmBrsl++Gqm3hao6n/wRS0ZJD2FB0IDkbXqNg2aOYrRUMnn8nsYIJ1Ez8Jom8sX3dxH7Na2rEkhblDVF8ZhBT6z8/227RDAiVgpWE1iporXYnnsob4YapEqwLIYQQQgghhOgFEqIOBEMPhaJiDGBUvoPeEGVldYRUNEme3+zr1g18ikIqNBRb9+FpWIHRWkHKX9IvxmzM96kcO0zl2GFu9/dE2mFlg8XizNiqS2stmpMOi2osFtVY2eOGhVTGF2qML3CD1RE5fTxhlarRPPJUWoZMJW/lv8lb/Qy+uiUMf+dmmoceR93+V5D2F/dd+/q5sN+krjVBVVOcYfn+vm5Oz9BMCA1yw9RItXvLKYW8keDL6+vWCSGEEEIIIYQYYPbwkiQBdAjrVFVhREGAiYPDODhUt8RxHGcHB4ueYvkKiBdOJu0vwWitRLESfd2krXh0hYlFOheP9/CrqX6eOifIP08P8IPDvZw62mBYjvuRsLHF5r9rU/xpQZxrX2nlnKdb+NGbrcz6Ms688hRNCbuTK/UOx/BTv//lrD/xbzQPOwGAnLJ3GPH6tQx7+/sM+vjXFH75N3JXPk2w7F28dUvRo9VgW52ceWBTVQh5dTY1xWmI9rt67l2jmW546s+D5k1QtgBqVkIq3tctE0IIIYQQok+8/fbbfPvb3+bQQw+lqKgI0zTx+XwUFxdz6KGHMmPGDP74xz+yYMGC7eYFt99+O4qidLh9//vf36l2vPjii1ud4/jjj99tz6E7tvW8u3obOXLkNs85e/bsrfY955xzdqpdS5Ys6fL1tqe6upoHHniAc845h/Hjx5Ofn4/X62XYsGEcfvjh/OhHP+Ltt9/e5dfTtm1GjBjRoa0ff/zxLp2zv5BK1AGqNOzF1FW+qmyhojlOScjbt5WEewnbDBIv2B9T82I2r8fy5PTrGeUVRWFYjsawHI1TR7vbmhM2y+osltVaLK2zWF5nEUu3n7DKNSSkupWqBRrjCzVGhXdftWraV0jVITfTOOYsChf/A3/tIryNK6Fx5Tb3d1BJe/NI+wpJ+4ra3ReQyqxb3jxQBu73Sl5DI560KWuI4jdDePQB9lx1D+QMhmQEapZBpBIK9nHHTZXxUoUQQgghxF5g2bJlfOMb32DevHlbPZZKpYjH49TU1PDpp58yZ84cACZMmMDixYu7dP45c+bw+9//Hl3vWpT00EMPdb3xGb39HPqLl156ibq6OgoKCrq0f3deyzatra389re/5a677iIajW71eFlZGWVlZXzyySf84Q9/4PDDD+euu+7imGOO6db13nrrLTZs2NBh20MPPcQRRxzRrfP1JxKiDmD5AZOJQ8OsqGymsilGcY4XY08fD3EP4GgeEvn7Yet+PE2rUOwklje/r5vVZTkelSMGqxwx2B0CwLIdNjTbLK21WFbnBqsbm23KW9zb6+vcykav7o6tOj4Tqo4v0Mjz9u7vWyJ3H8qPvhOzZT1GayV6rAY9Voceq8GI1aLHatFjdShOGiNehxGvg4YV2zyXo2ikvQWk/W7AmvIWbA5c/Zmg1Qzv0WNuhv0GtZE4FU1xRuT79+Snsn1mEAw/ROuh/FMID4X8UeAN93XLhBBCCCGE6DWff/45J5xwAo2NjdltJSUlHHrooZSWlqIoCnV1dSxevJhVq1Zlqw3b79+ZqqoqXn31Vc4444xO921sbOT555/vd89hZwwePHinKka7GogCJJNJnnjiCW644YZO97Vtm8cee6zL525v06ZNnHbaaXz55ZfZbYqicOihhzJ69GhCoRCVlZV8/PHH1NTUADB//nyOO+44/vjHP3LjjTfu9DW3Ffg+8cQT/PGPf8Tj2bPn7pEQdYALenQmDA6zSo9Q1hClIODBa/T9WJ0DnqKSCo/AMbx46r9Cb610x+zcAysdNXXzhFVnZCasak44rKi3WFqbZmmtxfJ6i2gKvqi2+KJdteqggML+hXo2VB2dq6L3dLWqopDMGUkyZ+S2H3dstERjNmA1YjWZcLU2s60WPVaP4lgYsWqMWPV2L2WrRqaKtRDLk4eteXA0E0c1sve2ZuKoprve7jFbNXE0I/OYe29n93G3ofTue1NRIOwzqWqKk+PVyQ8M0DGTFRUChe54qc1lEK2FvNFuoKoP0OcshBBCCCH2WqlUihkzZmTDxMGDB3Pvvfdy1llnoW6jV1ZNTQ3PPvssjzzyCGvWrOn0/Pvvvz9Lly4F4OGHH+5SiDp37lzi8fhWx/fVc+iOfffdl7/85S89es599tmH9evXk0qlePjhh7sUor7++uts2rQJ6Npr2aayspKjjjoqWxWqKApXX301v/jFLxgyZEiHfS3L4sUXX+Smm25i7dq12LbN9773PaLRKD/5yU+6/PwikQhPP/10dt3n8xGLxWhoaOD555/n/PPP7/K5+iMJUfcCXkNjXGkIU1NZV9dKyGMQ9MqPfndI+0uwNS/ehq8wIxWk/MVuWLaHy/EoHDZI57BB7u+R7XSsVl1Wa7G+2aai1aGiNcUb691qVY8Go8IqPkPBoymYGtu89+hgagoebfO9p21d37ze/jhDdf+jsBVFxfLmY3nzSWxvviHbQk80bA5Vo+69EatFj7uBqxZvQLVTmK0VmK0VvfK6OoqWCVyNbLgaLTmE2v1n4ui+HrmGqbvDLpQ3xPCbOl5jzwv2u0wzIWcIJFqgajG0VELBGAgW79EVxUIIIYQQQrT3zDPPsHz5csANrd566y3Gjh273f2Lioq4+uqrufrqq1m9enWn5580aRKGYfDFF1/w3HPP0dTURDi8455ebdWIhmFwySWX8P/+3//r0+fQXxQUFDBhwgSeffZZ5s+fz4oVK9hvv/12eEz7ys6ZM2d2KdR0HIeZM2dmA1RN03j00Ue5+OKLt7m/pmmcddZZTJs2jVNOOYWPPvoIgJ///OdMmTKFqVOndun5PfXUU7S2tgJuYHzWWWfxf//3f9nnISGq2CPomso+xUE8hsrK6ggp2ybPLxVZu4PtCRMrnISncRVGSxlpby6OMUBmSM9QFYWRYY2RYY3Tx7jbIkmH5XWZULUuzbJai0gKltf33qRUbWGqqSlb3IOhumHrlo8Z2W1BTC2EoY3GVMHwK27P8ExI6yVFyGognK4lmKrDl2rCcJLoTgqdFLqdRLOTaE4KzU6i2ikUO4lipVCtBIqdQrGS7e6TqFYKxUln2684Fko6hkps83Naswl/5SdUHfID4gXje+R1CvsMaiIJyhuj5HgNdM2tENYyN0NVB9Ywop5Qpot/XaaL/zDIH+luF0IIIYQQYg/33//+N7v89a9/fYfh45bGjBnTpf2uuOIKbr75ZuLxOHPnzuWaa67Z7r6rV6/mww8/BOD000+nsLCw0/PvjufQX1xxxRU8++yzgFvZ++tf/3q7+7a0tPDMM88AcMABB3DAAQd06RqzZs3itddey67/7ne/226A2l4oFOLll19m4sSJlJWVYVkWV155JStXrkTTOu852T7wveyyyzj77LOzIeorr7xCdXU1xcXFXXoO/dGADlGTySRPPvkkc+bMYcmSJVRVVZGXl8eoUaM499xzufLKK7v0Zt4Vn332GXPnzuX111+nvLyc+vp6CgoKKC0t5cADD2TatGmcdNJJlJaW9mo7AFRVYURBAK+hsaKyhermOEUhz7ar90SPcnQv8fxx2LoPs2k1jp3E8uT2dbN6VdBUOHSQzqGDdMCD7ThsbLbZ2GKTTEPCckhYkMzcZ9fTHbe3fzy5jXu73cSBScu9tabaNvbcLI2uUOY2qtM9VQU0xQ11dVVBV8nc3PBW192e5aZi41dT+JQUPjWNT0niVdz1YruWS1sfIhitZOh7t9Aw9jzqxs0AdRermRXI85lUtySobklkNiloKmiq6rZbUzF1FY+uYugquupWsOqqgq4p6KobvO4xHx+q5lagphPQuB5aa9yxUsNDYQBUhwshhBBCiL1XeXl5dnnEiBG9co0ZM2bw4x//mHQ6zcMPP7zDEPXhhx/OLs+cOZPq6u0PmdZmdzyH/uKMM86goKCAuro6Hn30Uf7nf/5nu7nMU089lZ0MaubMmV06v+M4/OEPf8iuH3zwwdx0001dbl84HOaee+7h3HPPBWDt2rX8+9//5sILL9zhcevXr+edd97Jrl922WWMGTOGSZMmsWjRItLpNI899hjf//73u9yW/mbAhqjLly/nkksuYeHChR22V1ZWUllZyUcffcTvf/97Zs2axemnn97j16+urubmm2/e5uC/FRUVVFRU8PnnnzNr1ixuuOGGHh9nY0dKcryYmsqKqhYqmuOUhLy7bVb1vZqqkwyPxtF9eBpXokerSfuK9ppuxaqiMCKsMSLcc+N+Oo5D2oaEBSnbDVVTlkPShlQmgE3Z7v02t7U/bottKYvMMVvu52TD2nTm+mm7Y5gL7rrtuOftGOZuK9g1MrctDecvjOOhwkc4OPIO+V/9C3/Vp1Qd8gOSObv2DwtdVygMbh7U23HcScTSto1tO8TTNq0JC8txcLAB9/dUZXPFqqYqGLqCR9Pw6KobrmqZwFUDXVHRNAWjP32+6B4ID4F4E1QugkgV5I9xx1DdS96LQgghhBBiYGk/ZujatWt75RolJSWcfPLJvPTSS3zwwQesXbuWUaO2Li5xHIdHHnkEgPz8fKZPn84///nPTs+/O55Df2GaJhdddBH33XcfGzZs4O2332batGnb3LctkNY0jUsvvZTPP/+80/O/++67LFu2LLt+0003bXNc2R05++yzGT16dHa82fvvv7/TEPXhhx/OTvY1ZcqUbIXw5Zdfzo9//GPArVSVELWfKSsr42tf+1p24F1FUZg6dSpjxoyhpqaG119/nVgsRnV1NWeffTavvPIKJ5xwQo9df8OGDRx//PEd3vj77bcfkyZNoqCggGg0yurVq1m4cGH2G4XdLS9gMnFImBWVzVQ2xygOeTG0gdR/t59SFFLBwdi6D0/DCozWSlL+IlAH5Fux1ymKgqG5XfLbQr6+YtkOlkMmVHWD2rTdcd2y3RA2bZNZb7/f5kA2lTnXhmabV9b4Obf2Wn5QfAjXxx7A27SGYW/fRN3+V9A45qwem6xMUciEoDsOuW0bLNvGchzSlkMq4dBip7GcdtW/joKmKWiKgpqpXvXoGj5DxWtqeHUNU1cxNbXvcktvGMygO+lU2QLIHQZ5I8ET7KMGCSGEEEII0T3tu7M///zzLF26lP3337/HrzNz5kxeeuklHMfh4Ycf5he/+MVW+7z33nvZLOSiiy7CNLs2jODueg79xcyZM7nvvvsAN3zcVojavrLz5JNPpqSkpEvnfuutt7LLpmly3nnn7XT7FEXhkksuyQ418NFHH5FIJPB4PNs9pn0F8uWXX55dvvTSS/nJT36Cbdt88cUXfPHFF10elqC/GZDJzYwZM7IB6ogRI3j22Wc7/IBqa2u5+OKLeeONN0ilUlxwwQWsXr2a3NzcXb52U1MT06ZNy35oTJs2jbvvvpvJkydvtW8ymeTNN9+kpaVll6/bHUGPzoTBYVZVRyhriFIQ8OA1end2cOGyvHnECifjafgKo7WStC8fR/f2dbPELtBUBQ13/NWeDHQnFGr8aUGcu6oP5aO8fbk3/A/yahdQtPhBApXzqTr4JtL+3TemjKq63xIbsO3iWQCnLVR23OpWyyGRSlHfauPgVrMamaECQl4dn6Hh0TU8xm4OVlUNgiWQjkP92kwX/9HuZFTagPzPoxBCCCGEGIDOPvts7rnnHgBisRhTp07llltuYcaMGVvNwr4rvv71rxMOh2lqauKRRx7ZZoi6ZVf+rtpdz6G/OOKII9hvv/1YsWIF//73v7n33nvx+zvOnfLII49kKzt35rV8//33s8uTJ0/e6rw708Y2iUSCBQsWcPTRR29z3w8++IBVq1YBbnDbvmp18ODBfO1rX8uO0frQQw9lx0nd0wy4vxJfeukl3nvvPcD9wT3//PNMmjSpwz6FhYU8++yzTJ48mTVr1lBfX8/vfvc77rzzzl2+/g9/+MNsufNFF13EY489tt3Bd03T5NRTT93la+4Kr6ExrjSER1dZW9tKyGMQ9A64X4t+yTH8xAsn4Oh+zOa1WGYQ25SJbkRHp442GRRU+eX7MT5sCHNK/GZmjX2P8av/ib/2S4a/+R1qDrielqHH95/u6ApuJep2wmTbhqRlkUjbtDTGcXBQcIcGMDWVoEfHb24OVj2a1rsTXenezV38K75s18W/oBcvKoQQQgghRM+YNm0aZ555Js8//zwAdXV1/PjHP+aWW25h7NixHH744Rx66KEceeSRHHzwweh69/7m93q9XHjhhTzwwAOsXr2aDz74oEOoFo/HeeqppwAYO3YsRx55ZL97Djtj5cqVfOc73+ny/pdffnmH4LEzM2fO5Gc/+xktLS385z//4dJLL+3weNuwCOFwmLPPPrvL5123bl12eeLEiV0+bktbHrtu3brthqjtJ5Q644wzyM/P7/D45Zdfng1RH3vsMX73u9/tlp9hT9vzWtyJe++9N7t8xRVXbBWgtgkEAtxxxx1cdtllAPztb3/jjjvu2KUf4sKFC3nwwQcBGDZsGA888ECXZi/ra7qmMqYoiEdXWVkTIdVqkxfoWsm92EWqQSJvH2zdi6dpFWosQdpb0H/CMNEvHFCsc89Jfn7+bozyFpvzlx7Lbw6eyMkb78HXsILST+8iUDGP6gNvwDZz+rq5nVJV8Koa3naVrI4DybRNyrKpbk5gOXZmuAa3YjVgavg9Oh5dw6urmLpGj45Aoijgy3W787fWQLQe8kZA7ggwu/fNrRBCCCHE3sBxHGIpq6+b0a/4DG23T+D8+OOPM3PmTP7zn/9ktzmOw4oVK1ixYkU2kAsEAkyfPp1rr712u+Nw7sjMmTN54IEHALfqtH2o9swzz9DU1JTdr78+h67atGlTh4ypM4ceeuhOhaiXXXYZP//5z7PDI7QPUefNm8dXX30FwAUXXIDX2/Weq/X19dnlvLy8Lh+3pS2PbX/e9uLxOHPnzs2ut+/K3+bcc8/l+uuvp7W1lerqal555RWmT5/e7bb1lQEVokYiEd54443s+lVXXbXD/c877zyuu+46IpEI9fX1vPvuu7s0Nupf//rX7PINN9xAKLTnVBWqqsLwggAeQ2NFZQuVzXH8hoaqKKiqO3O3qrqTA7k3dvt/FAYsRSWVM9ydcKphpTtOaqAYlP4fwIvdZ2hI454TA/zqgygLqy2+/0ke1x/4K64qeY6CFXMIbfoAX/0yqg66kWjJoX3d3J2mKLhVp8bmZNRxIGXZJNM2tZEkVnMCFDBUt9u/z6MR9OjucZlgVVeUXfsOQtUhNAhSUahdCZHqTBf/wW73fyGEEEII0UEsZbH/ba/2dTP6laV3nILf3L1xSzAY5Omnn+all17i7rvv5o033sC27a32a21t5cknn+TJJ5/krLPOYvbs2TsVtB1zzDHZCYfmzp3LPffckx0ns60aUVGUbQZp/eU59BfDhw/n+OOP56233uKNN96goqKCQYMGAR0rO3c2kG4/ZGQgEOh2+4LBjvNFNDc3b3O/9uF5fn4+Z5xxxlb7BAIBzj333GwQ/tBDD0mI2tc+/PBDEokE4P6ADjvssB3u7/V6Oeqoo7IlxW+++Wa3Q1TLspgzZ052vTsD9/YHJTleTM3t2p9I29iOg2W5Yxs6Ntg42DbYjpOdY1wB2taUzP/aQlZVcQNaVWmbZMYNYrW2bf1p1u52nMzzc5zMc2137+BgO2BqKqbec6VwaX+RW5Ha8BVmxJ1wytGkIlhsluNRuPM4P/d8GueVNSnu/TzNhn2+zs3HHsKQz+7CjJQx5KPbaRx5GrUTv7nHj7OrKLgTULV/n7ULVhtbU9RG4oA7eZWuqWgoKKp7rIqS/fxRFNAUUFT3s0jB/fxRFHdfBfczy11WUBUdjGLU1ibUpk8gOAgnfzT4891zZz7TPLqK2k8/x4QQQgghxN7n9NNP5/TTT6empoa3336bDz/8kE8//ZTPP/+cSCTSYd/nnnuOY489lo8++minisAuv/xyfvnLX9LY2Mhzzz3HBRdcQGVlZTZbOe644xg+fHi/fg5dcdxxx/H222/36Dm3NHPmTN566y0sy+LRRx/lRz/6EclkkieffBKAUaNGccwxx+zUOUOhEA0NDYAbOHfXlq91Ts62ez22D3wvvPDC7U4mdvnll2dD1Oeff56GhoY9LvweUCHqsmXLssuTJk3qUtf8gw8+OPtGb3/8zlq8eHE2lQ+Hw4wZM4Z0Os0jjzzCo48+ypIlS2hoaKCwsJDJkydz1lln8Y1vfGOHM5v1lbyASV7AxHHcsNCyHWzHvVn25hDVymyzbdzlzH4py3ZnHbdsdzZyyyZtu48nLffeajvOdrJz8LhhLNlK17aZvTveu49Du1CzXbDZ1mYnG3h23GazOSB1H1Wy11UyIzO2tUXNJCvqFgGLG8goNMSS4ECe3+yxMNU2Q8QLJ2I3rsLTspG0J4xtdP+bIzHwGJrCzYd5GRZSefCLBM+vSrEpMpjbjr6b4SsfJm/Nc+Suexl/zRdUHvIDEvn79XWTe5YChq5iZN9z7pgAacv9zLFtByfTm8yh7TMi855vt+yw+cufzM5bzAeW2eCoKI4fs2YNyvqNxIJDSQSH4OheN0Q1NIIejRyviddU8RoaXl3r0S9YhBBCCCH6M5+hsfSOU/q6Gf2Krx9M2FxUVMQFF1zABRdcAEA6nWbevHnMmjWLhx9+mHQ6DcCSJUv42c9+lp3UqStmzpzJL3/5S8Dt0n/BBRfw2GOPYVlW9vG+fg719fXcdtttOzz/kUcemR3isa+cf/753HDDDUSjUR555BF+9KMfZQNGcIPHne0FnJ+fnz1+e13wu6LtHO3Pu6WKiopspgbb7srf5mtf+xqDBw9m06ZNJBIJnnjiCa6//vput68vDKgQdcWKFdnlESNGdOmY9t+OLF++vNvX/uSTT7LLw4YNo6ysjPPPP5/58+d32G/Tpk1s2rSJV155hd/85jc89dRTnVbM9hVFUdAUeqxa1LKdzbd2Fa5p28a2yd4nLYtk2g1E3Ju7X1tAYmWiTpW2KrLNla8KmVnSM9VnuqqiqqBntmmZMFZT1WwF2pZDFKjZoLTjutohRIWWeJqyhijVzW71c37AxOiBQRodzUMibxyOHsBsXIViJbG8e9a3M6J3KYrCheM9DAmp/OajGJ9WWtz4lsOvpl7N6NLDKfn8bszWTQx770fUj72Q+v0udrupD2C6pqD35hjUoQBKKko4vgEr0kQ8ZwRxbzEJy6GqOUF5YwxQ0DUFj+aGqWGfgd+j49Uz4aqh9dvqeyGEEEKI7lIUZbd3XRc7T9d1jjnmGI455hi++c1vcsopp2QrDR944AF++9vf4vP5unSu0aNHc8wxx/D+++/zyiuvUFNTw8MPPwyA3+/n/PPP7/Pn0Nzc3Ol4ppFIpM9D1GAwyLnnnsujjz7KokWL+Pzzz7OvJXQvkB45ciSrV68G3IK/7try2JEjR261z6OPPpoNz0ePHs2UKVO2ez5VVZkxYwZ/+MMfALeCVULUPlRXV5ddLikp6dIxpaWl2eVdSeg3btzYYf20005jyZIlAIwbN47DDjsMTdP48ssv+eyzzwDYsGEDxx9/PO+++y6HHHJIt6+9p2gLMXeWk6mATdubq2Hbh5uwuXpVzVSt7g75AZM8v0F9bpKyhhg1LT0YpqoayfDIbPd+vbWKtL8IFKluE5sdPdTg/76m8v/ei7K+2ebG11q5/diJTJr2F4q+vJ+csncoWPEEgaoFVB7yA1KhYX3d5D2XAo7pxzJ8aIkGQvWL8fmLSfuLsby52YrxtqEGogmLhmgK27FRULLDfwQ8OjlePROuatnxXGWMaSGEEEIIsbtMmTKFn/70p/z0pz8F3ImBPvnkE6ZOndrlc8ycOZP333+fdDrNj3/8Y7788ksAzjnnnN0yP0xPPIf+YubMmTz66KMA3HXXXbz88ssAHH300YwZM2anz3f00Udn5wtatGgR0WgUv3/nJ8v9+OOPs8sej4dDD9167o32XfnXrFmzU3/XfPzxx6xYsYL99ttzek8OqBC1/XgNXf0Gpf1+W473sDMaGxuzy21pvd/vZ/bs2dnS8zZvvfUWF154IbW1tUSjUS666CKWLl263XEj2iQSieyYr7B5UN9UKkUqlep22/cUGu6Yhm7PiLZuuE72znHAAqzdPDFkjkdlXLGfkpBBRWOMmuZWVEUh17/rYWrSW0g638DTsAqtpZKUvxBUo/MDxV5jdK7Kn77m5xfvx1jdaPOjN6PcfJiXaQf/kJaSIyj98j68jasY/tb3qNn/ShpGnSFh/C6yzDwULYUaa8CIVKFrHtLePNK+InRPGE334tNVwH2dHcchadkk02nqmpNUNNrZavq2MV9DPoOgqeMxNLyGgkfXeqSyXYhd1fbvi73h3xlCCCHcz3vHcbBte5sT+oiB4+STT84GkADl5eUdfuaO43RY3vL34fzzz+fGG28kHo8ze/bs7PbLLrtsq323t952jW2df1efw/Dhw7MVkjuy5XXbP+9tPd4dnb0e06ZNY8iQIZSXl/PYY49lt+/Ma9necccdl11OJpPMnTt3pytaHcfpMO/PlClTMAyjw/U+/fTTbPFgd82ePZtf//rXu3QO27ZxHIdUKoXWzd6JXf237oAKUePxeHa5s0CyTfsxSWOxWLevva3Beh999FHOOeecrbZPmzaN5557jmOOOQbbtlm9ejWPPfYYV1111Q6v8b//+7/ZcUfae+utt7r1rYLoXd0fvnl7vNDQ/aBfDGzXjoVHVqosalD57cdxviiPcurQifjG/g8HbXiQ4pbFlCz+O8r6D/h8+DXEza3HsxE7SwXaJu9qzNx2TjRzX90j7RGi97Qf60oIIcTApes6paWlRCIRkslkXzdH9KK28UTb2LbdYfb19gVcqVRqq5nZFUXhtNNO4z//+U9226BBgzj88MO32rd9VpNOp7d6vP1s8j35HLqj/fPeVlu7o/3ztyxrm+c877zzOozp6vV6Oe2007baNxqNZpe393wPOugg9t13X1auXAnA3XffzVlnnYWqdr1I44UXXmDNmjXZ9csvv3yraz344IPZ5by8vC5XzTY1NWXb9vDDD/OjH/1op9q2pWQySSwW4913393qd6Kr2r+uOzKgQlSvd/NM1F39wG//Bulq9Wpn1wY46qijthmgtn/83HPP5amnngLgySef7DREvfXWW7n55puz683NzQwbNoxp06ZRUFDQ7baLnmfZDvWtScobo9S3JjFUlVy/uWvjIdpptHgDipVATUXQkhFUKwFWEsWxAQdH1XE0E1szcVQT1L4f0FzsPr8d4fDPLxM8tSLFK2UqMcXkB4ePpn70ndjrXqJ46T8pblnCiV/9jMpJ19My9LjOTyq6znFQ01HUZATFcbANP2lfEWlvHrYnp0tV5I7jDl2SSNskUxbpduNAO447sZiuquiqisdU8Bs6PkPH0BUMTcXQFUxVRddUGX9V9IhUKsVrr73GSSedhGFITwghhBjo4vE4GzduJBgMbvU3rhhY2sbMbLPffvt1mH29fcGZYRjbnJn9qquu6hCiXnrppeTm5m61X/vfJV3Xs+dyHIeWlhZCoVC3hrfq7Dl0R/vn3b6tu6L989c0bZvnvPrqqzuEqNOnT2fYsK2HY2tfQKeq6nbb98Mf/pBrr70WgC+++IJZs2bx/e9/v0vtbWpq4tZbb82ujx49mssuu6xDlWcqleLpp5/Orv/sZz/r8vmrq6sZOnQolmWxadMmFixYwIknntilY7clHo/j8/mYOnVqtz+3uhqWD6gQNRgMZpe7WlXafr/2x+/KtYEdBqjt92kLUT/88MNO9/d4PB3e0G0Mw5A/bPoZAxjsMSnJDVAbSbCxPkpNJIFH17ofpmo6jjEIB7CBtOOgWAk3VLXiKOk4WrIFNRVBtxKQas6EqwqOqrvBqubB0QxQJFwdiDQUrj3Ix7AcjXsWxHlnY5rqaIxfHutDGzOdePGBlH56F97GlQz57A/E1r9Ma/FBxAonEc8bK0NF7DIFtCCOJ4jj2KipVnyR9dC6HssIkfaXYHnzscycHX7BoQGebXSmaAtYU5ZN2nJoTTo0xlJYdhIyHym6pqCrCoaq4jVVfIaO33SHBjB11b3PLEvIKnaG/FtDCCH2DpZlufNPqOouVYaJ3ev//u//mDx5cpeDqGg0ym9+85vseklJCQcffHCHn3n7ULPtd2JLp59+eodJtvfZZ59t7rfltrb1tq7hiqJw99139/hz6I4tw9yeeB9s7/m3N2nSJD777LPsEATDhg3bqddyS1dffTVPPvkkb775JgC33HILQ4cO5aKLLtphWyORCNOnT6esrAxwQ99Zs2Zt9e/Al19+mdra2mwbZsyY0eXXqrS0lJNOOolXXnkFgEceeYSTTz65S8dui6q6c0zsyr9Xu3rcgApR21djVlVVdemYysrK7HJ+fve7t25ZCbr//vt3esz48eOzyy0tLdlvYMTAoakKJTleCgImtZEkGxuiVDbH8WVm7t6lEENRcHQvju7FJgxACiAbrsZR03FUK46abEFNtqCloxBPopAJVzUjW7XqaKaMlTlAnD7GZFBQ5Y73oyyrs/juf1v51VQ/o3KHsnHq78lf8ST5Xz2Jr24Jvjp3DBtb8xDL359Y4SRiRZOI5+4L6oD6T8TupajYZgjbDIFtoaYieBpX4Sgqthkm5S9xJ6QyQ11+3ymKgqEp2x0rtS1kTVsOadsmErNoiKRIZ8Z1UgBVVTBUBV1zJ7Tymxo+Q8Pv0SkKenbbxHxCCCGEEKLnzJ8/nx/84AcceuihXHXVVZx33nnbnWz7448/5jvf+Q6LFi3Kbrvlllu6FRZqmrbNyYa6o6+eQ39y0EEH9di5VFXl0Ucf5fDDD6esrAzLsrjkkkt48803ue222xgyZEiH/S3L4qWXXuKmm27q0I3/V7/61TYn62o/odQJJ5zAoEGDdqp9l156aTZEffrpp7nvvvv2iDxsQP2F3H5Gr/Xr13fpmA0bNmSXx40b1+1rb3lsV6pat/wFkRB14NI1ldKwl4KgSW0kwYb6KJXNMfyGTthvoPbkzNztw9X2hcuO7VatptsC1hhqshk11YqWakWJNwAOKKo7LADK5nBHUQAFJ3OfLXtTVHdqr7bt7R7P7qsAqJnHxO5yUInOn08K8LN3Y2yK2Nz0eis/P9rPYYN06sdfSsvwE/BXfYqvdhG+2kXoyWYCNZ8TqPkcloGteYkVuKFqtHAyidx9ZHiI7lI1bE8Y2xMGO4WWjOCtX+Z+ieEJk/KXYnlysY3ALr1PNoes4Nazbi1t2dmgNZqwaIqlsGw3ZB1ZEGBUUUAmtBJCCCGE2EMtWLCABQsWcMMNNzBmzBgmTJhAYWEhuq5TU1PDwoULWbt2bYdjzjnnHL773e/2UYu31p+ew8qVK/nOd76zU8fceuutWwWUfWXQoEF89NFHnHrqqSxZsgTHcfj73//OAw88wGGHHcaYMWMIBAJUVVXx8ccfU129eaYGRVH44x//yPe+972tzltbW8uLL76YXb/00kt3um1nn302fr+faDRKNBrlqaee6nSIy/5gQIWo7Ss7Fy1aRDqdRtd3/BQ/++yzbR6/syZOnNhhPRLpfAKgLQdPDofD3b6+2DMYmsqgsI/CoIfqFrebf0VTDL+pE/b1cJi6JUXF0X1Y+hZj/zo2SjqO2la9moqhpiKAjWLbbtWqbQOWOygjoDgO4LgVdmSWcTKPO+5qdt12s1naze6oaKR9+VLp2MuG5mj8+SQ/t78fY1GNxc/fjXL9QV7OHmuSCgyiafR0mkZPB8fGbNmAr2YR/kyoqqVaCFR/RqDa/Yy0dV/HUDU8RkLV7lANLG8eljcPxUqiJlvwRmtwdC9pTx6Wv5i0JxfH6J3JAnVNRddwxxxpJ56yWFMbIZayGFsSwmfKz1YIIYQQYk/xta99jfnz53cIF1evXr3VmKHt+Xw+br31Vm699dZOc5PdoT8+h02bNnHvvffu1DFXX311vwlRAYYOHcpHH33Eb37zG/74xz8Si8VwHIf58+czf/78bR5z2GGHcdddd3Hsscdu8/E5c+ZkZ7P3+Xycd955O92uYDDI2WefzeOPPw64la0Sou5mU6ZMwePxkEgkaG1tZcGCBRx55JHb3T+RSDBv3rzs+gknnNDta48aNYpRo0Zl3/BLly7ljDPO2OExy5Ytyy7n5+cTCAS6fX2xZzE0lSG5PoqCHqpb4pTVx6hoihHIhKndGVS72xQVx/BjdSW0cTqGpW0TWrXfrnQIT9v2a/e4k8aIbMKMVmEZfiwzLFWqvSjHo/Lb4/3cvSDOf9emuPezOGUtFtcf5N08nISikswZSTJnJE1jznRD1eb1+Gu/zFSqLkZLRQhUfUqg6lMALN1PvGAC0cJJxIomkwiPkrF2d5KjmVi+AixAScfR43UY0Uoc3UfaW0DaV0jaV7Bbxqr1GholIS+bmmIkLZuxJSHCPhn/UgghhBBiT3DNNddwzTXXsHjxYt555x3mzZvH8uXLWb9+PU1NTTiOQygUorS0lMmTJzNt2jQuuOAC8vLy+rrpWQPhOfRXoVCIX//619x4440888wzvPzyyyxbtozq6mqi0SiFhYUMHjyYqVOnMn36dI4//vgdZhLtu/KfeeaZ3e5Rfemll2ZD1HfffZe1a9cyatSobp1rd1Ecx3E6323PccYZZ/DSSy8BcO211/LXv/51u/vOmTOHGTNmAG6IWVVVtUvfXvzwhz/krrvuAtxA94MPPtjh/hdeeCH/+te/ALeUuf2sdl3R3NxMOBymtrZ2qzFZxZ4lkbaobnYrU5vjaYIenRyvvnvD1N3JTmO0VmI2r0NNRkj78nC2rJAVPcpxHJ5cluQfXyYAOGyQzs+m+AgYXfgdcyzMpi1C1XRrh10sPUCscAKxwsnECidlQlXpFr7THCcz1EYLimNjefJIhkeR9hXuli8bbMehpiWB19QYWxKkOCSz8u7tUqkUL730EqeffrpMLCWEEHuBeDyeDTK6O8u1EF1l2zbNzc3k5OTs8eOZir7TE59bbflaU1MTOTk5291vwIWoL774ItOnTwfc2ew//fRTJkyYsNV+0WiUAw44gFWrVgHwk5/8hP/93//dpWuvXr2a8ePHZ8uan332Wc4666xt7jt//nymTJmSnXntmWee4etf//pOXU9C1IEnnrKobo6zsSFGczxFjscgNIDDVCUVxWzZgBEpB8d2gyLpIt6r3tuY4rfzYiQsCJkKRw7WOXqoziGlOl69i79njoWnaS2+mkyoWrfEnbSsHcsIEiuYSKzI7f6fzBkhoerOciz0WD04FqngEFKhEdhm5+Nt94S6SAIbh32LQwzN8w3YzyDROQlRhRBi7yIhqtidJEQVPUFC1F00depU3nvvPQBGjhzJs88+y+TJk7OP19XVcckll/Daa68BbhXq6tWryc3N3epc69at61BOPGvWLK688srtXvumm27iT3/6EwCBQICHH36Yc889t8M+77zzDhdccAE1NTUAHHnkkXz44Yc7/UeqhKgDVzxlUdkUo6whRiSRJsdrEPQM0DDVcdDi9ZjN6zCi1VhmEMvMkS7+vWhFvcUd70epjm7++PdocEipzpQhOkcO0Ql7duIfMbaFp2kNvtov8dcuwlu3BC0d67CLZQRJhoaTDA0lGRxCKpi5D5TK2LidUKwEeqweW/eRzBlBKjh4t3Txb4mniCTSjCoMMKowgC4TTu2VJEQVQoi9i4SoYneSEFX0hN0Zog7Iv1wff/xxDj/8cCoqKli3bh0HHnggxx13HGPGjKGmpobXX3+daNStmtJ1nblz524zQO2O3/72t3z22We89957tLa2ct555zF+/HgOO+wwNE3jyy+/5NNPP83uP2jQIObOnTswwzHRbV5DY2RhkJIcnxumNsbY1BQjx2vgN/XNY1kOBIqC5Ssg5gmTbq3EbFqLEakg7cvH0eUfbr1hv3yNh6cHWVxr8WFZmg/LU1S2OnxYnubD8jSqAhMLNY4eqnPUEINBwU7+QaNqJPL2JZG3L437npcJVVfhr1m0uVI1FcFXvxRf/dIOhzqKRipQ2iFYTQaHkAoNkzA9w9E8pIKDUJPNeOuWYsRqSOSMxPIW9OrrE/IaGJrK6poIibTNPsVBvIZUigshhBBCCCH2TgOyEhVg+fLlXHLJJSxcuHC7+xQVFTFr1qwdTgC1s5WoAE1NTVx//fXMmTNnh/sdccQR/Otf/2LYsGE73G97pBJ17xFNpqlojFPRHCeetLBsB01V8BoaXkPFow+cYENNtWI0Z7r4K5D2FkgX/17mOA5rGm0+LE/zQVmK1Y12h8dH56ocPURnylCDMbnqzn/pY6fxNK/HiJRhtpRhRsoxIuWYkTJUK7HdwywjuDlcDQ0hGRzqdmsPDMbR9tKKOMdCj9WB45AKDiWVMxzb6N1JCVOWTXVznMKQh/1KQ4S8e+lrv5eSSlQhhNi7SCWq2J2kElX0BKlE7QHjxo3j448/5oknnmDOnDksWbKEqqoqcnNzGT16NOeeey5XXXUVhYWFPX7tcDjM448/znXXXcfDDz/M+++/T3l5OZZlUVJSwpFHHsmFF17I2WefLRWookv8ps6Y4iDD8v1Ek2miSYumWIrGaIqWeIradBJVAY/uhqpeQ0PdQ3+3bCNAIn8caX8RZvN6jNYqLDOA7Qn3ddMGLEVRGJOnMSZP4/KJHiojNh+Wp/iwPM2iGos1jTZrGpM8siRJiV9hylCDo4foTCzSulYVreokcseQyB3TcbvjuDPSdwhXyzBbytFjNW71asMKfA0rOh6GSspfTKpdsJoMDiURHoVtdm9myD2GopH2F6Ok45gt69FjNSRzRpIKDuq1Lv6GplIa9lHdEmdRWRNjS0MUBj29ci0hhBBCCCGE6K8GbCXq3kAqUYVtO0RTFtFEmpZ4moZoktZkmmTaxrLB1FR8hobHUDH2xPEM7RRGZBNm83rUdJS0V7r4725NCZuPN6X5sCzNgso0CWvzY92emKoLFCvh/uwj5ZgtGzOVq27IuuV4q20cRadlyDE0jZ5OPG+/vWIoADXRhJZsJe0vIpkzole7+DuOQ11rEgXYtzTE4LBXvgjcC0glqhBC7F2kElXsTlKJKnqCVKIKIbpEVRWCHp2gR6c4xw05Emmb1oRbrdoQTdIST1MfTWLZDqqi4NXdSlWP3o1u2bubapDKGYHlK8RoXu928U+2kPblgyJd/HeHsEfl5FEmJ48yiacdPqtM80F5mnnlaZqTDq+tS/HautSuTUy1DY7mIRkeRTI8aosHHLREA2ZLWXZIADNTyWpEq8gpe5ucsreJ5+5D46jpRIYei6MN3KpJ2xPGNoLo8Tp81Q2kQkNJhobjGP4ev5aiKBQGPTTFUizd1EwsmWZUYXBgjdEshBBCCCGEENshIaoQA4iitI2TqlEADMv3k7JsokmLaDJNS8wNVFsTaepbLUDBo6v4TA2P3sWu2X3A7eI/HstXhNm8DiNSieUJYZvb/4ZI9Dyv7nblnzLUwLKdnpuYamcoCpY3n5g3n1jR5A4PeRpWkrv2RYJl7+BtXEXp53djLfknTSNOpmnU6aT9xT3Xjv5EbdfFv2kderSGZHgUqUApqD3/n/mwz8DQFFbXREimbcYUBwfUuMxCCCGEEEIIsS3SnX8PJt35RXfYtkMsZdGaTBNNpGmIpogk0sSTNpZjY2SGAPCbev8MVe0URssmPC3rUdIx0r78AV1puCfoysRURw7WGRRUyfUo5Hrb7pUeHQKgjZpoIrz+NcJrX8SI1bhtRKW19HAaR08nVnTAwO3q7zhoyWa0VCspX3Gmi39+rzzflGVT3RKnOORlbGmIoEe+lx2IpDu/EELsXaQ7v9idpDu/6AnSnV8I0WtUVSHg0Ql4dAjBSCCesogl3WC1KZqiMZaipiWBjY3P0AmYOqbeT/6jphqkwiOwfAUYLZku/qpO2pMHqlTD9YWuTky1LV6drYLVXI9Cnlch16O665ltYY/SpWDf9oRpGHs+DfueQ6DyE3LXPI+/5guClfMIVs4jGRxK4+jpNA87oVe6vfcpRcHyhLHauvjXNLgTb/VCF39DUynN8VHVEidZZjO2NER+wOzRawghhBBCCCFEfyEhqhAiOwRAXsBkaJ5bYdYST9MUTVITSdAYT5KybDyaRsDU8Rp9P56qbQZJ5O/vdvFvWoceq0FpV1jvKCqOqoFq4CgajqrjqLo7lupArULsJ0qDKufu5+Hc/TzZiam+qLZoiDs0xm0aEw6NcYeUDfE0VKYdKlutTs+r4E5m1Raqbg5Y1Q5Ba9stZKq0DjqS1kFHYrRsJHfNC+RsfBMzUkbxl3+lYOlDtAz7Go2jzyAVGtb7L8zutGUX/1it28XfX9KjXfw1VWFQjpeaSIJFZY2MLQ1RmiMTTgkhhBBCCCEGHglRhRBbMTSV/IBJfsBkREGAlkSalrhbndocS9EQs9AUlYBHx29qqH0VmCgKaX8xaW8eWrIVxU6i2GmwU6jpOIoVd+/tFGo6ClYaxbEAB1BAIROwGm7gquiZsFWTiat6yOaJqTpudxyHaBoa4w6NCdu9jzvZgDW7LbPelHBwgOakQ3PSYUMXrq0AQdMNV3M8+YQ9V1BceCHTUu9yTMvLFCQ3kbv2BXLXvkBD/gE0jJpOeshhKL0wjmhfcXQvqeAgtGQTvtpF6P7qzV38e4iiKBSHvDRGkywpbyaetBheEOifw4EIIYQQQgghRDcNnL8UhRC9QlUVwj6DsM9gSK6PWMqiOZamLpKgIZqksjmFAvhNnYCpoWt90O1fNbC8udt/3E6j2Cn3ZmXu7TSKlUS1YijpBIoVd9fTUXf/bFWrk6lq1UHVcToErSqgSmVrNyiKQsCAgKEwJNT574xlO7Qk24esmft2la0NCYfmhBu4tiTd0LUl6S7T0nYmg2f4GnACR6uLuUL7L19TPyOv/gvy6r+gbEEhTysn8aZnGnjC5HoVcjwKYVMh7FUJexRyTHe4geE56p4RFCoKlifX7eIfq8MXrycVHEYyZxiO7uuxy+T6TaLJNF9VR4inLcYUhfrPMCBCCCGEEEIIsYskRBVCdJmiKPhNHb+pUxr2kki7gWpTLEltS5K61iRp28FnaAQ8Wv+ZsTvTld9hB4GRY7cLV92gFccNWhUrgZqOo6ZjKHY6E7Ra4FgdhhDInAi3BlLJLLuPO4rqblPcxxxFyYSw7r0DHdfb9ssMSbC309S27vtAuPP9LdutWG0LVbe8udsP5PeJA7g3Xs0Z6de4QH2LoUotNzKHa+NP8VzrUcy2TuFtZ9Q2rzEooHDx/h5OHGlgantAmKrqpAPFKOkYnqbV6LEakuGRpPylPTaesN/U0VWV9XVREimbfUtC7vjLQgghhBBCCLGHk79shBDd5tE1ikIaRSEPIwtsIok0TZlJqVriKWrTSUxNJeDR8Bla/x4nUVFxNA+O5oEdZZZ22g1a7dTmENWxURwbcJfBcdczNwUHbNsNZR0Lxbbcx2wLFatdIAvQtt1xl60kKCppX4EMMbATNNWtFs3r0uSMQeBayhNXULvhPYrXv0A4spoL9He5QH+X9Z6xvOk/lXfUI6lPajQlHKqjNhWtDn/8JM6jixNcMN7ktNEmXr0f/45nOLqPZHAwWrIJb+1it4t/aDi24cdRzV0OVE29bcKpGPG0zbjSELl+mXBKCCGEEEIIsWeTEFUI0SN0TSXXb5LrNxme7yeSSNMcT1PbkqAxlqQxlkJFIeDR0NXtd/HtDznrVsWlHSi4KauRGVO13WRWTqbuNLPJwdm8LbtPpjI183/ZQQPsdiGsY4Pj4DgWphWlKFmOGanE8oSwzZweeY5iax6PF/Y9iep9TqS5YTnhNS8QKv+AEYmvuCrxFZd7HqZp5Kk0jTyViFHAS6uT/Gt5kpqYw32fJXh8SZLzxpmcuY9JwOgHv8g70qGLfy2+aA3oJo5iYutebCOAbfhwVDPz5YKJrZldrop2J5zyUd2S4MuyJkYVBjB1d/gDTVFQVQVNVdBVBVVxl/eIoRGEEEIIIYQQey0JUYUQPU5RFEJeg5A3M45q0qIlnqK+1e3yH0un+7qJPULBDX0Ud46qbALc1pkfcCfdUjaHw6qioCjukUpmu4qaXXb3IbOPQiyVw7qmIDlKFYXpCoyWTaT9BW7FrOgdikI8fzzx/PHUTrya8LpXCK97GT1eT8GKJ8j/ai6RQVO4fMRJnHn6ZP673uHJZQkqWx3+8UWCJ5cmOHusyTljTXI8/XxMUFUnHShxK6EtdzgLNdWMFq/LVlc7qKAZmQnYTGwz4IasmicTsmZuqtnhWxBFUSjJ8dIQTbK0oskd4MJxt6uqgqa47we1XZCqqwqmrqKrKqauYGgqqqKga+3CV0VBy6xrmWN11X1MCCGEEEIIIXqLhKhCiF7nMzV8pkZxjpeUZWPZOyz13KO4GWnHMFVpH6Yq7NIwBpbtUJPrZ11dgLVNuRQmN5Ebq8bRdHeGdaWfh3R7OMubR/24S6gfewHBinmE17yAv24xoU3vE9r0PqVGiKGDj+Lcw4/lpdZxPL7cYmOzzaNLkjy1IsmZ+5icv59Jvq+f/5wUDUfX2OY7s228YCuFYsXQW5tR7LYvQpRMuKq71aq6H9sI4uhuwGrrHvJNE8fnzf6uOo6D7YDtOFi2g+042DakLYdkyiYST2Nl9nEct5obBXdYDNwvFxQVN4Rtq2zNBKyG5gav7q0taHW/pHDD2rYvMtz7tmMVNRPobvF427Z+PRSJEEIIIYQQYreQEFUIsVu54UZft2LPoakKpWEv+QGTqmYfG+pyaWzMpSi5iWCkEsuTg20G+7qZA5+qExlyDJEhx2A2rSW87hWCmz5ATzQSXv9fwuv/yzVmmIsHT+HDkVP44/oxrGqCfy1P8sxXSU4bY3DROA/FgX4epm5L+/GCt+Q42TGCFTuFHq9FiVZsHtJC0UAzsFUD28zBMkM4uhdb8+LoXhxj5yuq3dB1cxDbFsa2hbC2k3bDWTIhrNsS2urD26Z8a1tuqxZXFVBRsoGroiioZCpnFdA1BV1VURXQVDek9Xt0crw6QY8uQasQQgghhBADnISoQgixBzB1lWH5fopCHsobfJTX5VPfWEZxohJvMkLaV4CjdW28SrFrkuFR1BxwPTWTvoWvbjGh8vcIbvoQPdlE3rqXOYOXOcWTz6oRR/FA0+E83TiG51ameHFVipNGGly0v8nQ0AD5JkFRcDRj+797bQGrlUSPVmFEygE3XHWHAfBieXKxDT+27sXRvNi6F9Tt//NEVRRUrWcCS6d9xStuKOs4m+8dx60GTzsOiRTYTjq7n+2AbTuYujt8SVHIQ9jnDmMi47sKIYQQQggx8EiIKoQQexCvoTGmOEhxjofyhjDVNYUYzespaq1BM91ASrr47yaqRqzoAGJFB1A9+Tr8NV8QLH+fYMWH6Il6xlW9yF28yK9yCniNI5nVcgSvrB3Df9elmDpMZ8b+HkblDpAwdXtU3e3qr/uw22+306hWEsWKYbQ0oto2jqJkxlb1YBl+bDMH2/Bng1VH8/T4zHOK4o7NunkU452XSFu0JixqIy3oqkLQq1MYdCfZy/EamLq8H4UQQgghhBgIJEQVQog9UMhrMG6QQWnYy4a6AiqqNuJvXU9eYhOOPx/b8Pd1E/cuqk605BCiJYdQbX8bf/VCQuXvEaiYhz9Zx9d5ka97XqRaLeLp5BG8sPFIvrVhFFOGGMzY38N+BQM8TN2SqmOrOrT/PXUcFDuJYiXREvUY0SrAwVFU0DzYmgfbDLlDAmSDVS+OZvbZ0wDw6Boe3f35pSybaNJidU0rCq34PTqFAZP8gEnIa+Az97KfsxBCCCGEEAOIhKhCCLEHy/WbhH151OYGKKsuprxqDeGWcoJGM1agcIfdokUvUQ2ipYcRLT0MxUrir/6MYPl7BCvnU5yu4Tr9Ba7TX2CdXcILVUdy76Yj8RePYsYEL5OL9+Kfl6K0G3s1hNW23bFQrCSqlURvrcBoKXM3qzqOauIYPtJmDo4RyI61amteUHd/YGloKmGfSthnYNkOsaTFxoYY6+uj+AyNsM/t9p/jMwiYmoyjKoQQQgghxB5kL/5rTQghBgZFUSgKecgPlFJTmMfGTaVEalaS21iB1xfE8ub2eDdo0TWOZtI66EhaBx1JtZUgULmA4Kb3CVTOZyRVfEd9lu/oz7K6YRAvvHsUr+cczbGTxnBoqQRsWYqGo/uwdF/H7XbKHRIg1YoZr0dxMlNIaSa25iHtL8byFmB5wn0yxIWW6dof9Oo4jkMsZVEbSVDZHMejqYR8OsUhLzleg6BXl3FUhRBCCLFLjj/+eN55553s+rBhw1i5ciUeT+cTed5+++388pe/BOCiiy7iiSee2OH+b7/9NnPnzmX+/PmsX7+epqYmNE0jFAoxfPhwxo4dy2GHHcaxxx7LIYccslP/rnUch3feeYfXX3+d9957j7KyMurq6ohGo+Tk5JCfn8/EiRM5+OCDOf300zn44IO7fO4t/fznP+fXv/51dv26667j/vvv3+nzrFu3jtdee4133nmHRYsWsWHDBiKRCKFQiKFDh3LUUUcxY8YMjjvuuG63VfQPiuM4Tue7if6oubmZcDhMbW0tBQUFfd0cIUQ/kUzbVDW2UlG+FmpXkaPE0XMKcbYMoUSfUdJxApXzCZW/h79qAaqdyj62wh7KR+ZRePc9jvySYRT4VEImEqp2RduQAOk4WiqKo6jYZphUcBCWJw/bDPZ1CwGIpyxaE2niaQtdUwl6dEoyFao5PgND6z/jqKZSKV566SVOP/10DEMmrxNCiIEuHo+zdu1aRo0ahdfr7evmiJ2wZYgK8Kc//Ykbb7yx02O7GqIuW7aMb3zjG8ybN6/L7ZowYQKLFy/e5mO2bdPc3ExOTg6qqjJ37lzuuOMOlixZ0uXzjx49mu9///tcc801XQqM2ziOw8iRI9mwYUN2W15eHhUVFV0+z+eff851113H/Pnzu7T/8ccfz0MPPcTw4cO73E7RuZ743GrL15qamsjJydnuflKJKoQQA4ypqwwrDFEUnsCm6kHUln+F1riBoKGhhor7pJuz6MjRvUSGTiUydCpqKkqg8mPMDe+RU/MZ+6ll7Jf+Fyz7F4uXjOR56yhe5UgS3mIK/SoFPoUCn3tfuMW9R9/Lg9Z2QwLYnjCKlUJNteCtXYKje0h7CzIVqnmZYQP6htfQ8Bqbx1FtTaT5qiqCqioETI3CoAe/R0NXVXRNQVcVdE117zPLQgghhBCdufPOO7n66qvx+3d9voTPP/+cE044gcbGxuy2kpISDj30UEpLS1EUhbq6OhYvXsyqVatoq9drv//2xGIxrrnmGubMmdNhu9/v57DDDqO0tJRwOExjYyPV1dV8+umntLS0ALBmzRq++93v8tprr/Hss892+fm89dZbHQJUgIaGBp577jkuuOCCLp1jxYoVWwWoY8eOZeLEiRQWFtLY2MiHH35IWZk7HNXbb7/NUUcdxXvvvcfo0aO73FbRf0iIKoQQA5TX0Bg9pIii/DCVFYNp2rQcvXYD/mAeij+3r5snMmzDT8uwaTBsGg3JCMrGj0itepcxsS+ZqK5jorqOW5nDp6l9eb7+KF60jqCGvG2eK2hAoV8l36tkA9ctg9Y8r7LXdB13NANLy8fygpKOoceqMVorsI0AKX8xlq8Qywz36RcLhqaS6zfJ9YNlO7Qm0qyvi2I7TnYUDlVR0FRQVQVdVdFUBa+uYeoKXkPD0NrC1kzQ2racCWClilkIIYTYO1VVVXHPPffwk5/8ZJfOk0qlmDFjRjYQHTx4MPfeey9nnXUWqrr1l7s1NTU8++yzPPLII6xZs2aH504mk0yfPp0PPvggu+3www/ntttu46STTsI0t55ENJ1OM2/ePP7xj3/w+OOPk0wmaW1t3ann9NBDD2WXfT4fsVgsu72rIWqbffbZh6uvvprLLrvs/7P333F23uWd//+6+3369D6qtiQX2XI3LrKNbAwGUwJOgmNICMlClsDuN/vdhCTLNwkhAZLfprAkkIUNBrKmheKAbcCWi2Rs3GVLsi3J0kia3uf0crffH/eZMyNbVvNI067n43Fzyl3PzDE65z3X5/rQ2dl5xDrf97nzzjv5+Mc/TqFQYGBggN/4jd/gsccek89oi5AM51/EZDi/EOJkTOUKDPbuJz/4CoaXw062oloyxH+hUisZ4gOPEevbRmxsJwrVnp8o7LfP4xfGVfw8uJyD5TjjBZ+Sd5wDTh9XgTpLCYPVatB6ZYfOFR3LZKh24KM6ebRKjkBR8M06nFgrnt2Ab8QXZP9gzw/wgwDXC/CCAM8PF9f38fyAgAAIr1tFQdVAV8KwXFNVLEPB1FRsQ8PUtFq4aurhJFjH+gAvw/mFEGJ5keH8i9fs4fxXXnllbch9Q0MDPT09xxyifLzh/N/73vf41V/9VSAMHHfs2MG6detO6Lr279/P2rVrj7rO930+/OEPc+edd9ae+9M//VM+85nPnNCxAQYGBvj4xz9OOp3mgQceOKF9crkcbW1tteD1S1/6Er/3e78HgK7r9PX10draetzjPPLII/T09PCBD3wATTv2H+V/+MMf8iu/8iu1xz/96U+5+eabT+h6xbHJcH4hhBBzri4eJbn+fMZbOhg5/DKFsUMEKBjJZmzTms5gxALhm0kyq95KZtVb0UoTxPt/QaJ/G5GJlzirtIuzSrv4oPJ/KLRsInP+ZkabrmTEtRkvBowV/SNuxwvV21KAH8BEKWCiFLBv0gfgJ684bFnp8rFLbBLmEn8jKCq+mcA3E+C7aJUskfEX8XUb16rHjbXiWfUE+sL54qipChoKxgkUzPqzQtYwaA3IFX1c38ULAnw/rHANqsftqouwqilWay8ghBBCiMXvjjvuYHJykj179jAxMcH//J//sxaSnoqf//zntfvvete7TjhABV43QIUwhJwdoP6X//JfTipAhbAq9vvf/z7PPvvsCe/z/e9/vxagrl69mo985CP8y7/8Czt27MB1Xf7v//2//MEf/MFxj3Pddded8GRR73nPe7j88strw//vueceCVEXIQlRhRBiGVFVhebGRhrq3sTE2AqyA/spTPSTDnSCSAMxy8TQpd/iQuPZDaTX3kp67a3ohRES/duI923HTu8nNvwMseFnaFUNCq2Xku3aTL77sqOGgJ4fkC4HjBUDxos+Y8WAA1Me9+532HrIYceIyx9cZnP5cqlKVXU8ux7PrkdxS+ilMYz8EL4RxY224Eaa8Kw6UBfPxyVVUVC1EwtcS47HwfE8mZLD2uY4jfH56xMrhBBCiLmjaRp/8Rd/wa//+q8D8Pd///d84hOfOOURrP39/bX7K1eunJNrBPjsZz9bu7969Wo+97nPnfKxLr744hPedvZQ/jvuuANFUfjABz7Ajh07autPJEQ9WVdffXUtRD148OCcH1+cfvJNWQghliFNU2lu7WbNhdeydtNmVrY10+iNU86NM5ouki25eJ50e1mI3GgLk2e/j94b/pGDW77M+IbfoBLvQvUd4oOP0/7U51lz3x20Pf23xAafQPGc2r6aqtAQUVnXoPGmToNbzzL5L5dG+PstUboSKuPFgD/dVuTvniySd5bX7z/QbdxoC068nUDVMbOHiY48Q3ToKcz0QdRyGpZYByTb0GhPRciWXF7om+LgWA7X8+f7soQQQggxB371V3+VCy+8EIBsNsvnP//5Uz7W7L6nPT09b/japo9z//331x7/3u/93hlpIXHo0CEefvjh2uM77rgDgNtvv702JP+FF16oBapzaXYLJc87wV5cYkGREFUIIZYzVSPS2E3zhmtYfd4VrGtLclYkjeUXmCo6jOXKFMruUsuOlgwn0cXEhvdzaMuXOHTD/2Ji3W040VZUr0Si7xE6nvhLVt93By3P/gPRkWfBP/qHtXObdL50c4xfWRc27r/vgMNH7suxY9g9ky9nYVAUfDOOE2vDibSgBA7WxMtEh58hMroDIzeA4hbn+yrnjKootCRsbENnz3CW3QMZsiXn+DsKIYQQYkFTFIW//Mu/rD3+4he/yODg4Ckda/aQ/B//+Me8+OKLb/j6ZgeZEPZiPRO++c1vMj010BVXXFFrTdDW1sZNN91U2252tepc2blzZ+1+d3f3nB9fnH4SogohhADdRGlcTWzNVbSsvpANTSbnxjJ0xRV8YDxfZjJXoeTIX0wXJEWhklrN+Lm/ycGbvsrh6/4nk2vfhWs3oLl5UocfoPOx/4/VP/0gzc//M/bYLgiOrDi0dYXfu9jm/3dDlLaYwnAh4L8/VOCfni1Rcpdpiq5qeFYdTqIDz0qglSexx14gNvQU1viL6IVR8JdG0By3dFriNkOZEs/3TjEwVcT3l+nvXQghhFgibr31Vq644goAisUif/VXf3VKx3n3u99du18sFtm8eTN/+7d/e8Qw/5O1ffv22v22tjZWrFhxysc6Gd/4xjdq9z/wgQ8csW7247vuugvXnbvPeYcPH+bBBx+sPb7xxhvn7NjizJEQVQghxAwzCs3r0FZcTrLtLLojFc5LFFjXZFMfN6m4PqPZMumCg7tcg7WFTlEo169nbOPv0nPznfRe8zmmVt+CaybRK2nqeu6l+9FPsupnH6Jp51ewJvccMUz9wladf3lrnLevDfui/mhvhY/+LM/usaURFp6qQLNwI004sXZ8zcDI9REZfZbo8LMY2V4UpzDfl/iG6ZpKRypCEMCu/jR7hjOU5Q8nQgghxKI2e6Kmr3zlKxw6dOikj3HDDTdw66231h6Pj4/zh3/4h3R3d7NhwwY++MEP8oUvfIEnn3zyhIPHw4cP1+6fc845J31Np+Kxxx5j3759ABiG8Zrq13e/+93E43EARkZGuO++++bs3H/wB39QG8K/YsWKI36eYvFYPDMlCCGEOHPsFLSdD8l2zMmDNGaHaIyZFJMpMhWf8VyFbMXBLfpEDJ2oqaPKn+UWHkWl1HQ+pabzGd34EaJjzxPv20Z84HGM0jj1+++mfv/dVKJt5Lo2k+3aTCW5iqih8F8vi3B1l8HfPVmkP+vzB1sL3LbB5IPnW5iacvxzL1WKgm/E8I0Y+C5aJYs9tpvAiOBEW3EjzXh2PSiL9z+IuqhJxPU4NF5gKlea78sRQgghxBtw4403cv311/Pwww9TqVT49Kc/zf/5P//npI9z11138cEPfpAf/vCHteeCIGDPnj3s2bOHb37zmwDEYjHe8Y538JGPfIQbbrjhdY83MTFRu59KpY57/n379vGP//iPx9zmAx/4QK3y9mhmD9F/29veRlNT0xHro9Eo733ve2vbff3rX5+TsPPrX/863//+92uPP/vZz2JZMqHnYiQhqhBCiKNTFIg1QaQeciMw0UOkOELEjNHcWkfe8cgUHSbyFSYKZRQgaupEDA2Wcca2YKkahZaLKbRczOiFHyM68iyJ/m3EBn+JWRiiYe93adj7XcrJlWQ7N5Pr2sxl7e185W1x/vnZEvcfdPjOSxWeGHD571dEWNdwAtO/L3WqjmfX41l1qG4BM3MII3sY327AibXj2o0E+umfIOF0sPRw0qmxdFhhe3Asz6qWJIa2eMNhIYQQp0kQwBIYkTGnjGj4WXqB+MxnPsM111wDhIHeJz/5Sc4+++yTOkY8HucHP/gB9957L//wD//A1q1b8f3XTkiZz+f5zne+w3e+8x3e+c53cuedd1JfX/+a7bLZbO1+LBY77vn7+/v5p3/6p2Nuc+mll75uiFoqlfjud79be/zqofzTPvjBD9ZC1B//+MdMTEzQ0NBw3Ot7PU8//TQf/ehHa4/f//73c/vtt5/y8cT8khBVCCHEsakaJNvDQDU7CBM9qNk+EpE6EvUJWlI2uZLLVKHCVMFhLF9CU1Rilo6pS+CyEAWaQb79CvLtV6C4JWJDT5Lo20Z05GmszCGszDdpeumblOrXke3czB9feC3XdCX5+6dKHEz7fOL+PLefa3L7eRa6unC+IMybI6pTHbRyBrs4hq9HcWJteJEWPCu56KpTVUWhKWGRA14ZzZF3Ata0xEnaxnxfmhBCiIXEKcBfd8z3VSwsfzIA5vGDwTPl6quv5m1vexv33XcfnufxZ3/2Z9x1112ndKxbbrmFW265hdHRUR5++GEee+wxnnnmGZ577jlyudwR2/7Hf/wH1157LY8//jiJROKIdbMf5/P5U7qWk3H33XczNTUFQF1d3etWmF5//fV0dXXR19dHpVLh29/+Nv/5P//nUzpnT08Pt956K6VSOLLnggsu4Mtf/vIpHUssDIvr07wQQoj5oxlQtwK6L4fmc8BzIN2P4ZWojxqsbopxbkeSs1uS1EVNihWP0VyJbNHF9aR/6kIV6Da5rs0MXvk/6HnrvzF80SfIN19EgIo9uZfmXV9l9c9+i9sO/n/86PztvK2ziBfAN3dX+MT9eXqmpGfmEVQDL9KIE2snUHWs9AEiw08TGX0ePT+I4pXn+wpPSUvcYiRb5vneKfpl0ikhhBBi0fnMZz6DUq2O/c53vnPETPGnorm5mdtuu42///u/Z9u2bUxOTrJ9+3Z++7d/G12fqdfbvXs3f/qnf/qa/WdXd6bT6eOe7/rrrycIgtcsK1euPKHrnT2U/7bbbnvd4fSqqvIbv/EbR93vZAwODnLTTTcxNDQEwJo1a/jpT39KMpk8peOJhUEqUYUQQpwcIwLNZ0OiFaYOQ7oPilMQa8TSTay4SWPMpOC4ZEsuY7kymaKDj8/MOP+gej+AQKk9rVTvKIQjoBTCdeHj6tqZzWe2O2KdgqKA+up9lQU1qmpB8s04mZVvIbPyLWilSeIDj5Lo205k4kWiYztZNbaTf1Y0els28aWpK/iPyUv42M99PrjR4rb1JppUpc5QFHwzjm/GUbwKWnkSozCMZyRwYm24kSZ8M7lo3pS6ptKeMkkXHXb3p0kXKqxpjmMb0tZBCCGWPSMaVl6KGUZ0vq/gNS6++GLe85738IMf/ADf9/nUpz7Fj370ozk7vq7rXHPNNVxzzTV8+MMf5uabb65Vpn7lK1/h85//PJFIpLb97PDzpZdemrPrOJqhoSF+/vOf1x7fcccdx9z+Ax/4AJ///OcBePLJJ3n55ZfZsGHDCZ9vfHycm266if379wPQ3t7OAw88QHt7+ylcvVhIJEQVQghxauwktJ4HyQ6Y6IHcEKg6RBtQVJ2YGS7NcZt82cXxfYIAAgIIwA8CpmvZgiBc/OpflL0gqD32g9nrw2N41dnkAz88nl/dHsAn3IZget30/bD5/Uy/1ukgd9bDadUwVp2+Xw1pa2EsYGgqlrF0B3R4dj3pNbeSXnMremGERP824n3bsdP7WZF5hs+qz/AXtsH93kX8x86r+KPeS/ivVybpSkqo9mqBZuJGmiDwUZ0c1tQ+zMwhXLsBN9aGZzcQaOZ8X+YJSUUMbEPl8HiBTMllbXOc5oRMjCCEEMuaoiyooevi9X3605/mRz/6Eb7vc/fdd/PUU09x2WWXzfl5rrrqKv7kT/6EP/mTPwHCfqRPPfUUmzdvrm1z7bXX8q//+q9AGHIePnyYFStWzPm1APzbv/0bnjczeuq66647qf2//vWv89nPfvaEts1kMtx8883s3r0bgKamJh544AFWr159UucUC5OEqEIIIU6dokC0Aew6yI/AxEHIDIEZDSekUhQ0FZKR0/PPTS1cpRrI1oLYMDANqK6r9rz3q+vDfasBLTOB7fQxPX8mzPX9AK96Hi/wCfwwxC04LiVHIRUxlvxEWm60hcmz38fk2e/DyPaS6NtGon8bZq6ft2tP8nbtSbL5CA88cCljq67jggsvQdWkb+ZrKCq+mcQ3kyhuCb00FlanmgncWAdupBHfTBz/OPPM0jU66iKM5yu80D/FqoYYKxqjMumUEEIIscCdd9553H777fzbv/0bAP/jf/wPfvazn52Wc731rW+thagQDm+f7frrrz/i8be//W3+8A//8LRcy6kOyZ/2b//2b/zVX/0Vqnrszzr5fJ5bbrmFZ555BoBUKsVPf/pTzj333Dd0frFwSIgqhBDijVNVSLRBtBGyQzBxIBzmH6kD6/SFQmFVqI8a+GHKqRmcqURzsuBweDzPWK5MQ8ziOJ+plgwn0c3EOb/BxIbbsdIHiPc9QqxvG4nSGO9RtsPh7aR7E+Q7r8FbdR2lxnMX3YRKZ0Kg27i6DYGHVslhT7yMr1u4kWbcaAuu3RhO6rZAKYpCU9yiUHHZN5IlU3JY0xwP/6gghBBCiAXrz//8z/n2t7+N67r8/Oc/Z9u2baflPLZtH/H41T1IV61axVve8pbaMPsvf/nLfOITn3jNfm/Us88+y65du2qPL7vssuOGodOeeeYZXNelr6+PrVu3ctNNN73utqVSiXe+85384he/ACAajXLPPfdwySWXvLEXIBYUCVGFEELMHc2Aum6INUOmHyYPwVQfxBpmekMFAQRe9dZ/1f1jLVDro6oo1MbsK1q1r6QCXgV0KwxujcjrXuZcqI8aWHqC3okC4/kyqYiBqS+jsFBRKNetpVy3lvHzfgtr/CXGX3yYFeO/oJEMqb77oO8+HLuJYssmSvXrKNWvo5xcFbZ9ECFFw7NSeFYKxS2i5wcxcv24kSacRBeu3bSgw9SoqWPpWjiJXMllTXOMjlQEVfrjCiGEEAvS2rVr+dCHPsRXvvIVIKxGffOb3zzn53n++eePeHy0ofqf/OQnayFqT08Pn/zkJ/mHf/iHOb2O2VWoGzdu5MknnzzhfW+99VZ+8pOf1I7zeiGq4zi8973v5cEHHwTCwPjuu+/m6quvfgNXLhYi+RYjhBBi7hk2NK6FeAtMHoZMHxQmw3WKAqhh9ary6kUD1QRNB9UIQ1lVD28VNQyTFG3WfXXmPkApE1bClqYgPxZeh5UAfW7/oj0tamrVyXWKDKSL2LpG3F6G/7QqKuWm84hvPo9d6f/E/Y8/zQW5R3mr9hTJ0hjG4QdIHn4AAF81KdedFYaqDesp1a/HjTQvmgmWTqdAj+DqEfBd9NIkenEMN9qCE+8Me6ou0IpeTVVoS0Zqk05lig6rm+JEzIUb/gohhBDL2ac+9Sm+8Y1vUC6X2b59O47jHHP7v/u7v+OCCy7gxhtvPKHjFwoF/vqv/7r2uLW1lU2bNr1mu+uuu44PfehDfO1rXwPgH//xH0kkEvzlX/7lib+YY3Ach7vuuqv2+HgTSr3aHXfcUQtRf/jDH5LNZkkkjhxl53ket99+O/feey8QTrD13e9+94R/VmJxWYbf9IQQQpwxVgLazoNUB7iVo4eftfB0+v4bCNPsFKS6oJKD4tRMoJobA8M6LYGqoSmsaIgSMTV6JwpM5irUxcxlmwl2pAzueMuV/GDvxbzphRyXsYuL1X1sUvazSd1P0i8QmXiRyMSLEE5YSkZN0W+fzXh8HbnUOtzGs0nEEtTbChFjGf4gVR032gy+g14aRy+O4ERacRJdeHbDgg1TUxGDiKFxeKJIplqV2hy3UJbrfwxCCCHEAtXd3c1HPvIRvvCFLwDwy1/+8pjbP/nkk/y3//bfuPTSS/nQhz7Ee9/7XlpbW4+67RNPPMHv//7vs3Pnztpzf/RHf/S6Q+g/97nPsXfv3tow+M985jPcf//9fOpTn+Kmm27CNI8++eZLL73EP/7jP9LX1/e6133vvfcyNjYGhK2I3v/+9x/zdb7aO9/5ThKJBNlslkKhwPe+9z1++7d/u7Y+CAI+/OEP8+///u8AqKrKN7/5Td75znee1HnE4iEhqhBCiNMvUn/mzqUoYVhqJcJAtZwNg9TsUBisuqPVCtVkOPR/jk7ZkrCwdY1DE3lGcyUaoha6tjzDI01VuG2DxeXtOne9eBn35S7lrpLPVMmj0x+sBqqvcKG6n3OUwyT9NMnC01B4GkbA36uwP+hgh7+WXcpZ9BhnMWGvIhXRqbMV6m2FBlut3a+31TBw1VlagZ1q4EZbUDwHvTiKXhzFjTTjJLqrYerCe62mrtKRspnIV3ihL82qxiiddVGpShVCCCEWmD/5kz/hq1/9KoVC4YT3efrpp3n66af52Mc+xtq1aznvvPNoampC13VGR0fZsWMHPT09R+zznve8h49//OOve0zTNPnZz37G7/zO7/Dtb38bCIPYd7zjHUSjUS677DLa29upq6ujVCoxOjrK7t27OXjw4BHHWbt2LRdddNERz80eyr9582a6u7tP+LUCRCIR3vOe9/CNb3yjdrzZIeqXvvSlI86xdu1aHn30UR599NETOv4Xv/jFk7oeMf8kRBVCCLF0KQrYyXBJdc8KVAehmAavHFamWok5CVSTEZ2zWxL0ThYYzZZI2Aa2sXzDo5UpjT9+U7T2OAgCim6KydJ6Jks+T5cCHiqUsDP7aczto7O4j9XOPtoY5Wyln7PVfm5jG/hQzJvszK3meX8tO/yzeMhfSz9NzJ5IzNagzlboTKhc3KpzSZvO6joVdQGGjScj0AzcWCuKV5kJU6OtYZhq1S24MFVRFBqrk069MpKnf6pIyjZpjJskbJ2YpWNoC7OaVgghhFguWltb+cQnPsHnPve54267ZcsWnnzyySMC0v3797N///7X3ScSifDHf/zH/PEf/zG6fuzoKRKJ8K1vfYt3v/vdfPrTn+bFF18EwrYAjzzyyDH3XbduHR/96Ef52Mc+dkTV6vj4OPfcc0/t8ckO5Z+933SIun37dnp6eli9ejUAIyMjR2y7b98+9u3bd8LHlhB18ZEQVQghxPJwtEC1OAm5aoWqV5mTQNU2VFY3xbB1jYGpIo4bkIjIP7cQhmtRA6JGGHSGDGBTdYEsUChNYk/uRRvfgzGxl3h6LxGvwOXKHi5X99SON6Gk2BWcxTPeWp7yzuIFbw1D+ShDeY9nhjy+8nyZOkvhkjadS9o0Lm7TaYws3vAu0MxqmFpGLwzNhKnxLjwrteDC1KipEzE0io7HVKHCcLaEpihETI2GmEl91CRu60QNTSaiEkIIIebBH/7hH/KlL32JdDp9zO1+93d/l9/93d9l165dPPLII/zyl7/k5Zdf5tChQ6TTaYIgIJFI0NbWxgUXXMANN9zAbbfdRn39yY1G+7Vf+zVuu+02HnnkER544AG2bdtGf38/4+PjFItFkskkDQ0NnHPOOVx22WXceOONXHnllUc91re+9S0qlQoQTvT0vve976SuZdqb3/xm2tvbGRwcJAgCvv71r/Pnf/7np3QssfgpQRAE830R4tRkMhlSqRRjY2M0NjbO9+UIIcTiFARQzlR7qA5CKR32bzUjYMZPOVANAhjPV+idKFB2PeqjFq/TCkocT+Bj5PqxJ/diT+7BntiDlTmIEnhHboZCNtLFAWsDP3cv4q6pc5hyj/z9rUqp1VBVZ2Ozhq0v3vBOcUvopUkC1cCJteHEO/Ctujk9h++5HNzxKKs2XYOqvfE/BrieT9HxKFQ8PN/H1FVilk5z3CIRMYhb+rKu3hZCiPlWKpVqlXa2fXom5hRimu/7ZDIZksnk6/ZMFeJ45uL/t6bztXQ6TTKZfN3tpDRGCCHE8qYo4YRUdgrqVsxZoKoo0BQ3sQyV3vEC4/kS9RELfRGHdvNGUXES3TiJbrIrtoRPeWWsqf1hqDq5F3tiD0ZxhGSxl03FXjZxP/+vaTLUvInHtYv5Xn4TT0wmOZj2OZiu8P09FQwVzm8OK1QvbdNZs8iG/ge6jRNvR3FLmNlejMIQTqwjDFPN1//wN590TSWhqSRsA4CyGwaqe0dyAEQMjVTECIf+WwYxS0OXof9CCCGEEGIBkBBVCCGEmDY7UE11h4FqaQoyg9Uh/04YqFoJ0I4+U+irJSydtS1x+icLDGVKxE2DiCWVdm9UoFmUGs+l1Hhu7Tmt2gYgOvIssaEnMYqjdEw+yXt5kvcC+dZ1vBS9lPvci/nxWAcjRXhu2OO5YY//Ux36f1GrVqtUbYoujvBuJkwtYmYOYeQHcWKdOPF2fDMx35d3TJauYeka9YAfBJQcj4l8haFMEU1RiZk6DXGDuqhJ3NKJmtrSmjxMCCGEEEIsGjKcfxGT4fxCCHGG+P6RgWopDb4DihZWp+p2eKu+fjjq+zCcLdE3WQAU6iLG7DmRxFwLAsxMD/HBJ4gNPYk9dWSTfyfSwlDjZTyuXsrd2fU8OwpF98hDrEyGQ/8vbtO4oEUnskiqiFWngFaeItBtKrEO3HgnvhE7pWPN9XD+k+F4PsWKR8Hx8AMfS9eIWzpNcZOEbRC3dSxd/iAhhBBzSYbzizNJhvOLuSDD+YUQQoiFRFUhUhcuqRVQTkM5F05OVUqDUwxvAw8UtRqsWqBZoBm1Q7SnbGxDo3ciz1iuTENM+qSeNopCJbWGidQaJja8H604Tmz4KWKDTxAdfR6jOEJ33z10cw/v1aPkVlzM3til/KxyIY+ORtgz4XMo43MoU+EHe8FQ4bymcOj/JW06Z9Uv3KH/vhHFN6KoTh5r6gBmfohKvBMn1k5gROf78k6YoakYEZVkxCAIAsquT6HssTcfDv2PmhqpqEFDzCJu6cQtHU0mqBJCCCGEEKeJhKhCCCHEyVBViNSHC4QzSLllcAphmFrJhxWrlXwYtPouoIBugm5Tb5pYLQl6JwqM58ukIgamLknq6eZFGsmseiuZVW9FcUtER58nNhRWqerlKVIDj3IZj3KpolJsOJfxTZfzS+0SHpps4Zkhl+FCwI4Rjx0jHv/6Qjj0/4aVBm9bY7C6bmFWQ/pGDN+IoVZy2JP7MHL9YW/ZWBuBHpnvyzspiqJgG1pt0inPD4f+j2YqDEyV0DWFmKnT3RClLWlLmCqEEEIIIeachKhCCCHEG6EoYNjhMptbmQlWnWIYrFYrV6OewxozIOZ4DGV8HCtKLBoNjyVOu0C3ybdfQb79Cgh8rMl9xKuBqpU5SHR8F9HxXXTzr7wr3kVuzeUcTF3GQ8WzeHo44Plhl6lywA/3Vvjh3gobGjXetsbg+hUGUWPh/Q59M07FiKE6OayJlzGyfVQSK3BjrQT64hyqqakKMUsnZoUfZR3PJ1dy2dk3xVgqwqqmGKmIMc9XKYQQQgghlhIJUYUQQojTQTfDJVI385zn1oJVwy3SWZzCGh9lcGyKfH6cVEQHVSPQLXzNIlDNY/ZZFXNAUSk3rKfcsJ7xcz+Inh8mNvQk8aEniIztxMz10fBKHw38gAvNJPnWS8lceTmPBhfwk0M6j/e7vDzu8fK4x5eeK3H9irA69ZzGBTYBkqLgmwl8I47qZLEnXsLPHiLQLHw9gq/bBLpNoBrVRSdQTZRF0jnf0FTqYyZxT2c4U2KqUGFlY5SOuqhUegshhBBCiDkhE0stYjKxlBBCLAG+z2R6ip6hMTKZLC1mGcvNoXol8CoogR9upzAr3JoJulAkIDpdVCdPdORZYoNPEBt+Gs3J1db5qkGu81p6u97OjyZWcd8Bh76sX1u/KqXy1jUGN64ySFkL8HcUBKhuAcV3wHdRfHfmvYZCoKig6riBxoujPus7k6hmjEAPw/3pkDVQdQItfD8upPdiruSSLlVoilusborRGLfm+5KEEGJRkImlxJkkE0uJuXAmJ5aSEHURkxBVCCGWjmLF45WRHAPpAnW2QUzzULwSqueg+BUUt4zq5FDdIopXQQkcFM8BAsLQSwmDVW1WwKrKcOY543tEJl4MA9WhJzDzg7VVxfr1TK15B780ruTeg7Ct16HshesMFa7q1HnbWpOLWrUFOxnVa/geSuDiuw4vDVU4tylAVzyU6R6/QIACmk6g6NUw1Q6rqPXoEe9Fz0zMy3vR8wPGc2VQobsuyorGaK2nqhBCiKOTEFWcSRKiirlwJkNUGc4vhBBCLAARU+Oc9gRRU6NnLE9ZU6mP1eG/esMgQPGdcPEqKF65GrKWUJ08qltEc0u16sLqTq+pYA00AxQJlE6YqlFs2kixaSNj538Ya3IvdQd+QqJ/O5HJPUSe2cOtVh2bV72NgXPfyv3DCe47UGHfpM8jvS6P9Lq0xRRuXm1y8xqD5ugC/6KgagRo+IoJVPAiDfDqyZoCP3yP+S5K4KI6WZTyBErggc901ooTbaVcv47AiJ7Rl6CpCi1Jm2LF48BYjol8hdXNMZrjFqpMPCWEEEIIIU6SVKIuYlKJKoQQS08QBIxky+wbyZEvuygEhP9QK6iKgqYoaOqsRVHQteo6VQmDLa8SBqteBcV3UL1yGLBW8tUAtgK+gxIEEECgabiRRglVT4FWmiR18KekDt6HXpoAIFA0ch1XM7XmVnYpZ3Nfj8PWgw55J9xHVeDSNp23rTW4skNHX8CBnucH7OmdZH13/anNeO97GIVhPKuBUsN6fCs19xd5AoIgYCJfwfF92qsTT8UtqSUQQohXk0pUcSZJJaqYC1KJKoQQQixTiqLQmrRJ2DrFiofnBzh+gOcFVDyPkuNR8XwqboDrh8/5lQDPBy8IqqGrAhioijkTshoKWlxBx8MIHLTARQ/CoFUvjGDmhqjEWqQFwEny7HomNryfiXW3ER94jLoDPyEy8SKJ/m0k+rfRnFrLxWvewUfO38y2QYX79ju8MOrx5KDLk4MudZbCW1aHk1F1JZdgiK1qOLE29MIIkbGdlOvX40abz/hlKIpCY9yi4vr0TxWYLFRY3RSjLWmja/KlTQghhBBCHJ+EqEIIIcQCFDV1oubr/zMdBAGeHwapbjVkdX3/iMdl16suYejqBQEVHzxfx/d1vMBCARQ9TlIJSEwM4MebMcwoUgxwklSdXNdmcl2bsab2kzrwExJ9j2Cn92M/9480mV+jfeVbeOubbuGg28hPexx+3uMwWQr47ssVvvtyhY3NGm9bY3Btt4GtL9zq1JOmqLixNrTiGPb4Lsr+OpxYB8xDf1hTV+lIRUkXHXb1ZxjLllnVFKMuap7xaxFCCCGEEIuLDOdfxGQ4vxBCiBMVBNVwdTp49fza44rrkysUqQzvRZ/qoajFcbQIKAqGqmJoCoamYmhqrc+lOD61kiF18Oekeu7BKI4CEKCSb7+SqTXvINtwPk8Mevz0gMOTgy5+9RNZRA+H+1/RoXN5h069PX+J9hsezv8qajmN6happNZSSa4Cdf6qb13PZzxfQVcVVjRG6aqPYury1wMhxPI2PSx21apVRCKR+b4cscTJcH4xF4rFIgcPHpTh/EIIIYSYG4qiVMPQ19mgIUrQcTmV0Sac4ZcpE1DSYuQrHsWKS6Hi4fgOQRCgKSqGXg1XVRVNk2T1aHwzyeS69zF59nuIDT5J3YEfEx17gfjgY8QHH6OcXEnD6ndwzVU3MFqJ87Meh58eqDCUD9je57K9L5wYbEODyhUdBld06JxVr6LMQwXnXPGtFKgG9tQ+FK9CpW4tgTY/VaC6ptKatMmVXfYMZRnPV1jVGKMpbi7qn7EQQrwR00GW779makshhFiQpv//6kwE8VKJuohJJaoQQog5FwSQ7oPRl4EAYs14PlSqbQHKrkfR8ciXPSquT8Xz8YNwKnZdVTFUpRqwqvMxWnvBMzOHSPXcQ/Lwg6heCQDPiJFZcRNTa95BJdrKvgmfJwYcfjngsm/yyC+xjRGFK9rDKtWL2nQip3nY/1xXok5TvDJ6YRwn1ka5YT2BPr/VTp4fTjzlBwFd9RFWNsaImEuwR60QQhyH7/vs3buX5uZm+Y4pTjupRBVzYXx8nNHRUdatW3fK76MTrUSVEHURkxBVCCHEaZMbgeEXwSlCovWo/Ssrnl/ttxouubJLsexR8X0czycgQEXF1FT0atWqrinSEgBQKzmSh7eS6vkJZn4QgACFQuulTK15B4WWTaBojBd9nhxweWLA5Zlhl5I7cwxDhU2tGpe3G1zZodMWn/svH6crRAXAdzEKI3hWA6WG9WGV6jwrOR7juTKpqMHqpjgtCQt1rl+3EEIscH19fTiOw+rVq+f7UsQSJyGqmAs9PT0YhkFXV9cpH0NC1GVAQlQhhBCnVXEShndDcQoSbSfUv9L3oex5VNxwYquS45EruZQ9v9aHdTpc1dWwxYCuLePK1cAnOvwMdT0/ITb8TO1pJ9JEtvsGMt1bcBLhB8KKF/DCiMcTAy6/HHAYyh/5EW5VSuXydp0rO3TObdLmJPQ8rSEqQOBjFEbw9RilhvV4kaa5P8fJXlIQMFVwKLoenXURVjZGSdjGfF+WEEKcMZlMhv7+flasWEEsFpvvyxFLmISo4o3K5/McPnyYzs7OY4afxyMh6jIgIaoQQojTrpyDkZcgOxgGqdqphUmOH+BMV616PmXHo1DxKTkujhfgzOq9NrstgK6qLJfP1Eaun9SBe0j2Pojm5GrPF+vXk12xhWznZnwzDoRB3+GMXw1UXXaPebWJqQASZjg51ZUdBpe26yStUwtAT3uIWqUXxwCFcv16nFj7USufzzTH8xnNlomYGqsao3TURdC1ZfJmFEIsa77v09fXR6FQoLu7W4JUcdpIiCreiHw+T29vL9FolK6urjf0HpIQdRmQEFUIIcQZ4ZRgdA9MHYJ4M+inNuvl0Xg+VKqVqxXPo+L4FByPYtnD8X1cL8DHhyDsuaprSq01wFKd0ErxHGJDT5A4vJXYyDMoQRgw+6pBvv1KMiu2UGi+6IjK4Gwl4OnBcNj/k4Mu2crMxztVgXMbNa7oDKtUVyZPfHKqMxWiAmjlNIpbolJ3FpXEihOqfD4TMkWHbNmhNWnTkrSxdBVLV7ENDUNCVSHEEjUdpObzeWzbJplMYts2qrq4JzgUC4vv++RyOeLxuISo4riCIMD3fUqlEplMhlKpRCwWe8MBKkiIuixIiCqEEOKM8RwYfwXG90MkBdWKyNPF98Oeq44XVq5WXJ982aXoeGHlqufj+QGKEqChouth9ape7b+6VGilSRJ9D5M8vBUrc7D2vGvVk+m+geyKLVSSK4/Yx/MDXhoPh/0/MeDSkz5ycqrWqMIVnTpv6jDY1KqhHyMcPZMhKoDqFNDKaSqJFVTq1hJo5mk/54nw/IDxfBnXDydRMzQFUwuD1IStEzV1LCN8bOlhH2AJGYQQi910wJXJZMjlckh0IOZaEAQUi0UikYj8uylOmKIoxONxksnknAXwEqIuAxKiCiGEOKN8HyYPwtgeMGyw6874JQRBGK5WPD9sD+D5FCsehYpHxfWr1as+EUMnbutn/PpOmyDASh8gcfgBEn2PoFcytVWlurPJrHgz2a7r8M3Xfugbzvu1QPW5YRdnVqaaMOGqToPN3ToXteoYrwqgz3SICqB4ZfTCOE6sjXLDegI9ckbOe6KCIMD1A8ruzHvQq/b6NaoBqqmpJGyduGVgGyqWrmEZYQWrfEkUQixGvu/jui6+7x9/YyFOkOM4bNu2jc2bN2MY0n9cHJ+qqui6PueVyxKiLgMSogohhDjjggDSfTD6MhBArHm+r6hmOlwtlD36J4uUHI+6qLmkKlMB8B1iQ0+T7N1KbOgplMADIFB08m2Xk1mxhXzrJaC+NkQuugE7hsNA9Rd9LlPlmY+BMSMMVK/t1rmkTcfUlHkJUQHwXYz8CJ7dQKlxw1HD4YXIma6eroar05WrmqJg6AqWrhGzNBKWjm3oYWuAash6Rn++QgghxALgOA733nsvt9xyi4SoYl5JiLoMSIgqhBBi3uRGYPhFcIqQaF0QEwHNlq+49E+WGMuViJsGEWth9Neca1o5TbzvEZKHt2Kn99eed606sl3XkVmxhUpqzVH39fyAXaMe2/ocHu11mSjNfCSM6vCmToOruzQSTo6Nq85wiAoQ+BiFEXw9RqlhPV6k6cyefw55flALVqcrphVAoRquahpRK2wNYBsathGGrZa+NN+3QgghBEiIKhYOCVGXAQlRhRBCzKviJAzvhuIUJNoWzERA01w/YDRbpn+qiO8HpCImS3nOAjN9kGTvVhK9D6GXp2rPl1JryHZvIdt9HZ5Vd9R9p/uoPtLr8mivw1hx5uOhpQZc2Wlw3QqDy9p1bP0MhqlBgF4aBxTK9etxYu0LLrB/I/ygGq66YQWr4/v4AagoREyVhG3QGDeJWzpxS0eXiayEEEIsIRKiioVCQtRlQEJUIYQQ866cg5GXIDsYBqnawvsAnCm69E0WmCo6JG0Dy1jiQZTvER15luThB4gNPYHquwAEika+9dJwuH/bZaAe/XflBwEvj3ts63XZ1uswWpj5qGhrcFmHznXdBpe360SMMxNoauU0ilukUnd2OJGWsrR/h54fUHLCXr+O76EpKlFToy5mUB81iVk6cVNHlRYAQgghFjEJUcVCISHqMiAhqhBCiAXBKcHoHpg6BPFm0O35vqLXcLyAwXSRwakSmqqQihiwDPIntZIl0beNZO9W7Mm9tec9M0mu7QpKDRsoNaynkugG5bWVxK7nc/9LUxxyIvyiz2UoP/Ox0dTgsnadzd0GV3ToxE5zoKo6ebRSmkpqFeW6ta8bAi9FrudTrIaqnu9j6CpRU6cxZpKKGMQsnaipyaRVQgghFhUJUcVCISHqMiAhqhBCiAXDc2F8H4zvh0gKzPh8X9FrBAFMFiv0TxbJllzqIyb6mRyaPs+MbC/Jw1tJ9j6IXpo4Yp2vRyjVnU2pYT2l+g2U6tfh2fVHTCylKrBv0mdbr8P2XoeB3MxHSEOFS9t1ru3SeVOnQdw8PT9XxSujF8Zx4h2U69cRLMDA/kyouGGoWnRc/AAsXSVuhaFqImIQt8LeqkIIIcRCJiGqWCgkRF0GJEQVQgixoPg+TB6EsT1g2GDXzfcVHVXJ8RmYKjCcLWPrGnH7tbPYL2mBR3T0eSKjL2BP7sWe3IvqlV6zmRNtpVi3jkNKN4nVF+HWryXQzPAQQcD+KZ/tvQ7bel36sn5tP12FS9rCQPWqLoPEXAeqvouRH8GLNFJqWI9vvv4H3eUgCALKrk+x4lF0PBQFbEMjFTFoiIX9VGOWjqkv7RYIQgghFh8JUcVCISHqMiAhqhBCiAUnCCDdB6MvAwHEmuf7io7K92E8X6ZvskjJ9aiPmGja8qlKPULgYWZ6sSdfDkPViZcxs70oHPkRMVB0ynVrKNWvD5eG9TjRNgLgYDqsUN3W63I4MxOoGiq882yT3zjPmtswNfAx8sP4RoJSw3q8iHwOmuYHYT/VYsWj5ProqoJtatRHDOpiM5NUadJPVQghxDyTEFUsFBKiApVKhe985zt861vfYvfu3QwPD1NfX8/q1av5lV/5FX7rt36LpqamOTvfnXfeyYc+9KGT2ufDH/4wX/3qV0/pfBKiCiGEWLByIzD8IjhFSLQu2BnV8xWX/skS4/kSMdMgYsoQaADVKWBN7cUafxl3YDfNpQPolfRrtnPNJOX69RQb1lOuX0+pfh09Bbs2KdXBdBioJkyFO84zufUsE2OuwuogQC+OgapRql+PG21bsO+z+eT5AcWKR8Fxcb0AXVeI6joNcYPGuEV91JRAVQghxLyQEFUsFCcaoi7Z8Wsvv/wy73//+9mxY8cRzw8NDTE0NMTjjz/O3/7t3/K1r32NW265ZX4uUgghhFiq4i2gGTC8O6xM1XTQTNAt0Kxw3QIQM3XWNMeIWxoDUyWKFY+6qIm6zEc++0aUYvMmco0XsicyyfquOqzSCPbkHuyJPdiTe7DS+9ErGfThp4gNPwVAgEJXoovL6tfzsQ3redpfz9/ubeFg2udLz5X5j1cc/tOFFm/q1N/4JEiKghttRitPYY/tolJXxom1EqgGqEv2I+5J01SFuK3X2lY4nk+h4nF4osDhiQJ1UZP2lE1jzJI/IgghhBBCHMOS/ITZ19fHli1bGBgYAEBRFDZv3szatWsZHR3lgQceoFgsMjIywrvf/W5++tOf8uY3v3lOr2HDhg1s2bLluNtdddVVc3peIYQQYsGI1EPHRZAfg0oeSmlwS1DOg++G26hqGKrqVhiyzkO4qqsKHXUR4pZB32SB8XyJpG1iGcs8SZ1NUXBjbeRibeS6rguf8hzM9AHsyT1EJvdgTezBLAxhZXuxsr2kDj/A24FrO67h26t/m39+KUJ/1ufPHi1yQbPGRy+yObvhjYd2nlWHquaxJ17CzPQQqCaBauAbUXw9SqBbBKpBoJr4mkmgGaAujBB/PhiaSiqikooYuJ5PpuSyqz9NzNJpTdi0JC2StoEq1alCCCGEEEdYkiHq7bffXgtQV65cyd13382FF15YWz82Nsav//qvs3XrVhzH4bbbbmP//v3U1dXN2TVcccUVfPGLX5yz4wkhhBCLkhkLl2luBdwiOKVqoJqDciZ8XM6F4WoQhJWr08Gqbp2RysJkROcsM85QusTgVImSo5CKGCBZ0lEFmkG5YT3lhvVMD/TXylPVStW92JMvExnbSXLgUT48uoObN/0OX0pfzff3Orww6vGxn+e5cZXBhy6waI6+scDaN2JUdBvFc1B8F8UrojtZlMCFQAECAkUB1agGqga+HsE3YgSaRaCFIWugmbX1y6E1gK6pNMRMgsAgX/HoGc9zeLJAY8ykPRWhPmZg6VKdKoQQQggBSzBEvffee9m+fTsApmny4x//mI0bNx6xTVNTE3fffTcXXHABBw4cYGJigr/5m7/hr//6r+fjkoUQQojlQzfDxU4d+bxbDkNVpxSGrOXpytUylLPge+F2qjbTEkA35zxcNTWV7voocUunf7LIaK5MfcRE15d+oDYXPKuOfPsV5NuvAMCaeoWW576AnT7Ayuf/gU+1PML73vyf+dK+OrYecrj/oMO2Xof3bTD5tQ0WEeMN/JwVjUDXeN1m/4EXBqy+i+KX0Ut5KAyh+AEoYSsCNJ1AMQi0V4WsqhEGrJqFr52ZUP9MUhSlNuFUxfWZzDsMZ8okbJ2OlE1jwiJhzUELBiGEEEKIRWxpfQIE/umf/ql2/zd/8zdfE6BOi8VifPrTn+aOO+4A4F/+5V/49Kc/ja4vuR+JEEIIsfDp1SH9s8PVIACvEk5O5c6qXK2Fq5mZcFXTq71WzTccrioKNMRMIqbG4FSR4WwZW9dqPSXFiSvXnUXvdX9H/Ss/pOHlu4iNPMfF47/P5875IL88+218eYfD7jGP/7u7wn37HX5ro8VbVhunZ6IjRSPQNALNOvr6wJ8VsjpopQJ6YRglCIAAUKqVqia+HsGzkgR6BF+zwnBVt5dEmwBTV2lOWPhBQLbksmc4hzWepzFu0ZayaYia6Jq0uhBCCCHE8rOkvg3kcjm2bt1ae/yhD33omNu/973v5aMf/Si5XI6JiQm2bds2571RhRBCCHGKFGUmXJ0tCGYqV91SGLKWc1CuhqulDAQe4Tj8IDyOqodVrKr+quX1hypHDI1VjXHitkH/ZJGxalWqNlezyy8Xqs7kutvIdVxFy3P/i+j4Lpp3fYUb67ex8bKP82Cmk6/sKDGYD/i7p0r8aF+Fj2yyubjtDH9MVdRqtal59PWBj+I7KJ6D6mTQSmPVgJWZSlXdxjMS+Ea0FqyGlazmomsPoCphO4tUxKDkeIxkygylSyQjBp11ERpiJjFrSX2VEEIIIYQ4piX1yeexxx6jXC4DYaXpZZdddsztbdvmTW96E/fffz8ADz74oISoQgghxEKnKGDY4TLb7HDVc8B3wttaH9ZCWNnqOhAUw3WBf+RxXxWyqqpGS0wnasXpnygyni8TtwyZxfwUOPFO+q/5a5IHf0bT7q8RmdzDyof/K+9adxtX3nwbdx8I+L+7yxyY8vmjhwtc0aHzuxdarEwtkJ+1olb7p7421A/7sJZRnDxGaRIl8CEIqr1WjTBQNeN4RpxAt6vVq2HAuhjCVdvQsA0Nzw/IlBx2D6SJmBotCYvWZIS6iExEJYQQQoilb0mFqC+99FLt/saNG09oaP7FF19cC1Fn7/9GTU1N8b3vfY/du3eTTqdJJpN0dHTwpje9iY0bN0pPKSGEEGKuvV64Opvvz4SrvgOeW72tzApbi9XH5XCiK98lHvistXzqnDJDGYccGvFEHVjRM/bylgRFJbP6beTbLqPl+S8RH3qCxj3fIj7wC+646BO8ZfU6vrm7wo/3VXhiwOWpQZe3rzX44PkWdfYCHUKuKGFYqh1lKL/voHpO2IM1n8Wotp8IFBU0E1818c0EvhGvVa1O36IsvNerqQr1UZP6qEmh4tI3WaR/skRd1KCjWp1qGwsk9BZCCCGEmGNLKkTds2dP7f7KlStPaJ8VK1bU7r/88stzdi133303d99991HXnX322fzRH/0Rv/3bvy1hqhBCCHEmqSqoR2kR8Gqzw1avAr6L7jm0+g5WNk/fyBhTU8NEMqOYiSYUO3Zmrn+J8CJNDF7xP4gPPErzC/+ClT1M17b/TnzNO/j9Cz7Iu86K8ZXnyzzW7/LjVxy2HnK4/VyL96wzMRdTOwXVwFcN4FVhu++h+BVUrxL2XfX7AAhQQQ/DVc+qwzeT+EYMX48Q6Mf448A8iJo6UVPH8XwyRYcX+qaIWzptKZvmuE0yIhNRCSGEEGJpWVIh6vj4eO1+a2vrCe3T1tZWuz8xMTHn13Q0+/bt43d+53f40Y9+xLe//W1iMfniJYQQQiwoxwhb6+oh2uEzPj7G2MABMuO9GJlR7EQzakT+TT9hikKu81oKzRfSvPOrJHsfpP7Aj4kPPkFk08f4i2sv4flhly/vKPHKpM9Xny/zk1cqfPhCm+u6F3lAp2oEagRPjxz5fOCheA6KV8bID6BkewlQQLfxjBie3YBvRPH1cDlWT98zxdBUGuMWQRCQK7vsH81xaKJAUyyciCoVMbB0dXH/voQQQgghWGIhai6Xq92PRCLH2HLG7O1m73+qVqxYwW233caWLVvYuHEjzc3NeJ5HX18fW7du5Qtf+EKt4vUnP/kJt99+Oz/84Q9R1eMP2SqXy7WerwCZTAYAx3FwHOcNX7sQQgghTowCNDXUU193MZOTK5kYPER2ohclM4YZa8CIxuf7EueE5wdH3J6Wc+gJBi76f0h3Xkfb8/+EURyh8/E/I911Axec/zt84cYEWw+53LmzzFA+4K8eK/L9RpX/dKHNuU3zHyLOrWp4r1ow3R0g8FDdMko5i54fRQF8zcTXLHwriWek8I0IwQKoVo0ZCjHDpOx6jKbzDE7msA0VQ9OIWRpxU8c2NUxdxdJVTE1F1xZe2wIhhBBnxnSOIXmGmG8n+h5UgiA4fZ+Kz7AtW7bw4IMPAvCpT32KT3/608fd58EHH2TLli0AaJqG67qnfP6pqSmSyeQxA9FKpcJHP/pRvva1r9We++Y3v8kdd9xx3OP/+Z//OX/xF3/xmufvuusuolHpySaEEEKIxU3zSpwz+O+sGb0fhYCynuCFrg8wUHcFZV/hoQGFrQMqFT+saryo0efWFT6NC2ukuxBCCCGEWEQKhQK33357bU6j17OkQtS3v/3t3HvvvQD80R/9EZ/73OeOu899993HLbfcAkA8HiebzZ7WawTwfZ/rr7+e7du3A3D++eezc+fO4+53tErU7u5uBgcHaWxsPG3XK4QQQogTl01PMDV0kOxoL065iBZtwI4lFsMk7K/h+QGv9E9xVmcd2hmcfd2eeJn257+Ale0FINt6OcMX/B5upInxos/Xd1W4v8chAAwV3n22ya+fYxIzF+EPeS5MV6t6ZVQ3/KwYqAa+vvCqVQH8IMDxfBw3vK14Pl71K4muKpiaiqGrxC2NuGVg6hqWroTVq7p2Rt+LQgghTh/Hcbj//vu56aabMIyjTNAoxBmSyWRoamo6boi6pIbzx+MzQ+eKxeIJ7TN7u9n7n06qqvJnf/Zn3HjjjQDs2rWLvr4+urq6jrmfZVlY1mt7sxmGIf+HI4QQQiwQDU2tNDS1UsysY3JwP+nhQxRHxyHaSDSWQFtMEyNVaapyRoMrp+kceq//AvV7v0vD3u+RGH6S6EM7GT/vQ2ir3sp/vyLCe9aZ/O8dJZ4b9vjengo/7amwZZXJ29YYrKlbasP8j0cHTQdi+NVnFK+C5pUwisOouX4CRSHQI/hGFNeqDyesMuL4RhSUMzukXgV0HSJHmd/NrYaqjhcwlvcZzBZRAAUFQw8D1qipE7c1bEPD0jXilk7EXG6/cyGEWDok0xDz7UTff0sqRJ1djTk8PHxC+wwNDdXuNzQ0zPk1vZ7NmzdjGEat78JLL7103BBVCCGEEItHJFlPJHkpTZ1rmRrqYXLoIIWxCTyrnlg8ia4vvjD1TAo0g4lzfoNc5zW0PPcFIpN7aHn+n4n3bWPkoo9zVn0nn78+ypODLv+yo0xvxudHeyv8aG+FdQ0qb11jcsMKg/gyrU4NNJNAM/HNajVF4KG4ZVQnh1Ucr25j4Otx3EgDvpnAMxIEeoT5LJvWX6dPqh8EVFwfx/OZKlQYzQZ4gY8CpKImG9oS1EXNM3/BQgghhFg2llSIun79+tr9Q4cOndA+hw8frt3fsGHDnF/T6zEMg6amJgYHBwEYGxs7Y+cWQgghxJljxutpOauexo7VTA0dZGroILnJw2SMFLFYEsuQiXWOpZJcSd/mv6HuwE9ofPEbRMd3seLB32diw+1MnvUerugwuLRN55khl58ecHh8wGXvhM/eiRJffq7EtV0Gb1tjsLFFQ12MPRXmiqIRGFE8I4o3/ZRXRnWLWFP7gTB49fUYbrQZ34jjmfEwVF0AVEXBNsLq09mCIGA0V2b3QIZz2pM0xCRIFUIIIcTpsaRC1HPOOad2f+fOnbiui64f+yU+++yzR93/TMjn87X7sVjsjJ5bCCGEEGeWFq2ncU09De2ryAyHYWom3cu4liQaTYbDkZdxxndMisbU2neRa7uSlue/SGzkOZpe/Drx/u2MXPQJynVncXmHweUdBlMlnwcOOvz0gMOhjM/WQw5bDzm0xxRuXmNy82qDpqgE1wCBZuFpFp5VB0EwE6pO7g3X6xaekcCzG/HMOL4RXxA9VWdTFIWWhM1ItsTugTQb2pI0J47SJ0AIIYQQ4g1aUhNL5XI5mpqaapMvPf7441x55ZWvu325XKa5ubk2mdTWrVt585vffEau9cCBA6xdu7b2+KmnnuLSSy89qWNkMhlSqRRjY2MysZQQQgix2BSnyI0eJD18kKlsgawSx4okiFn6gpmEyvMD9vROsr67fuFM5hMEJHofpHnnV9GcLIGiMnnWe5jYcDuBZs3aLODlCY+fHXB46JBDwQ2fVxW4pE3nbWsMruzQMRZhj9ozIghQvBKqW5yZrEqP4JoJvEhjtZ9q7Iif+Xwbz5VRFDinPUlLcmGFvUIIIV7LcRzuvfdebrnlFumJKubVdL627CaW2rJlC/feey8Ad9555zFD1B/84Ae1ALWhoYHNmzefkesE+Nd//dfa/VQqxaZNm87YuYUQQgixAETqiK/YRLx5JY1jh8mMHGIiO8xEKYZhxYlbOqoUTL6WopBdsYVCy8U07/zfJPq307Dv+yR7H6KUWosT76QS78SJd3J+vINzLm3kIxfZbO8Nq1N3jno8Nejy1KBLylK4cZXBW9cYrErJxERHqE5E5emRcPh/4KO6JbTyJEZhBABfj+BZKTy7oTb8H3X+vgQ3xi0m8xVeHMjgBQHtqYXRikAIIYQQS8OSqkQFuOeee3jHO94BhLPZP/PMM5x33nmv2a5QKHDhhRfyyiuvAPDJT36Sz372s6d83lwuRzweP6FtH3vsMbZs2UKpVALgIx/5CF/+8pdP+pxSiSqEEEIsIcVJKhO9ZEYOMZ7Okq/46FaUSCQGhgXKmQ/5FmQl6qvEBp+g5fl/Qi9NHHW9r9lU4h1huBrrYFhv56HJFr432MzB0kw7pQ2NGm9dbXD9SoOYsTBf64ISeKjudKVqBV9VCfQonlWHZ9fjGTF8Iw7qma/ZmCpUqPg+61sTdNZFUBZKabcQQogjSCWqWChOtBJ1yYWoEM58v337dgBWrVrF3XffzQUXXFBbPz4+zvvf/37uv/9+IKxC3b9/P3V1da851sGDB1m9enXt8de+9jV+67d+6zXb3XnnnfzzP/8zv//7v8+73vUuUqnUa7YplUr87//9v/nkJz9JsVgEoK6ujhdffJH29vaTfp0SogohhBBLUHGKSjHLxMQEY6ODFPNZoqpL1FBA1Qg0C1+3w2HUyuktVV0MISqA4pawJ1/GzA1g5Pprt0ZhCCXwX3e/kp7kMG3sLLex32+jJ2inX2mnu6uLN6+Ns7FZkwDuRPleNVAtoPgugaKFoaqZqPVS9TWTQDMJVLP6/j19P9tM0aHoeKxrjdPdEJXfoxBCLEASooqFYlkO55921113cfnllzM4OMjBgwfZtGkT1113HWvXrmV0dJQHHniAQqEAgK7rfPe73z1qgHqynnrqKX7zN38TXdfZsGEDGzZsoL6+Hs/z6O/v5/HHHyeTydS2j0Qi3H333acUoAohhBBiiYrUYUbqaGvopn7V+YxMTDEwOsFoPkdSKZIkh+aWUEpTAASKWg2oLALNPO3B6kIU6DbF5k0UmzcducJ3MQrDmLn+arjajzEdsJbGsd0M68iwTtsLswt9h6F/qJEBtR0l2UljWxdG42qKTefPS2XloqBq+GYc36yOzPJdVLeIXhpDKQxCtWwjUHVQDXzVwK9Wqwa6VXv/zlXAmowYqIrCnuEsfhCwoiGGuoD/ECCEEEKIhW9Jfgrs6uriwQcf5P3vfz87duwgCAIefvhhHn744SO2a25u5mtf+xpbtmyZ0/O7rsuuXbvYtWvX625z+eWXc+edd3LOOefM6bmFEEIIsXRYukZ3SyPN9XUMZ0r0ThQYKTvU6T5J3Qkr/yoZtHIazS2glCYhgEDTqqGUddor/hY0Vcep9kd9NcUtYuQGMfNHBqxapg/Ty9OpjNMZjEN6F6TDfTJqip3xa3il8Qbc+jXU2yr1tkK9rRI1kGrH2VQd30zgkzjyed9B8RwU3zlGwKrPClhtAtXE162TDljjdjhJ297hHJ4Pq5skSBVCCCHEqVuSISrAhg0beOKJJ/j2t7/Nt771LXbv3s3w8DB1dXWsWbOGX/mVX+FDH/oQTU1Nc3K+97///axbt47HHnuMX/7yl+zfv5+xsTHGx8fxfZ9UKsXq1au58sored/73sc111wzJ+cVQgghxNJnGxorG2O0JGyG0kX6poocLmqkokni8c6ZmdSdAqpbRKukUctpNCcfBquEAZWvWwSaTaAayzdYrQr0CJW6NVTq1rxqRYBayRBM9dPTe5iJ4T4SpQEuU1+m2U9zdeYers7cw0v7u/mBdy0/8q5mlHpMDeothXpboc5WabBn3Y8otXXLPnBVDQLVIABe02jBd1G8CorvoJXGMQpDMwGrooFmzgpYYwR6pBaw+nr0qFXCMSsMUveNhBWpa5rjC7o1hRBCCCEWriXZE3W5kJ6oQgghxPJUqLgMTBXpnypSqHg0RE2i5qsCpMBHdYso1T6VWjmDWsmgeiUUzwk30Qx8zcbX7aMGUIulJ+rpdjjjsWu4TOPEc5w79TAbi09h4ALgBQrb/Qv4vnctP/cvpYx53OMdK3CttxVWpVRWJNXlG7Qeje+i+E4tZFV8F6X6NSZQDQLNxrOSeFYKX4+GIeusqtWS4zGeL7OqMcZZLXF0bfm1vRBCiIVGeqKKhWJZ90QVQgghhFjKoqbOWS0J2lIRBiaLDKSLTBUr1EcsIma1uaei4hsxMGJ4gJNg1uQ/RRS3gFaeQqtk0YsTKIE7q79qdeIqAcCKpMaKZBS4Griaw5Uc8f7tJHsfJDLxEtdrz3O99jyOFqWn/ip2JK5nl7qByXLAZGlmmSr5FFyoeDBcCBguHLUeE4DGiMLFrToXtWpc1KbTFFnmoZ+qE6g6gR55zSrFc1C8EnphCCPbDyoEmo2vRXAjDfhGnKgRRYlaHBrP4wcBZ7cmMCRIFUIIIcRJkErURUwqUYUQQggBkCk5DEwWGUwXqXgBDVET29COvyOA76A6+Wp/1Sx6aQrVK6C4ZTw/YNekzTmtBoppgypVIq9m5PpJHH6QZO9DGMWR2vNOtJVM95vJrNiCG2urPV9yp0NVn6lSwETpyMfjxYB9kx7Oq7LVFUk1DFXbNC5s1omZUqX6ugIfxSujuiVUrwy+T6AZBFqEkh5n1I3Q0tjAms4WLDu27FtbCCHEfJFKVLFQnGglqoSoi5iEqEIIIYSYLV1w6J8qMJgp4fsB9VETSz/BMHVarb9qnqCc45X9Bzm3RUcPyii+E1a4aha+Xq1WVaSaD4DAJzK2i0TvgyQGfoHqFmurio3nkuneQq7zmrA6+DjKbsDuMY/nhl2eG3bZO+Ez+wO7qsCGBo2L2jQuatU5p1HD1CQIPJbpalXVLeG7ZaaKHnXJBF0tjVjJFrASYEbBiIEmg/WEEOJMkBBVLBQSoi4DEqIKIYQQ4tWCICBddOibLDKUKUEA9VETUz/5sNP3XA7ueJRVF1yJHlTCiaucHHpxAtUrongl8AMCTa+GqhECTb4EKW6J+ODjJA4/SHR0B0o1AvVVk3z7lWRWvJlC80WgnljAnSkHPD8SBqrPDnv0Z48sU7U12NgSBqoXt+qsrlNRpbrymDzXYyqTockO6E6qWBphpbURATsFkXowY2BEw+fk5ymEEHNOQlSxUEhPVCGEEEKIZUhRFOqiJqmIQUddhL7JAiOZMgANMfPU+kCqejgBlRl+qKykgnC4tJOvTlqVDieuKqdRvAooSjhjumYT6Payq1YNdJts9w1ku29AK46R7H2YRO9WrGwvif5tJPq34Vr1ZLuvJ9O9hUpq1TGPl7QUru02uLY7/II5nPfDQHXI5blhj6lywFODHk8NekCZOkthU+tMqNoWX14//xOh6Rr1dfWM5Es4ZZNVjTEimgdOCXLDkO4N37e6HQap0cYwVNUt0MyZWwlXhRBCiGVDKlEXMalEFUIIIcTx+H7ARKFC30SB0VwZVVFoiJonNDt5rRJ10zWoxxvi7LthX1Unj+rk0cuTqE4BxSkQ6CaemVreVapBgDX1CsneB0n0PYJWydRWlVJryHZvIdu1Gc+uP8nDBhxM+zw77PLskMcLoy4l98htOuJKGKi26Wxq0UhaEqpO830Yz5dIRUxWNUWJmbPe54EPbgmcIrhhb1UUBTQDVBN0Ixz+byXCULUWsNrhrSo/ZyGEOBapRBULhQznXwYkRBVCCCHEifL9gLF8mb6JImO5MrqqYuoqmqKgqqAqSnUBTVVQFOXkQtSjUNwSWnkSIzeAVppACXw8K3lCfUGXNN8hNvwMycNbiQ09hRKEqWegqBRaLiHbeS2Flk14dsNJH9rxAl4e98JQddjj5XEPf9anfQU4q17lkjad61YYrK1TUZZ5NWUQwHi+TNzSWdUUI2Ed470eBOA74E0vlfDx9M9Y1cIAVTPAjIeLYYNmgW5Wb60TbuUghBBLmYSoYqGQEHUZkBBVCCGEECfL8wPGcmWG0iWKjofvB/hBgDd9G4QFeAEBge9SOvAM1upLUDR9JmSdDlxV5ZghbE3go5Wn0AsjGIVhFKeAb0TxzOSyD5PUSoZE3zaSvQ9iT+49Yl05uZJC8yYKLRdTbDwvbI1wkvJOwM6RMFB9btjlYPrIfqrdSZUbVhjcsFKnK7GMfxcBTOQrRE0tDFLtU+x65rthsOrNClqD6s9c0cLq1eneq2Y8nMxqOljVrbCKdZn/NyGEWD4kRBULhYSoy4CEqEIIIYR4ozx/VoDqB3hBgOeFt5WKw1Pbt7LpqhtA1XA8H8cLqrfh/WOFsBCgKioJWydaHSatOAX00hhGth+tkiFQNTwzeUoB4VJjZHtJ9j5MdOQZrKn9tQmpAHxVp9RwLoWWTRSaL6JctyYM5U7SeNHn2SGXX/S7PDng4szKVM+uV7lhpcF13QYtsWU4FL0apJqGypqmOKnIHE8f4bszwao/XcU6HbAqYQWrGYdU50wPViGEWMIkRBULhYSoy4CEqEIIIYQ4nU7ky82xQljPDxjPlRnNlik6HjFTJ2EbaKoCvotemkDPD6IXx1H8Cp6ZwDfiMlkPoJbTREefJzq6g+jIcxjF0SPWe0aCQvOFFFouotByEW605aTPka8E/KLf4aFDDs8OHznsf2Ozxg0rDK7t1qmzl1egOpmvYGgqq5pi1EfP0Jf6wA/D1UoOKoUwQI23QaIVIvVSnSqEWJIkRBULxYmGqHP851UhhBBCCLGcaKoShqKvozVpkyu7jOfKDE6VGM4U0TWVVMSAaAtupBm1kkEvjmLkhzByA/i6hWelwmHPy5Rvpch1bSbXtRmCACM/QHTkOaIjzxEZewHNyZIYeJTEwKMAVGIdYaDavIli8wUn1Hc2Ziq8ZbXJW1abTJV8tve6PHTYYeeoV1u++Cxc3Kpxw0qDqzsNYubSD7jrYybpgsOB0Ryrm2I0xMzTf1JFnRnSH2kAJw9TB8Ml0iDVqUIIIcQCICGqEEIIIYQ4reKWTtzSaU9FmCxUGEqXGMuXcd0KSdsgZiXxrRROvAu9NIGRHwirUwHXTBIY0fl+CfNLUXDinaTjnaTXvAN8F3tybxiqjj6HPbkXMz+A2TNAXc89BIpKqX59tZ/qRZTq14F67I/9dbbKrWeb3Hq2yUje55HesEJ136TP00MeTw95/INa4vIOnRtWGFzZoWPpSzdQTUUNskWXA6N5vCCgOW6duZMrysykVL4LpTQM7Agfx1ulOlUIIYSYJzKcfxGT4fxCCCGEOJ1O1zC7IAjIFF1GsiWGMiXyZZeIoZO0dXRNDSeiKk2iF4YxiiOoThHPjOGZiVPqA7rUqU6eyOgLtaH/Zn7giPWeHqHYdEHYT7XlYpxYxwm3TOjLeDx0OKxQ7c3MNFCN6HBVZzgh1SVtOvoxqpEXs1zJxfF9VjZEaUnY89dpIgjC6tRSJnxcq05tCienEkKIRUiG84uFQobzCyGEEEKIBUlRFFJRg1TUoLshyliuzGC1OlVBIWkbRCKNeJFGnMoKtOI4Rr4fIz8STkRlpQi0M1gZuMD5Rox8x5vId7wJAL0wUhv6Hx19Hs3JEh96gvjQEwA4keZw2H/TRopNG3Gjza977K6kxgfO17jjPJMDUz4PHXZ4+JDDcCFg6yGHrYccEqbC5m6d61cYbGzWjtneYbGJ2zr5ksvBsQLpoottqBiail5tY6GpKqoKuqqgqyqaoqCejhays6tTPQfKGRh8HoyYVKcKIYQQZ4hUoi5iUokqhBBCiNPpTFaIeH7AZKHCcLrEaK5MqeIRtw0Sto6qKOA76MVx9PwQemkcxXPwrGTY+1Mmonp9gYc1dYDo6HNER3YQGX8RJXCP2MSJtlKoBqphqHrsSaqCIOClcY+HDrk80uswWZr5OtFgK1y/wuCGlQbrG1SUJfK7KTkeJcfH8wMCAiAAFAhAnQ5UlXDRNQVDV7H0MHDVVAVdVVAVBU1TagGsrqhvLHCdrk4tpsOeqpF6qU4VQiwqUokqFooTrUSVEHURkxBVCCGEEKfTfH25yZYcxnNlBqZKZMsuhhpORGXqKgQBaiWNXhjByA+jujl8PYJnJo/b91OA4paIjO8Kh/+P7cSa2o+Cf8Q2TqSlGqieT6FpI2609XWDas8PeH7E46HDDo/2OuScmXVtMYXzmnRW1amsSamsrtNoiihLJlgFIAh/Bn4Q4AUBnhfgU33OD/BrgSsQKGHgqswKXTUFU1cxNQVT11CVsFJbUUBBQVWA2n0FheqvQgFVATVcieq7UM6guiUUM4qSbEeNt6BEG6Q6VQixYEmIKhYKGc4vhBBCCCEWpYRtkLANOuqiTOQrDKaLjOcreH4QTkRlpvCtOpzECvTSOEa2H704hhL4YcLkA9WcLlCUsEoPpXpfA0UhUFRAnXU/XFfbXjkdY7LnX6DbFFovpdB6KeOA6hSwJ14kMraLyNhO7Kl9GMURjN6tJHu3AuHw/2LT+RQbN1Js3ogTbauFqpqqcHGbzsVtOh+/xObpIZeHDzk83u8ylA8YyjtwaOb8CRNWpTTW1KmsTmmsrt5GjEUarCqgaQoaCgbAsTKAAPwAPN/HC8KQtewGFCteGLoS1Apcj9ip9mauBqzV84ZB68xzimKgBDqqV8DsewFUFc9K4cY78CONKGYUVVFI2DoddRFsQ8JVIYQQ4mRIiCqEEEIIIRYkU1dpS9m0Ji3SRYeRTJmhTImBtEPU0EhGLIJ4J060Da2SRvEdCPwwTA288Nb3UHwXJXCq98PHBC5KEIDvoRJA4BGmXD7gh+tqwiArUPVqP1Zzfn4gp4FvRGuhKoDiFIhMvBRWq47txJ7ch1Ecxeh9iGTvQwA4dmOtUrXYtLE2UZWpKVzVaXBVp0HRDXhhxGX/pE9P2qNnyqc365OtwM5Rj52jHjBTttoeU1hdp7G6WrG6uk6lM64uqf6qtepRVT1m1npM1SAWwA/C0LXWYKB6Hy2OY8QJvApqOYuZfwFXj1GONFOxmxhU44xky6xpjtEct5ZWZbAQQghxGkmIKoQQQgghFjRFUaiLmtRFTbobooznywxMFRnJlsJ1EQPbbji5gwYBBNXA1A8D1PDWnxXE+iiBB0GA4rvoxVG04jhK4OKZS7Mfa2BEKbReQqH1EqA6/H/ipZlK1cm9GKVxjL6HSfY9DIBrN1Bs2kihsRqqxjuJ6ApXdBhc0TFz7IoXcDjj0zPl0ZMObw9M+UyUAgbzAYN5l8f6Z7Y3NViZVGvh6ppquFpvL80q4RNSDWKhOpR/+smjikA0AkGA5eRJVgYI3EE8Pc5U1mLfaIx0Yx2dTfVEo3HQbU7PrFhCCCHE0iAhqhBCCCGEWDQipkaXGaUtaTNZcBjOlBjLlhnPV0hYOvHpiaiOZ3poPxqBGtYFHm+iACfeiVZOoxVHMPJDGPmBJd+PNdBtCi0XUWi5CAhDVXvyZSJju8KeqpN70EsTJPoeIdH3CACuVV8d/n8+5eRKnHgnnlWHqSmcVa9xVv2Rw8gzZZ+eKZ8D1YrVnimPg2mfkgf7Jn32TR7Zs7XOUmptAFbXqVzRoS/vYPV4FAXfjOObcfAdVLdIo5LGLY6Q2e/i9Om01CVpSMZRrQTYKTDsMFSdXiRcFUIIISREFUIIIYQQi4+uqTQnLJoTFpmSw1i2zEC6xGC6iK1rpCIGujbHwY+i4Nl1ePZr+7ECeGaSwFjas6IHuk2xeRPF5k1MAIpXxp7YQ2RsZ7VSdQ96eZJE/3YS/dtr+3l6DCfeQSXeiRPvnHXbQdKKcGGryoWtM19N/CBgMBfUWgH0THkcSPsMZH2mygHPDXs8N+wBYKhw8xqD29ZbdCQk7Dsm1cA3jXAqsQgkA8iWyuxPl0iXM7THc0TVajmwooJugmaBlQA7OROqGpHweQlXhRBCLCMSogohhBBCiEUtaRskbYPO+gjjuQr9U0XG8mUUFFIR47RMoBPoNs50P9byFHphGKM4glKewjeieGaiWum6tAWaRbH5AorNFwCgeBXsyT1ExnZhT7yEmetHL4yguXm0qX3YU/tecwzXbjhKuNpJZ6yVzoTBNV0z25bcgEPpsM/qgSmfXaMu+yZ9fvKKw737HTZ36/zaOdZrql3F61AgEbFwTZORQoV0VqM9ZdOcsNDxwauAV4bcMGT6woasqga6BZoZBqtWAvRI+JwRCUPWJdbmQgghhAAJUYUQQgghxBJh6RoddRFakzaThQpD6RKj2RLj+TJJ2yBu6XM/iY6q4UUa8SKNOM5KtMIYRn4AIz9CoGphdapuz+05F7BAM6uTTm2sPad4FYz8IEauHzPXX70dwMj1o1fS6KUJ9NIEjO088liKihNtOyJYjcQ7icU7WN/QCIpCEAS8MOrxnZcqPDXo8vDhcLmkTePXzrHY1KLJxEknQNcUmhIW+ZJLz1iOTNGhoy5Cwo6EwehsvhcGq14FskOQ7q3OvabOCldTEG+BWItUqwohhFgyJEQVQgghhBBLiqYqNMUtGmMm2XKUkUyJoXSJgXSRiKGTihinZdZ334jhp2I4iY4wGMwPo5fGUEoTeGYc34iHQdMyE2gmleRKKsmV5F+1Tq3kjgxX8wO1x6pXxswPYOYHYPipI/bzNbsarnbQmFjBVevWsHfdCr7Rk+ThXo9nhjyeGSqwrkHl18+xuKpTPy2/86UmZuvYhsZUwSFbcmlN2rSlbAxt1s9O1UCNwqtbV8wOVzP9Ybgab4OG1RA9yYnfhBBCiAVIQlQhhBBCCLEkKYpSG+rfVR9lLFdmYKrISLaEqpy+of6oBm60FTfSglrJoBfHwomockMEuolnpgg0Y+7Puwj5Zpxyw3rKDeuPXBEEYc/Zo1SvGoUhVK+End6Pnd5f26UDuFaPkWtdyfPuCn4+1cXOyRX8zS+6aUxE+NUNJjeuMjA1CVOPRdMUGuImpYpH72SBTCmsSq2LGMcepT87XLUJw9TcMBTGINkF9SvCof9CCCHEIiUhqhBCCCGEWPJsQ6OrPkpb0maiOtR/LFdmolAmaZnErNMw7FtR8K0UFSuFk+hCK01g5IfQimMogY9nJvCNmPSPPBpFwY004UaaKDZfeOQ638HID1fD1T6szEGsdA9mtg/NzZOaepHNvMhmHdDBDxR6ym28tGMFD+9cQVPnWs5ffzZmokV+9sdgmxqmrpEpOuwdztJWrUq19BOsptZMSLaDU4SJA2GgWr8Skp1gLJ8WF0IIIZYOCVGFEEIIIcSyoWsqLQmb5rhFpugyki0xlCkxkHaIGhrJ0zTUP9As3Fg7brQVrZxGL4xiFIbQcoP4ho1nJkGVj+YnRDVwEl04iS7gipnnfQczOytUTfdgZXrQy1OsVQZZyyDwBPQD/VBUYzipVfh1qymnwqWSWLGsetgej6pCXcyg4vr0TxXCXqn1Eeoj5om3OjUiUNcF5SwM74Z0fzjEP9EOmrznhRBCLB7yr5YQQgghhFh2FEUhFTVIRWeG+vdXh/prqkJdxMQ80Yq7kzqximfX49n1VJLd6MVxjNwARnGUAAXPShHokeMfR7yWalBJraaSWk22+4ba01ppMgxTp3qYGjyANtXDSr+fiJ8nMrkbJnfXtg1QceIdlJOrwlA1tZpychVupHlZV62aukpz3CZTctk3nKUlYdGeihAxT6IdhpUAMw7FSRjYAfF+qF8NsWaZfEoIIcSiICGqEEIIIYRY1iKmRndDlPaUzUS+wmC6xFi+jOsFpGyDmHV6PjIHeiSsqIy1o5UnMfJD6MVR1OIknhnDMxPLciKquebZ9RTsemi5GHUdeEHAt/uK/HJ3D2bmIOeohzlXPcQF2mGSQQYz14eZ6yMx8OjMMYwE+bbLyXZtptC8Kez/udwokIzouK7GcLZEuujSWR+hMWahnejbVFHCSabsJBQmoP+ZcMh/3UqZfEoIIcSCJyGqEEIIIYQQVIf6J22aExbposNIpsxgpsjUVIWYqR9RmRoE1dva/0BQvXPEutr2wZHPzdomXJcAO4GmtWOUxkmUh7BLAyimjWelQJWJqOaKqihc2R3liq5z2TW6nu+8XOGvB1wAmpniHQ19vKupnzX+IazMQcxsL5qTJdm7lWTvVlwzRa7zGrKd11JqPHfZBd26rtAUt8mVXPaP5pgqOLTX2SRO5o8Nqg7xFnDLkBmA3CjUdUOqG6z46bt4IYQQ4g2QEFUIIYQQQohZFEWhLmpSFzXpaogwli0zkC5R8fxw/cyGtcfTzyko4dPKzCbTW6mqMrOdEi4q6hGPoQHfb2Cq2ImfG63OSD+EqSmokXp0O7acR5XPKUVR2Niis7FFp2fK4zsvVXjocB1fm6jjaxPnc3a9yq+dY3Fte0A0vZdE/3bi/Y+iV9LU9dxDXc89OJFmcp3Xku3aTDm1dlkN+Y/bOranMZ4vky05tKdsmpM2xsn0FNYtSHZApQDjr0BmKJx8KtUZrhNCCCEWECWY/rO4WHQymQypVIqxsTEaGxvn+3KEEEIIscQ4jsO9997LLbfcgmEs70pI1/PxgoDpGHQ6K5sJRY8MSKefO1UV16dY8ShUKhSnRsmP9xJkhvAqJRwjjmImMQ0VU9fQteUT3J1uw3mff99T4b79Fcpe+FxHXOW2DSZXd+nUmwHR0R0k+rcTG3gMzS3U9q3EO8l2bibbtRkn0T1Pr2B+FMseuYpDfdSkoy5KKnKKtTqlDJTSEKkPJ5+Kt8nkU0IsYfI5QywU0/laOp0mmUy+7nYSoi5iEqIKIYQQ4nSSLzcLRxAElHJTlCYHcSYOU8xNkvNMiloch7A/p6lpmLqCqWkyT88blC773L23wo/2OWQrM1+XOhMqG5s0zm/WuKDB56z8syT6txEbehLVr9S2K6XWkOvaTLZzM260ZT5ewhnn+5AuVFBUaEva1MdNbF1DP5nKVIDADyefckoQb56ZfGoZVfkKsVzI5wyxUJxoiCp/1hNCCCGEEGKBUxSFSKKeSKIe2tdAfhR38jCV7DgVzyevJsm4KiXHp1Cu4OGjoWLq1UVTZ/UhEMeTslQ+uNHmtnMs7ttf4Wc9Dj1TPv3ZcPlpjwNAY2QjG5s3cdE6hxt4mjWT24mNPIedPoCdPkDT7jspNpxLtmszuY6r8ez6eX5lp4+qQn3cpOR49E4VGMyUsDSVmKWTsHVsQ8c2VCz9OAm/okK0EXwXCuOQH4dkJ9SvCCtUhRBCiHkilaiLmFSiCiGEEOJ0kgqRBc73wpApMwi5YXDLlI04ZSVGyfPJl11yZZey4+N4HiigqxpWNVTVpA3ASclVAnaPuewc9dg56rF3wsP1j9wmbsAVjUXeYz3JFaVf0JTejTI94RgqheYLyXVtJtf+JnxzaU+g5HoBFdej7IatMAAsXSNiqiQtg4ilYevhcszKabccvs81M5x4qq4bzNiZeRFCiNNKPmeIhUIqUYUQQgghhFjKVC2c4TzWHPaRzI1gZfqxykMkzSg0pPCJUXY9Sq5PyfHIllzyFZd00cHHJ6LrRC1dRkqfgLipcEWHwRUd4Rf9shvw8oTHrlGPnaMuL4555BzYOhRhK9cB19GtTfBb8Se5mcfoKr9CbPQ5YqPP0fz8P1FovZRs13XkWy8j0O35fXGnga4p6JpOtDo/lO9DxfMolH2mCmEvWV1VsA2NuKUTt3RsQ8M2NIzZAX9t8qk8jO2F7CDUrwqfk8mnhBBCnEESogohhBBCCLGYKQpE6sKlrhvyozDVB9lhVFUjEqknErUAg/YUOH5AqeIxVXAYz5cZz5fRFIWYpWMeb6i1qLF0hQtbdC5s0QELzw94Zcpn12hYrbpr1KO33MBfpt/KX/JWVipD3Kr9kvcZj7HK7yM++Evig7/E12xy7VeQ67qOfMvFoC7Nr2iqCraqYRsAOgTgeD5l12ckU2YoKKEqCqY+uwWAhm2o2LqGYsbAiEI5DUM7IdMPDWvCyaekCbAQQogzYGn+Cy2EEEIIIcRyZESgbgUkOsIh0Om+MFT1XbCTYMYxVAXDDkOq1pRFtuQynquQLlZIFwMihkbU1CWXOkmaqrC+QWN9g8Z714eTgfVmfXaNerww4rFrtJ0vFt7NF913s145zDu1x7hVfZwVjJLse4Rk3yNUjBS5FTeQXXEjldSq+X5Jp5cChq5izArufR/Krkem6DCeLwEKpqZiGSop2yBi6thmHDuRQC9NQv+zkOoMJ5+K1M3bSxFCCLE8SIgqhBBCCCHEUqPpkGgNh/uXpiA7DJmBMFQ1Y2CnQNUwNZXGmElD1CRXcckUHMZyZSbyJTRFJWZLdeqpUhSFFUmNFUmNW9aGz43kw1B159havje6ir9N/xqblP1hoKo9TrOTpmH/j2jY/yP6rTX0tW5BP+t6ksnU/L6YM0RVIWJqREwNMCCASrVadWCqhB/4aJpanbDKJmVaJCZ6sfNjULcqnHxKhvgLIYQ4TSREFUIIIYQQYqlSlHBG80j9rKH+vZAdqo6vToERRVEgYekkLJ2WpE225DCer5AuOKQLFSKmLtWpc6AlpvLmmMqbV4V9VTNln11jG9k5ci4/GP0AHenneI/6CFvUZ+ksH6Dz8AHKh77GduUSnku+GaftItY1mayr14gYy6CRrQKmrh4R5E9PWDWRrzCa9TH1OHWFMg3pF4imh7BazoJ4qwzxF0IIMeckRBVCCCGEEGI5MGPhkuwMh/pnByE/BvlxMKNgJUEzMDSFhphJfdQk74TVqeO5ChOFMiph71TLkIBqLiQtlas6Va7qNAAbx7uOnvS1fHV4kobBh7kk+xBnc4gbeYIbM08wlK7nhy9ew5f86/ASXWxo0FjfqLGhUWNVSkVXl36wesSEVQGUXI/xismIrxLPjZAaHiTWspJY2zrsRP18X64QQoglREJUIYQQQgghlhPNgERbuJSzUJgIh/rnxwAfzARYcRRFJW7qxE2d5mp16kSuwlTRIVOqYBs6MalOnVOGprCuQWNdQxOc8z7gfewZ24/6yv10jj5CmzfJ7+k/5vf4Mc8Uz+Z7h6/jX3uuJEsUU4Oz6rUwWK2Gqx1xBUVZwsGqQnXyKQ0Ck5JjMVQqoR3YiznQR7TlLJJtq0kl4tKWQgghxBsmIaoQQgghhBDLlZUIl1QXFKfC4f7ZIUgPgG6E1alGBENVaIiGvVMLFY90sdo7tVqdGrWqQZaYc2rTWmhay4D3YWJDT5I8/ADRkWe4RN3HJeo+/sL4Bvf7l3GXex2Pj53Li2Nebd+EqbC+QQ2rVavBar29RMNEBWxTwzZjBIkYTj5NrvcFxoZ7URrWUN/SSUPcJhUx0LUl+jMQQghxWkmIKoQQQgghxHKnahBrDJeG1eFw/8wgFCfCClUzBnYSVJ2oqRE1NZoTFtmSy2S+zGTBIVtysPVwvaYt4erHeRJoBrnOq8l1Xo1WmiDR+xDJww9gZXt5h/oL3mH+gqzRxGOR6/m2s5lH001kKwFPD3k8PTQTrJ7bqPH2swyu6zaw9KX5e1IUMOMpzFiCeGGC8vjzjGYG6YuvwI430JK0aIiZJCMG2jJogSCEEGJuSIgqhBBCCCGEmKFbkOyARHt1uP84ZPohNwqBH4apZhxdVaiPGtRHDYoVj3QprE6dKjpAQMzUw+pUyajmnGc3MHX2e5k661ewpvaSPPQAib5tJJwxbnb+nZv5d/Lt5/NK45vZpl7BzrTJnnGPwxmfF8c9Xhz3+NKzJW5abfL2tQYrU0u0ilhR8WNNmHaFjuIYbiHHlNfJ/kILPbpF3NZpS1rURU2StoEqgaoQQohjkBBVCCGEEEII8VqKEgamdhLqVkBxEnIjkB0OQ1XNDNfpNhFTI2JqNMdtMiWHyUJYnZrLu7XDaYqCroWTH+mqgqaq0k/1jVIUyvXrGa1fz9jG3yE2+EuShx4gOrqD2PguLhzfxUbNJtt5DZnLb2Qgeg4/7XG5d3+F4ULAD/dW+OHeChubNd6x1uSabh1zCVYRB5qJE+9AreRoKr5CvT9JwVjBlFPPy0NZdE0lFTFoS9okIwZJW1/avWSFEEKcEglRhRBCCCGEEMemahBrCpeG1eFkVNmhsErVqw73txJoqj5Tnep4lBwf1/OpuD5l16Po+FQ8n0rFx/NdfAIIQFGmg1UlnH1drc40LznWCQs0i1zXdeS6rkMvjJLofZDk4Qcw84OkDj9A6vADtMba2dB8IR85bxUvuN18Z6iTh4ZMdo567BwtknpO4S2rDW5Za9CVWHrVqb4Zxzci6KVJ4hMvYMU7cRIrKGs2uZLL7oE0ph4Gqq3JsH9q3JJAVQghREhCVCGEEEIIIcSJMyKQ6gyH/JczkJ8e7j8SrreTYMSIGBqRo0w25fgBrufjegGO5+NUQ9ai41NyPFwvoOQ4uH4Q7hDMVLFqKtVqVqliPRY32szk+l9jct2vYo/vJnl4K4mBRzHzg2GoCrQBbwFKqRZ6tJU8lu/imUo3z+xZwfdfbuPCVoO3rzW5qlPHWErVqYqGG2lC8cqY2V6M4jhaYiVmvJ36WJSK65MtOoxm09i6Rn3MZEVDlPqYOd9XLoQQYp5JiCqEEEIIIYQ4eYoCdipcasP9h8MwtdAPuglmHDQDVD3cHjBUBUPVwHjtIYMAHD8MVl2PWshacjxKrkdlOmj1XXzfr1aqzlSuShXrqygKpabzKTWdz+gF/4nY8DNY6f1Y6R7MzEGM4hh2aYRzGOEcnuLD1ZywGJjsmezi5SdX8BN9Jam2NWxcfxbN9an5fT1zKNCs6hD/LPbki3iFYSqpVRBppjFuAVByPEazZSbzFVY2RulqiGJokt4LIcRyJSGqEEIIIYQQ4o3RdIg3h0ulAMUJyAyGE1NVcuA7UC0sRVHD7VVj1q0BihrOqq6pmK8TVHk+uH7YEqBWyer6FB2P4nGqWHVVQauGrMuxijXQI+Q6ryHXeU3tObWSxcocxEz3YGUOhuFq9jARr8wm5QCb1APhhkPhMqY0UkyuItKyBie1ikpyNZV4Z9juYZHyzQS+EUUvTmCP7sCJd+IkVuKbcWxDwzY08mWXPcNZJgoV1jTFpSpVCCGWKQlRhRBCCCGEEHPHjIZLshPcMngV8JzqbRmcEjiFcPGc8LHnQOCH+yuEwaqqz1SxVm81FTRVxdJfm4IGAbj+dIuA4Igq1mLFC3uxOj6e99perGEV60zQulz4ZoJi00aKTRtnngw8jPwQVroHI91DfvgAduYgrcEoTcE4pMch/czMMVSDSmIFldRqyslVlFOrKKfW4JvJeXhFp0jRcKPN1SH+fRjFccrJlTjxDlANYpaObWiM58s83zslValCCLFMSYgqhBBCCCGEmHuKAoYdLkcTBLPC1emgtQxuBZx8WNHqVcKwtVQNWYMgDFkVbSZgrVayKmrYu9PQjl4VOR2wTlewVqZ7sVZ8yo5H2fPIV4JjtwlYDgGrooXVmPFO6LwGzoUKsHcyy849rzA1eICV3mHOUQ+xXukl5pex0/ux0/trhwhQybdfydTaWyk2nl9r5bDQhUP821ErGezxFzEKI1SSq3AjTWiqQkvClqpUIYRYxiREFUIIIYQQQpx5ihL2TdWPEUJ57qtC1mo1a6UYBq1uKax2LWfBd2f2m90mQDNANdBVDf11erH6ftiLdXabgEq1TcD0ZFdFx8HzfUDBUFVMPWw7sFwqV9vqE7RdeREVbxO/6HP5i/0VXhhx6FZGOUc5zCXWYa6N9rHaP4RdHCI++BjxwccoJ1cxteZWsl3XEeivE6gvML6ZxDdi6MXx6hD/DpxEN76ZlKpUIYRYxiREFUIIIYQQQixMmh4uRI++3vdnglW3MnO/nIdKvno/96p2AUotWJ0OWVXVwNJfv02A4/uU3TBYLVU8smWXYsUj7Tj4QRismpqGqSkYSzxYNTWFG1Ya3LDS4HDG4979Nj/vaeVnxcugCJoC72sd4LeNn3P2+MNYmYO07vhfNO2+k/Sqm0mvvgU32jLfL+P4FA032lId4t8bVqUmunHinWh6RKpShRBiGZIQVQghhBBCCLE4qSqox2gZ4LlhkOpVqiFrtSdrJV+tZHXC+7MnvlJV0MyZNgGaganp4WRXFhALN3O8gJLrUXZ8ihWPXMWhVPEpVBx8AhTA0DRMPQxYl+JkViuSGh+9SONDGy229Trcs99h95jHd4Y6+A6/Rad5G/9v/TbeUvoZsfIIDfv+nfp9P1hUQ/3DIf4dqE4ee3IfRn6YSnIlTqyVmGXUqlJ39E6ysjFGt1SlCiHEkiUhqhBCCCGEEGJpqlWyxl67LghmWgVMB6xuGZwiVHLhrVOEUhp8Lwz7IvVgRACq/Vd1Etb0ASNhsOp4lF2fYsUlV3YpOT6FcqUarCqYmoqxxIJVS1e4abXJTatNeqY8ft7j8OAhh/5SjP9n+G2o3Mxt0ef4T9bPWFvc9aqh/u8k230dgWYd/0TzyDdiVPQoWiWNPbYLIzdAJbUSIs21qtS9w1kmpSpVCCGWLAlRhRBCCCGEEMuPooBuhcvR8jvfqwas1UrW7DBkB6EwEYap5mtbDNSCVQDCEK3i+ZQdn5Lrha0ASi5l91XBqq5iaAqWri30wszjWl2n8ZGLNH7nQosdIx4PHHR4tM/hO4VL+E7hEtYpvfyX2P28xdtWHer/BZp2f21xDPVXFDyrDs9MoJcmiYzuwIm24yRWELPrsA2NsVyZHcWwKrWrPop5lBYRQgghFicJUYUQQgghhBDi1VQN1Eit8pR4C9R1Qbo/DFOLExBpOGqYOpuphRNQJWZ99ar1V3U9irOC1Vy5DAFYhkZE19D1xZuoaqrCJW06l7TpfMK1+f+zd9/hcV5l+se/b50+I426ZFnuJXGcxKkE0hNKQtvQEhZIyLLA0hZYltB7J9SlhfJLgF3IsixLKCGkQ3pz3EvcbVm9Te8zvz8mEQlxizwqtu/Pdc2VkXTe9xwptjy69Zzn3N9d5I5deR7r6+SdyauJ8Fout+/mn9zbaC4MHllb/Q2Loq8Ro1TASfdhZ4YoBDsohGbREg6oKlVE5CilEFVERERERORQ+Oqrj8hTYWpPtTLVXw/uPloG7MdTh1g9FaxWKtWK1XS+RDJbZCyTJ5kvUMxUsE0Tr2vitS2YoZniwfhsgwvnOFw4x2EkU+bu3QVu32ly3ehL+VHxEi40V/JPzp8501h/RG31r1gOhUArRjGDG9uBne4nH+oiGGzFG/aNV6XOjlZ7paoqVUTkyKYQVURERERE5Lnw1VUfdbMg3gPxvZAZBW8EPKHnfDvD+FuwWu936Cj7SBeLpHMlxtIFkrkiyWwWw6hu+fc5FpZ1ZCaqUZ/JZYs9XLbYw65YiTt2Fbhj52lcnj6VRcYerrRu5VX2PXiPoK3+FdtHIeTDzMfxjm6glOohH5lDS7CZVKHCloEEY5k8cxuDRFWVKiJyxFKIKiIiIiIiMhHeSPUR7vhbmBrrnnCY+hTThKBrE3RtmkMecsUyqXyxWqWaKhDLFChTwTFNvI6FxzaPyCrVrojF1cstrjrBw7rBErfvnMcX9vwTX86+jtdaf+FK61Y6n7bVP9l+JmPzXk624fgZudW/7IYpO0Gs3Bi+wTUU/c1Yodl4Q/UMpfLEVZUqInJEU4gqIiIiIiJyOLzh6iPSAfHeapA61l19nyd02IFftUrVJep3aa+rkMmXSOWLjKbzpHMlErkCBgY+x8Tr2JhHWD5nGgbLm22WN9u86xQvD/X4uH3nK7iw9yWcy0qusv7M8631hHruJ9RzP5nQHOLzX0589gVgzrAfaQ2TkjdKqVzEzgzhywxhB9tpC3WSqPhVlSoicgSbYf/iiIiIiIiIHKE8IWgKQbj9b2Fq7KkwNVyT6knbNAh5bUJem5aQl2yxRDpfIp6pVqiOpvNUKOOxbLyOiXOEVTy6lsHZnQ5ndzrEc17+svsFfH7XGRSHd3KldSuXWffgS+zEt+rbuJt/y9iKd1JsOn66l/1spk0x0IJRzOIm9uBkBrGDnfj87QymCqpKFRE5AilEFRERERERqSVPEJoWQqQdEn0wtvvJMDUEnkjNtqIbBvicao/UhoBLoVwhnSuRyhUYTRdI5YsUsxUsw8DnWHgcaybugt+vsMfkZQtdXrbQpSexlDt2LeCVO67gnOydvN3+PQ2Z3dTfdw33+i6gf+lVHD+rHsucWZ9gxfZSCLZj5pN4Rp/ASfXhCXcRsxrYMpBgNJ1nXpOqUkVEjgQKUUVERERERCaDG4CG+RBqe2aY6glV+6bWONF0TIOIzybis2mL+EgXnjycKlMgmS2STOUwMQj7HOwj7GCq9pDJG5d5eMPxLWwaeS1f234xp+79GZdxFy/I3MnIYw/zrcdez3DHhZzb5eGEJmtGBaplN0jZCWDlY/iG1uL4GgkEZ9OXgtXZAp31fjrq/fhca7qXKiIi+6EQVUREREREZDK5fmiYB+GnhanxvdWQ1RsBo/bbuQ0DAq5NwLVpevJwqnS+xFAyx3Ayh2WahL3OEdc/1TAMljbYLG1oonTK+7lr+4tYtPl7dBR282l+yMPdf+FjO65myDObszttzpvtcFyjhTkTSnANg5KnjpITws6OEBxeRZe/jZi3na2DZfoSObqiflojXhzrCPsfIyJyDFCIKiIiIiIiMhUcH0TnVitTk/0wuhNiT4apvrpJCVOfUj2cyiTidWgIuPTGsgynsvgcm6DHhhmQMT5Xlmkwa8Ey0vO+zcDW31G/6Reczmb+6H6EnxRfwre2XMZNW7w0+gzOne1w7mybJVELY7oDVdOi6G/CKOVx0n00ZIcI+ZoZyzSwoSdIX9xPV9RPY9CDOYOqaUVEjnUKUUVERERERKaS44X6Lgi1Phmm7qqGqY6v2k/V9k7a1KYJ0YBLyOcwnMzRG8symMgS8jl4nSN0K7lpE1t0GalZZ9O09kcEe+/n7fYfeI37IJ8svIk/ZE7lfzfn+d/NeVoDBud0Opw322FBvTmtgWrFcikEWjGKGdxUD830UO/WMZRrYm2inqb6CLOjfur86pcqIjITKEQVERERERGZDrYH6mZD8MkwNdED2TikhsBywA2C469571So9k9tDXuJ+BwGEzn641lSuSIRn3vE9Ut9StHfRO8ZH8Hf9wjNa35AQ7qf71hf55roaXzLvoo/9NfTl6rwq015frUpT3vQ5LzZ1S3/cyLTF6hWbB9F2wflInYuRntxmHw+wGCqgbUjTbQ0tTCrwY/f1Y/vIiLTSd+FRUREREREppPtQl0nRGZBPgnZGKQGIT0KmbHqNn83UH2Yta0W9TkWs6N+6v0uffEsw8kctmkSOgL7pT4l3XoauxpPIPrEr6jf8hs6Y4/wFWsN/7bscm7xXcqd3fBwT5GeZJlfbMjziw15ZodNzntyy//s8DRV5Jo2JV8DpUoFq5CkI7+H7FgPg2N1jA6209bWQWt9CNc+Qv/HiIgc4RSiioiIiIiIzASGAZ5Q9RGZBYXMk4HqMKSHqtWqlUr1oCo3AFbttnmHvDYBN0hDwKUnljni+6VWbC/Dx72JeOf5NK/6Lv7hdbRt+imvD93FRSe+g9HTj+eBniJ/2V3gkd4iu+NlfrYux8/W5ZhXZ3Luk1v+20PTEFgaBmU3RNkNYReztOfGyAwN0Du8leHGLtraOmmK1mOpX6qIyJRSiCoiIiIiIjITOb7qI9QKpUI1UM2MQbIP0iNQKlb7q7qB6rjDNN4v1eswlMzRF8symMwR8tpHbL/UQqiTvS/4IqE9d9G47id4ErvpvPdDRGZfRPD4N3NBV4RUvsL9ewvcvbvIY31Fto+V2T6W4/q1OY5vtPjnkzwc3zg9PzpXbC9F24vjK9GYi5PpW0v3wBbGGmfT0tFFXbQJ40gtGRYROcIoRBUREREREZnpLAcCjdVHdC7k4tX+qcn+v1Wr2s6Tgaq/2gJgghzLoC3ipc7vMBDPMZDIks6VCPucI7NfqmGQmH0BqdbTaNzwU8I7/0x49+0Eeh9k6Pg3Q9fFXDzX5eK5LvFchfu6C9y9u8CqgRLrh0q89/Y05822ecuJXloC0xRYmhZlXz0ebx1OLkmmfwu7hrYRa2ynqWMegfrW6p8RERGZNEf1r6zy+Tw///nPueSSS+jq6sLr9dLW1sZZZ53Ftddey9DQ0JSu5/3vfz+GYYw/5syZM6Xzi4iIiIjIUcC0wFcP9V0w6zSYfSZ0rKgeUFUsQLy3+sjGoFyc8DQ+x6Krwc+S1jD1AZexTJ5YukC5XMPPZQqV3RADJ72L7nO+Si48F6uQpGXVfzDrng/ixnYAEPYYvGS+y5fPD/BfLw/y4nkOBnD37iJX35zk+jVZMoXK9H0ShoHpDRFono0bbGRooIedq/9K79q7yA1shVxy+tYmInKUMyqVyjT+CzB5Nm3axBVXXMGqVav2O6a5uZnrr7+eSy65ZNLX8/DDD/O85z2P8tNecXR1dbFz584J3zMejxOJRBgaGqKhoaEGqxQREQ25U74AANdQSURBVBH5m0KhwM0338wll1yC46jCSeSIUMhUK1TTw9XDqfIpqJSr2/09wQn3US2XYTSTpzeWIZ4p4HdsAt4jeGNjuUTd9j/QsOk/MYsZKobJ2LyXM7zk9VQc/zOGbh0t8YPHs6weKAEQ9Rq8ebmHF851MI3pr8xNZ3PkUzHCVpbGunrqmjuxIu3VoF1b/WUG0+sMmSmeytdisRjhcHi/447KELW7u5szzjiDnp4eAAzD4JxzzmH+/PkMDg5y++23k8lkAHAch1tuuYULLrhg0tZTKBQ45ZRTWLt27TPerxBVREREZjL9cCNyhCsVqoFqdgwSvdUqxXIBTLu65d/xPect4IVSZbxfaqZQIux18DhHblBnZYZoWvsjQj33AVDwNTJ4wltJtT2vetDXkyqVCvfvLfLDVVl6ktUfoRfUm7z9ZC8nNk9/mFypQCJbpJSN02DnaAp5CEVbMCKd1RYQtme6lyjyLHqdITPFoYao0//dfhK8/vWvHw9Qu7q6uOmmmzjxxBPHPz40NMTll1/OHXfcQaFQ4DWveQ3btm2jrq5uUtbz5S9/eTxAff3rX88vfvGLSZlHRERERERknOVAoKH6qH+yj2ouUT2cKjNSrVYtF8GwwPWB7Tto2DbeL9Xn0J/IMZjIkspxxPZLLfka6Tv9w8T7H6Vp9Q9w0320P/wFUi2nMrD87RQDrUC1MOf5sxxOa7O5aUue/1yfY+tomQ/cmebsWTb/fJKXtuD0hcmGAWGfTcmtZyhTYDhRoCXbS/NoH75QPYQ7INgM3v2HAyIicmBH7q8M9+Pmm2/mnnvuAcB1XX7/+98/I0AFaGxs5KabbmLevHkAjIyM8JWvfGVS1rNp0yY+97nPAfCP//iPXHzxxZMyj4iIiIiIyH6ZJvjqoK4T2k6ArufD7OdB+wqo6wLDrvZQjXVX+6lmRqGYrZY47oPPtZjT4GdxyzP7pR6p+xzTLaey+8LvMrzodVQMm0D/o3Td8Q6im36Jmf9bn1HXMnjNEg8/vTTIyxY4mAbc013kn25O8qNVWVL56f0CWJZBNOgS8PnoKYTYkArSM5Yh37se9jwEAxurIbqIiDxnR12I+t3vfnf8+ZVXXskJJ5ywz3GBQIDPfOYz429fd911FIsTb7q+L5VKhbe85S3kcjnq6+v5+te/XtP7i4iIiIiITIhlV0PVSAe0Hg9dZ1VD1Y5TITqv2js1l4R4D8T2VqtWC+lnhaphn82CpiCLWkJ4HJOhZJZUtrY/V02ViuVh5Lg3suuC75BuXI5ZztOw6b+Yc+ubaVz3/7AyfzuYuM5r8p5TffzgRQFWtFgUyvCrTXmu+mOSP2zNUypPb5jq2iaNIQ+ObbMzZbEpE2YwZ1Ic3Ardj0DfumpQfqSm3iIi0+CoClGTySR33HHH+NtvfvObDzj+Va96FcFgEKhWo/71r3+t6Xq+//3vc9991d46X/3qV2lubq7p/UVERERERGrCtKpbvcNt0LwEZj8Zqs46FRoXgxOoHlqV6K2GqqkhyKehUsY0oSHgsqQ1zNzGIBVgKJFlNJUnWyjBEZbTFUKz2Pv8z9N76gfJhbuwihnqt/6Gube+heaV38JJ7BkfO7fO4kvn+fncOT46QyZjuQrfejTLv/w5xcq+6Q+Tfa5FU9BLsQxbRitsyYYZLbpURnfCnoerYWp6RGGqiMghOKp6ot5///3kcjmgWml62mmnHXC81+vlec97HrfddhsAd955Z80OmNqzZw8f+tCHADj77LO5+uqra3JfERERERGRSWea4AlWH6FWqCyohqj5ZLVCNT1U/e9T1Yy2i+P6aQv5qPM7JLNFRtMFErkCyVwBCxOfa+F1LDgSWqcaBslZ55DsOBt//6NEt/wa3/B6IrtvI7L7NpKtZzK66FVko0sxDIMz2h1OabX5/dY8P1+XY0eszDV3pzmz3eZtJ3mYFbam8XOBkNcm4NrEMnliGWgMRmjxVQjFdkO8G0JtEJkF/oZnHKglIiJ/c1SFqBs3bhx/fsIJJ2DbB//0VqxYMR6iPv36w/WOd7yDRCKB67pcd911GPqHSEREREREjlSGAa6/+gg2Q8O8J0PVVDVYTQ1XD67K9uMrl/HZLk31frKESObLxNJ54tkiQ6kcBgZ+x8LrWjM/rzMM0q2nkW49De/IRuqf+F+CfQ+OPzINxzOy8NWkW07FNg3+YZGHC7tcfr4+x++35Hmwp8gjvUVesdDlDcs8hNzp+4RNE+oDLsVihcFkjrG0SXO4jiYf+OI91V64wWaom10NU82jauOqiMhhO6pC1M2bN48/7+rqOqRrZs+ePf5806ZNNVnHjTfeyB/+8AcArrnmGpYuXVqT+4qIiIiIiMwYjq/6CDRC/Rwo5qqhai5R7aGaieEt9OMFGoNecmEfqZL95CFURYZTOQzA51h4HXvGZ3bZ6FJ6z/wYTmIP9Vt+Q3jPXfiG19MxvJ5cuIvRBa8iMescwh6bd67w8rIFDj9cleOhniK/eSLPbTsLvGmZh5cucLDN6QtTbdugMeghWyjRPZJm2LVpjdTT6DVwUv2Q7K+GqZHO6v9bcxqraEVEZpCjKkQdHh4ef97S0nJI17S2to4/HxkZqcka3vOe9wCwaNEiPvrRjx72PUVERERERGY821N9+KNQ3wWFbDVQzcUhOYAnn8RTzBJ1TfI+H6myj3geRtN5RtLVtmxe28LvzuxAtRDqZGDFvzK89B+p3/Y7Ijv/hCe+i9aVX6dh488ZW/BKYl0vYnbYy+fO8fNob5HrVmXZGSvz3ZVZfr81z9tO8nB6uzOtn4fXsfDaFslckR1DSYZ9Dm2RBupdMNNDkOiDYBPUdYG/sXoYmYjIMeyo+i6YTCbHn/t8vkO65unjnn79RL3vfe9jcHAQgB/84Ad4PJ7DvudTcrnceM9XgHg8DkChUKBQKNRsHhERERFg/PWFXmeIyMRY4KmrPkKdUEiP91E1MiMESzGCRpGmgEOq4iFVthlLlxhO5qhQwWtbeBwL25qZe/5Lngb6j3szgwtfQ93OPxHd/juczCBNa39EdNONjM69lNG5L+XklgjfvdjPn7YX+Pn6PLvjZT761wyntub55xM9dEWmt9LT51p4bItktsCmdJxowENzqJ6Qt4KRHIX4YDUYj3QqTJWa0usMmSkO9c/gUfXdL5vNjj93XfeQrnl6yJnJZA5r/ltvvZWf//znAFx55ZWcf/75h3W/v/fFL36RT3/60896/1133YXf76/pXCIiIiJPeap/vIjI5Mg/+TiCeS/CXHIOnSP3sqD/ZoL5ARqfuJG6Lb9hd8M5bG1+CQs9TXxoOdzabfLXPoNH+0qs7EtxVkuFizvK1NWu/uawDI2meeJZ7x188iFSe3qdIdMtnU4f0rijKkT1er3jz/P5Q/tH+OmVnYdavbovqVSKt73tbQA0NDRw7bXXTvhe+/PhD3+Y97///eNvx+NxOjs7Of/882loaKj5fCIiInJsKxQK3HbbbVx88cU4zvRuOxWRo1wxD/kEZBOQHoRcklIhS7ZYIVl2GC3YpIomxXIZj2XjdUwcewbu+e96Fd2VVxLqfYDolv/FF9vKvKHbmTt8J/H2sxlZ8CpOnjuXNybK/HhNjvv3Frm33+DBQZOLuhxeu8SlPTT9n1ehWCaWzeOxLVpCHhqCHlyzDNk45DPgq6seQBVoAvvQCphE/p5eZ8hM8dRO74M5qkLUYDA4/vxQq0qfPu7p1z9XH/3oR9m5cycAX/va12hsbJzwvfbH4/Hssz2A4zj6hiMiIiKTRq81RGTSOQ74AhBphcoCyKdwcgm82THqUkO055JksmlSJYORvE2i4JDIGXhtG58707b826RnnU264wX4hlZT/8T/Ehh8nMjevxDZ+xdSzSsILnw1n37BCaweKPHTdTnWDpa4ZUeBW3cWOKfT5vKlHubXT982f8u18Lo+MrkS3WNZYpkirREv9YEG7EAZsmMwsAZ89dUwNdgCjveg9xXZF73OkOl2qH/+jqoQ9enVmP39/Yd0TV9f3/jzaDQ6oXlXrlzJf/zHfwBw/vnnc+WVV07oPiIiIiIiIsc8wwBPsPoIt0G5hJlLEMglCKSHaUqPkk4nSOfL9JdDxDNlypTx2vbMOpTKMMg0nUSm6SQ8Y1up3/K/BPfeR2BgJYGBlWTrFhJc+GpOvOBM1g1VuHFjnod6ity9u/o4vc3miuNcljVN34/tPo+F17VIZotsHUxSl3Rojfio8zVg+OohG4Pe1eCNVMPUUCs4E9/hKSIykx1VIerixYvHn+/ateuQrtm9e/f48yVLlkxo3jVr1lAul8fvd+aZZ+537FOHTgH09vY+Y+zHP/5xLr300gmtQURERERE5KhkWtXt4746qOvEKOYIZOMERrcTjfeTCoWIlXyMpHKMpHMYgN+18ToWxgwpUM3VLaDvtGtwjuulbuv/Ed51O96xLbQ98kXygXYiC17JCWddwNZEgBs35vjrniIP91YfJzRZXHGch1NbLYxp+IQMA0I+m0DZJpbJE88kaAi6tES8hHz14K2rhql9ayHWDc3HQUDt5kTk6HNUhahLly4df7527VqKxSK2feBPceXKlfu8fqK2bdvGtm3bDmlsPp/noYceGn/76QGriIiIiIiI7IPtgWAT+OqwfLsIj2wnbGZobWsima8wls4zli4wlMxhG0a1mtKZvq3xT1cItDF44jsYWfJ6Itt+T92OP+Kmemhe/T0aNvyM6JwXs+jkl7LrhHp+tTHPbTsLrB0ssfYvaRbUm1y+1MMLZtlY5tSHqaYJ9QGXQrHMYDLHWLpAS9hDU8iL11dXrUZNDUDvKmheCuH2KV+jiMhkOqpC1LPOOguPx0MulyOVSvHoo48esCo0l8vx4IMPjr99wQUXTMUyRURERERE5HBZDjQuqPblHN6Ck+yl3h+lvjFArlgmmSsyksoTzxRIZIu4lonftWbEgVQlTx0jx72R0YWvIrz7Duq23YSb7iO65dfUb/0/GjvOZv6iV/LGZfP43815/rg1z9bRMp+7P8OskMnrlrpc2OXgTEMvWMc2aQx6yBZK7BlNM5TK0xbx0hD04ARbID0CPauhmIO6LmZOfwURkcNzVH03CwaDXHjhheNv33DDDQcc/5vf/IZEIgFU+6Gec845E5r3qquuolKpHNLj+uuvH7+uq6vrGR+76qqrJjS/iIiIiIjIMSvQAO0roGkp5FOQ6MNjVmgIuCxsDnJcW5gFzUECHotUvshgIkciW6RUqkz3yqk4fmLzX8aui6+j5/SPkmk4HqNSItx9N7Pvfi8nPfYR/q3lcf7zZT7ecLxLyIXuRJmvPZzlyj8k+c3mHJni9HweXseiKeiFCmwfTLK5L85wKk/ZGwVPAPrXw9BmKBWmZX0iIrV2VIWoAO94xzvGn99www2sX79+n+PS6TSf+MQnxt9+61vfetCt/yIiIiIiIjID2S40LYSOU8BbD/EeyKcB8LkWzSEPS1rDLGkLM7cxgGMZxDIFhhI5UtkiTx5xMX0Mi1T78+g++8vsPu+bxGedR8Ww8A+vo/3hz7P8nnfwHv9t/OIlNm89yUPUazCYqfD9x3O88fdJ/mt9jkR+GsJUA4Jem4aAl2y+zBP9CbYOJomVfVT8DTC0BfrXQSEz9WsTEamxoy5EvfTSSzn77LOB6nb9l770paxZs+YZY4aHh3nlK1/J1q1bgWoV6jXXXLPP++3cuRPDMMYfB6tuFRERERERkWkSaISOk6FpCeQSkOyHSjUhNQwIeWzaIl6Oa4uwpC3MrHofGDCSzjGSzJPNl2CaC1RzdQvoP/UD7HjhTxhZ+GpKThA31Uvz2us47o438/bif/HLizL866le2gIGsVyFG9bmeMPvEvxoVZaRzNQnwqYJEb9Dnc9lNJVnU1+cHbEiKU8jjO2B3tWQjU/5ukREaumoLL38xS9+wemnn05vby87d+7kpJNO4txzz2X+/PkMDg5y++23k05Xfytp2za/+tWvqKurm95Fi4iIiIiIyOGzPdC06MleqVshtre65d/xjw+xTIj4bCI+m9aIj0Su8OSBVEWSqSyWYRLw2LjT2D+15Gtk+PirGFl8+d/6pqZ6iG79DfXbfkt7+wv4h7NewZ8T8/jlxhw7Y2V+tSnP/z2R58XzHF6zxENbcGrXb1sG0aBLvlimL5ZlNGXRHKynOT6Ip7gKWo6rBt0iIkegozJEnTVrFnfeeSdXXHEFq1atolKpcPfdd3P33Xc/Y1xTUxPXX3/9M/qoioiIiIiIyFEg2ATeMIzsgNEdkEtWAzzjmcGiYxlE/S5Rv0uuWCaR/duBVLFMnoBr4/dM34/OFdtLbN6lxOa+hED/o9Rt/S3+oTWE9v6V0N6/8qboUl66/BXcWTmVX2wssXG4xO+3FvjjtgLnz3a4/DiXORFrStfs2iZNIS+ZfIk9Y1mGnQAduTHqCo/jtB4H4fZqabCIyBFkyv4leOrk+3/4h3/g3e9+96TPt2TJEh566CFuvPFGfvnLX7J+/Xr6+/upq6tj3rx5XHbZZbz5zW+msVG/BRMRERERETkq2R5oWgz+KAxtrfZK9TeA49vncI9t4gm6NARcMoUSY+k8ffEcg4ksdT4XZxorUzFMUq2nk2o9HXdsO/XbbiLU/Rd8IxvpGNnI5f4WXjTvZdx/3AX87AmLlf0l7thV4I5dBc7qsPmnEz3MDk9tmOpzLXyORTJXZGvGR302TUv6USKzlmE2zK32ARAROUIYlUplSjq+mKaJYRi8853v5Nvf/vZUTHnUi8fjRCIRhoaGaGhomO7liIiIyFGmUChw8803c8kll+A4znQvR0Tk8BSy1YrUkZ3V8G4fVan7ksoX6Y9lGUzkMQ2DsM+ZMdmflR0hsv2P1O38E1a+2nO0ZPuId72QlQ2Xcv32Ou7tLgJgm/C6JS5XHOfBY099FWi5DIlsgXI+QaOVJdq5mMis4zBsd8rXIjODXmfITPFUvhaLxQiHw/sdN0O+9YuIiIiIiIhMIsdbPXCqYwW4gWqv1EM4NT7g2sxtDLKoNUTAYzGcypLMFqdgwQdX8kYZOe6N7HjR9fSf9C5yoU6sYob6bTdxwcNv5/vut/ifs/ZwRrtNsQz/tSHPW29J8ljf1K//qcOnQqF6hsshdm1Zy44NDxFP6MApETkyHJU9UUVERERERESexTAg1PK3XqljuyCfBH/jAXt0GgbU+x2CXpvhZI7esSyDiSwRnzuth089pWJ5iM95MfGuF+IfeJy6bb8lMPA4oZ77OK3nPm6oX8w9y17Dh7ceR0+ywofuTnP+bJu3n+wl6pv6w6fqIiHyeQ+x3p2MxZLUzzmR1pYWfO7UthsQEXkupv+7vYiIiIiIiMhUcnzQvBTaTwbbB7FuKGYPfplp0Br2sqQ1RFvERzJXZDSZp1yegjUfCsMk3XIKPWd9ll0XfIdY1wspmw6+0c28cOvn+Ev087yvazumAXftLnL1zUl+vzVPeWq6/D2D67oEm2fjL44xuOUhVj+xlT0jaQqlmfLFFBF5JoWoIiIiIiIicuwxDAi1wqxTIToP0qOQHoZDCBR9rsWchgCLW0KEfA7DqVx1i//UZ5H7lQ/PYeDk97DzRdczsuAyyqZLcGQ9/9r/MR5o+wYXR7pJFeDbj2Z57+1pto+Vpn6RholV10GTt0JwaB3btm7i8V0j9MezlMoz6IspIoJCVBERERERETmWOT5oOb5alWp5IL4XirmDXmYYUOd3WNgSZEFzEMOAwUSWbGEawsgDKHnqGF52NTsv/iGxOS+mYpi0jDzCD3PX8MeWH7DQHmDjcIl/+XOKH67KkilOcXhpGBT9Tfh9Hmbnt1Ee3sHq3SOs2xtjOJljis7CFhE5KIWoIiIiIiIicmwzDAi3QccpUD+3WpF6iFWptmnQHPKwpDVMR72fbKHESDJPsTSzwr+Sr5GBk97Frgu/T6LjbAwqHB/7K392PsAP635GtBLjfzblecvNSR7YW5j69XkiVDwhWrPbmVXYxXA8yeN7xtjYGyeenfr1iIj8PYWoIiIiIiIiIgCu/29VqaZT7ZWaTx/SpV7HpKvBz+KWMPUBl7F0jkRmZm3xBygEO+g77Rp2n/dNUs0rMCtFXpi9hQf87+MT3v8hk07xiXsyfOreNIPpqe1PWnYCFP0N+JO76cxto94usmckw+O7Rtk6kCCTn1lVviJybLFrcZMLLrjgkMf+3//9H+vWrTvgGMMwuOOOOw53WSIiIiIiIiLPjWFAuB28ERjZCYkeyIyCrw7cwEEvD/tsAp4g9QGHvrEsg8ksIY+Dd4adPJ+rW0DPWZ/BN7iGhg0/xTe6mav5P17nv41v51/ODd0v5J/6ilx1godXLHSxTGNK1lWxPBQCzTipPupKebwNS0hU/GwdSNIXz9EV9dMW8WJbqgkTkallVGrQYMQ0TQzjwN9Qn5rmUMYZhkGppN8wHUw8HicSiTA0NERDQ8N0L0dERESOMoVCgZtvvplLLrkEx3GmezkiItMjG4N4T7VXaiFTDVc9oUO6NFcsMxDP0h/PUSiXqfO52NbUhJHPSaVCoPdBGjb+DE9iDwBDRpSv5l/Fr0vnMLfe4b2n+ljcMIVBcKWMkx6gbAfIRhdT9DYQzxZJ5Qu0hn3MbQoQ9urfpiOZXmfITPFUvhaLxQiHw/sdV7Nf3VQqlQM+nus4ERERERERkWnnjUDzUug8AxoXQ6kIY92QjR+0Z6rHNumM+lncGqIx6GEskyeWLhxKq9WpZRik2p/H7gu+Q9/J76Xga6KxMsKXnR9xm+eDLIw9wLtvS/KdxzKk8lO0eMOk4G/BKOfwDa3FTfUS8do0B730x7Os2j1G92iaUnmmfTFF5GhVkxC1XC4f9AHVKtR3vetdBx2rKlQRERERERGZUTwhaFoEnadXQ9VyudozNRs7aJga8trMbwyyqCWExzEZSubI5Gbgz72GRaLrInZddB2Dy/6ZohtmntHL991vcZP7MYa2reTqm5P8ZXdhaoqgDIOir5GKaeMZXo8b34ltVGiL+DANg3V7Y6zviZHMFSd/LSJyzFMTEREREREREZFD5QlC4wKYfQa0LKseHBXrhswYVPZ/EJNpQkPAZXFriK6on0K5zFAiR7E48yopK5bL2IJXsOviHzO85PWUbR/LzR38l/tF/qP0OX7/wFo++tcMvcmpOXiq5IlQdkN4Rp/AM/oERilHxOfQHPLSM5Zh1Z4xemMZyqpKFZFJpBBVRERERERE5Lly/dAwrxqmtp4AhgmxvZAeOWCY6lomHfU+FreFaAp5iGULjCTzFIpTE0g+F2XHz8iS17Pz4h8zOv8VlE2b51vrucnzCa4e+ipf/NNmbtyQozgF4WXZ8VP0RXHjO/ENrMbKjuBYJu0RH+VyhbXdMTb1xcnkZ2CFr4gcFRSiioiIiIiIiEyU44PoXJh9JrSfBJZbPYgqPQzl/Qd6QddmflOQxa0h6gMuqXyRoUSuGgLOsILKkifC0An/zK6Lfkh89kVUMHmJ9Qh/sD/Iog3/wSdv2cW6wcnfUl+xPBSCbZiFOL7BVbixnRiVEvV+l2jAZfdIhtV7xhiIZ3XmiojUnEJUERERERERkcNle6BudvUAqraTwPZCvBdSQ1Ded8BoGFDvd1jYHGRJa5iOeh/FcoXBZI5Etkh5hhWnFv3N9K94L7sv+A+SrWdiGRVeZ9/Nz3PvY/gv1/HjhwbITXZ7AsOk6G+mbHnxjGzCO7QOM5/AY1u0R7xkCyXWdMfY0p8kW1BVqojUjj3dCxARERERERE5atgu1HVCqBWSAzC2GxL9YDngj4L57B/DDaN6+FTIa9Mc8jKWyTOYyDGSymKZJiGPg20b0/DJ7Fs+3EXvmR/DO7KJunU/JTSylrfYf6K35yE+PvRBXveCpcyJWJO6hrIbpGx7cdL9WPk4+boFFAKtNAQ9ZAsltg8lGcvkmdcUpDHomdS1iMixQZWoIiIiIiIiIrVmORDpgFmnQccK8EaqoWpyAEqF/V7mdUxaw16WtIVZ1Bom4nOI5woMJXNkZ1i/z2x0CX1nf4G9Z32GuLeDNmOEb+U/yf/cdi83b8tP/pZ606YQbAMDvENr8Yxswihm8ToWbREfyWyJ1d1jbB1IkJ+BPWdF5MiiEFVERERERERkslg2hNufDFNPAV8UUoOQ6INSfr+XOaZBQ8BlUUuIpa1hWsNe8uUyg8ksyZm01d8wSDevYPCCrxFrOJGAkeP71rWMrvwtn78vTSo/+b1JS546ir4onvgufAOPY6cHMQ2DppCHoGuzdSDF2r1jjKb2//UWETmYKQ1R1dhZREREREREjkmmVd3i33FKNVANNENqGOJ9UMzt9zLDgLDPZm5jgONaw8xtCGKbBiPpHGOpAsXSzPg5u+wGGXj+pxnreiGWUeFTzs+4oO/HvPOWGBuHp+bQqXywDbOUwTu4GndsK0Ypj9+1aQ17GUsXWL1njJ1DSYqlmZJAi8iRZMp6ou7YsQOAcDg8VVOKiIiIiIiIzCymCcFm8DdCZgRie6pVqeUS+OvB8e/3Up9r4XMtGoMeYpnqFv9YukCFCgGPjdeZ3D6kB2XaDJ70bgrBWTSuv54r7duYXRjgvbe/m1cvr+e1S1xMYxJ7uxomRV8jZiGNZ2wLVi5Orm4eeOpoDnlJ5ops6kswli4wtylIxOdM3lpE5KgzZSFqV1fXVE0lIiIiIiIiMrOZJgQawd8AdaMQ74FEL6RGwBcBN1gtQ90HxzJoDLpE/S6JXJHhVJaRVIFEtoDPsQl47P1dOvkMg7GFl1EItNL66LWcz2puND7NP63+dx7va+FDz/NR753cTbFlx0/Z8mBnBvEPxslF5lMItBP02Hhtk8Fkjli2wLzGIO11Pixz5hzaJSIzl3qiioiIiIiIiEwXwwB/FFqXQefp0LQISkWI74XsGFT2v/XcNCHis5nXGOS4tjBd0QCGAcOpLLH09G71T7WfRffZX6boqWepuYebPB+nOPAEb7slxWN9k7+9H9OiGGilbNp4h9bjHdmIWUhhWyatYR+2YbKhN876nhjJ3BSsR0SOeApRRURERERERGYCbwSaFsPsM6BlGWBCrAfSw9Xt/gfgdy066n0c1x5mQVMIv2sRyxQYSebJFaanB2iufiF7zv06ufAcmowYv/J8ljPyD/Ghu9P8eHWWYnnyQ96yG6bob8JJduMbWIWd6oNKhbDPoSnooXcsy6rdo/SMZShPwXpE5MilEFVERERERERkJnEDEJ0LnWdA+4lge6tb/ZMDUCoc+FLLpCnkYXFrmMWtIRqCLtlCiaFEbloqU4v+Jvac/RVSLafiJc8P3G/ydut3/PfGHO+7I01vcvID3orlUAi0QaWAd2gNntEtGKUcjmXSXuejUoF1e2Ns6ouTzqsqVUT2bdJ6om7dupX+/n5GR0dJJBKEw2Gi0Sitra3MnTt3sqYVEREREREROTo4XqibDaE2SA1WD6FKDVZbAPiiYHv2e6llQr3fod7vkMgV6YtlGUzkCLgWfs+UHY8CQMXx03PGx2la92Pqtv+eDzk3stDq40PDV/P2P5d4/2k+zp09yYc8GQYlbxSjmMWNbcPKjZGrX0DJG6XO7+Ivltk1kiaWKTCvKUhzyIMxbY1lRWQmqtl3zkqlwq9+9StuvPFG7r33XkZGRvY7tqmpibPPPpsrrriCyy67rFZLEBERERERETn6WA6E2yHYUt3aH+uGZH91i7+/Hhz/AS8PeWz8jUGCHpuesQwjyTx1fhdzKvemmhaDy99GPthO05of8Srzbhb4B3lj+l/53P2wsq/Iv6zw4rUnN7is2F4KwVbszDC+wVXkw/PIh2bh2jYdER+j6QJrumN0Rf10Nfrx2NakrkdEjhw1+Zb5pz/9iSVLlvD617+e3/3udwwPD1OpVMYfwDPeHhgY4De/+Q2vec1rOOGEE7jjjjtqsQwRERERERGRo5dpQbAZ2k+ubvWvnwP5NIx1Qy4Blf1v17dMaIt4WdQSIuxzGE5lyRYO3Gd1MsTmvYyeMz9O2fZxYnk9t4c+RZfRz83bC7zr1hQ7xqZgTYZF0d9M2fLiGdmEd2gdZj6BYRhEAy51PoftQ0nWdscYS+cnfz0ickQ47BD161//Oi9/+cvZunXreGD69w70/vXr1/OSl7yE733ve4e7FBEREREREZGjn2GAPwqty6DzdGhaBKUixPdCdgwq++8zGvLaLGgJ0lkfIFsoMZrKHyh7nRTp1tPYc/ZXKPiaaC70cGvgE1zg3cyueJl33ZbiD1vz+80RaqnsBikEmnHS/fgGVuEke6BSxutYtIZ9jKULrN4zxp6RtA6dEpHD287/i1/8gg984AMA471CGhsbednLXsYZZ5zB4sWLiUQiBINBEokEsViMTZs28dBDD/GHP/yBoaEhDMOgWCzy7ne/m+bmZl796lcf/mclIiIiIiIicizwRqqPyCxI9Ff7psZ6wPWBt65avfp3HNOgM+oj5LXpHkszlMwS8bm49tTt789H5rLn3K/R/uBn8Y5t4cfG5/mP6Nv5xshZfOvRLCv7i7z/NB9Bd5L7kpo2hWAbVm4M79BazNwY+cg8LNtLS9hLPFNgQ0+M+JO9Un2utveLHKuMygR/vdPd3c0JJ5xALBYDIBwOc+211/KmN70J13UPen0ul+OnP/0pH/zgB0kkElQqFaLRKGvXrqWtrW0iSzrmxONxIpEIQ0NDNDQ0TPdyRERE5ChTKBS4+eabueSSS3CcST7wQ0REaqOQhdQAjO2GzChYLvjqq31V9yFXLNMXy9IXy2KZBhGfA1N4npJRzNL62NcJ9t4PwD0Nr+WqnldQqhi0+A0+cpaP4xqn5iAso5TDSQ9R9NaTj8yl6GsCwyRfLDOYzFHnd1jQHKQxuP8DveTQ6XWGzBRP5WuxWIxwOLzfcRP+NdPXv/51YrEYhmHQ1dXFypUrectb3nJIASqAx+PhrW99K4899hidnZ0YhsHo6Cjf+MY3JrokERERERERkWOb44W62dWeqR2ngK8OUoOQ6INS4VnDPbbJ7KifhS1BPLbJQDJLsTh1W9crtpfe0z/EyMJXAXD28K/466zr6PIX6E9XeN8daW7ckKM8Bdv7K5aHfLANs5jGN7AK3+Bq7PQgrgXtES+ZfIk13WPsGExSLO2/ZYKIHJ0mFKLmcjl+9rOfAeA4Dr/+9a+ZN2/ehBYwf/58fv3rX+M4DpVKhRtuuIFC4dnf2EVERERERETkEFkOhNuh41SYdRr4G6thamoQys88vMkwIBpwWdASpC3sZSybJ5ktTt1aDZPh499M/0nvpmJYdAz+lT9GvsTLZqUpV+Ana3J8+O40I5kpCC4Nk6KvkYK/ESs7jHfwcbyDa7CzwzQGHPyOzeb+BOt74iRzU/g1EpFpN6EQ9fbbb2dkZATDMHj961/PKaeccliLOPXUU7niiisAGB4e5o477jis+4mIiIiIiIgI1Z6owWboWAHtK8ANQbwX0iPPOoDK51jMaQiyoCkIwFAyR6k0dVWp8TkvYu9Zn6ZkBwiObuRr6Y/xueVDeC1Y2V/ibbekeKR3ioJL06Hob6bkbcDODOIbWIl3aB3hcoyWoIe+WJZVe8boi2Wn5BAsEZl+EwpRH3300fHn73rXu2qykKff5+GHH67JPUVERERERESEapgaboNZp0L7SdVeqbG9kI3B00JA04SmkIdFrUEaAh5G0nnSU1hxmWk6iT3nXkvB34Kb7uOKHR/mv07dyrw6k7FchY/8Jc1XHswQz01NcFmxHIqBFkreKHa6H9/ASoKj6+n0ZikXy6zdG2NLf5J8Udv7RY52EwpRH3vsMQBCoRArVqyoyUJWrFgx3rz16SGtiIiIiIiIiNSI5UBdZ3WLf+sJ1QA1thfyyWcMC7g285oCzG0MUChXGEnmKU9RTlgIdbLn3K+TiS7FKqRYsebT/HzxfbxykYsB3LazwD/dnOQvuwtTVgVasdwnw9Q6nHQfvv7HaMtuocFMsW0wwdq9Y8TSak0ocjSbUIi6fft2DMPg5JNPrtlCDMNgxYoVVCoVtm/fXrP7ioiIiIiIiMjfcbwQnQudp0PTYijmqmFqITM+xDYN2iJeFreECPtshlNZsoXSAW5aOyVPhL3P/zyJWediVEp0rP4PPuH5Jd+40MvscLUq9XP3Z/jkvRmG0lNXBVqxPBQCrZQ8YZzkXupHVjO3uIPE6BCrukfpHk1TLmt7v8jRaEIhaiwWA6C5ubmmi2lqanrG/UVERERERERkErkBaFoEs06H+jmQS0C8pxqqPinktVnQHKKzPkCmUGIsVWAqCkArlkvfKR9geHH1DJXolv/lou1f4brzK7zxeBfbhAf2FvmnPyX5/dY85SnsTVqxvRSCbZTcIN7UXroy6wmOPcHmHXvY1BefsrBZRKbOYYWo9fX1NV1MXV3dM+4vIiIiIiIiIlPAG4bWZdVt/uF2yIxCog/K1X6ojmXQGfWxsDmEz2MylMxOTR9Qw2Bk6T/Sd8q/UTZtgr0PsuCv7+Gt7Tv43gsDLGmwSBfg249m+cCdafbEpza8HA9TnQAN+b3MTm9geMdq1m7bw3Ayd/AbiMgRY0IhaiqVAsB13Zou5qn7PXV/EREREREREZlC/ii0nQQdp4K/EZIDkBqEcjWcrPc7LGwO0RbxkcgWiWeKMAUFoInO8+k++yvkA204mUFm3XsNp/T9im9e4OEdKzx4bVg7WOJtt6T4xfocxSneUl+xfRSC7RgeP7PKPdg9j7Jl3aPs6umjWNKhUyJHgwmFqFPVuFlEREREREREpphhQLAJOlZA+wpwgpDohfQIVCp4bJM5DQEWtgRxLBhMZikWJz8nyNUvYs953yI+6zyMSpmGTf/F7Ps/xms6E/zoxUFObbUolOH6tTneeWuKzSNTv6W+4vgphjoIh4LUpXcxsPEetm5cSSoxNuVrEZHamlCIKiIiIiIiIiJHOdOCcBt0nlatTjUdiHVDNoZBhYaAy8KWEM0hL2OZHMlscdKXVHb89J/6AfpWvJ+y7cM/vI7Zd76b+fGH+MK5fq4500vYNdg+VuY9t6W47vEs2SkIeJ+9zgBWtJNwIECmewM7Hr+LoZ3rqOSSU74WEakN+3AuTiQS7N69u1ZrIZFI1OxeIiIiIiIiIlIDlgN1nRBoqlakjuyshqn+enxukHmNQcI+h72jGYaSWeq8HmzbmNQlJWZfQDa6mNZHv4p3bCvtD3+esbmXcvGyqzmlNcD3V2a5a3eRX2/Oc193gfee5mNF62FFIBNiekMEW0KkEmPsfeJxskO7ae5ciFvfAa5/ytcjIhNnVCawN980TQxjcr4hVioVDMOgVNJJdgcTj8eJRCIMDQ3R0NAw3csRERGRo0yhUODmm2/mkksuwXGc6V6OiIjMFPkUjHVDbDcUc9U+qo6PdL5Ez1iGoWQOx7IIe22Y3CwVygUaN/yc+q2/ASAX7qLv1A+SD3fxUE+Bbz2aZTBdjT1eNNfhbSd7CbmTvah9y+VLpJOjNFhZWpqbCLbMrx7iZXumZT3TTa8zZKZ4Kl+LxWKEw+H9jjvs7fyVSqVmDxERERERERGZ4dwANC+GztOhfg5k4xDvxW8WmdcYZGFLCNc2GExmyRUm+VAl02Fo2dXsfd6nKXrq8MR30Xn3+wjv+BNntNn8+CVBXr7QwQD+vKPAP92c5K97CtOSQXhci0hdI4NmI9sGUwxtfYzCzodgbA+UClO+HhF5biYcok5G8KkgVUREREREROQI4Y1Ay/HVMDXcBqkhzEKChoDLopYQHXV+0oUio8k85UnOUtMtp7D7/P8g1bwCs5ynZfV3aXv4iwQrSd59io+vX+inM2wymq3w2fsyfOreDEPpSV7UPpgmNIS8lN0wW3IhtvaOMPjEQ+R2PgTxXihrV67ITDWhhiA7duyo9TpERERERERE5EhjGNXt/N666mNgI1RKeLx1dDX4ifgcesYyDKeyBF0Hn8eatKWUvPX0PO9T1G39LY0bfkaw9348Y1voO+XfWNa0jB+8KMAvNuS4cUOe+/cWWTWQ5K0nennJfAdzkloW7k/QaxPw2KRyLlsyOSJ7emka7ifcNAtv83zwN1S/tiIyY0woRO3q6qr1OkRERERERETkSGWa1a39pg0DGyA9DP4G6vwOAY/NYCJLbyxLKlmkzudiW5MUEBomYwsvI9O0nNZHvoyb6mXWvR9hZMnljCx6HVed4OXcToevP5xh00iZbz6a5c5dBd53mpdZ4ckLePe5VKMapgY9Nsmch22ZDOEdO4gO9hBp6cLfPBd89VO6JhHZv8PuiSoiIiIiIiIigmFAXSe0Lq++nRwAwLEM2ut8LGoN0RDwMJrOkcwWYRI7+uXqFrD7vG8R77wQgzINm37BrPs+gp0eYG6dxTcvCvAvJ3vwWrBmsMRbb0lx44YcxfI0tBl8MkxtDIcoBlrYlXbYvnUT3Wv/SmrPWsglpn5NIvIsClFFREREREREpHbCbdB6IlgeSPTCk+efhDw285uCLGgOgQGDySyF4uT1Ja04fvpPeR99p/wbJduHb3g9s+96D4Ge+7FMg8sWe/jhS4KsaLEolOEna3K869YUT4xMU19SA/wem4a6COVQO90pg+2b17B79d0k9m6CQmZ61iUigEJUEREREREREam1YBO0LQc3BPEeqFTDUsuE5pCHJS0hWsNe4tkisXSByTxnOtF5PnvO/zbZuoVYhSTtD3+B5lXfwShmaQuafOk8Px88w0vINdg2Vubdt6W4YU12eqpSn+RzLRrq6yHSQV+yxM4Nj7Bz1V3Ee7dSKeambV0ixzKFqCIiIiIiIiJSe/5oNUj1Nzzr5HmfazG3MciiliAex2QomSVbmLwK0EKgjT3nfIWRha8GILLzFjr/8n7c+E4Mw+DiuS4/uSTAebNtyhX4rw153ndHmp7E5FXKHgqvY1EfbcCIdDKYyLBz3QPsWPUXRnt3Ui4Wp3VtIseaCR0s9ZTHH3+cTKZaTj5v3jxaW1ufNeZTn/oUP/vZzw7pfpdddhnXXnvt4SxJRERERERERGYKb6QapPavr1akhtuqh09RbaEaDbgEPDYD8Sx98SzpXIk6v4s5GSVfpsPw8VeRaTqRlse+jiexm86738/QCW8hNucl1HtNPnqWn+fPKvDNRzJsGi7x9j8neecKLy+c62AYk3QY1iHwuBaeaDP5QoGx2DCJkXvxNbQT7VhItKkd05raQ7FEjkUTDlHXr1/PaaedRqVSoaGhgXXr1u1z3PDwMDt37gQ44DecSqXCt771La666iqWLVs20WWJiIiIiIiIyEziBqD1BDAsiO+FUAtY7viHPbZJZ9RP2OfSM5ZmOJUl4Nr4PYdV97Vf6eaT2X3Bf9Cy8psE+h+lefX38A+spP/k91B2w5w32+G4BosvPZhh7WCJax/O8khvkX89zUfInb4gFcB1HNyGVor5AqnRAVIjfQw1dNDQsZBoYyuWpQ3HIpNlwn+7PvOZz1AuV8vav/Wtb9Hc3HzA8YZhUKlU9vsAKJfLfOELX5jokkRERERERERkJnJ81SC1fi4kBqCYfdaQiM9mQUuIuY1BipUKQ8kcxdLk9CUteeroOfOTDC77ZyqGTbD3QWbf9R58Q2sBaA6YfPV8P1cv92AZ8Jc9Rd72pySrB2bGFnrbdQg2duCLNJMb3svutX9l4+oH6B8YoFCa3hYEIkerCf1aJx6Pc9NNN2EYBosXL+aKK644pOuuv/76/X7si1/8Ik888QS//e1vicViRCKRiSxNRERERERERGYi24XmpWCYMLIdAlFw/M8Y4pgGbREvIZ9N71iWoWQOj20R8thQ6yJQw2BswSvINC6j9dGv4Cb30nHvRxlZ/FpGFl+BZVpccZyHFS02X3ggQ0+yzL/fmeZ1S13etMyDY01vVSqA5XrwN3VSzmXIj+xg98he+hvn0NQxn4b6elxblakitTKhEPUPf/gD+XwewzB473vfe8jXXXnllfv9mOM4vOENbyCXy/G73/2ON77xjRNZmoiIiIiIiIjMVJYNzUvAcmB4S/WwKU/oWcOCrs38xiB1Poe9YxkGkzkiPmdSQsFc3Xx2n/dNmtb8kMju22jYfCOB/sfoO+X9FEKdLG6w+MGLAnzv8Sy3bC9w48Y8K/uLfPhMH7PCM6MXqenx4fV04c2lyA1toXtkD33RuTR1zKW5PqIwVaQGJvS36P777x9//vKXv7wmC/mHf/gHfD4fAA899FBN7ikiIiIiIiIiM4xpQeNCaD4O8inIxvY9zISmkIfFrSHaIh6S2SJj6QKVSdjhX7F9DKz4V3pP/XdKTgDv2BZm3/Ue6rb8BiolfI7Bv53u4xPP9xFy4YmRMv/y5xR/2pYfb1E4I3gCeBo6qfd7cIc20LPuHjZs28FIKj/dKxM54k0oRH388ccBWLp0Ka2trTVZiM/nY/ny5VQqFR577LGa3FNEREREREREZiDDgPo50HI8FHOQHtnvUJ9jMachyMLWIF7XZCiRpVicnOAyOetcdl3wXVItp2CWCzSt/3/MuudDOMm9AJzd6XDdi4Oc1GyRLcHXH8nymfsyxHMzqA+pYVDxRnAbOmlwCpR61rB+2062DSTJF2fQOkWOMBMKUXfv3o1hGMybN6+mi3nqfj09PTW9r4iIiIiIiIjMMIYBdbOhdTlQgeTAAYdG/S6LmkO0RryMZXIks5NzyFPJ10jPmZ+i/6T3ULJ9+EY2Mvuu9xDZ9juolGnym3z5fD//fKIH24R7u4u89ZYUK/tmxqFT4wyTcrCZqFsimtjK9r29rOkeU1WqyARNKEQdGxsDoKWl5aBjFy5cyLnnnss555xz0LGhULUPyujo6ESWJSIiIiIiIiJHmnAbtJ4IlguJXg60X99jm8xpCDKvKUi5UmEkmac8GcWVhkF8zgvZfcF3STedhFnK0bz2h3Tc+xHsVB+mYfDapR6+dVGAzpDJcKbCh+5O86NVWfKlGbS9Hyj6mwmQoquwg2RsjFV7RlWVKjIBEwpRC4UCAOVD+E71nve8h7vuuou77rrrkO+bz+u3IiIiIiIiIiLHjGATtJ0IbujJIHX/eYNpQkvYy6KWECGvzXAqO2mBYNHfzN6zPsvAie+gbHnxD6+j6853EdlxM1QqLIpafPdFAS6d71ABfrUpz7/enmJ3vDQp65kQw6Dgb8bNj9JZ3EHILLBlIMma7jGGk7npXp3IEWNCIWpDQwMAw8PDNV3MU/eLRqM1va+IiIiIiIiIzHD+KLQtB18U4j1QPnAQGfLaLGgJ0hbxkcgWJm17P4ZBbO4l7LrgO6QblmGWsjSv/h4d938cOz2AzzZ472k+Pv0CH2HXYOtomXf8OcXvt86gQ6cMk0KgFSszRH1yK21+iKULrO4eY+tAglxxBoW+IjPUhEPUSqXCpk2barqYjRs3AtDY2FjT+4qIiIiIiIjIEcAbgdYTINjyZJB64GDUtUzmNASY3xwEYCiZm5zt/UAx0MreF3yBwRP+mbLlwT+4itl3vovwrluhUuGsWQ7XvSTAihaLXAm+/WiWT9yTYSw7Q7bNGyYFfwtOqg//2GZaAgYB12brQIo13TFVpYocxIRC1OXLlwOwZcsW9u7dW5OFdHd3s2XLFgzDGL+/iIiIiIiIiBxjPMFqkBrugHgvlA7c8s8woCnoYWFrkHq/y1AyS64wScGlYTI2/xXsPv/bZKJLsIppWh7/Nu0PfhorM0yjz+SL5/l5+8keHBMe7CnytltSPNo7Qw6dMi3ygRacVC+e0S347QqtYS/xTIFVqkoVOaAJhagXXnjh+PPvfve7NVnI0+9zwQUX1OSeIiIiIiIiInIEcnzVILV+DiT6oXjwKsmgazO/KcjsqJ9Urkg8U4RJ2k1fCHbQffaXGTz+zZRNm0D/o3Td+Q5Ce+7CBF612MN/XBygK2wykq3w4b+k+f7KGXLolGlTCDTjJLrxjG7BokRzyEvQtZ/slRpjSFWpIs8yoRD1JS95Ca7rAvCd73yHrVu3HtYinnjiCb7zne8A4Loul1566WHdT0RERERERESOcLYLzcdBdD4kB6GQPugljmUwq97PgpYgllnd3l+arODSsBhb+Cr2nPdtsnULsQopWh/7Gm0Pfx4rO8r8eovvvjDAyxc6APzmiTzvvi3FztgMqPQ0HYr+Rtz4Ljxj26Bcwu/atEd8xDPVXqlb+lWVKvJ0EwpRW1tbufrqq6lUKiSTSS655BK6u7sntIA9e/Zw6aWXkkqlMAyDN7/5zbS0tEzoXiIiIiIiIiJyFLFsaF4CTYshMwb55EEvMQxoCLgsagnREPQwks6RzU9eGJgPz2bPOdcytPQNVAybYO+DdN35ToJ778FjG7z7FB+fPdtHncdg+1iZd96a4rdPTP+hUxXLpehrwBPfgRvbDpUypmGMV6VuG0yyes8YQ8nctK9VZCaYUIgK8LGPfYyGhgYMw2Dr1q0sX76cn/zkJ+TzB+5V8pR8Ps+Pf/xjTjzxRLZv3w5ANBrlYx/72ESXJCIiIiIiIiJHG9OChgXQtBRySUiPHNJlftdiXlOA2dEAmWKJsXRh0rb3Y1qMLr6c3ed9nVx4LlY+TtsjX6b1kS9j5mKc2eHww5cEOK3NJl+C767M8oE702wdnd5Kz4rtpeCtxxPbjhvfBU+GpX7Xpi3iI5ktsWrPGFsHkmQLqkqVY5tROYxfJ9x55528+MUvplQqUalUMAyDaDTKK17xCs444wyWLl1KXV0dgUCAVCrF2NgYGzZs4OGHH+amm25iZGRk/LcZjuPw5z//mfPOO69Wn9tRLx6PE4lEGBoaoqGhYbqXIyIiIkeZQqHAzTffzCWXXILjONO9HBEROdZVKpDohcHN1a39wZZqwHoIRtMFukfTJLIF6v0ebMuYvHWWC0Q3/zfRJ36FUSlT9NQxcOI7SbU/j0qlwk1bCvxodZZ8CQzgkvkOV53goc474Tq3w2YW0lj5GNm6JRTCs6vlvE/K5EuMpHNEAy5zG4M0Bl0M4/C/fnqdITPFU/laLBYjHA7vd9xhhagAv/3tb7nqqqtIJBIA42HqwTw1rlKpEA6H+elPf8orXvGKw1nKMUchqoiIiEwm/XAjIiIzUmYMhjZXD5wKNoHtPbTLCiX2jmYYSOQIujY+z6EFsBPlGd1Cy8pv4EnsBiA+63wGl7+NshukP1XmR6uy/GVPEYCAA2843sMrFro4kxnwHoCZT2IWUuSiSymEZj3jY+VKhZFUnlK5wuyon9kNfrzO4X399DpDZopDDVEP+9ccr3zlK3n44Yc555xzxqtKn/7fv3/8/cfPO+88HnnkEQWoIiIiIiIiInJwvjpoO6l64FRqGLJjh3aZYzG3McjcxgD5UpnRZJ7JbPWZq1/InvO+ycjCV1PBJNx9F113vgN/3yO0BEw+9nw/X7/Az4J6k1QBrluV4623pHhwb2FaepCW3SBlx4dndDN2qvcZHzMNg8agh7DXYftQklV7xhhMqFeqHFtqUiu+aNEi7rrrLh544AGuvPJKZs+evd+/SJVKha6uLq666ioeeOAB7rzzThYuXFiLZYiIiIiIiIjIscD2QPNSaFsO5VJ1m3+lfNDLLBPaIl4WtoTwey2GklkKxYNfN1EVy2X4+KvoPucr5IMd2NkROh78NM0rv4VZSHFCs813Lg7w/tO81HkMuhNlPn5Pho/8Jc2u2NT3IC27YSqWi3dkE3a6/1kf97kWbREfmXyJ1XvG2NKvXqly7Djs7fz7s2fPHnbv3s3IyAiJRIJQKEQ0GqWrq4tZs2Yd/AZyUNrOLyIiIpNJ2+xEROSIkB6p9klNDUKwuRqwHoJcsczesTT98Rxe2yLotSd1mUYxS8PGn1O37XcYVCh66hg6/moSneeDYZAqVPjF+hy/eSJPsQymAS9f6PLG4z2EPVO7xd/KjmIAmYbjKfka9zkmWygxnMpR53dZ1BIiGnCf0xx6nSEzxZT1RJ3J8vk8//3f/80vf/lL1q9fT39/P/X19cydO5fLLruMq666isbGfX8zmIihoSHuu+8+Hn74YdauXcu2bdvo6ekhmUziOA719fUsW7aM8847jze96U10dHQc1nwKUUVERGQy6YcbERE5YhQyMLQVxnaBNwye0CFdVi7DYDJL91iGYrFCnd/FnOTznbxD62h5/Nu4qR4AMtHjGFj+dvJ18wDYmyjzw1VZ7t9b7Zcacg2uPMHDS+c7WObUhal2ZoiKYZNtPIGSt36fY8qVCkPJHB7H4oT2CBH/ob9e0OsMmSmO+RB106ZNXHHFFaxatWq/Y5qbm7n++uu55JJLajLnS1/6Uv74xz8e0liPx8OHP/xhPv7xj2NO8Du0QlQRERGZTPrhRkREjijlEozthqEtQAUCTc84Zf5AEtkie0bSjGXyRHwurj25SapRKlC37bdEN9+IWcpRwSQ29yUML30jZTcIwMq+It9/PMvOWLXdwJyIyb+c7GVF6+RWzD6dnR6gYvnINB5P2VO333H98Swhr82yjggBz6GtT68zZKY41BB16v7mTaHu7m4uvPBCenqqv9UxDINzzjmH+fPnMzg4yO23304mk2FgYIBXvvKV3HLLLVxwwQU1XUNjYyNLly6lq6uLYDBIOp1m69atPPzwwxSLRXK5HJ/61KfYvn07P/3pT2s6t4iIiIiIiMgxx7QgOhfcIAxugngPhFrAPHj0EfLaLGgJ0juWpTeWwbEsQl77UDPY56xiOYwueg2JWefRuP7/Edp7D3U7/khw770MH38l8dkXsaLV5gcvCvDHbQVuWJtjZ6zMNXenOavD5q0neekITXLJLFD0NWGnB/AObyTbuIyyu+8K3+aQh95Ylif6EyxtC+N1rElfm8hUm1Al6mc+85nJWMszfOITn5jwteeccw733HMPAF1dXdx0002ceOKJ4x8fGhri8ssv54477gAgGo2ybds26urqDmvN1157LaFQiAsvvJAFCxbsc0x/fz/ve9/7+OUvfzn+vv/5n//h1a9+9XOeT5WoIiIiMplUISIiIkesfAqGnoCxPeCPghs4pMsqFRhO5emNZUhkC/gcm4Bn8sLUp/gGV9G05jo8iT0AZOoXM7j87eTqqwdxx3MVfr4+x++25ClXwDbhskUurz/eQ8CZ5MVVKjipPkqeerKNx1N29v21LJUr9MUzzKr3s7g1hGMdOOTV6wyZKSZ1O79pmhiT/B2kVJrY6W4333wzl156KQCu6/Loo49ywgknPGtcKpVi+fLlbN++HYAPf/jDfOELX5j4gp+DSqXCRRddxJ133gnARRddxG233fac76MQVURERCaTfrgREZEjWqkIIztgeCvYDvgP/efmQqnCSCpHXyxLKl/C51gEPTZMZhRSLlK37Xc0bP4lZjFDBYP4nBcxdNybKLvVYGdXrMQPHs/yaF81M6nzGFy93MML505yv9RKuRqk+hrJNBxPxfbtc1ihVGYgkWVuY5CFzUHMA6xJrzNkpjjUEHXCtd+VSmXSHofju9/97vjzK6+8cp8BKkAgEHhGRe11111HsVg8rLkPlWEYvPnNbx5/+/HHH5+SeUVERERERESOGZYNjQug/SQwbIjvhfKh/dzvWAYtYS9L2sLMbQyAUT2AKp2bxNzAtBlbeBk7L/wB8VnnYVAhsvMW5tz2NiI7boZKia6IxRfO9fO5c3zMCpmM5Sp8/ZEs77otxdqBSVybYVIItGBlhvCObMIoZvc5zLFMGgIedgwl2TWcOuyMR2QmmVBP1HPOOWfSK1EnIplMjm/RB54RVO7Lq171Kt7+9reTTCYZGRnhr3/9a817o+5PU1PT+PNEIjElc4qIiIiIiIgcUwwDwm3V7fxDT1T7pAYawdl3JeXf89gmbREv9X6X4WSOgUSOwXiWkNfB605O38+Sr4H+Uz9AbM6LaV7zAzzxnTSv/h7hXbcyuPztZKNLOKPdYUWLzU1b8vzn+hxbR8u8/84053ba/PNJXloCk9Av1bAo+FtwU31UMMg1LKVieZ41zOtY1Ptdtg6mcB2LjrpD+1qLzHQTClHvvvvuGi+jNu6//35yuRxQrTQ97bTTDjje6/XyvOc9b3wr/Z133jllIeqGDRvGn8+ZM2dK5hQRERERERE5JnnD0Lq8GqaObIdiFnz1h365Y9JR7yMadBlKVMPURKJQDVMn6RClbOMydp/3LSI7/kjDxv/EO7aVzr9+gNjsixg+/irw1PHqJR4umuNww9ocf9pe4C97ijzQk+Q1S1xet9SDz65xAZxpkQ+04KR6wbTJRheD+eyt+H7XplCq8ERfHMcyaA55a7sOkWkw+Ue5TaGNGzeOPz/hhBOw7YNnxCtWrNjn9ZOpp6eHa6+9dvztiRwqJSIiIiIiIiLPge1C0xJoOxEqQLwPys/tPBafY9EZ9bOkLURHnZ9cocxQIke+WJ6cNZsWsfkvZ9dF1xGffREAkd2303X724hs/z2US9R5Td57mo/vvTDAic0W+RL81/o8V/8xyZ07C7XfUm/aFALNOIluPKNb9tsiIeJzMDB4oi/BWDpf2zWITIOjKkTdvHnz+POurq5Dumb27Nnjzzdt2lTzNT0lnU6zYcMGvva1r3HyySfT09MDwNKlS/nQhz40afOKiIiIiIiIyJMMAyKzoOPkaiVqvAeKued8m4Br09XgZ3FbiJaIh3S+yFAyR2GSwtSSt57+Fe9lzzlfJRuZj1VI0bzmOmbf/a94h9cDML/e4qvn+/nE8320BgyGMhW++GCGLz+YJVOsdZDqUPQ34sZ34Rnbvt8wuiHoIVsos6kvQXIy+8mKTIGjKkQdHh4ef97S0nJI17S2to4/HxkZqdla7r33XgzDGH8EAgGOP/54PvCBDzAwMADAJZdcwv33308oFKrZvCIiIiIiIiJyEL766oFT0XmQGoJsfEK3CXls5jYEWdIapinoIZErMpLMU6x1aPmkbHQpe877OgMnvoOSE8QT30nnPdfQ8ujXsLIjGIbB2Z0OP7kkyJXLPJgG3LGrwHtuS7En/tyqbg+mYrkUfQ144tvxjG3BKO07jG4OeYhlCmzui5Mt1HYNIlNpQj1RZ6pkMjn+3Oc7tMbFTx/39OsnU319Pd/73ve4/PLLn9N1uVxuvOcrQDxe/SZfKBQoFAo1XaOIiIjIU68v9DpDRESOThbULwTLB8PbINcHgaZqtepz5HVMZkf91PtdBhI5RlN5TCDoc7CtWh/MbTLS9RJirWfRtOnnRHbdSrj7LgJ9DzK0+PWMzn0plmlzxXEuy5pMvvBAlp2xMu+6NcX7TvNydueze5hOfCkeSm499tgOnFySfN18yu6zC8Wa/Db9Y2ksyixqCeFYpl5nyIxxqH8Gj6oQNZvNjj93XfeQrvF4/naSXCaTqdla2tvbeec73wlApVIhkUiwefNmVq5cyejoKFdccQU//OEP+cEPfsCiRYsO6Z5f/OIX+fSnP/2s99911134/f6arV1ERETk6Z46hFNEROTot7emd+sfrentni36j9R5nsfy7p9Rn95Oy/qf4Nt2C2tnvZGh0HG4wPuOh58+YbEtYfD5B7KctzPNy2eXsWq6N9kHo0noWX3AUbuefDydXmfIdEun04c0zqjUvMPw9Ln00ku5+eabAbjmmmv40pe+dNBr/vSnP3HJJZcAEAwGSSQSk7rGnp4ePvrRj3LDDTcA1arUu+++m+XLlx/02n1VonZ2dtLb20tDQ8NkLVlERESOUYVCgdtuu42LL74Yx6lh1YqIiMhMlM/AyDYY2wP+OnADh3W7chlimTwDiRyxTB7HtAh6HczJaKxYKRPZfRtNG3+Kna/mGvH2sxk4/mqKvkZK5Qo3rM3zP5urBzwd12jxkTO9NPpruxgrO4pRypMPd1EIzwbzma8fcsUSw6k88xuDdEQcbr/9dr3OkGkXj8dpbGwkFosRDof3O+6oqkQNBoPjzw+1qvTp455+/WRpb2/n+uuvJxwO8+1vf5vR0VEuv/xy1q5di2VZB7zW4/E8o3L2KY7j6BuOiIiITBq91hARkWOC44BvOfjDMPQEVPLgP4yCJQuaHS/RoIexdIH+eJaxTB6PbRHy2hPpGnDAyZJzX0y64/k0bPxPIjv+RLjnHgIDj9J7+kfJNJ/EW0/2cnyTxVceyrBhqMS7bkvz0bN8nNRSw2jIH4ViBn9iO4VShnzdAsru37IWn2UTNSx2jWVx7WqAq9cZMt0O9c/fUXWw1NOrMfv7+w/pmr6+vvHn0Wi05mvany9+8Yvj6fbGjRv505/+NGVzi4iIiIiIiMg+mBY0zIf2k8GwId6z35PnD5VtGjQGXRa1hljYHMS1DYaSWZLZ2p9WX3ZDDJ74L+w57xtk6hdjFTO0P/gpAj33A/D8WQ7fe2GQeXUmY7kK19yd5sYNOco13KRcsX0U/K046T58g6ux0wPP+LjftQm4NtsGJ3cnsEitHVUh6uLFi8ef79r191029m337t3jz5csWVLzNe2P3+/nrLPOGn/7vvvum7K5RUREREREROQAQq3QcTIEGqtBanHfJ88/F45p0BTysKQ1zLymanXmYCJLsVT7Lou5uvnsfcGXSLSfhVku0vbwlwjvvBWAjpDJty4K8MK5DuUK/GRNjk/ekyGRr+E6TItCoA3KebyDa3BjO6D8t9A45HWwjWokNZrO125ekUl0VIWoS5cuHX++du1aisWD/1Zn5cqV+7x+KtTX148/Hx4entK5RUREREREROQAvBFoPRHq50JqCHK1qZx0LIPWsJfFrSGaQ17G0rlJqUqtWA59p11DrOuFGJRpWfVt6rb8LwBe2+ADp3t532leHBMe7Cnyjj8n2Tp6eFW3z2AYlHwNlN0AnpHNeIc3YBT+doBPXaB6IPjW/iSJ7KGdji4ynY6qEPWss84a7xmaSqV49NFHDzg+l8vx4IMPjr99wQUXTOr6/l5vb+/486lsJSAiIiIiIiIih8DxQstx0HI85NPVMLVGW9/9rsW8xiDzm0MADCVyta9KNSwGTno3IwtfBUDT+utpWH8DVCoYhsEl812+dVGA1oBBX6rCe25L8adtta0MLTsBCoEmnFQPvsHVWJlnFpElcgU29yXI5GsY4IpMgqMqRA0Gg1x44YXjb99www0HHP+b3/yGRKL6m6RoNMo555wzmct7huHhYR544IHxt6e6ClZEREREREREDoFpQXRutU+q5UKi97D7pI7f2oTmkIfFrSEaQx5GJ6Mq1TAYPv7NDB1/FQDRLb+medV3oFL9HBZGLb73oiBnttsUyvD1R7Jc+1CGXLGW2/sdCoE2zGIa39BqnPguqJQBaA55GUzmeKI/Qb5Yrt2cIjV2VIWoAO94xzvGn99www2sX79+n+PS6TSf+MQnxt9+61vfim1P/ES6kZGRQx5bLpd517veRS5X7ani8Xh46UtfOuG5RURERERERGSShVqqQWqgqWZ9Up8yXpX6ZK/UoWTtq1JHF76a/pPeTQWTyK4/0/rIVzFK1W30Idfg02f7uHq5B9OAP+8o8J7bU+xN1DDUNAyK/ibKlhfv8Ebc0c0AmIZBa8hLTyzD1oEEpXLte8SK1MJRF6JeeumlnH322UB1u/5LX/pS1qxZ84wxw8PDvPKVr2Tr1q1AtQr1mmuu2ef9du7ciWEY44/9Vbf+7Gc/47TTTuNnP/sZ8Xh8v+tbs2YNl1xyCTfeeOP4+/793/+dhoaG5/JpioiIiIiIiMhU84ah7USIzqtpn1QAy4SWsJdFrUEagx7GMvmaV6XG57yIvtM+SNm0CfXcS9uDn8EoZoBqmHnFcR6+dJ6fOo/B9rEy77w1yf3dte1XWnaDFP2NeBLd1XmzMWzLpDnoZfdImh1DSSo1apkgUksTL72cwX7xi19w+umn09vby86dOznppJM499xzmT9/PoODg9x+++2k09VmxrZt86tf/Yq6urrDnvfRRx/lyiuvxLZtlixZwuLFi6mvr8cwDIaHh1mzZs14cPuUV73qVXzyk5887LlFREREREREZArYHmg+DtwADG2BYhb8jWAYNbl9wLWZ1xgk5LXpGcsylMxR53OxrdrcP9nxAkpOkPaHPkdg8HE67vsYPc/7FGW32pv15Bab778owGfvz7BhqMQn783w2iUlrl7uwTJrs4aK5ZIPtMJoDN/wWoqVhRBoI+r3sH0whWuZzG4I1GQukVo5KkPUWbNmceedd3LFFVewatUqKpUKd999N3ffffczxjU1NXH99dc/o4/qRD11oBVAsVhk3bp1rFu3br/jQ6EQn/rUp/jXf/1XLMs67PlFREREREREZIqYZrVPqhuAgY2Q6IFgC5i1iVksE1rDXoJem57RapDqdywC3trcP9N8Et3P/zwdD3wS3+hmZt1zDXvP+iwlX3WXbKPf5GsX+Pnx6hz/uznPrzbl2TxS4iPP8xH11WhTs1G9T9kw8Q6tw8wnMCJzKXkcnhhI4toWrRFvbeYSqYGjbjv/U5YsWcJDDz3ET3/6U1784hfT2dmJ67o0Nzdz5pln8pWvfIUNGzZw6aWX1mS+f/mXf2Hz5s1897vf5U1vehOnnHIKTU1NOI6D4zg0NDSwbNky3vCGN3DDDTfQ09PD+9//fgWoIiIiIiIiIkeqYDN0rIBAC8R7q1Wptby9azO/Kci8pgAlKgwlc5Rq1Cs1F11M99lfpuiN4knspvOeD+Ike8Y/bpsGbz/Zy8fO8uGzYfVAiX/5c4q1A7VtMVD2RCh663FjO/AOrSNsVCtRN/fFGU7Wru+syOEyKmo0ccSKx+NEIhGGhobUU1VERERqrlAocPPNN3PJJZfgOM50L0dERGTmKuarW/vHdoIbrPZOrbFErkjvWJahZJaAa+P31KYq1U7103H/x3BTvRQ9dew96zPkI/OeMWZPvMRn7suwM1bGNOAtJ3p49WIX4zBaGJTKFTbvGWVxZ321TUClhJMepGx5ydUvordUh8e1WNYRIeLT6xCZPE/la7FYjHB4/393j9pKVBERERERERGRKWG70LwUWo6HUh6SA1DjmrWQx2ZeU4C5jUGK5QrDNapKLQZa6D77K+TCc7FzY8y658N4h9c/Y0xn2OLbFwe4sMuhXIEfrsrxmfsypPI1/BwNi0KgFajgHVpDR3E3mWyGJ/oTpPO1rX4VmQiFqCIiIiIiIiIih8s0oX4OtJ0Ejh/iPVCubfhnmwZtES+LWkLU+11GMzkyudJh37fkraf7BV8k03AcVjFFx/2fwN/3yDPG+GyDa8708p5TvDgm3Ntd5J23pdgxdvjz//1aSp4Invg2Zue2MTY6zBN9CXLF2s4j8lwpRBURERERERERqZVgE7SfDKHWap/UQqbmU4S8NvObg8xpCJIvlxlJ5imXD++eZTfI3ud9hlTLqZilHO0PfY5g91+eMcYwDF620OUbFwZo9hvsTZR5920p7u8uHN7kf6di+yj4W3Ez/czJPcHIwB629CcplA7zkxQ5DApRRURERERERERqyROE1uXQuBDSI5CN1XyKp6pSF7eEiPgdhlNZMvnDq9as2F56zvgY8VnnYlRKtD56LZHtf3zWuMUNFt9/UYDT2ixyJfjMfRnu2VPbIBXTohBow6oUmJ3dzPCu9WzpiylIlWmjEFVEREREREREpNZsF5qWQNtyKBUg2V/zPqnw9KrUAPlSDapSTZv+U/6NsbkvxaBC85rvE930y2etPewx+ezZfi7scihV4HP3Z7h7d42DVMOg5GvA8IToKOxmZMdqtvaOUFSQKtNAIaqIiIiIiIiIyGQwDKibDe0rwAlMSp9UAMc0aK/zsbglRNjnMHK4VamGyeDytzG8+AoAGjb9F41rfwSVZ4aXlmnw72d4uXhO9cCpLz6Q4c6dNQ5SgbITgGAjrcVeRnasYmvPoIJUmXIKUUVEREREREREJlOgATpWQKht0vqkQrUqdUFLkNnRAPlimdHUYVSlGgYjS/+RgRPeCkD99t/RsvIbzwqBLdPgA2d4efG8apD65Ycy3LYjf5ifybNVLA+VcAstpQFGtq9k294BSuXaV/aK7I9CVBERERERERGRyeYGqlv7GxdBZhQyY5MyjWMadNT7WNQSIuS1GU7lyBYmXpUam/9y+la8n4phEt5zF20PfwGjlHvGGNMweN9pXl66oBqkfvWhLLdsr32QiulQCbfTRIyx7Y+wY89eBakyZRSiioiIiIiIiIhMBcuBpsXVQ6cqlUnb3g8Q9tksaA7RWe8jnS8RSxdggnljYvYF9J7+UcqmS7DvYdrv/yRmIfWMMaZh8J5TvLxioUMF+NrDWf64dTKCVAvCbdQbaUa2PcKu3bsUpMqUUIgqIiIiIiIiIjJVDAPqOmHWKRBshXgfZOOTMpVjGcyq97OwJYjHMRlM5igWJxY4ptrOYO9Zn6Fk+/EPr6Pj3o9g5caeMcYwDN65wstli1wAvvlolpu2TEKQapgY4TYiTonhrY+we+dWygpSZZIpRBURERERERERmWreCLSdCK3LoFyYtKpUw4Co32Vhc4jWsIexbJ5kdmLzZBuXsfcFX6DoRvDGtjHrnmuw0wN/N5/B20/28Nol1SD1O49l+c3m3L5ud3gMAzPUQtjrMLztUXZv30hZh03JJFKIKiIiIiIiIiIyHSwbonOh4xQINFcPncolJmUqr2MypyHI/KYgFWAomZvQoVO5ugV0n/MVCr4m3OReZt3zQZxE9zPGGIbBW070cPnSapD6/cdz/M+mSQhSATPYQMAfYmTbSrq3rqVcmnj/V5EDUYgqIiIiIiIiIjKdfPXQfhK0LINirrrFv1z7MNA0oTnkYWFLkKjfZTiVndChU4VgB93nfJV8cBZOZohZ930EJ9X7jDGGYXD1cg9vOL4apP5wVY4bN0xOkGoHInhCUYZ3rWHvlpVUipPQQkCOeQpRRURERERERESmm+VAw7wnq1Kj1e39+eSkTBXy2MxrDtJZHyBbKDGWKlB5ji1Fi75Gus/+MrnQbOzsCB33fmSfW/uvPMHLlcs8APxkTY7/XDc5QarrD+GEmxnatZG9TzxGpZCZlHnk2KUQVURERERERERkpvBHoe1kaFoK+TQkJqcq1TENOqM+FjSH8LomQ8ksheJz299f8kTY+/zPkw924GQG6bjvo1iZoWeNe8MyD1cvrwapP12X46drs1Sea2p7CDxeP05dG4N7ttC7+REquckJoeXYpBBVRERERERERGQmsV1oWggdp4K37smq1PSkTFXvd1jUEqIt4iWWLZB4jodOlbz17H3+5yn4W3BTvcy672NY2dFnjbviOA9vPakapP7n+jw/XZd/ztWvh8Lj8WJHOujv2U3fEw9TyYzVfhI5JilEFRERERERERGZiQIN0LECGhdDLg7JAajU/gR6j109dGpBcxCD6qFTpdKhJ5xFXyPdz//Ck4dNddNx/8cwc7FnjXvNEg//cnI1SL1xY57f7TYnpSLV63WxIu309fUysPkhKsnBms8hxx6FqCIiIiIiIiIiM5XtgebF1apUNwSxvTAJ/T4NA5qCHha1BmkIeBjN5MjkD72NQDHQwt7nf56iN4onvouO+z+BuY+erpct9vCuU7wA3Nlj8sPVuUkJUn0eByvUTs/QGINbHoF478EvEjkAhagiIiIiIiIiIjNdsOnJqtSFkIlBapDJ2A8fcG3mNQXoigbIF8uMJg99230h2E738z9P0Y3gjW2j/YFPYhae3YbgFQtd3n1KtSL1/54o8L2VkxSkem3MUDPdI2kGtzwMo7sm5WsmxwaFqCIiIiIiIiIiRwLHC01LqmGq7YNYNxSzNZ/GNg3a63wsbAkR8NoMJbPkD/HQqUKok73P/xwlJ4RvdDPtD34KYx9rvHS+y+XzShjAb7fk+fZjWcqTEHD6PTZmoIFdiQpD21fC0FYo174lghz9FKKKiIiIiIiIiBwpDANCLTDrVIjOh/QopIcnpcIy4rNZ2BKko85PMlskninCIUyTj8xl7/M/S8kO4BveQPuDn8Eo5Z417nktFd5/uhcD+MPWAt98ZHKC1IDXxvJG2JmyGd61FgY2QqlQ83nk6KYQVURERERERETkSOP4oOU4aD8ZTBfie6H47KDycLmWyeyonwUtQSwThlJZiodw6FSubgE9Z32asu3DP7SGtoe/gLGP4PLiOQ7XnOnDNOBP2wt87eEspXLtg9Sg18Zyg+zMeBnp3gj9G6BQ+ypeOXopRBURERERERERORIZBoTbYNYpUDcHUkOQHql5VaphQEPAZXFLiMagl7FMnlS2eNDrstEl7D3zk5QtD4H+x2h95MtQfvZ1F85x+PDzqkHqrTsKfPWhyQtSTcfH9myQ0Z4t0L8O8qmazyNHJ4WoIiIiIiIiIiJHMjcALcdXq1INC+I9UMrXfBqfazGvMcjcxgClSoWRZP6g7UWzjcvoOePjlE2HYN+DtD56LZRLzxp33myHj53lwzLgjl0FvvRgZvKCVNvDtmyE0f490LMasrGazyNHH4WoIiIiIiIiIiJHOtOESEe1V2qkE5KDkBmr+TSWCa1hL4taQoR9NsOpHLnCgZPUTPNJ9J7+ESqGTajnXloe/yZUnn3N2Z0On3i+D9uEu3cX+fwDGYqTEKSGvDamZbMtF2JsZAB6VkFquObzyNFFIaqIiIiIiIiIyNHCE4TWE6DtxOohUPG+STl0KuS1WdAcorPeRyKbP2iQmm49jd7TPkjFMAnvuYvW1d/dZ5B61iyHTz7fh2PCPXuKfO7+DIVD6MH6nNfvszEMi23ZEGOJOPSugnhvzeeRo4dCVBERERERERGRo4lpQl0ndJwE3lB1e/8+ttAfLscy6KjzM6veTzxbIF88cJCaaj+LvlM+QAWTut23ckL3f+4z4D2zw+HTZ/txTLivu8hn7suQn4QgNeyzqWCwLRNgLFOo9khN9Nd8Hjk6KEQVERERERERETka+eqh7SQINj0ZpB78MKjnyjShvc5PR52PeDZP4SBBanLWOfSv+FcqGMwbup2mDf9vn0HqaW02nz3Hj2vBgz1FPnvf5Gztj/gdKmXYnvJUg9SBDZPSBkGOfApRRURERERERESOVp4gtC6vVqbGe6GYq/kUlgmz6v20hr2MZfIUD1I1mph9IX3L3wFAw7bfEt34n/scd0qrzeeeFqR+/eEs5UloTRDxO5TKFbalvQzHYlT610M+XfN55MimEFVERERERERE5Gjm+KD5eIjOg9QgFDI1n8IyoTMaoDXsZTR98CA1NufFrJn1BgAanvhv6jf/9z7Hndxi8/GzfJgG3LazwI9X1z4EBqjzO5gYbEn56enZS6FvAxTzkzKXHJkUooqIiIiIiIiIHO1sF5qXQsMiyIxCLlH7KUyDzoYAzSEPo+kcpYMEqTuaXsjAcW8GoHHjz6nb8pt9jjuzw+EDp3sB+J9Nef574+QEqUGvTcjnYXchzO4dW0j2boTygdsTyLFDIaqIiIiIiIiIyLHAtKBxITQfB7kkZMdqPoVjGnQ1BGgKeRlJ5w6aQY4suIzhJf8IQNP6/0dk+x/2Oe7iuS5vO8kDwI9X57hl++RUibq2STQUYIgwu7asY2D3JioKUgWFqCIiIiIiIiIixw7ThPo50HoClIqQGqr5FI5lMDvqpzHoZTiZPXiQuvhyRha9FoDmNT8gvPPP+xz36iUeXrfUBeAbj2S5f2+hput+imlCNBKm6ETYu3U1O7ZvIX+QA7Pk6KcQVURERERERETkWGIY1YOmWpeDYUOiD2p8YJPHNulq8BMNehhOHSRINQyGl76R0fmvBKB51XcI7blrn0P/abmHF891KFfgc/dlWDNQrOm6n84fiuDz+RneuYaN23YQz05OaCtHBoWoIiIiIiIiIiLHolALtJ8IbhDiPVCpbbWlxzaZ0xCg3u8ynMoeOKc1DIaW/RNjcy/FoELLY98guPfefQwzeO9pXs7qsCmU4eP3pNk2Wqrpup/OCkSJek3yvetYt72b3liGSo0DZzkyKEQVERERERERETlW+aPQdiL4GyDWA+XaVnZ6nWqQGvG5DKdycJAgdXD524jNvhiDMq2PfpVA74PPGmaZBh95no8TmizSBfjwX9L0JCZvu3050ESTncM3uoUNuwfZ0p/U9v5jkEJUEREREREREZFjmTdcDVLDbRDvhVJtD23yuRZzGwMEPfYhBKkmAye/i/is8zAqJdoe/hL+/kefNcxjG3z2bD/z6kxGsxU+dHeKkcwkBZuGQSHQTLQ8QktuJzsGYqzviWl7/zFGIaqIiIiIiIiIyLHO9VcPm6rrgkQ/FLM1vb3ftZjbFCDgsRlJ5Q8SpFr0r3gfifbnY1SKtD30BXyDq541LOAafPFcP20Bg95UhQ//JU0yP0lb7Q2Lgr+ZYKaX2fQxGM+yes+YtvcfQxSiioiIiIiIiIgI2B5oOR4aFkBqGPKpmt4+6NrMaQjgdUzGUgepdjUt+k79d5Ktp2OW87Q/8Bn8/Y89a1jUZ/Kl8wLUew22j5X5xD1pcsXJCTUrlkPRV48vsZ3Z1jCVCqzbG9f2/mOEQlQREREREREREamybGhaUn1kY5CN1/T2Ia/N3MYgjnMIkZRp03fah/8WpD74WQI99z9rWHvI5Avn+vE7sHawxBceyFAqT1KQavsoOQE8Y1toYow6n8P2oZS29x8DFKKKiIiIiIiIiMjfmCY0zIeWZVDIQHqkprcP+2y6on4A4ukDB48Vy6H39I+QaH9BdWv/I18itOfuZ41bUG/x2bP9OCbcv7fINx/JTto2+7IbpoKBZ/QJ/OUkrWEvg4kca/aM0RebvHlleilEFRERERERERGRZzIMqO+qHjgFkByo6e0jfqc6jQnxTPHAg02bvlP/nXjnBRiVMi2PfY3wrlufNWx5s83HzvJhGnDLjgI/WZOr6ZqfruRrwCim8Y5sxi5naYv4KFdg7d4YWwe0vf9opBBVRERERERERET2LdxWDVJtL8R7ocZVll1RPxUqJLIHC1It+le8l7E5L8GgQsvj3yay/ffPGnbWLIf3neYF4L835vmfTZMXpBb9zVi5ETwjm6FcoN7vUudz2Dao7f1HI4WoIiIiIiIiIiKyf4HGapDqjUC8B8qlmt26PuAypyFAqVwmebAg1TAZPPEdjM5/BQDNa66jfsuvnzXsxfNc3nKiB4Afrspx646DHGI1UYZJwd+Mk+rDM7YNKmW8jqXt/UcphagiIiIiIiIiInJgvrpqkBpsfjJIPUjg+Rw0BqtBar5UJnXQINVgaNlbGF70uuq1628guvG/nlUh+9olLq9e7ALwtYezPLB3kqpCTZuivwE3thM3vhsAyzS0vf8opBBVREREREREREQOzhOE1uVQ11nd2l+s3Vb5ppCHOQ1+csUymdxBKl0Ng5Hj3sjQcW8CoGHzL2lcf/0zglTDMPjnkzxcPMehXIHP3Z9h3WDtgt+nq1geSt4I7tgW7FTf+Pvr/S4Rr7b3Hy0UooqIiIiIiIiIyKFxvNCyDKLzIDkIhXTNbt0c8jK7wU+6UCKbP3jLgNFFr2XwhH8GoH7rb2ha8wOo/K3i0zQM3n+6lzPbbfIl+Nhf02wfq10rgqcrOwEqlot3dDNWdmT8/T5X2/uPFgpRRURERERERETk0FkONC+FpsWQGYN8sia3NQxoDXuZHfWRzBfJFg4eeI7NfwX9J72LCgZ1O/5I8+PfhsrfrrNNg4+e5WNZo0WqAB++O01vcnK21pe89VAu4BnZjPm0r8nTt/ev2xtj90jtgmeZOgpRRURERERERETkuTEt/n97dx4mVXXnf/xzb+1Vve/dNDSbgihqNICAiAY1BjUx8WcmLhNj4sTEbJpN4y5GTUycMZMxxiRuo3GcbOMSzeKGgoKCiCv7Dr2vte/1+6OkpKXpru6u7qab9+t5eLzV99zzPbfg4bl+OPcclR0mlR8hhbpyNiPVMKTqQpdqi9zyh2OKxPoOPL0Tz1DT8d9VSqYKdz6nqtV3dluz1Wk1tOQktyYVmmoPp3T10qA6wkMTpMZd5bJEu+To2Cgj0X25g2K3XR6HVZua/WroCg1JfQwdQlQAAAAAAAD0n2FIJZOkssOlQHvO1kg1DGlckUu1xW75IrGsNmXyjT9FjbN+qJRhUf6el1X9+k9kJD5cgzTfbui2k92q8hiq9yd1zUtBBaJD8Fq9YSjmqZQt2CR756b9NuDKc1jlsJja0OhTqz93a8pi6BGiAgAAAAAAYGAMQyqdkg5T/c1SIjebJ5mmVFPkVk2hS95wVLEsglT/uBNVP+c6JU2b8hpXqvq1W2TEw5nzZS5Tt5/sVpHD0OaOpG5cHlQ0MRRBqkUxd4Xs3t2ye7d32/BKkorcdqVS0vpGn7pCbDY1WhCiAgAAAAAAYOBMS3p91KIJkq9xv9mXA2Uxpdpit6oKXOoMRRXPIvAMVs1S/dwblbQ45Gleo5oVN8nYZ6mB2nyLblvoltsqvdWc0G0rQkokcx+kpiw2xV3FcnRtkc2/Z7/zZXkOhaMJbWj0KhDJzfeFoUWICgAAAAAAgMGx2KTy6VJ+teRrklK5WXPUYkq1JW6V5zvVEYx+dFJnj0Llx2rPvCVKWF1yt72rca9e322jp8NKLLp5gVs2U3pld1y/WB1WKpuO+ylldSlh88jRuVHWYMt+5yvyHeoIxLSxyZfVJloYWYSoAAAAAAAAGDybU6qcIblL0zNScxRM2kxD44vdKnTZ1BGIZnVNuPRI7Zl/qxK2PLk6NmjcK9fKjHRlzh9badWP5rpkGtLftsZ0/9tDsz5p0l6glCRHx4Zu9SXJMAxVFjjV5A1rc7NfscTQbHaF3CBEBQAAAAAAQG7YPekg1VEg+Zty1q3TZmpCiVt2qylfKLvX3yPFh2v3ibcrbi+Us2uLapf/SJZwe+b8gvE2fefjTknSY+ui+tP6oQlSE64yGfGgnO0bZMRD3c5ZTEMV+U7t7ghqa0tAySFYWgC5QYgKAAAAAACA3HEWSpVHShanFGjNWbf5TqsmlLoVSyYVjmb3+nu0cJJ2L/iJ4s4SOXw7Vbvs6m6v1i+eYtclMx2SpHvXRvTQO0Pzan/cXSFLuE2O9g1SsvtmUjaLqVKPQ9ta/drRFhiS+hg8QlQAAAAAAADklrskPSNVkkKdOeu21GPX+GKXfJGYYvHsXn+P5Y/X7gU/VcxVIXugXrXLrpIt0JA5f/4Muy460i5JeuS9qO58Pax4rmeEGqZinkrZAg1ydG7bb6kDp82iYrddm1sC2tMZOkAnGEmEqAAAAAAAAMi9/Eqp4ggpFpYivpx1W1ngUnWhU52hqJJZLiMa81Rr94KfKuqpkS3UnA5SfbskpdcmvXimU1d83CnTkP6xLaYblgUViuU4SDWtirtKZfduk82/Z7/TbrtVbptFG5t8avaGc1sbg0aICgAAAAAAgKFRME6qmJ4OUWPBnHRpMaVxxW6VeBxqD0SkLLPOuLtcuxf8VJH8CbKG21W77GrZu7Zmzp851a6bTnTJYZFWNST0vRcC6gjndrOnlNWphM0tR9fmbuuz7lXgsslimNrQ5Mt6Ey0MD0JUAAAAAAAADA3DkIrqpNLDpEC7FM/N5k12S3qjqTyHVZ3BWN8XfCDhLNbuE29XuHCKrNEu1S6/Ro6OjZnzc8fZ9PNPeFToMLSpI6lvPxvQLm92669mK+kolJJxOTo2yughWC7x2BWNJbWh0SdfOPt7w9AiRAUAAAAAAMDQMU2pdIpUMknyN0uJ3ASDbrtF40vcMkzJH45nfV3SUag9829VqHiaLDG/xr1yrZxt72XOTy+16BenelSTZ6gxkNIVzwX1fmv2/Wcj7iqXJdIpR+dmKbl/3+X5DnnDMW1o9CmU5SZaGFqEqAAAAAAAABhapkUqnyYVjZd8TVIyN8FgkdumCSVuReIJRWLZv3qftOdpz7xbFCybKUs8pHGv3iBX89rM+XH5pu461aNpJaa80ZR+8GJQr+7O4axQw1DMXSGbf4/s3u37bTRlGIYqC5xq9Ue1scmnaJabaGHoEKICAAAAAABg6FlsUvkRUn5VOkjNkfI8h8YVueQNRxVPZL8ZVMrmVv0JNypQcZzMREQ1r90ie+eHa6QWO0397BMeza62KpqQbn4lpKc25XCdUtOquKtE9q6tsgYb9z9tGKrMd6ihK6TNzT4lkjne6Ar9QogKAAAAAACA4WFzSpUzJFdx+nNq8MGgYUjVRS6V5zvVEYz2q8uU1amGOdcrUP6xdJD6+q0yI12Z8y6roSULXPrUZJuSKek/3wjrvrfCSuVg3On6LqWsTjk7NskS7tzvvNViqjzPqV0dQW1r8eesLvqPEBUAAAAAAADDx+6RKo9IHwdactKl1TQ0ocStQpet37vapyw2Nc76oaKeatmCTape9dNuyw1YTENXznLqi0c5JEmPrYvqjtfCivVj1mtvEo4iKRFJbzQVD+933m41VexyaGtrQDvb99+ICsODEBUAAAAAAADDy1GQ/q9pl4JtuenSampCqVt2qylvqH8bQSXt+WqYc62SFqfcrW+r7L37u503DEP/epRD35vtlGlIz22P6bqXgwrEchOkxt3lsoTbD7jRlMtuUb7Tpk3NfjV0hXJSE/1DiAoAAAAAAICRUTFNSialHl5lH4h8h1V1pW4lUsl+72ofLZioxuO/K0kq3vKE8ne+sF+bMybbdcsCl5xWaU1TQt99PqDWUA42fTJMxd3lsvl2y+7d0eMyB3kOqxwWUxsbfWr1RwZfE/1CiAoAAAAAAICRkVcpVRwhRUNS1J+TLks8do0vdisQiSnWz13tAzXz1Hb4v0iSKtb+Uo6OTfu1mV1j088/4VGRw9DWzqS+82xAO7r6F9j2JGWxKeEs+mCjqZ433ipy25VMSRsafeoKxQZdE9kjRAUAAAAAAMDIKayVyqdLYa8Uy82r6pX5TlUVOtUZiirZz4mi7UdcKH/lLJnJmKpfv1WWcMd+baaVWPSfp3k0Lt9UczClK58P6N2W/i0h0JOkza2UxS5Hx6ZuG1ztqyzPoVA0oQ2NXgUig6+J7BCiAgAAAAAAYOQYhlQ8USqZml4fNT74V9VNU6ot9qjU41B7ICL1Z+lSw1TTx7+vaF6tbKFWVa/6SY/rlFbnmfrFqW4dUWqRLyr98MWglu0a/OzQhLNYZiIkZ+emHjeakqTyfIfaA1FtbPIpHBv8LFj0jRAVAAAAAAAAI8s0pbKpUvEkyd/cY2jZXzaLoQklbuU5reoIRvt1bdLmUf2ca5WwuuRqe0/l7/y2x3aFDlN3nOLW3HFWxZLSLa+E9H8bBx8Cx9zlsgZbZO/aIiX3D0lNw1BVgUtN3rA2N/sVS+RgXVb0ihAVAAAAAAAAI8+0SGWHS0XjJW9Dj+Fhf7nsFk0o8chiGvKH+xfMxvLHq+n470uSirY9rYLt/+yxndNq6Mb5Lp011aaUpF+tiei3a8NK9rA5VNYMi2Luctl9u2X37eqxicU0VJHv1O6OoLa2BJRMDqIe+kSICgAAAAAAgIOD1S6VHyHlV0m+Rik1+BmWhS6rxpe4FYknFYn1c6Op6jlqm36hJKn87V/J2b6+x3YW09C3j3fqkpkOSdIf1kf1kxUhRRMDDzZTFrsS9nzZu7bIGmzusY3NYqrU49C2Vr92tAWUGkxwi16N6RA1Go3q4Ycf1uLFi1VXVyen06nq6mrNmzdPP//5z9Xa2przmtu3b9dvf/tbXXTRRTrmmGNUXFwsm82mkpISHX300brsssv00ksv5bwuAAAAAADAmGBzShUzJFeJ5GuSchAMluc5NK7IKV8kqng/g832af8if/Vcmcm4ql+/TZZwe4/tDMPQBUc69MM5TlkM6cWdcV37UlD+6MDHn7TnKWWY6Y2mor4e2zhtFhW77drcEtCeztxszIX9GakxGlGvX79e559/vtauXXvANhUVFXrggQe0ePHiQdd788039bWvfU2vv/56Vu1PPvlkPfTQQ5owYcKAa3q9XhUWFqq1tVWlpaUD7gcAAKAnsVhMzzzzjBYvXiybzTbSwwEAAGNIVs8ZoU6p4S0pHpLyKgddM55MaXtrQM3esMrynTKM7K81YkGNf/n7cvh2KlQyXXvm366U5cDPR6sb4lrySlChuDSx0NRtC90qdw9wLmMqJVugSXFXmcJlRyplcfTYzBuKKZpI6MiaQlUUOAdW6xC0N1/r6upSQUHBAduNyZmou3fv1qJFizIBqmEYWrhwob785S/r7LPPlsvlkiQ1NzfrnHPO0QsvvDDomhs2bNgvQD388MP1uc99Tl/96lf1+c9/XrW1tZlzS5cu1dy5c7V169ZB1wYAAAAAABhzXEVS5VGSaZOCbYPuzmoaGl/iVpHbrvZA/zZ/StncaphznRI2j1zt61X+9j29zpD9eLVV/77IoxKnoe1dSX3n2YC2dQ5wjVfDUMxTLmuwSfbOrQdc4qDAZZNpmNrQ5FNHoH8baaFvYzJEveCCC1RfXy9Jqqur05tvvqmlS5fqvvvu05NPPqmdO3dq0aJFktL/8nHeeeeps7MzJ7WnTp2qn/zkJ9q9e7c2bNigP//5z7r33nv1v//7v9qxY4fuu+8+ud1uSVJ9fb0uvPBC1qsAAAAAAADoiac0/Wp/Ii5F/YPuzmE1Nb7ULYfNIm+onxtN5dWo8eM/VEqGCnf8U4Xb/9Zr+6nFFv3iVI/GF5hqCaV05fMBvdXUv5oZhkVxd5nsvp2yHWCjKUkq8dgVjSf1Xn2Xmr3hgdVCj8ZciPrMM89o2bJlkiS73a6nnnpKxxxzTLc2ZWVleuKJJzR58mRJUnt7u+64445B1a2urtYDDzyg9evX66qrrtK4ceP2a2Oapr785S/rkUceyfxs5cqV+uc/e97dDQAAAAAA4JBXUC2VHSYFO6XE4GdY5jusqitxK5FKKhTp3+zQYOXxaptxsSSp/O175Wx9t9f2VXmm7lrk0ZFlFgVi0o9eCuq1+tiAxp2yOJSw58nRtUWW0IH3+anIdyqRlN6p79LOtoCSSSbv5cKYC1HvvvvuzPHFF1+smTNn9tjO4/FoyZIlmc/33nuv4vEB/muApIULF+pLX/qSLBZLn20/+9nPavbs2ZnPTz/99IDrAgAAAAAAjHnFE6WiCZK/+YCvs/dHiceu8cVuBaIxxeL966/jsHPlG7dARiqh6lU/kbWXQFOSChyGfnqyW/NrrYolpZuXh/RG48AyqKQ9X5Lk6NgoMxY4YLsSj11uq1XrG33a3OxXLDH47+xQN6ZCVL/fr+effz7z+ZJLLum1/bnnnqu8vDxJ6dmoL7/88pCOb1/z58/PHG/fvn3Y6gIAAAAAAIw6piU9G9VVkg5Sc6Ay36mqQpc6QzEl+5MxGoaaPvYdRQomyhrpVPVrt8roY4asw2rounkuzRuXDlJvXBbUW80DC1LjzlJZol45Ojb2WjfPaVWx266trX6ta/AqFB3gmqyQNMZC1FdffVWRSHphYI/Ho1mzZvXa3ul0au7cuZnPudhgKlvGPlvAJRL8IQYAAAAAAOiV3S2VT5dMqxTuGnR3pinVFrtV6rGrPRiW+vHWe8rqVP2c65Sw5cvZuUkVa+/udaMpKb2x1bXzXJpVbVUkIV33clDvtw4gSDUMxdyVsgaaZO/a3mtdp82iynyn6jvDere+S12hgS0lgDEWoq5bty5zPHPmTFmt1j6vOe6443q8fqi98847mePx48cPW10AAAAAAIBRy1MqlR0uRQNSPDLo7mwWQxNK3Mpz2Pq9o33cU6WG2VcpJVMFu55X4dan+rzGbjF043yXPlZpUTieXiN1Q/sAJteZFsVdJbJ7t8nm39NrU6vFVHWhU13BmN7Z06VmHxtODcSYClE3bNiQOa6rq8vqmgkTJmSO169fn/Mx9WTnzp3dZr2eeuqpw1IXAAAAAABg1CscLxXVpV/rTw7+7V6X3aIJJR5ZraY6g/2bqRkqP1atR31ZklT+7u/kanm7z2scVkM3L3BrZrlFwZj0o6UBbeno/32krE4lbG45OjfJEm7vta1pGKoscCoeT+rdPV3a1R5Qqo+Zs+huTIWobW1tmePKysqsrqmqqsoct7f3/gcuV7773e9mXuGfMGGCzj777GGpCwAAAAAAMOqZZnp91PxKyd+Uky4LXVZNKvPIahrq8Ef79Wp/55TPyFt7ioxUMr3RVKDvMbmshm45ya3ppRb5otLVS4Pa0dX/IDXpKJRSifT6qLFgn+1L8xxyWi1a15DecCrOhlNZ6/t991HE7/dnjl0uV1bX7Ntu3+uHykMPPaQ///nPmc+33367HA5HVtdGIpHMmq+S5PV6JUmxWEyxGGtaAACA3Nr7fMFzBgAAyLXBP2eYUtEUKRiQfG2Su3jQY8pzWFRX4taOtoBafREVe+yS0fd1ktRwzDdk9+2Us2uLql+7VTtO/KlSVmev1zgt0o8XuHT1S0Ft7kjqBy8G9fNT3BqX3785jwlHmWyBRlnbNylSMi29ZmwvPDZDFpna0tSlQDiiqeV5ctgs/ao5lmT7Z3BMhajh8IdrOtjt9qyu2TfADIVCOR/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r963F6tWruemmm5g8eTLhcJicnBwOOuggbr31Vqqrq7t13MrKSubNm8dVV13FIYccQkFBAYZhkJeXx6RJk7jmmmt46aWXunWs7rzXpmkyYsQI5s6d2+fvdXNzM/feey/nnHMOo0ePJhgMEolEOOCAA/jyl7/Ma6+91qPjDSRSibqfMHWVgrCJZbs0Jy3WbI8SMjVKcvzkBQwCplR49jfHgbTjYDsutuN6y7aL5bgkLZuU5eK6kBfUifgNAoa2o5OBooA/x7ulY9CwuVXf1OHevWb06+sTQgghhBBC7D++973vceedd+K6uxbv1NbWUltby7Jly/jzn//MZZddxt/+9jeCwWCvnPvxxx/nq1/9Kk1NTW0eX7FiBStWrODee+/lT3/6EyeffHK3j1lZWcmcOXN49dVXd3lu8+bNbN68maeeeoqf//znPProoxx++OHdPvaiRYu4/PLL2bJlS7f36UsrVqzgoosuYuXKlW0eLysr4/HHH+fxxx/ntttuaxPYdmX9+vVccMEFfPrpp20e37ZtGw8//DD/93//x9NPP81pp50GwAcffMD555/P1q1bdznOPffcw8MPP8xLL73E0UcfvZuvcvf8+c9/5qabbiKZTLZ5fOnSpSxdupT77ruPF198sdN//7vuuoubb74Z27Z3ea6hoYGGhgZWr17N/PnzOemkk1iwYAGFhYXdHmNH7/XWrVt56KGHWLBgQZ+91//3f//HjTfeSEVFxS7PrV27lrVr1zJv3jzOPvtsHn74YXJz962raCVE3c/omkJu0MB1W/qmRvEZGgVBk6Kwj7Cvg76pYre5Lliui2U7WI6bDUYtxyFtOSQth5TlkLYdbBdsx8F2wCUzcRYKKgqa6v3D1DYnMTSVnIBBftAg7NcJGK1CcCPo3ewUxGtb9U0dCaESMHvnBxMhhBBCCCGE6MiWLVtwXRdFUZg4cSITJ06ksLAQwzCoqanhk08+Yd26dYAXejY2NvLvf/+7TcXf7vjXv/7FlVdemQ2oNE3juOOO44ADDiAajbJo0SLKysq47rrr+OMf/9itY27fvp3jjjsuO16A8ePHc9RRR+Hz+VixYgXvv/8+AGvWrGH27Nm8+OKLHHfccV0ee+3atdx00000NDQQiUSYNWsWw4YNo66ujrfeeqvbr/v8889n2rRpLF68mA8++ACAI444giOPPHKXbTsLw7Zt28bJJ59MeXk5eXl5zJw5kyFDhlBdXc1rr71GQ0MDAHfccQdTpkzh0ksv7XJsjY2NnHHGGXz++efk5ORwwgknMGTIEMrLy3nttdeIxWIkk0nOP/98PvvsM9LpNCeffDKNjY0UFRUxa9YsCgsL2bx5M6+99hrpdJrGxkbOO+88Vq9evdeCuPnz5/P1r38dgIkTJ3L44YcTCARYtWoVixYtwnVdampqOPfcc1m5cmWH49q2bVv28zlu3DgmT55McXExfr+f+vp6PvvsM5YvXw7Aa6+9xsknn8x7772Hz+frcowdvdcVFRW8+uqrffpe/+53v+M73/lO9g8nOTk5HHPMMYwYMQLbtlm+fDkffvghruvy73//mxNPPJFFixb12h9P9gYJUfdTigJhv07Yr5NI2VQ0JqhsSpIfNCkKm+QEDHRV0tSu2A5YjoPlONg2WK6DZXuVpAnLJpV2Sdm295jrPe5k/xLroqCiKQqapqApYGgKAcNAU5VOw+yU5dAQS1MTTWAaGjl+g4KQSdin49MzXTo0E8Il4Nhe39TypWBGIGcoRIZ4waok5kIIIYQQQog+cNhhh3H66adz9tlnU1RU1O42Cxcu5Mtf/jJr167l+eef55FHHuHKK6/c7XNWVVVx3XXXZQOqQw45hCeeeIIDDjggu43ruvzpT3/i29/+Nt/97ne7ddxrrrkmG6CGQiHuv/9+LrvssjbbfPjhh1x66aWsX7+eaDTK5ZdfztKlS8nLy+v02L/61a+wLIsbbriBX/7yl4TD4exz6XQaTeveVaPf+ta3AO/S7pYQ9cwzz8xe3t1dd9xxB8lkkltuuYXbbrutTcBVW1vLxRdfnL0c+4c//CGXXHJJl8H3PffcQzKZ5LrrruPOO+8kEokA4DgOK1eu5KKLLmLVqlXE43H+53/+h2XLltHU1MTtt9/Orbfeimma2WMtX76ck08+mYqKCrZv384f/vAHbrvtth69xt11/fXXU1xczIMPPsjpp5/e5rm33nqLc845h8bGRsrLyzsd14EHHsgf//hHzj//fIYPH97uNkuXLuUrX/kKH374IUuWLOE3v/kNP/rRj7ocY0fvNXiVxKecckqfvNevvvoq3/3ud3FdF9M0ueOOO/jmN7+5S0C6ZMkSrrjiClasWMGSJUv47ne/yz333NPl6xooJEQV+E0Nv6mRthzqm1PUNCcJGhrqIAlRFQUUdn0tnb26HZfJt/Nc5kHbyVSXui6O4+5SPaqhoKpeBamuKpiqiq6qqL3QidjUVUxdBdcgYdnURVNUNSUJGBq5QZ28oEnEZ2BoCqgaBAsgkA+pKNSshfrN3sRUOcO851Rp5yCEEEIIIYToPd/73ve63GbmzJm8/PLLTJ48mUQiwR//+Mc9ClHvvPNOampqABg2bBgvv/zyLpdBK4rCN7/5TSzL4uabb+7ymK+//jovvPBCdv2JJ57grLPO2mW7ww8/nFdffZWDDz6YhoYGtmzZwl133dVlwGdZFtdeey1/+tOfdnnOMPZ+S7ZkMsmtt97Kz3/+812eKygo4NFHH2X8+PE0Nzezfv16Fi9ezFFHHdXlMa+88kr++te/7vLc8OHD+etf/8qsWbMAeOCBBwD48Y9/zI9//ONdtp86dSq//e1vs5+TltYCe8srr7zCjBkzdnl81qxZ/PznP+cb3/gGAI899liH4/ryl7/c5XlmzJjBK6+8wqRJk6ioqOCee+7h1ltv7TJU7+y9HjFiBPfffz/HH3880HvvteM4fP3rX8fJzMny+OOPc/7557c7voMPPjj7dbJ9+3buv/9+fvjDHzJixIhOX9dAIRNLiSxDV8kPmxQEfd4l6LY7KG5pyyWVuWQ+lbl8Pmk5JNq7pb1bPJW5JXfcYplbc9KmOWmTtLxvED5NI+zzKkGLwj6Kwn6Kwj7ywya5mcvt/aaGqfdOgNqGAn5DIz9sUhz2oakKVY3eBGLLtjWwuTZGXSyN5bheMuyLeD1SfWFo3AZlH3i3hq1gpXp5cEIIIYQQQgjRuTFjxjB79mzA683Y2Ni4W8dxHId58+Zl12+//fZO+0jeeOONTJgwocvj/uUvf8kun3vuue0GqC3GjBnDD3/4w+z6n//853Z7wrbm9/v59a9/3eU49pbi4uJOQ8nS0tI278HixYu7PKZpmvz2t7/t8PnjjjuOUaNGtTlH6/dxZxdccEG2YnLVqlW79L7tK1/96lfbDVBbzJ07F133ahVXr16925/lFrm5udkwsry8vN0JoXbWH+/1s88+y5o1awA477zzOgxQWwwZMoSbbroJ8KqtFyxY0On2A4lUoopdqCqE/PLR2OcoEDA1AqaG60I8ZbG1Po5CnJDpVafmBgxCPh3NCIARADsNiXrY+rE3KVXeKG8SKl+4y9MJIYQQQgghRHds3ryZxYsX8/nnn1NfX088Hm8TLm7YsAHwLrX/9NNPmTlzZo/PsXLlSiorKwHQdb3LXp2apnH55ZfzP//zP51u9/rrr2eXu1NBeM0113DrrbfiOA7l5eWsXr2aSZMmdbj9qaeeSn5+fpfH3VvOOecc/H5/p9sccsgh2eBr48aNXR5z5syZlJaWdrrNtGnT2Lx5c3YMrS8r31kgEGD8+PGsXLkS13XZuHEj06dP73Ice+riiy/u9PlIJML48eNZvXo1ruuyadOmLsdVWVnJe++9x8qVK6mrq6O5ubnN18aHH36YXV6yZEmXx+uP9/r555/PLs+ZM6fTc7c46aSTsstvv/12t6rCBwJJyoQYhBQFgj6doE/HcSCWsiiri7GtXiHo0ygMmUT8BiHTQA0Vg+tAohG2L/MmpQqXghny+qpqJmhG5pZZFkIIIYQQQoguvPvuu/zgBz9g4cKFXVZktqiurt6tcy1ZsiS7PHnyZHJycrrcp6vL0Ldu3ZoNZgGOPfbYLo9ZXFzMgQceyKpVqwD4+OOPOw1RDzvssC6PuTd1J4xsXeHbnWrLadOmdblN6yB56tSpXW5fUFDQozH0ht58b1asWMEtt9zCCy+8kO3h25XufG30x3v97rvvZpf/+c9/8uabb3Z5zJYJysCbhG5fISGqEIOcqu6YRMy2XWJpm401MXRNIWzqFIRNIn6doD8PJZDn9U1t2AyZfibeQTRQdVAzYaoR9CpZDX/boFVtCVrlW4sQQgghhBD7s7///e9ce+213Q5PW+zupdlVVVXZ5ZEjR3Zrn676MLY+ZiAQoLi4uFvHHTNmTDZE7Sr46u4x95buzHTfuldrOp3ulWO2XAa/O9t3Zwy9obfem5deeokvfvGLJJPJHp2/O18b/fFeb9u2Lbv8xBNPdHm8ndXV1fV4n/4iSYcQ+xFNU4hoOhG/jmW7xFI266ujGKpKxO/1dY34AgQiO13O71jezU6DnYR0M9iWV8HaQtXaBqlmEPQA6L5WQavu3ev+VrN3CSGEEEIIIQaTFStW8LWvfS0boE6dOpWvfvWrHHPMMYwePZqcnJw2l4xfffXV2UlunNbFHD0QjUazyzvPCN6RcLjzNmatjxkKhbo9ltbbdhV8BQKBbh93b1D64Pe0nh6zL8bQG3pjXFVVVVx66aXZAHX06NFcf/31zJw5k3HjxpGXl4ff78+e6/bbb+cnP/kJ0L2vjf54r1tXle4Oy7L2eAx7i4SoQuyndE0hJ6ADOinLIZqwqIulMDSViM8gaKqYuoqhqxiqiqGZ6IYPXe3gm2xLyOpYYMUh2egtt/zlWQEU3QtafWGvZYAvB/y5XgArhBBCCCGEGBR+//vfZ4OR0047jWeeeabTvou9MTFQ60A0Fot1a5/m5uZuH7OrbTs6biQS6fZ+YvC77777sqHjQQcdxFtvvdVp64m9NWnWngiFQtnX9PHHH3PIIYf084j6joSoQghM3QtMAZJph6ZEmrqY6/3lWAEVBU1T0FUFU1MJmBp+Q8PQ1MxNwdA0dF3vuMDUdTMVrWmv/2q0ygtPzUygGsj3JrfSfZ2O1XVdLMfFdrx7y3awHC+o1VUFXVO9+8yyEEIIIYQQYu969dVXs8s//elPOw1QATZt2rTH5ywqKsoul5WVdWufrrZrfal9PB6nurq6zXk60nqype5sL/Yfrb82fvSjH3XZu7c3vjb6WmlpaTZEraio6OfR9C0JUYUQbfgMFZ/RNnx0HLAcB9t2SaS9qlU7E7BCJrxUVXRNIWB4AaupewGrrnnBq6GqqFqrnqoAdho32YxV+TmO42IbASx/IZYvn7QRIa0FsB2XlOWQSNskLYe07WK7LrbtYLsujoM3FtdFU1VUFbTMeDRVwa9rmLqSDX11LTNWVUHXFAxNzWyvDNjLRoQQQgghhNiXtO6R2NVkPA0NDSxdunSPz3nwwQdnl1euXElTU1OXVaCLFy/u9Pnhw4dTUlKSnVzqnXfe4dxzz+10n+rqaj7//PPs+qGHHtrFyHuX/E4zsPXka8O2bRYtWtTXQ9pjRx11VPYzv2jRIs4444x+HlHfkRB1EChaMZ+cSBhX8+FoJq7mw9VMHM2Hq/lbLbfc+1pta4Iil1KLzqkqmKra/ncMFyzbxXIdLNulLp3GdpK4uOCCmglXDUXFZ2gETBXHdUnbLmnLwbIVbDeE41go6WaUVBU4aWwtQNqXS8pXiGvm4PoiaKqGmgk8faaOpiqoioKWaTFgOy6O62JlglbLdqlPpbzQ1XG9MWWSX6+6FjRFQdNUNEXBZyj4dA2fruLTNS9c1XYExEYmmDU0CVyFEEIIIYToiKruKMqIxWL4fB1fbXb//ff3ysRAU6ZMyQae6XSaBQsW8JWvfKXD7R3H4bHHHuvyuLNnz85OljN//vwuQ9T58+dne1cOGzaMiRMn9uBV7LnWvWb31oRLovt2/trozFNPPbVPVHaeffbZPPTQQ4A3odyPfvSjNp/DwURC1EGgYNML5Ph2P9BxVAM3E75mQ9beDlYVZUeIq/pwdR+OanYQ7O4c+LYOgf1e6NvPAZaraNi+vH4fx4CggK4r6Ghg7Pq0be+47L6lTYCCVy2qqgoqXiWrqpuoPh+aWoCCi2In0NLNKKk6XMvASUewgsXYvlxsIwLqrt++NFVBQ8HoxsfXyQSrdqvWAE1xh3rHyoaxKF4XAlXxJuXSFC/A1RQVQ1cI+XTCPh2foeI3tEzVq7QQEEIIIYQQ+7dx48axbNkyAJ555hmuuuqqdrdbs2ZNdtKcPaWqKldddRW/+c1vAG9CnvPPP5+CgoJ2t//Tn/7UpmK0I1/72teyIeq//vUvXnrpJU477bR2t920aRM/+9nP2uy7t4svCgsLs8tbt27dq+cWXRs3bhwrVqwAvK+NjvqHVlVV8e1vf3tvDm23XXjhhUyYMIG1a9dSXl7Of/3Xf/G3v/2tW5/9aDSKoig9mritP0mIOgj8xTqTA8MKR5U6BJUkip1Ctb17xU5mlts+rjqp7P6qk/b6VKa73yhbQDpYSnTo0TQPOYp44VSZHKkDmub1U925RUDnFFw9gKV7M1Uqdgo13Yyv7nNcFFwjhBUowvbnYZu5uHrP/8qlKgqq1r3A1XV3BK0toWss6VAfS2crXA1dxad51bY5fp2gqXvBquFVtUq4KoQQQggh9hfnnHNONkS9+eabGTJkyC7B46uvvsrcuXNpamoiFAr1aOKmjnznO9/hb3/7G7W1tZSVlXHaaafx2GOPMWHChOw2ruty7733cvPNN+Pz+bKzpHdk9uzZnHHGGbzwwgsAXHTRRfz973/n4osvbrPdRx99xGWXXUZ9fT0AI0eO5MYbb9zj19RT06ZNyy7/5z//oaGhgdzc3L0+DtG+c845h3//+98A/OIXv2D8+PFceeWVbbb5+OOPufLKK9myZUuvfW30JU3TuPfeezn99NOxbZt58+ZRUVHBnXfeyeTJk9vdZ8mSJTz22GP89a9/ZeHChW0+twOZhKiDwH1cSKopSF5K4ZajAxw+tBv/rK7TKmRN7RSyJlFcu3cH6To7zuOkUK0kipNEsZKozs7jSO4UAu/0uNPLY9ut12NjxLaTv+5p8tc9jW2EaS49guahR9FccihuS89P0StczcTWTGwAx0a1mjGaNmE2bMA1gli+XGx/IY7ux9UDXsVyL4baipK5rL+TQ6Zth5TlEE/ZNMTSWI6LkglXTc2rVI34dUI+HZ/uhastfVqFEEIIIYQYTG666Sbuv/9+qqqqqK2t5fTTT+fQQw9lypQpKIrCxx9/zPLlywE47bTTKCkpyV4OvCdKS0v5y1/+wqWXXorjOHz44YdMmjSJmTNnMmHCBJqbm3n77bfZsmULAL///e/55je/CbS9zHpn8+bN47jjjmPdunVEo1EuueQSDjjgAI466ihM02TFihW8//773sS8eLOVP/bYY+Tl5e3xa+qpI488kpEjR7JlyxbKy8uZNGkSp556KkVFRdnKwCOOOIJLL710r49NwFVXXcWdd97J559/TjKZ5Etf+hI///nPOeigg/D7/SxbtowPP/wQgIMOOojTTjuNX//61/086q6dfPLJ3HvvvXz961/Htm1eeOEFXnzxRaZMmcKMGTPIyckhFotRXl7Op59+SlVVVX8PebdIiDoI/GZ2kD8sVVlf7/DDN2NcPsVk7jRftk9kuxQVV/fj6n6cvTfUQUOx4gQrPyFc/j6h7R+gpRrJKXudnLLXcVSdeNFBNA89iuiQI7EDMhtjr1I1HDMHx8wB10W14ujxKoxohXf5vWbiqj5sM+Rtpwe8cFXz42q+PmvBYGjeRFo7X4TQEq7GkjZ1sbTXJsDNhKu6hl9XyQ0YBExvQi6fLuGqEEIIIYTYt5WUlPD0009z7rnnUl1dDXjVdR9//HGb7c477zzmz5/Pt771rV4790UXXcRDDz3E1772NaLRKLZt88Ybb/DGG29kt/H5fPzxj3/kxBNPzD7W2SzppaWlLFq0iDlz5vDaa68BXiuCNWvW7LLthAkTePTRRzniiCN67TX1hKqq3HPPPVx44YWkUikqKip48MEH22xz1VVXSYjaT3w+H88++yxnnHEG69evB7yJ0FauXNlmu+OOO44nnniC++67rz+GuVuuu+46JkyYwNe+9jXWrFmD67osX748+weT9kydOrXDlhsDkYSog8DwsMofTwlx7ycJ/r02zaMrUnxWZfPDYwMUBSSI6QuuHqB52LE0DzsWXBt/zUrCFe8TKn8Ps7mcUOVHhCo/ouTTe0jkHUB06FE0DzmKVM4Y6aPamxQFxwjitFT+ui6Kk0KxU2iJGozmcu9hRQPNh6P5sX25OEaoz6pWd5YNV1v10nddrzVAslW4ajsOiqJgagqGrhEwVHL8BhG/QWmOTyayEkIIIYQQ+5RjjjmG5cuX8/vf/55nn302GxgNHTqUww47jCuvvJJzzjmnT849Z84cZs6cyR//+Eeee+45Nm/ejKIojBgxglNPPZXrr7+eSZMm8f7772f36apqtLS0lFdffZUXX3yRJ554grfffpuKigrS6TQlJSUccsghnHfeeVx55ZUYRjuTRexFZ599Nh9++CF33303b7/9Nps3byYajWYrZUX/OvDAA/nkk0+4++67efLJJ1m9ejWpVIohQ4Ywffp05syZwyWXXIKm7XstA2fPns3KlSt56qmneO6553jvvfeoqKigsbGRYDBIaWkpkyZN4thjj+WMM87g4IMP7u8h94jiylfRPquxsZHc3Fw+ePN5cnPCALyxOc3vFseJWZDnU/j+0QGO6M7l/aJ3uC5GtIxw+XuEKt7HX7sahR1fYulgKdEhR9I89OhMH1X5t9krHLttmwjH6deq1Y64rkvadkllqldTloOiwPQRuZTmDM7ZDYUQA1s6neb555/nzDPP7PdfCIUQQvS9RCLBhg0bGDt27KCdXbu1++67j69+9asAXH/99dx77739PKL9i+M4NDY2kpOT02k7BSE60xvft1rytYaGhk6r0iXBGWROHGUwIV/lp4virGt1ef9VXV3eL3qHopCOjKQuMpK6Ay9GS9QRqviAUMV7BCuXeH1U1z9L/vpnsY0QzaWH0zz0aGIlh+2ophS9T9Vw1SB26/e4p1Wrmh9HD/Rp1aqiKJi64k1ClalcrWtOsaYyStDUiPglwBBCCCGEEKK3PPHEE9nl/rr8Xgix75AQdRAaEdG465QQf/4kwbNr0zy2IsWyKpsfHhOgKCh/3dmbbH8+jWNOpXHMqShWgmDVEkLl7xGq+AA91UBO2ZvklL2Jq+jEiqfTPORomocehSV9VPueouBqPq/ilAjZ6cqyVatxjKaGTqtWUfr+8ooiTaMsYbK2MsrUYblewCqEEEIIIYTYI08++SSvvvoqAH6/n/PPP7+fRySEGOgkRB2kTE3hxsMDHFSi87+L43xWZXP9S83cIpf39xtX99M89Giahx7t9VGtXU2o/D3CFYsxo2WEKj8hVPkJLL2XRO54moceTXTIUaRyx0of1b2pB1Wr0Pf/Lq6iMMbMY1usiM36SMYPLZT+qEIIIYQQQnTgnXfeYd68edxwww3t9ltMJpPce++93HLLLdnHvvrVr5Kfn78XRymE2BdJmjbInTDKYEK+xk/fibG2zru8/7LJJldPl8v7+5WikSicQqJwCjXTvozRVEa44j1C5Yvx167E37AOf8M6Clc9QjpQQvPQo4gOOYp40TTpo9ofOqpa3RscCz3ZwLBENfWrN1KVOpCSoaPAF9mboxBCCCGEEGKfkEqluP/++7n//vsZOXIkBx98MKWlpbiuy9atW3n33XdpaGjIbj9lyhR+/vOf9+OIhRD7Cklj9gPDIyp/OHnH5f2Pr8xc3n9sgGK5vH9ASEdGUBe5iLoDLkJL1nt9VMvfJ1j1CUa8krz1z5K3/llsI0J02DE0DZ9FvGh6n/bnFAOEqmMHClH8DkZTPVXrlhBq3kyocCREhkIgH6QJuxBCCCGEELvYsmULW7Zs6fD50047jUcffZRQKLQXRyX6Sm1tLbfddtseH+db3/oWBxxwQC+MSAw2EqLuJ3a+vH9Ztc31LzZzy9F+jhwmk9UMJLYvj8bRp9A4+pRMH9VPCVW8T6hiMXqyntxN/yF303+wfHlEhx1LdPhM4oVTQZEgbVBTVII5BdREQ5RFLcaxAaN+C4SKIHeEd6/J17IQQgghhNi/zZo1i9dee43nn3+eDz74gPLycqqrq7OzwA8bNozjjz+eyy67jBNOOKG/hyt6UWNjI3ffffceH+eiiy6SEFW0S0LU/UzL5f0/eyfGmjqH/34rzmWTbbm8f4Dy+qgeRfPQo8C1CVQvI7J1IeFt76An68nb8Dx5G57H8hfQNOx4oiNmksifJD1UB7H8oI/qZhe/E2FUREeJ10J0O/hzIW8khErADHZ9ICGEEEIIIQYhVVWZPXs2s2fP7u+hCCEGGQlR90PDIyq/PznEX5ckeHqNd3n/Z1U2PzwmQElIqhkHLEUjXnwQ8eKDqJxxPcGqTwlvXUi4/F30RC35658hf/0zpAPFRIfPpGn4TJJ5EyRQHWRUFfICJuUNcYJmmOJICTg2JBqgfCmYYcgZBpFS8OfJv78QQgghhBBivzBmzBhc1+3vYYhBTELU/ZSpKXzjsAAzSnTuXBxnebXN119q5vtH+zlKLu8f+FSdWOlhxEoPo8q+gWDlx16gWvE+RryK/LVPkr/2SVKhoUSHH0/T8JmkcsZKoDZImLqKT9fYUhfHb2pEfDoEC7z+qKko1KyF+k0QLoGc4RAslP65QgghhBBCCCHEHpAQdT83a6TBhDyNn2Yu7//RW3EuzVzer8vl/fsEVzOyl/xX2kmC2z8isnUhoYrFmM3lFHz+fxR8/n+kwiNoGj6TphGzSEdG9vewxR4K+3VqoynKamOMLwljaqoXkvsi3s1KQFM5NG6DQEHmUv9i0H39PXQhhBBCCCGEEGKfIyGqYFjm8v77liR5ak2KJ1ameGZNCn3AXtmvoKugKXj3qrJjWfHWdQW07DYKmkqrx5RW22aezx6r7fMdHd+nwQH52oBrf+BqPpqHHUvzsGNRrAShisVEti4kuP1DzGgZhasfo3D1YyRzxtA0fCbR4TNJh4f197DFbsoLmtQ0J9haF2d0QQi19cdR90NkKDgWxOth68de39TcEV6Fqi/SX8MWQgghhBBCCCH2ORKiCsC7vP+Gw/zMKNG4c3Gc5nR/j6gzO/c46b+eJ8PCKoeUahxcqnNQiUa+f+CEqq7uJzpiFtERs1DTMULl73mBauUn+Bo34mvcSNHKh0jkTcgGqlawpL+HLXpAVSE3YFLRmCDk0ymJtFNlquoQKgLXgWQTbF8Oteu9gDVcCpoOiuZd7q+o3rKiZtalGl0IIYQQQgghhAAJUcVOZo40OHyoTnXM6e+hdMhxwXbBdsByXWynZRlsx83ce9tYjovlePtYjree3dcB23Uz990/nu1ANO2yvt5hW9S7PbfOS53H5KocXKpzcInGjBKdiDkwQijHCNI06iSaRp2EmooSLn+H8NaFBKs+xV+/Fn/9WoqXzyOeP5Ho8Fkk8sbjagauYoCqZ5Z3ulcz4ZvoV6au4tc1ttTFCBgaEX8H39YV1atE9edCKub1TK3bAIrupbFK5obadl3zPgOoRqvljkJXtdXyTo9LT1YhhBBCCCGEEPswCVHFLgK6wsgcCTy60pxy+azKYkmlzZLtFuvqHTY2OGxsSPHU56AAE/JVDinVObhUZ1qRRsDo/1DVMcM0jj6VxtGnoiUbCG17h8jWtwhULyNQt5pA3epuH8tVVFzVC1Tbu6edx21fHnXjvyh9WXtRS3/ULZn+qL6uenGYQe/muuDamXtnp5sNThqseDvPtTqWonj74+4IUZVMFWv2PhPMBou8Clh/rlS5CiGEEEIIIYTYp0iIKsRuCpkKRw83OHq4AUBD0mFppc0n271gdUujw5o6hzV1KRasSqEpMKlQ4+BSjUNKdCYXaZha/wZJti+XxrFn0Dj2DLRELeGtiwiXv4OeqEVxLBQnnb3HSaM6Vpv9FddBsZNgJ3t03pxN/6FhzBnUTJqD48vtzZe038oPmVRHE2yrjzG6INy2P2pHFMWrRO0tu4StmZvjgG1BzTqo3wzhIV5v1kA+3RuoEEIIIYQQQgjRvyREFaKX5PpUZo5UmTnSC1Wr4w6fbveqVJdUWlQ0uyyvtllebfPI8hSmBlMKvX6qh5RqHFigoav9F6ra/gIaxp9Dw/hzOt7IdcG12gasdhrFbXXvpNs+lg1hLRTXIlTxAeGK98nb8ByRLW9QO/FSGsadg6sZe+21DkaKAnkBk4rGJEFTpzTH3w+DaGkJ0IFAHqTj0LgVGrd5E1zljvB6tsrl/kIIIYQQQgghBjAJUYXoI0UBlS+MUfnCGC8cLI86fFppsWS7V61am3C9VgCVNvM/g4AO04t1r1K1VGdcnoo60C55VhRQDO/SfAK7dYjGMacTqFpK0bL78Tesp3j538nb8BzVU68hOuw4ucx7Dxi6SkDXKKuLEzB0cgID8Fu8EfBudgpiVdBUDsFCyBsFoWLQzf4eoRBCCCGEEEIIsYsB+Bu2EIPT0LDK0LDJ6ePAdV22NDksyVaq2jSlXBaXWywut4AkERNmlOgcXOJVqo7KUVEGScAYL57BlhN/R2Tz6xStfBAjtp2hH/ySeMEUqqZ/hWT+xP4e4j4r1NIftS7GBKMb/VH7i2ZCuBQcC+L1sPVjr1I1b5RXoWrsXkgvhBBCCCGEEEL0BQlRBwE13YyaVnEVBfAmc3EVJVPRp0pl3wCkKAqjcjRG5Wice4CJ47psqHdYkqlUXVpp0ZSCRWUWi8q8PqT5foUZxRpTizWmFumMz1PR+vHy/z2maDSNPpno8OPJX/NP8tc+SaB2BaPe/A6NI06gZspVWMGS/h7lPqmlP+rWuhhjCrvZH7W/qLp3Ob9jQ7IRyj8FXwRyR0Kk1FsWQgghhBBCCCH6mYSog0AyZaHYKVQyM2zjehO54KC4rafRdvHmjG9Z9mZX93oYKpng1Vt36YNwrlWo69JyLmXHuVsC3856KvaU6wIts4k7KJn77GzirouSufc2cjPvWavHXMd7N1wnc0zv3tV82P78XhmmqiiMz9cYn69x4USwHZfP6+xspeqyapu6hMubWyze3OJVqvp1mFSwI1SdUqgRMve9UNXV/dROvoKGMadRtPJhIptfJafsTcLb3qV+wnnUHnARrhHs72HuUxQF8gM+tjcmCPp0hvRHf9SeUjVvoil/nhemVq6E+o2QMxwiQ7zH5Q9CQgghhBBCCCH6iYSog0Bl7nTs3DzyAroX+LlegJpdbufeCxQdb7Ifx0ZxrR3LjgXYmRCxdymuC46NF6O2Cn3dzHJLqJnVstw6/G0nSFHIjLftc15YCzsC2pZq3Ux4S8v6jiDZVRVAA1XFUbRM2Kt54a+iZ8JmDaO5HKO5gnSw2Hu+F2mqwuRCncmFOpdP8ZGyXVbW2Cyr8iamWlltEU2T7akKKRRgbJ7K1CIvVJ1apFEaUvaZFgB2oIjth95E/bizKVr2N4LVn1Hw+QJyNv2HmslX0jjqFJl8qAd0XSFo6tn+qLkDsT9qexQF/LneLRWFmnVQvxnCQyB3OAQKGNiltUIIIYQQQgghBqN95Ldq0ZkDh+VRmTLYHncpDgcGbmjWEpS2BLiZdSUbpLZUzu4c+Lo7ts/s67YKPlFatzLwKlqzVbXZKtfW62qbMNVtdZwdx+iaFSzGX/c5ZnQ76WBxn84ub2oKB5XoHFTifck6rsumBofl1V6ourzKorzZZX29w/p6h2fXpgEoDCiZUFVjarHOhH2gBUAybwJbj/s5oYrFFC37G2bzNkqX/Im89c9SPe0rxEoO7e8h7jOCPp26aIotdc34jcjA7Y/aETPs3dJxaNzq3cIlkDsCgkWgyX9hQgghhBBCCCH2DvkNdBAoifgp9Uf4vKKJisYEJRH/wAzKMhWcoLVba7qvccwc4oXT8GlrMZrKsPx5e+2yc1VRGJunMTZP4+wJ3mM1cYcVrULVNXUONXGXt7ZYvNXSAkCDSYU7QtUB2wJAUWgeehTNpYeSu+EFClc9iq9xE8PfuY3m0sOonvoVUjmj+nuU+4S8kEl1U4IttTHGFoXR9rEcFfAmmTICYKcgVg1NFRAshLyRECoB3ezvEQohhBBCCCGEGOQkRB0kCkImU4fn8Pn2Jioa4pTk+DH2ybRk3+LqfhIFk3D0AGbDOlwnje3L7ZexFAZUZo5UmTnSq4hNWC6ra22WZ1oArNgXWwCoBg3jz6Vp5GwKVj9O3vrnCG3/iGDlJzSMPo3ayVdg+/L6e5QDmqJAfshHVTRJyKczNHcf6I/aEc2EcCk4FsTrYesnEMiDvFFehaoR6O8RCiGEEEIIIYQYpCREHUQifoOpw3L5XGtiW32cwpAPvyE9JPucqpPKHYerB/DVf44eq8QKFPf7JDh+fdcWAJsbnWyourzaYlu0/RYAU4o0phRqTCnSmJCvYWr9+1ocM0L19OtoGHsWRcvnEy5/h7yNLxApe4O6Ay+lfvy5uJpUI3ZE1xRChk5ZXYyAoZEX7LvWE3uFqkOoCBzbm4Sq/FPwRSB3pNc3VcJUIYQQQgghhBC9TEoVBxm/oTF5aA7jisLUNieJJq3+HtL+QVFIh4cRL5qBo4cwouVewDOAqIrCmFyNsyaYfP/oAA+cHeGJL4a57bgAF040mVSgoilQE3dZuMXiL0uSfOuVGOf9s4kbX27mz58keHNzmqqY02+vIR0eRvlRP2TL8b8kkTcBzYpTtGI+o1+5npJP7qJg1aPkbPoPwcpPMJq2oFiJfhvrQBPwaeAqbKmLkUj3379hr1I1COR7PVIVFSpXQNmH0LgNnEHyGoUQQgghhOihN954g//6r//i8MMPp7i4GNM0CQQClJSUcPjhhzNnzhx+97vf8eGHH+J2MKH07bffjqIobW7f/va3ezSO5557bpdjnHjiiXvtNeyO9l53d29jxoxp95jz58/fZdvzzz+/R+Navnx5t8/XkcrKSu677z7OP/98Jk+eTEFBAX6/n5EjR3LkkUfyve99jzfeeGOP30/HcRg9enSbsb7//vt7dMyBQipRByFDU5lQEsZnqKypjJK2HfKDUqW3N9j+AhLFM/DVfY7RvB0rWIir+fp7WB0q6KAFwMpqmxU13n190mVljc3Kmh2hcHFAYXKRV6k6uXDvV6smiqax5YT/JVL2JoUrHsCIV5K76T/tbmsbYaxAEelAMVawGCtQhBUozj5m+wv7dFKwgSQvaFAVTVJWtw/3R22PooA/x6tGjdfC1o+9itSCceDvn/YaQgghhBBC7G0rV67ky1/+Mu+9994uz6XTaRKJBFVVVXz00Uc89thjAEydOpVly5Z16/iPPfYYv/nNb9D17kVJDzzwQPcHn9HXr2GgeP7556mpqaGwsLBb2+/Oe9miubmZX/3qV9x5553EYrFdni8rK6OsrIwPPviA3/72txx55JHceeedHH/88bt1vtdff53Nmze3eeyBBx7gqKOO2q3jDSQSog5SqqowujCET9dYvb2RyqYExWHfwOl1OYg5RohE4VRMPYDZuAnbjOCY4f4eVrfs3ALAdV3Koy4raixWVHtB6vp6h6q4S1V2wiowVDggX8sGq1MKNYqCfZzQKSpNI2cTHXoM4fJ3MZor0ONV6PHqzK0KzYqjpaNo6Si+xo0dHsry5bUKVneErNl7f4FX9bivUyA/aFLZlCRoagzLG2SXvSuKN+GUnYLGrRCr9YLU3BGwnwTlQgghhBBi//TJJ59w0kknUV9fn32stLSUww8/nCFDhqAoCjU1NSxbtoy1a9dmqw1bb9+V7du389JLL3HWWWd1uW19fT3PPvvsgHsNPTFs2LAeVYx2NxAFSKVSPP7449xwww1dbus4Do888ki3j93atm3bOOOMM1i6dGn2MUVROPzwwxk3bhyRSISKigref/99qqqqAFi8eDEnnHACv/vd77jxxht7fM72At/HH3+c3/3ud/h8A7fIrDskRB3khuT6MXWVzyuaKG9MUBrxo6kSpPY1VzNJ5h+IowXwNaxFcVLY/oL+HlaPKYrCsIjCsIjJyWO8x+Jpl89rvUrVlmC1Iel66zU2/1ztbVccVLJ9VScXaUzI0zD6oFrV1f00jZzd7nNqutkLVmNeuGpkwlW91b3qpNGT9ejJeqhf0/45FBXLX9A2WPXl4+p+XNXA0Uxc1cDVfJl7E0c1cbW2j7mqiavq/dovV9cUwj6drfVxAqZOXsDo7/a9vU8zIWc4JBqh4jNoroSC8V7AOuherBBCCCGE2N+l02nmzJmTDROHDRvG3Xffzbnnnouq7lrcUlVVxdNPP81DDz3E+vXruzz+lClTWLFiBQAPPvhgt0LUBQsWkEgkdtm/v17D7jjggAP405/+1KvHnDBhAps2bSKdTvPggw92K0R95ZVX2LZtG9C997JFRUUFxxxzTLYqVFEUrr32Wn784x8zfPjwNtvats1zzz3HTTfdxIYNG3Ach29961vEYjF+8IMfdPv1RaNRnnzyyex6IBAgHo9TV1fHs88+y0UXXdTtYw1EEqLuBwpCJtNG5LK6opGKxjglET/GoLmOdwBTVNK5o3ENP77az9GbK7CCJV7vxn1YwFA4qFTnoNId1apbo062BcCKapuNDQ5VMZc3YxZvtq5WLdA4IF8loCv4NAWfDqam4NN23Pta1vUd62are0Ol2xXVjhEiZYRI5YxpfwPXRUs17hKsZsPWWDV6ogbFtTEyj8OqPXr/XJRMoGpk752WgLXN4yaOZhIrPYymESf2avgXMDWSlsO6qig+XcWna/gNFVNXMTQVXVUxNAVdUzBUdd/NHf05YIagucqrSs0fA3mjwQz298iEEEIIIYToNU899RSrVnm/pwQCAV5//XUOPPDADrcvLi7m2muv5dprr2XdunVdHn/69OkYhsGnn37KM888Q0NDA7m5nbfNaqlGNAyDyy+/nP/3//5fv76GgaKwsJCpU6fy9NNPs3jxYlavXs3EiRM73ad1ZefcuXO7FWq6rsvcuXOzAaqmaTz88MNcdtll7W6vaRrnnnsus2fP5rTTTuPdd98F4Ec/+hHHHnsss2bN6tbr+8c//kFzczPgBcbnnnsu//u//5t9HRKiin1C2KczdVguayujbK2LURDy4TcGweXJ+wArWIqj+fHXfY4ZLScVKgF18FxarCgKIyIaIyIap4z1Houlvd6qLZWqK6ttGlMuK6q9x/aEqtAmVG25NzUFUwWjzXIHj2lgqC33AUxtNIY2GjOgYIS945uq4u2nOISseoLpGoKJavzJKoxENVqyHtVOozgpFDuVuffWVbvtY6qT2vF+4aLYSbCTkO769eaUvUF469tUHvJNbF/eHr13reUFDRJpG8t2SabT1Da7OK6TCUwVdFVBV1U0VcGna/gMBb+hoasquqpg6N7zhqrSzh+GBw5Vg8gQSMegei1Eq6BwPESGMrAHLoQQQgghRPf85z875of44he/2Gn4uLPx48d3a7urrrqKm2++mUQiwYIFC7juuus63HbdunW88847AJx55pkUFRV1efy98RoGiquuuoqnn34a8Cp7f/azn3W4bVNTE0899RQABx10EAcddFC3zjFv3jxefvnl7Pqvf/3rDgPU1iKRCC+88ALTpk2jrKwM27a5+uqrWbNmDZrWdYbUOvC98sorOe+887Ih6osvvkhlZSUlJSXdeg0DkYSo+xG/oTFpSARTU9lY00zEZxD2y0dgb3B8ucSLpuOrW4MRLcMKFODqg6wfZStBQ+GQUp1DWlerNjmsqLHZ0uiQtCFluyRtSFpu23XbJbXTfdKClvkBHRcSljcJlqf3ZmLsmA8YlrmBrnoVsbqqZO7JhI6tnjNarSvgVy0CSpqAksrcp/Epafyk8Ssp/KQxSeNTUpikMd00+VYVh1Q/S7jiffyvrqLykBtpHtp7zbj9hgbt5fkuWI6L5ThYtktTIk19zMV2nWwVsKYqaKqCoagYhoJf17yQVfPCVV1TMDNVrQOi8N0IQm7Am3iqfEnmEn+ZeEoIIYQQQuz7tm7dml0ePXp0n5xjzpw5fP/738eyLB588MFOQ9QHH3wwuzx37lwqKyu7PP7eeA0DxVlnnUVhYSE1NTU8/PDD/PSnP+3wast//OMf2cmg5s6d263ju67Lb3/72+z6oYceyk033dTt8eXm5nLXXXdxwQUXALBhwwb++c9/cskll3S636ZNm3jzzTez61deeSXjx49n+vTpfPbZZ1iWxSOPPMK3v/3tbo9loBnUCVoqleKJJ57gscceY/ny5Wzfvp38/HzGjh3LBRdcwNVXX92tv4jsiY8//pgFCxbwyiuvsHXrVmprayksLGTIkCEcfPDBzJ49m1NOOYUhQ4b06Tha6JrKhJIwPkNlTWWUtO2QHzL3yrn3d67uJ1E4GccI4GtYh22ncHz7R4CjKAojcjRG5Oxe9bPruqQddg1XbUhZLgkb0o5LOhPGtmybdrxt07ZLysk8Z7NjuYPH0plztOyfsttGtZbj3do+2lWYqwBm5tZ9M/SjeCByL/nxTQx7/39oGH0aVdOv7dsQXvF6p+pa5yGr7bhYtkMs6dIUs7Bd13uZgKq0VLMqGJqK31AJ+nQCho7fUPHp/ZCs7jLxVA3kZyae0uX7oBBCCCGE2De17hm6YcOGPjlHaWkpp556Ks8//zyLFi1iw4YNjB07dpftXNfloYceAqCgoICzzz6bv//9710ef2+8hoHCNE0uvfRS7rnnHjZv3swbb7zB7Nntz/PREkhrmsYVV1zBJ5980uXx33rrLVauXJldv+mmm9rtK9uZ8847j3HjxmX7zd57771dhqgPPvhgdrKvY489Nlsh/KUvfYnvf//7gFepKiHqALRq1Souv/xylixZ0ubxiooKKioqePfdd/nNb37DvHnzOPPMM3v9/JWVldx8883tzqBWXl5OeXk5n3zyCfPmzeOGG27o9WbFnVFVhdGFIfyGxuqKJiobExRHfN3uMyn2gKqTyh2Pqwfw1X2OGqvCChTJZDddUJSWS/YhzN5/r1zXxXbZJVj1qjXBaqnctCHtgJ0Jfa1MIGu7ZNbdbABrOd6xdqzv2Kdlu21Rh6X1ozim/ic8OPRJjqh9ltxNLxGoXsr2w75DomDSXn8vgFYhq4LPaP8/Y9t2sV0vZE2kHaJJC6sxiaKAX9cImjo5AZ2AoREwtb0bqrZMPJVsgu3LIFrpXeIfkq9FIYQQQgix72l9Ofuzzz7LihUrmDJlSq+fZ+7cuTz//PO4rsuDDz7Ij3/84122WbhwYTYEvfTSSzHN7hUr7K3XMFDMnTuXe+65B/DCx/ZC1NaVnaeeeiqlpaXdOvbrr7+eXTZNkwsvvLDH41MUhcsvvzzbauDdd98lmUzi8/k63Kd1BfKXvvSl7PIVV1zBD37wAxzH4dNPP+XTTz/tdluCgWZQhqhlZWV84QtfyM5epigKs2bNYvz48VRVVfHKK68Qj8eprKzkvPPO48UXX+Skk07qtfNv3ryZE088sc1fTyZOnMj06dMpLCwkFouxbt06lixZki3L7g+lOX5MTWX19ibKGxKU5vjRVAkQ+pyikA4Px9H8+OpWYzSXkw6Wer0bxYCkKAq64l2az14McS3H5a4PE7ywHi7ZdhnfGXkI10fvxmwuZ8Rb36d24iXUTrwM1IH3rVzTFDQUzJ3CUceBlGXTlEhTG0tAZpugqZHrNwiYXrDq0/fChFa+iHeZf6watn4IuaOgYKxMPCWEEEIIIfYp5513HnfddRcA8XicWbNmccsttzBnzpxdZmHfE1/84hfJzc2loaGBhx56qN0QdedL+btrb72GgeKoo45i4sSJrF69mn/+85/cfffdBINtfw956KGHspWdPXkv33777ezyjBkzdjluT8bYIplM8uGHH3Lccce1u+2iRYtYu3Yt4AW3ratWhw0bxhe+8IVsj9YHHngg2yd1XzPwfvPuBXPmzMkGqKNHj+bpp59uk3JXV1dz2WWX8eqrr5JOp7n44otZt24deXl5e3zuhoYGZs+enQ1QZ8+eze9//3tmzJixy7apVIrXXnuNpqamPT7v7soPmUwbnsvnFU1UNMYpifgxBkQDw8HPDhSS0Gbgq1+D0VyBFSzC1Tr+q47Y/+iqwreP8DMionL/p0nu3DKRD0t/w+/yH6Bg2xsUrn6c0PaPqDjsO6QjI/p7uN2iquA3NfymBhi4LiQtm+aETX1zGhQwNZWAoZEbMAj4NAKGhl/X+iZUVTUIl0I6DrXrvEA1O/GU/GFDCCGEEEIMfLNnz+acc87h2WefBaCmpobvf//73HLLLRx44IEceeSRHH744Rx99NEceuih6PruRUF+v59LLrmE++67j3Xr1rFo0aI2oVoikeAf//gHAAceeCBHH330gHsNPbFmzRq+8Y1vdHv7L33pS22Cx67MnTuX//7v/6apqYl//etfXHHFFW2eb2mLkJuby3nnndft427cuDG7PG3atG7vt7Od9924cWOHIWrrCaXOOussCgoK2jz/pS99KRuiPvLII/z617/eK/+GvW3fG3EXnn/+eRYuXAh46fezzz7L9OnT22xTVFTE008/zYwZM1i/fj21tbX8+te/5uc///ken/+73/1utmfEpZdeyiOPPNLhDGamaXL66afv8Tn3VNinM2VYDmalSlldjMKQz5twRvQ5xwyTKJyCqfkxmzZj+3JwjFB/D0sMIIqicMlkH0PDKr96L86b231cmHs9f55+BBNW3YO/fg2j3vgW1dO+QsOYM/a5y9EVxZvgKvs9x4Wk5bUAaEjEcF0XU9fwGyq5foOQT/e21zV62Nanc0bA640ar4NtSyCy3QtTA3m9eBIhhBBCiMHHdV3iabu/hzGgBAxtr7fLe/TRR5k7dy7/+te/so+5rsvq1atZvXp1NpALhUKcffbZfO1rX+uwD2dn5s6dy3333Qd4VaetQ7WnnnqKhoaG7HYD9TV017Zt27j77ru7vf3hhx/eoxD1yiuv5Ec/+lG2PULrEPW9997j888/B+Diiy/G7/d3+7i1tbXZ5fz8/G7vt7Od92193NYSiQQLFizIrre+lL/FBRdcwNe//nWam5uprKzkxRdf5Oyzz97tsfWXQReitv6AX3XVVbsEqC1CoRB33HEHV155JQB/+ctfuOOOO/YoCV+yZAn3338/ACNHjuS+++7rMEAdaPyGxqQhEXy6yobqZkKmvsdBqrvTRDuaoqBLlesuXM1HsmAirh7ArF+LYqew/bv/jU4MTjNHGpSEVG57K8aGBofLPjuU3xx5F8duuItg1aeUfHoPoYr32X7It7D9BV0fcKBSwGeo+AyVCDq4kLIdkpZDWX0c1/UqVX2GSm7AIGjqBEyVgK7veaiqKBAsADsNTeUQr4WCcZA7UiaeEkIIIYToQDxtM+W2l/p7GAPKijtOI2ju3bglHA7z5JNP8vzzz/P73/+eV199FcdxdtmuubmZJ554gieeeIJzzz2X+fPn9yhoO/7447MTDi1YsIC77ror2yezpRpRUZR2g7SB8hoGilGjRnHiiSfy+uuv8+qrr1JeXs7QoUOBtpWdPQ2kW1/tHArtfpFWOBxus97Y2Njudq3D84KCAs4666xdtgmFQlxwwQXZIPyBBx7YJ0PUQZVoRaNRXn311ez6Nddc0+n2F154YfZDUVtby1tvvbVH5//zn/+cXb7hhhuIRCJ7dLy9TddUJpSEmTQkgu26NCZSnd6aEulOb9GE1eZWE0tR3hBnW+ZW2ZSgrjlFNGGRSNtY9q7fHAcqx+1qJvYeUlRSuWNIFE0DFPTm7eDuO++H2DsmFmj88ZQQ4/JU6hIuNywK8PjI26iafh2OahDa/hGjX/sGoW3v9PdQe48Cpq4S8esUhX0UR3wETQ3LdtlWn2BNZSMrtjWyvLyBDdXNVDQmqGlO0RC3iKVsUrZDj79cNQNyh4Pug+3LYetH3uRTvf11L4QQQgghRC8788wz+c9//kNFRQULFizgpptuYubMmbsEYgDPPPMMM2fO7HGLwZaAtL6+nmeeeQbwJvFuuVz7hBNOYNSoUQP6NXTHCSecgOu63b5dffXVPT5HS0Bq2zYPP/ww4LV+fOKJJwAYO3Ysxx9/fI+O2TqLam5u7vGYWkSj0TbrOTk57W7XOvC95JJLOpxMrHWw/uyzz1JXV7fbY+svg6oS9Z133iGZTAJeyn3EEUd0ur3f7+eYY47JfqG/9tpruz3BlG3bPPbYY9n13Zn9bCBQFIVRhSGKIr7dzgs6umohbbukbYeU5ZC2HZqTNrGURcpyiKVs0o6LbTvZA+iqgqGqGJqKrikYmtrhxFeu69W9uq4XcLa+d8nctzxGq+dcF8fddf8dL8YFFBRcXBSUzDaqomC7DgVBHwGz96qNrdAQHN2Pv/ZzjGgF6VAxqEavHV/s+0pCKr/7QoifvhPng3KLO95Jsu2g07nyhIMZ8vGd+BvWM2zxz2kYdTLV07+KYwy+SZIMXcXQVVp+hLIsl4RlU9mYxKHljw8Kuqqgq973D5+uETC8/UxNRVdVDM2rjtdVpf3vW9mJp2qg7CPIGwUFY8CUlhtCCCGEEC0ChsaKO07r72EMKIEB0B6vuLiYiy++mIsvvhgAy7J47733mDdvHg8++CCWZQGwfPly/vu//zs7qVN3zJ07l5/85CeAd0n/xRdfzCOPPIJt29nn+/s11NbWctttt3V6/KOPPjp7dXJ/ueiii7jhhhuIxWI89NBDfO9732sTMH7pS1/qcWuIgoKC7P4dXYLfHTuHnDv3OQUoLy/PZmrQ/qX8Lb7whS8wbNgwtm3bRjKZ5PHHH+frX//6bo+vPwyqEHXlypXZ5enTp3fr0vxDDz00+w/eev+eWrZsWba0OTc3l/Hjx2NZFg899BAPP/wwy5cvp66ujqKiImbMmMG5557Ll7/85WzZ+0CzNy89sB0vXE1mwtUdIatXSZbsIGRtCTa9ZS/YBFBUr8RaUbxgRFUUFEVBBdRMWKKrXiCrKgqaCprqBSla5qZm9lUUBTV7DO9eVbwwtTqaZFNtjGjSojBsZs+/pxxfHvHi6fjq1mA0b8XyF+Lq3e9/Iga/oKHwPzMD3PtJgqfXpLn/0yRlTSV8a+ZvKV39KPlr/knu5lcIVn9GxWE3kyic2t9D7lO6rhDe6fu964Jtu1iug2W7JNNpapu9vxCjuCioaCrZkNXrs6pi6t4fboxMuKrrKka4BKwE1K2H5iqvV2rOMJl4SgghhBAC73emvX3puug5Xdc5/vjjOf744/nKV77Caaedlq00vO+++/jVr35FIBDo1rHGjRvH8ccfz9tvv82LL75IVVUVDz74IADBYJCLLrqo319DY2Njl/1Mo9Fov4eo4XCYCy64gIcffpjPPvuMTz75JPtewu4F0mPGjGHdunWAl1Xtrp33HTNmzC7bPPzww9nwfNy4cRx77LEdHk9VVebMmcNvf/tbwKtglRC1H61evTq7PHr06G7t07rEfNWqVbt97g8++CC7PHLkSMrKyrjoootYvHhxm+22bdvGtm3bePHFF/nlL3/JP/7xjy4rZgc7L7jUOuzBajsuKcshZXvhatp2UPDCTaVNuNk29NwRhO5Yb9mmN+QFDfKCJhuqo5Q3xHu1KtXVAyQKp+DofnwNG7DNEI7Zfum82D9pqsI3DgswIqJx7ycJXlyfpiLqcNvxV9FcejhDPv4dRmw7Ixb+gLoDLqRm8hX7VVWzonjhqo4G7bzsbMjqeCFrfTqN7bjZXs4qmT+qaF5Fa8DQ8OsF+KJNGA0foOUORy0YixbKR9O0TDXrvjWplxBCCCGE2D8de+yx/PCHP+SHP/wh4E0M9MEHHzBr1qxuH2Pu3Lm8/fbbWJbF97//fZYuXQrA+eefv1daG/bGaxgo5s6dm72U/8477+SFF14A4LjjjmP8+PE9Pt5xxx2XbXX52WefEYvFCAZ7foXi+++/n132+Xwcfvjhu2zT+lL+9evX9+h3ovfff5/Vq1czceLEHo+tvwyqELWmpia7XFpa2q19hgwZkl3ekzLnLVu2tFk/44wzWL58OQCTJk3iiCOOQNM0li5dyscffwzA5s2bOfHEE3nrrbc47LDDujxHMpnMtiuAHU190+k06XR6t8e+L9AV0HVAV+leK183c9ux6AC93WU0z68ypTREWZ3KlroYTTGFgl6sSk1ExmIpfnwN61DS1Vj+gn1u9nXRt86ZYFASVPjle3GWVNrc+HIzd8ycTPyEuyhZ9lfytrxKwZp/EKz8mG2HfodUZPd7Ew02iorXMqSd5xwHbMfBcVxSaYdY0sZyHEBDcf34q9eibtiAbYaxgqW4vjyUQART19E1BTNTzZqtblcVb3I9VUFVQVdU1EwVfEdtSoQYCFp+vhjsP2cIIYTwpNNpr+WZ47Q7oY8YPE499dRsAAmwdevWNv/mbqs2dy2fidYuuugibrzxRhKJBPPnz88+fuWVV+6ybUfrLedo7/h7+hpGjRqVrZDszM7ndXfqa9gbXwddvR+zZ89m+PDhbN26lUceeST7eE/ey9ZOOOGE7HIqlWLBggU9rmh1XbdNy8pjjz0WwzDanO+jjz7K5l67a/78+fzsZz/bo2M4joPruqTT6d2e3L27P+sOqhC1ddPb7paht95u56a5PVFfX59dbil5DgaDzJ8/P9u/o8Xrr7/OJZdcQnV1NbFYjEsvvZQVK1Z02Hy3xS9+8Yts35Gdj7c7f1UQfWP3P0WdUTK3+j45uti35QHfnAJ/XaVR1uTwzf9EuXaizbiiqxiqT+GgzfPwN6xn9Bs3sWLYpawvPtlLEMUeyHRkbbahbhuwrV9HI0Rfa93rSgghxOCl6zpDhgwhGo2SSqX6eziiD7X0E23hOE6b2ddbF3Cl0+ldZmZXFIUzzjiDf/3rX9nHhg4dypFHHrnLtolEos15d35+dyeF6uo17I7Wr7u9se6O1q/ftu12j3nhhRe26enq9/s544wzdtk2Fotllzt6vYcccggHHHAAa9asAeD3v/895557Lqra/d8B//3vf7N+/frs+pe+9KVdznX//fdnl/Pz87tdNdvQ0JAd24MPPsj3vve9Ho1tZ6lUing8zltvvbXLZ6K7Wr+vnRlUIWrrD2ZXgWSL1j1J4/H4bp+7vRnPHn74Yc4///xdHp89ezbPPPMMxx9/PI7jsG7dOh555BGuueaaTs9x6623cvPNN2fXGxsbGTlyJLNnz6awsHC3xy56T8qy2VIbZ0tdDJXerUpVU81osXL0VBNKOo7iWCiO99cSV1FxNQNX8+FoJqiD6ktbdMNE4KDRDre/HWdNncM9K3VuPsLPxOmnsvmAwxm65A+EKz9m+taHGZdaRvnBN2EF5PtGb1HsFGq6Gc2K46g+bF8OVqAYx5eLY4SyFeS24+K4bvbeccB2XVzHxXZdHMfFzkyGl2n5jJaZJEvLTLAXMDWCho7P8KpdTV3J9HD1JsuStgKiN6XTaV5++WVOOeUUDGP/aQkihBD7q0QiwZYtWwiHw/j9Mi/DYNbSM7PFxIkT28y+3jorMQyj3ZnZr7nmmjYh6hVXXEFeXt4u27X+LOm6nj2W67o0NTURiUR262fYrl7D7mj9uluPdU+0fv2aprV7zGuvvbZNiHr22WczcuTIXbZrXUCnqmqH4/vud7/L1772NQA+/fRT5s2bx7e//e1ujbehoYFbb701uz5u3DiuvPLKNlWe6XSaJ598Mrv+3//9390+fmVlJSNGjMC2bbZt28aHH37IySef3K1925NIJAgEAsyaNWu3v291NywfVElL6zeru381a/1Xhu5Wr3Z1boBjjjmm3QC19fMXXHAB//jHPwB44oknugxRfT5fuxNRGYYhv9gMEIZhMHGYj6LcIOuromyPpnqvV2ogFzuQiw3gpFGtBKqVQLETXniTbESxEyjJZhTXu2zBVTUvWFW9gFUmwhncSkIad34hxK/ejbNoq8Wv3k9Q3uxy5dQCyo/5Cbkbnqdo+d8JVS1h7BvfoHbiZcRKDvEu8Zfgbc+oPjB82IBiJzFSTfjqqnB1H7YvHytQjO3LQ20VqHaX7ezo3Zq2HeriDlXRJE6r/q2GpqBrCrqmEjQ1gqaGT9fwtUyUpauZFgMSsordIz9rCCHE/sG2bW+eCVXdo8owsXf97//+LzNmzOh2EBWLxfjlL3+ZXS8tLeXQQw9t82/e+mfGls/Ezs4888w288NMmDCh3e12fqxlveXScEVR+P3vf9/rr2F37Pyzcm98HXT0+lubPn06H3/8cbYFwciRI3v0Xu7s2muv5YknnuC1114D4JZbbmHEiBFceumlnY41Go1y9tlnU1ZWBnih77x583b5OfCFF16guro6O4Y5c+Z0+70aMmQIp5xyCi+++CIADz30EKeeemq39m2PqqooirJHP692d79BFaKGw+HscnerSltv13r/PTk30GmA2nqblhD1nXfe2e1zi4FFURSKwj4ifp3NNTE218WIJi0Ke7EqFdXAMQ0cs23DbsVOolgJVDuJYifQUk2oqSianYRUU6tw1cDRTFzNh6sZoEi4OlgEdIXbjg/wt0+TLFiV4sFlSbY2Odx8pJ+GcWcRKz6IIR/dib9+DcXLvMsvLF8e8aLpxIumEyuaQTo8XELVPeBqPuxAJlC1EqjJOvzN23F1H5YvHztYgt1SodoNLZPv+Tr4H9tx3WzAatkutdEU222v0lVRXBRUdA30TJ/WgOGFrH5Dw9R3PNZbE+MJIYQQQoi9a/HixXznO9/h8MMP55prruHCCy/scJ6Y999/n2984xt89tln2cduueWW3QoLNU1rd7Kh3dFfr2EgOeSQQ3rtWKqq8vDDD3PkkUdSVlaGbdtcfvnlvPbaa9x2220MHz68zfa2bfP8889z0003tbmM/3/+53/anayr9YRSJ510EkOHDu3R+K644opsiPrkk09yzz337JUJyfbUoApRW1/Svn379m7tU1FRkV0uKCjolXMDTJkypct9Jk+enF1uamrKlrGLwcGnaxxQGiE/ZLKhupnyhjj5QZOg2Xdfdl4o6stOoJUGcF0vXLVbKleTmXC1Ec2KQTKF4jqAgqtlwlXVIHst8c46DNfae3zXx1wFUHQJ6fqQqihcd7Cf4RGVP3yY4NVNabY3O9w+M0BuZARbZv2G3A3PE65YjL92JXqynsjWhUS2LgTA8hcQK5pOvGgG8eIZpIND5N9rN7m6H1v3ZwNVPVmLESvH1QNYvnysYAm2mYtr7H5fa1VRMHUFU2//h8aWkNVyHNK2S10qRWWTm2ma7/UNCJoa44rDDM31S6WqEEIIIcQ+6sMPP+TDDz/khhtuYPz48UydOpWioiJ0XaeqqoolS5awYcOGNvucf/75fPOb3+ynEe9qIL2GNWvW8I1vfKNH+9x66627BJT9ZejQobz77rucfvrpLF++HNd1+etf/8p9993HEUccwfjx4wmFQmzfvp3333+fysrK7L6KovC73/2Ob33rW7sct7q6mueeey67fsUVV/R4bOeddx7BYJBYLEYsFuMf//hHl1dnDwSDKkSdOHFidnnTpk3d2mfz5s3Z5UmTJu32uXfetztVrTsHphKiDk4tValbamJsqovRnLR7tyq1K4qCq/txdT9OphuEF646KHYS1WoJWOOoqcZMX8cE0HZWQnaapbBz7Wzr7lhQ7RSWPx9nD4Ij0bUzx5sMCancsSjGsmqbG19u5qezgozM0WkYfy4N489FsdP46lYTrP6MQPVS/LWr0BO15JS9SU7ZmwCkA8XEi6YRL5pBrGgGVqj9vwiLzrm6H0v3Wr8oVhw9XoUR3YZrBLH8BZlL/nNx9d1vLdOebMhK+yGr67o0xNMs39ZIc9JiTFEIQ9u3/4ovhBBCCLE/+cIXvsDixYvbhIvr1q3bpWdoa4FAgFtvvZVbb70VXe//aGggvoZt27Zx991392ifa6+9dsCEqAAjRozg3Xff5Ze//CW/+93viMfjuK7L4sWLWbx4cbv7HHHEEdx5553MnDmz3ecfe+yx7Gz2gUCACy+8sMfjCofDnHfeeTz66KOAV9kqIepe1rqy87PPPsOyrC6/kD7++ON29++padOmtVmPRrueo33nGehyc3N3+/xiYPPpGhNKI+TtxarULikqrh7A3jmwcezshFXth6Hth6lKd7d1bfTYdszoVrRkA1agEFfr3kRwoucOHaLzh5ND/OitGNuiLje+3MyPjw9ycKn32XM1g0TRNBJF04DLUewU/tpVBKqXEqxeir/2c4x4FcaW18nZ8joA6WBpm0pVK1DUj69w3+TqASw94FWKW3H02HaMpq2tAtUibF8ert73EzooikJe0CSRtllXFaU5aTGhNEK4o/4BQgghhBBiQLnuuuu47rrrWLZsGW+++Sbvvfceq1atYtOmTTQ0NOC6LpFIhCFDhjBjxgxmz57NxRdfTH5+fn8PPWswvIaBKhKJ8LOf/Ywbb7yRp556ihdeeIGVK1dSWVlJLBajqKiIYcOGMWvWLM4++2xOPPHETq9Oa30p/znnnLPbxYBXXHFFNkR966232LBhA2PHjt2tY+0tiuv2qLxsQItGoxQVFWUni3r33Xc5+uijO9w+mUxSXFycDTNfffVVTjrppN0+/7hx47J/Nfn1r3/N9773vU63f/TRR7NlzwUFBdTU1PTofI2NjeTm5lJdXb1LOwExcCUtO1uViutVqu61qtQBRE3WYzaVoTdvA0XF8hfKxFd9qC7hcPvCOCtqbDQFbjrCz+njug6vFSuBv3YVweqlXqVq3Zpsb90WqdBQL1Atmk6seAa2f/dbo+zXXDdTEd6E4jo4eoB0eDjp8PC9EqaCN4nV9sYEEb/OhNIwJRGZlXd/l06nef755znzzDNlYikhhNgPJBKJbJCxu7NcC9FdjuPQ2NhITk7OPt/PVPSf3vi+1ZKvNTQ0kJOT0+F2g+pTGg6H+cIXvpBdnz9/fqfbP/nkk9kAtaCgoN1muT1xwQUXZJefeuqpLrdvvc2enlvsO1qqUg8akUdOwKC8IU4sZfX3sPY6x5dHonAqieJDsH35mLHtaIm6HrYNEN2V71f5zUlBThylY7tw5+IEv34vzoflFmm74/fc1f3ESw6mZspcymb9lnVnPc7WY35C7QEXksg7ABcVs7mc3E0vMeSj3zLuxbmMfuV6ipfcTXjrQrRk/d57kfs6RcExglihUtKhIbiqjq/uc4LbP8aIbgPH7voYe0hTFYbm+klZDp9tbWBjdRTbka9JIYQQQgghhBhUlagAzz33HGeffTYAPp+Pjz76iKlTp+6yXSwW46CDDmLt2rUA/OAHP+AXv/jFHp173bp1TJ48Odsb4umnn+bcc89td9vFixdz7LHHYtveL8VPPfUUX/ziF3t0PqlE3fclLZsttTE21e7fVak4FkZsO2bDJtRUgzdzudl1X2HRc47r8uCyJI8sT2UfCxlw1DCd40YYHDFEJ2B0/zOoppvx16zwKlWrluJrWL9La4dkZBTxoumkckaTCo8gFRmB7cuXyaq6w3XRkvWo6ThWqJRUZJRX6bsX3rvmpEV9PM2I/AATSsL4DakU3x9JJaoQQuxfpBJV7E1SiSp6w96sRB10ISp4VZ0LF3qzTI8ZM4ann36aGTNmZJ+vqanh8ssv5+WXXwa8KtR169aRl5e3y7E2btzYpifDvHnzuPrqqzs890033cQf/vAHAEKhEA8++GCbClWAN998k4svvpiqqioAjj76aN55550ez4gsIergUR1NsqG6mZpoivyg0b+9UvuRYiUwmrdhNm1BsRJY/vy9dhnz/mZppcVrm9K8s9WiLrHjvwFDhcOG6Bw7XOeY4Tp5/p79MKOmogRqlhGo8nqq+ho3trudrQdIh0dkQtXh2eV0eJj0yG2PY6HHawDFu8Q/ZxSOEerz06Zth8rGBAVhkwNKIuSH5N9mfyMhqhBC7F8kRBV7k4SoojfszRB1UCY1jz76KEceeSTl5eVs3LiRgw8+mBNOOIHx48dTVVXFK6+8QiwWA0DXdRYsWNBugLo7fvWrX/Hxxx+zcOFCmpubufDCC5k8eTJHHHEEmqaxdOlSPvroo+z2Q4cOZcGCBT0OUMXgUhT2EfHr2arUaNLaL6tSXd1PKnccVqAYo6kMo3kbJBuwAgWgyi/vvWlGic6MEp0bD3dZWWPzTpnF22UW26IO722zeG+bhfohTC3SOG6EzrHDDYaGu/7BxjHDNA89muahXj9qNdlAsHoZ/rpVmE1lGNEyjObtaFYcrX4N/vo1bfZ3UbCCJV64Gh5OOjJCqlcBVB0rVIpiJTCbNqHHq0hFRmOFh/Zp6GxoKkPzAlQ1JVlaVs+E0gjDcv3yf5YQQgghhBBivzMoK1EBVq1axeWXX86SJUs63Ka4uJh58+Zx1llndbhNTytRARoaGvj617/OY4891ul2Rx11FP/3f//HyJEjO92uI1KJOjjVRJOsl6rUzGXMdRiNmzFi23E0A9ufD4pcUtxXXNdlU6PDojKLRWVp1tQ5bZ4fl6dy/AiDY4frjMtTdztIU+w0RnM5RrQMM1qG2bQ1u6ylmzvcT6pXd1BTjWipJmxfIamcUVjBElD69q/3DfE0sZTF6MIQY4tCmLpUC+wPpBJVCCH2L1KJKvYmqUQVvUEqUXvBpEmTeP/993n88cd57LHHWL58Odu3bycvL49x48ZxwQUXcM0111BUVNTr587NzeXRRx/l+uuv58EHH+Ttt99m69at2LZNaWkpRx99NJdccgnnnXeeVPOIXRSGfYR3qkotDPnQ1P3ss6Io2P4CbDMXKz4Es3EzRvN2bCOEY+bsvxWJfUhRFMbkaozJ1bhiqo/KZodFW9O8U2axtMpmfb3D+vokDy5LMiSkcNwIg+OG60wp0nr0+XQ1g1TOKFI5o2gTmbouWqoBoykTrka39qh6NZF/IA1jTideNGPQfz4cMwfHCKEl6ghUfUo6NJRUzigcX16fnTM3YODTVTZUNxNLWUwoCRPxS6gmhBBCCCGE2D8M2krU/YFUog5+UpW6g2Kn0JvLMRs3o6WjWP58HCPY38PabzQmvcv8F5VZfFhhkWo1UXyeT+Ho4TrHDdc5dIiOqfV+gNmT6tVkZBQN486mceRsXD3Q62MZaBQ7jZ6owVWNTAuEkX36um3HpbIpQdCnc2BJmJIcqVIZzKQSVQgh9i9SiSr2JqlEFb1BKlGFEEDbqtTNtTEaExampqIqoCoKqqpklzVV8R5TGJQVzq5mks4Z7fVLzVQpaskGrEDhfncpd3/I8amcOtbk1LEmccvlowqLd8os3tuWpj7p8uL6NC+uT+PX4YihOscPNzhymE7Y7J3PYlfVq2bTFsJb3yZn86v4mjZT8uk9FC5/gMbRJ9Mw9izS4WG9Mo6ByNUM0qEhqOkY/vp1GLEqUjmjSYeGgNr7/81rqsLQ3AC1zSmWbm1gXNJiVEEQXZMffIUQQgghhBCDl4SoQgxwPl1jQkmE/KDJ9sYEKcsl7ThYlovtuqRtF8fN3BxwWhWXu2SW3R2Bq5YNX5XMciaQzQSwLc8NVK4RJJV/IFawBLOpDL15Gygqti8fV9UH/WXcA0FAVzh+hMHxIwwsx89nVTaLyrzL/qviLgu3WCzcYqGrcFCJxnHDDY4erlMUUHo/4FcUbF8ecV8e8aLp1EyZS87mV8hd/2/M5nLy1z1N/rqnaS49jPpx5xArObTPe4f2F8cIktIDaKkGAjXL0GPbSeWMxvYX9snXRUHIJJayWFPZRDRpcUBJhIApPYuFEEIIIYQQg5OEqELsIwrDPgrDvuy667rYjhek2o53cxyy607rx12XlOWQth3StkvadrAyz1m2i9OyvQtu5hiaqhD26QRNbUCGqo4vj4SZix4sxWjajJasR3EswAVXARVcRcNV9Uy4quOqWmZZgp7eoqsKh5TqHFKqc8OhLp/XObxTlmZRmcWmRoePKmw+qrC56yMwVO/S/zx/5uZTM/dK9j7f7z2W61N2qy2AY4SoH/9F6sedQ7DyY/LWP0to+0fZWyo0jIZxZ9E46mQcI9QH70g/y4TKthFBT9QQqKwlHR5GOjIKx4z0+umCpo6hqWyrjxNL2RxYGqEgJJXhQgghhBBCiMFHQlQh9lGKoqBryh59EbcOWW3HxXK8QDVlO9Q0J6mNpqhoSKGpKiFTJ+gbYIGqomAFi7H8+ahWDMWxUJw0ip1GcdLeY1YSxU6g2ClUywbHQnEdwAUUXEUBVc8ErkaroFWqWntKURQmFmhMLNC4ZgaUNdos2upd9r+yxibtQFXcpSreUi1td3q8kAF5fnWnkFVp97GwuVMFtaISKz2cWOnhGNFt5G54jpxNL2M2b6P4s/soXPEQjaNOomHs2aRyRvXdm9JfVA0rWIJiJTAbt2DEq0lFRpMOD8XVfF3v3wOGpjIsN0BVNMnSLfWMLwkzPC+Aur9NhieEEEIIIYQY1CREFWI/pqlKh7Oql+b4SaRtGhNpaqMpqptTbG9MoCh4gaqp92hG9j6l6jhmx82fcV0vXHXS4KR3hK1OGsVKolpxVCuRCV4T4Njetq0PoWrZytYdoasGqKCQuR8g78cAMSJH49IcjUsn+0jZLvUJl/qkS33CoT7pUpfY9bGWdcuB5jQ0px22NnV9LlXxqlxzfEr2Pjd7KyI352oKD7mMSfVvMnbbcwSbt5C34XnyNjxPrPgg6sedQ/OQIwZdlbKr+0lHhqGmovhqV6E3l5PKHYsVKAa1916roiiURPw0xtOsLG8kmkwzrjiMTx9c76cQQgghhBBi/yUhqhCiQ35Dw29olET8JC2bxrhFbXOS6miKyqYE4AWqId8AClTboyi4mtn1BFSZ8FTJBq2pHYGrFUexEqh2AsW2UN0EuJn+BzgorXrR0tKLlrbviaso3mOZe1dRMv05vXvveS+MdVseUzVQ9/0ZsU1NoSSkUBIC6DxYc12XaBovWM2GrG4meN35MYemFDgu1CZcahNup8eGWcBMjlFX8BX9JWarHxGs+pRg1adUq8W8l3MaqwpPxgzmeAGsXyHXVMj1q4QMBlYldg84ZhjHCKIl6wlUfUo6WEo6ZzS2P79Xz5MTMPAZKptqYsRSNhNKIuQG9v3PrxBCCCGEEEJIiCqE6BafrlEc0SiO+BhrOTQm0tQ1p6hqSlIVTeC4XqAaHuiBamdUr7rUxd/xNq4LruW1DMgEqLiZENV1Wj3mesvZkNUBx/H2dW0Ux/aec2xU1wLX3nEcx0bFBVywkqDpWP6CQTsh0s4URSFiQsTUGNlJgXGLtO3SkPJC1cakF7B6906b9YbsDd51pvJuaiojlCqu1F7hUu11ipwqzq5/mJPrnuAp+zgesE9jpTs6ex5VgRxzRxuBo4frnDneJKDvI593RcX2F2A7afR4JXqilnR4BKnICFwj2Gun8ekaQ3ICVEUTLC2r54CSCKU5vt6fVEwIIYQQQggh9iIJUYUQPWbqKkVhH0VhH2OKQjTG09TFUlQ1pqiKJnEcl5BPJ2Rq6NogC/4UBRTD65/a28duU9nqBbFaqhGzYT1mtJx0oBBX7yTg3U8ZmkJRQKEo0L3tHdelOQ0NSYeGZJCG5Jd5NDaHkTULOazmeYanN3KZ/gaX6W/wCZN4yD6VZ9KHY7m6VwGb9P7ll1TaPLYixYUTTc49wCRk7CMhoWpghYagWHF8DevQ45WkIiNxdT+uamYmYzO8yu3dDO41VWFIToC65hTLtjZQ2+wn7DMwdAVDUzF1FVNTMTR13/2jixBCCCGEEGK/IiGqEGKPGJpKYdhHYdjH6EKHxnia+liaqqYkNc0pHNclYGiEffrgC1R7m6JkenJq2YDW0v3YZg5m42aMpo24aR17P6pK7Qtqq0rXEdkJ6w044Exi7hlsqV1B3vp/E962iEPcVRyireJXoULKR5zO2uJTqXJz2dzo8OTqJOXNLn9fmmTByiTnHWhy/oE+cnz7Rijo6gFS4WFoqUb8NSt3tJHI9v3VcXUTRw/g6MFMsGq0DVpVo9Peqvkhk3jKprw+geXEsx0uNFXB0BQM1QtUQz6doKlhZILVHSGrIt83hBBCCCGEEAOChKhCiF7TNlAN0piwaIil2J4JVG3XIWDoGKqKi+sVXmb2dd0d626mv6i3TNttW62j7Og66vZ6WWjXdFUh5NMJmFqf9sp0dT/J/AOw/XmY9eukKrUvKQqJwqlUFE5Fi1eTu/FFcje+iJGoYdTaRxix/gmiw2ZSP/5szplwIK9tSvPYyhRbGh0eXp7in6tTnHuAyYUTTfL9+0D4pyjYvlxsX6637jpeqwkn7bWdSDejJ+tRXBscsl9wLeGpqxiZoNWPowUzvYeNbMDqqgYB3SCQ0/azatkOluOSth1iSZuGeBrLyXwRuy6apmKoXoBq6iohUyNgaJiGhqllAlZdwdRUCVmFEEIIIYQQe4WEqEKIPqFrKgUhk4KQyahC75L/hniK7Y1JLMdFAVRV8YovAVVVUfAq1FTFe1xVyCwr2WW1ZVlVUPC2A9jb7RZdF+rjKepjaRob0wAEzR3VdL1OUbCCJZmq1I0YTVtw082ZqtR9o/JxX2MHiqidfCV1B15KeNvb5K1/Fn/d5+SUvU5O2eskc0ZzyfCZnHb8TF6vL+HRFUnW1zs8sTLFU5+nOHO8ySWTTIqC+1DIp6i4mgpaJ+0qXBfFsbz+vo6VCVobUFwrE7R6f+FwsxWtBo7uwzYjuHoQR/ejaj503Y/faH/SKTsTsFq2Szxl0xhPYzsuLt6xNUVBz1Sp+nSVgKESNHWvgjVTxaqqrb5fZL+n7HhMerQKIYQQQgghekJCVCFEn9NUhfyQSX7IZFRBKBODZK5e34eDjJEESaRtmhIWDfEU1dEUtc0pLMfFn7lE2W90PhN9T3lVqROx/fmZqtRtUpXax1zNoGnkbJpGzsZXt9q71H/rQnyNm/A1bqJo5cMMzx3PF8fN5C39GO5bm8uqWod/fZ7i32tTnDrW4NLJPoaG96EwtTOKgqsZQOdBazZkdSzUdBNaogbVcXAVJdtz1dX92EYOjhHE1Xw4uh9X86FpJpqqQfsZ646Q1XFJpGya4haWk8iOR8v8dWbnAFVRFFS87zua6n1v0lU1s6yiqwpa5qYqSiaIbT+EVVWvEtanq/v09zEhhBBCCCFE90iIKoTYq9RBNomM39DwGxrFER9ji1yaEmmaEhaVTQmaEha1zUl0VSWY6fnYK5f9KwpWsNSrSm3YiBHdgmuZ2L58qUrtY8n8iWw/bCJV079GuPwdwlsXEqz6FH/DOvwN67iQ+ZyZP5GVE4/jD9VH8GZNLs+tS/PC+jRfGG1w+RSTkTm9G6wPSJ1NwJapZFXsJEq6GSNRi+K4oLCjDYARwDYiOEYoE676cDW/N9kVZILOjt9Hx3VxHK9u1cm0Cml9bzsult2ybmW3c9xMaxFvoLT0L8i2Dcksq5mQ1tAUAoZGbsAg7DcIGF7bAb8hwaoQQgghhBCDjYSoQgjRSzRVIS9okhc0GZEfIJayaUykqY2mqIul2N6YxgWChkbIp+/xZf+uHiBZMMmrSm1YjxEtxwoW4mq+3nlBokOOGaZx9Kk0jj4VLdlAaNs7RLa+RaB6GYG61Rxat5r5zKO6ZDJPpY/mL3VH8PLGXF7ZmOaEUTpzpvgYm7cfhKntyVSyetWsrbSEq04qE67WoThOJlzVvQmtNB+2LzdTuerfJVxtoSoKqtY3IabbKmxN2y7JtM2WeBzLbUZFwaer+AyNvIBB2K97waqp4de1QfdHJCGEEEIIIfYnEqIKIUQfUBRv0qmQT2doboCk5V32Xx/LXPYfS2HZDn5dI2jqu1+5pihYoSHYvlzMhg2Y0S04mk+qUvci25dL49gzaBx7BlqilvDWRV6gWruS4sYVXMcKrvXPZ5k+lUfiR/Hi5iN4Y3OEY4frzJnqY2LBfhqm7qx1uGqE2j5lp71w1Y5jNDWguA6wc7ia06py1Y9jhEHp/RYKiqLg5bMKugYBc8e/n+O6JNMOScumrC6O5ThoLZf9Gxo5AZ2IzyBoSrAqhBBCCCHEvkZCVCGE2At8uoYvrFEU9i77jyYsGhNpqqNJGuNp6uI2mqISMnUCpobWw2DFq0qdjO0vwFcvVan9xfYX0DD+HBrGn4MeqyS89W0iWxfir1/DdOszfml8xk+NeSy0p/Hv8mO4devhTBoaYc4UH9OK5b/kjnQUruKkUe32wlUD25eLFRqK5S/Yaz2DVUUhkAlIs0N0XVKWQ9JyKK9LsMWNowCmruLTNXIDOhG/4e2XaQcgwaoQQgghhBADj/zGJoQQe5mmKuQGDXKDRvay/6aERW0sSW1zmqpoAseBoNnDy/5bqlLNHMzGDZhNZTi6H9uXJ1Wp/cAKllB/wAXUH3ABRnM54a0LiZQtxNe4gdnap8zWPiXp6rxZfRD/fv0YHi88ggum5nJIqSb9NLtLNXDU9ipXU6ipBvzxKhw9iBUsxQoWY5u50Ekv1T4ZoqJkeycT8FoYuK5LsiVYbUiwpTYOCvg0L1iNBDRyA2ZmP5WAoaHvYfsPIYQQQgghxJ6REFUIIfpR68v+h+T6SVkOTYk09bE0VdEkdfEUluWia0q2SrWryalcI5ipSi3EV78Oo7kcK1C0S99IsfekQ0OpO/AS6g68BKNpC5GtC4mUvYUvWsap2kecqn1EvNHktUUHsyB4POOnH8lhw0MSpu4mVzOxA0XYrouabsZs3IjRtAnHzCMdHortL8DZuap1L1JaB6vsCFZTtkMy7VDZmGJrfRxcr2LV1DXCPp0cv07Qp+PPVKyaugSrQgghhPCceOKJvPnmm9n1kSNHsmbNGny+rq9Mu/322/nJT34CwKWXXsrjjz/e6fZvvPEGCxYsYPHixWzatImGhgY0TSMSiTBq1CgOPPBAjjjiCGbOnMlhhx3Wo59pXdflzTff5JVXXmHhwoWUlZVRU1NDLBYjJyeHgoICpk2bxqGHHsqZZ57JoYce2u1j7+xHP/oRP/vZz7Lr119/Pffee2+Pj7Nx40Zefvll3nzzTT777DM2b95MNBolEokwYsQIjjnmGObMmcMJJ5yw22MVA4Piuu4uE+eKfUNjYyO5ublUV1dTWFjY38MRQvQyx3FpSlpEkxa1zUkaYmliKRvXZcdkNUbnVXVKOiZVqQOV62I2biSydSGBLW8RiFdkn4q6ft7VDuOz8PGU5x5MXtCkKKBSGFQoDCgUBVT8uvw79oiTRks1oaYTuEaAdKAIO1CC5c8HdeD+TTllOZl2ADZJ2wFcNFXFr6sETI3cgEHI501g5Tc0fPpu9lfuQDqd5vnnn+fMM8/EMIyudxBCCLFPSyQSbNiwgbFjx+L37512OKJ37ByiAvzhD3/gxhtv7HLf7oaoK1eu5Mtf/jLvvfdet8c1depUli1b1u5zjuPQ2NhITk4OqqqyYMEC7rjjDpYvX97t448bN45vf/vbXHfddd0KjFu4rsuYMWPYvHlz9rH8/HzKy8u7fZxPPvmE66+/nsWLF3dr+xNPPJEHHniAUaNGdXucomu98X2rJV9raGggJyenw+0G7m8NQgixn1NVhdyAQW7AYHjejsmpmuJpqptTNCe8cFVTVYKmN0HVzr1Ud1SlFmSqUiuwAoVSlToQKAqp3LHU5I6FyV/C17AOfeObBLYsJN+u5hRnEac0LqK+IcQL9pE86xzDe84UHLzqw7ABhQHVC1WDajZczd4HFfJ9So/76w5aqoHtL8D2g5qOYUS3YjaVYZs5pEPDsAMFOGakv0e5C68SVSXc6kc2y/ZaAUQTNjXRFC6gKQqmruI3VHIDBmG/kQ1aZQIrIYQQYv/085//nGuvvZZgMLjHx/rkk0846aSTqK+vzz5WWlrK4YcfzpAhQ1AUhZqaGpYtW8batWtpqddrvX1H4vE41113HY899libx4PBIEcccQRDhgwhNzeX+vp6Kisr+eijj2hqagJg/fr1fPOb3+Tll1/m6aef7vbref3119sEqAB1dXU888wzXHzxxd06xurVq3cJUA888ECmTZtGUVER9fX1vPPOO5SVlQFeBe8xxxzDwoULGTduXLfHKgYOCVGFEGIf0XpyqjFFLs0pm2iml2pdszdJleW4+HWVoKnjNzIVaYqKFRqKY+ZgNmzAiG7FMQJeVaoYGBSFZN4EkgdPoPmga9i+fRX2+jcZXbOIPLuey/XXuZzXqSaP5+2jeMo6ho/TBxBNO2xqBLDbPayqQL5foSig7AhcWwWvLY+Hzf0rYHOMII4RBMdGSzcRqF2Bo/ux/IVYoVJsX/6A/kODrqnomkqoVZGE7bgkLZtE2qExHsd2m1FQshNY5fh1cgKG1wrA1PDrqvRZFUIIIQa57du3c9ddd/GDH/xgj46TTqeZM2dONhAdNmwYd999N+eeey6quuvPE1VVVTz99NM89NBDrF+/vtNjp1Ipzj77bBYtWpR97Mgjj+S2227jlFNOwTR3/ZnMsizee+89/va3v/Hoo4+SSqVobm7u0Wt64IEHssuBQIB4PJ59vLshaosJEyZw7bXXcuWVVzJ8+PA2zzmOw/z58/nmN79JLBZj27ZtXHHFFbzzzjvSumsfJJfz78Pkcn4hRIu07RBNeJf+V0UTNMUtEpaDqkDA0An+f/buO86Ou773/2v6zOnbi3ZX3ZJ7L7jIxiUGB1Njgh1D4hACSQi5N/ndBMjlJiEkwM3NvQmBQCo1YCAUBzDGDRds3LBlW7Ity+rb6+ll6u+PWa0ky7KKV9r2efKYx845Z2bOnLMrPOd9Pt/P19TiCaqiEKMyjJnfhupX8e2mEzZzuTgGUYAzvol0//2kBh9G88ozD9XsdnY0X8YzqYt5MVrOeD1iohoxUQsZr0VM1iPCI/wv/GmtGn90gU1P5sROujSfKH4dzS2ihAGhkcZLdeHbzYRmZsG2wAijaLoVQNwOwAtCFNgXrDoGfS0JMvahh+nLcH4hhFhaZDj/wrX/cP6LLrpoZsh9c3MzO3bseNUhyocbzv/tb3+bd77znUAcOG7cuJGTTjrpiM5r27ZtrF69+hUfC8OQ9773vXzpS1+aue9P//RP+cQnPnFExwYYHBzk93//9ykUCtx9991HtE+5XKazs3MmeP385z/P7/zO7wCg6zr9/f10dHQc9jj3338/O3bs4N3vfjea9urX0d/73vd4+9vfPnP7jjvu4Nprrz2i8xWvTobzCyGEOCqGptKUNGlKmvQ0OdS8uEq1UPMYL7tMVl38MMRUNZJWO4m2NFZ5D0ZlGKU+JWHqfKVo1NrOpNZ2JqNn/g7J0adI9T9AaugRnPoopwx+h1P4Do10L+VlGyit24CXir/9DsKIfCNivBYHq/sHrOO1kInp+0subBoP+MBPKvzWmTZvXmscdvKyxSjSbXzdhihAdctYUy9iqgaB3YSX7CKwcgvu34h6iAmsvCCuWh3M15isuKxuT9GVsWXIvxBCCLFI3HzzzUxNTbFlyxYmJyf527/925mQ9FjceeedM+tvectbjjhABQ4ZoEIcQu4foP7BH/zBUQWoEFfFfuc73+HJJ5884n2+853vzASoK1eu5P3vfz//9E//xMaNG/F9n//4j//gD//wDw97nMsvv/yIJ4t629vexgUXXDAz/P9HP/qRhKgLkISoQgixyCiKQsLUSZg67RmbVW0R5bpPqeExUXYp1j3yrg7aCjLpVnLeCHZ9FKWRj8NU7cgbsosTSDWodF5ApfMCRv06yZHHSfc/QGLkCazSHqwX/oOWF/6DenY1pZ7LKS+7jJZEGy0OwKG/GR+thPztYzWeHAn43JN1Hur3+B8XOrQnl+hQb0UjtLKEVhYlaKDVJzGqIwRGCi/RTuC0EVhZUBbm+6MoCqYeD/NP2waFmsfmgQKFqsuqttRhJ6sTQgghxPynaRp/8Rd/wbve9S4A/t//+3986EMfOuYRrAMDAzPry5cvn5VzBPjkJz85s75y5Uo+9alPHfOxzjnnnCPedv+h/DfffDOKovDud7+bjRs3zjx+JCHq0brkkktmQtSdO3fO+vHF8bcwPwEIIYQ4YpqqkE0Y9DQlOLM3x/krmjl3eRNr2tMoyWYG7DXssE9mTGkhrEyhV0ZQAneuT1u8iki3KS+7jKEL/5Qdb/waw+f8dyrt5xApKnZhG22b/52Vd95Cz4N/THb7j9AahUMeqz2p8skrEnzwXBtLg42jAe+7o8xPtrss9Y4/kWbhJ9pwk51EioJV2I4z8gSJ0ScxygMofn2uT/E1yzoGLUmL3RNVNu7JM1ZqzPUpCSGEEGIWvPOd7+TMM88EoFQq8elPf/qYj7V/39MdO3a85nPbe5y77rpr5vbv/M7vnJAWErt27eK+++6buX3zzTcDcNNNN80MyX/mmWdmAtXZtH8P1CB45TkNxPwmIaoQQiwxthFPTrW6PcX5K5o5f0ULa1csR+0+k7Hs6QwFWcpTIwSFQRTfm+vTFYcRGklKfVcxePHH2fGGrzJ65u9SazkVAGfiOdqf+Twr73g33Q9/jPSuu1Hd8kHHUBWFt6w1+cIbkpzSolH14P88VufPflZjshae6Jc0/ygqoZnGS3UT2M0obhF7/BkSw49hTr2IVs/DAg6cTV2lO+dQcwOeGcizbbSMF8jvXQghhFjIFEXhL//yL2duf/azn2VoaOiYjrX/kPwf/OAHPPfcc6/5/PYPMiHuxXoifPWrX50pFLjwwgtnWhN0dnZyzTXXzGy3f7XqbHn22Wdn1nt7e2f9+OL4kxBVCCGWsL1Vqr3NCc5Z3syZ69ew4vSLMVdcQNVooTgxRHmsn2q1RiiZyrwXWFkKK6+j/7JPs+PaLzF26m9Sz61FiUKSo0/R+dTfsfKOm+l69BOkBh48qJKyJ63xf69K8N4zLQwVfj7g874fV3hgj4Tpe0WaQeC04iW7iVR9pjrVGduIXhlesFXciqLQmrJImTpbR0tsHihQrMvvXQghhFjIrr/+ei688EIAarUaf/VXf3VMx3nrW986s16r1diwYQN/8zd/c8Aw/6P14IMPzqx3dnbS19d3zMc6Gl/5yldm1t/97ncf8Nj+t7/+9a/j+/6sPe/u3bu59957Z25fffXVs3ZsceJIiCqEEAKIQ5SUpdPdlOSUNWs45bzL6T3zMpraujAb41QmB5kolinVffxg4VbdLRW+00p+7dvZc8X/Y+fV/8TE+l+jke5FDX1SQ4/Q9finWfXjm+l44m9IDj0KYRyYaarCu062+NwvJVmVUym6EX/5UI1P/rxKyZXf+wxFITRT09WpObT6JM7Y0ySGn8As7ER1S3N9hsckYep0ZhxGSw027s4zVFj4LQuEEEKIpWz/iZr+5V/+hV27dh31MV7/+tdz/fXXz9yemJjgj//4j+nt7WX9+vW85z3v4TOf+QyPPfbYEQePu3fvnlk/+eSTj/qcjsXDDz/M1q1bATAM46Dq17e+9a2kUikARkdH+fGPfzxrz/2Hf/iHM0P4+/r6Dng/xcIhE0sJIYR4RbZpYHf20da+DK80SnVkG7WpYfJuhaKfwUfBVOOZvy1dBZnYe97yUsuYXH8jk+vehVncSXrgAdL9D2BUR8j030+m/34CI0W5+xJKPZdTaz2VlTmNz16T5GubG9z6vMu9u3yeHi3zRxc4nN8llw/7izQTP9EGUYjmlrAnnyfUbXynDT/RgW83g7pwJmzSVIWurEOh5vH8UNxPt+EFGIYxx2cmhBBiXooi8KpzfRbzi5EAZX5cHF999dVcccUV3Hfffbiuy8c//nH+7d/+7aiP8/Wvf533vOc9fO9735u5L4oitmzZwpYtW/jqV78KQDKZ5E1vehPvf//7ef3rX3/I401OTs6sZ7PZwz7/1q1b+fu///tX3ebd7373TOXtK9l/iP4b3/hGWltbD3g8kUjwjne8Y2a7L3/5y7MSdn75y1/mO9/5zsztT37yk1iWTOa7EMmnICGEEK9O1TCyXWTT7WTLo7RP7aKWH6YaaExEKSpuQKnhoqLimHGoOk+uGcXLKQpudiUT2ZVMnPwerKkXSfffT3rgQfTGFNldPyG76yf4djOlZZdR6rmCW05fw0XLdP7mkTp7SiEfvb/KL682eP9ZNo4hv+gDKCqBlSWwsih+Db0yhFEZIDCb8FLd+E4Lke7M9VkesaxjYKohQ8AzAwVO6oqH/AshhBAH8Krw191zfRbzy0cHwUzO9VnM+MQnPsGll14KxIHehz/8YdauXXtUx0ilUnz3u9/l9ttv5+/+7u+45557CF+h31elUuGb3/wm3/zmN3nzm9/Ml770JZqamg7arlTaN2onmTz8ezUwMMDnPve5V93mvPPOO2SIWq/X+da3vjVz++VD+fd6z3veMxOi/uAHP2BycpLm5ubDnt+hPPHEE3zgAx+YuX3jjTdy0003HfPxxNyS4fxCCCGOjKpBpgu15zySKy+graWVdU6ZU7Iea1uTtKZMgjBiotJgvNygXPcJZNj//KUoNJrXMX7Gb7PjDV+i/5K/orD8lwiMJHp9kqZtt9F3/39n+d2/zSWjt/JvF0/ytpNMAH60zeO37yjz7Ojs9YlabCLdwU924DltKEENe3wTyeHHsSZfRKtPQbQwmgxbelxBW2sEPN0vk04JIYQQC9Ell1zCG9/4RiCeFf7P/uzPjvlY1113HXfeeSfDw8N861vf4r/9t//GZZddNjMMfn//9V//xWWXXXZAYLpXOp2eWa9UKsd8PkfqtttuI5/PA5DL5Q5ZYXrFFVfQ09MDgOu63Hrrrcf8nDt27OD666+nXo/bI51xxhl84QtfOObjibknlahCCCGOjqZDphuSbSjlUZypHTi1CVpTDm5zloobUap75CsehZpHGEWYuoapKTND/hUUlOmbCvGKQtyXFUCNHxAniqJRazuTWtuZjJ3xOyRGnyTdfx/J4ccwK0O0bLmVli238snsKm456VL+dM/5PFtp4Y/urfKOdSa3nGHFv19xMFUnsJsIrByqV8Es7sAo7SZwWvCSnQR2M5E2/6s7W9MW9QC2jpYo1T1WtafI2DK8XwghBPHQ9Y8OzvVZzC9GYq7P4CCf+MQnuOOOO4iiiG9+85t85CMf4fTTTz/m47W1tXHDDTdwww03AOD7Po888ghf/OIX+cpXvjLTG3Xz5s386Z/+KZ/5zGcO2H//6s5CoXDY57viiiuIooMLNFasWHFEfV73H8p/ww03HHI4vaqq/Nqv/Rqf/vSnZ/b73d/93cMe/+WGhoa45pprGB4eBmDVqlXccccdZDKZoz6WmD8kRBVCCHFsNAOyyyDVDqVhmNqJWR7CNJM0NeXozjlUGwEV12ey4uIGIYQQAdH0ShRBRHwxFLGvOC8i7rGEQryRokzfuzeom17f/y5AV1R0TYkXVUVXFQljj1KkGVS6LqTSdSGKXyM19Ajp/gdIjD6JXdjOGYXt/ICvsDW9ni9XX8ftWy7ksaEcf3yRw7rmhdP384SbnogqNFMogYfWmMKojhAYabxUF77TSmik503/tFeSMHUsXWO0VKfU8FnVlqIrY6Oq8/echRBCnACKMq+GrotXds455/C2t72N7373u4RhyMc+9jG+//3vz9rxdV3n0ksv5dJLL+W9730v1157LeVyGYgntPr0pz+N4+xra7R8+fKZ9eeff37WzuOVDA8Pc+edd87cvvnmm191+3e/+90zIepjjz3GCy+8wPr164/4+SYmJrjmmmvYtm0bAF1dXdx99910dXUdw9mL+URCVCGEEK+NZkCuF1IdUB6GqV1QGEC30mTsLBlHpzNj48eJKRFRHJ7uDVAjCKej1ChOWKcfi4PU+K69+0IY7VufeTyCMIyoeQE1L8APImqeRxBOHxAFQ1XRVAVDUzE0FVUa2hxWpDuUel9Pqff1qG6R1ODDpPfchzOxmbXeC3zCeIE/N77MQ7XT+K97LmbjSRfzjtOb4vBaHFKkGfhOK0QhqlvCmnwRU9/5somo5ucl2t5Jp/JVl00DBQo1l1WtKWxDAnQhhBBivvv4xz/O97//fcIw5LbbbuPxxx/n/PPPn/Xnufjii/noRz/KRz/6USDuR/r444+zYcOGmW0uu+wy/v3f/x2IQ87du3fT19c36+cC8LWvfY0gCGZuX3755Ue1/5e//GU++clPHtG2xWKRa6+9ls2bNwPQ2trK3XffzcqVK4/qOcX8ND+v0IUQQiw8ugm5vjhMLQ5CfjcU+sFOo1hZjJlg7fgGbFEEXhjiBSGuH+EHIXUvpOYF1L2ARhBXx+4NYxUlDlZ1FXRNRVclYH0loZmhuOINFFe8Aa02TnrgQdL992PnX+Jy7Rku156hvv3feGzX2WRPuZLkyguINHOuT3t+U1RCK0toZVH8OnplGKM8SGBl8dK9eIl2UOfnkPlcwsTxA3aPVynWfNa0p2TSKSGEEGKeO/XUU7npppv42te+BsD//J//k5/85CfH5bne8IY3zISoEA9v398VV1xxwO1bb72VP/7jPz4u57L/UP5j8bWvfY2/+qu/Qj3Mh4RKpcJ1113HL37xCwCy2Sx33HEHp5xyymt6fjF/SIgqhBBidukWNK+EdBeUhqYrU/vj+483M4FiJDE1FVNTSb4swwvDOGB1gzhk9fyQhh9ScX3c6aA1CHxCQkBBQ0HX47YAhhq3CpD2ABA4reTXvI38mrdhlAdI9z+AtuM+co0BNoSPwabHqD+XoLHsIso9l1NrPYNIm59h4HwR6Ta+bkMYoLlFnPFnMaxm3EwfvtMWT+w2z1i6RlfOYaLs8kx/nhUtSXqbExiafAshhBBCzFd//ud/zq233orv+9x555088MADx+V5bNs+4PbLe5CuWLGCX/qlX5oZZv+FL3yBD33oQwft91o9+eSTbNq0aeb2+eeff9gwdK9f/OIX+L5Pf38/99xzD9dcc80ht63X67z5zW/moYceAiCRSPCjH/2Ic88997W9ADGvSIgqhBDi+DDs6TC1M+6Z2jh4Vs5ZFfpQK0B1ADQNrEzc1H+/HpOqCpaqYukHXzgFIbhB3Apgb8hacwOqboAbhDRcDz/c18ze0jTStr7kQ1UvtYzJ9TfCunexa/Qldj75U86rP8SycAJ7z71k99xLqOq42VXUmtbRaFpHvXkdXqJzXvf/nDOqFk9EFWXQ6lM4Y0/jO2146Z64BYAyvwJKVVFoS1tUGj4vjpQo1mTSKSGEEGI+W716Nbfccgv/8i//AsTVqFdeeeWsP8/TTz99wO1XGqr/4Q9/eCZE3bFjBx/+8If5u7/7u1k9j/2rUE8//XQee+yxI973+uuv54c//OHMcQ4Vonqexzve8Q7uvfdeIA6Mb7vtNi655JLXcOZiPpIQVQghxPFlOHGYeiJ4NajloTwK1QmoTcW9Ja1MfB6vEtppKjiqBq+Q/XhhhO+HuEGEGwR4fshExWWsXCfrmJivEMouOYpComMtJ79hDf+57T08vvEZruVh3qg9RmtYxJ56EXvqReAHADT0DOXsSXgt6wha11HPnURopub2NcwnikbgtBKEPnp9Er0+hud04KV7CezmeRdAJy0dS1cZLTUoNXxWt6XolEmnhBBCiHnpYx/7GF/5yldoNBo8+OCDeJ73qtv/3//7fznjjDO4+uqrj+j41WqVv/7rv5653dHRwVlnnXXQdpdffjm33HILX/ziFwH4+7//e9LpNH/5l3955C/mVXiex9e//vWZ24ebUOrlbr755pkQ9Xvf+x6lUol0On3ANkEQcNNNN3H77bcD8QRb3/rWt474vRILi4SoQgghFg/DiZdMF7hVqOehPALVyThU1U2w0nGF6tEcVlUwTI14PtH4P50tKYuhQp2RQh1VVcg6xnzLteaEoihct8bm7M7z+JtHT+VjY7fQq4xytrKNs9WtnKVu4xRlJ5ZfxJp4AiaegBfjfXcr3ew01zLkrGUivY5GZgVNjk6TrdBkq+RsBUdfYm+yquMn2lECD702hl4bx0924qV6COzcXJ/dAXRNPWjSqZUy6ZQQQggx7/T29vL+97+fz3zmMwA88sgjr7r9Y489xh/90R9x3nnnccstt/COd7yDjo6OV9z20Ucf5YMf/CDPPvvszH1/8id/csgh9J/61Kd48cUXZ4bBf+ITn+Cuu+7iYx/7GNdccw2m+co99p9//nn+/u//nv7+/kOe9+233874+DgQX6PeeOONr/o6X+7Nb34z6XSaUqlEtVrl29/+Nr/5m78583gURbz3ve/lP//zPwFQVZWvfvWrvPnNbz6q5xELh4SoQgghFiczES+ZbnAr0xWqI1CbhMpE3KPVSh11oLqXpassb06QcXQGpmqMl+tkbBPLkKpUgK6Uyv+5MsEvhgOGysuZqvfyRP1y7qpHlGsurfUdrPK2chovcZayjRXqCH3RIH2NQWjcD3moRSbPRivZGK7hjnANG8M15PVmmmx1elFmAtZ96wrdKZWcvbh+D5Fm4Cc7UIIGRnkAvTaKl+zGS3UTmpm5Pr0D7J10atdElULNZ1VbktakJVWpQgghxDzy0Y9+lH/913+lWq0e8T5PPPEETzzxBL/3e7/H6tWrOfXUU2ltbUXXdcbGxti4cSM7duw4YJ+3ve1t/P7v//4hj2maJj/5yU/4rd/6LW699VYgDmLf9KY3kUgkOP/88+nq6iKXy1Gv1xkbG2Pz5s3s3LnzgOOsXr2as88++4D79h/Kv2HDBnp7e4/4tQI4jsPb3vY2vvKVr8wcb/8Q9fOf//wBz7F69Wp+9rOf8bOf/eyIjv/Zz372qM5HzD0JUYUQQix+ZjJessugUY4rVEvTgWp1ErS9FarOUR1WUaA5YZI0dYYLdYaLdWquQjYhVakQ98s8v+uVLjUSwNlE0VnUfNhZj9hcmsKYfJF04UVayy+yrL6VBFUuULZwgbplZs+RKMfGxhqeqq1hY7SGe8JVVDl4AoI1TSrnduqc26lzaquGqS2OX0ikWXipLhS/hlnchVEZwk0tw08tIzSSc316MyxdoyvrMFlxeXpPgY6MRW9TglzCQJF/HEIIIcSc6+jo4EMf+hCf+tSnDrvtVVddxWOPPXZAQLpt2za2bdt2yH0cx+EjH/kIH/nIR9D1V4+eHMfhG9/4Bm9961v5+Mc/znPPPQfEbQHuv//+V933pJNO4gMf+AC/93u/d0DV6sTEBD/60Y9mbh/tUP7999sboj744IPs2LGDlSvjVmWjo6MHbLt161a2bt16xMeWEHXhkRBVCCHE0mKl4iWzDNxyXKFaGo6D1coEGFYcqOpHPjOopav0NSfIOAYD+apUpR4hRVFIGJAwFEi3QPfrgNcBMBCFGOWB6V6qW7AnX8Aq7qSDPNdqT3Ct9gQAISqDei9btDU8E63mUW8Nj9W6eWkKXppy+ebzLpYGZ7TrnNepcW6nTl9GXfBBXqQ7eCkH1atg57cRVoZx0714yS6io/jbPZ5URaE1ZeEFIaPFBmPlBt1Zm56mBGmZeEoIIYSYc3/8x3/M5z//eQqFwqtu9773vY/3ve99bNq0ifvvv59HHnmEF154gV27dlEoFIiiiHQ6TWdnJ2eccQavf/3rueGGG2hqajqq8/nVX/1VbrjhBu6//37uvvtuHnjgAQYGBpiYmKBWq5HJZGhububkk0/m/PPP5+qrr+aiiy56xWN94xvfwHVdIJ7o6Vd+5VeO6lz2uvLKK+nq6mJoaIgoivjyl7/Mn//5nx/TscTCp0RRFB1+MzEfFYtFstks4+PjtLS0zPXpCCHEwhVF0ChNV6gOx8Fq0IiDVCsdD/0/Qg0/ZKRYZ6hQR0WqUmeT4texCtuwJ7fEwerUixi1sYO2840021Pnck90Dv+RP43++oGhYqujzFSpntOpkbUWftituiW0RpHQTOOme/GTnUTakf/dHkoY+Ozc+DNWnHUpqvbavnuvewGT1Qa2rtHTlKA75+CY0i9VCCHmk3q9PlNpZ9vz40s5sXiFYUixWCSTyRyyZ6oQhzMb/7+1N18rFApkModulSWVqEIIIYSigJ2Jl2xvHKjWpqA8Haj6jekeq6nDBqp7q1LTtsFgvsZYuU7GNmRynVkQ6Tb1llOpt5w6c59Wn9wvVN2CPbUV3Stx0tR9nMR9vF/Vmew6nSfM8/hO7Wzun8gxXov4yQ6Pn+zwUIC1zfuG/p/SomEswKH/oZkmNFJobhF78jmC8gBeZjleoh3U+VH1aRsa3dkE5YbP1tESQ8U6y5sTdGRsTF0+OAkhhBBCiPlNQlQhhBBif/sHqrk+aBTjQLW4t0LV3ReoaiaHKjNtShgkLY2RQp2hYp2aG5B1TORL9tkV2M1Uul9HpTtuA0AYYE8+T2r4MZJDj2BWBmmdeoo38BRvAGqtq3kpfT53B+fwXxO97ChGvDgZ8uKkyzeec7F1OKtdnw5VNXrSC2jov6IQWFkCM43WKOCMP4thNeNm+vCdNlDnR5CfsnSSpkax7rN5sMBAvsbylgTtaRtNJp8SQgghhBDzlAznX8BkOL8QQpxAYbgvUC0Nx9WqQdxnCU2PK1R1GzTroGA1X/UYyNco1DzSti5VqSeQUdpDavhRkkOPYU8+j8K+yx7PaWWi9QIe18/lh5WTeXREId848LKoPbFv6P/ZHToZawGFfFGAVp9CDTx8pxUv3YvvtIJy5En+bA7nfyVBGJGvujT8gPZM3C+1NWUunOBaCCEWGRnOL04kGc4vZoMM5xdCCCHmG1UFJxcvueXgVcCrgVeFeiFeGmXwJ6a31+JQVbfIORZJK81wocZwsU6tEZBNSFXqieCle5lK9zK19lfQGgUSw4+TGn6UxOiTGLVxOvfczvXczi/rDpVl57A9cz53+2fxszGHTWMBo9WIH2/3+PF2D1WBk5o1zu3UOK9T55RWDXU+h32KRuC0EoQ+en0SvT6O53TgpXsJ7OZDVlGfSJqq0JKy8IOQybLLRNmlM2vT0+SQS5iHP4AQQgghhBAniISoQgghxNFS1XjCKSu9774wjANVrwZ+DeolqE/F99UmMaKIXl0jm9EZLAdMlD3Sto0tE+ucMIGVpbT8akrLr0YJXJyxp+Mq1eHH0OuTpAcf4szBhzhDUfmd5lPIn3Uhj+vncn++nV8M++wqhrwwEfDCRMB/bHbpSiq8YZXJtasMWpx5nIirOn6iHSXw0Gtj6LUx/GQXXmoZoW6DohIp+pwO99c1lfaMjeuHDBVqjJXqdGUdepoTpCy5XBVCCCGEEHNPhvMvYDKcXwgh5rkomq5Wna5YbZSglsdrVBnPFxkrVQlDhVQqjWJYhJo1b/pWLilRiJV/ieTQo6SGH8Uq7jzg4Ua6l0rnhQw0nc/9tVU8MRLx2JBP1YsfVxW4sFvnulUG53fp876vpxI00GuTRIoKqk6kaKBoRKoKqkGomkSaQaSa+JHKS9t3sXrtWjTdIFL1eD9FJ1K14xbA1tyAyWqDhKnT2+TQlXOkDYYQQpwAMpxfnEgynF/MBhnOL4QQQiwGijI9CVUCmP6yK4ow/AZdXhWnWKR/ZIyxqVEyQY2EWkKJAkAh1EwizYpDK80ARQKk40ZRaTSdRKPpJCZPeTd6ZYTk8GOkhh/FGX8Wq7QHq7SHZv6Tk80slc7zmbrwQm5vnMmPdkRsHg/4+YDPzwd8Wh2Fa1caXLvKpCs1Pz8MRJqFl+qC0EMJA5QohCiE0EcJXLSoOHOfHoSAjTP+7Ew4HIeoGqgqEeohA9hI1UHVCawcoZE8qnN0TI1lZoJy3WfLSInBQp3lLQk6MjaGNj/fVyGEEEIIsbhJJeoCJpWoQgix8HlBSP9kld2jU0RejTYrRA9qqG4BzauhhI047Jr+z3WkKESaSaQaM4tUrx4/qlchMfKLuI/q8BNofmXmMd9uJr/yOjY3X8N/9Se5a4dH0Y1/TwpwdofGdatNLl6mY2jzuzr1UIIwYsueKdb1Nu2rsI0ClDCMf+4NYGfW990X/4wIrBz1llMIrewxnUMURRRqHlXPpylhsrwlSWvKmvcVv0IIsRBJJao4kaQSVcwGqUQVQgghlghDU1nZliKXMNkxXmFPqU7WbiOV0yEMUEIX1W+ghA2UwEXxa6huBc2vofpVCLw4rGI6YFWN6UrAuBpQAtbXJjSSlHs2UO7ZAKGPM7GZ5NCjpAceQK9P0vr817hMvZWzl23gdy9/Ez+trOT2bS5PjgTTS42spXDNCoM3rjboyyyC34eiEWkaYHDYb+KjCL06gjO+mXrLyQR209E/naKQS5ikQ4N81eXpPXna0xa9zQmakybKPJggSwghhBBCLH5SibqASSWqEEIsLl4QMjBVZedEFT+ISNs6uqqiqcrBVXfTAasSNFADdzpgraJ6FVS/hhp6ELjT1YAQqcp0awBzvwpW+S71mIUe6YGHyG7/Ac7Ulpm7a83rya+6npcyF/HjnRE/2eExUdt3qXVaq8Z1qw0u6zWw9fkf/r1iJerRiiL02hiRasVBqtP6ms7JC0ImKy4AnVmb3uYEWcd4TccUQggRk0pUcSJJJaqYDVKJKoQQQixBhqayojWuSt05XqFY96mFAX4YEUQRChERCgqgKsp0wJpAU5NouoLuTAeuShSHqkEDNZiuYA3qccDqVdD8OgR7+69CpGr4Tov0XT0aqkGp9wpKvVdgTW0ht+2HpAcexJl8AWfyBdrsZk5Z8UZuueZafj6V5vZtHo8N+WwaD9g0HvC5J+tcudzgutUma5oW+fuuKPiJdvTaOM7EZurN6/ETHcd8OENT6cjYNPyAgXyN8VKDZU0O3TmHpCWXtkIIIYQQ4viQStQFTCpRhRBi8QrDCC8M8YMoXsIQP4ziJQipewENP6Thh3h+/Fg4/fgrB67KTMCqRx5m5KHjoUceenUUozKMl2iPJ7ESx0SrT5HdeQfZnT9Gr08CECk6pWWXkV99PQPWGn6yw+OO7S7DlX2XX2ubVN642uTK5QZJY35Vp85KJep+tPoUShTGQWqyaxbOEKquz1TVI2lpdGcd2jMWaVv+joUQ4lhIJao4kaQSVcyGE1mJKiHqAiYhqhBCCIiDLn9v4Dodsh5V4Bq4ZIsvkXWH0NLtYMiHptck9EgNPkxu+w9wJl+YubvWtI7CqjdR6L6EjWMqt29zeWjAx49b2mJrsKHP4I2rDE5u0ebFxEmzHaICaI0Cit+g0bwOL9UDs9TTtFT3KNZ9bEOlPWPRlXHIJQzpmSqEEEdhbxixYsUKHMeZ69MRi5yEqGI21Go1du7cKcP5hRBCCHF4cc9UjSMZyXxAhet0yNrwQyZKCSrDFurUDjwjjeFksA0NfYHOKj+nVINyz+WUey7HmnqR3PYfkBp4EGdqC84vttC66d9pXflGzj/3jUyel+WuHR63b/fYUwy5c4fHnTs8cpbCBd06F3XrnNOpz7sK1dcisLKoSglr8gUIQ7xM36wEqWnbIG0bVF2f/skag/k6bSmLrqxNc9JE1+TDmRBCHM7eICsMwzk+EyGEODJ7///qRATxUom6gEklqhBCiNnU8Dwqw9toDD7PlKdQVtP4QYihatimiq1rsHiyvBPq0EP9LyW/6nrqTSexeTzg9m0eDw14VL19++oqnNGmcWG3zkXdBt3pExcGHo9K1L1Ut4zmlmjk1uBmV4Iyu6/L9UPyVZcgisglDJY1JWhNmVj6Iu9BK4QQr0EYhrz44ou0tbXJZ0xx3EklqpgNExMTjI2NcdJJJx3z35EM518CJEQVQghxXBQGCEeeo+q6VPVm8jWfcsOn4fkoioKla1KleqxCf7+h/s/P3F3PrSW/+s2Uuy/FU3Q2jQU8MujzyKDPQOnAaqDejMpF01Wqp7Ye32H/xzNEBVC8Kno9TyO3Cje7GtTZDziDMKJQ86h5PmnbYFnOpi1tyyRUQghxCP39/Xiex8qVK+f6VMQiJyGqmA07duzAMAx6enqO+RgSoi4BEqIKIYQ4birjMLIZ3DKkO2kEUHF9ynWfQtWj6gUEYYipxYGqpatSpXqUrPxL5Lb9gNTA/aihD4Bv5SiseAPFvqvxk50A9BfjQPXRQZ9nxwKC/a7cUgac3xVXqJ7XpZOxZveXcLxDVADFr6PXJnGzK2jkVoN6fCaFCqOIUt2n3PBwTI2ujENHxibj6NI3VQgh9lMsFhkYGKCvr49kMjnXpyMWMQlRxWtVqVTYvXs3y5Yte9Xw83AkRF0CJEQVQghxXNULMPJcHKhmOkGNK/eCMJ4RveL65KselYZPww9RFQVbV3FMHbkOPnJaI09m50/I7fjRzFB/gGrr6RT7rqbcfTGRHk/uUXYjfjEcV6g+NuhTdPddxqkKnNq6d9i/Tl9Gfc3h4IkIUQGUoIFeG8dN9+LmTiLSzOP2XACVhk+h5mHoCq0pi+6cQ1PCnBeTeQkhxFwLw5D+/n6q1Sq9vb0SpIrjRkJU8VpUKhX27NlDIpGgp6fnNf0NSYi6BEiIKoQQ4rhzqzD6PBQHINUOunXQJjUvoOoGFGsexZpH3QsJowhT17ANFVOXi+IjEvqkhn5OdudPcMaeRiG+RAs1m/KySyn0XU295ZSZ3qFBGPH8RMCj08P+dxYOHPbflVS4cJnBRd06p7dpmMfQfuFEhagASuChV0fxUstoNJ1EpB/b7KpHo+4F5GseENGUMFnW5NCStORvVgix5O0NUiuVCrZtk8lksG0bVX3tX9AJsVcYhpTLZVKplISo4rCiKCIMQ+r1OsVikXq9TjKZfM0BKkiIuiRIiCqEEOKE8F0Y2wJTOyHZDEbikJt6YUStEVBxfaYqLlU3wAtDIGL/8f4KCqoCqqKgqgoKoKkKyt779i5L9Hpar46S3vNTMrvvxqwMzdzvJjop9V1FsfdK/GTHAfsMl0MeHfJ5dNBj40iAt1+m6uhwbqfOhd3x0mQf2Rt7IkNUAEIfszKCl+yk3rx+pgL3ePOCkELNo+GH5ByD7um+qY554iah8oMQP4wIwvjSPGFqElQIIebU3oCrWCxSLpeR6EDMtiiKqNVqOI4j/80TR0xRFFKpFJlMZtYCeAlRlwAJUYUQQpwwYQAT22D8RbDSYB++51AUxVWqDT8kiuJwKIgioigOreLQaF94FE4/Fm8TEYZxH8sDeq1OZ7EaCoq6N2xlJpBVFAVNVRbPpFdRhD35PJndd5MaeBDNr808VG09g2LfVZS7LzmoarPmRTw5sm/Y/2R93+WeAqxr0Xhdt86GXp2ezKGDwhMeogKEAUZlGD/RTqN5PaFx4oaRBmFEqe5RcQOSlkZX1qY9Y5Oxj65PaxhGM4GoH4b4wYG3gzDC9UMafoAbhLj+9L+PMCIM47/55qRJZ9amOWGia0v02wQhxLwRhiG+7xOG4eE3FuIIeZ7HAw88wIYNGzCM49MTXSwuqqqi6/qsVy5LiLoESIgqhBDihIoiyO+GsRfiWdQTs/ffnr3haTgdngZROB2i7r8ePx4HUvuCKS8IiUIIiB8PwogohFzCXFSVrIpfJzX0czK778YZe2bfcH/dodR9CcW+q6m3nAovq+QIo4itUyGPDng8MuizderAD8Crciobeg029Or0vixQnZMQFSAKMCojBFYz9ZaTCc30iXtu4sqYSiOgUHexdY32jEVn1sHUVYJgXxC6NxidCUT9iIYfzHxhsPdnGEAYhSjK3t9aHPpr06G/psbrqhpXZIchFOseYRSRcQy6szYtKYukpZ/Q90EIIYQ4njzP4/bbb+e6666TEFXMKQlRlwAJUYUQQsyJ4lDcJzVoQKrjoNBuLoR7Q9QwouGFDBZqTFUapCwD+wQOyT5R4uH+95LZfc8rD/fvuwo/0f6K+47XQh4b9Hlwj8dTIwHBfleCK7L7AtXlWW3uQlSAKIyDVDMTB6lW7sQ+/7SaG4epCnHIGYf8EQpRHIhG+1pPHBCKTldK779+tIIwolj3qLo+jqHRlrHoSNvkZBIsIYQQi4CEqGK+kBB1CZAQVQghxJypTsLIZmgUINUZV6bOI14YMVqoM1SoE4TRoqtKnRFF2JPPkdl9D+mBB1EPGu5/NeXuiw85SVOxEfHwgMcDe3yeHPYPClQv7dHp1atcvm4OQlSAKEKvjhLpCeotJxPYzSf+HKb5QUgEM8HoiVZ1fYp1DyKFXNKgO+fQkjSxjfn1b08IIYQ4UhKiivlCQtQlQEJUIYQQc6pRgtHnoDQC6U7Q5t/Fb6HmMzBVJV/zSNv6og6c9h/unxh7eub+eLj/pRT7rnrF4f57ldyIh/unA9URH3+/Uf99GZUNvTobeg1WZE/8zMx6dZRINWk0n4yfaDuhzz3feEFIsebR8AOSlk5HxqYtbZF1DJmUQwghxIIiIaqYLyREXQIkRBVCCDHnvFrcIzW/B1LtoFtzfUYH8YKI4UKNoWIdJVLIJoz50IHguNKro3F16u57MKvDM/e7yS5KvVe+6nB/iAPVnw94PLDb44lhnyDa94b17heorjyBgapWG0dRVOpN6/GTnSfkOeezvX1bi3UPXVdoSZh0Zh2akyamvhjLroUQQiw2EqKK+UJC1CVAQlQhhBDzQuDB2IswtQOcHJgnbjb1ozFV9RjIVynWPLLOEgmaogh7YnMcqA7+7IDh/rWmddSb18dL0zp8p+2gKtUgjNi4Y4pxJcXP+n1+Mezj7Veh2pPeF6iuyh3/QFWrT6FEAY2m9Xip7uP6XAuJ64cUah5eGJK2dLqyNi1pi4wtH0iFEELMXxKiivlCQtQlQEJUIYQQ80YYxiHq2BYwHbBzc31Gr6jhhwwX6gwX6miqQtYxYJFXpe6l+HVSgw/Hw/3Hnznocd9upt60jnrzOmpN62nk1uCr1gETS1XciEcGfR7Y4/H40IGB6rL9AtXVxzFQ1RoFFL9Bo3kdXqpnXkxsNl+EUUSp7lNu+Ni6SkvapDPj0JQw0LUl8KWBEEKIBUVCVDFfSIi6BEiIKoQQYl6JIij0x8P7iSA5P3tXRhFM1VwGpmqUah65hImxFKpS96NXR3HGN2FPbcGe2oJV2I4ShQdsEykqjcwKhowVWL1n4javw0stmwktK17EowNxoPrYywLV7lQcqF7eZ7Cmafb70KpuCdWr4OZOws0slyD1FdS9gELNI4wiMo7BspxDS8okYepzfWpCCCEEICGqmD8kRF0CJEQVQggxL5VHYWQzeHVId8zbgKvhhwzmq4wUG5iaRtrWl0xV6sspfh2rsA17cgv21As4ky+g1ycP2i4wUjPVqvWmeAnNFFUv4tHBfYGqG+zb56JunfedZdGXmd0wVfUqaI0ijdwa3OxKUJZWEH6kgjCiWPeouj6OqdGRtmnP2OQcA1Vdon/wQggh5gUJUcV8ISEq4Lou3/zmN/nGN77B5s2bGRkZoampiZUrV/L2t7+d3/iN36C1tXXWnu9LX/oSt9xyy1Ht8973vpd//dd/PabnkxBVCCHEvFWbioPU2hSkO0Gdn9VvUQQTFZf+qSpV16fJsdB1CZYA9No45sQLVHc/zTJ/F3b+JdTQPWg7N9VDvXl93GO1aR0Fp49HRyIe2O3x8IBPEIGmwPVrTN59mknGmr2wU/Gq6I0CbmYljdxqUGe/6nUxqbo+xbqHgkIuYdCZtcklTJKmdsImCBNCCCH2khBVzBdHGqLOz080s+CFF17gxhtvZOPGjQfcPzw8zPDwMD//+c/5m7/5G774xS9y3XXXzc1JCiGEEIuV0wRdZ8Ho81Aaie/TdNBM0CzQzXkRrCoKtKZMkpbGwFSNsXIDW9dI2XN/bnPNd1ppdF/CluAUgt4mNAKs4k7syRdmKlbNyhBmuR+z3E9m990AhJrFmtxa3tG8nj3d6/l0/2k8PBjy/a0ud+90ufk0izevMTG01x7aRUYCX1ExC9shCvCTnUSqTqQaRKoGij5vK6HnQsLUSZg6XhBSrHlsLhexdJWmpElb2iKXMGS4vxBCCCHEISzKq6T+/n6uuuoqBgcHAVAUhQ0bNrB69WrGxsa4++67qdVqjI6O8ta3vpU77riDK6+8clbPYf369Vx11VWH3e7iiy+e1ecVQggh5g0rBV1nxNWofh3qJWgUwW9AvQjR9JhvTd8XrGpzE646hsaq1hRZx6B/qsZ4qUEuYaLPQtC3aKg6jdwaGrk1FFa9Kb6rUcCeejHurToZ91fV/CqJiU0kJjbRDPxb0zruu+CD/M2LbWzPh3zhqQb/tdXjt8+yuHiZ/porICPdxk+0YhZ3YpT2xH8/qkqk6ESqRqRaRLpFqDlEWhywoujTYevSDFwNTaUlZQFx79SJsstwoYZtaDSnTNrTNlnHwDakslcIIYQQYq9FGaLedNNNMwHq8uXLue222zjzzDNnHh8fH+dd73oX99xzD57nccMNN7Bt2zZyudysncOFF17IZz/72Vk7nhBCCLEg6VY8nH+vKIpDVL8W//RqcbDaKMU9VGsFiMK4N6lqTAer1nS4enwDHVWFtrRF0tIZyNcYl6rUwwqtLNXO86l2nh/fEYWYpX7sqbhaNTXwIM7UFq4t/HfOW/urfHP1m/m3zSGD5ZA//1mNM9s13n+Wzdrm1/a7jTQTL70s/tuJApQwQAl9CH3UoIHS8CEKUaIIiACFCOVVAlebSDMOClxD3ZkXFdSzyTY0bEMjiiJqXsBoocHAVJ2kpdGSMmlNWeQcE3OJTb4mhBBCCPFyi+sqELj99tt58MEHATBNkx/84AecfvrpB2zT2trKbbfdxhlnnMH27duZnJzkf//v/81f//Vfz8UpCyGEEEuHooBhx8v+oiiuVvVq+0LW+t5wtQq1fByQAWhGHM7q0+HqLE8olDDjqtS0rTOYrzNebtDkmGhSlXp4ioqb6cPN9FFc/ktMrr+Rto2fIzXyOG1b/oP3ZR7ily75EF8a6uM/t7g8PRrwe3dWuGalwS1nWLQ6r/F3qaigqHF16eG2PWTgGsT3R1Ec5kfMBK6h7uAn2gnsJgIzs6gCVUVRZob7R1FExQ0YnKqzZ6JK0jZoT1k0p0yyjoGhSaAqhBBCiKVn8Vz5Tfvc5z43s/7rv/7rBwWoeyWTST7+8Y9z8803A/BP//RPfPzjH0fXF91bIoQQQsx/igKGEy/7C8M4XN27eNPhqlsCtwL+ZBzAwr6q1b1tAV5DuKqp0JmxSVo6g1M1JqsNkoaBY8nw5qPhO60MXfS/SA08QNsz/4RV3Mnah/4//r81b+X6a2/kXzZH3LvL584dHg/s9njnyRY3rDexT8TkXkcZuCphgOpXsfJbiVAJzVQcqFpNBFYmrpxeJBRFIWXppCydMIqoNHx2TlTYNVkhZRq0ZyyakyYZx0BT5csFIYQQQiwNiyoxLJfL3HPPPTO3b7nlllfd/h3veAcf+MAHKJfLTE5O8sADD8x6b1QhhBBCvAaqCmYiXvYXhge2BNi/LUCjDIEbh6t72wJo08GqZsTLEUpbOqvbU2RKBgP5GrVyQC5hokoh3pFTFMo9l1NrO4vWZ/+ZTP/9NL/0Xc4d+jm9Z3+It550Ml94qsFz4wFf2dTg9m0uv3mGxVUrDNT50qNUUYk0lUDLElhZCANUr4yV3wYKhHoaL9FKYDfHjy+iQFVVFNK2Qdo2CMKIcsPnpdEymqqQsnU6MxZNCYu0raNKoCqEEEKIRWxRhagPP/wwjUYDiCtNzz///Ffd3rZtXve613HXXXcBcO+990qIKoQQQiwEqgpmMl72FwbTVauNfdWrjVK8+G78M/TjbRV1X9WqZhyyelVXFbqyNilLp3+qykSlTtoysE2pSj0agZVl5Lz/Qbnncto2fg6zMkTPzz5CesUbOGXDb3DfsMO/bKwzUo3434/W+f5Wlw+cZXN6+zy8XFU1QitLuDdQ9StYhR1Q2EFopPASbYRWE4GVJdLMuT7bWaOpClnHIOsY+EFIqeHzwnAZQ6+QtQ06MjbZhEHaeu0ThgkhhBBCzDfz8Kr02D3//PMz66effvoRDc0/55xzZkLU/fd/rfL5PN/+9rfZvHkzhUKBTCZDd3c3r3vd6zj99NPlwlIIIYQ4HlTtlcPVKIqrU/cPWN1qXL3q1Q6sXoV9oep+P9O2zpqONMP5OsPFGlU3IGXrMuHOUap0XkDtqlNp3fxFsjvvILvzDhLDj/PGsz7I6375PL77oss3Njd4cTLkD++tclmPzvvOsulKzdP3WdUIzQyhmYEoQPUqWMWdEO0gNJL4Ttt0hWqGSLPm+mxnja6pNCVMmhLgBSGlus/moQKWppJLmLRnbHKOQdJaVB83hBBCCLGELaqrmi1btsysL1++/Ij26evrm1l/4YUXZu1cbrvtNm677bZXfGzt2rX8yZ/8Cb/5m78pYaoQQghxIijKvsmoXi7wIWgconrViwPW6epVQ1HptU2yqspoXWGy7lOsR6QsHduQytQjFRpJRs/6IKVlG2jf+A+YlSGWPfIXpHsu59dO/22uXZnmy882+PF2jwf7fR4ZLPPWk0xuOsUiZc7jayfl5YFqFbO0C4o7CfUEfmI6UDUzRLp9+OMtEIam0pw0AZO6F5CveoyWGli6SsbRaXJMknY8aVXC0GTYvxBCCCEWpEUVok5MTMysd3R0HNE+nZ2dM+uTk5Ozfk6vZOvWrfzWb/0W3//+97n11ltJJpOH30kIIYQQx4emx8tRVK9m1BpppUSnHjEeOIzXQ0p1j5Rl4Mgw/yNWazuD3a//B1pe+Dq5l75Ppv9+EqNP4Zzxfv7beRt4y1qTLzxV58mRgG+/4HLnDo/3nGbxy6sXwIRGikZopgnNNEQhqlfFKO3GLO6KA1WnhcBpITCziypQtQ1t5guFmhtQrPqMlVwATE3BMfWZlgAJUyNhSjW3EEIIIRaGRRWilsvlmXXHcV5ly332327//Y9VX18fN9xwA1dddRWnn346bW1tBEFAf38/99xzD5/5zGdmKl5/+MMfctNNN/G9730P9QhmqGg0GjM9XwGKxSIAnufhed5rPnchhBBCvJwKWiJeLGBvzhr4UJ/CKg6yrDxGk+IyFTiMN0KKdZeErpOw9HhiqwUsCKMDfh4XqsXIKbdQ6LqEzo3/gF3aSdcTf0N5z30oZ/wuf7WhhceHA/5lY4M9pZB/+EWd27a6vO9Mi/M6tQUyqkch0JOgJ2cCVbXYj1bYQ6jbBHYTvt1CaC2uQNXSwHI0QCOKItwgpO569Ffq7CJCQ8EyVFKWQdbRSVgGCVPF1qVaVQghloK9OYbkGWKuHenfoBJF0XG8Kj6xrrrqKu69914APvaxj/Hxj3/8sPvce++9XHXVVQBomobv+8f8/Pl8nkwm86qBqOu6fOADH+CLX/zizH1f/epXufnmmw97/D//8z/nL/7iLw66/+tf/zqJROIV9hBCCCGEWDiU0Gft6A9ZN3wbahTgqQ6bl72LXS2XE0QqD48q/HiPSsWPA7b12ZC3rAjplssgIYQQQghxjKrVKjfddNPMnEaHsqhC1F/+5V/m9ttvB+BP/uRP+NSnPnXYfX784x9z3XXXAZBKpSiVSsf1HAHCMOSKK67gwQcfBOC0007j2WefPex+r1SJ2tvby9DQEC0tLcftfIUQQghxBNwylMehOIBbzVPwNcYaDmU/xNR0kpbOEQw8mVeCMOKlgTxrluVO6PB5s7iLrqf/AWcq7ndfaTmd4TM/iJfqpuxGfOP5Brdt9fBDUBV4w0qD95xmkrMX2Bu8vyhC9WuoXgUl9AGFCCWeLE1RiRQVFJ1I1Ql1i0gziFSLSNVB0YhUjUg1QNFA1YkUNX5MXTgDz6IoouGHNLyAuh8S7q1WNTXSlk5TwsQ2NZKGhmWoC6QKWQghxKF4nsddd93FNddcg2EYc306YgkrFou0trYeNkRdOFdVRyCVSs2s12q1I9pn/+323/94UlWVP/uzP+Pqq68GYNOmTfT399PT0/Oq+1mWhWUdPCGGYRjyfzhCCCHEXDOaINkEzb0YlTGS+T20VSYoNkKGPYdCLUDXNFKWjq4trPBHU5UTGqIGuRX0b/jf5Lb9kJbnv0Jy4llW3vf7TJx8M9rqt/CBsx3evMbiX5+u82C/z+3bPe7d5XFFn8EbVhuc0rJQhvnvTwEtSWQlmalwiEKIApQwQN27HjXAraJEAUQhysvqISJFnQ5eNSJFJ1LVOGzVTELNBM2cvl8n1B1CIxVvP08kdEjs19HAD0Lqfki+HjBaqQAKtq7imBpNCZO0bZC24y8phBBCLEySaYi5dqR/f4vqamP/asyRkZEj2md4eHhmvbm5edbP6VA2bNiAYRgzfReef/75w4aoQgghhFgADBtyvZDuwqiO01IYIFsaoVRrMOrZTNVCVBTStoGuL7Sg7wRSNPJr3kK560I6Nv4DibGnadv876QHHmTk7D+gO7uC/3VpgmdGfb7wVJ2tUyF37PC4Y4dHX0blDasMrl5h0LSQq1MVNa5CVQ2OaOhYFE0Hq8FM+EroowYuSsOfDmFDiBRQIiLVINQdAruFwMoSGklCIxk/7zyhayopTSU1HZLurVateQE7x6uEUUjKNljfmaYldXCxgRBCCCHEbFlUIeq6detm1nft2nVE++zevXtmff369bN+TodiGAatra0MDQ0BMD4+fsKeWwghhBAngKZDuhNSHei1KZqKg2SKQ5TKRcY9i4laBIpCypbZyV+Nn+xk4OJPkNl9F63P/ht2fit99/0Bkye9k6mT3skZ7Qaf+6Ukm8YCfrzd44E9HruLIf+8scG/Pd3g4mU6b1hlcG6nfkKraeeEosQVqMSVpYcLXpXAQ/GrGKVdmMUwrlbVE9OTXGUIjRShnoiPO08oioJtaNjGvurZ8XKDTQMF1nVm6Mwunom5hBBCCDG/LKoQ9eSTT55Zf/bZZ/F9H11/9Zf45JNPvuL+J0KlUplZTyaTr7KlEEIIIRYsRYFEMySa0XJ95EojZIv9dBSnGG/ojDdsijWVlK0fEAyJ/SgKxeW/RKX9XNqf/jyp4Udo2fINUoMPMXr2h6g3r+f0dp3T23V+7xybn+72uGO7y5bJkAf7fR7s92lzFH5plcG1K026UhJaA3FfVS1LaGUBUIIGql/DKu5AiUJCzSLUk/hOC6GZITBTRJo9r0JVgNaUxVTVZfNQAS8I6WlyFmA7ByGEEELMd4sqRL344ouxLItGo0GlUuGJJ57goosuOuT2jUaDRx55ZOb2lVdeeSJOE4Dt27dTLBZnbnd3d5+w5xZCCCHEHLEzYGdQcj2kK2OkpnbRXphgoh4x5iYo1TVSpo5jaiAZ0EECp4WhC/+U1OBDtD3zBazSbnoe+B/kV7+ZiZPfTaTbJE2FN60xedMak+35uDr1np0eY7WI/9js8h+bXc7u0HjjKpNLenTMBdaf9niKNItAswgsIIr2har5l+LHdYvASMfD/80UoZEi0udH5WdTwqRU93hhuIjrh6xsTaIu9spjIYQQQpxQiypETaVSXHXVVdx+++0AfOlLX3rVEPW73/0upVIJiPuhbtiw4YScJ8C///u/z6xns1nOOuusE/bcQgghhJhjhgO5PpR0F8nKOMlCP635YfLVBmNegnHPREHBMVRsQ0eVwsl9FIXyskuptp1B27P/SmbPvTRtu410//00sqtxU914qR7c1DJOSnWz6uxW3nemxcMDPj/e5vLkSMBTIwFPjdRIm3DVcpM3rjZYlZMq4AMoCpFuE+g2AUyHqnVUr4Rei9tQRbqDb2YInOZ46L+RItLMOTvltG2gqQovjZXxgpDV7SkMTf7xCCGEEGJ2LKoQFeB3f/d3DwhRf//3f59TTz31oO2q1Sr/63/9r5nbv/3bv33Yof+vplwuk0qljmjbhx9+mL/927+duf2ud73rNT23EEIIIRYozYBMF6Q6SDRPkSgO0pwfoFYrUq77FGsKxapOoFiYlo1j6DIZ1bTQzDBy7h9S6tlA+8bPYdTG0Ed/QXL0Fwdup5p4qW76Ut28o6OHsWVd3Fdo59uDbbxUS/H9rS7f3+pyUrPKG1eZvL7PIGnKe3wQRSHSHQLdmQ5VQ1S/jtaYxKiOEDH9uJUlsONQNTCToJ7Y2ZYTpo6qKOycqOCHEWs7Uli6BORCCCGEeO2UKIqOaLLPhWTDhg08+OCDAKxYsYLbbruNM844Y+bxiYkJbrzxRu666y4grkLdtm0buVzuoGPt3LmTlStXztz+4he/yG/8xm8ctN2XvvQl/vEf/5EPfvCDvOUtbyGbzR60Tb1e55//+Z/58Ic/TK1WAyCXy/Hcc8/R1dV11K+zWCySzWYZHx+npaXlqPcXQgghxDzUKIFbAbeKV5miWpqiWqtQKleoeyEuKpqRwLBsLMvheJapBmHElj1TrOttmteTMilBA3vqRYzyAGZ5cPrnAEZlGCXyD7lfQ0+zm06ebXTyUtjFjqiLAaWL3p4erlqd4rQ2TXprHqkoQPVqqH4NJfSJFJVITxDoCdAMQs0E1SRStXjyK0UlUvV4fea+vev6a+676gUho6U6nRmbkzrTJEwpWBBCiPnG8zxuv/12rrvuOgzjxH7pJsT+9uZrhUKBTCZzyO0W5dXE17/+dS644AKGhobYuXMnZ511FpdffjmrV69mbGyMu+++m2q1CoCu63zrW996xQD1aD3++OP8+q//Orqus379etavX09TUxNBEDAwMMDPf/7zA/qgOo7DbbfddkwBqhBCCCEWKSsdL4DRAtkwIOtV6WhUqVRLVIqTlKYmqNXKlEoTqESYuo5pJ8CwiHQLlKVVeRdpFrXW06m1nn7gA2GAUR3ZF65WpsPV8gBGbRzLL7GWEmu1rbD/WzYCA8MtDKldRNke2jp70FtWUGs5DdRFefn82ikaoZkiNKdHZoU+ql9D8woojQCiECUKiJv9KkAIKEQooKigaqCocZCqqKDohJoBmkmoxj/jkFWf3m5fABupBpFmHRC8GppKZ8ZhuFjDCyPWdabJ2PIBXQghhBDHblFeBfb09HDvvfdy4403snHjRqIo4r777uO+++47YLu2tja++MUvctVVV83q8/u+z6ZNm9i0adMht7ngggv40pe+xMknnzyrzy2EEEKIRUbVwEqjWmnSmQ7SndAZhtSqZcqVEoVCkWJhknIlj1Ir4uBj6WDoOqFmEmnWdBXgEgyQVA0v1Y2X6qb6socUv45RGTywcrU8gFbsxwwqLFMmWBZNQH4T5ON9imqWZ9OXsa3tSoLcSppthSZbJWcrONJm4UCqTmimD79dFO4LWKMQJQohClDCOppf2Xf7FQbPRYoSf2Gg6oRGEt9uITQShHqS0EigqSpdWYfRUp3nBoqs60zTlJy7nq1CCCGEWNgWZYgKsH79eh599FFuvfVWvvGNb7B582ZGRkbI5XKsWrWKt7/97dxyyy20trbOyvPdeOONnHTSSTz88MM88sgjbNu2jfHxcSYmJgjDkGw2y8qVK7nooov4lV/5FS699NJZeV4hhBBCLEGqipPK4KQytHUswwtCSjWPUrnERKFIoVIirJdxvBJJv4FNGYUQgFCLq/biZekGSpFu42ZX4WZXveyBCNUtEuUH2LFnN5Mj/WTqA5yvbqE1LHBJ4YdcUvghm8PlfCfYwG3BxUyQxdGhyVbI2ep0uBoHrE0z6/tu2xK47qOocWXp9MeSo+oztjdgDTxUr4xVGwcUIs0k1B0Cq4nAytBlOozWAp4dCFnfmaY9Yx+PVyKEEEKIRW5R9kRdKqQnqhBCCCFeLgwjyq5Pqe4zXmpQLFdwa2WMqE4Sj2RUxgyqKEEDJXBBVQk1i1B3DhoSvVB6oh5vuwoBm0YatE7+glPz93F6/Qn0eHolvEjjvvBMvhNs4N7wbFwOX/Gb0DkgbM3ZCs37Ba4rshrdaZlV/phEEUroovp1FL+GEoVEik6kO0yGCVwzw8ruDjpbm1EMZ67PVgghljTpiSrmiyXdE1UIIYQQYqlSVYWMbZCxDZblHOpemmLdI1/xGC83mHIDAt8lqXpkVBcrrKDXJtG8Ckp9CogIdZtQs0G15vrlzAvLsxrLswngMuAydrlF0v0PkNl9D3Z+K9doT3KN9iSunualpkt5Mn0Fz7OKfAMm6xFT9YipWshUI8INoOpDtRwyWD70c3YmFc7p0DmnU+esDo2sJaHqEVEUIs0i0Cywpid6DT1Uv05LNEEtP8jI5PPQ0kRHaytqshWsFJhJMBKveUIrIYQQQixeUom6gEklqhBCCCGOhh+ElOo+xbrHaKlBse7h+REJQyWjeVhhFdWroNXjUDX0amyatDi1NUQxbELdiXu0ihlmcTfpPfeS2XMven1y5v5GupdS71UUe68gcOL2UVEUUfWJA9V6xFQjYrIWka+HM2HrRC1kRyHED/c9hwKsaVI5u0Pn3E6dU1s1LGkJcMzqDZdatcyylEJHQkHXVNBMMJKQbI0ndjOT8SJ/70IIcdxIJaqYL460ElVC1AVMQlQhhBBCHKswjCjVfaaqDYaLDcp1nyAKSZoGKUtHDxtE9SLbtzzHup4cpldCCaaHR6s6oe4Q6vbSnLDqlUQBidGNZPbcS3Lw56ihG9+NSrX9TEq9V1HuuohIP3w/zpoX8cyYz1MjAU8O++wohAc8bqhwWps2U6m6Oqcu6XYLx8L1Qwo1l86MTW9TAiNqgFcDvx73WtVMMBxwmsHOToeqKdCXbh9hIYSYbRKiivlCQtQlQEJUIYQQQsyGIIwo1jwmKy5jpQalhkcYQUKDyS2PsuKsS9EIUb0qqldGa+TRGsU4VA09IkUlmg5VI01aAKhehdTAz8jsuQdn4rmZ+wM9QXnZpRT7rqLefMoRDx2frIVxoDri8+Swz3jtwMv3tKlwVofGudOhaldKhv4fCd+PmKo1aE3ZLG9JYOn7vW9+Iw5UvRqEASgaGHYcpjrN08P/nfinJh/8hRDiWEiIKuYLCVGXAAlRhRBCCDHb/CCkMB2oDucrTL7wKM6qc0k7DglLQ90b/IU+qldB9atojSJafRI1qKEEXvywbr/iZFVLjVEZIr07Hu5vVEdm7neTXZR6r6TYeyV+suOIjxdFEXtKIU8OBzw14rNx1KfqHbhNZ1Lh3E6dszt0zu7QyEg/1UMKgojJqktTwmB5S5KEeYjh+6E/HarW44CVKK7C1u14+L/TBGYi7qtqJECTqSeEEOJwJEQV84WEqEuAhKhCCCGEOJ4qtQZ333kHa869jKlaQMUN0BSFlKWTMDWU/cPRaF+lquqV0WuTqEEVxa8R6g6BmQF1CQdLUYgzsZnM7ntIDT6E6tdmHqq2nEax72rK3RcTGYmjOmwQRmyZDHhyOK5UfW48INjv6n5vP9VzOnXO6ZB+qq8kDGGy2iBl6axoSZK2j/DvNPDiYNWvgx+3b0DbG6xmwMntq1g1EtJfVQghXkZCVDFfSIi6BEiIKoQQQojjaf8PNwEqxZrHWKnBRMWl5vnoqkraMnBeqXovilD8Gnp9EqM8iOZOEaEQWLkj6gu6mCl+ndTgw/Fw/7FnUIgvx0PNotx9MaVlG6i1nkakO0d97L39VPeGqjtf1k/V1OC0Vo3zunQu7zVoT0qVKgARTFZcTENlRUuSpsQxfpgP3Olq1XocsgLoVrzYubi/qpGIq1Z1B1R5/4UQS5eEqGK+ONIQdQmXAwghhBBCiCNlGxq2odGesam5Afmay2ixQb7qMlVzMTWVlKVjG9OBqqIQGQk8I4GX7EKvT6JXR9BrYyi1SQIrRWikQFl6IVKk25T6rqTUdyV6dZT0nvvI7LkHszxAZs9Pyez5KZGiU2teT7X9HKrtZ9PIrYr7ch6GYyhc2G1wYXf8YXSiFvLUyL5QdaIW8eRIwJMjAf+8scFprRqvX26woVcnZy+938UMBZpTJoWqx7axMstbErSljqG/r2bGC9MfwKIoDlb9OpQGIb87vl+34opVpwnszL42AIazpNtfCCGEEPOZVKIuYFKJKoQQQojj6UgqRCoNn3zNY7RYp1D1qPsBtq6Rtg1M/eBQTnWL6LVxjPIQqlsi1E0CKxv3l1zKogh7agvpPT8lOfLEAf1TAQIjTbX9LKptZ1FtPxs/0X4MTxGxuxjy5IjPQ/0+z4wG7P0goCpwTofGlcsNLu4xSBpLN8gr133cIKSvOUFnxp79TDOKIGjsV7HqxxWpugVWFjLdkGiJJ7ISQohFTCpRxXwhlahCCCGEEOK4S1o6SUunO2tTbvjkqx4jxTr5uovnRyRMjbSlo2txoBqaGVwzg5dahjY91F+vTaAAgZkhPMqeoIuGolBvXk+9eT1jxBNSJUafIjH6FM7Y02heifTAg6QHHgTATfXMBKrV1tOPqJeqoigsz2osz2q87SSL8WrIfbs9frrb48XJkCeGA54YDjCfqHNhl87rlxtc2K1jaksrUE3ZOrVGwM6JCn4Q0p1LoM1mka6ixFWo+7e1iMI4UK1NQnkYzBSkuyDVHrcBkGH/QgghxJyTEFUIIYQQQrxmiqKQtg3StsGynEOp4ZOvugwV6oxXXKIoIm0bJKcnpIo0Cz/ZhZ/oQGvk0SsjGLURtEae0EgQmOkjGr6+WHnJLgoruyisvA7CAHvqRRJjcahqT23BLPdjlvvJ7fghkaJRb15Ppf1sqm1n02hac0TvXWtC5VfWW/zKeov+UsBPd/n8dLfHnmLIg/0+D/b7JAy4ZJnB65cbnNOhoalLI1B1LA1FhT1TNfwwpKc5iXE8X7ui7hvSH0XQKMHESzC5AxJNkFkWV6eaS/RLBiGEEGIekOH8C5gM5xdCCCHE8TQbw+yCMCJfdRkvNxgtNai6Poaqkbb36586TfUqaNVxjMoAmlsiUjUCK0ukHUNvykVM9So4Y8/MhKpmZeiAxwMjRbXtjLifattZ+MnOIz52FEVsy4f8dFdcoTpW3fdRIWcpbOjTeX2fwSmtGuoS6N3p+SH5mktb2mZZzsHWtRNbFBq4UC+A14irU1PtkO6Ie6mqS/dLBiHE4iDD+cV8IcP5hRBCCCHEnNNUhZaURUvKYnlLwFQ1npBqstJgotwgaemkbQNNVQiNJGE2iZfuRq9NoFeG0esTKKE3PdQ/KZPuAKGRpNL9OirdrwNArwzHQ//HniIx9jSaVyY9+DDpwYcBcJNdM4Fqre2M+H08BEVRWNOksaZJ471nWjw3HnDvLo8H9vjkGxH/tdXjv7Z6dCQUrlhu8Po+g1U5FWWR/l4MXaUpYTFWinv+mppKwtJIWjqWoWLqKpauHb8qVc2EZFtcneqWYWoH5HfFIWqmG5KtYB769ymEEEKI2SOVqAuYVKIKIYQQ4ng6XhUiURRRavhMVeLh/qW6B0DK2jfcf3pDtEYBrTaKURlG9auEuk1gZqUK71DCACv/EsnRJ0mMPYU9uQUlCmYejhSVetO6mUC13rSOSDMPe1g/jHhqJOCnuzwe6veo+vse68uoXDkdqHanF2nvzgjcIMTzQ7wgwg9DUOIvCQxNxTE0kqaOY2pYehyumpp6fDL/wINGEdxqHKCmOuLFaQJNamSEEAuHVKKK+eJIK1ElRF3AJEQVQgghxPF0Ij7c+EFIvuYxXmowVm5QafhYejzc39L3BaWKX0OvTWCUB9EaU0SKQmDliHSZwfzVqF4VZ/xZEqNPkhjbiFkeOODxUDWoN6+n1nIatdbTqTevP2yo2vAjHh3y+ekuj0cHfbxw32PrmuNAdUOfQauzSAPV/fhBhBeEuH6IH4ZEgIqCoauYukLK0kmYOqamYhkqljbL7QDcCtSLQAR2Nu6dmmwFKz2LTyKEEMeHhKhivpAQdQmQEFUIIYQQx9OJ/nBT9wImKy4jxTpTVRfXj0ia2sxwfwBCH70+hV4dQa+NofgNAitFaKTiyXnEq9Kro3GgOv4sztgz6I2pAx4PVYN60zpqracfUahacSMeGvC4d5fHUyMB4fQnCwU4o13j1FaNVTmNlTmVZSl1SUxMFYbgBgFeEOH5IUEUoihxxaqpHtgOIK5anYV2AKEfh6leFXQbku2Q7oREM2gSTAgh5icJUcV8ISHqEiAhqhBCCCGOp7n6cBNFEcW6z1SlwXCxQbHmoSp7q/qmh/tHEapXQq+NY5SHUL1yvLMCkaIRKSrs/1PVQFGJFC2euX6R9vA8KlGEURmMK1XHn8UZfxa9PnnAJkcTqk7VQx7Y43PvLo/nxoODHjdUWJFVWZnTWJVTWZmNw9UmewmE3y9vBxAFgDLTDiBh6CStuBWAqiqoioKuKigqaEq83d77DsurxpNRRRFYmenq1JZ4Xf7uhRDziISoYr6QiaWEEEIIIcSCpCgKWccg6xj0NCWYqnqMleuMl1wKBXd6uL+BaWZwzQxeahlafQoldFECf/qnixq6ELgoUYjq+xAFEAb79QiNIFJAiabD1umQVd0/hNUOuH9RURS81DK81DKKK95wyFA1MbGJxMQm2PINQlWn3rR+v1B1HZFmAdBkq7xlrclb1pqMVEIeGfTZPhWwvRCysxBQ92HrVMjWqfCA02iyFVbuF66uymn0ZVRMbREFfgpxn1R9b2AchwV72wGU6h6T1QYQ17dEEaiKiqrG7QHiYDXuwaqrCrqmYmgKhqqiacpM0KooCrpqolptqFGI5pXRhp9FM5x4mH+6K+6dqlsSqAohhBBHSUJUIYQQQggxb+maSlvaoi1tUWsJmKq6DBdrTFVdPD8kZRmkLJMo2fnKB4giiAKU0I/D0yhACePbRNOBauijhB5q0IDQQ/VdiHyUwEfFnQlf1TAgMBMERnrxBaowq6FqRzIOVPcKo4jhcsT2QsCOfMiOfByuDpZCpuoRU/WAJ0f2Va+qCvSk1QMqVlflNNoTyr6JxxYBXVPQNQ3HPPjvKYogCCOiKCKIIqJwOnT1I4IoIAojAiL2Bq8xBZW4glVVFDRFRVEy6GEDa3QbRvQiViJNMpUhmW1Bs1OgO2DY8U+ZmEoIIYQ4JPmvpBBCCCGEWBAcU8MxHbqyNsWaz2SlwXChwUipjqYopO14Ep8DKAooOpGqc1Q9rKLwgMBVCX3URgGjMohRHY0ntjIzREZiNl/i/PIqoereYPXQoepp1FpPw82sIDCzqIpCd1qhO61yac++p6j5EbsK+0LVHfmA7fmQkhuxuxiyuxhyH/7M9gkDVk2HqnsrV9c1a0c2zH2BUZQ4ZAWFoxnkujd8DaN4iULwFAtXswjCgKhUQcuPkhwepNnRSJo6juOgGjaYSbBzYDj7Ft2WqlUhhBACCVGFEEIIIcQCoygK2YRBNmHQ05wgX/UYK9UZKzXIVz1sQyNj6+jaa+i1uXd4v2rMhK+BncNLd6PX8/HEVvVxlPoUoZEgMNOgLvJL66MOVePdAiOJl1qGO73sXfeS3Ti6zfoWjfUt+yoxoyhioh6xIx+yPT9duVoI2F0MqXqwaTxg03gAeAC0JRR+ZZ3JG1ebOLqEffuHrwfTAQs/iKh6AZONAN2DdCOi2WmQ1qs4paF4T0WLh/3rFlhZsNMHVq3qh55wTAghhFiMFvmVnhBCCCGEWMyM/Yb7Vxo+kxWXoUKN8YoLRKQtY99kVLNBNfATbfiJNlSvglafxCgPodfGUYDATBPqiaVRuXeYUNWZfAG9OormVdCmXsSeevGgQ3hOG16qGzfVM/PTTS2jNdFGa5fO+V37Pq54QUR/KWT7dKi6PR+yZSJgrBrx+acafG2zy9tOMnnLWoOMtQQmq3oNdE0hremkbR3fj6i4PlPFAEM1SdtJmpMmaUPB0XzwXSgNQH66IljV42DVcOKqVetlLQFUee+FEEIsThKiCiGEEEKIRSFp6SQtne6cQ77qMlZqMFpqkC+42LpGxjEwXkt16suERpLQSOIlu9EaefTqKEZtDK0xSKjZBFYG1CU02/DLQ1VACRoY5SHM8gBGeWD6Zz9meQDNK2PUxjBqYyTGnj7gUKGq4yW7DwpY16SWsTKbASV+X90g4q4dHt96ocFgOeIrmxp86/kG1602ecc6k/akBHqHo+sKWd0ADFw/pFSPW2VY0/9mmhIJUlYG25h+LwMPgga4ZahOxP0DFECbrlo10+BkIdEK9qFnOBZCCCEWGglRhRBCCCHEoqKpCi0pi5aUxfKWgMmqy1C+xmTFJYgiMpZB0prN6lSNwGkhcFpw/RXo9UmMyhB6bRIlCuPqVCO5NKpTXybSLNzsCtzsioMeU90iZmlvuNqPWR7EqAxglAdRQw+rtBurtPug/QIjeUCw+s50H9dfvoJ7J1u49XmXbfmQ777o8l8vuVy13OCdJ5v0ZRbhRGDHgamrmLoKGDS8kKmKy3i5jqXr5BydXMIkZeuYZgrM1L4doxACF/wGVEahsCcOU9vWQrpbqlOFEEIsChKiCiGEEEKIRcsxNZaZDl0Zm0LNm65OrTNUdDE1jYxtTIdGsyPSnbgaM9mF1iig1cYwKiMY5SEi3Ywno9KklyRAaGaot2Sot5x84ANRgF4dxyz3Y5QHD6hi1WtjaF4FZ2oLztSWA3ZboSf4tcwK+rMruLPQw12FHu7f0cudOywu7tF518nWAb1XxauzDBXLMCGCuhcwWnIZKdaxDZ1cwpgJVA1ViXsI63a87FWbgsGN0JSHltXx8H8hhBBiAZMQVQghhBBCLHqqqtCUNGlKmvS1JJisxIHQRMUlCENSpkHK1lFnq1pUUQnsJgK7CS/dh9aYwqgMo9UnUUKfwEwSGqk4fBIHUjT8ZAd+sgM6zj3woYPaA+zBLO7CKu5G86skJp/jJJ7jJOCDFoQo7Ag7eX5kOc8N9bExs5LT163llL52FKmOPDIK2KaGbWpEEdTdgJFineFinYSh0Zw0yTgmSUtDV/f79+M0gZGAye1xoNq2DlLtc/c6hBBCiNdIQlQhhBBCCLGk2IZGd86hM2NTrHuMlxsMFxsMFeqYmkrG0bH02atYjHQbX+/CT3SiugX02gRGZRijMkKkanF16v4VfOKQDtkeIPQxS/1YxR1YhR2YhR1YxR3ojTyr1SFWM8SbtEegBmyE4sYU5dQK7PZVeNmVNLIrcdN9UiV8GIoCjqXhWBphCDXXpz9fQ8nXSVoazQmTjGOQNPV4BL9uQbYHKmMw8AtoXg1NK0CX91kIIcTCIyGqEEIIIYRYklRVIZcwySVMepsTTFW86erUBq7fIGUZpCwdTZ2t6lSF0MrhWjm8dA9afQq9MozemESpTRKaSQIzBYoMOT9qqj4TrpZ6Xz9zt1afwipsxyruIJrYgT+xnTZ3gIxSJlPeBOVNM9tGioqb6okD1exKGpmVNLKrCOymuXhF856qQtLWSaITBBE1L2DXZAVNVUlZOq2p+N+WpatxBapbhbEXoJ6H1rVxpaoQQgixgEiIKoQQQgghljxL1+jManRkLIp1n4lyg+FCnZFiDV1VyThx79TZGu4faRZ+shM/0YHqldBrk+iVQYzKKJGiEtg5Is2aledaygK7iap9LtWOc2FtfN9gtc6jz21naPc2VoS7OVnZxSnabnJRed9kVv33zxzDt3I0squodF5AedmlBFZubl7MPKZpCilNJ2Xr+EFE1Q3YNlbGMXXaUxZNSZOEmYgrUMtj0ChCy9q4SlWVLw2EEEIsDBKiCiGEEEIIMU1RFLKOQdYx6GlKkK+6DBfrTJZd8tWI+H9AFKEoChABcbAazaxHECnszVsV4nUlvoGqKOyNYlVFAcVGMbpRs+0YjTxWfYREbRyDCN/KEBmJE/smLHKZhM01551C7cyT+fF2lz94wWWsFtLJJGcbu3lraz/nWXtIl3dilAfQG3n00SdJjj5J27P/TLXtLEo9l1Ppeh2h/G4OomsKGUeHSKfS8Nk1WWG4WKc5adKaskilu1AaBRh+Bmr5eNIpKzXXpy2EEEIcloSoQgghhBBCvAJTV2nP2LSlLSpugB+EhBFEURyXhlEEEfF9RERRfF8UxfvvXQ/CiDCKl33rEIYQEhKG8TYRJoHWTslpJV+ZQC8PkSiMYSjjqE4O3ckwW/NeCXAMhbevs7h+jcm9uzy++UIbPy628OOhszE1eMMqg3eeD33hbpzxzaQHHsTObyU5HaiG6ueodJ5HqecKqh3nST/Vl1Omh/vbOnUvYLhQZ6zcoClh0ppKkEk4aPnd08P7T4J0J/IHLoQQYj6TEFUIIYQQQohXoSgKKevEXDZHUYQfRlTdHDV3BdXiBOWJQYL8HhrlnXhaEsXKYhoqpq6haxI6vVaGpnDtKpNrVhr8fMDn1ucavDAZ8l9bPX74Ery+r49fPXkNK9e+HaM8QLr/AdL992OW+0kPPkx68GECPUGl+2JKPRuotp4pQ9RfxjY0bEPD9UMmyi4T5QZZx6At1UbWL2EMPgXNK6F5VTwZlRBCCDEPSYgqhBBCCCHEPKEoCoamkHVUso4B2WVEPd3UK+uoTw3iTeyiVh6j3DAp+yn8SAEUTE3D1OOfqjrXr2JhUhWFS3oMLl6m8/RowK3PN/jFcMA9uzzu2eXRnVI4va2Z09rewRkXvJMV4U7S/feTHngQozZGZvfdZHbfjW/lKHdfSqnncurN66W6cj+mrtKSMvGDiHLDJ18rk7IM2h2dppEXMWv5uCo12TLXpyqEEEIcREJUIYQQQggh5jFFUXBSGZxUBjpXQGUUf3IXbnmCRqRTVjKU3Ii6H1JpuIRRiK6oGLqKrWvouoR4R0NRFM7q0DmrQ2frZMA3n2/wYL/PYDlisOzxkx0eAM12O2e0v4vTVt7EBvNF1uYfJD34EHojT27HD8nt+CFeooPSssso9VyBm10xty9sHtE1hVzCIAyh4vpsmwpw9BQd1WFypTyJrnWQ6wNNPq4KIYSYP+S/SkIIIYQQQiwUhg25PvR0F3pljER+N03VCbBUGkaOeqRT93wqDZ9yPaDsevj1uEmroapYetwGQKpVj8zaZo3/eUmCihuxedzn2bGAZ8cCtkwGTNYj7tvtc99u+CwrSJsrOKPl3VzftplL3IfonnwUozpC89b/pHnrf9JI91HquZxSz+X4yc65fmnzgqpC2tZJWzpV12enm8Zp1GgtPk62Y4z0svUodnauT1MIIYQAJEQVQgghhBBi4dEMyHRDqgMq41DoxyqPYhGSdZogkyIIoeEH1P2AWiOg2PCouyHVqktAiKlqJC1d+qoegaSpcEG3wQXdBgANP+KFyYBnRwOeHfN5biKg5MJDQ/AQpwKnktN+nZsyT/Mm9eesq/4Cq7Qb6/mv0vr8V6k1raPUcznlZZcR2E1z++LmAwUSlk7C0ql7OgM1g4ntL5EaG6Wp91RyncvRNOkzK4QQYm5JiCqEEEIIIcRCpWqQ7oBUO1QnoTgIpSGoTqI5WRJmioSpQQKW4eAGIQ0vpOr6TJRdinWPMIxwDI2EpUv7ziNk6Qpntuuc2a4DFn4YsW0q5Jkxn03T1ap51+Ifpy7gH7mADBXeqD/Or5o/56xwM87UFpypLbQ9+6/U2k6PA9WuiwnN1Fy/tDkXT0KVxPMdCsVxSpsfZnhkiOblJ9OSzWHqUkYthBBibkiIKoQQQgghxEKnKPFkPMkWyPXGQWpxEKr9YKfByoCiYGoqpqaStnXaUjYV1ydfdZmouExUGmiKQtLSJag6SrqqsK5FY12Lxg3rIYwidhfDmUrVZ8dSfLN2Bd/0r6CNPNdpj/IW7SHOUV8iMfY0ibGnadv4j1S6LqS4/Bqq7WeDsrQrLw1dxWhuJ3TruBPb2V2YZLBtLW1dvbSlbRxzab8/QgghTjwJUYUQQgghhFhMnFy8ZHuhNAyFPVDoBysFdhaUOCCd6Udp63RkbUr1uDq1UHMp1EIcQydh6tI/9RioisKKrMaKrMb1a02iKGK4Ek0Hqm3cPfZGvly6ll5lhOvVn/Nm7eesV/eQHnyI9OBDlPRmBjteT7T2GrRcz1y/nDmlmjZ2ax+J6iS1safZWZxgd8tKOpvStKVs0raOqkoJtRBCiONPQlQhhBBCCCEWIysF1hrILoPyKOR3Q2EwnpzKyYG676OAqam0JE2aEyZVz6dY8xkvN5iqNlBQSFgatq6BZFXHRFEUulIKXSmTX1oZ3zdZC3l2zOHZsR5+d+zt2IXt3KDdz1u0h2j2J1k38B0Y+A7PKuvYmL2SUvelrG5PsTyjoi210FBRCZOtOGaVvvoeSpNVdlX62JXIkbUNOjI2uYRBytJRpCeFEEKI40RCVCGEEEIIIRYzw4Gm5ZDugsoo5PfEoSoR6Hb8uG6DosZdAUydpKnTlrYo1X2mqg2mqh7lho+hqjIZ1SxpdlQu71O5vC+erKrins6LU6fw+bFbSA4/xrnle7k4eprT2cLp+S1Upv6d25+5kE9wOYXcqaxv1VnXrHFyi0ZbQlkS4WFoJAg1i1RtjJRbo6L1MOXl2FxxsDWNbMKgPWOTcwySlnzUFUIIMbvkvyxCCCGEEEIsBboJ2R5IdUJtEholqIyBW4Hq1L5tjAToNrqq0ZQwaEoY1LyAUt1nvNSgWPMIo4iEqeGYMhnVbEmaCmd36JzdkYLTrgSu5KnJMdh2D8tH76XNG+QG/QFu4AF2Fjv49tTl/FtwGUO00GQrrGvWWN8SLyc1a6TNRfqLUTX8ZCeqWyJdfJGk4eAlOilrbeQrSUaKdRxDoylp0p6OK1RtQ/qnCiGEeO0kRBVCCCGEEGIp0XRItcdL8yrwanGQ6pahMg6NMtTzEEWgmWA4OIaDk7ZoTVqUGz6Fmst4xWW83EBXZTKq4yXb3AbN7yIf/Sr1yRdI77qT1MCDrGCE/6F+iz8yvs3PwtP5lns5dw2eyyOD5sy+PWn1gGB1VU7FXEQVxKGZxjXTqF4Vs7iLJnWAtN2Cn+qmqGYZKzUYKtRwDJ3WlElryiKbMLB0CVSFEEIcGwlRhRBCCCGEWKoUBcxEvNAGzSvBq+8LVasTUC9CeQyiAFXVyRgJMlmHjqxNseYzWZmejKoa4pgyGdVxoSjUW06m3nIy42e8n9TgQ2R23UViYhMb1GfYYD5DTU3xsHUJX3M38NPKCvpLIf2lkHt2eQDoKqzOqVzaY3DtKoMme3H8kkIjQWgkUIIGen0cozqCaTWRTffgJZupBCoD+Tp7JqskbYO2lElLyiLrGBja4ngPhBBCnBgSogohhBBCCCH2Mex4SbbEvVR9Nw5U3QrUpuKlOoEZ+rQqGi0Zh0rapugqTFRcJqsN1L2TUckw6lkX6Talvqso9V2FURkivetuMnvuxamNcVXtJ1zFT6i2reC5piu5W7uUJ/MpXpgIKLoRWyZDtkw2+PKmBpf26LxptckZ7dqi6KcaaRZ+oh1CH61RwB57BtNMY6aWkU604esJqo2A3ZNVdk1USVk67RmL5mQcqC65ybqEEEIcNQlRhRBCCCGEEIemm6A3Q6IZcr0Q+PuFqnmU2iQpr0xKcWlPKpQdg6mGyqQL5boHCiio6KqCpioY2vT6IhpaPle8ZBeTp7ybyZNvIjH2NJldd5Mc+jmJ0k7OK/075ypfodJ5AYXXXcW25DlsHIv48XaP5ycC7tvtc99un960ypvWGFyz0lwcfVRVncBpIYhCVLeEPfk8YWkXXqIDI9FJKp0liKDc8Nk2WmGnWiVl63SkLZqSJhnbQJVAVQghxCuQEFUIIYQQQghx5DQdnFy8ZJdBGEwP/6+g1wvkqhPkrCpd9TINL8RTTeqRSTUyqfsRjSCg4kaEYQiKgoKCrk4vmoqhqdIO4GgpGtX2c6i2n4Pqlkn3309m993Y+a2khh4mNfQwHVYTp/VdydvPPJstUS/f3Z3gnl0ee0ohn3+qwb890+CKPoM3rTFY37wIqlMVldDK4lpZVK+CWdyFUR7Ad9rwk11odjNZx8EPQsoNny0jJXRNJesYdGZssgmDtKUv/PdBCCHErJEQVQghhBBCCHHsVA3sTLxkuiAMwatiuxVstwyVsThk9UqEUYSnGLiqha8kcENw/ZCaF1J3g+mA1SeMIoADAlZDV9FVCVgPJzRTFFb9MoVVv4xZ2Elm912k99yH3piieet3aN76HXqAy60mqp0r2MJy7ios4/5yLz/d0c2dOzxW51TetMbkyuUGCWPhh4ihkSQ0knHf1OoIRmWIwGrCS/egOC3kEha5hIkXhJTrPpsHC5i6Si5h0J626cjY0j9VCCGEhKhCCCGEEEKIWaSqYKXihQ5oXgV+PFmV6paxqpNY9QJ4eYgCMDRIOISag6fouEGIF4R4fojrh1TdkIYXUPcC/MAnJIIIFGU6XNXiClYJWA/mZlcwfvr7GD/1N0gOP0564EGs/DaMyhB6Y4pMY4rzeYrzgY9a4KOxNerhuUovzz+1nM883Udbz2quOKmN1U0Lv79tpFn4yY4D+qaGZgYv1Y2faMMwkjQlTZowafgBxarPWLHAaLHBqrYkuYQ51y9BCCHEHJIQVQghhBBCCHH8KAoYTrwkW6FpxYGTVdULUJtEbeSxAhdLUUG3wXFAd0BR4uLWMA5V9/50/ZDaKwWs7Ktg1VQFXVPQ1bgPKwu/qPLYqAaV7oupdF8MgOLXMYu7sIo7sAo7sIo7MAs70f0qJyu7OFnbBdrP4n2HYGwwy259OWrzSlqXrSZsWomb7gHVmMMX9Rrs1zdVO6Bvahdesp3QzGLpGlZKIwgjxssNinWPla1JluUcdKlKFUKIJUlCVCGEEEIIIcSJtf9kVfQe0FeVRhEqE/F6dRIAVbewDAfLtEE9sBowCMEPQ9wgxA8ivCCk4YXUpsNVL4ioeR5BGO17ekWdDlfjgFXTFJZS68tIt2k0r6PRvG6/OyP06ihWcSfmdLjK5A6S9SHalAJtwTMw9gyMxZuHio6X7qGRXUkjsxI3u5JGZgWB3TQ3L+pYKCqBlSWY6Zu6HaO8Z6Zvqm83o6kaHRmbUt3j+aEi+arHyrYkGXuBBshCCCGOmYSoQgghhBBCiLm1f19VuqA1Aq86HaqWoToe/6wXIIpAM2aqWzVVR1NVLP3g6sAoiitY4/YAUVzFujdg9QM8P6Lue/h7A9YINGVvewAFbbqKdUm0CVAU/GQHfrKDSteF++726zTGd7Jj+0vUxrbTF+zmZGU3GapYxZ1YxZ3AT2e2960cjdxaCsuvodJ5Yfy7XQBm+qb69bhvanWIwGrGSy3DS7STtg0cQ2O4WKdY91jVlqIrY6OqSyh9F0KIJU5CVCGEEEIIIcT8oihgJuMl1Q4tq8CrT1erlqE2FQeqlfG4ihXiYFW34kUzQVHjw2gqpqbCK7Sz9MII3w/xgmimTUDdC6i5AW4QB67BTJuACF3VMDUFU9fQtaURnkW6jdm5nnWd6wmjiF8MB/zd1gZ7hoZZp8SB6hn6bs4299DqDaE38ugjj5MceRzPaSe/6pcpLr+W0EzN9Us5IpFu4+v2TN9UZ/wZdKcNN7Mc7Ba6sw6Fmsem/jxTTQlWtiZJWvKxWgghlgL5f3shhBBCCCHE/GfY8ZJsgablEHhxqOpVwatBvQhuKa5YDdy4DFVR4nBV2z9c3Rd+GqqCYWo4r/B0QUhcwTq9NPyQcsOn2vApNzy8IIrbvaoqpq5iaOqiD1ZVReH8Lp3zu3RGKyv58fZlfH3beXy2HkEDHBq8tW2IG5O/4JTJOzFqo7Rt/iItL3ydUu/rya96M26mb65fxpHZ2zc1DNDrEzijk3FVarqPrJMiYWr0T1Up1DxWt6XoyFgoS6knhBBCLEESogohhBBCCCEWHs0AJxcve4Uh+DXwG3Gw6tXiilW3DI1SfD9Mh6vmvmD1ZeEqgKaCpqrYxoFj+f0wouEHNLy4arXcCKi4PvWGRxCGgIKp7atYXaytANqTKr9+us2vnWrxyKDPD19y+cWwxTfGVvCNsRV0WG/mvzU/wi+7PyZT2Ul25x1kd95Bte0s8quup9J5PigL4M1RNfxEezwZV2kPRm2cRno5SqqL7qxDvurx7ECeqarDytYUtrEw2hcIIYQ4ehKiCiGEEEIIIRYHVd3XBmB/YRAHqn4jDlndahyuetW4gjVw4+0UNZ70av+A9WV0VUE3dZL7PeSFEXUvwPVDam5AqeFRd0OqVZeQCAUFU1Mx9DhgXUzBqq4qXNpjcGmPwWAp5EfbXO7a6TFSN/jI0GV8hEu5PrmF37F/wsmVx0mMbSQxthE32UVh5ZsoLr+a0Ege/onmWKTbeKkuVLeEPfUcQXUEN7ucpkQbjUBj13iVQs1nVVuStpRUpQohxGIkIaoQQgghhBBicVM1sFLxsr/Aj0NVrw7+dM/Vej6+XcvHLQMgDmeNBFiZgypWYbotgKWDBSQBHNwgjKtV/YC6G1Cq+9T9kGrDJYwiFEXBmm4DYOrqKx12welOq7zvLJvfPMPiyZGAu3f+/+zdd5idZZ3/8ffTTi/TWzIzaaQACaE36WIJtrXsCuqC/ly7rrqrothwXVkVLGtfC6hrXdcVC4KU0HsJ6b1O76eX55TfHwdGYgIZJmdKwud1XefizMz9PPc9AU7OfOZ7f+8893UV+ENqKX9ILWWuMciHQrdxSfEOfKleGtd/n/rN/028/SLGFr4SNzRnpr+FQyp5wpScAFZ2FP/gGtxAK2akk7aaCCOpPGv3xeisD9BRH8BrqypVRORoohBVRERERERemCwbrDB4w/t/vug+Vbn6VLiaTUBqEGJdlSpXX/SQp84/faBV+Bk/cuUKlWA1VyiSfqpiNVeo/BPKWJj4HAuvc2RXq1rmX3unpt0y93a53LbbZU1/I/+SuJRP8ne83r6Pd3pvYW6hi5pdf6Rm1x9JNZ/M2IJXkW46cXZv9Tcsiv4GSkUXJ9WHnR0mH+6gITSHdMlhx2CSsYzLgoYg9SHvTK9WRESqRCGqiIiIiIjIM1lO5UHkr59zM5AcgLG9kOh7qidr7VPjJsZrm3htk6d/DCuXnwpWCyWyboFktkA8V2AsnadYLuOxTLyOide2jthK1YBj8JL5Hl4y38NgusQde1xu223y09hF/LRwIWeb63mHcwvnGE8Q7H+MYP9j5ENzGVvwSuIdF1K2D3bs1+xQthzcUAumm8I7uhU73Y8dmYc33MRQ2uXJrjE664J01AdwrFkcCouIyIQoRBURERERETkUxw+1nRBpe6oqdR+khgADAjVg+573LQ0DfE7l8Kqo36Y5Am6xTCZfJO0WiKULpPIFkrkclMFrW3idSoUrR2Co2hgw+YdlXv5+qYcdYyVu2+1yx54VXJ5dTqfRx+XWX/gH+y6CyS6a1n6H+o0/Id55MWMLXkEh2DLTy39WJSdIyQ5g5cbwDa3DDjThRDqJGxG2DSSIZVwWNoaIBiYeuIuIyOyjEFVERERERGSiLKcSpIaaIT0C8a5KhWpxGPw1Bx5q9Tw5loHjt4n4bVoilUrVdL5IOldgLOOScYvEMi6WYeCxK9v/bevISlQNw2BRrcWiWot/OuHp/qlz+WLXP3Jd9g283rqby61bWFDoo3bH76jZcSOpltMZW/hKMg0rDtqXdsYZBkVfLcVSATszhD87gh1qJxCcw0AqTyI7yvyGIG01fmxVpYqIHJEUooqIiIiIiDxfpgWhRgg2VA6jivVAshfSo+ALP+shVM/X0y0AagMObTV+sm6RtFsklSsQy7gkci7FUhkL44jsp3pg/1Qft+1exYv7L+Zc80neat3CedZaQn0PEup7kGy4k9jCV5KYez7lSVT/TjnTphBsxihk8MR2Yqf78UTnMWrUs7E3wWjaZUFjkLBPVakiIkcahagiIiIiIiKTZRiV3qj+Wsh1PNU3dd9Th1AFwFdzyEOontdUHgu/x6I+6KFYgkyhQCZXJJ5xSTzVT7VEGdustAk4kvqpHtg/9Qw+s/tkrPg+Lrf+wuusuwkm9uBb801q1/+Y0WPfRHz+y8Gozp9vNZVtP27Ih5WP4xvaQFOggVCwnZ5YmXjWZUFjiNaID9M8Qv7liIiIQlQREREREZGq8IYrj8gcSD19CFUvWJ7nfQjVRFgmhDw2IY9NY9iLWyqTyVX6qcYzBZK5I7ef6v79Uxdz2+75/GDPP3Cxu5orrL/QXhikee13yW25jX3HvZfG9kUYsy0tNgyK3ihFJ4SdHSaUHWF+aA7DbivruwqM1gaY3xAk6NWP5SIiRwK9WouIiIiIiFST44OaDgi3Vu0QqglNaz57P9VYxiXtFoll8vgdm6DXPiIqVPfvn9rM4/1v4Opdr6Sj92Y+aP6Kjtx25jz2Yf53zcvY0nkZZ82P0BGZZZWppkUh0IRRzOGJ76PFGSIcaKd7qG780KmmsFdVqSIis5xCVBERERERkakwfghVC6SH/+YQqih4QlM6/cH6qcayLgPxLMPJLF7HJnSEhKnwzP6pITKF1/HH3ecwf+sPOTN/P39f+jO9Ox/is1v+kW3h0zm/08P5HQ6todnTILZseXHDbZj5JKH4VhZ6ogyV5rIuV0dD2E9L1EdtwIPPmWUhsIiIAApRRUREREREppZp7n8IVby3ss0/3VXVQ6ieyzP7qdYFPYym8gzEcwwls/jsSmXqkXQgld82OHVRMyz6BDt6HqNhzbdpzffzPc/XuD19Ip9ZdwU/WtvIkjqT8zsczutwaAzMjm+w5AlRcgJY2VFa8huJlpoZLjSzNh4m6PXQHPHRGPYS8TmqThURmUUUooqIiIiIiEyHZx5CVdMByf6/OYQqCubU/4jmsUyaIz7qgl5G03n641lG0lk8VqUy9UgKUwFKbScz2PxtClt+Te22/+Ui6wleZG3ga4XX8v2RVWwZKfG9NTmOb7A4v9Ph3HabWt8Mf5OGSdFfT6no4ssOMIcBCt46YsUmdqWj7BnxUhtwaI36qQuqOlVEZDZQiCoiIiIiIjLdvKHKY79DqPrBMCvVqU5wyqtTHcugKeylNuBhLJ2nL55lOJXDY5mEfc4RFaaWLS8jx76FRPv5ND35bQJD6/iY/Uv+X/A+vmy+nV+NHsP6oSLrh4p8+3E4ocni/A6HF811iHhnrtqzbDkUgi1QcrFzMRqzQ9Q5YdK0MFKIsi6ZI+ixaY74aAh5ifpVnSoiMlMUooqIiIiIiMyUZx5ClRmt9ExNDlS2+tte8EWm7CCq8SVYBo1hLzVBD2OpPP2JLCPpHI555IWpbrid7rO/QHjfHTSs/yENuX18kc/w4YUX84vAm7i528fmkRJP9Bd5or/Ifz6a5eQWm/M7bM6a6xB0ZiigNB0K/gYolzDzCcLxrQRtH3l/I/FyAzsHQ+wZtqkNqjpVRGSmKEQVERERERGZaZYDoabKw81AeuSpvqkjUBh6art/ZEq3+zvmM8LUdKVn6kgqi2NZR1aYahgkOi4i1XIaDRtuILrnFpq7b+X9nod443FvY2vdBdy1r8DqvS47x0o83Fvg4d4CziNZTmuzOb/D4fQ2G789A4GqYVLyRsl7oxiFDJ5UDw30UOerI+1rYTQZYW0iR9Br0xyu9E5VdaqIyPRQiCoiIiIiIjKbOH6IzoFIG+TilSA13gPJQaAEnnClFYAxNammYxo0hp7e5u8yEK9UptqmSdhrY1lHRmBX8oQZOPH9xDsuounJb+GN76Hlia8Rqb+NjpXv5Y3HtrM3XuSuvZVAdV+8xH1dBe7rKuCz4Iw5Ni+Z7+GUFgtjilsrHEzZ9lOw/VAqYOVihNODBD1h8oEW4m4du4YK7B1JUxNwaK3xU6/qVBGRKWWUy+XyTC9CJicejxONRhkaGqK+vn6mlyMiIiJHGdd1uemmm1i1ahWO48z0ckRe2EpFyIxBahASfZBPgGmBN1qpUp1ChVKZWKYSpo5lXGzDJOSzsY+QMBWAUoGaHTdSv/nnmMUcZcNm9JjXMbLk7ylbXsrlMrtiJVbvcblrr0tv6q8/Jp/UbPGuE33Mr5nhgLJcxnQTWPlUpZeqv4mMr5GRUphcCQJPVac2hL3UqDpVjgB6nyGzxdP5WiwWIxKJPOs4VaKKiIiIiIjMdqYFwfrKo25+pX9qoh/Sg5AerlSvesOVPqpVZpsG9UEPNX4PsUye/niWsUweyzAI+5wjI0w1bcaOeR3JOefQ+OR3CPU/Qt3WXxHquovBE95NuvlkFtRYLKixeNsKL1tHSty2x+VP2/M83l/kXbekWLXQ4fLjvdT4ZqivgWFQ8kQoeSIYhSx2qodIqpugp5Z8sJV4qZbdw8X9qlPrAh78HlWniohUw5HS1WZS8vk8P/3pT1m1ahWdnZ34fD5aW1s566yzuPbaaxkaGprW9Xz4wx/GMIzxx7x586Z1fhEREREROQrYXgi3QNsJ0H4GtK2sBKiZMRjrqvyzVKj6tJYJdUEPi5sjLGkJE/E7xDJ5RpN5CsUjY4NjIdBE7xmfpue0T+D6G/Ck+5jzwGdoeeSLWJlhAAzDYEm9xXtP8vHDVSHOabcpleGP212u+FOS32zO4c7w91u2fRSCLbj+RoxiGv/IehpHn6Cz3E2jnSGZcVnXNcYju0fY3BtnJJWnVDoy/h2JiMxWR+12/s2bN3PppZeyZs2aZx3T1NTE9ddfz6pVq6Z8PQ8//DBnnnkmpVJp/HOdnZ3s3r170vfUdn4RERGZStpmJ3IEKZUgF/tr/9RsDAyjEq56QpXnUzBlLFvZ5j+adjGAiM/BnokDmSbBcNPUb/45NTt/j1EuUbT9DC/7R2ILVvbxhtwAANMMSURBVIGxf/Xm2oEC33kiy/bRys9zc8Im71zp5Yw2e0b6pR6gXMZ0U1j5BGXToeBvwA00EzOjJPJlTKNyaNi8+iDRgF7PZXbQ+wyZLSa6nf+oDFG7uro4/fTT6enpASq/STz33HNZuHAhg4OD3HbbbWQyGQAcx+Hmm2/mwgsvnLL1uK7LySefzLp16/b7vEJUERERmc30w43IEaroVqpRkwOVh5sEywO+CNi+qk/3dJg6mMgxmsoDEPbZOPaRsfHRM7aT5ie/iW90KwDZmkUMrHwfuZpF+40rlsrcutvlR2tzjGYrP0bPmn6pz2AUslj5OEapRNEbwQ3NIeOpYyhn4lgm7bUB5tb58dqzZ83ywqT3GTJbTDREPTL+VnueLrvssvEAtbOzkyeeeII777yTH/7wh/z+979n7969XHTRRUDlf9o3vOENjI2NTdl6vvjFL44HqJdddtmUzSMiIiIiIoLlQKgRWo6DzjOg7SQINEAuCbGuSqVqehhyCSjmD3s604TagMOixhBLWsLUhTwk8wWGEjmy+WIVvqGpla9ZwL5zv8zACe+haAfxjW2n/c4P07j2e5huanycZRq8bIGH6y8J8cZlHhyT8X6p//lohliu9ByzTJ+y7aMQaMINNGIUc/iGNhAdfIzOwl6C7ijb+8Z4ct8YA4ksR2FNlYjIlDnqQtSbbrqJe+65BwCPx8Mf/vAHTjjhhP3GNDQ0cOONN7JgwQIARkZG+NKXvjQl69m8eTOf//znAXjTm97ExRdfPCXziIiIiIiIHMDxQ3QOzDkJ2k+vBKr1x4A3UikhTY9CrLvySA5AdgwKWSg//0DQNKHmqTB1WUuEtho/+VKJwUSWZLbArM7rDIvY/FXsefF3ic89D4MSNTv/QOet76B2y68x88nxoUHH4P+d8FS/1LmVfql/2O5yxR+T/HbLzPdLHWdaFH21uKFWyqaNJ7GHxtiTLMisozS4gw079rKpZ4xUrvr9c0VEjkZHXYj6rW99a/z55ZdfzvLlyw86LhgM8rnPfW784+9973sUCtX9y6NcLvP2t7+dXC5HbW0tX/nKV6p6fxERERERkQkxjMp2/ugcaFwM7afBvLOh80yYeyo0H1c5rMqwKxWrid6nqlZ7K1Wr+dSED6syjMp2/s76AMe2RpjfEMI2DYaSOcbS7qw+hKroq6X/lI/QddbnyQfbsPMxGjb9hPl/eSsN6380fvgUQGvI5NMvCnDthQEW1pgkXfjOEznecXOKh3rc2VPlaRiUPCHcYAuuvwmLIi35XcxNPEls2/1s3Lie7v4BCsXZUUkrIjJb2TO9gGpKJpPcfvvt4x+/9a1vfc7xr3vd63jXu95FMplkZGSEu+++u6q9Ub/zne9w3333AfDlL3+Zpqamqt1bRERERETksFgOWFHwRf/6uVIJChlws+CmK+Fpdgzymcr2/1KhkpKaTqW/qu2t9Ft9lsOV/I6FP2rREPISy7gMJrLEMpVDqIJeG68zO+t6Mk0r2XPRdwh330Pttt/gje+mdvtvie78PYn2Cxld9Frc8FwATmiy+dZLgvxlV6VfaleixCfvznByS6Vf6rzoLOo9aloUvVGK3ihGMU9zPkF2dAM9w1tJ1DXT0jaPmvpmcKrfO1dE5Eh3VIWo999/P7lcDqhUmp566qnPOd7n83HmmWdy6623AnDHHXdULUTdt28fV155JQDnnHMOb3vb26pyXxERERERkSljmuAJVh484/DaQg7czF8f2bFKqJpLVL4GYFpPhareSghn/DUgdSyDhpCHuoCHeNZlOJljNO0Sz7oEPRYBjw2z4JD7/ZgWifbzScw9j0D/o9Rt+w3+4Q1E9/yFyJ5bSbadyegxrydXuxjLNHj5Qg/ndjj8YmOO327J81hfkXfenOIVixz+8XgvUe/sCozLloeivx7HX08klyY90su+kb0ka+tpbGnHG20Bfy1YR1VsICIyaUfVq+GmTZvGny9fvhzbPvS3d9JJJ42HqM+8/nC95z3vIZFI4PF4+N73vofxLL+ZFRERERERmfVsb+Xhr/nr50rFv4aqhQxkE3/tqZodg3IZvEHwhMCs/Gz2dN/UmoBDMl9gNOkylMwxmMzitW1CXhtzdmWNYBikW04l3XIqvuFN1G77DaG+hwj33E+4537SDSsYXfwG0o0rCToGbz/Bx6oFHr7/ZJZ7uwr8fpvLHbtd3nK8l1cd48E2Z9/PhqY3QMgbIJsv0B2LkUxsoDmyg2hNPWa0rRKm+mqYff9yRESmz1EVom7ZsmX8eWdn54Su6ejoGH++efPmqqzjl7/8JX/84x8B+NjHPsayZcuqcl8REREREZFZw7TAG6o8nlYuV0LUXALSI5AagOQQlAuVQ648wUobACDksQnV2TRFvIyl8wwmc4ykc1gYhHw2jj37Arts/TJ66z+FJ76H2m3/S7jrLgJDawkMrSUbXcjo4teTbDuLtrDFZ14U4Mn+At9+IsvOsRLfeSLHH7e7vPNEL6e12rOy0MbnsfHW1hPPuIwlXZrcGC2JYQI+byVIDbdCoA684ZleqojItDuqQtTh4b82+W5ubp7QNS0tLePPR0ZGqrKGD3zgAwAsXryYq6666rDv+bRcLjfergAgHo8D4LourutWbR4RERERYPz9hd5niMjzY4O3tvKIdEI+Adl4JVBNJ6AwWOnH6gmC48c0TOqCHiJ+h0TWZTjpEsvkKZbKhDw2Xs8s6in6lEyog8yJH8Je8ibqdt5IzZ5b8MV20PrIF8kHWxlZ+HfE2i/i+EYP33hxgL/sdvnxujz7ntEv9R0neOmcTf1SnyHksykULHqzJiPFAC2GSV0pjhPrr4ThgToINVeqU9U/VSZJ7zNktpjof4NHVYiaTCbHn/v9/gld88xxz7x+sj70oQ8xODgIwHe/+128Xu9h3/Np11xzDVdfffUBn1+9ejWBQKBq84iIiIg809Otj0REqif/1GP0OUcNTctaDocD0dfjHPtSFgzexoLBv+BJ9dKy9tvUbPwZO5peyu6GC1ngBPj4CvhLt8mdvQaP9RV5d1+Ks1vKvHxuiaAz09/Hc+sefOZHGaD7qYfI4dP7DJlp6XR6QuOOqhA1m82OP/d4PBO65pkhZyaTOaz5//KXv/DTn/4UgMsvv5wLLrjgsO73tz7+8Y/z4Q9/ePzjeDxOe3s7F1xwAfX19c9xpYiIiMjz57out956KxdffDGOM8t/wheRI4+bg1wMMmOQHoJcstJn1fP0tn8v2XyRWMZlMJEj5RZxTJOg18a2ZttW+FqY/zZ2FS6jZu9fqNvxf/gyQxzX82uWDvyRsXkvZ2TBqzlhfpQ3JUv84Mkc93cXuKfP4Ilhk1cf4+E1x3gIe2fb91VRKkE8nQcTmsJemsI+vLYB+VTl31u5BL4IhFqhtqPS6kHkEPQ+Q2aLp3d6H8pRFaL6fH/dRpDP5yd0zTO3x0+0evVgUqkU73znOwGor6/n2muvnfS9no3X6z1oZavjOHrBERERkSmj9xoiMiUcBwIhqJ0DxQLk4pCNQaKv0lM1O4xjeQiHgjRHooxlXYYSOWKZAgYQ8Fr4nFkW1nn8xBe9mviCSwh33UXttv/Fm9hL/fb/pXbn70l0XIRv0Wu5+pw21vQX+M5T/VJ/tjHP/27N88pFHl63xEO9f3b1g7VMqI94ybkl+uJZkrkCrTV+6gMRzECkEn7nEjCyBXChcQlYR1XcIFNI7zNkpk30v7+j6lUtFPprQ/OJVpU+c9wzr3++rrrqKnbv3g3AddddR0NDw6TvJSIiIiIi8oJi2ZU+m4E6qJ33VIgag9QgZMZw3DEaDZP6aIB4OMBwusBYxiWZK1SqUz02tj2LqjhNm0THRSTaLyDY9wi12/4H/8hmortvJrL7LyTnnM3px7yO5S9ZyH3dBX6+IceOsRL/sznP77bmedkChzcs9dIaml1hqtcxabR9JLIFtg8kGQu5tER9hL02+Gsq/VJHdgBlaFyqIFVEjipH1SvaM7e09/f3T+iavr6+8ed1dXWTmvfxxx/nG9/4BgAXXHABl19++aTuIyIiIiIi8oJnGJWt4b4I1LSDm6kEqukRzNQgNYURarxlMv4ACUIMJ3Mkcy5upozPsQg4FtZs2e5vmKRaTyfVchq+4Q3UbfsNwf5HCXffQ7j7HlKNJ/LSxa/jnJes4JG+Ij/fmGfDUJE/bHf50w6XCzsd3rjMM7sOoDIg7LfxFy2GkjniGZfWqI/GsA/H9kKoCUZ2QrkMTUsrh4iJiBwFjqoQdcmSJePP9+zZM6Fr9u7dO/586dKlk5p37dq1lEql8fudccYZzzr26UOnAHp7e/cb+6lPfYpLLrlkUmsQERERERE5Kjn+yiPcAkUXsnHIjOIf24O/MExjYyPJokEi4zKcyjOWcSlTJuBY+D02xmzIUw2DbMPx9DQcjye2i9pt/0u4+26Cg08QHHyCbHQhkUWv4bQLX8TaIYNfbMzxaF+R23a73L7b5ey5Npce62Vx3ewJU23LoCHkJZMrsns4xWjapa3GT43fixFqgtFdlYEKUkXkKHFUhajLli0bf75u3ToKhQK2/dzf4uOPP37Q6ydrx44d7NixY0Jj8/k8Dz300PjHzwxYRURERERE5G9YDgTrn3o0wPAOjEQvYU+QcE0NzRE/yVyBWCbPcCrPcDKLaZiV/qm2BbMgUM1H59N/yr8yvOzN1G7/PyJ7b8MX20HLY9fRsOF6ahe8kpVnvYxNySC/3Jjj3q7C+OPkFovLjvWyvNHCmBXpMPi9Fl7HIp5x2dqfoC3qo6XGjxNurgSp5RI0LQN7Yoc/i4jMVkdViHrWWWfh9XrJ5XKkUikeffTR56wKzeVyPPjgg+MfX3jhhdOxTBERERERETlc/hpoWwnxRhjaAbFurFAjUb+HqN+mJeojmS0wmsozlnVJZl1syyLosXDsme81Wgi2MHjCuxle9iaiu26mZucfsLMjNGz8MXVbfkl9x4s5fuWr2L68hV9uynPHHpfH+oo81pfmuAaLy471cGqrPSvCVNOEmqBD1i2ybzRNOl9kTp2fULgFxvYAJWg6FuwDD0oWETlSzPzfHFUUCoW46KKLxj++4YYbnnP8b3/7WxKJBFDph3ruuedOat4rrriCcrk8ocf1118/fl1nZ+d+X7viiismNb+IiIiIiMgLkmlBTQe0nwLRdkgNQXoEymU8lkld0MPCphDHtkZY1BQm7LNJ5QsMJrIkMgUKxfJMfweUPBFGl/w9u1/yI/pO+hC5yHzMYo6aXX+i87Z3ccama/jMoh3csCrIKxc5OCZsGCpy1d0Z3n1Lirv2uhRLM/99APgci/qgj5F0nm19SQbTJcrhVhjbB33rwc3O9BJFRCbtqApRAd7znveMP7/hhhvYsGHDQcel02k+/elPj3/8jne845Bb/0VERERERGQW8oahZTm0rgTThlgXFHLjX/Y7Fo1hL0uawyxrizC/IYTHMYhnXIYSOVLZAk8dczFjypZDouMi9l7wn3Sd/e+kmk/FoEyo70Ha772S0x77F65qfoj/vsTHG5Z68NmwY6zE5+/P8E9/TnHLzjyFWRCmmiY0hCoVp9sHk+wezZELNEO8G/o3VA4KExE5Ah11Ieoll1zCOeecA1S267/iFa9g7dq1+40ZHh7mNa95Ddu3bwcqVagf+9jHDnq/3bt3YxjG+ONQ1a0iIiIiIiIyA0wTonNg7ilQO79SkZoaqpwS/xTDgJDHpjXqY1lLlGWtEebW+sGAkXSOkWSebL4IM5lFGgaZxhPoOfMz7L7oO8TmvYyS6cE3tp2Wx67lpHvfwUeDf+KXL4O3HOch7IF9iRLXPpzl8j8m+d3WPLnCzIepIZ9NxOfQG8uwfShLzGmqBKl96yGfnunliYg8b0dl6eXPf/5zTjvtNHp7e9m9ezcrV67kvPPOY+HChQwODnLbbbeRTldetG3b5te//jU1NTUzu2gRERERERE5fJ4gtBz/1MFT2yHWXTmIyvHvN8wyIeK3ifhtWqJ+EjmXsXSesXSBZCqLbVgEvBaeGeyf6obbGVj5PoaWvYXo7j9Ts/OPOJkhGjdcT/3mX9DZeTGXXfQqfttTx2+25BlIl/nW41l+tiHH65Z6eOUiD0Fn5nqmemyThpCPsVSebfkic6J1NMV7sChD8/HgCczY2kREnq9pC1GfPrTp7/7u73j/+98/pXPNnTuXO+64g0svvZQ1a9ZQLpe58847ufPOO/cb19jYyPXXX79fH1URERERERE5whkGRForh0+N7ILRPZBLVIJV48BQ1LEM6gIe6gIesm6JRM5lNOUSy+SJZ8tEfc6MHkZV8kYZXfJGxha9lnDXXdTs+B3e+B5qd/6Bmp1/5J9bz+TSs1/N70YX8avNefrTZX74ZI5fbczx6sUe/m6xh6h3ZtZvGFAb8pDJFdk1kiUZitI+1oOvXKq0YPAEZ2RdIiLP17SFqHfeeSeGYXD88cdPy3xLly7loYce4pe//CW/+MUv2LBhA/39/dTU1LBgwQJe+9rX8ta3vpWGhoZpWY+IiIiIiIhMM8cPTcsq4enQU1WpgfrnrID0OSY+x0tD0EsyV6A/nmU4mccAIn4Hy5q5ys6y5SHeeTHxjhcTGFxDzY7fEex/jFDv/YR67+c9tYv5+xNfwx/cU/n55iL74iV+tiHP/27Oc9lxXl6/xIMzQ+v3ey0c22QwmSPrCdOe7yFaKmG0Lq/0tBURmeWMcrk8Lc1STNPEMAze+9738p//+Z/TMeVRLx6PE41GGRoaor6+fqaXIyIiIkcZ13W56aabWLVqFY7jzPRyREQOTyEHI7thbDeUSxBsBNM65GXlMoxlXPrjWUZTOTy2TdhnY8xclrofT3wPNTtuJLxvNWbJBcD1NzK64FXc4lzAT7bYbButnJo1L2ryz6f4OL5xBjv7lSGWcSmWirTbMRqbW3BaV4AvMnNrkhmh9xkyWzydr8ViMSKRZ38tOuoOlhIRERERERE5gO2FpiUw52Tw10K8B/LJQ15mGFAbcDimKcyi5jAe22AomSWZLczsAVRPyUc6GTjxA+x+6fUML72MgieKkxmkacMPuWz9P/Hrtl/w7ycmqPEa7I6V+NDtab72SIZEfoYWb0A04BDwOuzOh9nb1U1y7xOQjc3MekREJkghqoiIiIiIiLxwBBug7SRoPg7cLMT7oFQ45GWWCY0hL0tbIsxvCAEwmMySzRenesUTUvTWMLL0Mna/9Hr6V36AXLgDq5ChdseNXLbp3dw294dc1lkJKv+0w+Vtf0pyxx6XadqcegCfY1EfCjBAHbu7uhnc9iil9OiMrEVEZCIUooqIiIiIiMgLi+2B+oWVqtRgAyT6IBuf0KWOZdAa9bGsNUJ7bYBcscRQMke+UJriRU9M2fIQn/cS9l74LbrPvJpU04kYlGjovo3PD36Avyz4FceHU4zlylzzQIaP35WmJzEzazdNaAj7cP0t7OvtY++mB8nGh2dkLSIih6IQVURERERERF6YAnXQdiI0H1+pRo11Q9Gd0KU+x6S9LsCSljDNYS/JbIGRZJ5CcRbs8QcwDNLNJ9Nz1r+x99zrSDcsxyy5LO65kRvL/8wP5/yBiJnlsb4i/3Rzkl9szOHO0NpDfgdf7RyGh0fYteEBRof6Z2QdIiLPRSGqiIiIiIiIvHBZNtTNr1SlhlshOQDZsQlfHvbazG8IsaQlTE3AYSyTJ5Z2Kc2OwlQAcnVL6D77C3SfeTXZ6AKsQpqLhn/BI6F/4eM1t1MqFvjR2hzv+UuK9YOHbm0wFRzHItzQTi6ZYM/6+9nXtZdiaZYE0iIiKEQVERERERERAX8NtK2E1hVQ4qmq1PyELjUMqAk4LGoKc0xTGJ/HZDg1ew6fAsYrU/ed/zV6T/kI+UAL3vwo78z+kMciH+PvvQ+yJ1aY0YOnDNMg2DgXLwV6tzzK5h07SednJtQVEflbdjVucuGFF0547P/93/+xfv365xxjGAa333774S5LREREREREZOJMC2o6wF8Lwzsh3lX5nK8GbO8hL7dMaAh5iPodhlM5emNZBpNZwl4Hn8ea+vVPhGGSnHseybaziO6+hbotvySa6+VLxn/yvvB8rkr9A3/asZz7ugq8+yQfF3TYGIYxrUu0a1qoTQ4wtucJNuRcOjvn0RjyTvs6RESeqSoh6p133jmhF7NyuUxPTw89PT3POUYvjCIiIiIiIjJjvGFoWQ7h5kpFanqo0ivVG648DvEzq2MZtER81Pg9DCayDCRyJBMFIn4Hjz1LNoSaDrEFryDecRE1O26kdtv/0uHu4qee/+Bx4ziuzv4D1zywiL/ssvjAyX7awtO87lAT9eYQicENbM4ViLd30lkfxLFmyZ+fiLzgVO3Vp1wuP+fj+Y4TERERERERmTGmCeEWmHMStJ8GDYuhXKqEqqmhCR1ANX74VGuY5oiXZG6WHT4FlG0/o0veyO6Lf8DowldTMm1OKm/gRu+n+a7na4z275uxg6eKgQbCPovG9Db27dnJ+u4Y8ezEDv4SEam2qoSopVLpkA+obNN/3/ved8ixxWKxGssSEREREREROTyGUdne37gYOs6s9E31hitBarwH8qlD3iLkqRw+tbQlQm3QMysPnyp5owwt/yf2vPi/iHe8mDImLzMf5lbvR/ms8X3+tLZ3Rg6eKvrr8ToWHfmdxAf2smbvGHuHU7jFWfSHJyIvCKqDFxEREREREZkIxwc17TD31Ep1ak0nFLIQ64LMKJSevSDIMCDqt1nUGGJxcxi/x2IkPcsOnwIKgSb6T/ogey/8BsmW07EocZm9mru8H+KNqZ/xmdsHpv3gqaKvFsOy6HB34s/0sbE3ztquMYaSOe1oFZFpoxBVRERERERE5PkwLQg2QMvx0H4GNB8PpgOJvsqjkHv2S02oD3pY3BJmQUMIw4DBZI5ktsBsygPzkU56z/gU+875Epn6Y/EZLu+y/8A93g/Ssft/ec+fhrljjzttIWbRV0vZdGhIbqWj1EMsmWbNvjG29CVI56e3OlZEXpgUooqIiIiIiIhMljcEdfOh4wyYewoEmyAbq/ROzcZ5tmTUMQ2aIz6WtUaY3xDENGA4mSWRLcyqbf7Z+mPpetEX6T7jM+Qi84gaaT7m/JLf8SF2P/xHrrozQU9iehZc9EYpeUIEYtvoyG2n1syyezjN43vH6B7LUCzNohRaRI469kwvQEREREREROSIZzmVg6hCzZAdg+RgpWdqrKvSBsBXUxnzN7y2SWvUR33Iw2gqz0Aix3Aqh9e2CHltzNlQ+mQYpFtOZW/zSYT33UXdpv+mJTPANc4P2TF6E1+75e9pXHYOr1/qxbGMKV1KyQlQsjw46QFq80kCNQsZKtazvjvGYDxLZ32Q2qBnStcgIi9MClFFREREREREquXpg6j8tVDTAemhSpCaGgLK4IuCJ3jAZR7LpDnioy7oZSydpz+RZTiVxWNVwlRrisPJCTEsEh0XkpxzDpHdf6Zm869Y6PbyDfPrPLnlD3xnz+W89kUrmRuxpnYdpo0basXKjuIfXkdzuJN0qJOhZJ7RdJ722gBz6wL4nCleh4i8oMyG32mJiIiIiIiIHH0cH0TnwtzT9j+Iamzfsx5E5VgGjWEvS1siLG6OEPBYjGbyjKVcCsXZsV29bDnEFr6KvS/5PsNLLiVv+jjB3MlXcp/jL7fexK278tOyjqKvloK3Fk9sF+HhdbR5MgQ8NtsHk6zZO0ZfLEtJW/xFpEoUooqIiIiIiIhMJdPc/yCqluWVg6iS/c96EJVtGjSEPCxpibCkOUzYbxPL5BlN5mdPmOoEGFn2Jrpe+gOGms/GMYpcY32P4mM/4csPpMi4U7/Osu3DDbVi5mP4B9cQzXbTFvaQK5RY2zXG+p4YsYw75esQkaPftIao03Vqn4iIiIiIiMis9MyDqOacXDmIKjMG8W7Ipw4YbplQF/SwuCnMkpYINUEP8YzLSDKPW5gdJ1AVvTWMnvExho55AwDvt3/HK3q+xoduGWXH6IHVtlVnmBSCzZQsD76RzfhHN1PvKdAQ8tIXy7Jm7yi7BpPkCtOwFhE5ak1bT9Rdu3YBEIlEpmtKERERERERkdnpmQdRZUYh3gvJXkiPVPqmesOV/qpPMU2oDThEfQ7xsMtgMsdIKk85Wybsc/DYM7zR1DAZPe5yiqE2Gtd8k1dZD9CWH+a9t36Yvz+xiVcucjCMKT50yhOmbPlwkl2Y+ThWzSJao00kcwW29CcZTOaYVx+kMeyd8rWIyNFn2l5lOzs76ezspLa2drqmFBEREREREZndDAMCddByHLSfDo3LoFyqHEaVHjmgb6ppQk3AYVFjiGUtERpDXtL5AkPJHFl35ist450X03PW5yjYQU4xt/Jr+9P86fGd/Nt9GZL5adjebzm4wVaMYhbf4Fo8Y9sJOWVaoz5SuSJPdsXY1BsnmStM+VpE5OiinqgiIiIiIiIis4E3DI3HVLb6t54AlqfSMzU5AMX9+3oaBkT8NgsaQyxtidAS8ZJzSwwls2TzMxumZhpPoOu8a8kHmuk0B/it5zO4PWt5181JNg5NQ3hpGBT9DRQ9Ibxj2/APrcd2EzSEvNQGHPaNpnl8zyh7h1O4xdnREkFEZj+FqCIiIiIiIiKzieOH2s6n+qaeBP4aSA1Wtvz/zSFUhgFhn838hhBL28K0RQPkiyUGEzkyuZkLU91wO13nXUemdgk1Roqfeq7h7OxdfPj2NL/alKM0DWemlJ0AbqAFOz2Af2ANTrIHr2XQFg1gGQYbe+M8uW+MoWROZ7iIyCEpRBURERERERGZjSwHIm0w5xSYexpEWp/zEKqQx6azPsCy1gjttX4K5TKDiSypbAFmICMsemvoftEXSMw5B4ciX/F8lw9Y/8MPnsxy1V1pRrPTUAVqWrihVjDAN7QO78gWjEKWiN+hJeInlnFZs2+MLX0J0nlt8ReRZzdlB0tt376d/v5+RkdHSSQSRCIR6urqaGlpYf78+VM1rYiIiIiIiMjRxbQg1AjBBqj520OoIuCN7HcIVcBjEagL0BD2MpLMM5DIMZjMURvwYFvTe6BS2fLSd8pHcIMt1G39H/7Z/j8WmP38a987eNfNJa4808+JzVN/5nXRW0PJ9uON78bKJ8jVLgJfHU1hH1m3yO7hNEOpPPMbgrREfFimDp4Skf1V7ZWqXC7z61//ml/+8pfce++9jIyMPOvYxsZGzjnnHC699FJe+9rXVmsJIiIiIiIiIkevpw+hCtRBrgMS/ZUDqGJd4AmCL1oJXJ/idyzm1PqpC3noGs0wlMgS9nnwOtO8KdUwGT72ctxgK01rvsUrzfvp9A9zeeZDfGx1mcuO9fCW471THlyWLS/5UCt2Zgj/4BpykYW44bn4HIu2qI9YxmV9d4zBeJb5DSGiAWdK1yMiR5aqvHL++c9/ZunSpVx22WX8/ve/Z3h4mHK5PP4A9vt4YGCA3/72t7zhDW9g+fLl3H777dVYhoiIiIiIiMgLgzcMDYug4/RDHkLldyzmNwSZUxsgmXNJZmdm23q88yV0n3U1RTvIivIWbgl+hnlGLz/bmOcjq9MMpqdhe79hUgg0UbJ8+Ec34RvegOmmMAyDmoCHppCXoWSeJ7vG6I1l1CtVRMYddoj6la98hVe96lVs3779WV9cnuvzGzZs4OUvfznf/va3D3cpIiIiIiIiIi8sBz2EagjifVDIjg+zTYP22gALGkMUy2XGUu6M9EnNNK6k69wv4waaaSr28+fAZzjX3sS6wSLvvDnFA93uoW9SBSVPiHygESfVi39gDXa6H8plbMukOeIDYEN3nJ2DKQrFaQh3RWTWO6zt/D//+c/513/9VwCMp/qvNDQ08MpXvpLTTz+dJUuWEI1GCYVCJBIJYrEYmzdv5qGHHuKPf/wjQ0NDGIZBoVDg/e9/P01NTbz+9a8//O9KRERERERE5IXk6UOoQi2QHoZ411NVqcOVYNUTxDCgKezFY5nsG0kzlMxRF/RiTvPu/nykg33nXUfrg/+Gf3QLNzjX8GX/O/hO4kV8+p4Mr11c5O0neHGmun+r6eAGW7Byo/gGnyQfmYcbmUfZ8lAb8JDOF9g+mCDjFlnUFMLnWIe+p4gctYzyJGvTu7q6WL58ObFYDIBIJMK1117LP/7jP+LxeA55fS6X48c//jEf/ehHSSQSlMtl6urqWLduHa2trZNZ0gtOPB4nGo0yNDREfX39TC9HREREjjKu63LTTTexatUqHEd94UREjijlMmTHINZTOYQqn4FQA9iVKst0vsi+kTTDqRw1fg+OPc1JKmAUczQ/9lXCPfcC8JfoG3hH/2sAg2NqTT55VoC28PSsyyhksDOjFAKN5GoWUvLWAOAWSwzEs9SHvSxuDhP16+/DatH7DJktns7XYrEYkUjkWcdN+tXoK1/5CrFYDMMw6Ozs5PHHH+ftb3/7hAJUAK/Xyzve8Q4ee+wx2tvbMQyD0dFRvvrVr052SSIiIiIiIiIClUOo/LXQchy0nw518yE9WqlOLRUJeCwWNIZojfoYy+TJ5IvTvsSy5aXv1I8yckxlR+pLYv/D6rbvUe8psG20xLtvSbJ6z/Rs7y/bftxQM1Z2mMDgkziJvRjFHI5l0lrjJ5Z2Wds1Rn88e+ibichRaVIhai6X4yc/+QkAjuPwm9/8hgULFkxqAQsXLuQ3v/kNjuNQLpe54YYbcN3peZEUEREREREROep5w9B8HMw5GbwRiPdALoFjGXTWhZjfECJbKBLPzMCBU4bJ8HFX0L/yA5QNi/kjd7O67j84uz5FugBfeCDDVx7OkC1MQwNXw6IQbKFkmPiGN+Dvfxwn2Y1ZLtAc8VEuwbruGLsGkxRLOnBK5IVmUiHqbbfdxsjICIZhcNlll3HyyScf1iJOOeUULr30UgCGh4e5/fbbD+t+IiIiIiIiIvIMhgHh5kqQ2nwcFPMQ68Ysu7RGfSxqDGEaMJLMMxMH0sfnvYTuM6+maAeJjG3kej7NPx8zhAH8eafL+29NsTs2PdWyJW8UN9iKUcrjH1xLoP8J7FQftX6TkMdmS3+SLX1xsu70V++KyMyZVIj66KOPjj9/3/veV5WFPPM+Dz/8cFXuKSIiIiIiIiLPYHugfiHMOQWicyA1COlh6gIOi5pDhH02Q4ksheL0J6mZppV0nftl3EAznlQvH+i7ih+dvIs6n8HuWIn3/SXFH7fnmeTRLs+PYVL01ZIPtWAUUvgHnyQwuIZocZjGgM3ekTQbemLEs9pJK/JCMakQ9bHHHgMgHA5z0kknVWUhJ5100njz1meGtCIiIiIiIiJSZf4aaFkBrSvB9ECsm7CZZ2FTiKaIj9F0bkYqLfORDvadey3Z2sVYboLzN36G/1nxMKe2WuSK8PVHs3x0dZreZGl6FmRYFP31uIEmzHwc/8AaomPrmeskGUlmWdsVYyChPqkiLwSTClF37tyJYRiceOKJVVuIYRicdNJJlMtldu7cWbX7ioiIiIiIiMhBmFalGnXuKdCwCLIJvJkB5tX5aK8NkMoVSWanv09q0VdL19lfINF2Fka5wMK1X+U7Tb/j3Ss9eC1YM1Dkn/6c5Debc9PXm9S0KPgbcAMNWNlhgkNrmJfbhpEcZF3XGHuGU5TUJ1XkqDapEDUWiwHQ1NRU1cU0Njbud38RERERERERmWKeADQurYSpgTrsVB9z/S4LG4OUymVGU3mY5nywbPvoO/VKRo55PQANW37Bu5Pf4vsv8bKyqVKV+r01OT54W4pdY9NYMWs6FAJNFH312JlB2lIbaEhsYfuevWzpi5ErqE+qyNHqsELU2traqi6mpqZmv/uLiIiIiIiIyDQwDAg2QNtJ0Hw8RrlEY2mIRfVe/B6LwWSW0jTtoP/rmkyGj7uC/pXvo2yYRLpWc+qTn+QrZ6T48Kk+gg5sHinx7ltS/Hhdlvw09nEtWw6FYDNFXw1Rd4D29AaGdz7Bll37SKhPqshRaVIhaiqVAsDj8VR1MU/f7+n7i4iIiIiIiMg0shyom1+pSo22Ey2NsSiYpT7gMJzKkS9Md5IK8Xkvo+fMqynaAfwjm+hc/c+8PvA4P1gV4uw5NsUy/PeGPO+5JcXGoeltP1C2vLjBFkxflLbyAPk9D7N93SMMDQ1N6zpEZOpNKkSdlpPwRERERERERGRm+CLQshzaTsIfCLHAG6MtUCKeyZPJTf+W9XTTiew7/2tkaxZhuQnaHvo8y7b+F5890+JTZ/up8RrsiZf44G1pvv14low7vblF2fZRDLdRE4nijO2ka91qerY9SSmbnNZ1iMjUmVSIKiIiIiIiIiJHOdOESCvMOQWneRkdIVjoS5B3c8TS079l3Q21se/cLzO66O8AqNn1Rzru/hcuqunjh6tCXDzPoQz839Y877g5yWN9038oVtkTwNvYieX46d/5JF3r7iTfvw3czLSvRUSqyz6cixOJBHv37q3WWkgkElW7l4iIiIiIiIhUgeODxsWYwQaaRnbiGdjLvqTBcCJEbdCHOZ3lWabD0PH/j3TjCTQ/9lW88d103PlB/CveyUdPv5gLOh2+/kiGvlSZK+9M85L5Du9c6SPiNaZxkeALRcn7wvTFRyhseZTWpr34mxZAuLXy5ykiRxyjPIm9+aZpYhhT8wJULpcxDINiUSfaHUo8HicajTI0NER9ff1ML0dERESOMq7rctNNN7Fq1Socx5np5YiIyGxQKkK8h1TfFnr6BxguR4iGI9jW9IaUAFZ2hJbHriMw+CQAiTnnMrDyvaQI8KN1OW7cmqcM1PoM3n+yj3Pap//vslIJRpJZomaGuQGXSE0j1M2DUAvY1T1n5kij9xkyWzydr8ViMSKRyLOOO+zfF5XL5ao9RERERERERGQWMy2oaSe44Ew6Fh1PiydLaqSbbD4/7Usp+uroPuvfGDr2csqGSbj7bjpWf4Ca5Fbee5KPr744QHvEZDRb5nP3ZfjsvWmGM9N7MJZpQkPYR8oIsTUbZSCeotyzBroehlgXFKe/5YCITM6kQ9SpCD4VpIqIiIiIiIgcATxBvG3LaT/+HFoamymN9ZBOjMF0/1hvmIwufgNd53wJN9CMk+6n/e6PUrvtNxxXb/LdlwZ503EeLAPu6yrw9puS3LwzP735gwE1QQfbtNiRdNhbqMXNZ6BnDXQ/Com+SsmqiMxqk+qJumvXrmqvQ0RERERERESOJIaBFWlmzvE1eLp2MLBnI7GhbjzhZvy+wzqC5XnL1i1l7/lfp2nNNwn33EvDhhvwDz5J/0kf5orltZzb7nDdwxm2jpS47uEsd+xx+dCpflpD09fQNeizcQom3bEsuaKPudEIgewYdD1a6ZVa2wmBepii9okicngm9arW2dlZ7XWIiIiIiIiIyBHIsL00zTuWcLSO0d1rGBnpYzBXS8jvw++xpm0dJU+IvlM/RnrPShrXfZ/gwBN0rH4//Sd/mAVNJ/GfLw7y2615bliX44n+Iu/4c5IrVnh5zTEeLHN6gkuPbVIX8DKcypLIuUR8AWq8EB7rw5ccgEgb1HaAv3Za1iMiEzedZ+iJiIiIiIiIyFHKX9tC27KzWDivk/meGAU3x2AiS9adxoOjDYP4vJex77yvkot0YufGmHP/p6lf/yMsCrxhqZf/elmIE5osskX47hM5Pnhbil1j07dGyzJoCPrwWCajqTzbh7KsT/jZlnQY7t1JeseDlPs3Qi4xbWsSkUNTiCoiIiIiIiIi1eGL4O84idZ5x7IslGZuEHKFEkOJHDl3+vp+5iMd7DvvK4zNXwVA3fbf0n7Px7BTfcwJm3z5ggAfOtVHwIHNIyXe85cUP1mXJV+cpl6pBvgci9qgh4aQD59tMZY32ZIOs2mkyI7NTzKw8R4SXZso5dLTsyYReU4KUUVERERERESkehwfNB+Lv+14OgIuS2uLtES9ZNwCQ8kc+cL0hKlly8vgCe+h57RPUHSC+Ea30rH6A4S67sIwDFYt9PDDl4c4c45NoQQ/3ZDnPbek2DhUmJb1jTPA65jUBBwaw158gTBjTjO7RnPs3PQoWx+7na4dGxhLJCmWdCC3yExRiCoiIiIiIiIi1WVa0LAIWlcQsg3m+1IsbQ7THPaSyhcYTuZwpylMTbWdxd4LvkGm7lisQprWR79M0+NfxyhkaQiYXP0iP588y0+N12BPvMQHb0vzgyezuNNVlfo3PLZJNOBQV9eAp6aDvFtkYNtjbH9sNU9uWM/O/jFGUnkKxemr7BWRSR4s9bQnnniCTCYDwIIFC2hpaTlgzGc/+1l+8pOfTOh+r33ta7n22msPZ0kiIiIiIiIiMhsYBkTngu2HgY2EswOE6pppCPnoT2QZSeYBiPgdbGtqD3YqBJroetE11G35BXVbfkV07634RzbRe+pHyUcXcF6Hw4nNFt95Isdtu11+tSnPE/0FPn6mn7nh6Tsc62/ZjokdrYdILaRHyQ+sY2B4H/tC7TjRZhojfmqDHiI+B4+tOjmRqTTpEHXDhg2ceuqplMtl6uvrWb9+/UHHDQ8Ps3v3bgAM49lfFMvlMl//+te54oorOP744ye7LBERERERERGZTYL10HYiDG7GiPcQCTURbgwRC7kMJHKMpPKYQHiqw1TTYmTZm8k0rKDlsWvxJLtov+tfGDr+bcTmv4KI1+RjZ/g5a47NVx/JsHWkxLtvSfHek3y8dL7znJnGlDNMCNbj8dfQnB2hnNlErDBIV6KFXZ5aAj6HhqCHulAlUPU5Mxf8ihytJv1ris997nOUSpXS8a9//es0NTU953jDMCiXy8/6ACiVSnzhC1+Y7JJEREREREREZDbyhqBlBdQtgNQQhpukJuCwqDHEkpYw0YDDWCbPWMqlOMXb6DONK9hzwTdINp+KWXJpWvs9Wh/6d8x8HIBz2h2++9IQJzRZZAtw3cNZPn9/hkR+FvQjNS0KgUZKgQZqiiPMy2yiw92Jk4vRNZrhiT2jPLJ7hA3dMfpiWTL54kyvWOSoMalK1Hg8zo033ohhGCxZsoRLL710Qtddf/31z/q1a665hq1bt/K73/2OWCxGNBqdzNJEREREREREZDayPdC0DJwADG6BQh4zUEdtwCHic4hl8vTHs4ymcziWRdjnYE7RDvWSN0rvGZ8muvMPNGz4EaG+B/Gu3k7fyf9KtuF4moImXzw/wK835/nxuhx37yuwaTjJlWf4WdF0WJ0Rq6JsORSCzRiFLL5UN97sILXBOeSCrSTx0BvLsm80Q8BjMa8+wNzaAKY5g5W0IkeBSf2f/8c//pF8Po9hGHzwgx+c8HWXX375s37NcRze/OY3k8vl+P3vf89b3vKWySxNRERERERERGYr04L6BeD4YGAzJPog1IRlmtQFPUT9HsYyefpiWUbSOTyWRchrT02YahjEFr6KbP1xtDz6JTzJbube+wlGlvwDI0veiGVaXHqsl5Oabb7wQIaeZImPrE5z6TIPbz7eiz0LQsmy7cMNtWK4aTyxHTjpPjzhuYSDbZQsH4lsgY29cZK5AgsaQ9rmL3IYJvUydP/9948/f9WrXlWVhfzd3/0dfr8fgIceeqgq9xQRERERERGRWSjSBm0rwRuGWA+UCgBYJtQHPSxpCbOoKYTHNhhJZ0lkC5SnaDd9rmYhe8//GvGOF2NQon7LL5h7z0dxkt0ALKm3+M5Lg7xkvkOpDD/bmOdDt6fpTZamZkGTUHYCuOE5lEwb78gWAv2P4Ul2EfWUaQz52DuSZn13jFjanemlihyxJhWiPvHEEwAsW7aMlpaWqizE7/ezYsUKyuUyjz32WFXuKSIiIiIiIiKzVKCucuBUpA3ivVDIjn/JNg0aQ16WtkZY2BjGMQ2GklmS2QJMQZhatv30n/RB+k7+F4p2AP/oFjpWf4Dojt9DuUTAMfjI6X6uOstP0IHNw0XedXOS23bnq7+Yw1DyhHBDbUAJ3/AG/ANP4C/EaI36GUu7PNk1Rm8sM342jYhM3KRC1L1792IYBgsWLKjqYp6+X09PT1XvKyIiIiIiIiKzkCcIrSugbiGkhiGX2O/LjmnQFPaypDXMgsYQGDCYzFIoTE0ImGi/gL0Xfot040rMYo6mdf/FnPuuwk71A3B+h8P3Xhbi+AaLdAG++GCWax5Ik5oNh049zTAoeqO4wRbMfBzf8EbsfIzmiA8DWN8dZ/tAErc4eyppRY4EkwpRx8bGAGhubj7k2GOOOYbzzjuPc88995Bjw+EwAKOjo5NZloiIiIiIiIgcaSyncuBU83GQT0N6+IAhHsukJeJjaUuYloiPsWyeRLYwJcspBBrpPuvfGDjhPZQsL4GhdXSufh+R3bdAuUxz0OTaCwNcsdyLacAdewq865YkG4amZj2TZpgUAk0YhTS+4Y2Y+Tg1AQ9Rn8OOwSQbe+KkcrNszSKz2KRCVNet9NAolQ79W4sPfOADrF69mtWrV0/4vvn87CqHFxEREREREZEpZJpQN7/SJ9WwKtv7ywdmDn7HYl59iEWNIQwDhpJZCsUpqAI1DGLzV7H3wm+SqT8Ws5Chec03aHvws1iZISzT4E3HefnqRQFaggZ9qTIfvj3NT9fnKJZmV1VqIdCE5SafClIT+D0WzWEffbEsa7vGGEzkZnqVIkeESYWo9fX1AAwPH/jbocPx9P3q6uqqel8REREREREROQKEWyp9Uv21EO+B4oEHIZkmNIa9LGkO0xjyMZbOVXqlTgE32ErXi65h8Pj/R8l0CPY/Rucd7yW8bzWUyxzbYPPdl4W4qLNy6NRP1uf4lzvS9M2iQ6cwDNxAM1Yujm94E6abwrZMWqM+cm6Jdd1j7B5Kzq7wV2QWmnSIWi6X2bx5c1UXs2nTJgAaGhqqel8REREREREROUL4ayoVqdG5kOgDN3PQYQGPxfyGEAubKq0Bh5K5KapKtRhb9HfsveA/ydYcg+WmaHnsOlofvgYrN0bQMbjyTD9XnuEnYMOGoSLvvCXJ6j0HBsAzxjBwg01YuRF8I5sw3DSGYVAf8uJ3bDb3JdncFyfrFmd6pSKz1qRC1BUrVgCwbds2uru7q7KQrq4utm3bhmEY4/cXERERERERkRcgxw/Ny6FhMaRHIBs76DDLhKawl8UtIRpCXkbTeVJTVZUabmffudcytOzNlA2LUO/9dNz+XoI99wNw0TyH774sxLH1FmkXvvBAhi89mCHtzpIKT8PEDbZgZYbxjWzGKGQBCHltmsJe9g2nWdcdYyytFosiBzOpEPWiiy4af/6tb32rKgt55n0uvPDCqtxTRERERERERI5Qlg2NS6BlORTykBqE8sEDyaDHZkFDiAWNQYqUGUrmKE5FVappMbrkjew976vkIvOw8zHaHv4CzY9ei5lP0hoy+cpFAd58nAfTgFt3u7z7liSbhmfJAU6GiRtswk4PVCpSnwpSHcuktcZPLO3yZNcYPWMZys/yZy3yQjWpEPXlL385Ho8HgG9+85ts3779sBaxdetWvvnNbwLg8Xi45JJLDut+IiIiIiIiInIUMAyo7axs77e8lT6ppYNvObdMaIn4WNwcpj7oZTSTIz1Fp8/naxaw77yvMrL47yljEum6k8473kOg/1Es0+Dy5T6uuzBAU8CgJ1nmg7el+dmGWXLolGHhBptxUv14RzZjFCsHS5mGQXPEh2WYbOiJsa0/Sb4wi3q7isywSYWoLS0tvO1tb6NcLpNMJlm1ahVdXV2TWsC+ffu45JJLSKVSGIbBW9/6Vpqbmyd1LxERERERERE5CoWaKgdOBRsg0QulZw9Hw16bBY1B5tWHKJTKjCTzlKYgCyxbDsPH/iP7zv0y+dAc7OwIcx74LE1PfAPDTXN8o833Xhbi/A6bUhluWJfjI6vTDKRmQTBpWuSDTXhSvXhHtmAU/7qFP+p3qPF72DmUYmNPjOQUBdEiR5pJhagAn/zkJ6mvr8cwDLZv386KFSv44Q9/SD4/sd4Z+XyeH/zgB5xwwgns3LkTgLq6Oj75yU9OdkkiIiIiIiIicrTyRaD1hMqBU/FeKOSedahtGrRGK1Wp0YDDcCpLJj81hybl6paw9/yvM7rw1QBE99xC5+r34x9cS8hj8Ikz/XzkdB9+G9YNFnnnzUnu3jcLDp0ybfLBJpxkD97RrVD665p8jkVLxEd/IseT+8YYSGRncKEis4NRPowmF3fccQcve9nLKBaLlMtlDMOgrq6OV7/61Zx++uksW7aMmpoagsEgqVSKsbExNm7cyMMPP8yNN97IyMjIeI8Nx3G45ZZbOP/886v1vR314vE40WiUoaEh6uvrZ3o5IiIicpRxXZebbrqJVatW4TjOTC9HRESkoujC4BYY2QWBOvAEnnO4WyozGM/SM5alWCpTE/BgTrqk7Ln5B9fS/MTXcdL9AIwueCXDx15O2fbRnShxzQNptoxUKlHP77D5pxN8NAWnaDETZBRd7MwA+XAnudrFYNrjXyuXy4yk8hTKZRY2BOmoD2KZRlXm1fsMmS2eztdisRiRSORZxx1WiArwu9/9jiuuuIJEIgEwHqYeytPjyuUykUiEH//4x7z61a8+nKW84ChEFRERkamkH25ERGTWKhVheCcMb6uEqL7oIS+JZwp0j6UZTecJ+xx8jjUlSzPcNI0bfkR0980A5INt9J/8IbJ1yyiUyvxkfY5fbsxTBrwW/MMyL3+/1IPXrk44Oak1F/PY6UHy0fnkao4Bc/8/m1SuwFgmz9zaAAsbQ/g9h/9np/cZMltMNEQ97F93vOY1r+Hhhx/m3HPPHa8qfeY///bxt18///zzeeSRRxSgioiIiIiIiMjEmBY0LIKW46GQh/TwIS+J+G0WNYVprw2SdYuMTlWvVCfAwMr30X3m1bi+ejypHube/THqN9yAUy7wthU+vv3SIMsbLXJF+Mn6HG+7Kclde10Os85t8mu2PBQCDXhju/CO7YDy/n8wQa9NU9hH12iGdd1jjKYm1spR5GhSlZrxxYsXs3r1ah544AEuv/xyOjo6nvV//HK5TGdnJ1dccQUPPPAAd9xxB8ccc0w1liEiIiIiIiIiLxSGATUdlT6pWJUDpw4RQjqWQXudn8XNEUI+m+FUjqw7Nb1S080ns/fCbxFvvwCDEnXbfkP7XR/EO7aDRbUW110Y4Kqz/DQGDAbSZT5/f4Z/vSPNjtGpWc+hlC0vrr8eT3wXntjOA4JUxzJpjfpIZAqs7RqjazRNqTQzoa/ITDjs7fzPZt++fezdu5eRkRESiQThcJi6ujo6OzuZO3fuVEz5gqPt/CIiIjKVtM1ORESOGOkR6N8A2RiEWw7Yjn4w+WKJ/liW3ngWo2wQDThMoDvhpAR77qdpzbew8zHKhsXIkjcysvgNYNpkC2X+Z3OeX23KkSuCacDLFzhcsdxLjW/6+6UahQx2doxc7THkI/M52B9KLOOSzhfoqAuwoDGEx37+69T7DJktJrqd337Wrxym9vZ22tvbp+r2IiIiIiIiIiIVgTpoWwkDGyHeC+FmsJ47mPNYJu11AUI+h+6xNEPJLBGfB69T/eAy1XYWe+uPo/HJbxHuuZ/6zT8j1HMfAyveBQ3H85bjvbx0vsP3n8xy594Cf9rhctdel7cc7+VVx3iwq3SY00SUbT9Fbxnv6DbAJB/pPCBIjfodvLbJruEUGbfIMc1hQt4pi5hEZoWZPQJORERERERERKQavGFoOQFq5kKiDwrZCV1WG3A4pinMnJpA5QCltHuorgCTUvRG6Tv14/Se8hGKThhvfDft915J82PXYWVHaQqaXHVWgK9cGGBRrUnShe88keMdN6d4pLdQ/QU9h5IToOiN4BnbipPYe9A2CT7HojXiZyCRY3NvfMraIojMFkd1iJrP5/npT3/KqlWr6OzsxOfz0drayllnncW1117L0NBQVecbGhrixhtv5KqrruJVr3oVxx13HLW1tTiOQyAQYM6cObz0pS/lmmuuobu7u6pzi4iIiIiIiLzgOT5oPh7qF0FqCPLJCV3mtU066gIc0xLC55gMJbNk8lMQChoGybnnsfvi7xGb9zLKGET2rabztndSs+NGKBVZ3mTzzYuDfOhUHzVeg33xEp+4K82n7k7TlZi+oLLkBCk5IbyjW3CSB88wLNOgJeJjKJFja3+CQnEKTuoSmSUm1RP1c5/73FSsZT+f/vSnD+v6zZs3c+mll7JmzZpnHdPU1MT111/PqlWrDmuup73iFa/gT3/604TGer1ePv7xj/OpT30K05xclq2eqCIiIjKV1KtMRESOWKUSjO6Coa2VYNVXM+FLc4USA/EcA4ks+WKJqM/BmUTPz4nwjm6l6cnv4BvbVpk7Mo+BFe8i23A8AMl8mf/ekON3W/MUy2Cb8NrFHi47zkvQmZ4t/mY+julmydUfixtqO+gYt1hiMJFlQWOIRU0hjAk0l9X7DJktJtoTdVIhqmmaE/of4nAUi5P/7UpXVxenn346PT09ABiGwbnnnsvChQsZHBzktttuI5PJAOA4DjfffDMXXnjhYa/5mSFqQ0MDy5Yto7Ozk1AoRDqdZvv27Tz88MMUCn8tw//Hf/xHfvzjH09qPoWoIiIiMpX0w42IiBzRymWIdcHgZqAMwcbndXkyX6BvLMtwMo9hQNTvYZI1UIdYZ4nInr/QsOHHWG4CgHj7BQwd9zaKvloA9sWLfOeJ3Pi2/lqfwdtWeHnJfAdzivMZACsXwyi6ZOuPpRBsOeiYrFtkNJ1nWWuE9rrAIe+p9xkyW0x5iDqVDMM4rBD13HPP5Z577gGgs7OTG2+8kRNOOGH860NDQ7zxjW/k9ttvB6Curo4dO3ZQU1NzWOu+9tprCYfDXHTRRSxatOigY/r7+/nQhz7EL37xi/HP/c///A+vf/3rn/d8ClFFRERkKumHGxEROSokB6B/I7iZyoFTzyN0LJdhLOPSF8swmnbxORZhrw1TkFua+TgNG39CZPctGJQp2gFGlr2JsfmvANMC4KEel+8+kaMrUdk2f0ytyXtP9nFcw9Qf6mRlRzHKpUqQGmg+6JhE1iVXKHL8nBoaw97nvJ/eZ8hsMaUh6vnnnz/llairV6+e1HU33XQTl1xyCQAej4dHH32U5cuXHzAulUqxYsUKdu7cCcDHP/5xvvCFL0x+wc9DuVzmxS9+MXfccQcAL37xi7n11luf930UooqIiMhU0g83IiJy1MiMQv+Gyj/DLWA+v9CxUCozksrTO5Yh5RYIexx8HmtKlnqoLf5usczvtuX57w050m7lmgs7bd5+go/GwNQWvVnZEQwMsnXHUggcvLJ3OJnDtk1WzI0S8T37+we9z5DZYkpD1Nnskksu4aabbgLgn/7pn/iv//qvZx37s5/9jDe/+c1ApRq1v78f2576394A/Pd//zdvectbAKivr5/UIVcKUUVERGQq6YcbERE5quSSMLAJEr2VilTL8/xvUSgxEM/Sn8jhTmW/1INt8Z97AUPH/3WL/2i2xPVrc9y806UM+Cx447FeXr/Eg9eeusI3KzMEhk22/jiK/oNnEX3xDLUBD8fPieJzDh42632GzBYTDVGn9lcU0yyZTI5v0Qd461vf+pzjX/e61xEKhQAYGRnh7rvvntL1PVNj419/Y5NIJKZtXhEREREREZEXJG8IWldATSck+ivb+5/vLWyT9roAS1rCNIa8JLIFRlN5StU+lN4wic97Gbsv/h6xeS+jjEGkazWdt72Tmh03QqlIrc/kw6f5+eZLghzXYJEtwg3rcrz9z0nu2ecyVTVzRX8DRsnFN7IJKzt60DFNYR9DiRxb+xMUitX+wxGZGUdViHr//feTy+UACAaDnHrqqc853ufzceaZZ45//PT2+umwcePG8efz5s2btnlFREREREREXrBsLzQfBw3HQHoEcpMragp7bRY2hljcEibssxlO5UhmC1Dl3LLkiTCw8n3sO+86sjXHYBXSNK77Ph13/jO+ofUALK6z+OpFAT5xpp9Gv0Ffqszn7svwkdVpdo5N/ryZ51IINGIUs/iGN2Hmxg74umkYNEV89Ixl2DWUmrJAV2Q6HVUh6qZNm8afL1++fEJb80866aSDXj+Venp6uPbaa8c/nsyhUiIiIiIiIiIyCZYNDUsqYWouVemTOgmGAbUBh2OawyxsDGIYMJjMks1XP7jM1S5m33nX0r/yfRSdMN74btrvvZLmR6+rHPhkGFzQ6fDDS0K8+TgPHgueHCjy7ltS/GZzbkpCzIK/EaOQwje8ETMXO+DrjmVSH/SyayhF12i66vOLTLejKkTdsmXL+PPOzs4JXdPR0TH+fPPmzVVf09PS6TQbN27kuuuu48QTT6SnpweAZcuWceWVV07ZvCIiIiIiIiLyN0wT6uZXtveXS5AcmPStbNOgOeJjWWuE9toAuWKJoWSOQqHKwaVhPfsW/+2VLf5+2+Dy5T5+tCrE2XNtSmX43pocn78/Q9qt9noMCoEmTDeJf2h9pVfq3/A5FiGvzfaBJIOJXHXnF5lm03OK0jQZHh4ef97c3Dyha1paWsafj4yMVG0t9957L+ecc85zjlm1ahU/+9nPCIfDE7pnLpcbb1cAlca3UGnG7Lru5BcrIiIichBPv7/Q+wwRETlqBZqgwYTBLTDaA+EmMCZXb2Ya0BL1EfLZDMRzDCfzWIZB2O9gVrGErWiH6V3xXkbbL6Z53Xfwj22ncf33Ce+5lf4V7yJTfxwNfoNPnunjD9td/uvJHHfvK7BrLMUnz/LRGT34QU+TXo+vCTs7gmdgHbmahRSCrZUy3acEHYNcrsimnlHMtggRX+UQKb3PkNliov8NHlUhajKZHH/u9/sndM0zxz3z+qlUW1vLt7/9bd74xjc+r+uuueYarr766gM+v3r1agKBQLWWJyIiIrKfW2+9daaXICIiMk16qn7Hvqrf8WmNMO+TdA7fxbE9v8aX2E3nfVeyr/YsNsx5IzmnhiU+eN+xcP1Wi32JEu+/NcWlC0uc1FDt7f1PpcRDO4Gdzzrq3oNsANb7DJlp6fTE2k0Y5aOou+9FF100fjjUpz71KT73uc8d8po77riDiy66CADLsigUClVZy86dO/nKV74CQLlcJpFIsGXLFh5//PHxOS644AK++93vsnjx4gnd82CVqO3t7fT29lJfX1+VdYuIiIg8zXVdbr31Vi6++GIcx5np5YiIiEytfBqGtkC8t1KRankO+5ZuqcxoMkd/PEfaLRD2Onid6laCApj5OI2bfkLNnr9gUKZoBxhachmj818BpsVYtsR/PJhlzUClX+trjnH4fyu8OJZxiDs/P4abxs7FyIfn4EYXULa8418rlcv0xbO0Rn0saQ5TLhX1PkNmhXg8TkNDA7FYjEgk8qzjjqpKVJ/PN/48n89P6JpnhpITrV6diAULFvDNb37zgM/39PRw1VVXccMNN7B69WrOOOMM7rzzTlasWHHIe3q9Xrxe7wGfdxxHLzgiIiIyZfReQ0REXhCcKHhPAI8fRndDoBY8wcO7pQWB2gD1IR+DiexTYWqeGp8H265igOmLMnTi+0nMeylNT34H39g2mjf8gJp9t9NzxqeoDzTxH+cHuGFdjl9uyvO7bS5bR0t86iw/DYEq9hrwBinbHgLJLtxygVzNMZQ8IaBSq9octehLZAn68nTWVvINvc+QmTbR//6OqoOlQqHQ+PNMJjOha5457pnXT5W2tjauv/56PvCBDwAwOjrKG9/4RorF6p/eJyIiIiIiIiLPg+2F5mOhaRlkE5CuztkpPsekvS7AkpYwDSEvsazLWNql2nuDc7WL2XfetfSvfB9FJ4w3vou593wUJ7EPyzT4fyf4uPpFfoIObBwq8u5bUqzpr86O3KeVLYd8qAU73Y9vaB1WdnT8a45lUh/0smsoRc/YxHIbkdniqApRn7mlvb+/f0LX9PX9tTtJXV1d1df0bK655prxEuFNmzbx5z//edrmFhEREREREZFnYVpQvxDaTgBMiPdBuVSVW4d9NgsbQixuCeH3mAwls+Tc6tx7nGERn/cy9l74DXLhdpzMEHPv+Rjese0AnDXX4VsvCbGgxmQsV+Zjd6b51aYcVe32aFi4wVbMQgr/0Frs1F+zF59jEfLa7BicnnNpRKrlqApRlyxZMv58z549E7pm796948+XLl1a9TU9m0AgwFlnnTX+8X333Tdtc4uIiIiIiIjIczAMiLTBnJXgr4F4DxSrc4q8aUJdwMMxTWHm1gZI5QuMpapflVrwN9D1ov8gW7MIOx9nzr0fxz+0DoA5YZOvvzjIxfMcSmX4wZM5rr43QypfzSDVoBBoomwY+IbW4YntHg+jwz4Hk0o7g3i2On+uIlPtqApRly1bNv583bp1Ezok6vHHHz/o9dOhtrZ2/Pnw8PC0zi0iIiIiIiIih+CvhbaVEJ0LiT5wJ3aK90R4bZP22gCLm8P4vVNTlVryRuk++wuk64/HKmRou/8zBPseBsBnG3zkdB8fPMWHY8J93QXee2uKXWPVbTdY9NZQ8oTwjmzGO7oVo1g5w6YuVOmJun0gSdZVi0OZ/Y6qEPWss84aP3gplUrx6KOPPuf4XC7Hgw8+OP7xhRdeOKXr+1u9vb3jz6ezlYCIiIiIiIiITJDjh+bl0LgUMjHIjFXt1oYBtQGHxc1TV5VacgL0nHU1yZbTMEt5Wh/6POF9q5+a3+CSRR6+elGQpoBBd6LE+29NcdvuiR3WPfE1BCkE6vHEduMd3ojxjDB6JJVna38Ct1jltgYiVXZUhaihUIiLLrpo/OMbbrjhOcf/9re/JZFIAJUQ89xzz53K5e1neHiYBx54YPzj6a6CFREREREREZEJsmxoOAZaV1S2pCf6qGbS6bEOrEqtZnVm2fLSe9oniM+9AKNcovmxrxDd+afxry+pt/jOS4Oc0mKRK8IXH8zyn49myBer9z2WLS9usAkn3Yd/aD1mLgZAY8hLz1iG3UMpSqUq9zQQqaKjKkQFeM973jP+/IYbbmDDhg0HHZdOp/n0pz89/vE73vEObNue9LwjIxM/sa9UKvG+972PXC4HgNfr5RWveMWk5xYRERERERGRKWYYlW39bSeCNwyxbihV72T7v61KzbjF6lalmjb9J3+IsfmvwKBM09rvULvlV+NhcMRr8vlzA7z5OA8Af9ju8i93pBlIVbFC1LRxgy2Y+Ri+oUpe41gm9UEvO4dSdI9Vr12CSLUddSHqJZdcwjnnnANUtuu/4hWvYO3atfuNGR4e5jWveQ3bt1dOpqurq+NjH/vYQe+3e/duDMMYfzxbdetPfvITTj31VH7yk58Qj8efdX1r165l1apV/PKXvxz/3Ec+8hHq6+ufz7cpIiIiIiIiIjMhUFcJUiNtEO8FN1PV23ssk466AMc0hQl4repWpRomgyveyfCSNwLQsOmnNGz40XiQapkGly/38flz/YQ9sHm4yLtvSfFYX/XCYgyTQrAZqISzdnwfPtsk7LXZNpBkIJGt3lwiVTT50stZ7Oc//zmnnXYavb297N69m5UrV3LeeeexcOFCBgcHue2220inK7/dsG2bX//619TU1Bz2vI8++iiXX345tm2zdOlSlixZQm1tLYZhMDw8zNq1a8eD26e97nWv4zOf+cxhzy0iIiIiIiIi08QTrGzt9wRgeAd4Q+CLVnWK2oBD0GvRH8vSG8+SyRepCXgwjMO8sWEwsuzNlJwQjet/QO32/8PMJxlY+T4wLQBOb3P41kss/u2+NNtGS3z8zjSXL/dy6bEezMNeQEXRVwuM4hvdSgGXcHQB+YLB1v4kXtsi6neqMo9ItRyVIercuXO54447uPTSS1mzZg3lcpk777yTO++8c79xjY2NXH/99fv1UZ2spw+0AigUCqxfv57169c/6/hwOMxnP/tZ/vmf/xnLsg57fhERERERERGZRpZTOWzKE4TBLZAcgGAjh59y/pXHMmmvCxDyOfSMZRhKZgn7HHzO4ecIY4teQ8kJ0vTEN4juvRXLTdF3ykcoW5XwsjVk8rUXB/nmY1n+vNPlhnU5Ng8X+egZfsKe6n2PBV8N3thOzEKOhtpj6EsX2dqfYPmcaFW+T5FqOSpDVIClS5fy0EMP8ctf/pJf/OIXbNiwgf7+fmpqaliwYAGvfe1reetb30pDQ0NV5nv3u9/NRRddxG233cZDDz3Ehg0b2Lt3L2NjYwBEIhFaW1tZuXIlL37xi3nd615HKBSqytwiIiIiIiIiMgMMA2o6wAnAwCaI90C4Gczqxi1TVZUa77yYohOk5dEvEeq9n9YHP0fv6Z+gbPsB8FgGHz7Nz7ENFv/5aJYHewq855Ykn3lRgEW11Qk4y7YP127Ek+zCLOVorllMd7LM1v4Ey1ojONZR14lSjlBGuVzF4+RkWsXjcaLRKENDQ+qpKiIiIlXnui433XQTq1atwnG0pU5EROQ55RKVitR4D4SawPYe+ppJGE279IxlGMvkiVSpKtU/sIa2hz6PWcySqV1Cz5mfpeQJ7zdm+2iRq+9N05cq47Hg/Sf7eNkCz6TnLJbKbNk3ypL2WizTgHIRJzVAyQmTjC6ipxBiQUOIRU0hTLN6la8if+vpfC0WixGJRJ51nOJ8EREREREREZHD5Q1DywqoWwipoUqoOgVqAw7HNIfoqA2QcYuMpvIcbnlcpmklXWf/O0UnhH90C3PvvRIrO7LfmEW1Ft9+aYjT22zyRbju4SxffThDvlil2jzDwg22YJSyhEc30FoeYvdQkq7RdHXuL3KYFKKKiIiIiIiIiFSD7YGmZdB8HLgZSA1y2AnnQTzdK3VxU5ig12YomSPrFg/rnrm6JXSd8x8UfHV443uYe8/HsFN9+40Jeww+d46fK5Z7MYCbdrp88LYUg+nSYc09zjAo+BsomTaR+GYacvvY3h9jIJGtzv1FDoNCVBERERERERGRajFNqJsPbSeC5YVEL5QOL+B8NjVPVaW21/rHq1JLh5Fn5iPz2HfOl3ADzXhSvbTf81E88T37jTENgzcd5+UL5wWIeAy2jZb4l9tTDKSqFKQCJW+UoidCfWYX4dhWtvUME8u4Vbu/yGQoRBURERERERERqbZQUyVIDTZU+qQWclMyzd9WpQ6nDq8qtRBsYd85XyIX7sDOjjD3nivxjm45YNwprTbfekmQ1qBBb6rMv9yRor+KQWrZCeD6G2gs9OH0r2fL3l5iaQWpMnMUooqIiIiIiIiITAVfBFpXQu38Sp/UfHLKpqpmVWrRX0/XOf9BtnYxlptg7n2fxD/45AHjWkIm110UpC1k0pcq8y+3p+hNVjFItTy4wRYajTHM3jVs3rGdwcTUhNEih6IQVURERERERERkqtheaD4Wmo6FXBLSw1M21cGqUnPu5ELNkidC19n/TrrxBMxChrYHPkOw54EDxjUGTK67MMDcsEl/usy/3lHdIBXTohBqpc5bxD/wJDs3PU7PcJzyFPSaFXkuClFFRERERERERKaSaUH9gsr2fsOqbO8vVzFo/BtPV6XOrfWTzLmksoVJ3ads++k547MkW8/ELBVofeQawntvP2BcQ8Dk2gsDtIdNBtKVitTuRBW/P8Og6G8gEKklkthJ14YH2NfTQ6mkIFWmj0JUEREREREREZHpEG6pBKn+eoh1Q2HqTp33WCbttQHmNwQplMqMpVyYROZYthx6T72SeMeLMcolWh7/KjU7bjxgXL2/EqR2REwGM5WK1K5EdQ/UKjsB7No5RIqj9G+6n907tlAoTC4gFnm+FKKKiIiIiIiIiEwXfw20rYS6hZAerWzvn6Kt6YYBzREfi5pCeB2DoVRucn1STYv+Ez/A6MJXA9C47vvUbfrZAeuueypInRc1GcqU+Zfb0+yLVzdIxbSwaucQ9nsZ3fkIuzY+QjY9db1mRZ6mEFVEREREREREZDo5vkqf1LYTwfRAvBsKU3dgUk3AYVFTmNqAh+FUlkJhEqGtYTJ0/NsZXvomAOq3/IKGdf91QFuCWp/Jly4IMD9qMpIt8693pNkTq3KQCljBWoK1LSR6trF33T2kRvuqPofIMylEFRERERERERGZboYBkVaYezLUzIPUEKRHpmy6gMdiQWOQlqiP0UyebH4SwaZhMLL0UgaWvxOA2p1/oPnxr0Fp/3vV+ky+fGGABTWVIPUjq6coSPX4CDZ2kojH2LvuHhJdW6Co7f0yNRSiioiIiIiIiIjMFE8Qmo+rbPE3LIh1QTE/NVNZJp11IebVB0jniyQmeeBUbOEr6Tvpw5QNk8i+O2h57Doo7x+SRr0mX74gwMIak9GnKlJ3jVU/SDUtk0jDHFIlL/u2PsrIjkchl6j6PCIKUUVEREREREREZpJpQnRupSo1OheSA5Adm5KpLBPaavwsag5hACPJ/KRasiY6LqT3tE9QNizC3XfT/MQ3DtjaH/GafOmCIMfUmozlKhWpO6cgSMWAaE0tGU8j3Xu3M7jlfsqx7inrNSsvTApRRURERERERERmA28YWlZA6wlQKkO8B0pTsz29PuhhUVOIoM9iKJmlWHz+gWOq9Qz6TvkIZUwie2+jce33DgguI16DL14QZHGdSSxX5iN3pNk+OgVBKhAJ+SmE5rBvMEH/5oco9W+a0l6z8sKiEFVEREREREREZLYwLajpqFSlhlog3gfZ+JRMFfbZLGoM0xj2MZLOkS+UDn3R30jOeRH9J3+IMgY1u/5Ew4YfHRCkhj0GXzw/yNI6k3i+zEdXp9k2RUFqyGfjhBvYnXHo2bkOt+uxKe01Ky8cClFFRERERERERGYbX7RSkdpyPJRciPdOSVWqzzGZ1xBkTk2AeNYlnXv+cyTaL2Bg5XsBqN3+f9Rt/vkBY0Ieg/84P8iyeotEvszH70yzL3nYyz8on8ciHIqwtxClq7uX3N5HYGTXAQdgiTwfClFFRERERERERGYjy4a6+TDnZAg2VqpS89VPHh3ToKMuwPyGIG6xzFjahee5uz8+72UMLH8HAPVbfkHt1v85YEzQY3DN+QGObbBIuvCtjRZbRqYm2PTYJrXBAL2lCLtHC2S61kLfesinpmQ+OfopRBURERERERERmc38tdC2EpqPhXwGEn1Vr6o0DGiJ+FjYFMJjGQylcpSe5+7+2MJXMXTsFQA0bPwxNTtuPGBM0DG45rwAxzVYZIoGH78rzabhqen7alsG9UEfIwUvO9IBUgM7oftxSPTr0Cl53hSiioiIiIiIiIjMdpYD9QsrVam+2sqhU/l01aepDTgsag5R43cYTmUpFJ5f2Di6+PUML7kUgMZ13yey++YDxgQcg8+f42dhuEzahStXp9k4NDVBqmlCQ8hLqmCyNRNlNJGoBKlD26DoTsmccnRSiCoiIiIiIiIicqQI1sOcE6FxKeQSkByA8vM/EOo5p/DYLGwK0RLxMZrJk3WfX9XryNLLGFn0WgCa1nyL8N47DhjjdwzeuazIikaLdAGuvDPN+sGpCVIxoC7koViG7UkvgwUv5cHN0LMGMmNTM6ccdRSiioiIiIiIiIgcSWwvNC6GOSeBJwSxbnAzVZ3CY5l01ofoqAuQzhVJZp9HwGkYDB/3VsbmX4JBmebHv0ao+94Dhnkt+Nw5flY2WWQK8PG70qwbmKIgFYgGHGzTZMdYmZ5iLaVkf6UqdWwfz7t3gbzgKEQVERERERERETkShZoq2/vrF0E2Bqmhqvb6tEyYU+NnYVOIMjCSzE/8wCnDYHDFO4l1XIxBiZZHv0yw96EDhvlsg387N8BJzRbZAnzi7jRPTmGQGvLZBL0We8ay7HFrcMtA31oY2Fj1IFqOLgpRRURERERERESOVI4PmpZB24lg+yDeDYVc1W5vGNAQ8nBMU4iA12IwmaVYnGCSapgMnPg+4nPPwygXaXnkGgIDTxwwzGcbfO6cACe3VILUT96VZk3/1AWpPsci6vfQG8uwO+WQ89TCyM7K9v58asrmlSObQlQRERERERERkSOZYUC4pVKVWjMP0sOVRxWrUsM+m0VNIRpClT6p+cIEt78bFv0nfZhk61mYpQKtD30e39D6A4Z5nwpST221yRbhk3enebxv6oJUj21SG/AyGM+yc9Ql7W+pVPIObYXi1M0rRy6FqCIiIiIiIiIiRwNPAJqPg9aVYDoQ76nqCfR+x2J+Y5C2qJ941iWdm2DYaFr0nvoRUs2nYBZzzHnwanyjWw5cvmXw2Rf5Ob3NJleET92T5tHeqQs0bcugPuRjLO2yYyhNwqmHWBeM7p6yOeXIpRBVRERERERERORoYZoQnVOpSo3OgURfVbf3O6ZBe22AefVB8sUSsfQEQ1rTofe0j5NuWIFZyND+4GeIpncfMMxjGXz6bD9ntNnki/Dpe9I8MoVBqmlCQ8hLOldk+3COkXIQhrdBon/K5pQjk0JUEREREREREZGjjTcEzcdD3UJIDkI+XbVbmya0Rn0sagpjW8aED5wqW156zvg0mbpjsdwUZ27/Ep74ngPGPR2knj3Hxi3BZ+5J81BP9SpqD2BAXchDsVRm5xgMpUuUBzZBLjF1c8oRRyGqiIiIiIiIiMjRyHKgaSk0LoXsWNVDwdqAw8KmEAGPxUhqgkGq7aPnzM+SqTkGbzFJxwOfxEl2HzDOsQw+ebafF82tBKmfuy/D+sGp7VUaDThYpsGOpJeB4SFKg1ur2g5BjmwKUUVEREREREREjlamBQ2LoOnYSjVqeqSqtw97beY1BPF7TEbT+QldU3IC7DvjamK+duzcGHPuuwo7deD2eds0uOqsv27t/9TdaXaNFau6/r8V8tkEvDa7MkF6926nMLSjqgd0yZFLIaqIiIiIiIiIyNHMMKBuPrSuAMqQHKjq7cM+m/kNITy2yWhygkGqJ8z9iz5GLjQXJzPE3Ps+gZUZOmDc00HqsQ0WSRc+flea/lSpquv/Wz6PRTgYYF/OT8+OdeTGDqyUlRcehagiIiIiIiIiIi8EkTZoOQFsH8T7qlphGfbZLGgI4Tgmo6mJBal5J8K+sz5PPtiKk+5n7n2fxMqOHjDOZxv82zkB5kVNhjNlPn5nmlhuaoNUj20SjdTQny6zb8sTZOIHrkteWBSiioiIiIiIiIi8UIQaKxWpvjDEe6BUve3xEf9TQaplMpaaWC/Rgq+e7rP/HdffiCfZxZz7P4WZjx94b6/BF84L0Bgw2JcocdVdaTLu1G6zty2DSF0r8dgYu7c8TiKVmtL5ZHZTiCoiIiIiIiIi8kLir4XWlZVANd4Dpeod2BT128xvCGJbBmPpCQapgSa6z/53Cr46vPHdzLn/05j55AHjGgMm/3F+gIjHYMtIiavvS+MWpzZINU0INbSTG+lmx6a1jCZzUzqfzF4KUUVEREREREREXmi8IWhZATXtEO+FQvXCwZqAw7yGIJZpEJtgkOqG2ug6+98peKL4xrbT9uBnMQqZA8Z1RCw+f54fnwWP9RW59uEMpSk++MmwLEJ1rRhju9i6bTMD8eyUziezk0JUEREREREREZEXIscPTcdB3QJIDoKbrtqtawMO8xuCGCbEMxOrdHXD7XSf/W8UnSD+kc20Pfg5jOKB4e6yeptPvyiAZcAdewp874kc5SkOUsuOj3A4jC+2k82799I1mp7yOWV2UYgqIiIiIiIiIvJCZXugaRk0LoHMGOQSVbv100FqmTKJCQap+egCus/6N4q2n8DQOlof+gJG8cBq1lNbbT5yuh+A327N86tNEzvM6nAUvTVEnALRxC42dw2zeyhFqaQg9YVCIaqIiIiIiIiIyAuZaUH9Img6FnKpSphaJXUBDwsagpTKZRLZiQWpudrF9Jz5WUqWl+DAY7Q8+sWD9m29aJ7Du0/0AvDDtTlu3jn1QWoh0Ei0NEpjfi9b+mJsH0hSKJamfF6ZeQpRRURERERERERe6EwT6uZD6/JKYJkaqtqt64Ie5jUEKZZKJCcYpGbrj6PnjE9RMh1CvQ/S8ui1Bw1SX7vEyxuXeQD46iNZ7u+eWA/WSTMsCoEGopluWhlm51CSzX0JcoXi1M4rM04hqoiIiIiIiIiIVETnQusJYNqQ6IUq9f1sCFWC1MLzCFIzjSvpPe0TlA2bcM+9tD78Hwfd2v+2FV5eOt+hVIZ/vz/DuoGJ3X+yypaXohMgktpFq5OhazTNpp446fzUziszSyGqiIiIiIiIiIj8VaipEqR6wpDogXJ1tqs3hrzMqw/ilkqkJhikpltOpeeMT1IyPYT6HqT1oc8fcNiUYRh86FQfZ7TZ5IvwqXvS7Bqb2srQkjcKRZdQfAetAYP+RJb13THi2SmuhJUZoxBVRERERERERET2F6irBKmBBoj3HHQr/WQ0hitBav559BFNN59Cz5mfGe+R2vbA1RiFzH5jLNPgqrP8HNdgkXLhyjvT9CWntldpIdCInR3Bn9hJS9hLLOOyvivGcDJ36IvliKMQVUREREREREREDuSLQMsKCLdBvBeK1Tm4qSnspaPOD0AmN9Gt/SfQfdbnKNp+AkNrmXP/ZzDd1P7LtQ3+7dwA86ImI9kyH78rzVh2CoNUw8QNNOCJ78Ob7KI57CPrlljfE6M/np26eWVGKEQVEREREREREZGD8wSgZTnUzodEP7iZQ18zAU0RHwBZt0QmN7Gt99n64+g++/MUnSD+kY3Mue+TmPnEfmPCHoNrzgvQHDDoSpS46u40abc6fV0Ppmx5KHrDeGM7sbMjNIa9GBis74mxbyRNuUo9ZWXmKUQVEREREREREZFnZ3ugaRk0HAPpEcgnq3br9jo/abdIJj+xIDVXu4Tus79A0RPBN7aNufd+AisX229MQ8DkmvMDRL0GW0dKXH1vGrc4dWFmyROGchHv2DaMQobagAe/bbG5L87OwRTFkoLUo4FCVBEREREREREReW6WDQ1LoOlYyCUhGzv0NRPQFPHRWR8gnS+QnWiQWrOQrhddQ8Fbgze+izn3XomVHdlvTHvE4t/PDeCz4fH+Il96KENpCqtCC/5GrOwY3rEdUCoS9jlEfA7bBpJs60/gPo8esDI7KUQVEREREREREZFDM02omw/Nx0EhD+nhw76lYUBLxEdHXYBkvkDWnViQmo900nXOF3F99XgT+5h7z8ew04P7jVlSb/GZswPYJty5t8B3Hs9N3fZ6w6AQaMST7MKT2AdAwGPTEPKwezjFpt74hL83mZ0UooqIiIiIiIiIyMQYBtR0QOsKwIRkPxxmMGkY0Br1014bIJmbeJDqhuZUgtRAM55UL3PvvRI71bffmFNabT5yeuUQq99ty/OLjdU5HOtgypZDwRPBE9s5Huh6bYumsI+esQybeuOkJniQ1v9v777jpCzv/f+/73v6zPa+S1kElKKI0SCiYsOSoOSY+DVH1BM1ekxikhNT1ZgokqiJSU6SX47HFOvReEw9lmiKJQgoKIgIKL3Dsr3MTq+/P0bGXWF3Z3Znd9nl9Xw8eHjPznVfn2sGwuPOm6vgyEOICgAAAAAAgOzkV0nVMyWrO3Xg1AAZhlRT6NLYIrd8oajC0cyWv8c8Vdp35g8U8VTLFmjQ2GW3yObb363NebU23XSyQ5L0yPqwXtg+eEFqwp4nGZK9favMqF+SZLOYqipwqdEb1ob9HfKGooNWH4OHEBUAAAAAAADZ85RK1TMkm0vyNw+4O9OUxhS5NLbYLW8ookgswyDVXa59c3+ocP442UItGrvsFtm9u7u1+eRxDi2cbpck/Xx1SK/tG7wgM+YslSXSKXv7dimRmnlqMQ1VFzrlDUW1iRmpIxIhKgAAAAAAAPrHVSxVTEst6c/BYVOpINWtscVudQSjGQepcWeJ9p95r8IFE2QNt2vM8ttkb9/Rrc11Mxz62ESbEknp7teDWtc4SEGmYSjqLpfNt79bmGsYhirynWrzR7Wpnj1SRxpCVAAAAAAAAPRffqVUMVWK+KVIYMDdHQxSxxS51BHMfEZq3FGkfWfeq1DRsbJGvBr72m1ytG1Ov28Yhm7+qFOnj7EqmpDuWBbQjvZBCjJNq+LOYtk7dsoa+GC7A9MwVFngVFNnRJvrOzP+bBh+hKgAAAAAAAAYmMJxUulxUqBVioUH3J3FlMYWu1VTlFraH80wbEzY87X/jO8rWDJNlqhfY177jpwt73bp19C357g0o9wif1S6bUlAB3yDE2QmbG4lTYscbdtkRnzdxlCZ79CBjqC2NXYqFidIHQkIUQEAAAAAADAwhiGVTpSKJ0i+xvReoANhMaVxxW5VFbjUHowoFk9mdF/C5tH+0xcrUHaiLLGgxrx+h1xN76Tfd1gNLZ7r1jGFplpDSd26JKC20OAEmXFnicyoT472rVLig31YrRZTFflO7W0NaHuTX/FEZp8Nw4cQFQAAAAAAAANnWqTyKVJBjdTZICUHHkxaTGlciTu1l2ggrESGXSatLtXNuVP+ipNlxsOqWbFI7obV6ffz7IbuOcetKo+hOl9Ct78aUCA6CEGmYSjqrpA1UC97x67U3rHvs1lMlXgc2tXi165mv5JJgtQjGSEqAAAAAAAAcsNqTx005SqROhtz06VpaHypWyUeh1oDISnDrDFpcejA7O/KVzVbZiKqmpXfl6duRfr9Mpepe892q9BhaGtbQncuG6Qg1bQo5iyR3bur2/6okuS0WVTksml7k097Wwe+nywGDyEqAAAAAAAAcsfukSqnSTaX5G/OTZcWU7WlbuU7bWr1RzK+L2mx6cCpt6mz5kwZyZiqV92rvH1L0++PLbDo7rPdclmltY1xfeMV/6As7U9aXUpa7HK0bZUZ8XZ7z223Kt9p05YGn+ragzmvjdwgRAUAAAAAAEBuuYpTM1KTSSnUkZsubRbVlnhkt5nqCET7vuEg06r6j35T3nHnykgmVLX6x8rf83L67SklFv3oXI+K3p+R+h8v+rWvM56TMXcVdxbLjAVkb99xyJ6xeQ6rnDaLNtd71egN5bw2Bo4QFQAAAAAAALmXXylVTJUifimSm6Xq+U6rJpR6JEPyhbI4vMq0qOHkr6qj9kIZSqhqzU9VsOtv6benlFr0s/M9qvYYqvcndfNLAW1qyX2QGnWXy+avl71z3yHvFbpsMg1Tm+o7s5pti6FBiAoAAAAAAIDBUThOKj1WCrRKsXBOuix221Rb4lYkllAokkXQaZhqPOlLaj/mEklS5dr/UuH2Z9Nvj8k39fMLPDquxFRHOKlvvuLXG3VZzHjNhGlV3FEgu3enLKG2Q94u8dgVjSe08YBXHcEc18aAEKICAAAAAABgcBiGVDpJKp4g+RoPWcbeX2V5Do0rcckXjioSy2IPU8NU04mfU+vkT0mSKtb/WsVb/ph+u9hp6sfnejSr2qJQXLpjWVB/3Z7bWaEJe56UiMvRsV1G/NC+y/McCkbi2njAK184N98XBo4QFQAAAAAAAIPHtEjlx0kFNVJng5Qc+MFNhiFVFbhUU+SWNxhRLJ7M6uaW469Ty5SFkqSy9x5VycbfpvZvleSyGVo8160Lj7EpkZT+c1VIj28IK5nMokYfYu5SWQLNsnXuOczwDFXkO9QRiGpzvVfBbGbbYtAQogIAAAAAAGBwWR2pg6ZcJVJnY066NE1pTLFL5flOtQXCSmSTzRq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" ] @@ -505,7 +505,7 @@ "\n", "igdp_indicator = iohinspector.indicators.anytime.IGDPlus(reference_set = ref_set)\n", "\n", - "df_igdp = iohinspector.plot.plot_indicator_over_time(\n", + "df_igdp = iohinspector.plots.plot_indicator_over_time(\n", " df, ['obj1', 'obj2'], igdp_indicator, \n", " evals_min=10, evals_max=2000, nr_eval_steps=50, free_variable='algorithm_name'\n", ")" @@ -529,7 +529,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 70, "metadata": {}, "outputs": [], "source": [ @@ -543,7 +543,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 71, "metadata": {}, "outputs": [ { @@ -558,7 +558,7 @@ } ], "source": [ - "_ = iohinspector.plot.single_function_fixedbudget(df_hv, fval_variable='eaf', maximization=True)" + "_ = iohinspector.plots.plot_single_function_fixed_budget(df_hv, fval_variable='eaf', maximization=True)" ] }, { @@ -574,7 +574,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 72, "metadata": {}, "outputs": [ { @@ -591,7 +591,7 @@ "source": [ "df = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False)\n", "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", - "iohinspector.plot.plot_eaf_pareto(df, 'obj1', 'obj2', scale_xlog=False, scale_ylog=False)" + "iohinspector.plots.plot_eaf_pareto(df, 'obj1', 'obj2', scale_xlog=False, scale_ylog=False)" ] }, { @@ -605,7 +605,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 73, "metadata": {}, "outputs": [ { @@ -652,8 +652,7 @@ "\n", "igdp_indicator = iohinspector.indicators.anytime.IGDPlus(reference_set = ref_set)\n", "\n", - "\n", - "iohinspector.plot.plot_robustrank_changes(df, ['obj1', 'obj2'], evals, igdp_indicator)" + "iohinspector.plots.plot_robustrank_changes(df, ['obj1', 'obj2'], evals, igdp_indicator)" ] }, { diff --git a/examples/SO_Examples.ipynb b/examples/SO_Examples.ipynb index 83129d5..26b8fdb 100644 --- a/examples/SO_Examples.ipynb +++ b/examples/SO_Examples.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -114,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -137,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -154,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -201,7 +201,7 @@ "└─────────┴──────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴───────────┘" ] }, - "execution_count": 22, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -219,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -235,7 +235,7 @@ " Function(id=1, name='Sphere', maximization=False)))" ] }, - "execution_count": 23, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -261,7 +261,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -271,7 +271,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -318,7 +318,7 @@ "└─────────┴───────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴──────────┘" ] }, - "execution_count": 25, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -329,7 +329,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -338,7 +338,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -349,7 +349,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -379,7 +379,7 @@ "└─────────┴───────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴──────────┘" ] }, - "execution_count": 28, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -404,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -451,7 +451,7 @@ "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘" ] }, - "execution_count": 29, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -470,7 +470,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -490,7 +490,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -506,21 +506,21 @@ ], "source": [ "#Note: we filter the data by function ID here. This is equivalent to doing the subselecting before loading the performance data. \n", - "data_singleft = iohinspector.plot.single_function_fixedtarget(df.filter(pl.col(\"function_id\") == 1))" + "data_singleft = iohinspector.plots.plot_single_function_fixed_target(df.filter(pl.col(\"function_id\") == 1))" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 32, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, @@ -540,8 +540,8 @@ "import matplotlib.pyplot as plt\n", "\n", "fig, axs = plt.subplots(2,1, sharey=True, figsize=(16,14))\n", - "data_singleft1 = iohinspector.plot.single_function_fixedtarget(df.filter(pl.col(\"function_id\") == 1), ax=axs[0])\n", - "data_singleft2 = iohinspector.plot.single_function_fixedtarget(df.filter(pl.col(\"function_id\") == 2), ax=axs[1])\n", + "data_singleft1 = iohinspector.plots.plot_single_function_fixed_target(df.filter(pl.col(\"function_id\") == 1), ax=axs[0])\n", + "data_singleft2 = iohinspector.plots.plot_single_function_fixed_target(df.filter(pl.col(\"function_id\") == 2), ax=axs[1])\n", "axs[0].legend('') #Disable legend to avoid duplication" ] }, @@ -554,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -569,7 +569,7 @@ } ], "source": [ - "data_singlefb = iohinspector.plot.single_function_fixedbudget(df.filter(pl.col(\"function_id\") == 1))" + "data_singlefb = iohinspector.plots.plot_single_function_fixed_budget(df.filter(pl.col(\"function_id\") == 1))" ] }, { @@ -581,7 +581,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "metadata": {}, "outputs": [ { @@ -596,12 +596,12 @@ } ], "source": [ - "df_eaf = iohinspector.plot.plot_eaf_singleobj(df)" + "df_eaf = iohinspector.plots.plot_eaf_single_objective(df)" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -614,7 +614,7 @@ }, { "data": { - "image/png": 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" ] @@ -624,7 +624,7 @@ } ], "source": [ - "df_ecdf = iohinspector.plot.plot_ecdf(df)" + "df_ecdf = iohinspector.plots.plot_ecdf(df)" ] }, { @@ -636,12 +636,12 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -651,7 +651,7 @@ } ], "source": [ - "rating_df = iohinspector.plot.plot_tournament_ranking(df)" + "rating_df = iohinspector.plots.plot_tournament_ranking(df)" ] }, { diff --git a/src/iohinspector/__init__.py b/src/iohinspector/__init__.py index 7bdd748..a11311a 100644 --- a/src/iohinspector/__init__.py +++ b/src/iohinspector/__init__.py @@ -1,7 +1,6 @@ from .align import * from .data import * from .manager import * -from .old_metrics import * from .indicators import * -from .plot import * -from .metrics import * \ No newline at end of file +from .metrics import * +from .plots import * \ No newline at end of file diff --git a/src/iohinspector/metrics/__init__.py b/src/iohinspector/metrics/__init__.py index a12b9f3..a6df82b 100644 --- a/src/iohinspector/metrics/__init__.py +++ b/src/iohinspector/metrics/__init__.py @@ -1,6 +1,9 @@ -from .utils import (get_sequence) +from .utils import (get_sequence, normalize_objectives, add_normalized_objectives, transform_fval) from .fixed_budget import (aggregate_convergence) from .fixed_target import (aggregate_running_time) -from .normalise_objectives import (normalize_objectives, add_normalized_objectives, transform_fval) from .aocc import (get_aocc) -from .ecdf import (get_data_ecdf) \ No newline at end of file +from .ecdf import (get_data_ecdf) +from .eaf import (get_discritized_eaf_single_objective) +from .ranking import (get_tournament_ratings) +from .attractor_network import (get_attractor_network) +from .trajectory import (get_trajectory) \ No newline at end of file diff --git a/src/iohinspector/metrics/attractor_network.py b/src/iohinspector/metrics/attractor_network.py new file mode 100644 index 0000000..9951057 --- /dev/null +++ b/src/iohinspector/metrics/attractor_network.py @@ -0,0 +1,113 @@ +import numpy as np +import pandas as pd +import polars as pl +from typing import Iterable, Tuple + + +def _get_nodeidx(xloc, yval, nodes, epsilon): + if len(nodes) == 0: + return -1 + candidates = nodes[np.isclose(nodes["y"], yval, atol=epsilon)] + if len(candidates) == 0: + return -1 + idxs = np.all( + np.isclose(np.array(candidates)[:, : len(xloc)], xloc, atol=epsilon), axis=1 + ) + if any(idxs): + return candidates[idxs].index[0] + return -1 + + +def get_attractor_network( + data, + coord_vars=["x1", "x2"], + fval_var: str = "raw_y", + eval_var: str = "evaluations", + maximization: bool = False, + beta=40, + epsilon=0.0001, + eval_max=None, +): + """Create an attractor network from the provided data + + Args: + data (pl.DataFrame): The original dataframe, should contain the performance and position information + coord_vars (Iterable[str], optional): Which columns correspond to position information. Defaults to ['x1', 'x2']. + fval_var (str, optional): Which column corresponds to performance. Defaults to 'raw_y'. + eval_var (str, optional): Which column corresponds to evaluations. Defaults to 'evaluations'. + maximization (bool, optional): Whether fval_var is to be maximized. Defaults to False. + beta (int, optional): Minimum stagnation lenght. Defaults to 40. + epsilon (float, optional): Radius below which positions should be considered identical in the network. Defaults to 0.0001. + eval_max (int, optional): Maximum evaluation number. Defaults to the maximum of eval_var if None. + Returns: + pd.DataFrame, pd.DataFrame: two dataframes containing the nodes and edges of the network respectively. + """ + + running_idx = 0 + running_edgeidx = 0 + nodes = pd.DataFrame(columns=[*coord_vars, "y", "count", "evals"]) + edges = pd.DataFrame(columns=["start", "end", "count", "stag_length_avg"]) + if eval_max is None: + eval_max = max(data[eval_var]) + + for run_id in data["data_id"].unique(): + dt_group = data.filter( + pl.col("data_id") == run_id, pl.col(eval_var) <= eval_max + ) + if maximization: + ys = np.maximum.accumulate(np.array(dt_group[fval_var])) + else: + ys = np.minimum.accumulate(np.array(dt_group[fval_var])) + xs = np.array(dt_group[coord_vars]) + + stopping_points = np.where(np.abs(np.diff(ys, prepend=np.inf)) > 0)[0] + evals = np.array(dt_group[eval_var]) + + stagnation_lengths = np.diff(evals[stopping_points], append=eval_max) + edge_lengths = stagnation_lengths[stagnation_lengths > beta] + real_idxs = [stopping_points[i] for i in np.where(stagnation_lengths > beta)[0]] + if not real_idxs: + continue + + xloc = xs[real_idxs[0]] + yval = ys[real_idxs[0]] + nodeidx = _get_nodeidx(xloc, yval, nodes, epsilon) + if nodeidx == -1: + nodes.loc[running_idx] = [*xloc, yval, 1, evals[real_idxs[0]]] + node1 = running_idx + running_idx += 1 + else: + nodes.loc[nodeidx, "evals"] += evals[real_idxs[0]] + nodes.loc[nodeidx, "count"] += 1 + node1 = nodeidx + + if len(real_idxs) == 1: + continue + + for i in range(len(real_idxs) - 1): + xloc = xs[real_idxs[i + 1]] + yval = ys[real_idxs[i + 1]] + nodeidx = _get_nodeidx(xloc, yval, nodes, epsilon) + if nodeidx == -1: + nodes.loc[running_idx] = [*xloc, yval, 1, evals[real_idxs[i + 1]]] + node2 = running_idx + running_idx += 1 + else: + nodes.loc[nodeidx, "evals"] += evals[real_idxs[i + 1]] + nodes.loc[nodeidx, "count"] += 1 + node2 = nodeidx + + edgelen = edge_lengths[i] + edge_idxs = edges.query(f"start == {node1} & end == {node2}").index + if len(edge_idxs) == 0: + edges.loc[running_edgeidx] = [node1, node2, 1, edgelen] + running_edgeidx += 1 + else: + curr_count = edges.loc[edge_idxs[0]]["count"] + curr_len = edges.loc[edge_idxs[0]]["stag_length_avg"] + edges.loc[edge_idxs[0], "stag_length_avg"] = ( + curr_len * curr_count + edgelen + ) / (curr_count + 1) + edges.loc[edge_idxs[0], "count"] += 1 + node1 = node2 + return nodes, edges \ No newline at end of file diff --git a/src/iohinspector/metrics/eaf.py b/src/iohinspector/metrics/eaf.py new file mode 100644 index 0000000..a16d713 --- /dev/null +++ b/src/iohinspector/metrics/eaf.py @@ -0,0 +1,53 @@ + +from iohinspector.align import align_data +from iohinspector.metrics import transform_fval, get_sequence +import numpy as np +import pandas as pd + + +def get_discritized_eaf_single_objective( + data, + fval_var: str = "raw_y", + eval_var: str = "evaluations", + eval_values = None, + eval_min = None, + eval_max = None, + eval_targets = 10, + scale_eval_log: bool = True, + f_min = 1e-8, + f_max = 1e2, + scale_f_log: bool = True, + f_targets = 101, + ): + + if eval_values is None: + if eval_min is None: + eval_min = data[eval_var].min() + if eval_max is None: + eval_max = data[eval_var].max() + eval_values = get_sequence( + eval_min, eval_max, eval_targets, scale_log=scale_eval_log, cast_to_int=True + ) + + dt_aligned = align_data( + data, + eval_values, + x_col=eval_var, + y_col=fval_var, + output="long" + ) + dt_aligned = transform_fval( + dt_aligned, + lb=f_min, + ub=f_max, + scale_log=scale_f_log, + fval_col=fval_var, + ) + targets = np.linspace(0, 1, f_targets) + dt_targets = pd.DataFrame(targets, columns=["eaf_target"]) + + dt_merged = dt_targets.merge(dt_aligned[[eval_var, 'eaf']].to_pandas(), how='cross') + dt_merged['ps'] = dt_merged['eaf_target'] <= dt_merged['eaf'] + dt_discr = dt_merged.pivot_table(index='eaf_target', columns=eval_var, values='ps') + + return dt_discr diff --git a/src/iohinspector/metrics/ecdf.py b/src/iohinspector/metrics/ecdf.py index 44cad57..c9dc629 100644 --- a/src/iohinspector/metrics/ecdf.py +++ b/src/iohinspector/metrics/ecdf.py @@ -1,8 +1,8 @@ import polars as pl from typing import Iterable from .utils import get_sequence -from ..align import align_data -from .normalise_objectives import transform_fval +from ..align import align_data, turbo_align +from .utils import transform_fval @@ -20,6 +20,7 @@ def get_data_ecdf( y_min: int = None, y_max: int = None, scale_ylog: bool = True, + turbo: bool = False ): """Function to plot empirical cumulative distribution function (Based on EAF) @@ -49,14 +50,23 @@ def get_data_ecdf( x_values = get_sequence( x_min, x_max, 50, scale_log=scale_xlog, cast_to_int=True ) - data_aligned = align_data( - data.cast({eval_var: pl.Int64}), - x_values, - group_cols=["data_id"], - x_col=eval_var, - y_col=fval_var, - maximization=maximization, - ) + if turbo: + data_aligned = turbo_align( + data.cast({eval_var: pl.Int64}), + x_values, + x_col=eval_var, + y_col=fval_var, + maximization=maximization, + ) + else: + data_aligned = align_data( + data.cast({eval_var: pl.Int64}), + x_values, + group_cols=["data_id"], + x_col=eval_var, + y_col=fval_var, + maximization=maximization, + ) dt_ecdf = ( transform_fval( data_aligned, diff --git a/src/iohinspector/metrics/fixed_budget.py b/src/iohinspector/metrics/fixed_budget.py index 48ebb16..dea4b4d 100644 --- a/src/iohinspector/metrics/fixed_budget.py +++ b/src/iohinspector/metrics/fixed_budget.py @@ -1,6 +1,6 @@ import polars as pl from typing import Iterable, Callable -from .utils import get_sequence, geometric_mean +from .utils import get_sequence from ..align import align_data def aggregate_convergence( diff --git a/src/iohinspector/metrics/fixed_target.py b/src/iohinspector/metrics/fixed_target.py index 27495c3..2df7ec5 100644 --- a/src/iohinspector/metrics/fixed_target.py +++ b/src/iohinspector/metrics/fixed_target.py @@ -1,6 +1,6 @@ import polars as pl from typing import Iterable, Callable -from .utils import get_sequence, geometric_mean +from .utils import get_sequence from ..align import align_data def aggregate_running_time( diff --git a/src/iohinspector/metrics/normalise_objectives.py b/src/iohinspector/metrics/normalise_objectives.py deleted file mode 100644 index bdc88ad..0000000 --- a/src/iohinspector/metrics/normalise_objectives.py +++ /dev/null @@ -1,127 +0,0 @@ -import polars as pl -import numpy as np -import warnings -from typing import Iterable, Optional, Union, Dict - - -def normalize_objectives( - data: pl.DataFrame, - obj_cols: Iterable[str] = ["raw_y"], - bounds: Optional[Dict[str, tuple[Optional[float], Optional[float]]]] = None, - log_scale: Union[bool, Dict[str, bool]] = False, - maximize: Union[bool, Dict[str, bool]] = False, - prefix: str = "ert", - keep_original: bool = True -) -> pl.DataFrame: - """ - Normalize multiple objective columns in a dataframe. - - Args: - data (pl.DataFrame): Input dataframe. - obj_cols (Iterable[str]): Columns to normalize. - bounds (Optional[Dict[str, tuple(lb, ub)]]): Optional manual bounds per column. - log_scale (Union[bool, Dict[str, bool]]): Whether to apply log10 scaling. Can be a single bool or a dict per column. - maximize (Union[bool, Dict[str, bool]]): Whether to treat objective as maximization. Can be a single bool or dict. - prefix (str): Prefix for normalized column names. - keep_original (bool): Whether to keep original objective columns names. - Returns: - pl.DataFrame: The original dataframe with new normalized objective columns added. - """ - result = data.clone() - n_objectives = len(obj_cols) - for col in obj_cols: - # Determine log scaling - use_log = log_scale[col] if isinstance(log_scale, dict) else log_scale - is_max = maximize[col] if isinstance(maximize, dict) else maximize - - # Get bounds - lb, ub = None, None - if bounds and col in bounds: - lb, ub = bounds[col] - if lb is None: - lb = result[col].min() - if ub is None: - ub = result[col].max() - # Log scale if needed - if use_log: - if lb <= 0: - warnings.warn( - f"Lower bound for column '{col}' <= 0; resetting to 1e-8 for log-scaling." - ) - lb = 1e-8 - lb, ub = np.log10(lb), np.log10(ub) - norm_expr = ((pl.col(col).log10() - lb) / (ub - lb)).clip(0, 1) - else: - norm_expr = ((pl.col(col) - lb) / (ub - lb)).clip(0, 1) - - # Reverse if minimization - if not is_max: - norm_expr = 1 - norm_expr - # Add normalized column with appropriate name - if n_objectives > 1: - if keep_original: - norm_expr = norm_expr.alias(f"{prefix}_{col}") - else: - idx = list(obj_cols).index(col) + 1 - norm_expr = norm_expr.alias(f"{prefix}{idx}") - else: - # If only one objective, use the prefix directly - norm_expr = norm_expr.alias(prefix) - result = result.with_columns(norm_expr) - - return result - - -def add_normalized_objectives( - data: pl.DataFrame, - obj_cols: Iterable[str], - max_vals: Optional[pl.DataFrame] = None, - min_vals: Optional[pl.DataFrame] = None -): - """Add new normalized columns to provided dataframe based on the provided objective columns - - Args: - data (pl.DataFrame): The original dataframe - obj_cols (Iterable[str]): The names of each objective column - max_vals (Optional[pl.DataFrame]): If provided, these values will be used as the maxima instead of the values found in `data` - min_vals (Optional[pl.DataFrame]): If provided, these values will be used as the minima instead of the values found in `data` - - Returns: - _type_: The original `data` DataFrame with a new column 'objI' added for each objective, for I=1...len(obj_cols) - """ - - return normalize_objectives( - data, - obj_cols=obj_cols, - bounds={ - col: (min_vals[col][0] if min_vals is not None else None, - max_vals[col][0] if max_vals is not None else None) - for col in obj_cols - }, - maximize=True, - prefix="obj", - keep_original=False - ) - - -def transform_fval( - data: pl.DataFrame, - lb: float = 1e-8, - ub: float = 1e8, - scale_log: bool = True, - maximization: bool = False, - fval_col: str = "raw_y", -): - """ - Helper function to transform function values (min-max normalization based on provided bounds and scaling) - """ - bounds = {fval_col: (lb, ub)} - res = normalize_objectives( - data, - obj_cols=[fval_col], - bounds=bounds, - log_scale=scale_log, - maximize=maximization, - prefix="eaf" - ) - return res \ No newline at end of file diff --git a/src/iohinspector/metrics/ranking.py b/src/iohinspector/metrics/ranking.py new file mode 100644 index 0000000..0005433 --- /dev/null +++ b/src/iohinspector/metrics/ranking.py @@ -0,0 +1,84 @@ +from skelo.model.elo import EloEstimator +import numpy as np +import pandas as pd +import polars as pl +from typing import Iterable + + + + +def get_tournament_ratings( + data: pl.DataFrame, + alg_vars: Iterable[str] = ["algorithm_name"], + fid_vars: Iterable[str] = ["function_name"], + perf_var: str = "raw_y", + nrounds: int = 25, + maximization: bool = False, +): + """Method to calculate ratings of a set of algorithm on a set of problems. + Calculated based on nrounds of competition, where in each round all algorithms face all others (pairwise) on every function. + For each round, a sampled performance value is taken from the data and used to determine the winner. + This function uses the ELO rating scheme, as opposed to the Glicko2 scheme used in the IOHanalyzer. Deviations are estimated based on the last 5% of rounds. + + Args: + data (pl.DataFrame): The data object to use for getting the performance. + alg_vars (Iterable[str], optional): Which variables specific the algortihms which will compete. Defaults to ["algorithm_name"]. + fid_vars (Iterable[str], optional): Which variables denote the problems on which will be competed. Defaults to ["function_name"]. + perf_var (str, optional): Which variable corresponds to the performance. Defaults to "raw_y". + nrounds (int, optional): How many round should be played. Defaults to 25. + maximization (bool, optional): Whether the performance metric is being maximized. Defaults to False. + + Returns: + pd.DataFrame: Pandas dataframe with rating, deviation and volatility for each 'alg_vars' combination + """ + fids = data[fid_vars].unique() + aligned_comps = data.pivot( + index=alg_vars, + columns=fid_vars, + values=perf_var, + aggregate_function=pl.element(), + ) + players = aligned_comps[alg_vars] + n_players = players.shape[0] + comp_arr = np.array(aligned_comps[aligned_comps.columns[len(alg_vars) :]]) + + rng = np.random.default_rng() + fids = [i for i in range(len(fids))] + lplayers = [i for i in range(n_players)] + records = [] + for r in range(nrounds): + for fid in fids: + for p1 in lplayers: + for p2 in lplayers: + if p1 == p2: + continue + s1 = rng.choice(comp_arr[p1][fid], 1)[0] + s2 = rng.choice(comp_arr[p2][fid], 1)[0] + if s1 == s2: + won = 0.5 + else: + won = abs(float(maximization) - float(s1 < s2)) + + records.append([r, p1, p2, won]) + dt_comp = pd.DataFrame.from_records( + records, columns=["round", "p1", "p2", "outcome"] + ) + dt_comp = dt_comp.sample(frac=1).sort_values("round") + model = EloEstimator(key1_field="p1", key2_field="p2", timestamp_field="round").fit( + dt_comp, dt_comp["outcome"] + ) + model_dt = model.rating_model.to_frame() + ratings = np.array(model_dt[np.isnan(model_dt["valid_to"])]["rating"]) + deviations = ( + model_dt.query(f"valid_from >= {nrounds * 0.95}").groupby("key")["rating"].std() + ) + + rating_dt_elo = pd.DataFrame( + [ + ratings, + deviations, + *players[players.columns], + ] + ).transpose() + rating_dt_elo.columns = ["Rating", "Deviation", *players.columns] + return rating_dt_elo diff --git a/src/iohinspector/metrics/trajectory.py b/src/iohinspector/metrics/trajectory.py new file mode 100644 index 0000000..25ea53b --- /dev/null +++ b/src/iohinspector/metrics/trajectory.py @@ -0,0 +1,45 @@ +import numpy as np +import polars as pl +from typing import Iterable +from iohinspector.align import align_data + + + + +def get_trajectory(data: pl.DataFrame, + traj_length: int = None, + min_fevals: int = 1, + evaluation_variable: str = "evaluations", + fval_variable: str = "raw_y", + free_variables: Iterable[str] = ["algorithm_name"], + maximization: bool = False +) -> pl.DataFrame: + """get the trajectory of the performance of the algorithms in the data + This function aligns the data to a fixed number of evaluations and returns the performance trajectory. + + Args: + data (pl.DataFrame): The DataFrame resulting from loading the data from a DataManager. + traj_length (int, optional): Length of the trajecotry. Defaults to None. + min_fevals (int, optional): Evaluation number from which to start the trajectory. Defaults to 1. + evaluation_variable (str, optional): Variable corresponding to evaluation count in `data`. Defaults to "evaluations". + fval_variable (str, optional): Variable corresponding to function value in `data`. Defaults to "raw_y". + free_variables (Iterable[str], optional): Free variables in `data`. Defaults to ["algorithm_name"]. + maximization (bool, optional): Whether the data is maximizing or not. Defaults to False. + + Returns: + pd.DataFrame: DataFrame: A polars DataFrame with the aligned data, where each row corresponds to a specific evaluation count and the performance value. + """ + if traj_length is None: + max_fevals = data[evaluation_variable].max() + else: + max_fevals = traj_length + min_fevals + x_values = np.arange(min_fevals, max_fevals + 1) + data_aligned = align_data( + data.cast({evaluation_variable: pl.Int64}), + x_values, + group_cols=["data_id"] + free_variables, + x_col=evaluation_variable, + y_col=fval_variable, + maximization=maximization, + ) + return data_aligned \ No newline at end of file diff --git a/src/iohinspector/metrics/utils.py b/src/iohinspector/metrics/utils.py index 8821c98..4703b7c 100644 --- a/src/iohinspector/metrics/utils.py +++ b/src/iohinspector/metrics/utils.py @@ -1,11 +1,7 @@ import numpy as np import polars as pl - - -def geometric_mean(series: pl.Series) -> float: - """Helper function for polars: geometric mean""" - return np.exp(np.log(series).mean()) - +import warnings +from typing import Iterable, Optional, Union, Dict def get_sequence( min: float, @@ -49,3 +45,128 @@ def get_sequence( if cast_to_int: return np.unique(np.array(values, dtype=int)) return np.unique(values) + + + + +def normalize_objectives( + data: pl.DataFrame, + obj_cols: Iterable[str] = ["raw_y"], + bounds: Optional[Dict[str, tuple[Optional[float], Optional[float]]]] = None, + log_scale: Union[bool, Dict[str, bool]] = False, + maximize: Union[bool, Dict[str, bool]] = False, + prefix: str = "ert", + keep_original: bool = True +) -> pl.DataFrame: + """ + Normalize multiple objective columns in a dataframe. + + Args: + data (pl.DataFrame): Input dataframe. + obj_cols (Iterable[str]): Columns to normalize. + bounds (Optional[Dict[str, tuple(lb, ub)]]): Optional manual bounds per column. + log_scale (Union[bool, Dict[str, bool]]): Whether to apply log10 scaling. Can be a single bool or a dict per column. + maximize (Union[bool, Dict[str, bool]]): Whether to treat objective as maximization. Can be a single bool or dict. + prefix (str): Prefix for normalized column names. + keep_original (bool): Whether to keep original objective columns names. + Returns: + pl.DataFrame: The original dataframe with new normalized objective columns added. + """ + result = data.clone() + n_objectives = len(obj_cols) + for col in obj_cols: + # Determine log scaling + use_log = log_scale[col] if isinstance(log_scale, dict) else log_scale + is_max = maximize[col] if isinstance(maximize, dict) else maximize + + # Get bounds + lb, ub = None, None + if bounds and col in bounds: + lb, ub = bounds[col] + if lb is None: + lb = result[col].min() + if ub is None: + ub = result[col].max() + # Log scale if needed + if use_log: + if lb <= 0: + warnings.warn( + f"Lower bound for column '{col}' <= 0; resetting to 1e-8 for log-scaling." + ) + lb = 1e-8 + lb, ub = np.log10(lb), np.log10(ub) + norm_expr = ((pl.col(col).log10() - lb) / (ub - lb)).clip(0, 1) + else: + norm_expr = ((pl.col(col) - lb) / (ub - lb)).clip(0, 1) + + # Reverse if minimization + if not is_max: + norm_expr = 1 - norm_expr + # Add normalized column with appropriate name + if n_objectives > 1: + if keep_original: + norm_expr = norm_expr.alias(f"{prefix}_{col}") + else: + idx = list(obj_cols).index(col) + 1 + norm_expr = norm_expr.alias(f"{prefix}{idx}") + else: + # If only one objective, use the prefix directly + norm_expr = norm_expr.alias(prefix) + result = result.with_columns(norm_expr) + + return result + + +def add_normalized_objectives( + data: pl.DataFrame, + obj_cols: Iterable[str], + max_vals: Optional[pl.DataFrame] = None, + min_vals: Optional[pl.DataFrame] = None +): + """Add new normalized columns to provided dataframe based on the provided objective columns + + Args: + data (pl.DataFrame): The original dataframe + obj_cols (Iterable[str]): The names of each objective column + max_vals (Optional[pl.DataFrame]): If provided, these values will be used as the maxima instead of the values found in `data` + min_vals (Optional[pl.DataFrame]): If provided, these values will be used as the minima instead of the values found in `data` + + Returns: + _type_: The original `data` DataFrame with a new column 'objI' added for each objective, for I=1...len(obj_cols) + """ + + return normalize_objectives( + data, + obj_cols=obj_cols, + bounds={ + col: (min_vals[col][0] if min_vals is not None else None, + max_vals[col][0] if max_vals is not None else None) + for col in obj_cols + }, + maximize=True, + prefix="obj", + keep_original=False + ) + + +def transform_fval( + data: pl.DataFrame, + lb: float = 1e-8, + ub: float = 1e8, + scale_log: bool = True, + maximization: bool = False, + fval_col: str = "raw_y", +): + """ + Helper function to transform function values (min-max normalization based on provided bounds and scaling) + """ + bounds = {fval_col: (lb, ub)} + res = normalize_objectives( + data, + obj_cols=[fval_col], + bounds=bounds, + log_scale=scale_log, + maximize=maximization, + prefix="eaf" + ) + return res \ No newline at end of file diff --git a/src/iohinspector/old_metrics.py b/src/iohinspector/old_metrics.py deleted file mode 100644 index b960ebc..0000000 --- a/src/iohinspector/old_metrics.py +++ /dev/null @@ -1,234 +0,0 @@ -from functools import partial -from warnings import warn -from typing import Iterable, Callable, Optional - -import polars as pl -import numpy as np -import pandas as pd -from skelo.model.elo import EloEstimator - -from .align import align_data - -def get_tournament_ratings( - data: pl.DataFrame, - alg_vars: Iterable[str] = ["algorithm_name"], - fid_vars: Iterable[str] = ["function_name"], - perf_var: str = "raw_y", - nrounds: int = 25, - maximization: bool = False, -): - """Method to calculate ratings of a set of algorithm on a set of problems. - Calculated based on nrounds of competition, where in each round all algorithms face all others (pairwise) on every function. - For each round, a sampled performance value is taken from the data and used to determine the winner. - This function uses the ELO rating scheme, as opposed to the Glicko2 scheme used in the IOHanalyzer. Deviations are estimated based on the last 5% of rounds. - - Args: - data (pl.DataFrame): The data object to use for getting the performance. - alg_vars (Iterable[str], optional): Which variables specific the algortihms which will compete. Defaults to ["algorithm_name"]. - fid_vars (Iterable[str], optional): Which variables denote the problems on which will be competed. Defaults to ["function_name"]. - perf_var (str, optional): Which variable corresponds to the performance. Defaults to "raw_y". - nrounds (int, optional): How many round should be played. Defaults to 25. - maximization (bool, optional): Whether the performance metric is being maximized. Defaults to False. - - Returns: - pd.DataFrame: Pandas dataframe with rating, deviation and volatility for each 'alg_vars' combination - """ - fids = data[fid_vars].unique() - aligned_comps = data.pivot( - index=alg_vars, - columns=fid_vars, - values=perf_var, - aggregate_function=pl.element(), - ) - players = aligned_comps[alg_vars] - n_players = players.shape[0] - comp_arr = np.array(aligned_comps[aligned_comps.columns[len(alg_vars) :]]) - - rng = np.random.default_rng() - fids = [i for i in range(len(fids))] - lplayers = [i for i in range(n_players)] - records = [] - for r in range(nrounds): - for fid in fids: - for p1 in lplayers: - for p2 in lplayers: - if p1 == p2: - continue - s1 = rng.choice(comp_arr[p1][fid], 1)[0] - s2 = rng.choice(comp_arr[p2][fid], 1)[0] - if s1 == s2: - won = 0.5 - else: - won = abs(float(maximization) - float(s1 < s2)) - - records.append([r, p1, p2, won]) - - dt_comp = pd.DataFrame.from_records( - records, columns=["round", "p1", "p2", "outcome"] - ) - dt_comp = dt_comp.sample(frac=1).sort_values("round") - model = EloEstimator(key1_field="p1", key2_field="p2", timestamp_field="round").fit( - dt_comp, dt_comp["outcome"] - ) - model_dt = model.rating_model.to_frame() - ratings = np.array(model_dt[np.isnan(model_dt["valid_to"])]["rating"]) - deviations = ( - model_dt.query(f"valid_from >= {nrounds * 0.95}").groupby("key")["rating"].std() - ) - rating_dt_elo = pd.DataFrame( - [ - ratings, - deviations, - *players[players.columns], - ] - ).transpose() - rating_dt_elo.columns = ["Rating", "Deviation", *players.columns] - return rating_dt_elo - - - -def _get_nodeidx(xloc, yval, nodes, epsilon): - if len(nodes) == 0: - return -1 - candidates = nodes[np.isclose(nodes["y"], yval, atol=epsilon)] - if len(candidates) == 0: - return -1 - idxs = np.all( - np.isclose(np.array(candidates)[:, : len(xloc)], xloc, atol=epsilon), axis=1 - ) - if any(idxs): - return candidates[idxs].index[0] - return -1 - - -def get_attractor_network( - data, - coord_vars=["x1", "x2"], - fval_var: str = "raw_y", - eval_var: str = "evaluations", - maximization: bool = False, - beta=40, - epsilon=0.0001, - eval_max=None, -): - """Create an attractor network from the provided data - - Args: - data (pl.DataFrame): The original dataframe, should contain the performance and position information - coord_vars (Iterable[str], optional): Which columns correspond to position information. Defaults to ['x1', 'x2']. - fval_var (str, optional): Which column corresponds to performance. Defaults to 'raw_y'. - eval_var (str, optional): Which column corresponds to evaluations. Defaults to 'evaluations'. - maximization (bool, optional): Whether fval_var is to be maximized. Defaults to False. - beta (int, optional): Minimum stagnation lenght. Defaults to 40. - epsilon (float, optional): Radius below which positions should be considered identical in the network. Defaults to 0.0001. - eval_max (int, optional): Maximum evaluation number. Defaults to the maximum of eval_var if None. - Returns: - pd.DataFrame, pd.DataFrame: two dataframes containing the nodes and edges of the network respectively. - """ - - running_idx = 0 - running_edgeidx = 0 - nodes = pd.DataFrame(columns=[*coord_vars, "y", "count", "evals"]) - edges = pd.DataFrame(columns=["start", "end", "count", "stag_length_avg"]) - if eval_max is None: - eval_max = max(data[eval_var]) - - for run_id in data["data_id"].unique(): - dt_group = data.filter( - pl.col("data_id") == run_id, pl.col(eval_var) <= eval_max - ) - if maximization: - ys = np.maximum.accumulate(np.array(dt_group[fval_var])) - else: - ys = np.minimum.accumulate(np.array(dt_group[fval_var])) - xs = np.array(dt_group[coord_vars]) - - stopping_points = np.where(np.abs(np.diff(ys, prepend=np.inf)) > 0)[0] - evals = np.array(dt_group[eval_var]) - - stagnation_lengths = np.diff(evals[stopping_points], append=eval_max) - edge_lengths = stagnation_lengths[stagnation_lengths > beta] - real_idxs = [stopping_points[i] for i in np.where(stagnation_lengths > beta)[0]] - - xloc = xs[real_idxs[0]] - yval = ys[real_idxs[0]] - nodeidx = _get_nodeidx(xloc, yval, nodes, epsilon) - if nodeidx == -1: - nodes.loc[running_idx] = [*xloc, yval, 1, evals[real_idxs[0]]] - node1 = running_idx - running_idx += 1 - else: - nodes.loc[nodeidx, "evals"] += evals[real_idxs[0]] - nodes.loc[nodeidx, "count"] += 1 - node1 = nodeidx - - if len(real_idxs) == 1: - continue - - for i in range(len(real_idxs) - 1): - xloc = xs[real_idxs[i + 1]] - yval = ys[real_idxs[i + 1]] - nodeidx = _get_nodeidx(xloc, yval, nodes, epsilon) - if nodeidx == -1: - nodes.loc[running_idx] = [*xloc, yval, 1, evals[real_idxs[i + 1]]] - node2 = running_idx - running_idx += 1 - else: - nodes.loc[nodeidx, "evals"] += evals[real_idxs[i + 1]] - nodes.loc[nodeidx, "count"] += 1 - node2 = nodeidx - - edgelen = edge_lengths[i] - edge_idxs = edges.query(f"start == {node1} & end == {node2}").index - if len(edge_idxs) == 0: - edges.loc[running_edgeidx] = [node1, node2, 1, edgelen] - running_edgeidx += 1 - else: - curr_count = edges.loc[edge_idxs[0]]["count"] - curr_len = edges.loc[edge_idxs[0]]["stag_length_avg"] - edges.loc[edge_idxs[0], "stag_length_avg"] = ( - curr_len * curr_count + edgelen - ) / (curr_count + 1) - edges.loc[edge_idxs[0], "count"] += 1 - node1 = node2 - return nodes, edges - - - -def get_trajectory(data: pl.DataFrame, - traj_length: int = None, - min_fevals: int = 1, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - maximization: bool = False -) -> pl.DataFrame: - """get the trajectory of the performance of the algorithms in the data - This function aligns the data to a fixed number of evaluations and returns the performance trajectory. - - Args: - data (pl.DataFrame): The DataFrame resulting from loading the data from a DataManager. - traj_length (int, optional): Length of the trajecotry. Defaults to None. - min_fevals (int, optional): Evaluation number from which to start the trajectory. Defaults to 1. - evaluation_variable (str, optional): Variable corresponding to evaluation count in `data`. Defaults to "evaluations". - fval_variable (str, optional): Variable corresponding to function value in `data`. Defaults to "raw_y". - free_variables (Iterable[str], optional): Free variables in `data`. Defaults to ["algorithm_name"]. - maximization (bool, optional): Whether the data is maximizing or not. Defaults to False. - - Returns: - pd.DataFrame: DataFrame: A polars DataFrame with the aligned data, where each row corresponds to a specific evaluation count and the performance value. - """ - if traj_length is None: - max_fevals = data[eval_var].max() - else: - max_fevals = traj_length + min_fevals - x_values = np.arange(min_fevals, max_fevals + 1) - data_aligned = align_data( - data.cast({evaluation_variable: pl.Int64}), - x_values, - group_cols=["data_id"] + free_variables, - x_col=evaluation_variable, - y_col=fval_variable, - maximization=maximization, - ) - return data_aligned \ No newline at end of file diff --git a/src/iohinspector/plot.py b/src/iohinspector/plot.py deleted file mode 100644 index 76f9da1..0000000 --- a/src/iohinspector/plot.py +++ /dev/null @@ -1,868 +0,0 @@ -from typing import Iterable, Optional -import polars as pl -import numpy as np -import pandas as pd -from moocore import eaf, eafdiff - -import matplotlib -import matplotlib.pyplot as plt -from matplotlib.patches import Polygon, Rectangle -import seaborn as sbs - -from .old_metrics import ( - get_tournament_ratings, - get_attractor_network, -) -from .metrics import aggregate_running_time, aggregate_convergence, get_sequence, transform_fval -from .align import align_data, turbo_align -from .indicators import add_indicator, final - - -matplotlib.rcParams["pdf.fonttype"] = 42 -matplotlib.rcParams["ps.fonttype"] = 42 -font = {"size": 24} -plt.rc("font", **font) - - -# tradeoff between simple (few parameters) and flexible. Maybe many parameter but everything with clear defaults? -# Can also make sure any useful function for data processing is available separately for more flexibility - - -def single_function_fixedtarget( - data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - f_min: float = None, - f_max: float = None, - max_budget: int = None, - maximization: bool = False, - measures: Iterable[str] = ["ERT"], - scale_xlog: bool = True, - scale_ylog: bool = True, - ax: matplotlib.axes._axes.Axes = None, - file_name: str = None, -): - """Create a fixed-target plot for a given set of performance data. - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. - f_min (float, optional): Minimum value to use for the 'fval_variable', if not present the min of that column will be used. Defaults to None. - f_max (float, optional): Maximum value to use for the 'fval_variable', if not present the max of that column will be used. Defaults to None. - max_budget (int, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. - maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'ERT', 'mean', 'PAR-10', 'min', 'max'. Defaults to ['ERT']. - scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. - scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - - Returns: - pd.DataFrame: The final dataframe which was used to create the plot - """ - dt_agg = aggregate_running_time( - data, - evaluation_variable=evaluation_variable, - fval_variable=fval_variable, - free_variables=free_variables, - f_min=f_min, - f_max=f_max, - scale_flog=scale_xlog, - max_budget=max_budget, - maximization=maximization, - ) - - dt_molt = dt_agg.melt(id_vars=[fval_variable] + free_variables) - dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) - - if ax is None: - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) - sbs.lineplot( - dt_plot, - x=fval_variable, - y="value", - style="variable", - hue=dt_plot[free_variables].apply(tuple, axis=1), - ax=ax, - ) - if scale_xlog: - ax.set_xscale("log") - if scale_ylog: - ax.set_yscale("log") - - if not maximization: - ax.set_xlim(ax.get_xlim()[::-1]) - - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - - return dt_plot - - -def single_function_fixedbudget( - data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - x_min: float = None, - x_max: float = None, - maximization: bool = False, - measures: Iterable[str] = ["geometric_mean"], - scale_xlog: bool = True, - scale_ylog: bool = True, - ax: matplotlib.axes._axes.Axes = None, - file_name: str = None, -): - """Create a fixed-budget plot for a given set of performance data. - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. - x_min (float, optional): Minimum value to use for the 'evaluation_variable', if not present the min of that column will be used. Defaults to None. - x_max (float, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. - maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. - scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. - scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - - Returns: - pd.DataFrame: The final dataframe which was used to create the plot - """ - dt_agg = aggregate_convergence( - data, - evaluation_variable=evaluation_variable, - fval_variable=fval_variable, - free_variables=free_variables, - x_min=x_min, - x_max=x_max, - maximization=maximization, - ) - - dt_molt = dt_agg.melt(id_vars=[evaluation_variable] + free_variables) - dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) - if ax is None: - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) - sbs.lineplot( - dt_plot, - x=evaluation_variable, - y="value", - style="variable", - hue=dt_plot[free_variables].apply(tuple, axis=1), - ax=ax, - ) - if scale_xlog: - ax.set_xscale("log") - if scale_ylog: - ax.set_yscale("log") - - - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - - return dt_plot - - -def heatmap_single_run( - data: pl.DataFrame, - var_cols: Iterable[str], - eval_col: str = "evaluations", - scale_xlog: bool = True, - x_mins: Iterable[float] = [-5], - x_maxs: Iterable[float] = [5], - ax: matplotlib.axes._axes.Axes = None, - file_name: Optional[str] = None, -): - """Create a heatmap showing the search space points evaluated in a single run - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - var_cols (Iterable[str]): The variables which correspond to the searchspace variable columns - eval_col (str): The variable corresponding to evaluations. Defaults to 'evaluations' - scale_xlog (bool, optional): Whether the evaluations should be log-scaled. Defaults to True. - x_mins (Iterable[float], optional): Minimum bound for the variables. Should be of the same length as 'var_cols'. Defaults to [-5]. - x_maxs (Iterable[float], optional): Maximum bound for the variables. Should be of the same length as 'var_cols'.. Defaults to [5]. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. - - Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot - """ - assert data["data_id"].n_unique() == 1 - dt_plot = data[var_cols].transpose().to_pandas() - dt_plot.columns = list(data["evaluations"]) - dt_plot = (dt_plot - x_mins) / (x_maxs - x_mins) - if ax is None: - fig, ax = plt.subplots(figsize=(32, 9)) - sbs.heatmap(dt_plot, cmap="viridis", vmin=0, vmax=1, ax=ax) - if scale_xlog: - ax.set_xscale("log") - ax.set_xlim(1, len(data)) - - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - return dt_plot - - -def plot_eaf_singleobj( - data: pl.DataFrame, - min_budget: int = None, - max_budget: int = None, - scale_xlog: bool = True, - n_quantiles: int = 100, - eval_var: str = "evaluations", - fval_var: str = "raw_y", - ax: matplotlib.axes._axes.Axes = None, - file_name: Optional[str] = None, -): - """Plot the EAF for a single objective column agains budget. For the EAF-plot for multiple objective - columns, see 'plot_eaf_pareto'. - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - n_quantiles (int, optional): Number of discrete levels in the EAF. Defaults to 100. - eval_var (str, optional): The variable corresponding to evaluations. Defaults to 'evaluations' - fval_var (str, optional): The variable corresponding to function values. Defaults to "raw_y". - scale_xlog (bool, optional): Whether the evaluations should be log-scaled. Defaults to True. - min_budget (Iterable[float], optional): Minimum bound for the variables. Should be of the same length as 'var_cols'. Defaults to [-5]. - max_budget (Iterable[float], optional): Maximum bound for the variables. Should be of the same length as 'var_cols'.. Defaults to [5]. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. - - Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot - """ - if min_budget is None: - min_budget = data[eval_var].min() - if max_budget is None: - max_budget = data[eval_var].max() - evals = get_sequence(min_budget, max_budget, 50, scale_xlog, True) - long = align_data(data, np.array(evals, "uint64"), ["data_id"], output="long") - - quantiles = np.arange(0, 1 + 1 / ((n_quantiles - 1) * 2), 1 / (n_quantiles - 1)) - if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - colors = sbs.color_palette("viridis", n_colors=len(quantiles)) - for quant, color in zip(quantiles, colors[::-1]): - poly = np.array( - long.group_by(eval_var).quantile(quant).sort(eval_var)[eval_var, fval_var] - ) - poly = np.append( - poly, np.array([[max(poly[:, 0]), long[fval_var].max()]]), axis=0 - ) - poly = np.append( - poly, np.array([[min(poly[:, 0]), long[fval_var].max()]]), axis=0 - ) - poly2 = np.repeat(poly, 2, axis=0) - poly2[2::2, 1] = poly[:, 1][:-1] - ax.add_patch(Polygon(poly2, facecolor=color)) - ax.set_ylim(long[fval_var].min(), long[fval_var].max()) - ax.set_xlim(min(evals), max(evals)) - ax.set_axisbelow(True) - ax.grid(which="both", zorder=100) - ax.set_yscale("log") - if scale_xlog: - ax.set_xscale("log") - - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - return long - - -def plot_eaf_pareto( - data: pl.DataFrame, - x_column: str, - y_column: str, - min_y: float = 0, - max_y: float = 1, - scale_xlog: bool = False, - scale_ylog: bool = False, - ax: matplotlib.axes._axes.Axes = None, - filename_fig: Optional[str] = None, -): - """Plot the EAF for two arbitrary data columns. For the EAF-plot for single-objective - optimization runs, the 'plot_eaf_singleobj' provides a simpler interface. - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - x_column (str, optional): The variable corresponding to the first objective. - y_column (str, optional): The variable corresponding to the second objective. - min_y (float): Minimum value for the second objective. - max_y (float): Maximum value for the second objective. - scale_xlog (bool, optional): Whether the first objective should be log-scaled. Defaults to False. - scale_ylog (bool, optional): Whether the second objective should be log-scaled. Defaults to False. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. - """ - data_to_process = np.array(data[[x_column, y_column, "data_id"]]) - eaf_data = eaf(data_to_process[:,:-1], data_to_process[:,-1] ) - eaf_data_df = pd.DataFrame(eaf_data) - if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - colors = sbs.color_palette("viridis", n_colors=eaf_data_df[2].nunique()) - eaf_data_df = eaf_data_df.sort_values(0) - min_x = np.min(eaf_data_df[0]) - max_x = np.max(eaf_data_df[0]) - if min_y is None: - min_y = np.min(eaf_data_df[1]) - if max_y is None: - max_y = np.max(eaf_data_df[1]) - for i, color in zip(eaf_data_df[2].unique(), colors[::-1]): - poly = np.array(eaf_data_df[eaf_data_df[2] == i][[0, 1]]) - # poly = np.append(poly, np.array([[max(poly[:, 0]), max(poly[:, 1])]]), axis=0) - # poly = np.append(poly, np.array([[min(poly[:, 0]), max(poly[:, 1])]]), axis=0) - poly = np.append(poly, np.array([[max_x, max_y]]), axis=0) - poly = np.append(poly, np.array([[min(poly[:, 0]), max_y]]), axis=0) - poly2 = np.repeat(poly, 2, axis=0) - poly2[2::2, 1] = poly[:, 1][:-1] - ax.add_patch(Polygon(poly2, facecolor=color)) - # ax.add_colorbar() - ax.set_ylim(min_y, max_y) - ax.set_xlim(min_x, max_x) - ax.set_axisbelow(True) - sm = plt.cm.ScalarMappable(cmap="viridis", norm=plt.Normalize(vmin=0, vmax=1)) - sm.set_array([]) - plt.colorbar(sm, ax=ax) - if scale_ylog: - ax.set_yscale("log") - if scale_xlog: - ax.set_xscale("log") - ax.grid(which="both", zorder=100) - if filename_fig: - fig.tight_layout() - fig.savefig(filename_fig) - - -def eaf_diffs( - data1: pl.DataFrame, - data2: pl.DataFrame, - x_column: str, - y_column: str, - min_y: float = 0, - max_y: float = 1, - scale_xlog: bool = False, - scale_ylog: bool = False, - ax: matplotlib.axes._axes.Axes = None, - filename_fig: Optional[str] = None, -): - """Plot the EAF differences between two datasets. - - Args: - data1 (pl.DataFrame): The DataFrame which contains the full performance trajectory for algorithm 1. Should be generated from a DataManager. - data2 (pl.DataFrame): The DataFrame which contains the full performance trajectory for algorithm 2. Should be generated from a DataManager. - x_column (str, optional): The variable corresponding to the first objective. - y_column (str, optional): The variable corresponding to the second objective. - min_y (float): Minimum value for the second objective. - max_y (float): Maximum value for the second objective. - scale_xlog (bool, optional): Whether the first objective should be log-scaled. Defaults to False. - scale_ylog (bool, optional): Whether the second objective should be log-scaled. Defaults to False. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. - """ - # TODO: add an approximation version to speed up plotting - x = np.array(data1[[x_column, y_column, "data_id"]]) - y = np.array(data2[[x_column, y_column, "data_id"]]) - print(x) - print(y) - eaf_diff_rect = eafdiff(x, y, rectangles=True) - color_dict = { - k: v - for k, v in zip( - np.unique(eaf_diff_rect[:, -1]), - sbs.color_palette("viridis", n_colors=len(np.unique(eaf_diff_rect[:, -1]))), - ) - } - if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - for rect in eaf_diff_rect: - ax.add_patch( - Rectangle( - (rect[0], rect[1]), - rect[2] - rect[0], - rect[3] - rect[1], - facecolor=color_dict[rect[-1]], - ) - ) - if min_y is None: - min_y = np.min(x[1]) - if max_y is None: - max_y = np.max(x[1]) - ax.set_ylim(min_y, max_y) - ax.set_xlim((0,1000)) - if scale_ylog: - ax.set_yscale("log") - if scale_xlog: - ax.set_xscale("log") - if filename_fig: - fig.tight_layout() - fig.savefig(filename_fig) - - -def plot_ecdf( - data, - fval_var: str = "raw_y", - eval_var: str = "evaluations", - free_vars: Iterable[str] = ["algorithm_name"], - scale_xlog: bool = True, - x_min: int = None, - x_max: int = None, - x_values: Iterable[int] = None, - y_min: int = None, - y_max: int = None, - scale_ylog: bool = True, - maximization: bool = False, - ax: matplotlib.axes._axes.Axes = None, - file_name: Optional[str] = None, -): - """Function to plot empirical cumulative distribution function (Based on EAF) - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - eval_var (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_var (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_vars (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. - x_min (float, optional): Minimum value to use for the 'eval_var', if not present the min of that column will be used. Defaults to None. - x_max (float, optional): Maximum value to use for the 'eval_var', if not present the max of that column will be used. Defaults to None. - x_values (Iterable[int], optional): List of x-values at which to plot the ECDF. If not provided, the x_min, x_max and scale_xlog arguments will be used to sample these points. - scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. - y_min (float, optional): Minimum value to use for the 'fval_var', if not present the min of that column will be used. Defaults to None. - y_max (float, optional): Maximum value to use for the 'fval_var', if not present the max of that column will be used. Defaults to None. - scale_ylog (bool, optional): Should the y-values be log-scaled before normalization. Defaults to True. - maximization (bool, optional): Boolean indicating whether the 'fval_var' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - - Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot - """ - if x_min is None: - x_min = data[eval_var].min() - if x_max is None: - x_max = data[eval_var].max() - x_values = get_sequence(x_min, x_max, 50, scale_log=scale_xlog, cast_to_int=True) - - data_aligned = turbo_align( - data, - x_values, - x_col=eval_var, - y_col=fval_var, - maximization=maximization, - ) - dt_plot = ( - transform_fval(data_aligned, fval_col=fval_var, maximization=maximization) - .group_by([eval_var] + free_vars) - .mean() - .sort(eval_var) - ).to_pandas() - - if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - if len(free_vars) == 1: - hue_arg = free_vars[0] - style_arg = free_vars[0] - else: - style_arg = free_vars[0] - hue_arg = dt_plot[free_vars[1:]].apply(tuple, axis=1) - - sbs.lineplot( - dt_plot, - x="evaluations", - y="eaf", - style=style_arg, - hue=hue_arg, - ax=ax, - ) - if scale_xlog: - ax.set_xscale("log") - ax.grid() - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - return dt_plot - - -def multi_function_fixedbudget(): - # either just loop over function column(s), or more advanced - raise NotImplementedError - - -def multi_function_fixedtarget(): - raise NotImplementedError - - -def plot_tournament_ranking( - data, - alg_vars: Iterable[str] = ["algorithm_name"], - fid_vars: Iterable[str] = ["function_name"], - perf_var: str = "raw_y", - nrounds: int = 25, - maximization: bool = False, - ax: matplotlib.axes._axes.Axes = None, - file_name: str = None, -): - """Method to plot ELO ratings of a set of algorithm on a set of problems. - Calculated based on nrounds of competition, where in each round all algorithms face all others (pairwise) on every function. - For each round, a sampled performance value is taken from the data and used to determine the winner. - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - alg_vars (Iterable[str], optional): Which variables specific the algortihms which will compete. Defaults to ["algorithm_name"]. - fid_vars (Iterable[str], optional): Which variables denote the problems on which will be competed. Defaults to ["function_name"]. - perf_var (str, optional): Which variable corresponds to the performance. Defaults to "raw_y". - nrounds (int, optional): How many round should be played. Defaults to 25. - maximization (bool, optional): Whether the performance should be maximized. Defaults to False. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - - Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot - """ - # candlestick plot based on average and volatility - dt_elo = get_tournament_ratings( - data, alg_vars, fid_vars, perf_var, nrounds, maximization - ) - if ax is None: - _, ax = plt.subplots(1, 1, figsize=(10, 5)) - - sbs.pointplot(data=dt_elo, x=alg_vars[0], y="Rating", linestyle="none", ax=ax) - - ax.errorbar( - dt_elo[alg_vars[0]], - dt_elo["Rating"], - yerr=dt_elo["Deviation"], - fmt="o", - color="blue", - alpha=0.6, - capsize=5, - elinewidth=1.5, - ) - ax.grid() - - if file_name: - plt.tight_layout() - plt.savefig(file_name) - return dt_elo - - -def robustranking(): - # to decide which plot(s) to use and what exact interface to define - raise NotImplementedError() - - -def stats_comparison(): - # heatmap or graph of statistical comparisons - raise NotImplementedError() - - -def winnning_fraction_heatmap(): - # nevergrad-like heatmap - raise NotImplementedError() - - -def plot_paretofronts_2d( - data: pl.DataFrame, - obj_vars: Iterable[str] = ["raw_y", "F2"], - free_vars: Iterable[str] = ["algorithm_name"], - ax: matplotlib.axes._axes.Axes = None, - file_name: str = None, -): - """Very basic plot to visualize pareto fronts - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_vars (Iterable[str], optional): Which variables (length should be 2) to use for plotting. Defaults to ["raw_y", "F2"]. - free_vars (Iterable[str], optional): Which varialbes should be used to distinguish between categories. Defaults to ["algorithm_name"]. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - - Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot - """ - assert len(obj_vars) == 2 - - df = add_indicator(data, final.NonDominated(), obj_vars) - - if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - sbs.scatterplot(df, x=data.obj_vars[0], y=data.obj_vars[1], hue=free_vars, ax=ax) - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - return df - - -def plot_indicator_over_time( - data: pl.DataFrame, - obj_columns: Iterable[str], - indicator: object, - eval_column: str = "evaluations", - evals_min: int = 0, - evals_max: int = 50_000, - nr_eval_steps: int = 50, - free_variable: str = "algorithm_name", - ax: matplotlib.axes._axes.Axes = None, - filename_fig: Optional[str] = None, -): - """Convenience function to plot the anytime performance of a single indicator. - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. - indicator (object): Indicator object from iohinspector.indicators - eval_column (Iterable[str], optional): Which columns in 'data' correspond to the objectives. Defaults to 'evaluations'. - evals_min (int, optional): Lower bound for eval_column. Defaults to 0. - evals_max (int, optional): Upper bound for eval_column. Defaults to 50_000. - nr_eval_steps (int, optional): Number of steps between lower and upper bounds of eval_column. Defaults to 50. - free_variable (str, optional): Variable which corresponds to category to differentiate in the plot. Defaults to 'algorithm_name'. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - """ - - evals = get_sequence( - evals_min, evals_max, nr_eval_steps, cast_to_int=True, scale_log=True - ) - df = add_indicator( - data, indicator, objective_columns=obj_columns, evals=evals - ).to_pandas() - if ax is None: - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) - sbs.lineplot( - df, - x=eval_column, - y=indicator.var_name, - hue=free_variable, - palette=sbs.color_palette(n_colors=len(np.unique(data[free_variable]))), - ax=ax, - ) - ax.set_xlabel(eval_column) - ax.set_xlim(evals_min, evals_max) - ax.set_xscale("log") - ax.grid() - if filename_fig: - fig.tight_layout() - fig.savefig(filename_fig) - - return df - - -def plot_robustrank_over_time( - data: pl.DataFrame, - obj_columns: Iterable[str], - evals: Iterable[int], - indicator: object, - filename_fig: Optional[str] = None, -): - """Plot robust ranking at distinct timesteps - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. - evals (Iterable[int]): Timesteps at which to get the rankings - indicator (object): Indicator object from iohinspector.indicators - filename_fig (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - """ - from robustranking import Benchmark - from robustranking.comparison import MOBootstrapComparison, BootstrapComparison - from robustranking.utils.plots import plot_ci_list, plot_line_ranks - - df = add_indicator( - data, indicator, objective_columns=obj_columns, evals=evals - ).to_pandas() - df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] - dt_pivoted = pd.pivot( - df_part, - index=["algorithm_name", "run_id"], - columns=["evaluations"], - values=[indicator.var_name], - ).reset_index() - dt_pivoted.columns = ["algorithm_name", "run_id"] + evals - benchmark = Benchmark() - benchmark.from_pandas(dt_pivoted, "algorithm_name", "run_id", evals) - - comparison = MOBootstrapComparison( - benchmark, - alpha=0.05, - minimise=indicator.minimize, - bootstrap_runs=1000, - aggregation_method=np.mean, - ) - fig, axs = plt.subplots(1, 4, figsize=(16, 9), sharey=True) - for ax, runtime in zip(axs.ravel(), benchmark.objectives): - plot_ci_list(comparison, objective=runtime, ax=ax) - if runtime != evals[0]: - ax.set_ylabel("") - if runtime != evals[-1]: - ax.get_legend().remove() - ax.set_title(runtime) - - plt.tight_layout() - if filename_fig: - plt.savefig(filename_fig) - plt.close() - - -def plot_robustrank_changes( - data: pl.DataFrame, - obj_columns: Iterable[str], - evals: Iterable[int], - indicator: object, - filename_fig: Optional[str] = None, -): - """Plot robust ranking changes at distinct timesteps - - Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. - evals (Iterable[int]): Timesteps at which to get the rankings - indicator (object): Indicator object from iohinspector.indicators - filename_fig (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. - """ - from robustranking import Benchmark - from robustranking.comparison import MOBootstrapComparison, BootstrapComparison - from robustranking.utils.plots import plot_ci_list, plot_line_ranks - - df = add_indicator( - data, indicator, objective_columns=obj_columns, evals=evals - ).to_pandas() - df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] - dt_pivoted = pd.pivot( - df_part, - index=["algorithm_name", "run_id"], - columns=["evaluations"], - values=[indicator.var_name], - ).reset_index() - dt_pivoted.columns = ["algorithm_name", "run_id"] + evals - - comparisons = { - f"{eval}": BootstrapComparison( - Benchmark().from_pandas(dt_pivoted, "algorithm_name", "run_id", eval), - alpha=0.05, - minimise=indicator.minimize, - bootstrap_runs=1000, - ) - for eval in evals - } - - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) - plot_line_ranks(comparisons, ax=ax) - - plt.tight_layout() - if filename_fig: - plt.savefig(filename_fig) - plt.close() - - -def plot_attractor_network( - data, - coord_vars: Iterable[str] = ["x1", "x2"], - fval_var: str = "raw_y", - eval_var: str = "evaluations", - maximization: bool = False, - beta=40, - epsilon=0.0001, -): - """Plot an attractor network from the provided data - - Args: - data (pl.DataFrame): The original dataframe, should contain the performance and position information - coord_vars (Iterable[str], optional): Which columns correspond to position information. Defaults to ['x1', 'x2']. - fval_var (str, optional): Which column corresponds to performance. Defaults to 'raw_y'. - eval_var (str, optional): Which column corresponds to evaluations. Defaults to 'evaluations'. - maximization (bool, optional): Whether fval_var is to be maximized. Defaults to False. - beta (int, optional): Minimum stagnation lenght. Defaults to 40. - epsilon (float, optional): Radius below which positions should be considered identical in the network. Defaults to 0.0001. - - Returns: - pd.DataFrame, pd.DataFrame: two dataframes containing the nodes and edges of the network respectively. - """ - try: - import networkx as nx - except: - print("NetworkX is required to use this plot type") - return - from sklearn.manifold import MDS - - nodes, edges = get_attractor_network( - data, maximization, coord_vars, fval_var, eval_var, beta, epsilon - ) - network = nx.DiGraph() - for idx, row in nodes.iterrows(): - network.add_node( - idx, - decision=np.array(row)[: len(coord_vars)], - fitness=row["y"], - hitcount=row["count"], - evals=row["evals"] / row["count"], - ) - - for _, row in edges.iterrows(): - network.add_edge( - row["start"], - row["end"], - weight=row["count"], - evaldiff=row["stag_length_avg"], - ) - network.remove_edges_from(nx.selfloop_edges(network)) - - decision_matrix = [network.nodes[node]["decision"] for node in network.nodes()] - mds = MDS(n_components=1, random_state=0) - x_positions = mds.fit_transform( - decision_matrix - ).flatten() # Flatten to get 1D array for x-axis - y_positions = [network.nodes[node]["fitness"] for node in network.nodes()] - pos = { - node: (x, y) for node, x, y in zip(network.nodes(), x_positions, y_positions) - } - - hitcounts = [network.nodes[node]["hitcount"] for node in network.nodes()] - if len(hitcounts) > 1: - min_hitcount = min(hitcounts) - max_hitcount = max(hitcounts) - # Node sizes and colors based on fitness values (as in your original code) - if len(hitcounts) > 1 and np.std(hitcounts) > 0: - node_sizes = [ - 100 - + ( - 400 - * (network.nodes[node]["hitcount"] - min_hitcount) - / (max_hitcount - min_hitcount) - ) - for node in network.nodes() - ] - else: - node_sizes = [500] * len(hitcounts) - fitness_values = y_positions # Reuse y_positions as they represent 'fitness' - norm = plt.Normalize(min(fitness_values), max(fitness_values)) - node_colors = plt.cm.viridis(norm(fitness_values)) - - # Draw the graph - if ax is None: - fig, ax = plt.subplots(figsize=(10, 6)) - nx.draw( - network, - pos=pos, - with_labels=False, - node_size=node_sizes, - node_color=node_colors[:, :3], - edge_color="gray", - width=2, - ax=ax, - ) - - # Add colorbar for fitness values - sm = plt.cm.ScalarMappable(cmap="viridis", norm=norm) - sm.set_array(fitness_values) - plt.xlabel("MDS-reduced decision vector") - plt.ylabel("fitness") - plt.tight_layout() diff --git a/src/iohinspector/plots/__init__.py b/src/iohinspector/plots/__init__.py new file mode 100644 index 0000000..08171c5 --- /dev/null +++ b/src/iohinspector/plots/__init__.py @@ -0,0 +1,16 @@ +import matplotlib +import matplotlib.pyplot as plt +matplotlib.rcParams["pdf.fonttype"] = 42 +matplotlib.rcParams["ps.fonttype"] = 42 +font = {"size": 24} +plt.rc("font", **font) + + +from .fixed_target import plot_single_function_fixed_target +from .fixed_budget import plot_single_function_fixed_budget +from .ecdf import plot_ecdf +from .eaf import plot_eaf_single_objective, plot_eaf_pareto, plot_eaf_diffs +from .multi_objective import plot_paretofronts_2d, plot_indicator_over_time +from .ranking import plot_tournament_ranking, plot_robustrank_over_time, plot_robustrank_changes +from .attractor_network import plot_attractor_network +from .single_run import plot_heatmap_single_run \ No newline at end of file diff --git a/src/iohinspector/plots/attractor_network.py b/src/iohinspector/plots/attractor_network.py new file mode 100644 index 0000000..16bf4f7 --- /dev/null +++ b/src/iohinspector/plots/attractor_network.py @@ -0,0 +1,122 @@ +import numpy as np +import pandas as pd +import polars as pl +from typing import Iterable, Tuple +import matplotlib +import matplotlib.pyplot as plt +from iohinspector.metrics import get_attractor_network + + +def plot_attractor_network( + data, + coord_vars: Iterable[str] = ["x1", "x2"], + fval_var: str = "raw_y", + eval_var: str = "evaluations", + maximization: bool = False, + beta=40, + epsilon=0.0001, + file_name: str = None, + ax: matplotlib.axes.Axes = None, +): + """Plot an attractor network from the provided data + + Args: + data (pl.DataFrame): The original dataframe, should contain the performance and position information + coord_vars (Iterable[str], optional): Which columns correspond to position information. Defaults to ['x1', 'x2']. + fval_var (str, optional): Which column corresponds to performance. Defaults to 'raw_y'. + eval_var (str, optional): Which column corresponds to evaluations. Defaults to 'evaluations'. + maximization (bool, optional): Whether fval_var is to be maximized. Defaults to False. + beta (int, optional): Minimum stagnation lenght. Defaults to 40. + epsilon (float, optional): Radius below which positions should be considered identical in the network. Defaults to 0.0001. + + Returns: + pd.DataFrame, pd.DataFrame: two dataframes containing the nodes and edges of the network respectively. + """ + try: + import networkx as nx + except: + print("NetworkX is required to use this plot type") + return + from sklearn.manifold import MDS + + nodes, edges = get_attractor_network( + data = data, + coord_vars = coord_vars, + fval_var = fval_var, + eval_var= eval_var, + maximization = maximization, + beta = beta, + epsilon = epsilon + ) + network = nx.DiGraph() + for idx, row in nodes.iterrows(): + network.add_node( + idx, + decision=np.array(row)[: len(coord_vars)], + fitness=row["y"], + hitcount=row["count"], + evals=row["evals"] / row["count"], + ) + + for _, row in edges.iterrows(): + network.add_edge( + row["start"], + row["end"], + weight=row["count"], + evaldiff=row["stag_length_avg"], + ) + network.remove_edges_from(nx.selfloop_edges(network)) + + decision_matrix = [network.nodes[node]["decision"] for node in network.nodes()] + mds = MDS(n_components=1, random_state=0) + x_positions = mds.fit_transform( + decision_matrix + ).flatten() # Flatten to get 1D array for x-axis + y_positions = [network.nodes[node]["fitness"] for node in network.nodes()] + pos = { + node: (x, y) for node, x, y in zip(network.nodes(), x_positions, y_positions) + } + + hitcounts = [network.nodes[node]["hitcount"] for node in network.nodes()] + if len(hitcounts) > 1: + min_hitcount = min(hitcounts) + max_hitcount = max(hitcounts) + # Node sizes and colors based on fitness values (as in your original code) + if len(hitcounts) > 1 and np.std(hitcounts) > 0: + node_sizes = [ + 100 + + ( + 400 + * (network.nodes[node]["hitcount"] - min_hitcount) + / (max_hitcount - min_hitcount) + ) + for node in network.nodes() + ] + else: + node_sizes = [500] * len(hitcounts) + fitness_values = y_positions # Reuse y_positions as they represent 'fitness' + norm = plt.Normalize(min(fitness_values), max(fitness_values)) + node_colors = plt.cm.viridis(norm(fitness_values)) + + # Draw the graph + if ax is None: + fig, ax = plt.subplots(figsize=(10, 6)) + nx.draw( + network, + pos=pos, + with_labels=False, + node_size=node_sizes, + node_color=node_colors[:, :3], + edge_color="gray", + width=2, + ax=ax, + ) + + # Add colorbar for fitness values + sm = plt.cm.ScalarMappable(cmap="viridis", norm=norm) + sm.set_array(fitness_values) + ax.set_xlabel("MDS-reduced decision vector") + ax.set_ylabel("fitness") + if file_name: + fig.tight_layout() + fig.savefig(file_name) \ No newline at end of file diff --git a/src/iohinspector/plots/eaf.py b/src/iohinspector/plots/eaf.py new file mode 100644 index 0000000..e74f30c --- /dev/null +++ b/src/iohinspector/plots/eaf.py @@ -0,0 +1,205 @@ +import numpy as np +import polars as pl +import pandas as pd +import matplotlib +import matplotlib.pyplot as plt +from matplotlib.patches import Polygon, Rectangle +import seaborn as sbs +from typing import Optional, Iterable +from iohinspector.metrics import get_sequence +from iohinspector.align import align_data +from moocore import eaf, eafdiff + +def plot_eaf_single_objective( + data: pl.DataFrame, + min_budget: int = None, + max_budget: int = None, + scale_xlog: bool = True, + n_quantiles: int = 100, + eval_var: str = "evaluations", + fval_var: str = "raw_y", + ax: matplotlib.axes._axes.Axes = None, + file_name: Optional[str] = None, +): + """Plot the EAF for a single objective column agains budget. For the EAF-plot for multiple objective + columns, see 'plot_eaf_pareto'. + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + n_quantiles (int, optional): Number of discrete levels in the EAF. Defaults to 100. + eval_var (str, optional): The variable corresponding to evaluations. Defaults to 'evaluations' + fval_var (str, optional): The variable corresponding to function values. Defaults to "raw_y". + scale_xlog (bool, optional): Whether the evaluations should be log-scaled. Defaults to True. + min_budget (Iterable[float], optional): Minimum bound for the variables. Should be of the same length as 'var_cols'. Defaults to [-5]. + max_budget (Iterable[float], optional): Maximum bound for the variables. Should be of the same length as 'var_cols'.. Defaults to [5]. + ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. + file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + + Returns: + pd.DataFrame: pandas dataframe of the exact data used to create the plot + """ + if min_budget is None: + min_budget = data[eval_var].min() + if max_budget is None: + max_budget = data[eval_var].max() + evals = get_sequence(min_budget, max_budget, 50, scale_xlog, True) + long = align_data(data, np.array(evals, "uint64"), ["data_id"], output="long") + quantiles = np.arange(0, 1 + 1 / ((n_quantiles - 1) * 2), 1 / (n_quantiles - 1)) + + if ax is None: + fig, ax = plt.subplots(figsize=(16, 9)) + + colors = sbs.color_palette("viridis", n_colors=len(quantiles)) + for quant, color in zip(quantiles, colors[::-1]): + poly = np.array( + long.group_by(eval_var).quantile(quant).sort(eval_var)[eval_var, fval_var] + ) + poly = np.append( + poly, np.array([[max(poly[:, 0]), long[fval_var].max()]]), axis=0 + ) + poly = np.append( + poly, np.array([[min(poly[:, 0]), long[fval_var].max()]]), axis=0 + ) + poly2 = np.repeat(poly, 2, axis=0) + poly2[2::2, 1] = poly[:, 1][:-1] + ax.add_patch(Polygon(poly2, facecolor=color)) + + ax.set_ylim(long[fval_var].min(), long[fval_var].max()) + ax.set_ylim(1e-8, 1) + ax.set_xlim(min(evals), max(evals)) + ax.set_axisbelow(True) + ax.grid(which="both", zorder=100) + ax.set_yscale("log") + if scale_xlog: + ax.set_xscale("log") + + if file_name: + fig.tight_layout() + fig.savefig(file_name) + return long + + +def plot_eaf_pareto( + data: pl.DataFrame, + x_column: str, + y_column: str, + min_y: float = 0, + max_y: float = 1, + scale_xlog: bool = False, + scale_ylog: bool = False, + ax: matplotlib.axes._axes.Axes = None, + file_name: Optional[str] = None, +): + """Plot the EAF for two arbitrary data columns. For the EAF-plot for single-objective + optimization runs, the 'plot_eaf_single_objective' provides a simpler interface. + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + x_column (str, optional): The variable corresponding to the first objective. + y_column (str, optional): The variable corresponding to the second objective. + min_y (float): Minimum value for the second objective. + max_y (float): Maximum value for the second objective. + scale_xlog (bool, optional): Whether the first objective should be log-scaled. Defaults to False. + scale_ylog (bool, optional): Whether the second objective should be log-scaled. Defaults to False. + ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. + file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + """ + data_to_process = np.array(data[[x_column, y_column, "data_id"]]) + eaf_data = eaf(data_to_process[:,:-1], data_to_process[:,-1] ) + eaf_data_df = pd.DataFrame(eaf_data) + if ax is None: + fig, ax = plt.subplots(figsize=(16, 9)) + colors = sbs.color_palette("viridis", n_colors=eaf_data_df[2].nunique()) + eaf_data_df = eaf_data_df.sort_values(0) + min_x = np.min(eaf_data_df[0]) + max_x = np.max(eaf_data_df[0]) + if min_y is None: + min_y = np.min(eaf_data_df[1]) + if max_y is None: + max_y = np.max(eaf_data_df[1]) + for i, color in zip(eaf_data_df[2].unique(), colors[::-1]): + poly = np.array(eaf_data_df[eaf_data_df[2] == i][[0, 1]]) + # poly = np.append(poly, np.array([[max(poly[:, 0]), max(poly[:, 1])]]), axis=0) + # poly = np.append(poly, np.array([[min(poly[:, 0]), max(poly[:, 1])]]), axis=0) + poly = np.append(poly, np.array([[max_x, max_y]]), axis=0) + poly = np.append(poly, np.array([[min(poly[:, 0]), max_y]]), axis=0) + poly2 = np.repeat(poly, 2, axis=0) + poly2[2::2, 1] = poly[:, 1][:-1] + ax.add_patch(Polygon(poly2, facecolor=color)) + # ax.add_colorbar() + ax.set_ylim(min_y, max_y) + ax.set_xlim(min_x, max_x) + ax.set_axisbelow(True) + sm = plt.cm.ScalarMappable(cmap="viridis", norm=plt.Normalize(vmin=0, vmax=1)) + sm.set_array([]) + plt.colorbar(sm, ax=ax) + if scale_ylog: + ax.set_yscale("log") + if scale_xlog: + ax.set_xscale("log") + ax.grid(which="both", zorder=100) + if file_name: + fig.tight_layout() + fig.savefig(file_name) + +def plot_eaf_diffs( + data1: pl.DataFrame, + data2: pl.DataFrame, + x_column: str, + y_column: str, + min_y: float = 0, + max_y: float = 1, + scale_xlog: bool = False, + scale_ylog: bool = False, + ax: matplotlib.axes._axes.Axes = None, + file_name: Optional[str] = None, +): + """Plot the EAF differences between two datasets. + + Args: + data1 (pl.DataFrame): The DataFrame which contains the full performance trajectory for algorithm 1. Should be generated from a DataManager. + data2 (pl.DataFrame): The DataFrame which contains the full performance trajectory for algorithm 2. Should be generated from a DataManager. + x_column (str, optional): The variable corresponding to the first objective. + y_column (str, optional): The variable corresponding to the second objective. + min_y (float): Minimum value for the second objective. + max_y (float): Maximum value for the second objective. + scale_xlog (bool, optional): Whether the first objective should be log-scaled. Defaults to False. + scale_ylog (bool, optional): Whether the second objective should be log-scaled. Defaults to False. + ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. + file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + """ + # TODO: add an approximation version to speed up plotting + x = np.array(data1[[x_column, y_column, "data_id"]]) + y = np.array(data2[[x_column, y_column, "data_id"]]) + eaf_diff_rect = eafdiff(x, y, rectangles=True) + color_dict = { + k: v + for k, v in zip( + np.unique(eaf_diff_rect[:, -1]), + sbs.color_palette("viridis", n_colors=len(np.unique(eaf_diff_rect[:, -1]))), + ) + } + if ax is None: + fig, ax = plt.subplots(figsize=(16, 9)) + for rect in eaf_diff_rect: + ax.add_patch( + Rectangle( + (rect[0], rect[1]), + rect[2] - rect[0], + rect[3] - rect[1], + facecolor=color_dict[rect[-1]], + ) + ) + if min_y is None: + min_y = np.min(x[1]) + if max_y is None: + max_y = np.max(x[1]) + ax.set_ylim(min_y, max_y) + ax.set_xlim((0,1000)) + if scale_ylog: + ax.set_yscale("log") + if scale_xlog: + ax.set_xscale("log") + if file_name: + fig.tight_layout() + fig.savefig(file_name) diff --git a/src/iohinspector/plots/ecdf.py b/src/iohinspector/plots/ecdf.py new file mode 100644 index 0000000..e7a94c3 --- /dev/null +++ b/src/iohinspector/plots/ecdf.py @@ -0,0 +1,86 @@ +import matplotlib +import matplotlib.pyplot as plt +import seaborn as sbs +import polars as pl +from typing import Iterable, Optional +from iohinspector.metrics import get_data_ecdf + + +def plot_ecdf( + data: pl.DataFrame, + fval_var: str = "raw_y", + eval_var: str = "evaluations", + free_vars: Iterable[str] = ["algorithm_name"], + maximization: bool = False, + x_values: Iterable[int] = None, + x_min: int = None, + x_max: int = None, + scale_xlog: bool = True, + y_min: int = None, + y_max: int = None, + scale_ylog: bool = True, + ax: matplotlib.axes._axes.Axes = None, + file_name: Optional[str] = None, +): + """Function to plot empirical cumulative distribution function (Based on EAF) + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + eval_var (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". + fval_var (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". + free_vars (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. + x_min (float, optional): Minimum value to use for the 'eval_var', if not present the min of that column will be used. Defaults to None. + x_max (float, optional): Maximum value to use for the 'eval_var', if not present the max of that column will be used. Defaults to None. + x_values (Iterable[int], optional): List of x-values at which to plot the ECDF. If not provided, the x_min, x_max and scale_xlog arguments will be used to sample these points. + scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. + y_min (float, optional): Minimum value to use for the 'fval_var', if not present the min of that column will be used. Defaults to None. + y_max (float, optional): Maximum value to use for the 'fval_var', if not present the max of that column will be used. Defaults to None. + scale_ylog (bool, optional): Should the y-values be log-scaled before normalization. Defaults to True. + maximization (bool, optional): Boolean indicating whether the 'fval_var' is being maximized. Defaults to False. + measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. + ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. + file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + + Returns: + pd.DataFrame: pandas dataframe of the exact data used to create the plot + """ + dt_plot = get_data_ecdf( + data, + fval_var=fval_var, + eval_var=eval_var, + free_vars=free_vars, + maximization=maximization, + x_values=x_values, + x_min=x_min, + x_max=x_max, + scale_xlog=scale_xlog, + y_min=y_min, + y_max=y_max, + scale_ylog=scale_ylog, + turbo=True + ) + + if ax is None: + fig, ax = plt.subplots(figsize=(16, 9)) + if len(free_vars) == 1: + hue_arg = free_vars[0] + style_arg = free_vars[0] + else: + style_arg = free_vars[0] + hue_arg = dt_plot[free_vars[1:]].apply(tuple, axis=1) + + sbs.lineplot( + dt_plot, + x="evaluations", + y="eaf", + style=style_arg, + hue=hue_arg, + ax=ax, + ) + if scale_xlog: + ax.set_xscale("log") + ax.grid() + if ax is None and file_name: + fig.tight_layout() + fig.savefig(file_name) + return dt_plot \ No newline at end of file diff --git a/src/iohinspector/plots/fixed_budget.py b/src/iohinspector/plots/fixed_budget.py new file mode 100644 index 0000000..018a4a3 --- /dev/null +++ b/src/iohinspector/plots/fixed_budget.py @@ -0,0 +1,79 @@ +import matplotlib +import matplotlib.pyplot as plt +import seaborn as sbs +import polars as pl +from typing import Iterable +from iohinspector.metrics.fixed_budget import aggregate_convergence + +def plot_single_function_fixed_budget( + data: pl.DataFrame, + evaluation_variable: str = "evaluations", + fval_variable: str = "raw_y", + free_variables: Iterable[str] = ["algorithm_name"], + x_min: float = None, + x_max: float = None, + maximization: bool = False, + measures: Iterable[str] = ["geometric_mean"], + scale_xlog: bool = True, + scale_ylog: bool = True, + ax: matplotlib.axes._axes.Axes = None, + file_name: str = None, +): + """Create a fixed-budget plot for a given set of performance data. + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". + fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". + free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. + x_min (float, optional): Minimum value to use for the 'evaluation_variable', if not present the min of that column will be used. Defaults to None. + x_max (float, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. + maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. + measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. + scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. + scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. + ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. + file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + + Returns: + pd.DataFrame: The final dataframe which was used to create the plot + """ + dt_agg = aggregate_convergence( + data, + evaluation_variable=evaluation_variable, + fval_variable=fval_variable, + free_variables=free_variables, + x_min=x_min, + x_max=x_max, + maximization=maximization, + ) + + dt_molt = dt_agg.melt(id_vars=[evaluation_variable] + free_variables) + dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) + if ax is None: + fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + sbs.lineplot( + dt_plot, + x=evaluation_variable, + y="value", + style="variable", + hue=dt_plot[free_variables].apply(tuple, axis=1), + ax=ax, + ) + if scale_xlog: + ax.set_xscale("log") + if scale_ylog: + ax.set_yscale("log") + + + if ax is None and file_name: + fig.tight_layout() + fig.savefig(file_name) + + return dt_plot + + + +def plot_multi_function_fixed_budget(): + # either just loop over function column(s), or more advanced + raise NotImplementedError \ No newline at end of file diff --git a/src/iohinspector/plots/fixed_target.py b/src/iohinspector/plots/fixed_target.py new file mode 100644 index 0000000..5532b8f --- /dev/null +++ b/src/iohinspector/plots/fixed_target.py @@ -0,0 +1,87 @@ +import polars as pl +import matplotlib +import matplotlib.pyplot as plt +import seaborn as sbs +from typing import Iterable +from iohinspector.metrics.fixed_target import aggregate_running_time + + +def plot_single_function_fixed_target( + data: pl.DataFrame, + evaluation_variable: str = "evaluations", + fval_variable: str = "raw_y", + free_variables: Iterable[str] = ["algorithm_name"], + f_min: float = None, + f_max: float = None, + max_budget: int = None, + maximization: bool = False, + measures: Iterable[str] = ["ERT"], + scale_xlog: bool = True, + scale_ylog: bool = True, + ax: matplotlib.axes._axes.Axes = None, + file_name: str = None, +): + """Create a fixed-target plot for a given set of performance data. + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". + fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". + free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. + f_min (float, optional): Minimum value to use for the 'fval_variable', if not present the min of that column will be used. Defaults to None. + f_max (float, optional): Maximum value to use for the 'fval_variable', if not present the max of that column will be used. Defaults to None. + max_budget (int, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. + maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. + measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'ERT', 'mean', 'PAR-10', 'min', 'max'. Defaults to ['ERT']. + scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. + scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. + ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. + file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + + Returns: + pd.DataFrame: The final dataframe which was used to create the plot + """ + dt_agg = aggregate_running_time( + data, + evaluation_variable=evaluation_variable, + fval_variable=fval_variable, + free_variables=free_variables, + f_min=f_min, + f_max=f_max, + scale_flog=scale_xlog, + max_budget=max_budget, + maximization=maximization, + ) + + dt_molt = dt_agg.melt(id_vars=[fval_variable] + free_variables) + dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) + + if ax is None: + fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + + sbs.lineplot( + dt_plot, + x=fval_variable, + y="value", + style="variable", + hue=dt_plot[free_variables].apply(tuple, axis=1), + ax=ax, + ) + if scale_xlog: + ax.set_xscale("log") + if scale_ylog: + ax.set_yscale("log") + + if not maximization: + ax.set_xlim(ax.get_xlim()[::-1]) + + if ax is None and file_name: + fig.tight_layout() + fig.savefig(file_name) + + return dt_plot + + +def plot_multi_function_fixed_target(): + # either just loop over function column(s), or more advanced + raise NotImplementedError \ No newline at end of file diff --git a/src/iohinspector/plots/multi_objective.py b/src/iohinspector/plots/multi_objective.py new file mode 100644 index 0000000..be62692 --- /dev/null +++ b/src/iohinspector/plots/multi_objective.py @@ -0,0 +1,93 @@ +from typing import Iterable, Optional, cast +import numpy as np +import polars as pl +import matplotlib +import matplotlib.pyplot as plt +import seaborn as sbs +from iohinspector.indicators import final, add_indicator +from iohinspector.metrics import get_sequence + +def plot_paretofronts_2d( + data: pl.DataFrame, + obj_vars: Iterable[str] = ["raw_y", "F2"], + free_var: str = "algorithm_name", + ax: matplotlib.axes._axes.Axes = None, + file_name: str = None, +): + """Very basic plot to visualize pareto fronts + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + obj_vars (Iterable[str], optional): Which variables (length should be 2) to use for plotting. Defaults to ["raw_y", "F2"]. + free_vars (Iterable[str], optional): Which varialbes should be used to distinguish between categories. Defaults to ["algorithm_name"]. + ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. + file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + + Returns: + pd.DataFrame: pandas dataframe of the exact data used to create the plot + """ + assert len(obj_vars) == 2 + + df = add_indicator(data, final.NonDominated(), obj_vars) + if ax is None: + fig, ax = plt.subplots(figsize=(16, 9)) + sbs.scatterplot(df.filter(pl.col("final_nondominated") == True), x=obj_vars[0], y=obj_vars[1], hue=free_var, ax=ax) + if file_name: + fig.tight_layout() + fig.savefig(file_name) + return df + + +def plot_indicator_over_time( + data: pl.DataFrame, + obj_columns: Iterable[str] = ["raw_y", "F2"], + indicator: object = None, + eval_column: str = "evaluations", + evals_min: int = 1, + evals_max: int = 50_000, + nr_eval_steps: int = 50, + eval_scale_log: bool = True, + free_variable: str = "algorithm_name", + ax: matplotlib.axes._axes.Axes = None, + file_name: Optional[str] = None, +): + """Convenience function to plot the anytime performance of a single indicator. + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. + indicator (object): Indicator object from iohinspector.indicators + eval_column (Iterable[str], optional): Which columns in 'data' correspond to the objectives. Defaults to 'evaluations'. + evals_min (int, optional): Lower bound for eval_column. Defaults to 0. + evals_max (int, optional): Upper bound for eval_column. Defaults to 50_000. + nr_eval_steps (int, optional): Number of steps between lower and upper bounds of eval_column. Defaults to 50. + free_variable (str, optional): Variable which corresponds to category to differentiate in the plot. Defaults to 'algorithm_name'. + ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. + file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + """ + + evals = get_sequence( + evals_min, evals_max, nr_eval_steps, cast_to_int=True, scale_log=eval_scale_log + ) + df = add_indicator( + data, indicator, objective_columns=obj_columns, evals=evals + ).to_pandas() + if ax is None: + fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + sbs.lineplot( + df, + x=eval_column, + y=indicator.var_name, + hue=free_variable, + palette=sbs.color_palette(n_colors=len(np.unique(data[free_variable]))), + ax=ax, + ) + ax.set_xlabel(eval_column) + ax.set_xlim(evals_min, evals_max) + ax.set_xscale("log") + ax.grid() + if file_name: + fig.tight_layout() + fig.savefig(file_name) + + return df diff --git a/src/iohinspector/plots/ranking.py b/src/iohinspector/plots/ranking.py new file mode 100644 index 0000000..1a7acd0 --- /dev/null +++ b/src/iohinspector/plots/ranking.py @@ -0,0 +1,186 @@ +from typing import Iterable, Optional +import polars as pl +import numpy as np +import pandas as pd +import matplotlib +import matplotlib.pyplot as plt +import seaborn as sbs +from iohinspector.metrics import get_tournament_ratings +from iohinspector.indicators import add_indicator + + +def plot_tournament_ranking( + data, + alg_vars: Iterable[str] = ["algorithm_name"], + fid_vars: Iterable[str] = ["function_name"], + perf_var: str = "raw_y", + nrounds: int = 25, + maximization: bool = False, + ax: matplotlib.axes._axes.Axes = None, + file_name: str = None, +): + """Method to plot ELO ratings of a set of algorithm on a set of problems. + Calculated based on nrounds of competition, where in each round all algorithms face all others (pairwise) on every function. + For each round, a sampled performance value is taken from the data and used to determine the winner. + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + alg_vars (Iterable[str], optional): Which variables specific the algortihms which will compete. Defaults to ["algorithm_name"]. + fid_vars (Iterable[str], optional): Which variables denote the problems on which will be competed. Defaults to ["function_name"]. + perf_var (str, optional): Which variable corresponds to the performance. Defaults to "raw_y". + nrounds (int, optional): How many round should be played. Defaults to 25. + maximization (bool, optional): Whether the performance should be maximized. Defaults to False. + ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. + file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + + Returns: + pd.DataFrame: pandas dataframe of the exact data used to create the plot + """ + # candlestick plot based on average and volatility + dt_elo = get_tournament_ratings( + data, alg_vars, fid_vars, perf_var, nrounds, maximization + ) + if ax is None: + _, ax = plt.subplots(1, 1, figsize=(10, 5)) + + sbs.pointplot(data=dt_elo, x=alg_vars[0], y="Rating", linestyle="none", ax=ax) + + ax.errorbar( + dt_elo[alg_vars[0]], + dt_elo["Rating"], + yerr=dt_elo["Deviation"], + fmt="o", + color="blue", + alpha=0.6, + capsize=5, + elinewidth=1.5, + ) + ax.grid() + + if file_name: + plt.tight_layout() + plt.savefig(file_name) + return dt_elo + + +def robustranking(): + # to decide which plot(s) to use and what exact interface to define + raise NotImplementedError() + + +def stats_comparison(): + # heatmap or graph of statistical comparisons + raise NotImplementedError() + + +def winnning_fraction_heatmap(): + # nevergrad-like heatmap + raise NotImplementedError() + + + + +def plot_robustrank_over_time( + data: pl.DataFrame, + obj_columns: Iterable[str], + evals: Iterable[int], + indicator: object, + filename_fig: Optional[str] = None, +): + """Plot robust ranking at distinct timesteps + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. + evals (Iterable[int]): Timesteps at which to get the rankings + indicator (object): Indicator object from iohinspector.indicators + filename_fig (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + """ + from robustranking import Benchmark + from robustranking.comparison import MOBootstrapComparison, BootstrapComparison + from robustranking.utils.plots import plot_ci_list, plot_line_ranks + + df = add_indicator( + data, indicator, objective_columns=obj_columns, evals=evals + ).to_pandas() + df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] + dt_pivoted = pd.pivot( + df_part, + index=["algorithm_name", "run_id"], + columns=["evaluations"], + values=[indicator.var_name], + ).reset_index() + dt_pivoted.columns = ["algorithm_name", "run_id"] + evals + benchmark = Benchmark() + benchmark.from_pandas(dt_pivoted, "algorithm_name", "run_id", evals) + comparison = MOBootstrapComparison( + benchmark, + alpha=0.05, + minimise=indicator.minimize, + bootstrap_runs=1000, + aggregation_method=np.mean, + ) + fig, axs = plt.subplots(1, 4, figsize=(16, 9), sharey=True) + for ax, runtime in zip(axs.ravel(), benchmark.objectives): + plot_ci_list(comparison, objective=runtime, ax=ax) + if runtime != evals[0]: + ax.set_ylabel("") + if runtime != evals[-1]: + ax.get_legend().remove() + ax.set_title(runtime) + + plt.tight_layout() + if filename_fig: + plt.savefig(filename_fig) + plt.close() + + +def plot_robustrank_changes( + data: pl.DataFrame, + obj_columns: Iterable[str], + evals: Iterable[int], + indicator: object, + filename_fig: Optional[str] = None, +): + """Plot robust ranking changes at distinct timesteps + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. + evals (Iterable[int]): Timesteps at which to get the rankings + indicator (object): Indicator object from iohinspector.indicators + filename_fig (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + """ + from robustranking import Benchmark + from robustranking.comparison import MOBootstrapComparison, BootstrapComparison + from robustranking.utils.plots import plot_ci_list, plot_line_ranks + + df = add_indicator( + data, indicator, objective_columns=obj_columns, evals=evals + ).to_pandas() + df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] + dt_pivoted = pd.pivot( + df_part, + index=["algorithm_name", "run_id"], + columns=["evaluations"], + values=[indicator.var_name], + ).reset_index() + dt_pivoted.columns = ["algorithm_name", "run_id"] + evals + + comparisons = { + f"{eval}": BootstrapComparison( + Benchmark().from_pandas(dt_pivoted, "algorithm_name", "run_id", eval), + alpha=0.05, + minimise=indicator.minimize, + bootstrap_runs=1000, + ) + for eval in evals + } + + fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + plot_line_ranks(comparisons, ax=ax) + + plt.tight_layout() + if filename_fig: + plt.savefig(filename_fig) + plt.close() diff --git a/src/iohinspector/plots/single_run.py b/src/iohinspector/plots/single_run.py new file mode 100644 index 0000000..340ff7e --- /dev/null +++ b/src/iohinspector/plots/single_run.py @@ -0,0 +1,50 @@ +import matplotlib +import matplotlib.pyplot as plt +import seaborn as sbs +import polars as pl +from typing import Iterable, Optional +import numpy as np + + +def plot_heatmap_single_run( + data: pl.DataFrame, + var_cols: Iterable[str], + eval_col: str = "evaluations", + scale_xlog: bool = True, + x_mins: Iterable[float] = [-5], + x_maxs: Iterable[float] = [5], + ax: matplotlib.axes._axes.Axes = None, + file_name: Optional[str] = None, +): + """Create a heatmap showing the search space points evaluated in a single run + + Args: + data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. + var_cols (Iterable[str]): The variables which correspond to the searchspace variable columns + eval_col (str): The variable corresponding to evaluations. Defaults to 'evaluations' + scale_xlog (bool, optional): Whether the evaluations should be log-scaled. Defaults to True. + x_mins (Iterable[float], optional): Minimum bound for the variables. Should be of the same length as 'var_cols'. Defaults to [-5]. + x_maxs (Iterable[float], optional): Maximum bound for the variables. Should be of the same length as 'var_cols'.. Defaults to [5]. + ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. + file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + + Returns: + pd.DataFrame: pandas dataframe of the exact data used to create the plot + """ + assert data["data_id"].n_unique() == 1 + dt_plot = data[var_cols].transpose().to_pandas() + dt_plot.columns = list(data[eval_col]) + x_mins_arr = np.array(x_mins) + x_maxs_arr = np.array(x_maxs) + dt_plot = (dt_plot.subtract(x_mins_arr, axis=0)).divide(x_maxs_arr - x_mins_arr, axis=0) + if ax is None: + fig, ax = plt.subplots(figsize=(32, 9)) + sbs.heatmap(dt_plot, cmap="viridis", vmin=0, vmax=1, ax=ax) + if scale_xlog: + ax.set_xscale("log") + ax.set_xlim(1, len(data)) + + if file_name: + fig.tight_layout() + fig.savefig(file_name) + return dt_plot diff --git a/tests/test_metrics/test_attractor_network.py b/tests/test_metrics/test_attractor_network.py new file mode 100644 index 0000000..8adad4d --- /dev/null +++ b/tests/test_metrics/test_attractor_network.py @@ -0,0 +1,52 @@ +import unittest +import polars as pl +import numpy as np +from iohinspector.metrics import get_attractor_network + +class TestGetAttractorNetwork(unittest.TestCase): + def test_basic(self): + data = pl.DataFrame({ + "x1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], + "x2": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], + "raw_y": [35, 33, 31, 29, 27, 23, 18, 16, 14, 12, 10, 9, 6], + "evaluations": [1,42, 81,121,161,201,241,281,321,361,401,442,481], + "data_id": [1]*13 + }) + nodes, edges = get_attractor_network( + data, + coord_vars=["x1", "x2"], + fval_var="raw_y", + eval_var="evaluations", + ) + # Check nodes DataFrame shape and content + self.assertEqual(nodes.shape[1], 5) # x1, x2, y, count, evals + self.assertGreaterEqual(nodes.shape[0], 1) + # Check that node coordinates and y values are as expected + self.assertIn("x1", nodes.columns) + self.assertIn("x2", nodes.columns) + self.assertIn("y", nodes.columns) + self.assertIn("count", nodes.columns) + self.assertIn("evals", nodes.columns) + # Check that the first node matches the first stagnation point + self.assertEqual(nodes.iloc[0]["x1"], 0) + self.assertEqual(nodes.iloc[0]["x2"], 0) + self.assertEqual(nodes.iloc[0]["y"], 35) + self.assertEqual(nodes.iloc[-1]["x1"], 10) + self.assertEqual(nodes.iloc[-1]["x2"], 10) + self.assertEqual(nodes.iloc[-1]["y"], 10) + # Check that counts and evals are positive + self.assertTrue((nodes["count"] > 0).all()) + self.assertTrue((nodes["evals"] > 0).all()) + + # Check edges DataFrame shape and content + self.assertEqual(edges.shape[1], 4) # start, end, count, stag_length_avg + self.assertTrue((edges["count"] > 0).all()) + self.assertTrue((edges["stag_length_avg"] > 0).all()) + # Check that start and end refer to valid node indices + self.assertTrue(edges["start"].isin(nodes.index).all()) + self.assertTrue(edges["end"].isin(nodes.index).all()) + + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_eaf.py b/tests/test_metrics/test_eaf.py new file mode 100644 index 0000000..f6eec00 --- /dev/null +++ b/tests/test_metrics/test_eaf.py @@ -0,0 +1,74 @@ +from turtle import pd +import unittest +import polars as pl +import numpy as np +import matplotlib +from pathlib import Path +from iohinspector.metrics import get_discritized_eaf_single_objective +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + +class TestGetDiscritizedEAF(unittest.TestCase): + def setUp(self): + # Create a simple polars DataFrame for testing + self.data = pl.DataFrame({ + "evaluations": [1, 10, 100, 1000], + "raw_y": [1.0, 0.1, 0.01, 0.001], + "data_id": [1, 1, 1, 1] + }) + + self.multi_data = pl.DataFrame({ + "evaluations": [1, 10, 100, 1000, 1, 10, 100, 1000], + "raw_y": [1.0, 0.1, 0.01, 0.001, 1.5, 0.15, 0.015, 0.0015], + "data_id": [1, 1, 1, 1, 2, 2, 2, 2] + }) + + def test_basic_single_data_id(self): + result = get_discritized_eaf_single_objective(self.data) + self.assertIn('eaf_target', result.index.names) + self.assertTrue(len(result.columns) == 10) # default x_targets + self.assertEqual(result.shape[0], 101) # default y_targets + # Assert all values are 1 or 0 + self.assertTrue(result[self.data["evaluations"].to_list()].applymap(lambda x: x in [1, 0]).all().all()) + self.assertEqual(result[1].tolist()[-1], 0) + self.assertEqual(result[1000].tolist()[0], 1) + + def test_basic_multi_data_id(self): + result = get_discritized_eaf_single_objective(self.multi_data) + self.assertIn('eaf_target', result.index.names) + self.assertTrue(len(result.columns) == 10) # default x_targets + self.assertEqual(result.shape[0], 101) # default y_targets + # Assert all values are 1, 0.5 or 0 + self.assertTrue(result[self.multi_data["evaluations"].to_list()].applymap(lambda x: x in [1, 0.5, 0]).all().all()) + self.assertEqual(result[1].tolist()[-1], 0) + self.assertEqual(result[1000].tolist()[0], 1) + + def test_custom_eval_values(self): + eval_values = [1, 3, 5] + result = get_discritized_eaf_single_objective(self.data, eval_values=eval_values) + self.assertTrue(all(x in result.columns for x in eval_values)) + + def test_custom_eval_min_max(self): + result = get_discritized_eaf_single_objective(self.data, eval_min=2, eval_max=4, eval_targets=2) + self.assertTrue(all(x in result.columns for x in [2, 4])) + + def test_custom_f_min_max_targets(self): + result = get_discritized_eaf_single_objective(self.data, f_min=0.0, f_max=1.0, f_targets=5) + self.assertEqual(result.shape[0], 5) + self.assertAlmostEqual(result.index.min(), 0.0) + self.assertAlmostEqual(result.index.max(), 1.0) + + def test_scale_eval_log_and_f_log(self): + result = get_discritized_eaf_single_objective(self.data, scale_f_log=False, scale_eval_log=False) + # Check that all values except the last row are 1, and the last row is 0 + values = result.values + self.assertTrue(np.all(values[:-1] == 1)) + self.assertTrue(np.all(values[-1] == 0)) + + self.budgets = result.columns.to_list() + np.testing.assert_allclose(self.budgets, np.linspace(1, 1000, 10)) + + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_ecdf.py b/tests/test_metrics/test_ecdf.py index e8b4922..0fea6fe 100644 --- a/tests/test_metrics/test_ecdf.py +++ b/tests/test_metrics/test_ecdf.py @@ -66,5 +66,15 @@ def test_ecdf_with_x_min_x_max(self): algo2_eaf.sort() np.testing.assert_allclose(algo2_eaf, [0, 1/6, 1/3]) + def test_basic_ecdf_turbo(self): + result = get_data_ecdf(self.df, scale_xlog=False, scale_ylog=False, turbo=True) + algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() + algo1_eaf.sort() + np.testing.assert_allclose(algo1_eaf, [0.5, 0.625, 0.75, 0.875, 1]) + + algo2_eaf = result[result["algorithm_name"] == "algo2"]["eaf"].to_numpy() + algo2_eaf.sort() + np.testing.assert_allclose(algo2_eaf, [0, 0.125, 0.25, 0.375, 0.5]) + if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_normalise_objectives.py b/tests/test_metrics/test_normalise_objectives.py deleted file mode 100644 index a493574..0000000 --- a/tests/test_metrics/test_normalise_objectives.py +++ /dev/null @@ -1,162 +0,0 @@ -import unittest -import polars as pl -import numpy as np -import warnings -from iohinspector.metrics import normalize_objectives, add_normalized_objectives, transform_fval - -class TestNormalizeObjectives(unittest.TestCase): - def setUp(self): - self.df = pl.DataFrame({ - "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], - "other": [10, 20, 30, 40, 50] - }) - - def test_basic_normalization(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"]) - self.assertIn("ert", normed.columns) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) - - def test_maximization(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"], maximize=True) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [0, 0.25, 0.5, 0.75, 1]) - - def test_bounds(self): - bounds = {"raw_y": (0, 10)} - normed = normalize_objectives(self.df, obj_cols=["raw_y"], bounds=bounds) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [0.9, 0.8, 0.7, 0.6, 0.5]) - - def test_log_scale(self): - df = pl.DataFrame({"raw_y": [1, 10, 100, 1000, 10000]}) - normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) - arr = normed["ert"].to_numpy() - np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) - - def test_log_scale_with_zero_warns(self): - df = pl.DataFrame({"raw_y": [0, 1, 10]}) - with warnings.catch_warnings(record=True) as w: - warnings.simplefilter("always") - normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) - self.assertTrue(any("Lower bound" in str(warn.message) for warn in w)) - arr = normed["ert"].to_numpy() - self.assertTrue(np.all((arr >= 0) & (arr <= 1))) - - def test_multiple_objectives(self): - df = pl.DataFrame({ - "raw_y": [1, 2, 3], - "other": [10, 20, 30] - }) - normed = normalize_objectives(df, obj_cols=["raw_y", "other"]) - arr_raw_y = normed["ert_raw_y"].to_numpy() - np.testing.assert_allclose(arr_raw_y, [1.0, 0.5, 0.0]) - arr_other = normed["ert_other"].to_numpy() - np.testing.assert_allclose(arr_other, [1.0, 0.5, 0.0]) - - - def test_column_prefix(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"], prefix="normed") - self.assertIn("normed", normed.columns) - - def test_dict_log_and_maximize(self): - df = pl.DataFrame({"a": [1, 10, 100], "b": [3, 2, 1]}) - normed = normalize_objectives( - df, - obj_cols=["a", "b"], - log_scale={"a": True, "b": False}, - maximize={"a": True, "b": False} - ) - arr_raw_y = normed["ert_a"].to_numpy() - np.testing.assert_allclose(arr_raw_y, [0.0, 0.5, 1.0]) - arr_other = normed["ert_b"].to_numpy() - np.testing.assert_allclose(arr_other, [0.0, 0.5, 1.0]) - # a is maximized and log scaled, b is minimized and linear - - def test_add_normalized_objectives_basic(self): - df = pl.DataFrame({ - "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], - "other": [10, 20, 30, 40, 50] - }) - normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"]) - self.assertIn("obj1", normed.columns) - self.assertIn("obj2", normed.columns) - arr_obj1 = normed["obj1"].to_numpy() - arr_obj2 = normed["obj2"].to_numpy() - np.testing.assert_allclose(arr_obj1, [0, 0.25, 0.5, 0.75, 1]) - np.testing.assert_allclose(arr_obj2, [0, 0.25, 0.5, 0.75, 1]) - - def test_add_normalized_objectives_with_bounds(self): - df = pl.DataFrame({ - "raw_y": [1.0, 2.0, 3.0], - "other": [10, 20, 30] - }) - min_vals = pl.DataFrame({"raw_y": [0.0], "other": [0]}) - max_vals = pl.DataFrame({"raw_y": [10.0], "other": [40]}) - normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"], min_vals=min_vals, max_vals=max_vals) - arr_obj1 = normed["obj1"].to_numpy() - arr_obj2 = normed["obj2"].to_numpy() - np.testing.assert_allclose(arr_obj1, [0.1, 0.2, 0.3]) - np.testing.assert_allclose(arr_obj2, [0.25, 0.5, 0.75]) - - def test_add_normalized_objectives_single_objective(self): - df = pl.DataFrame({"raw_y": [1, 2, 3]}) - normed = add_normalized_objectives(df, obj_cols=["raw_y"]) - self.assertIn("obj", normed.columns) - arr = normed["obj"].to_numpy() - np.testing.assert_allclose(arr, [0, 0.5, 1]) - - def test_add_normalized_objectives_no_min_max(self): - df = pl.DataFrame({"raw_y": [5, 10, 15]}) - normed = add_normalized_objectives(df, obj_cols=["raw_y"]) - arr = normed["obj"].to_numpy() - np.testing.assert_allclose(arr, [0, 0.5, 1]) - - def test_transform_fval_basic(self): - df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) - res = transform_fval(df) - arr = res["eaf"].to_numpy() - # log10(1e-8) = -8, log10(1e8) = 8 - # normalized = (log10(x) - (-8)) / (8 - (-8)) = (log10(x) + 8) / 16 - expected = [np.abs((np.log10(x) - 8) / 16) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] - np.testing.assert_allclose(arr, expected) - - def test_transform_fval_maximization(self): - df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) - res = transform_fval(df, maximization=True) - arr = res["eaf"].to_numpy() - expected = [(np.log10(x) + 8) / 16 for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] - - np.testing.assert_allclose(arr, expected) - - def test_transform_fval_minimization(self): - df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) - res = transform_fval(df, maximization=False) - arr = res["eaf"].to_numpy() - expected = [1 - ((np.log10(x) + 8) / 16) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] - np.testing.assert_allclose(arr, expected) - - def test_transform_fval_linear_scale(self): - df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) - res = transform_fval(df, scale_log=False) - arr = res["eaf"].to_numpy() - expected = [1-(x - 1e-8) / (1e8 - 1e-8) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] - np.testing.assert_allclose(arr, expected) - - def test_transform_fval_custom_bounds(self): - df = pl.DataFrame({"raw_y": [0, 5, 10]}) - res = transform_fval(df, lb=0, ub=10, scale_log=False) - arr = res["eaf"].to_numpy() - # For minimization, 0 maps to 1, 10 maps to 0 - expected = [1 - (x / 10) for x in [0, 5, 10]] - np.testing.assert_allclose(arr, expected) - - def test_transform_fval_column_name(self): - df = pl.DataFrame({"score": [1, 10, 100]}) - res = transform_fval(df, lb=1, ub=100, scale_log=True, fval_col="score") - arr = res["eaf"].to_numpy() - expected = [1- (np.log10(x) - np.log10(1)) / (np.log10(100) - np.log10(1)) for x in [1, 10, 100]] - np.testing.assert_allclose(arr, expected) - -if __name__ == "__main__": - unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_ranking.py b/tests/test_metrics/test_ranking.py new file mode 100644 index 0000000..dc7bdb1 --- /dev/null +++ b/tests/test_metrics/test_ranking.py @@ -0,0 +1,51 @@ +import unittest +import numpy as np +import polars as pl +import pandas as pd +from iohinspector.metrics import get_tournament_ratings + +class TestGetTournamentRatings(unittest.TestCase): + def setUp(self): + # Create a simple polars DataFrame for testing + self.data = pl.DataFrame({ + "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], + "function_name": ["f1", "f2", "f3", "f1", "f2", "f3", "f1", "f2", "f3"], + "raw_y": [1.0, 2.0, 1.7, 1.5, 2.8, 2.1, 0.9, 0.5, 1.6] + }) + + def test_basic(self): + result = get_tournament_ratings(self.data) + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("Rating", result.columns) + self.assertIn("Deviation", result.columns) + self.assertIn("algorithm_name", result.columns) + self.assertEqual(len(result), 3) # Three algorithms + # Check that algorithms are ordered by rating: C, A, B + sorted_algos = result.sort_values("Rating", ascending=False)["algorithm_name"].tolist() + self.assertEqual(sorted_algos, ["C", "A", "B"]) + + def test_basic_maximisation(self): + result = get_tournament_ratings(self.data, maximization=True) + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("Rating", result.columns) + self.assertIn("Deviation", result.columns) + self.assertIn("algorithm_name", result.columns) + self.assertEqual(len(result), 3) # Three algorithms + # Check that algorithms are ordered by rating: C, A, B + sorted_algos = result.sort_values("Rating", ascending=False)["algorithm_name"].tolist() + self.assertEqual(sorted_algos, ["B", "A", "C"]) + + + def test_single_function(self): + data = pl.DataFrame({ + "algorithm_name": ["A", "B"], + "function_name": ["f1", "f1"], + "raw_y": [1.0, 2.0] + }) + result = get_tournament_ratings(data, nrounds=25) + self.assertEqual(len(result), 2) + self.assertTrue(set(result["algorithm_name"]) == {"A", "B"}) + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_trajectory.py b/tests/test_metrics/test_trajectory.py new file mode 100644 index 0000000..bce92c2 --- /dev/null +++ b/tests/test_metrics/test_trajectory.py @@ -0,0 +1,66 @@ +import unittest +import polars as pl +import numpy as np +from iohinspector.metrics import get_trajectory + +class TestGetTrajectory(unittest.TestCase): + def setUp(self): + # Example data with two algorithms, two data_ids, and three evaluations each + self.data = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2, 2], + "algorithm_name": ["A", "A", "A", "B", "B", "B"], + "evaluations": [1, 10, 20, 1, 10, 20], + "raw_y": [0.5, 0.4, 0.3, 1.0, 0.9, 0.7] + }) + + def test_basic_trajectory(self): + result = get_trajectory(self.data) + self.assertIsInstance(result, pl.DataFrame) + # Should have as many rows as input (since all evaluations present) + self.assertEqual(result.shape[0], 40) # 2 algorithms * 20 evaluations + self.assertIn("evaluations", result.columns) + self.assertIn("raw_y", result.columns) + # Check that all evaluation points are present + for algo in self.data["algorithm_name"].unique(): + evals = result.filter(pl.col("algorithm_name") == algo)["evaluations"].to_list() + self.assertEqual(set(evals), set(range(1, 21))) + # Check that raw_y is non-increasing for each algorithm + for algo in self.data["algorithm_name"].unique(): + raw_y_values = result.filter(pl.col("algorithm_name") == algo).sort("evaluations")["raw_y"].to_list() + self.assertTrue(all(x >= y for x, y in zip(raw_y_values, raw_y_values[1:]))) + + def test_traj_length(self): + # Only first two evaluations should be present + result = get_trajectory(self.data, traj_length=1) + for algo in self.data["algorithm_name"].unique(): + evals = result.filter(pl.col("algorithm_name") == algo)["evaluations"].to_list() + self.assertEqual(set(evals), set(range(1, 3))) + + result = get_trajectory(self.data, traj_length=10) + for algo in self.data["algorithm_name"].unique(): + evals = result.filter(pl.col("algorithm_name") == algo)["evaluations"].to_list() + self.assertEqual(set(evals), set(range(1, 12))) + + def test_min_fevals(self): + # Start from evaluation 2 + result = get_trajectory(self.data, min_fevals=2) + for algo in self.data["algorithm_name"].unique(): + evals = result.filter(pl.col("algorithm_name") == algo)["evaluations"].to_list() + self.assertEqual(set(evals), set(range(2, 21))) + + + def test_custom_free_variables(self): + # Use only data_id as free variable + result = get_trajectory(self.data, free_variables=[]) + self.assertIn("data_id", result.columns) + self.assertIn("raw_y", result.columns) + + def test_maximization(self): + result = get_trajectory(self.data, maximization=True) + + for algo in self.data["algorithm_name"].unique(): + raw_y_values = result.filter(pl.col("algorithm_name") == algo).sort("evaluations")["raw_y"].to_list() + self.assertTrue(all(x <= y for x, y in zip(raw_y_values, raw_y_values[1:]))) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_utils.py b/tests/test_metrics/test_utils.py index 9482304..856dffb 100644 --- a/tests/test_metrics/test_utils.py +++ b/tests/test_metrics/test_utils.py @@ -1,7 +1,9 @@ import unittest import numpy as np -from iohinspector.metrics.utils import get_sequence, geometric_mean +from iohinspector.metrics.utils import get_sequence import polars as pl +from iohinspector.metrics import normalize_objectives, add_normalized_objectives, transform_fval +import warnings class TestGetSequence(unittest.TestCase): """ @@ -75,29 +77,160 @@ def test_cast_to_int_with_duplicates(self): seq = get_sequence(0, 0.9, 10, scale_log=False, cast_to_int=True) np.testing.assert_array_equal(seq, np.array([0])) -class TestGeometricMean(unittest.TestCase): - def test_geometric_mean_positive(self): - s = pl.Series("a", [1, 10, 100]) - result = geometric_mean(s) - expected = np.exp(np.mean(np.log([1, 10, 100]))) - self.assertAlmostEqual(result, expected) - - def test_geometric_mean_with_ones(self): - s = pl.Series("a", [1, 1, 1, 1]) - result = geometric_mean(s) - self.assertEqual(result, 1.0) - - def test_geometric_mean_single_value(self): - s = pl.Series("a", [42]) - result = geometric_mean(s) - self.assertAlmostEqual(result, 42.0) - - def test_geometric_mean_large_numbers(self): - s = pl.Series("a", [1e10, 1e12, 1e14]) - result = geometric_mean(s) - expected = np.exp(np.mean(np.log([1e10, 1e12, 1e14]))) - self.assertAlmostEqual(result, expected) +class TestNormalizeObjectives(unittest.TestCase): + def setUp(self): + self.df = pl.DataFrame({ + "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], + "other": [10, 20, 30, 40, 50] + }) + + def test_basic_normalization(self): + normed = normalize_objectives(self.df, obj_cols=["raw_y"]) + self.assertIn("ert", normed.columns) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) + + def test_maximization(self): + normed = normalize_objectives(self.df, obj_cols=["raw_y"], maximize=True) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [0, 0.25, 0.5, 0.75, 1]) + + def test_bounds(self): + bounds = {"raw_y": (0, 10)} + normed = normalize_objectives(self.df, obj_cols=["raw_y"], bounds=bounds) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [0.9, 0.8, 0.7, 0.6, 0.5]) + + def test_log_scale(self): + df = pl.DataFrame({"raw_y": [1, 10, 100, 1000, 10000]}) + normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) + arr = normed["ert"].to_numpy() + np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) + + def test_log_scale_with_zero_warns(self): + df = pl.DataFrame({"raw_y": [0, 1, 10]}) + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always") + normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) + self.assertTrue(any("Lower bound" in str(warn.message) for warn in w)) + arr = normed["ert"].to_numpy() + self.assertTrue(np.all((arr >= 0) & (arr <= 1))) + + def test_multiple_objectives(self): + df = pl.DataFrame({ + "raw_y": [1, 2, 3], + "other": [10, 20, 30] + }) + normed = normalize_objectives(df, obj_cols=["raw_y", "other"]) + arr_raw_y = normed["ert_raw_y"].to_numpy() + np.testing.assert_allclose(arr_raw_y, [1.0, 0.5, 0.0]) + arr_other = normed["ert_other"].to_numpy() + np.testing.assert_allclose(arr_other, [1.0, 0.5, 0.0]) + + + def test_column_prefix(self): + normed = normalize_objectives(self.df, obj_cols=["raw_y"], prefix="normed") + self.assertIn("normed", normed.columns) + + def test_dict_log_and_maximize(self): + df = pl.DataFrame({"a": [1, 10, 100], "b": [3, 2, 1]}) + normed = normalize_objectives( + df, + obj_cols=["a", "b"], + log_scale={"a": True, "b": False}, + maximize={"a": True, "b": False} + ) + arr_raw_y = normed["ert_a"].to_numpy() + np.testing.assert_allclose(arr_raw_y, [0.0, 0.5, 1.0]) + arr_other = normed["ert_b"].to_numpy() + np.testing.assert_allclose(arr_other, [0.0, 0.5, 1.0]) + # a is maximized and log scaled, b is minimized and linear + + def test_add_normalized_objectives_basic(self): + df = pl.DataFrame({ + "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], + "other": [10, 20, 30, 40, 50] + }) + normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"]) + self.assertIn("obj1", normed.columns) + self.assertIn("obj2", normed.columns) + arr_obj1 = normed["obj1"].to_numpy() + arr_obj2 = normed["obj2"].to_numpy() + np.testing.assert_allclose(arr_obj1, [0, 0.25, 0.5, 0.75, 1]) + np.testing.assert_allclose(arr_obj2, [0, 0.25, 0.5, 0.75, 1]) + + def test_add_normalized_objectives_with_bounds(self): + df = pl.DataFrame({ + "raw_y": [1.0, 2.0, 3.0], + "other": [10, 20, 30] + }) + min_vals = pl.DataFrame({"raw_y": [0.0], "other": [0]}) + max_vals = pl.DataFrame({"raw_y": [10.0], "other": [40]}) + normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"], min_vals=min_vals, max_vals=max_vals) + arr_obj1 = normed["obj1"].to_numpy() + arr_obj2 = normed["obj2"].to_numpy() + np.testing.assert_allclose(arr_obj1, [0.1, 0.2, 0.3]) + np.testing.assert_allclose(arr_obj2, [0.25, 0.5, 0.75]) + + def test_add_normalized_objectives_single_objective(self): + df = pl.DataFrame({"raw_y": [1, 2, 3]}) + normed = add_normalized_objectives(df, obj_cols=["raw_y"]) + self.assertIn("obj", normed.columns) + arr = normed["obj"].to_numpy() + np.testing.assert_allclose(arr, [0, 0.5, 1]) + + def test_add_normalized_objectives_no_min_max(self): + df = pl.DataFrame({"raw_y": [5, 10, 15]}) + normed = add_normalized_objectives(df, obj_cols=["raw_y"]) + arr = normed["obj"].to_numpy() + np.testing.assert_allclose(arr, [0, 0.5, 1]) + + def test_transform_fval_basic(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df) + arr = res["eaf"].to_numpy() + # log10(1e-8) = -8, log10(1e8) = 8 + # normalized = (log10(x) - (-8)) / (8 - (-8)) = (log10(x) + 8) / 16 + expected = [np.abs((np.log10(x) - 8) / 16) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_maximization(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df, maximization=True) + arr = res["eaf"].to_numpy() + expected = [(np.log10(x) + 8) / 16 for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_minimization(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df, maximization=False) + arr = res["eaf"].to_numpy() + expected = [1 - ((np.log10(x) + 8) / 16) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_linear_scale(self): + df = pl.DataFrame({"raw_y": [1e-8, 1e-4, 1e-2, 1, 1e8]}) + res = transform_fval(df, scale_log=False) + arr = res["eaf"].to_numpy() + expected = [1-(x - 1e-8) / (1e8 - 1e-8) for x in [1e-8, 1e-4, 1e-2, 1, 1e8]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_custom_bounds(self): + df = pl.DataFrame({"raw_y": [0, 5, 10]}) + res = transform_fval(df, lb=0, ub=10, scale_log=False) + arr = res["eaf"].to_numpy() + # For minimization, 0 maps to 1, 10 maps to 0 + expected = [1 - (x / 10) for x in [0, 5, 10]] + np.testing.assert_allclose(arr, expected) + + def test_transform_fval_column_name(self): + df = pl.DataFrame({"score": [1, 10, 100]}) + res = transform_fval(df, lb=1, ub=100, scale_log=True, fval_col="score") + arr = res["eaf"].to_numpy() + expected = [1- (np.log10(x) - np.log10(1)) / (np.log10(100) - np.log10(1)) for x in [1, 10, 100]] + np.testing.assert_allclose(arr, expected) if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_plots/__init__.py b/tests/test_plots/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/test_plots/test_attractor_network.py b/tests/test_plots/test_attractor_network.py new file mode 100644 index 0000000..4d95524 --- /dev/null +++ b/tests/test_plots/test_attractor_network.py @@ -0,0 +1,26 @@ +import unittest +import polars as pl +import numpy as np +from iohinspector.plots import plot_attractor_network + +class TestGetAttractorNetwork(unittest.TestCase): + def test_basic(self): + data = pl.DataFrame({ + "x1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], + "x2": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], + "raw_y": [35, 33, 31, 29, 27, 23, 18, 16, 14, 12, 10, 9, 6], + "evaluations": [1,42, 81,121,161,201,241,281,321,361,401,442,481], + "data_id": [1]*13 + }) + plot_attractor_network( + data, + coord_vars=["x1", "x2"], + fval_var="raw_y", + eval_var="evaluations", + ) + + + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_eaf.py b/tests/test_plots/test_eaf.py new file mode 100644 index 0000000..83a1c25 --- /dev/null +++ b/tests/test_plots/test_eaf.py @@ -0,0 +1,50 @@ +import unittest +import polars as pl +import numpy as np +import matplotlib +from pathlib import Path +from iohinspector.plots import plot_eaf_single_objective, plot_eaf_pareto, plot_eaf_diffs + +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + + +class TestPlotEAFSingleObjective(unittest.TestCase): + def test_basic_call_returns_dataframe(self): + df = pl.DataFrame({ + "raw_y": [10, 8, 6, 20, 18, 16], + "evaluations": [1, 2, 5, 1, 4, 5], + "data_id": [1, 1, 1, 2, 2, 2] + }) + dt = plot_eaf_single_objective(df) + self.assertTrue(hasattr(dt, "columns")) + self.assertIn("evaluations", dt.columns) + self.assertIn("raw_y", dt.columns) + +class TestPlotEAFPareto(unittest.TestCase): + def test_basic_call_returns_dataframe(self): + df = pl.DataFrame({ + "x": [1, 2, 3, 1, 2, 3], + "y": [10, 8, 6, 20, 18, 16], + "data_id": [1, 1, 1, 2, 2, 2] + }) + plot_eaf_pareto(df, x_column="x", y_column="y") + + +class TestPlotEAFDiffs(unittest.TestCase): + def test_basic_call_returns_dataframe(self): + df1 = pl.DataFrame({ + "x": [1, 2, 3], + "y": [10, 8, 6], + "data_id": [1, 1, 1] + }) + df2 = pl.DataFrame({ + "x": [1, 2, 3], + "y": [9, 7, 5], + "data_id": [2, 2, 2] + }) + plot_eaf_diffs(df1, df2, x_column="x", y_column="y") + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_ecdf.py b/tests/test_plots/test_ecdf.py new file mode 100644 index 0000000..129d40b --- /dev/null +++ b/tests/test_plots/test_ecdf.py @@ -0,0 +1,31 @@ +import unittest +import polars as pl +import os +from iohinspector.plots import plot_ecdf +from iohinspector.manager import DataManager + +BASE_DIR = os.path.dirname(__file__) +DATA_DIR = os.path.realpath(os.path.join(BASE_DIR, "..", "test_data")) + +class TestECDF(unittest.TestCase): + + def setUp(self): + data_folders = [os.path.join(DATA_DIR, x) for x in sorted(os.listdir(DATA_DIR))] + data_dir = data_folders[0] + manager = DataManager() + manager.add_folder(data_dir) + self.df = manager.load(monotonic=True, include_meta_data=True) + + def test_basic_call_returns_dataframe(self): + dt = plot_ecdf(self.df) + # Check that the result is a DataFrame and has expected columns + self.assertTrue(hasattr(dt, "columns")) + self.assertIn("evaluations", dt.columns) + self.assertIn("eaf", dt.columns) + sorted_dt = dt.sort_values("evaluations", ascending=True) + values = sorted_dt["eaf"].to_numpy() + # Check that as evaluations increases, eaf does not increase (i.e., it decreases or stays the same) + self.assertTrue(all(x <= y for x, y in zip(values, values[1:])), "eaf should increase or stay the same as evaluations increases") + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_fixed_budget.py b/tests/test_plots/test_fixed_budget.py new file mode 100644 index 0000000..744aeeb --- /dev/null +++ b/tests/test_plots/test_fixed_budget.py @@ -0,0 +1,33 @@ +import unittest +import polars as pl +import os +from iohinspector.plots import plot_single_function_fixed_budget +from iohinspector.manager import DataManager + +BASE_DIR = os.path.dirname(__file__) +DATA_DIR = os.path.realpath(os.path.join(BASE_DIR, "..", "test_data")) + +class TestSingleObjectiveFixedBudget(unittest.TestCase): + + def setUp(self): + data_folders = [os.path.join(DATA_DIR, x) for x in sorted(os.listdir(DATA_DIR))] + data_dir = data_folders[0] + manager = DataManager() + manager.add_folder(data_dir) + self.df = manager.load(monotonic=True, include_meta_data=True) + + def test_basic_call_returns_dataframe(self): + dt = plot_single_function_fixed_budget(self.df) + # Check that the result is a DataFrame and has expected columns + self.assertTrue(hasattr(dt, "columns")) + self.assertIn("value", dt.columns) + self.assertIn("variable", dt.columns) + self.assertIn("evaluations", dt.columns) + self.assertIn("algorithm_name", dt.columns) + sorted_dt = dt.sort_values("evaluations", ascending=True) + values = sorted_dt["value"].to_numpy() + # Check that as evaluations increases, value does not increase (i.e., it decreases or stays the same) + self.assertTrue(all(x >= y for x, y in zip(values, values[1:])), "value should decrease or stay the same as evaluations increases") + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_fixed_target.py b/tests/test_plots/test_fixed_target.py new file mode 100644 index 0000000..d35272e --- /dev/null +++ b/tests/test_plots/test_fixed_target.py @@ -0,0 +1,33 @@ +import unittest +import polars as pl +import os +from iohinspector.plots import plot_single_function_fixed_target +from iohinspector.manager import DataManager + +BASE_DIR = os.path.dirname(__file__) +DATA_DIR = os.path.realpath(os.path.join(BASE_DIR, "..", "test_data")) + +class TestSingleObjectiveFixedTarget(unittest.TestCase): + + def setUp(self): + data_folders = [os.path.join(DATA_DIR, x) for x in sorted(os.listdir(DATA_DIR))] + data_dir = data_folders[0] + manager = DataManager() + manager.add_folder(data_dir) + self.df = manager.load(monotonic=True, include_meta_data=True) + + def test_basic_call_returns_dataframe(self): + dt = plot_single_function_fixed_target(self.df) + # Check that the result is a DataFrame and has expected columns + self.assertTrue(hasattr(dt, "columns")) + self.assertIn("value", dt.columns) + self.assertIn("variable", dt.columns) + self.assertIn("raw_y", dt.columns) + self.assertIn("algorithm_name", dt.columns) + sorted_dt = dt.sort_values("raw_y", ascending=True) + values = sorted_dt["value"].to_numpy() + # Check that as raw_y decreases, value does not increase (i.e., it decreases or stays the same) + self.assertTrue(all(x >= y for x, y in zip(values, values[1:])), "value should decrease or stay the same as raw_y decreases") + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_multi_objective.py b/tests/test_plots/test_multi_objective.py new file mode 100644 index 0000000..c9c90e9 --- /dev/null +++ b/tests/test_plots/test_multi_objective.py @@ -0,0 +1,187 @@ +import unittest +import polars as pl +import numpy as np +import matplotlib +from iohinspector.plots import plot_paretofronts_2d, plot_indicator_over_time +import tempfile, os +from iohinspector.indicators import HyperVolume, Epsilon, IGDPlus + + +matplotlib.use("Agg") # Use non-interactive backend for testing +import matplotlib.pyplot as plt + + +class TestPlotParetoFronts2D(unittest.TestCase): + def setUp(self): + # Minimal DataFrame with two objectives and a category + # All algorithms with 3 elements in final Pareto, different data_id for each algo + # Construct the DataFrame so that: + # - Algorithm A has only 1 point on the Pareto front + # - Algorithm B has 2 points on the Pareto front + # - Algorithm C has 3 points on the Pareto front + # Both objectives are to be minimized + self.df = pl.DataFrame({ + # For minimization, Pareto front = non-dominated points with lowest values in both objectives + # A: Only (0.1, 0.9) is non-dominated for A + # B: (0.2, 0.8) and (0.4, 0.6) are non-dominated for B + # C: (0.3, 0.7), (0.6, 0.4), (0.7, 0.3) are all non-dominated for C + "raw_y": [0.1, 0.5, 0.9, 0.2, 0.5, 0.9, 0.3, 0.6, 0.9], + "F2": [0.2, 0.5, 0.8, 0.8, 0.2, 0.9, 0.7, 0.4, 0.1], + "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], + "evaluations": [1, 2, 3, 1, 2, 3, 1, 2, 3], + "data_id": [1, 1, 1, 2, 2, 2, 3, 3, 3] + }) + + def test_basic_call(self): + result = plot_paretofronts_2d( + self.df, + + ) + # Check that the correct points are marked as non-dominated for each algorithm, point by point + # Instead of relying on order, check by (algorithm_name, raw_y, F2) + # Define expected non-dominated points + expected = { + ("A", 0.1, 0.2): True, + ("A", 0.5, 0.5): False, + ("A", 0.9, 0.8): False, + ("B", 0.2, 0.8): True, + ("B", 0.5, 0.2): True, + ("B", 0.9, 0.9): False, + ("C", 0.3, 0.7): True, + ("C", 0.6, 0.4): True, + ("C", 0.9, 0.1): True, + } + for row in result.iter_rows(named=True): + key = (row["algorithm_name"], row["raw_y"], row["F2"]) + self.assertEqual(row["final_nondominated"], expected[key]) + + + def test_custom_obj_vars(self): + # Test with custom objective variable names + df_custom = self.df.rename({"raw_y": "obj1", "F2": "obj2"}) + result = plot_paretofronts_2d( + df_custom, + obj_vars=["obj1", "obj2"], + free_var="algorithm_name" + ) + self.assertIn("final_nondominated", result.columns) + # Check that the correct points are marked as non-dominated for each algorithm, point by point + expected = { + ("A", 0.1, 0.2): True, + ("A", 0.5, 0.5): False, + ("A", 0.9, 0.8): False, + ("B", 0.2, 0.8): True, + ("B", 0.5, 0.2): True, + ("B", 0.9, 0.9): False, + ("C", 0.3, 0.7): True, + ("C", 0.6, 0.4): True, + ("C", 0.9, 0.1): True, + } + for row in result.iter_rows(named=True): + key = (row["algorithm_name"], row["obj1"], row["obj2"]) + self.assertEqual(row["final_nondominated"], expected[key]) + +class TestPlotIndicatorOverTime(unittest.TestCase): + def setUp(self): + # Minimal DataFrame with two objectives and a single algorithm + # All points belong to algorithm "A" with 10 evaluations + # The points are constructed to simulate a progression towards the Pareto front + self.df = pl.DataFrame({ + "raw_y": [0.9, 0.7, 0.5, 0.3, 0.1], + "F2": [0.8, 0.6, 0.4, 0.2, 0.1], + "algorithm_name": ["A"] * 5, + "evaluations": [1,10,100, 1000, 10000], + "data_id": [1] * 5 + }) + # Create a dict mapping evaluation to (raw_y, F2) point + self.eval_points = dict(zip(self.df["evaluations"], zip(self.df["raw_y"], self.df["F2"]))) + + def test_plot_indicator_over_time_hypervolume(self): + # Use a simple indicator and check output DataFrame + indicator = HyperVolume(reference_point=[1.0, 1.0]) + result = plot_indicator_over_time( + self.df, + indicator=indicator, + nr_eval_steps=5, + evals_min=1, + evals_max=10_000, + eval_scale_log=True, + obj_columns=["raw_y", "F2"], + eval_column="evaluations", + free_variable="algorithm_name" + ) + # Make a dict of {evaluation: hypervolume} + hv_dict = dict(zip(result["evaluations"], result["HyperVolume"])) + + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + hv = (1.0 - point[0]) * (1.0 - point[1]) # Since we minimize both objectives + self.assertAlmostEqual(hv_dict[eval], hv, places=5) + + def test_plot_indicator_over_time_epsilon_additive(self): + # Use a simple indicator and check output DataFrame + indicator = Epsilon(reference_point=[1.0, 1.0]) + result = plot_indicator_over_time( + self.df, + indicator=indicator, + nr_eval_steps=5, + evals_min=1, + evals_max=10_000, + eval_scale_log=True, + obj_columns=["raw_y", "F2"], + eval_column="evaluations", + free_variable="algorithm_name" + ) + # Make a dict of {evaluation: hypervolume} + ae = dict(zip(result["evaluations"], result["Epsilon_Additive"])) + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + eps = max(point[0]-1.0, point[1]-1.0) # Since we minimize both objectives + self.assertAlmostEqual(ae[eval], eps, places=5) + + + def test_plot_indicator_over_time_epsilon_multiplicative(self): + # Use a simple indicator and check output DataFrame + indicator = Epsilon(reference_point=[1.0, 1.0], version="multiplicative") + result = plot_indicator_over_time( + self.df, + indicator=indicator, + nr_eval_steps=5, + evals_min=1, + evals_max=10_000, + eval_scale_log=True, + obj_columns=["raw_y", "F2"], + eval_column="evaluations", + free_variable="algorithm_name" + ) + # Make a dict of {evaluation: hypervolume} + ae = dict(zip(result["evaluations"], result["Epsilon_Mult"])) + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + eps = max(point[0]/1.0, point[1]/1.0) # Since we minimize both objectives + self.assertAlmostEqual(ae[eval], eps, places=5) + + def test_plot_indicator_over_time_igd_plus(self): + # Use a simple indicator and check output DataFrame + indicator = IGDPlus(reference_set=[[0.0, 0.0]]) + result = plot_indicator_over_time( + self.df, + indicator=indicator, + nr_eval_steps=5, + evals_min=1, + evals_max=10_000, + eval_scale_log=True, + obj_columns=["raw_y", "F2"], + eval_column="evaluations", + free_variable="algorithm_name" + ) + # Make a dict of {evaluation: hypervolume} + ae = dict(zip(result["evaluations"], result["IGD+"])) + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + idg_plus = np.sqrt((point[0]-0.0)**2 + (point[1]-0.0)**2) # Since we minimize both objectives + self.assertAlmostEqual(ae[eval], idg_plus, places=5) + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_ranking.py b/tests/test_plots/test_ranking.py new file mode 100644 index 0000000..56ab6f0 --- /dev/null +++ b/tests/test_plots/test_ranking.py @@ -0,0 +1,138 @@ +import unittest +from build.lib.iohinspector.plots.ranking import plot_robustrank_changes +import polars as pl +from iohinspector.plots import plot_robustrank_over_time,plot_tournament_ranking +from iohinspector.indicators import HyperVolume + +class TestPlotTournamentRanking(unittest.TestCase): + def test_basic_call_returns_dataframe(self): + data = pl.DataFrame({ + "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], + "function_name": ["f1", "f2", "f3", "f1", "f2", "f3", "f1", "f2", "f3"], + "raw_y": [1.0, 2.0, 1.7, 1.5, 2.8, 2.1, 0.9, 0.5, 1.6] + }) + + dt = plot_tournament_ranking(data) + self.assertTrue(hasattr(dt, "columns")) + self.assertIn("Rating", dt.columns) + self.assertIn("Deviation", dt.columns) + self.assertIn("algorithm_name", dt.columns) + +class TestPlotRobustRankOverTime(unittest.TestCase): + def test_basic_call(self): + data = pl.DataFrame({ + "algorithm_name": ["A"] * 9 + ["B"] * 9 + ["C"] * 9, + "evaluations": [1, 10, 100] * 9, + "f1": [ + # A: best at eval 1, B: best at eval 10, A: best at eval 100 (for run 1) + 0.8, 1.5, 0.7, # A, run 1 + 1.0, 1.6, 0.9, # A, run 2 + 0.9, 1.4, 0.8, # A, run 3 + + 1.0, 0.7, 1.2, # B, run 1 + 1.2, 0.8, 1.3, # B, run 2 + 1.1, 0.6, 1.1, # B, run 3 + + 1.5, 1.5, 0.1, # C, run 1 + 1.6, 1.6, 0.2, # C, run 2 + 1.4, 1.4, 0.3 # C, run 3 + ], + "f2": [ + 1.0, 2.0, 0.9, # A, run 1 + 1.2, 2.1, 1.1, # A, run 2 + 1.1, 2.2, 1.0, # A, run 3 + + 1.3, 0.8, 1.4, # B, run 1 + 1.5, 0.9, 1.5, # B, run 2 + 1.4, 0.7, 1.3, # B, run 3 + + 2.0, 2.0, 0.1, # C, run 1 + 2.1, 2.1, 0.2, # C, run 2 + 1.9, 1.9, 0.3 # C, run 3 + ], + "f3": [ + 2.0, 3.0, 1.8, # A, run 1 + 2.2, 3.1, 2.0, # A, run 2 + 2.1, 3.2, 1.9, # A, run 3 + + 2.3, 1.2, 2.4, # B, run 1 + 2.5, 1.3, 2.5, # B, run 2 + 2.4, 1.1, 2.3, # B, run 3 + + 3.0, 3.0, 0.1, # C, run 1 + 3.1, 3.1, 0.3, # C, run 2 + 2.9, 2.9, 0.2 # C, run 3 + ], + "data_id": [1]*3 + [2]*3 + [3]*3 + [4]*3 + [5]*3 + [6]*3 + [7]*3 + [8]*3 + [9]*3, + "run_id": [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3, + }) + + evals = [1, 10, 100] + plot_robustrank_over_time( + data, + obj_columns=["f1","f2", "f3"], + evals=evals, + indicator=HyperVolume(reference_point=[5.0,5.0,5.0]), + ) + + +class TestPlotRobustRankChanges(unittest.TestCase): + def test_basic_call(self): + data = pl.DataFrame({ + "algorithm_name": ["A"] * 9 + ["B"] * 9 + ["C"] * 9, + "evaluations": [1, 10, 100] * 9, + "f1": [ + # A: best at eval 1, B: best at eval 10, A: best at eval 100 (for run 1) + 0.8, 1.5, 0.7, # A, run 1 + 1.0, 1.6, 0.9, # A, run 2 + 0.9, 1.4, 0.8, # A, run 3 + + 1.0, 0.7, 1.2, # B, run 1 + 1.2, 0.8, 1.3, # B, run 2 + 1.1, 0.6, 1.1, # B, run 3 + + 1.5, 1.5, 0.1, # C, run 1 + 1.6, 1.6, 0.2, # C, run 2 + 1.4, 1.4, 0.3 # C, run 3 + ], + "f2": [ + 1.0, 2.0, 0.9, # A, run 1 + 1.2, 2.1, 1.1, # A, run 2 + 1.1, 2.2, 1.0, # A, run 3 + + 1.3, 0.8, 1.4, # B, run 1 + 1.5, 0.9, 1.5, # B, run 2 + 1.4, 0.7, 1.3, # B, run 3 + + 2.0, 2.0, 0.1, # C, run 1 + 2.1, 2.1, 0.2, # C, run 2 + 1.9, 1.9, 0.3 # C, run 3 + ], + "f3": [ + 2.0, 3.0, 1.8, # A, run 1 + 2.2, 3.1, 2.0, # A, run 2 + 2.1, 3.2, 1.9, # A, run 3 + + 2.3, 1.2, 2.4, # B, run 1 + 2.5, 1.3, 2.5, # B, run 2 + 2.4, 1.1, 2.3, # B, run 3 + + 3.0, 3.0, 0.1, # C, run 1 + 3.1, 3.1, 0.3, # C, run 2 + 2.9, 2.9, 0.2 # C, run 3 + ], + "data_id": [1]*3 + [2]*3 + [3]*3 + [4]*3 + [5]*3 + [6]*3 + [7]*3 + [8]*3 + [9]*3, + "run_id": [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3, + }) + evals = [1, 10, 100] + plot_robustrank_changes( + data, + obj_columns=["f1","f2", "f3"], + evals=evals, + indicator=HyperVolume(reference_point=[5.0,5.0,5.0]), + + ) + + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_plots/test_single_run.py b/tests/test_plots/test_single_run.py new file mode 100644 index 0000000..394fd21 --- /dev/null +++ b/tests/test_plots/test_single_run.py @@ -0,0 +1,81 @@ +import unittest +import polars as pl +import numpy as np +import matplotlib.pyplot as plt +from iohinspector.plots.single_run import plot_heatmap_single_run + +class TestPlotHeatmapSingleRun(unittest.TestCase): + def setUp(self): + self.data = pl.DataFrame({ + "data_id": [1]*5, + "evaluations": [1,2,3,4,5], + "x1": np.linspace(-5, 5, 5), + "x2": np.linspace(-5, 5, 5)[::-1], + }) + self.var_cols = ["x1", "x2"] + self.x_mins = np.array([-5, -5]) + self.x_maxs = np.array([5, 5]) + + def test_basic(self): + dt_plot = plot_heatmap_single_run( + data=self.data, + var_cols=self.var_cols, + eval_col="evaluations", + scale_xlog=False, + x_mins=self.x_mins, + x_maxs=self.x_maxs, + ) + self.assertEqual(dt_plot.shape, (2, 5)) + self.assertAlmostEqual(dt_plot.values.min(), 0) + self.assertAlmostEqual(dt_plot.values.max(), 1) + self.assertTrue(np.all((dt_plot.values >= 0) & (dt_plot.values <= 1))) + + def test_asserts_on_multiple_data_ids(self): + data = pl.DataFrame({ + "data_id": [1, 2], + "evaluations": [1, 2], + "x1": [0, 1], + }) + with self.assertRaises(AssertionError): + plot_heatmap_single_run(data, ["x1"]) + + def test_single_variable(self): + data = pl.DataFrame({ + "data_id": [1]*3, + "evaluations": [1, 2, 3], + "x1": [-5, 0, 5], + }) + dt_plot = plot_heatmap_single_run( + data=data, + var_cols=["x1"], + eval_col="evaluations", + scale_xlog=False, + x_mins=[-5], + x_maxs=[5], + ax=None, + file_name=None, + ) + self.assertEqual(dt_plot.shape, (1, 3)) + np.testing.assert_allclose(dt_plot.values, [[0, 0.5, 1]]) + + def test_non_default_eval_col(self): + data = pl.DataFrame({ + "data_id": [1]*4, + "evals": [1, 2, 3, 4], + "x1": [0, 1, 2, 3], + "x2": [3, 2, 1, 0], + }) + dt_plot = plot_heatmap_single_run( + data=data, + var_cols=["x1", "x2"], + eval_col="evals", + scale_xlog=False, + x_mins=[0, 0], + x_maxs=[3, 3], + ax=None, + file_name=None, + ) + self.assertEqual(dt_plot.shape, (2, 4)) + +if __name__ == "__main__": + unittest.main() \ No newline at end of file From 409091974870eea5694028b3a8f4eae8317186ad Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Thu, 16 Oct 2025 10:36:05 +0200 Subject: [PATCH 08/17] small fix --- tests/test_plots/test_ranking.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/tests/test_plots/test_ranking.py b/tests/test_plots/test_ranking.py index 56ab6f0..bf6347c 100644 --- a/tests/test_plots/test_ranking.py +++ b/tests/test_plots/test_ranking.py @@ -1,7 +1,6 @@ import unittest -from build.lib.iohinspector.plots.ranking import plot_robustrank_changes import polars as pl -from iohinspector.plots import plot_robustrank_over_time,plot_tournament_ranking +from iohinspector.plots import plot_robustrank_over_time,plot_tournament_ranking, plot_robustrank_changes from iohinspector.indicators import HyperVolume class TestPlotTournamentRanking(unittest.TestCase): From e9dcb943f1d56afa413242c74a5278c0d6bb6494 Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Fri, 7 Nov 2025 18:44:40 +0100 Subject: [PATCH 09/17] plot args --- examples/MO_Examples.ipynb | 120 ++++-- examples/SO_Examples.ipynb | 2 +- image.png | Bin 66843 -> 0 bytes pyproject.toml | 2 +- src/iohinspector/indicators/__init__.py | 4 +- src/iohinspector/indicators/anytime.py | 32 +- src/iohinspector/indicators/final.py | 4 +- src/iohinspector/metrics/__init__.py | 7 +- src/iohinspector/metrics/aocc.py | 58 ++- src/iohinspector/metrics/attractor_network.py | 45 +- src/iohinspector/metrics/eaf.py | 153 ++++++- src/iohinspector/metrics/ecdf.py | 82 ++-- src/iohinspector/metrics/fixed_budget.py | 74 ++-- src/iohinspector/metrics/fixed_target.py | 94 ++--- src/iohinspector/metrics/multi_objective.py | 70 +++ src/iohinspector/metrics/ranking.py | 122 +++++- src/iohinspector/metrics/single_run.py | 37 ++ src/iohinspector/metrics/trajectory.py | 28 +- src/iohinspector/metrics/utils.py | 90 ++-- src/iohinspector/plots/__init__.py | 3 +- src/iohinspector/plots/attractor_network.py | 134 ++++-- src/iohinspector/plots/eaf.py | 398 ++++++++++++------ src/iohinspector/plots/ecdf.py | 115 +++-- src/iohinspector/plots/fixed_budget.py | 105 +++-- src/iohinspector/plots/fixed_target.py | 115 +++-- src/iohinspector/plots/multi_objective.py | 177 +++++--- src/iohinspector/plots/ranking.py | 226 +++++----- src/iohinspector/plots/single_run.py | 94 +++-- src/iohinspector/plots/utils.py | 338 +++++++++++++++ tests/test_data.py | 2 +- tests/test_metrics/test_aocc.py | 30 +- tests/test_metrics/test_eaf.py | 223 +++++++++- tests/test_metrics/test_ecdf.py | 16 +- tests/test_metrics/test_fixed_budget.py | 6 +- tests/test_metrics/test_fixed_target.py | 2 +- tests/test_metrics/test_multi_objective.py | 165 ++++++++ tests/test_metrics/test_ranking.py | 128 +++++- tests/test_metrics/test_single_run.py | 76 ++++ tests/test_metrics/test_trajectory.py | 12 +- tests/test_metrics/test_utils.py | 32 +- tests/test_plots/test_attractor_network.py | 22 +- tests/test_plots/test_eaf.py | 35 +- tests/test_plots/test_ecdf.py | 23 +- tests/test_plots/test_fixed_budget.py | 27 +- tests/test_plots/test_fixed_target.py | 25 +- tests/test_plots/test_multi_objective.py | 166 +------- tests/test_plots/test_ranking.py | 62 +-- tests/test_plots/test_single_run.py | 77 +--- 48 files changed, 2747 insertions(+), 1111 deletions(-) delete mode 100644 image.png create mode 100644 src/iohinspector/metrics/multi_objective.py create mode 100644 src/iohinspector/metrics/single_run.py create mode 100644 src/iohinspector/plots/utils.py create mode 100644 tests/test_metrics/test_multi_objective.py create mode 100644 tests/test_metrics/test_single_run.py diff --git a/examples/MO_Examples.ipynb b/examples/MO_Examples.ipynb index 7f38e21..dcd4570 100644 --- a/examples/MO_Examples.ipynb +++ b/examples/MO_Examples.ipynb @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -58,7 +58,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -75,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 31, "metadata": {}, "outputs": [ { @@ -122,7 +122,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 59, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -140,7 +140,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -156,7 +156,7 @@ " Function(id=0, name='pymoo_ZDT1', maximization=False)))" ] }, - "execution_count": 60, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -182,7 +182,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 33, "metadata": {}, "outputs": [], "source": [ @@ -192,7 +192,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 34, "metadata": {}, "outputs": [ { @@ -238,7 +238,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 62, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } @@ -249,7 +249,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 35, "metadata": {}, "outputs": [], "source": [ @@ -258,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 36, "metadata": {}, "outputs": [], "source": [ @@ -269,7 +269,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -299,7 +299,7 @@ "└─────────┴───────────────┴───────────────┴──────────────┴───┴────────┴───────┴──────────┴─────────┘" ] }, - "execution_count": 65, + "execution_count": 37, "metadata": {}, "output_type": "execute_result" } @@ -324,7 +324,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 38, "metadata": {}, "outputs": [ { @@ -371,7 +371,7 @@ "└─────────┴─────────────┴────────────┴────────────┴───┴─────────┴────────────┴──────────┴──────────┘" ] }, - "execution_count": 66, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" } @@ -397,12 +397,12 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 39, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -420,7 +420,7 @@ "\n", "df = manager.select(function_ids=[0]).load(False, True)\n", "#Currently, this normalization function assumes that our function was already scaled to have all 0's as the ideal point.\n", - "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", + "df = iohinspector.metrics.add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", "# df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", "\n", "#The cast-to-int is there to handle data type differences and prevent duplicate values for function evaluation count\n", @@ -428,7 +428,7 @@ "\n", "\n", "hv_indicator = iohinspector.indicators.anytime.HyperVolume(reference_point = [1.1, 1.1])\n", - "df_hv = iohinspector.indicators.add_indicator(df, hv_indicator, objective_columns = ['obj1', 'obj2'], evals = evals)\n", + "df_hv = iohinspector.indicators.add_indicator(df, hv_indicator, obj_vars = ['obj1', 'obj2'], evals = evals)\n", "\n", "plt.figure(figsize=(16,9))\n", "sbs.lineplot(df_hv.to_pandas(), x='evaluations', y=hv_indicator.var_name, hue='algorithm_name')\n", @@ -447,12 +447,12 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 40, "metadata": {}, "outputs": [ { "data": { - "image/png": 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QQ5g7dy65ubkAPPvss3tsf1sRERERERH5+TAMg+IaP9/vqKbaG6J7ugubJbEZi0JU2aP69u3LxIkTAViyZAm1tbXtaicajTJ9+vTY/V133UVmZmaz5a+//noGDhzYartPP/107PqMM87g1FNPbbZs3759ufXWW2P3//znP2NLm5vjdDp5+OGHWx3HnpKdnc20adOafT43N7fJexBPiGq325uEcT919NFH07t37yZ9NH4ff+qss86KBX5r1qyhrq6u1TEkwq9//WsOPvjgZp+fOnUqVmvDkoCCgoJ2fy7vlJaWxplnnglAUVHRbg+E+qmueK9nz57NunXrAJg0aVJszM3Jy8vjhhtuACAUCvHqq6+2WF5ERERERESkLcKRKBvLPKzYUYNhQG6qE3MHt4/cHe2JKgm3detWFi9ezNq1a6mursbn8zUJFzdt2gQ0/JXgu+++45hjjmlzH6tXr6a0tBQAq9Xa6l6dFouFCy+8kHvvvbfFcp9++mns+vLLL291HJdddhm33HIL0WiUoqIiCgoKGDJkSLPlf/GLX9CtW7dW291TTj/99NjM4OYceuihseBr8+bNrbZ5zDHHxGYeNueggw5i69atsTH8dFZkYy6XiwEDBrB69WoMw2Dz5s0MHz681XF01Lnnntvi8ykpKQwYMICCggIMw2DLli2tjqu0tJSFCxeyevVqqqqq8Hg8Tb42li5dGrv+9ttvW22vK97rOXPmxK4nT57cYt87HXvssbHrL7/8khtvvDGueiIiIiIiIiIt8QUb9j8trPGS7rLjtnde1KkQVRJmwYIF3HzzzXzxxRetzsjcqby8vF19ffvtt7HrAw88kNTU1FbrjB49usXnd+zYEQtmAcaMGdNqm9nZ2QwePJg1a9YAsGzZshZD1MMPP7zVNvekeMLIxjN845ltedBBB7VapnGQPGzYsFbLZ2RktGkMiZDI92bVqlXcdNNNvPfee3Et04f4vja64r1esGBB7Pr111/ns88+a7XNnQeUQcPWFyIiIiIiIiIdVe0NsrakjkpPiJwUZ8KX7/+UQlRJiP/85z9cccUVcYenO7V3aXZZWVnsulevXnHV6dmzZ9xtulwusrOz42q3b9++sRC1teAr3jb3lHhOurfZbLHrUCiUkDZ3LoNvT/l4xpAIiXpvPvjgA375y1/GtSdvY/F8bXTFe11YWBi7fuWVV1pt76eqqqraXEdERERERERkJ8MwKKrxs660jnDEoHta5yzf/yntiSodtmrVKq666qpYgDps2DCeeOIJFi9eTElJSWw5/86PSy65JFZ35+E0bVVfXx+73t2BNrvz04OcWmpz52FK8WhctrXgy+Vyxd3unmDqhG8ybW2zM8aQCIkYV1lZGeeff34sQO3Tpw8PPvggX375JYWFhXi9XqLRaOxr484774zVjedroyve68azStsjHA53eAwiIiIiIiLy8xSORNlQVs/KwlrMmMhJ2TMBKmgmqiTA448/HgtGTjzxRN55550W911MxMFAjQNRr9cbVx2PxxN3m62Vba7dn56QLj9vzzzzTCx0HDFiBJ9//nmLW0/sqUOzOiIpKSn2mpYtW8ahhx7axSMSERERERGRnwNvMNyw/2m1jwy3A5fdskf710xU6bC5c+fGru+7774WA1SALVu2dLjPrKys2PX27dvjqtNaucZL7X0+X9z7tTY+bKnxuEQaf23cfvvtre7dm4ivjc7W+CCr4uLiLhyJiIiIiIiI/FxUeoJ8v72GwmofuSnOPR6ggkJUSYDGeyS2dhhPTU0N33//fYf7POSQQ2LXq1evjmsG3+LFi1t8vkePHuTk5MTuv/rqq1bbLC8vZ+3atbH7ww47rNU6ibS3LoWXBm352ohEIsyfP7+zh9RhjQ9o2xfGKyIiIiIiIvsuwzDYUe1j+fZqPP4w+WkurJ18gFRzFKJKh5nNP34atba0/tlnn03IwUBDhw6NBZ6hUIhXX321xfLRaJRZs2a12u7EiRNj1zNmzGi1/IwZM2J7V+bn53PAAQe0WieRnE5n7HpPHbgk8WvL18Zbb721T8zsPO2002LX//nPf/D7/V04GhEREREREdlfRaMG60vrWVVYg8VsJifV2aWTyRSiSof1798/dv3OO+80W27dunXcfffdCenTbDY3OaDqrrvuorKystnyf//735vMGG3OVVddFbt+8803+eCDD5otu2XLFu6///4mdff0F3NmZmbseseOHXu0b2ldvF8bZWVl/O53v9sTQ+qws88+m4EDBwJQVFTEb37zm9ihcq2pr69v037DIiIiIiIi8vO1vcrLpnIPaU47aS5bVw9HIap03Omnnx67vvHGG3cbPM6dO5cJEyZQV1fX5DT7jvj9739PRkYG0LDf6Yknnsj69eublDEMg3/84x/ceOONOByOVtucOHEiJ598cuz+nHPO4b///e8u5b7++muOP/54qqurAejVqxfXX399B15N+xx00EGx6w8//LDDJ6dLYjX+2njwwQd54YUXdimzbNkyxo8fz7Zt2xL2tdGZLBYLTz31FBZLw/4z06dP59RTT2X16tXN1vn222+56aab6NWrF5s2bdpTQxUREREREZF9VHl9gA1l9SQ7rF2y/+nuWLt6ALLvu+GGG3j22WcpKyujsrKSk046icMOO4yhQ4diMplYtmwZK1euBODEE08kJyeHmTNndrjf3Nxcnn76ac4//3yi0ShLly5lyJAhHHPMMQwcOBCPx8OXX37Jtm3bAHj88ce57rrrgKbLrH9q+vTpHH300WzYsIH6+nrOO+88Bg0axOjRo7Hb7axatYpFixbFZt8lJSUxa9Ys0tPTO/ya2uqII46gV69ebNu2jaKiIoYMGcIvfvELsrKyYrNiR40axfnnn7/HxyZwySWX8Oijj7J27VoCgQAXX3wxDzzwACNGjMDpdLJixQqWLl0KwIgRIzjxxBN5+OGHu3jUrTv++ON56qmnuOaaa4hEIrz33nu8//77DB06lIMPPpjU1FS8Xi9FRUV89913lJWVdfWQRUREREREZB9RHwizvqQeMJHi7PoZqDspRJUOy8nJ4e233+aMM86InWi/bNkyli1b1qTcpEmTmDFjBr/97W8T1vc555zDzJkzueqqq6ivrycSiTBv3jzmzZsXK+NwOPjb3/7GhAkTYo+1dEp6bm4u8+fPZ/LkyXzyySdAw1YE69at26XswIEDeemllxg1alTCXlNbmM1m/vGPf3D22WcTDAYpLi7m+eefb1LmkksuUYjaRRwOB7Nnz+bkk09m48aNQMNBaD+dtXn00Ufzyiuv8Mwzz3TFMNvlyiuvZODAgVx11VWsW7cOwzBYuXJl7A8muzNs2LDY7HERERERERGRnwqGo6wvqaPGF6J7mrP1CnuQQlRJiKOOOoqVK1fy+OOPM3v27Fhg1L17dw4//HCmTJnSZGlzIk2ePJljjjmGv/3tb7z77rts3boVk8lEz549+cUvfsHVV1/NkCFDWLRoUaxOa7NGc3NzmTt3Lu+//z6vvPIKX375JcXFxYRCIXJycjj00EOZNGkSU6ZMwWbr2r+KnHbaaSxdupQnn3ySL7/8kq1bt1JfXx/3PpXSuQYPHsw333zDk08+yRtvvEFBQQHBYJC8vDyGDx/O5MmTOe+882LL4/clEydOZPXq1bz11lu8++67LFy4kOLiYmpra3G73eTm5jJkyBDGjBnDySefzCGHHNLVQxYREREREZG9VDRqsKncQ3FtgLw9dYhUNEJS7ca4ipoMJS37rNraWtLS0igvL29ywFC8/H4/mzZtol+/fk1Oed9fPfPMM/z6178G4Oqrr+app57q4hGJSFv93L5viXSlUCjEnDlzOOWUU7r8D4YiIiKy/9HPGvJT2yq9rC6qpZvbjtO2ByYaGVHsNRspXfs1486+ipqamhZXLutgKfnZeOWVV2LXXbX8XkREREREREREmqqoD7ChtJ4ku3UPBagGttptOKo3YDLCcVVRiCo/C2+88QZz584FwOl0cuaZZ3bxiERERERERERExBMIs66knqgBqa49MyvZ5inEUV1AxJ6CYYqvT4Wosk/76quvuPLKK/n22293+3wgEODxxx/nwgsvjD3261//mm7duu2hEYqIiIiIiIiIyO4Ew1HW/XCQVFayfY/0afWW4KgqIGp1EbUnx1+vE8ck0umCwSDPPvsszz77LL169eKQQw4hNzcXwzDYsWMHCxYsoKamJlZ+6NChPPDAA104YhERERERERERMQyDzXv4ICmLvxJnZQGGyUzUkdamugpRZb+xbds2tm3b1uzzJ554Ii+99BJJSUl7cFTSWSorK5k2bVqH2/ntb3/LoEGDEjAiEREREREREYnXjmofmys8ZCbZsZg7P0A1B2pwVqyGaJCIO6fN9RWiyj5t3LhxfPLJJ8yZM4clS5ZQVFREeXk5tbW1pKamkp+fz9ixY7ngggsYP358Vw9XEqi2tpYnn3yyw+2cc845ClFFRERERERE9qCK+gDr9+BBUuaQB2dlAaawh7A7t11tKESVfZrZbGbixIlMnDixq4ciIiIiIiIiIiKt8ATCrCutJxI1yEzq/IOkTGE/jso1WAKVhJK6Q6NtA6KGwcqq+EJchagisk/q27cvhmF09TBEREREREREJE6hSJT1pfXU+IJ0T3V1en+mSBBH5Rqs3jJCybm7BKiPL/Hz7uqUuNoyd9YgRURERERERERERKDhIKlNZR6KanzkJO+Bg6SiYezV67B5iggl5YDpxxmnhmHwt6/9vLcxhJn4JmgpRBUREREREREREZFOVVjj/+EgKQdWSydHkkYUR/VG7LVbCbtzwPzjYnzDMPj7Mj//Wx/CBFx1gDeuJrWcX0RERERERERERDpNpSfIupI63HviICnDwF67BXvtJsKuTAyLrdFTBk99E+CddQ0B6u+PcDKCUFzNaiaqiIiIiIiIiIiIdApvMMzakjoiUYM0V+cfJGWr346jei0RRxqG1Rl73DAMnv42wJtrgwD8bpSTE/vb425XIaqIiIiIiIiIiIgkXCgSZV1Jw0FS2cmOTu/P6inGUbWWiC2ZqM0de9wwDJ79LsDrBQ0B6g0jnZw8IP4AFRSiioiIiIiIiIiISIIZhsHm8j13kJTFV46zag2G2UrUntJkHNOXB3h1TUOAet3hTk4d2LYAFRSiioiIiIiIiIiISILtPEgqw935B0lZ/NU4K1ZjGFEizm5Nnnt+RYBZqxoC1GsPc3LGoLYHqKAQVURERERERERERBKoyhNkfUkdLpsVl71zD5IyB+twVK7GFAkQcWU1eW7migAvrGwIUK8+1MGkwe0LUEEhqoiIiIiIiIiIiCSINximoKSOcKTzD5IyhX04K9dgCdYRdmc3ee6llQGeXxEA4NeHODj7gI7tyaoQVURERERERERERDosHImyvrSeam+Q7JTOPUjKFAk0BKj+CkJJOdBoz9WXVweYvrwhQP3VCAfnDun4WBSiioiIiIiIiIiISIcYhsHmCg9F1T5yUzr5IKloCEfVOmyeYkLuXDD9GHH+d02Af3/XEKBeOtzBBQcmJsxViCoiIiIiIiIiIiIdUlTjZ1O5l26dfZBUNIKjegO2+m0Ek3LA/OOeq28UBPjXtw0B6tSDHFw0LHGzYRWiioiIiIiIiIiISLtVeYKsK63DZbN07kFShoG9dhOO2s2EXVlg/nHP1bfWBnnqm4YA9aJhdi4+KI4A1YiQXLs+rq6t7RqwiIiIiIiIiIiI/Oz5ghHWldYRChtkpHbuQVK22q04qjcQcnbDsPwYks5eF+TJZX4ALjjQziVxBagG2d//i9yC/8XVt2aiioiIiIiIiIiISJuFI1HWldZR4en8g6Rs9YU4qtcSsadgWF2xx99dH+SvXzcEqOcNsXP5wY649mPttva/pG96F4P49m5ViCoiIiIiIiIiIiJtsvMgqcIfDpIyd+JBUlZvKY6qAgyrk6g9Ofb4+xuDPL60IUA9+wA7V4yIL0BN3fIhWaufB6Cw9xlxjUEhqsg+aMKECZhMpthH7969CQQCcdW96667YvUuuOCCVsvPmzeP3/zmN4wcOZLs7Gzsdjsul4ucnBxGjhzJ5MmTeeyxx1i6dCmGYbTpdRiGwbx587j99tsZP348AwYMID09HbvdTlZWFoMHD+ass87ivvvuY9myZW1q+6duv/32Ju/ZNddc0652Nm/ezDPPPMOUKVMYMWIE3bp1w2azkZGRwcEHH8xVV13FZ5991qGxioiIiIiIiOztimt3HiRlx9aJB0lZ/FU4KtdgmExEHGmxxz/cFOQvixsC1EmD7Vx1SHwBalLxYnK+/TsAlYPOoTx3XFzj0J6oIvuBbdu28fTTT3P99dcnrM3Vq1dz+eWXs3Dhwl2eC4VC+P1+ysrK+Prrr5k1axYAw4YNY8WKFXG1/+qrr3LPPfewcuXK3T5fUVFBRUUF69at48033+SOO+6gf//+/O53v+PKK6/E4Yh/mYBhGMycObPJY6+88gqPP/543O188803XH311SxevHi3z1dVVVFVVcXy5cv517/+xYQJE3juuefo3bt33OMUERERERER2RdUeYKsLanDaTXjtndevGgO1uKsWI0pGiTszok9/vHmIH9e5McAzhhk4zeHxhegOitXk7fkT5iMKLW9jqNi6CWwqSCusShEFdlPPPDAA1xxxRW43e4Ot/XNN99w7LHHUl1dHXssNzeXkSNHkpeXh8lkoqKighUrVrB+/frYDNTG5Zvj8/n41a9+FQted3K73YwaNYq8vDzS0tKorq6mtLSUr7/+mrq6OgA2btzIddddx0cffcTbb78d9+v59NNP2bp1a5PHqqqqeOeddzj33HPjaqOgoGCXAHXw4MEcdNBBZGVlUV1dzVdffcX27duBhhm8Rx11FF988QX9+/ePe6wiIiIiIiIie7P6QJiC4jrCYYOc1M7bB9UcrMdZsQZzuJ6QOzf2+CdbQjzyQ4B62kAb/3eYM64A1Va3jfwF92COBPDkjqTk0OugDVsQ7JchaiQSYeXKlSxZsoSlS5eyZMkSvv/+e0KhEADjx49n3rx5nTqGYDDIK6+8wqxZs1i5ciUlJSV069aNfv36cdZZZ3HppZeSlZXVqWOQn5eSkhL++te/cvPNN3eonVAoxOTJk2OBaH5+Pk8++SRnnHEGZvOu0/PLysp4++23mTlzJhs3bmyx7WAwyAknnMD8+fNjjx1xxBFMmzaNE044AbvdvkudcDjMwoUL+fe//81LL71EMBjE4/G06TU999xzsWuXy4XP54s9Hm+IutPAgQO54oormDJlCj169GjyXDQaZcaMGVx33XV4vV4KCwu56KKL+Oqrr+L6hi4iIiIiIiKyN/OHIhQU11LjD9E91dlp/TQEqKuwBKoIJeXGws7Ptob400IfUQNO7m/jusPjC1AtvnJ6fDUNS6gOX7cDKBp1M5jbFovud3uivvXWW6SmpjJixAiuuOIK/vnPf/L111/HAtQ9Yc2aNYwePZqpU6fy3nvvsXXrVgKBAMXFxSxYsIA//OEPDBs2jDlz5uyxMcn+68gjj4xdP/LII9TW1naovbfeeos1a9YADYHjp59+yqRJk3YboAJkZ2dzxRVX8Nlnn7X6x4nrr7++SYB62223sWjRIk499dTdBqgAVquVsWPHMn36dDZt2sRZZ53VptdTX1/P66+/Hrv/y1/+Erv+4IMPKCkpiaud7t27M336dNasWcNNN920S4AKYDabufzyy3nhhRdijy1cuJAPP/ywTWMWERERERER2duEIlHWltRRVhsgNyW+8LI9zCHPTwLUhjzii20hHljQEKCe2M/GDaPiO8zKHKynx4I7sfnKCCb3pPDIaRjWtgfA+12IWl1djdfr7bL+t2/fznHHHce3334LgMlkYvz48Vx++eWcfvrpuFwuAEpLS5k0aRKffPJJl41V9g9TpkzhgAMOAKCyspJHH320Q+01Dvx++ctfMnjw4LjrDhgwoNnnPvvsM55++unY/W9/+1vuu+++No0tPz+f119/nYcffjjuOq+//nps5mq/fv246qqrOOSQQ4CGWa4vvvhiXO2MHz+eSy+9FIvF0mrZM888kyOOOCJ2/+6778Y9XhEREREREZG9TTRqsKG0nsJqHzmpTizmzg5QK5sEqPO3h7j/q4YA9YS+Nn4XZ4BqigTIX3QvjtothJ0Z7DjqbqKNDqdq09jaVWsfkJuby2mnncbdd9/NnDlz+O1vf7tH+p08eTKFhYUA9OnTh2+++YZ58+bx73//m3feeYetW7dy3HHHAQ3Lps8999y49pEUaY7FYuHuu++O3T/22GNUVFS0u70dO3bErvv06dOhsTX2wAMPxK779evHQw891O62DjvssLjLNl7KP2XKFEwmExdffPFun0+ko48+Ona9efPmTulDREREREREpLMZhsGWCg9bKr1kJTuwWTonTjSFvDgrV2PxVxBKyosFqAt2hLjvKx8RA47tY+X3R8QZ4hoR8pb+GVfFSiJWNzuOuptwUm7r9Zqx34WoJ510Elu2bKG4uJjZs2czbdo0Tj75ZNLT0zu97zlz5vDFF18AYLfbmT17NiNGjGhSJisri7fffjt20ExlZWWbZtWJ7M55550X+1yrq6vjT3/6U7vbarxsf9OmTR0e2852Gs9wveaaa3A6O2/vlJ22bNnSZIuBKVOmAA1/7Ng5o/T777+PzRxPpMbLGiKRSMLbFxEREREREdkTCmv8rC/zkO6y4bC2vjqzPUwhL67KVVi85U0C1EWFIe6d7yMchQm9rfxxtCvOANUg+7t/kly0gKjZStHo2wmm9evQGPe7EDUvL4/evXt3Sd9PPvlk7PqSSy5h+PDhuy2XlJTEPffcE7t/+umnCYfDnT4+2X+ZTCbuvffe2P3f//53ioqK2tVW4yX5s2fPZtWqVR0e30/3Sj3//PM73GY8Zs6ciWEYAIwePTq2NUFeXh4nnHBCrFxnzEZdvnx57LpXr14Jb19ERERERESks5XVBVhXXIfLZsFt75zz6U1hX8MMVF8FoeQfl/AvKQpz95c+QlEY18vKzUfGGaACGQUvk775PQxMlBz+//BlH9zhce53IWpXqa+vZ+7cubH7yy67rMXyZ599NsnJyUDDbNTPP/+8U8cn+7/TTz+d0aNHA+Dz+bj//vvb1c6kSZNi1z6fj3HjxvHII480WebfVjtnaMOe/UPH888/H7tuvIT/p/cvvfRSQv+QsXXr1ib7HR9//PEJa1tERERERERkT6jxhigobji8Os1l65Q+TGEfzopVWH1lhJJywNQw0/WTzSGmfeElFIWje1q55aj4A9TUze+Tuabh/JOyg6+mvsfYhIxVIWqCfPXVVwQCAaBhpumoUaNaLO90OjnqqKNi9zpgShKh8UFNzzzzDFu2bGlzGxMnTuT000+P3VdUVPDHP/6RXr16MWTIEKZOncpf//pXFi9eHHfwuHXr1tj1gQce2OYxtcdXX33FunXrALDZbLvMfp00aVLsDxmlpaW89957Cev7xhtvjC3h7927d5P3U0RERERERGRv5wmEWV1ciz8UJTPZ0Sl9mMJ+nJVrfghQc2MB6mtrAjy48Mcl/Lcd5cIaZ4CaVLSQnG//AUDF4POp6X9qwsbbOfNwf4ZWr14dux4+fDhWa+tv7WGHHcZHH320S/29mWEY+ELa37Exl83SZP/LrnT88cczYcIE5s2bRzAY5J577uHf//53m9t56aWXmDp1Km+++WbsMcMwKCgooKCggJkzZwINfzA47bTTuOqqq5g4cWKz7VVWVsau49mfeN26dTzxxBMtlrn44otjM293p/ES/ZNPPpmsrKwmz7vdbs4+++xYueeeey4hYedzzz3H66+/Hrt/8MEHcTg65z8cERERERERkUQLhCOsLamj2hskP83VKX00BKirsXpKfljCbyFqGDzzbYDXCoIAnDnYztWHOjDHmbk4K1aRt+RhTESp6fMLKg+cktAxK0RNkIKCgth1vCeaN17SvGbNmoSPqTP4QhGGTvugq4exV1l1z4mdti9Ie9x3332MHdswVf25557j5ptvZtCgQW1qIzk5mTfeeIM5c+bw+OOPM3fuXKLR6C7lPB4Pr7zyCq+88gpnnHEGM2bMoFu3bruUq6uri10nJSW12v+OHTua7DG8OyNHjmw2RPX7/bz66qux+58u5d9p6tSpsRB19uzZVFZWkpGR0er4mrN06VKuvvrq2P2FF17I5MmT292eiIiIiIiIyJ4UjkRZV1JPSa2fvFRXp0waaxKg/jADNRQxeHSxn7lbQgBcOcLBuUPscfdvr91C/sK7MUeD1OcdQemIayHBY9dy/gSpqKiIXefm5sZVJy8vL3bdeKaeSEccffTRnHzyyUDDqfB33nlnu9s65ZRT+PDDDykuLubVV1/lhhtu4Jhjjoktg2/snXfe4ZhjjmkSmO6UkpISu/Z4PO0eT7zefvttqqurgYaZr83NMJ0wYQI9e/YEIBgM8vLLL7e7z02bNnH66afj9/sBOPjgg/nnP//Z7vZERERERERE9qRo1GBjmYftVV5yUpxx70HaFjsDVJunuCFANVvwhgxu/9zL3C0hLCb442gn5x3oiDtAtXrLyF9wJ5aQB1/GEIpH/hHMlrjHZMRZbu+ZPrePq6+vj127XPFNdW5crnH95gQCgdi+qwC1tQ2b+4ZCIUKhULxDjQmFQhiGQTQa3e0sw91xWEysuOuE1gv+jDgsprjfv86wu3+/e+65h/fffx/DMHjllVe46aabGD58OEDstPqd1/GMPTMzk7PPPpuzzz4bgHA4zMKFC5kxYwYzZ86M7Y26cuVKbr311l2W4jee3VldXd1qn+PGjYvtKdpY//79Y/u8tvR5O2PGjNj1Oeecg81ma7bs5MmTefjhh4GGmbuNZ5LGq6ioiBNOOIHi4uLYOOfMmUNycnKXfm7sj6LRKIZhEAqFsFji/09RRNpu588W7fkZQ0RERKQ1+llj77Ot0sumsjq6uexYiBKNJPb3WVPYj61qHWZvMT53LmCmyhvhji98rK+K4rTC7Ue5GNndSiQaX7RpDtaR/9U0bL5yAsm92HbENKJmB8RZv94fxhrnFFOFqAmyc/YZgN1uj6tO430SfT5fq+UffPBB7r777l0e//TTT3G73XH12ZjVaiUvL4/6+nqCwWCb60uDOn/rZRKt8YFOfr8/FqjvNHDgQE477TRmz55NNBrl1ltv5cUXG06maxzEh0KhXerG6+CDD+Yvf/kL559/Puecc07sDwHPPvsst956a5M/EnTv3j12vWrVqnb32TiQ3N3rBigpKYntNQwNB0i11N+kSZNiIerixYtZunQpgwcPjntMlZWVnHrqqWzYsAFomGH+xhtvkJSU1O7XKc0LBoP4fD4+//zzuA82E5GOafw9VURERCTR9LPG3qe403twQVUtZT54arWFioCJZKvBrw+MkBKuo2BbfK2Yo0HGrP8TDs82fLZufNHnd/hKwkBVm0bj9e262nZ3FKImiNPpjF3HG0g2DrPimb16yy23cOONN8bua2tr6dWrFxMnTiQzM7MNo23g9/vZtm0bycnJTcYve7/GB5c5nU5SU1N3KXP//ffz7rvvEo1GmTNnDgUFBYwaNapJeG+z2XZbty1OOOEEbrnlFm677Tag4fOqoKCAcePGxcpMnDiRF154AWgIOaurq5vsCRwvs/nHPw8197qfeeaZJrNYTzvttDb18cYbb/DAAw/EVba2tpbzzjsvtqdxVlYWH330EUOHDm1TnxI/v9+Py+Vi3Lhx+r4l0slCoRAfffQRJ5xwAjabrauHIyIiIvsZ/ayx96j0BFldWIPZZCLNHd/EwLYwRQLYK9di9xYTdOeA2craygh/W+ajJmCQl2Ti/nFJ9Ehpw66j0Qg9lj5IimcdEVsSRUffS+/U+M4oAvAHI/iCEXpnunDWbY+rjkLUBGm8R2Q8s0p/Wm53e0z+lMPh2O0p3zabrV3fcCKRCCaTCbPZ3CSckn1Lc/9+w4cPZ/LkybHwctq0aXzwwQdN9hTZ+e/fUSeffHIsRIWGoLRxu8cee2yT8q+++ip//OMfO9Rnc6/7+eef71C7L774Ig888ECr74vH4+G0007j66+/BiAtLY3333+fgw46qEP9S8vMZjMmk6nd3/dEpO309SYiIiKdST9rdK1af4j15T6iJiuZKbtmTh1ligRw1GzA7ismmJyLxWxlaVGYu+d78YdhYDcz949zk+FqQzZhGOQs/wcpxYuImm0Ujr6DSHpf4t3wzR+K4AtH6JudRF6qkzpvnHuvxj9CaUnjmaAlJSVx1dm5fyLQoRPBRZpz11138fLLLxMOh/nwww/5/PPPO6Wfn84I/GnY37dvX0488UQ++OADAP75z39y/fXXJ3wm4bJly1ixYkXsftSoUXGHxF9//TXhcJjt27czd+5cTjih+b1//X4/Z5xxBvPnzwfA7Xbz7rvvcvjhh3fsBYiIiIiIiIjsIb5ghILiOrzBMLkpiV/pZ4oEcVQWYKvfQTApF8xWPt4c5M+L/EQMODTXwp1j3STZ2naAVcaal0jb8iEGZopH/hF/VvyTmYLhKPWBMD3T3eSlOonz7CpAIWrCHHDAAbHrnQfftGbr1q2x6yFDhiR8TCIDBgzgsssu45lnngHg9ttv32VWaCJ89913Te53t1T/lltuiYWomzZt4uabb+bxxx9P6Diee+652PXw4cNZvHhx3HVPP/10/ve//8XaaS5EDYVCnH322XzyySdAQ2D89ttvc/TRR3dg5CIiIiIiIiJ7TjAcZW1JHRX1AbqnuZqsWk0EUySIo2ottvodhJJyMEwWXlsT4F/fNmxtObG3lT+MdmGztK3ftE1zyCyYBUDpiGvw5B8Vd91w2KDGF6RHupse6a42BagAWsOdIAceeGDsevny5XEdeLJs2bLd1hdJpDvuuCM2M/SLL76IBZnN+ctf/sLHH38cd/ter7fJHqK5ubkccsghu5QbP358k5Pvn3jiCe644464+2lNKBTipZdeit1PmTKlTfUbl3/zzTepq6vbpUwkEmHy5MnMmTMHaNib9tVXX+X4449v56hFRERERERE9qxI1GB9aR1FNT7yUl2YOytArdtGKCmHqMnK09/+GKCefYCdm49qe4CaVPgV2d89BUDFARdS2+/kuOuGIwZVviB5qU56dHPRnp0NFaImyJgxY2JBlcfjYenSpS2WDwQCLFy4MHbfGbMDRQB69erFVVddFbtv/Hm3O4sXL+aEE05g1KhR/OMf/2hxe4pFixYxfvx4li9fHnvspptuanYJ/RNPPNFkxuZ9993HkUceybvvvtvigWyrV6/m6quvZvv25jd7njNnDuXl5UDDXq8XXnhhs2V354wzziAlJQVoCIb/+9//NnneMAx+9atf8dprrwENe3POnDmTM844o039iIiIiIiIiHQVwzDYVF7P1kov2clOLObEBqhEQz8EqNsJJeUQNKw8uMDH6wUNv/P/+hAHVx/qbHNw6ypfTt7SRzBhUNP3JCqHTI5/SFGo8gbITnHQKyMJaztfs5bzJ0hycjLHHXdcbIbajBkzOPLII5st/8Ybb8RmumVkZDQ5yVwk0W699VaeffZZvF5v3HWWLl3K0qVLufbaaxkwYADDhg0jKysLq9VKWVkZ3377LZs2bWpS58wzz+S6665rtk273c5HH33E5Zdfzssvvww0BLGnnXYabrebUaNG0b17d9LT0/H7/ZSVlbFy5Uo2b97cpJ0BAwZw6KGHNnms8VL+cePG0atXr7hfK4DL5eLMM8+MHUz13HPPcfnll8eef+qpp5r0MWDAAL788ku+/PLLuNr/+9//3qbxiIiIiIiIiCTa9iofG8s8ZLgd2K0JnlvZKEANu7PxRKzc/aWXb0oiWEzwh9Eujuvb9kPE7DWb6b7wPszREPXdj6R0xDXEuxbfMKDC4yczyUHvDHebZ782phA1gX7zm980CVGvu+46hg0btks5r9fLtGnTYve//vWvsVr1TyGdJzc3l+uvv56HHnqo1bLHHXccixcvbhKQbtiwgQ0bNjRbx+Vyccstt3DLLbe0+rnscrmYNWsWkyZN4p577mHVqlVAw9fFZ5991mLdwYMHc/XVV3Pttddit9tjj1dUVPDuu+/G7tu6lL9xvZ0h6hdffMGmTZvo168fAKWlpU3Krlu3jnXr1sXdtkJUERERERER6UoltX7WldaR7LDissd7ln2cfghQ7XVbCbtzqAhauPUzDxuqo7isMO1oNyO7tz37snpL6bFgGpawB1/mUIpH/gFMcY7dgApPgHSXnT6ZSTg6GBprOX8rNm/ejMlkin3MmDGj2bKnnnoqxxxzDNCwXP+0007j+++/b1KmoqKCSZMmsX79eqBhFupNN93UaeMX2emPf/wjaWlprZa78sor2bhxI8uXL+fvf/87U6ZMYeTIkWRnZ2O327HZbGRkZDB06FAuuOACnn76aXbs2MEdd9zRpj8GnH/++SxfvpxPPvmEW2+9lbFjx9KvXz9SU1Ox2WxkZmYyaNAgzjjjDO69914WLFhAQUEBv/vd75oEqACzZs2KbQfgcDg455xz2vbm/ODYY4+le/fuQMMSh8YzT0VERERERET2VVWeIAXFdVhNZlKcbZ8N2qJo+McA1ZXNNo+Z337cEKCmO0z8+dikdgWo5mAtPb6ahtVfSSClN4Wjp2FYHPFVNqDSEyTZYaVvVhJOW8cjUJNhGEaHW9nLnHLKKRQWFjZ5rLi4OLa3Y1JSEgMHDtyl3pw5c8jPz2/y2ObNm2Mz0QCmT5/OpZde2mzf27dv54gjjqCoqAho2Jtx/PjxDBgwgLKyMj7++OPYkmqr1cr777/Pcccd167XWVtbS1paGuXl5WRmZra5vt/vj820czqd7RqDiMiepO9bIntOKBRizpw5nHLKKdhsCf5BW0RERH729LPGnlMfCLNiew2eQJic1AT/HhUN46hah71uM2FXNmuqLdz2uZeagEF+sokHxifRI6XtAaYp7KfHV7fjqlxDyJXN9nGPEHZlxV2/yhPEYTXTPyeZFEfLAW7tjnWkHXE+NTU1pKamNltuv1xDvmrVKrZs2dLs8x6Ph++++26Xx1s62CZePXv25JNPPuHCCy/k22+/xTAM5s2bx7x585qUy87OZvr06e0OUEVERERERERERFriD0UoKK6lxh+ie2cFqLWbCbuzWVxq5p4vPfgjMKibmfvHu+nmbMcMUCNC3td/xlW5hogtmcKj7m5TgFrjDWGzmOmX1XqA2hb7ZYja1YYMGcKiRYt4+eWXmTVrFitXrqSkpIT09HT69+/PWWedxWWXXUZWVvyfACIiIiIiIiIiIvEKRaKsLamjrDZAXpoLU5yHMcUlGsZRvf6HADWLD7fCo4u9RAw4PM/CtKPduG3t6M8wyP7+GZKLFhI12ygcfTvB1N5xV6/zh8EEfbOSSHUlNvbcL0PUn57k3RF9+/alPTse2O12pk6dytSpUxM2FhERERERERERkdZEowYbSuvZUeUjN9WJxZzIADWEo6ohQA25Mnl5Lfz7Oz8Ax/Wx8fsjnNgs7esvff2bpG/6HwAlh/8ef9ZBcdf1+MOEo1H6ZyXTzR3nFhFGtOEjDvtliCoiIiIiIiIiIvJzZBgGWyo8bKn0kp3iwGZJ3LnypkgQR9VabPXbCLqy+Mf3Bm+tDQBw7hA7V4xwYG7njNfk7Z+RvfI/AJQddAX1PcbGXdcfjBAIR+mb5SYr2d56BYBoGGqLwZ0dV3GFqCIiIiIiIiIiIvuBSNSgsNrH+jIP6S4bDqslYW2bwn4clWuweYrwOrL506Iwn20LA3DVIQ7OGeJod9uusu/JXfYYAFX9z6B64KS46wZCUeqDYfpkuMlJiXPf150BakoeuHrGVUUhqoiIiIiIiIiIyD6uPhBmc7mHHVVeUpw23PbExX6msA9n5RpsnmJqHTnc8WWQb0sjWM3wh9Euju0T5/L53bDXbqH7ovsxR8PU5Y+hfPiv4q4bDEep9Yfo1c1FXqqLuCbBRoJQVwLpvSD7QPDFd9C8QlQREREREREREZF9VDRqUFzrZ2O5B08gRHaKM6FL+M0hD47KNVh9ZXhdudw7vyFAdVnhrrFuDstrf7xo8VWQv+AuLGEPvoyhlBz+ezDFN3s2HDGo8QXJT3eTn+7GHM9LDvuhvgy69YPsA8BqV4gqIiIiIiIiIiKyP/MGG2afbqvy4bJZyE9zJ7R9c7AOZ8VqLIFKAu4cHlkUZHFRGIcFHhjv5qDs9keL5pCXHgvuwuYrI5jck8Ijb8ewxLclQCRiUOUNkpfqpGc3F3FlxkEv+KogaxBkDgJL28auEFVERERERERERGQfYhgGJbUBNpbVU+sPkZ3sxG5N3OxTAHOguiFADdYSdOfyj2+CfLIljMUEdxzt6lCASjRM3uIHcdRuIuxIZ8dRdxG1p8ZXNQqV3gDZKU56ZSRhNcexhj9QB/5ayBoMmQPA3Pa9YhWiioiIiIiIiIiI7CN8wQibK+rZXuXDYbGQn+bCFNdmoPGz+KtwVqzCFPYSSsrjhZVB3l4XAuCPo12Mzm//HqgYBrnf/I2ksm+IWpwUHnkn4aS8eKtS4fGTkeSgd4YbmyWO1+2vgZAPcodBt77Et3HqrhSiioiIiIiIiIiI7OUMw6CsLsDGcg/VniBZKQ4c1rbPqGyNxVeOs2I1pmiAsDuHt9aFeH5FAIBrD3NybN8OBKhAxpoXSd02F8NkpmjUTQS6DYqvogEVngDpLjt9Mt044pl5662EaLghQE3r1e4AFRSiioiIiIiIiIiI7NX8oQhbK7xsrfRiNZvIT0/87FMAq7cEZ+UaMCKE3TnM3RziyWV+AKYe5GDSYHuH2k/d/D6ZBS8DUDriWrx5o+KuW+kJkuyw0jcrCZctjvDYUwYmM+QNh9T89g45RiGqiIiIiIiIiIjIXsgwDMrrg2woq6faGyQzyYEzngCxHayeIpyVazBMZiKuLBYVhnhkkQ+ASYPsTBnWsQDVXbyEnO/+AUDFARdQ2/fEuOtWeYI4bGb6ZiXhtrfy+g0D6kvA6myYgZqc05FhxyhEFRERERERERER2csEwg2zT7dUerGYTHRPc2HuhNmnGAa2+h04qgowLDYijnRWlIW5Z76PiAHH9bFxzWGODs18dVSto/uShzAZUWp7HUflkIvirlvjDWGzmOmXlUyKo5Uo04hCXTHYUyDvIHBntHvMP6UQVUREREREREREZC9SUd+w92lFfYAMtwNXa7Mv28swsNVuxVG9lqjNRdSeyoaqCLd/7iUYgdH5Vv7faGeHwlurp5j8hXdjjgTwZB9KyaHXxb03ab0/DECfLDdprlZizGikIUB1ZUDeMHCmtXvMu6MQVUREREREREREZC8QDEfZVullS6UHw6DzZp8CGFHstZtxVK0jYk8hak+msC7KLZ958YTgoCwLt49xYTW3v39zsJYeC+7EGqgmkNqP4iNuAXPrcWQ4YlDjC2KzmOmT5SbD3cpWAtFwQ4CanAM5w8CR3O4xN0chqoiIiIiIiIiISBer8gTZWF5PWV2Abm47bnsnxnbRCPaajThqNhJxpBG1uSn3Rblpnocqv0H/dDP3jnPjtLY/QDVFAuQvvBd7/Q5Crmx2HHUXUZu75UoG1AXCBEJhMpOddE9zkuJs5X2IhBoC1NR8yBkK9lb6aCeFqCIiIiIiIiIiIl0kFImyvdLLlgovEcMgL9WFpQOzP1sVDeOoXo+jdjMhZzcMq4u6oMEt87wUewzyk008ON5Nsr0DYzAi5C19FFflaiK2JAqPuouIK7PFKsFwlBpvELfDysCcFDKSHFjMrfQTDkB9KaT3hpwDwepo/5hboRBVRERERERERESkC9R4Q2wsr6ek1k+ay05yawcndVQ0hKNqLfbarYTcWRgWB76wwe2fedlcEyXDaeKhCUlkuFpLL1tgGGQtf5bkoq+Imq0Ujb6dYGqf5ocUhRpfEAPonu6ie5oLpy2O/kM+8FZARn/IPgAstvaPOQ4KUUVERERERERERPagcCTKjmofm8s9hCJ7YPYpDcvrHVXrsNVtJ+zOxrDYCUUM7p3vZVVFhGQbPDTBTffkDgSoQPqGt+i2cTYAJYf9Dl/W8GbLegNhvMEwaS473dNdpLts8Z05FfSArxoyB0HWIDB30sFbjShEFRERERERERER2UNq/SE2lXkorvWR6rCTkdT58Zwp7MdRuQabp4hQUg6YbUSiBg8v8rGkKILTAvePd9MvvWNhZPKOL8he8W8AyoZdTn3P8bstF44YVPuC2K1m+mYlk5XiwBZviByoa/jIHtIwC9XcsdA3XgpRRUREREREREREOplhGOyo9rGxzIM/FCEn2Ym11U0/O84U9uGsXIPNU0wwKRfMVgzD4MllfuZtDWM1w7SxboZmdSwmdJavIPfrRwGo7n861QPP3LWQAbX+MMFIhKxkB93TnSS35QAtfzUE/Q0HSHXrS3zTVhNDIaqIiIiIiIiIiEgn21HtY3VRHS6bhe5prj3SpzlYj7NqDRZfOcHkPDA1zDR9bkWA2etDmICbjnQxqnvHIkJ77VbyF92LORqmvvtRlA2/YpeA0x+KUOcPkeKw0SczhQy3vW2TSL0VDRuodh8OaT07NN72UIgqIiIiIiIiIiLSiUpr/awtqcNts5Dq6twDkHYyB2txVqzBEqgilJQHpobE8o2CAC+uDAJw3eFOJvTu2Hgs/kryF9yJJeTBlzGE4pH/LxbWQkPuWe0NYjZDz25uclOdOKxtnIFbXwpmK3Q/GFLyOjTe9tozmwaISKeZN28ev/nNbxg5ciTZ2dnY7XZcLhc5OTmMHDmSyZMn89hjj7F06VIMw9htG3fddRcmk6nJx+9+97s2jePdd9/dpY0JEybssdfQHrt73fF+9O3bd7dtzpgxY5eyZ565myUMLVi5cmXc/TWntLSUZ555hjPPPJMDDzyQjIwMnE4nvXr14ogjjuAPf/gD8+bN6/D7GY1G6dOnT5OxLlq0qENtioiIiIiI7E8qPUHWFNdhNZn3XIAaqMZZvgJLsJpQUm4sQP1oU5CnvgkAcOlwB6cPsneoH1PIS/6Cu7H5yggm5VM4+g4MiyP2vMcfptLrJ9VlY3BuKr0z3G0LUA0D6orB4oDuI7osQAXNRBXZZ61evZrLL7+chQsX7vJcKBTC7/dTVlbG119/zaxZswAYNmwYK1asiKv9WbNm8cgjj2C1xvdt4rnnnot/8D/o7Newt5gzZw4VFRVkZmbGVb497+VOHo+HP/3pTzz66KN4vd5dnt++fTvbt29nyZIl/PnPf+aII47g0UcfZezYse3q79NPP2Xr1q1NHnvuuecYPXp0u9oTERERERHZn9T6Q6wtriMUiZKT4twjfVp8FTgr12AK+wi5c2PL6hfsCPHnxX4AzhpsZ/LQjgWoRMN0X/IQzpoNhB3p7BhzD1FHGgDhsEGVL4DLZqVvZjLZKQ6s8R4ctZNhQF0ROFIhdxi4Mzo23g5SiCqyD/rmm2849thjqa6ujj2Wm5vLyJEjycvLw2QyUVFRwYoVK1i/fn1stmHj8q0pKSnhgw8+4NRTT221bHV1NbNnz97rXkNb5Ofnt2nGaLyBKEAwGOTll1/m2muvbbVsNBrlxRdfjLvtxgoLCzn55JP5/vvvY4+ZTCZGjhxJ//79SUlJobi4mEWLFlFWVgbA4sWLGT9+PI899hjXX399m/vcXeD78ssv89hjj+FwOHZTQ0RERERE5OfBF4xQUFxHrT9EXuoeCFANA5unCEf1WohGCCflxJ76vjTMfV/5iBpwfF8bVx3qwNSRQ5kMg5xv/05S6TKiFgeFR04jnJSHYUCtL0Q42hAa56e7cNstrbe3O/XFDQFq94PBmdb+sSaIQlSRfUwoFGLy5MmxMDE/P58nn3ySM844A/NudmQuKyvj7bffZubMmWzcuLHV9ocOHcqqVasAeP755+MKUV999VX8fv8u9bvqNbTHoEGD+Pvf/57QNgcOHMiWLVsIhUI8//zzcYWoH3/8MYWFhUB87+VOxcXFHHXUUbFZoSaTiSuuuII777yTHj16NCkbiUR49913ueGGG9i0aRPRaJTf/va3eL1ebr755rhfX319PW+88Ubs3uVy4fP5qKqqYvbs2ZxzzjlxtyUiIiIiIrI/CYQjrC2po6I+QPc0V8cCy3hEw9hrt2Cv2YBhdRFpNGtzfVWEO77wEozAkflWfn+EE3MHx5Ox5iXStn6MgZniUTcR6Db4x4OjnDb6pSfRzdXGg6Ma85SDxdUwA3UvCFBBe6KK7HPeeust1qxZAzSEVp9++imTJk3abfgIkJ2dzRVXXMFnn33GvHnzWm1/+PDhjBgxAoB33nmHmpqaVuvsnI1os9m48MILu/w17C0yMzM55ZRTgIYZnwUFBa3WaTyzc+rUqXH1YxgGU6dOjQWoFouFl156iX/961+7BKg7nz/jjDP47rvvOOqoo2KP33777Xz++edx9Qnw2muv4fF4gIbA+Jprrtnt6xAREREREfk5CUeibCitp6jGR16qq8OBZWtMYT/OyjU4qtYRsacScfwYOm6vi3DLPC/eEAzPtnD7GFfbl9U3Fg2R/e2TZBY0bLlXOuIaarNHUVkfxB+K0Kubm8G5KWQmdSBA9Vc3LOXPHdrlS/gbU4gqso/58MMPY9e//OUvGTx4cNx1BwwYEFe5Sy65BAC/38+rr77aYtkNGzbw1VdfAXDKKaeQlZXVavt74jXsLXa+l9Aws7cldXV1vPXWWwCMGDEiFma3Zvr06Xz00Uex+4cffpgLLrig1XopKSm899579OzZE2iYoXrppZcSiUTi6rdxUDplypQmoe/7779PaWlpXO2IiIiIiIjsL6JRg41lHrZWeslJcWLpSGAZB3OwFmfFSux12wm7szFs7thz5d4oN3/qpTpgMLCbmXuPceOwtn88Fn8VPb+8jfTN72FgomzoZRR2P4FKb5B0t40DclPp1daDo34q6IGgD3IOhJTc9rfTCRSiiuxjduzYEbvu06dPp/QxefLk2IFSrQV/jZ+Pd+bknngNe4tTTz01tn/qCy+8ENvbdXdee+212GFQbZmF+uc//zl2f9hhh3HDDTfEPb60tDT++te/xu43bdrE66+/3mq9LVu28Nlnn8Xup0yZwogRIxg+fDgA4XC43Xu7ioiIiIiI7IsMw2BrpYdN5fVkJjmwWTo3drN6y3CVLcfqryCYnIthscWeqw0Y3DzPS4nXoEeKmQfGu0mytz9AdVStpde8G3BVriJidbP9iDtY171h+78B2UkMyEkm1dXBXUPDfvBVQfYBkNazY211AoWoIvuYxkveN23a1Cl95Obm8otf/AKA+fPnN9uPYRjMnDkTgIyMDE477bS42t8Tr2FvYbfbOf/88wHYunVri9sR7AykLRYLF110UVztf/7556xevTp2f8MNNzS7LUJzJk2aRP/+/WP3Tz31VKt1nn/++VggPGbMmNgM4YsvvjhWRkv6RURERETk56Swxs/6Ug9pLjtOWzsPU4qHEcVWuxVnxXKIBgkl5YHpx/58IYPbPveypTZKlsvEQ+PddHO2PwJM2TqXnl/chM1fQTC5J1vH/YVtKSPITnEyJC+F3FRnx7YIAIiEoL4MMgZAt37Q2XvItoNCVJF9TOPl7LNnz4774KG22jkT0jCMZmejfvHFF7EQ9Pzzz8dut8fV9p56DXuLxrNKm3svG8/s/MUvfkFubnzLFj799NPYtd1u5+yzz27z+EwmU5O9bBcsWEAgEGixTuPX0Tg4veiii2Ih7nfffcd3333X5vGIiIiIiIjsa0rr/KwrrsNps5Dk6MRz3KMhHFXrcVauJmpxEHFlNnk6GDG460svayoipNhNPDTBTV5yO+O/aJis758mb9ljmKMh6vNGs238Xyg155DmstE7w43LnoCwOBqBumJI7wNZg2j/Zqqda+8clYg0a9KkSbFrn8/HuHHjeOSRR5oskU+EX/7yl6SlNWxGvXO26U+1Zyk/7LnXsLcYPXo0BxxwAACvv/56bMl+YzNnzozN7GzLe/nll1/Grg8++GDcbncLpVse406BQIClS5c2W3b+/PmsX78eaAhuzzvvvNhz+fn5HHfccbF7zUYVEREREZH9XbU3yNriOgDSXLZWSrefKeTFWb4Se+0Gws5uRO0pTZ4PRw0eWOBjWUkEpxXuH++iT1r7Qk5zoIYeX02j28bZAFQccCFFo2+jKmTDbjPTO7ODe5/uZBhQVwQp3RuW8Vs67/3rqE6MxkWkM0ycOJHTTz+d2bN/+EZWUcEf//hHbrrpJgYPHswRRxzByJEjOfLIIznssMNie5u2ldPp5LzzzuOZZ55hw4YNzJ8/n6OPPjr2vN/v57XXXgNg8ODBHHnkkXvda2iLdevW8X//939xl7/44oubBI+tmTp1Krfddht1dXW8+eabuyzX3xlUp6WlNQmZW7N58+bY9UEHHRR3vZ/6ad3Nmzc3+fdurHEweuqpp5KR0fS0xIsvvjh20NWLL77Iww8/vEf+DUVERERERPa0+kCYNcV1+ENRclOdndaPxV+No2otlkAlIXcumJv+jhWOGjzwlY/528PYzHDXWDcHZrbv9zB79UbyF92HzVdK1Oqi+LAb8eQfhTcQxsCgT2YSKYmabVtXDK6MhoOkbJ33/iWCfquVtjEMCO06i+5nzebe43t1vPTSS0ydOpU333wz9phhGBQUFFBQUBAL5JKSkjjttNO46qqrmDhxYpv7mTp1Ks888wzQMOu0caj21ltvUVNTEyu3t76GeBUWFvLkk0/GXX7kyJFtClGnTJnC7bffHtseoXGIunDhQtauXQvAueeei9MZ/38clZWVsetu3brFXe+nflq3cbuN+f1+Xn311dh946X8O5111llcc801eDweSktLef/99+PeL1dERERERGRf4Q9FKCiupcYXonsnBqhWTzHOqrUQ2bn/adMZoJGowYMLfHwRC1BdHJ7Xvsgveftn5H7zV8yRAMGk7hSNvp1gah+C4SjeUIR+WUlkuOPbyq9V9aUNmUruUHAkJ6bNTqQQVdom5IUH8rt6FHuXWwvBnrRHu0xOTuaNN95gzpw5PP7448ydO5doNLpLOY/HwyuvvMIrr7zCGWecwYwZM9oUtI0dO5b+/fuzceNGXn31Vf7617/icDiAH2cjmkym3QZpe8tr2Fv07t2bCRMm8OmnnzJ37lyKioro3r070HRmZ1sD6bq6uth1UlL7Pw+Tk5v+h1VbW7vbco3D84yMDE499dRdyiQlJXHWWWfFgvDnnntOIaqIiIiIiOxXguEoBcV1lNUFyUt1YuqMyVXRCPa6rdir12NY7ESScnYpEokaPLTQx+fbwljNcOdYF0fkt2NJvBEhc9XzZKx7HQBPzuEUj/wDUXsy4YhBjS9Ij3Q3OckJCot91Q1hcO4wcO0bv+NrT1SRfdgpp5zChx9+SHFxMa+++io33HADxxxzzC6BGMA777zDMccc0yR0i8fOgLS6upp33nkHgOLi4thy7fHjx9O7d++9+jXEY/z48RiGEffHpZde2uY+dgakkUiEF154AYBgMMgrr7wCQL9+/Rg7dmyb2kxJ+XEPHI/H0+Yx7VRfX9/kPjU1dbflGge+5513XrOHiTUO1mfPnk1VVVW7xyYiIiIiIrI3iUQN1pfVUVTjJzfFgaWjJ9PvhikSwFFVgLOqgKg9mYhz16AxEjV4eJGPeVsbAtRpR7sY3Y4A1RysI3/BXbEAtXLQORQeNY2oPRnDgCpvkOwUJ/ndXIk58ylQByE/5AyF5OwENLhnaCaqtI3N3TDzUn5ka99BPomUnZ3Nueeey7nnngtAOBxm4cKFTJ8+neeff55wOAzAypUrue222/jrX/8ad9tTp07l7rvvBhqW9J977rm8+OKLRCKR2PNd/RoqKyuZNm1ai+0feeSRTJkyJSFjba9zzjmHa6+9Fq/Xy8yZM/nDH/7QJGC8+OKL2/zXy4yMjFj95pbgx+OnIedP9zkFKCoqioXnsPul/Dsdd9xx5OfnU1hYSCAQ4OWXX+aaa65p9/hERERERET2BoZhsKm8nq0VXrKTnVgtiZ+faA7W46heh9VTTMidjWHZdfJKJGrwyCI/n2wJYzHBHWNcHNWj7QGqvXYz3Rfdj91TRNTioOSwG6jvcUzs+SpPkDSXjd4ZbmyJCItDvoYQNWcopPXoeHt7kEJUaRuTaY8vXZe2s1qtjB07lrFjx/KrX/2KE088MTbT8JlnnuFPf/oTLpcrrrb69+/P2LFj+fLLL3n//fcpKyvj+eefB8DtdnPOOed0+Wuora1tdT/T+vr6Lg9Rk5OTOeuss3jhhRdYvnw533zzTey9hPYF0n379mXDhg0ArFixot1j+2ndvn377lLmhRdeiIXn/fv3Z8yYMc22ZzabmTx5Mn/+85+BhhmsClFFRERERGRft63Sy8YyDxluB/ZEnE7/ExZfBY6qAizBOkLJeWCy7FImEjV4dLGfuVtCWExw+9EuxvRse4CaVPgVeV//BXPET8idS+Ho2wim9Y89X+MNYbeZ6Z3pxpGI1xoJgqccsgZDep+Ot7eHaTm/yH5uzJgx3HrrrbF7v9/PkiVL2tTGznAvHA7zxz/+ke+//x6AM888s8ly8s6SiNewt2gclD766KO89957ABx99NEMGDCgze01Puxr+fLleL3tO/ht0aJFsWuHw8HIkSN3KdN4Kf/GjRsxmUwtfuwMUHe2X1BQ0K6xiYiIiIiI7A2KanysLa0nxWHDZd813OwQw8BWvwNX+feYw74fDpDatY+oYfCXJX4+2hzCbILbxrgY29YA1YiSsWom+YsfwBzx4806mK3j/9IkQPUGwhgY9Ml0k+JIwBzMaBjqSqBbP8gcSGL2Bdiz9r0Ri0ibnXTSSU3ui4qK2lT/vPPOi50YP2PGjNjjiVrKH4+WXkPfvn1b3cO08bi70nHHHUePHg1LFl588UVCoRDQ/vdy4sSJsetgMMhrr73W5jYMw2DWrFmx+zFjxsQOENvp66+/ZuXKle0a406NQ1gREREREZF9SXl9gLXFdTgsZpKdCV7YHQ1jr9mAs2IFUbOVsDu7YSXwT4sZBo8t8fPhpoYA9dajXBzTq20BqjnkofvCe8lc23A2R9WAX7JjzL1EHWmxMsFwFG8oQs9ubjLcuz8Ho02MKNQWQ2o+ZA8Gy765MH7fHLWItMnOAHSnnwZkrUlLS+OMM87g1VdfjT2Wn5/P8ccfn5DxxaOjr2FvYTabueiii3j44YdjjzmdTs4777x2tTd+/HgOOOCA2CzPJ554gilTpmBuw1/13nrrLTZu3Bi7v/rqq3cp0zgAzcjIYNCgQXG1XV1dHRvbzJkzue+++9o0NhERERERka5W4w2xpriOqAEZSQkIFRsxhf04qtZiq99B2JWBYd391ntRw+CJJX7e39gQoN5ylIvxvdsWoNrqtpG/6H7s9duJmm2UHnIddb2PbVImHDGo8QXpke4mN8XZTEttYBhQVwxJWQ37oFr3zd/lQSGqyM/Cd9991+S+d+/ebW5j6tSpTULUiy66aI+GYYl4DXuLqVOnNglRTz/9dNLT09vVlslk4v/9v//HlVdeCcCyZct4/PHHufHGG+OqX1NTw/XXXx+779+/P2effXaTMqFQqMlM1dtuuy3u9ktLS8nPzycSibB9+3Y++eSTPRq+i4iIiIiIdIQnEGZNcS3+YITc1ASEio2YAzU4Kwuw+CsJJeWAefehqGEY/O1rP3N+CFBvGu1iQhsD1KSiReR+/WcsYR8hVxZFR9xGoFvTyTGGAVXeINkpTvK7uRKz4t5TBvZkyB0K9q4/mLsjFKKK7GP+8pe/cPDBB8cdRHm9Xh544IHYfW5uLoccckib+z3ppJOa7EM6cODANrexU1e9hr3FsGHDWLZsWeyQpl69enWovcsvv5xZs2bxySefAPDHP/6RHj16cP7557dYr76+nlNOOYXt27cDYLFYmD59OhZL03133n33XcrLy4GGmbQXXnhh3GPLycnhhBNO4P333wcaZrQqRBURERERkX2BPxShoLiOam+I7mmJDVCt3hIclWsxRXw/HCC1+8RyZ4D6v/UhTMAfRjs5tm8bAlQjSre1r5K5+kVMGPgyh1E06mYizm67FK3yBElz2ejVzY3NvOt2Am3mrQSzFXIPAmda6+X3clpTKbKPWbx4MSeccAKjRo3iH//4ByUlJc2WXbRoEePHj2f58uWxx2666aZ2zSC1WCyMHDky9tHemZPQda9hb3LooYfG3svc3NwOtWU2m3nhhRfo2bMnAJFIhAsvvJCrrrqKHTt27FI+Eokwe/ZsRowYwVdffRV7/N5772XcuHG7lG+8lP/YY4+le/fubRrfRRddFLt+4403qKura1N9ERERERGRPS0UibK2pI7SOj+5qU5Mu9mjtF2MKLaaLTjLVwARwkktB6hPLvMzu1GAenzf+LcTMIW8dF/8EFmrX8CEQXW/U9l+9H27DVBrvCHsNjO9M904bQn4fdtfC5EQ5BwISZkdb28voJmoIvuopUuXsnTpUq699loGDBjAsGHDyMrKwmq1UlZWxrfffsumTZua1DnzzDO57rrrumjEu9qbXsO6dev4v//7vzbVueWWW2KHRHW17t27s2DBAk466SRWrlyJYRj861//4plnnmHUqFEMGDCApKQkSkpKWLRoEaWlpbG6JpOJxx57jN/+9re7tFteXs67774bu28ciMZr0qRJuN1uvF4vXq+X1157jcsuu6x9L1RERERERKSTRaIGG0rrKaz2kZPixJKIWZkA0TCO6vXYa7cQsacQtSc3W9QwDJ76JsDb6xoC1BuPcHJCv/gDVJuniO4L78VRt5Wo2UrZwddQ2/fE3Zb1BsIYGPTJTCLFkYCoMOiFQB3kDms4TGo/oRBVZB9z3HHHsXjx4ibh4oYNG9iwYUOzdVwuF7fccgu33HILVmvXf9nvja+hsLCQJ598sk11rrjiir0mRAXo2bMnCxYs4KGHHuKxxx7D5/NhGAaLFy9m8eLFu60zatQoHn30UY455pjdPj9r1ixCoRDQ8G/w0/1S45GcnMykSZN46aWXgIaZrQpRRURERERkb2QYBpvLPWyp9JKV7MBmSdAqyGgIR9U67HVbCbsyMSzNH7BkGAZPfxvgzbVBAH43yslJ/eMPUN0lX5O39GEsIQ9hZwZFR9yCP+PA3ZYNhqN4QxH6ZiaR4U7AoVnhQMMy/uwDoFvfjre3F+n6NEVE2uTKK6/kyiuvZMWKFXz22WcsXLiQNWvWsGXLFmpqajAMg5SUFPLy8jj44IOZOHEi5557Lt267Tpdv6vsD69hb5WSksL999/P9ddfz1tvvcV7773H6tWrKS0txev1kpWVRX5+PuPGjeO0005jwoQJLS5LabyU//TTTyclJaVd47roootiIernn3/Opk2b6NevX7vaEhERERER6Szbq3xsLK8n3WXDYbW0XiEe0RCOqrU/BKjZGJbmw0rDMHjmuwCvF/wYoJ48IP5wM23ju2R//zQmovi6HUDREbcSce1+OX0kYlDjC9Ij3U1uSgL2fI2Gob4UMvpD5gBI1BYIewmTYRhGVw9C2qe2tpa0tDTKy8vJzGz7/hJ+vz8WZDidid0gWUSkM+j7lsieEwqFmDNnDqeccgo2W9tOfxURERFpzd74s0ZJrZ+VhTU4rRZSnIkZkykSxFG1FlvddsLubAxL8+0ahsGz3wV4dU1DgHr9SCenD4w/QO227jWyVs4AoKbPLyg7+Jpm+zMMKK8PkJ3ioG9WUscPkopGoK4IUvIhbzhYEzCrdQ/Zma/V1NSQmprabDnNRBURERERERERkZ+1ivoAa4prsZrMXRag/uf7HwPU6w5vQ4BqGGSseZHMgpcBqDjgAiqHXNTiTNAqT5A0l41e3dwdD1ANA+qLISkbcofuUwFqWyhEFRERERERERGRn60ab4jVxXVEIpCdkpgA0BQJ4KgswFa/g1BSDphbDlCfWx7g5dUNAeq1hzk5Y1D8AWrWin/TbcNbAJQPvZSqwee0WKXGG8JuM9M7043TloA9X+tLwJHWcJCUzdXx9vZSClFFRERERERERORnqc4fYnVxLf5ghNzUxGwZ1pYAFWDmigAvrmoIUK851MGkwfEGqFFyvvsHaZvfB6B0+FXUDDi9xSq+QAQDgz6ZSaQ4EhALeivA4mwIUB3tO0NjX6EQVUREREREREREfnY8gTBriuuo9YXIS1SAGvbjqFyD3VNEMCkXzC1HbzNXBJi5siFAvfpQB2cd4Iivo2iE3G8eJ3XbpxiYKD30Omr7/KLFKsFwFE8oTN/MJDLcCZhx66+BaBS6HwTujI63t5dTiCoiIiIiIiIiIj8r/lCENcW1VNQH6J7mwpSAk+TbGqC+uDLA8ysCAPz6EAdnxx2ghshb+mdSCudjmMwUH/576nuOb7FKJGJQ4wvSI91NbkoCAmN/LQS9kHcQpOR1vL19gEJUERERERERERH52QiEIxQU11FWFyQv1YU5QQGqs3I1Nk8xwaQ8MFtaLD9rVYAZyxsC1F+NcHDukPgCVFMkQPfFD5JUspSo2UrxqJvxdD+yxTqGAZXeINkpTvK7uTB3ZBtUwwBPGZjMDUv403p1oLF9i0JUERERERERERH5WQhFoqwrqaeoxkdeqgtLR0+m58cA1eopiStAfWV1gP983xCgXn6wgwsOjDNADfvIX3gv7vLviVocFB1xK97cw1utV+UJkuay0aubG1tHXm803HCIlD0Vcg6E5Oz2t7UPUogqIiIiIiIiIiL7vXAkyvrSOrZX+chJcSYoQPXhrFyD1VNCKCm31QD1v2sCPPtdQ4B66XAHFw6NL0A1hzzkL7gLV+VqolYXO468E3/WQa3Wq/GGsFvN9M5047R1YApqOAD1pZDSHXKG7PeHSO2OQlQREREREREREdmvRaMGG8s8bK30kp3sxGbpyJr2BqaQt2EGqq+MUHIumFoOUN8oCPCvbxsC1KkHObhoWJwBaqCGHl9Nw1mzgYgtiR1j7iHQ7YBW6/kCEQwM+mQmkeLoQAQYqGs4RCqjP2QNAmuce7fuZxSiioiIiIiIiIjIfsswDDaVe9hYXk9mkgO7NTEBqqtyFRZfRcMM1FYC1E+3hHjqm4YAdcowOxcfFF8QafFX0WP+bTjqthK2p7Hj6HsJpvVvtV4wHMUTCtM3M4mMJHtcfe2WpxyiEcg9CNL70LENVfdtClFFRERERERERGS/ZBgGWyu9bCirp5vbjtPWctgZD3PIg7PihwA1jhmo35eGeWSRD4AzB9uZGmeAavWW0mP+bdg9RYSdGWw/+n5CKa0f5BSJGNT4gvRId5Ob4oyrr11EIw37n9qSIO9gSMltXzv7EYWoIiIiIiIiIiKyX9pR7WNdST0pThtue8djMHOwviFADVQSSs5rOKW+BVtqItz5hZdQFMb2tHLVIQ5Mptb3YrXVF9Jj/m3YfGWE3LlsP/p+wkl5rdYzDKjwBshJcZLfzdW+iaORINSVQHJOwwFSzrR2NLL/2a/n4AaDQWbOnMkpp5xCnz59cDqddO/enTFjxvDnP/+Z8vLyTuv7s88+48orr2TIkCGkpaXhcrno378/kyZNYtasWYTD4U7ru60Mw+jqIYiIxEXfr0REREREJF7FNX7WltThsllI7sieoD8wB+t+CFCrCCW1HqBW+KLc9pmX+hAMzbRw85GuuA6zstdupeeXN2PzlRFM7sH2sQ/FFaACVHuDpLls9Ormxtaeg7OCHqgrhW79oPshClAb2W9noq5Zs4YLL7yQb7/9tsnjxcXFFBcXs2DBAh555BGmT5/OKaeckrB+KyoquPjii3nvvfd2eW7Tpk1s2rSJt99+m0cffZQXXniBIUOGJKzvtjL/8OeIaDTaZWMQEWmLnd+vzD/jfXhERERERKR1ZXUB1hTXYjWbSXXZOtzejwFqzQ97oLb8O4kvZHDH515KvAY9UszcM86FwxpHgFq9kR5f3Y41WEsgtQ87xtxHxNktrjHW+8NYLCb6ZCThtLXjdyZvJYSDkDsUuvUFc8e3Ptif7Jch6vbt2znuuOMoLCwEwGQyMW7cOAYMGEBZWRkff/wxPp+P0tJSJk2axPvvv8+xxx7b4X6rqqoYM2YMa9eujT3Wv39/jjrqKJxOJxs2bGD+/PmEQiG+/vprJkyYwMKFC+nbt2+H+24Pq9WKyWTC7/eTlJTUJWMQEWkLv9+PyWTCat0v//sSEREREZEEqPQEWVNcCwZ068ihSj8wB2sbBah50Mpy/EjU4N6vfKyripLuMPHAODdpjtZDTWflGvIX3Ikl5MGfPogdY+4mak+Na4z+UIRgOEr/nCRSnG38fcmINsw+tTohfwSkdG/1Nf4c7Ze/hU6ePDkWoPbp04e3336bESNGxJ4vLy/nggsuYO7cuYRCIc4991w2bNhAenp6h/r91a9+FQtQnU4n//rXv7j44oublNmwYQMXXnghS5YsoaSkhLPPPpulS5fGtR9GopnNZpKTk6mtrSUzM3OP9y8i0la1tbUkJydrJqqIiIiIiOxWjS/E6qJaguEoOe09VKkRc6CmIUAN1cUVoBqGwV+X+llSFMZhgXvGuchPaf33F1fZ9+Qvuhdz2IcvYyiFR91J1BbfhLdwxKA+EKJnupuspPgOrYqJhBoOkHJnQc4QcMU36/XnaL/7LXTOnDl88cUXANjtdmbPnt0kQAXIysri7bffpn///gBUVlby8MMPd6jfr7/+mjfffDN2/5///GeXABVgwIABfPjhh/Tu3RuAZcuW8dJLL3Wo745ITU3F7/fj8Xi6bAwiIvHweDz4/X5SU+P7S6yIiIiIiPy81PkbAlRfMEJ2chvDxN0wB6pxVqzEHKoj5M6Na3bmS6uCzNkYwmyCW49ycWBm6/MX3SVfk7/gLsxhH97sQ9gx5p64A1TDgCpvkKxkJ93TXW2bQBr0Ql0xpPWE/EMUoLZivwtRn3zyydj1JZdcwvDhw3dbLikpiXvuuSd2//TTT3fosKf//ve/seuDDz6YCy+8sNmy6enp3HrrrbH7J554ot39dlRycjJJSUls27ZNQaqI7LU8Hg/btm0jKSmJ5OTkrh6OiIiIiIjsZbzBMGuK66jxhchJcXR4xa85UI2rfBXmkIdwnAHqx5uDzFgeAOA3hzkZ07P1vViTCr8if+G9mKNB6nNHUXjkNAxr/DNoqzwNB0n1znBjbctBUr5q8NdA9hDIHQ42V/x1f6b2q+X89fX1zJ07N3Z/2WWXtVj+7LPP5uqrr6a+vp7Kyko+//zzdu+NumjRoth1PAdVnXrqqbHrJUuWsHXr1tjs1D3JbDbTs2dPtm/fztatW3E6naSmpuJ0OjGbzV2yzYCIiGEYRKNR/H4/tbW1sb2be/bsqaX8IiIiIiLShD8UoaC4jkpPgLxUV4ezDIu/YQaqKewj7M6JK0D9piTMo4v9AJw3xM4vB7W+F2vKtnnkLvsLJiNKXY9jKD7892COP6qr84exW830znDjsMb5e5JhNCzft9ih+8GQ2kP7n8ZpvwpRv/rqKwKBhsQ/KSmJUaNGtVje6XRy1FFH8dFHHwHwySeftDtELSkpiV336dOn1fI9evTAYrEQiURifV966aXt6rujdgap9fX11NbWUlZWhmEYXTIWEZHGTCYTycnJZGZmai9UERERERHZRTAcpaC4jpIaP3lpLswdDlCrcFaswhTxEXZnxxUwbqqOcNeXXsJRmNDbyq9GtL6VQOrmD8j59u+YMKjtfTwlh14HJkvc4/SHIoTCUQbkJMd/kFQ0DLXF4O4GOUPBnRF3f7KfhairV6+OXQ8fPjyu05sPO+ywWIjauH5btTV0NJlMTf4ysnLlynb3nQhms5nU1FRSU1OJRqOEw2Gi0WiXjklEft7MZjNWq1XBqYiIiIiI7FYoEmVtSR1FNT5yU51Y2rKcfTcs/sofAlR/wwzUOJR5o9z2mRdvCIZnW/jD6NaD3PQNb5O9/BkAqvudStnBV4Ep/t97whGDOn+IXt2SyExqfcYrACEfeMobZp7mDAF7fHuuyo/2qxC1oKAgdh3PbFCgyRL6NWvWtLvv7OzsWP2tW7e2Wn7Hjh1N9mDtSICbaGazGbs9zi9CEREREREREZE9LBI1WF9ax/YqLzkpTqyWjk2+sPgrcZavxBQNxB2gekIGt3/upcxn0CvVzF1j3dgtLQeo3QpeJWv18wBUDTyL8mGXtWk5vWFAlSdATqqT/HgPkvLXQKAesgZB5kCwtL5Xq+xqvwpRKyoqYte5ublx1cnLy4tdV1ZWtrvvww8/nC+++AKA999/nwceeKDF8nPmzGlyH0/fgUAgtl0BQG1tLQChUIhQKNTWIYuIiIg0a+fPFvoZQ0RERDpDR37WiEYNNpV72FzhITPJjoUo0Uj7V9OaA7XYKlYRjQQalvBHW19tHI4a3POlj43VUbo5Tdx7jIskW0O4u1tGlOzVz5O5/nUAyg6YTMXgC8CgIRmNU1V9kBSnje5pTqJGlGikhcKG0TD71GSG7GENs1CjQFQ/3zUW7+fgfhWi1tfXx65drvhOFWtcrnH9tvrlL3/J448/DsA333zDa6+9xjnnnLPbsnV1dTz00EO7PNaaBx98kLvvvnuXxz/99FPcbnfbBy0iIiLSip3bHomIiIh0ho7+rFGUoHE0sEJFVaulDANe2mBmWZkZu9ngV4PC1FTWUNPM/DhLNMChW54hs3oxACvyL2CD+yTYXt2uUZYCG4tq2lap4Hvg+3b1t7/zer1xlduvQlS/3x+7jnc5usPx42a/Pp+v3X1PmDCBo48+mvnz5wNw6aWXEg6HueCCC5qU27x5MxdddBEbN25s8ng8fd9yyy3ceOONsfva2lp69erFxIkTyczMbPfYRURERH4qFArx0UcfccIJJ2CzacmXiIiIJFZ7f9bYXullXWkdKU4bbnvHYi1T2Iezcg0WXyWhpNy4l9XPXBFgcVkQswluP9rNEd2bH4fFX0XPxQ/jql6HYbJSNOL/sPY+jgPaONZAMII3FKF/dhIZre2DGg5AfRmkdm9Ywm9PbmNvPy87V3q3Zr8KUZ1OZ+w6GAzGVafx8vh4Z68254UXXmDUqFGUl5fj8Xi48MILueOOOzjyyCNxOp1s2LCBL7/8klAohNvt5phjjuGDDz4AICUlpdX2HQ5Hk9B3J5vNpl9uREREpFPo5wwRERHpTG35WWNHtY8NFX5SXC6S4z2RvhmmSABnzXqsgQpCKXlY4jzY6f2NQV5c1ZA5/Xakk6N6ND92e81G8hfei81XRsSWQuHo2/BnHYSljWMNhw08oQh9MtzkpjpbKRwAXwVkD2wIUK0686Y18X7+7VchanLyj8l6vLNKG5drXL89+vbty1dffcXZZ5/N8uXLAVi/fj3r169vUi43N5cXX3yRt99+Oxaipqend6hvEREREREREZH9VUmtn7XFtThtlg4HqERDOCoLsHmKCSblNewZGoclRWEeW9KwCnryUDunDGg+oEwqXkze0kcwh30Ek3tSeOQ0Qsn5bR9qFKp8AfJSneSltTL5LxKC+lLI6A85Q8Dc1rhWWtKxo8v2Mo2XtJeUlMRVp7i4OHadkZHR4TEMGjSIb7/9llmzZnH22WfTq1cvnE4naWlpHHroodx7772sWLGC4447jvLy8li9Xr16dbhvEREREREREZH9TVldgDVFtVhMZtJcHVwhE43gqFqHrb6QYFJO3EHj+qoI9873EjXg+L42Lh2+60phAAyD9PVv033hfZjDPrxZB7Nt3J/bFaACVHkDdHPb6dHNjaWlFC8ahrpiSO8D2QcoQO0E+9VM1AMO+HFHiS1btsRVZ+vWrbHrIUOGJGQcZrOZCy64YJf9UH9q5cqVsetRo0YlpG8RERERERERkf1FWV2AVUU1GAZkJHdwaboRxV6zAXvtVsLuLDDHF8iWeqLc9pkXXxgOybFw4ygnpt3tnxoNk/3906Rvfg+Amj4nUjriGjC3L36r9YVx2Cz0ynTjsLaQoEYjDQFqao+GGagWbcXUGfarEPXAAw+MXS9fvpxwOIzV2vJLXLZs2W7rd7bq6mpWr14dux8zZswe61tEREREREREZG9XWudndWEthgGZyc3M/IyXYWCv3YyjZhNhVwaGJb5Atj5ocOtnXir9Bn3TzNw11o3NsmuAag7Wk7fkTySVfYOBifKDLqd6wKS4D6v6KV8wQsSI0i8jmeSWDtAyolBXBMk5kDsUrB18n6RZ+9Vy/jFjxsQOXvJ4PCxdurTF8oFAgIULF8bujz322E4dX2NvvPEGoVAIgKFDh3L44Yfvsb5FRERERERERPZmpbUNASqYOh6gAra6rTiq1xFxpGFYWzmc6QfBiMFdX3rZUhsly2Xi/nFukuy7hqJWTzE9v/gDSWXfELU4KRp9O9UDz2x3gBoOG3iCYXqmu8hIaiHsNQyoLQJ3FuQMA1vHDkyXlu1XIWpycjLHHXdc7H7GjBktln/jjTeoq6sDGvZDHTduXGcOLyYQCHD//ffH7q+++uo90q+IiIiIiIiIyN6upNbPqqKGALXFEDFOtvpCHFXriNhSiNrccdWJGgaPLvbxXWkEtxXuG+cmJ2nXGM1ZsZLen92Io24bIWcm2455GE/30e0eazQKld4AuakOclNbCUXrS8CZBrnDwNGxw9KldftViArwm9/8JnY9Y8aMJvuONub1epk2bVrs/te//nWrS/8TwTAMrrnmGjZu3AjAQQcdpBBVRERERERERAQormmYgWpOUIBq9ZbgqCrAsDqI2uMPGqd/H+CTLWEsJpg21s2Abrse1JSy9RN6zL8NS7AWf/ogto3/C8H0/u0frNEQoGYk2enZ2kFS9aVgdTUEqM7U9vcpcdvvQtRTTz2VY445BmiY8Xnaaafx/fffNylTUVHBpEmTWL9+PdAwC/Wmm27abXubN2/GZDLFPlqa3frhhx9y5513xgLSn9qwYQOnn34606dPB8DlcvGf//wHm00b/oqIiIiIiIjIz1tRjY/VRTWYzSa6JSBAtfgqcFYWYJhMRBxpcdf73/ogL68OAvC7UU4Oz/vJpDsjSuaqmeQt+wvmaJj67mPYPvZBIq7MDo23xhfCZbPQO9ONvaUE1VvRcFhV3kHgzuhQnxK//epgqZ1eeukljjjiCIqKiti8eTOHHHII48ePZ8CAAZSVlfHxxx/j9XoBsFqtvPrqq6Snp3e438rKSu655x7uueceBg8ezPDhw8nMzKSuro6CgoImh1g5nU7efvttRo0a1eF+RURERERERET2ZQ0Bai02s5l0d8cDVHOgGmflGoiGiLiz4663cEeIv33tB2DqQQ5O7N90LKZIgNxlj5Oy4wsAKgedQ8XQqWDq2DxFXyCCgUHvzCSSWjpIylfdsOa/+8GQlNWhPqVt9ssQtWfPnnzyySdceOGFfPvttxiGwbx585g3b16TctnZ2UyfPr3JPqqJsnbtWtauXbvb50aOHMnTTz/NYYcdlvB+RURERERERET2JYXVPtYU12K3WEhzdXy1rjlYh7NiNaawl3BSbtz1Cioi3P+Vj6gBJ/WzMWVY0wDV4q8if9G9OKvWYpislBzyf9T1Ob7D4w2Fo3iCIfpmJZPRUoAcqIOwH/KGQ0peh/uVttkvQ1SAIUOGsGjRIl5++WVmzZrFypUrKSkpIT09nf79+3PWWWdx2WWXkZWVuNT+tNNO480332Tu3LksWrSIoqIiysrKcLlcdO/enSOOOIJzzz2Xk08+GbN5v9tJQURERERERESkTYpq/Kwr9+JIUIBqCnlxVqzGEqwllBR/0FhUH+X2z734IzAyz8JvRzkxmUyx5+01m8hfeA82XxkRWwpFo2/FlzW8w+ONRqHaF6R7mpPcFGfzBYOehhA1Zyik9exwv9J2JsMwjK4ehLRPbW0taWlplJeXk5nZsX03RERERBoLhULMmTOHU045Rfu3i4iISMLt/FnDPWAkLocjMQFq2I+zcjVWb0lDgBrnEvsyb5SbPvWyrS7KgHQzfzkuCbftxwDVXbyE7ksfxhz2EUzuQeGR0wgl9+jweDGg3BOgm9tO/+yk5vdBDfnAWwk5B0JGf2gU7krH7czXampqSE1t/pCu/XYmqoiIiIiIiIiI7H0Mw2BHlQ8ApzVBM1AjQRxVa7F5Sggm5cYdoG6sjnDbZ17KfQbZbhP3jXf/GKAaBukb3yFr+b8xEcWbdTBFR9xK1J7c4fFCw0FSbpuF3hktHCQVDoCnArIGQbd+ClC7kEJUERERERERERHZIwzDYHuVl3UldQCkJiBAJRrGXr0OW30hwaQcMFviqvZ1cZh7vvTiDUPvVDP3j3OT5TLH2sz+/mnSN78HQE2fX1A64jdgTkyU5g2EfzhIKhm3vZnxRkJQX9ow+zRrEGhryC6lEFVERERERERERDqdYRhsq/SytqQet92KNyGNRnFUb8Reu5WwOzvukPODjUEeW+InYsDB2RbuOsZNir1hlqc5WE/ekj+RVPYNBibKh11G9cAzEzYLNBiO4g1F6JuZRDd3MyFyNAx1xZDeB7IPiDsYls6jEFVERERERERERDqVYRhs/SFATbZbcdugvOONYq/ZhL12E2FXJoalhZPtG43jhZVBnl8RAODYPlZ+f4QLu6UhILV6islfeDeOum1ELQ6KR/4BT/cjOzrSmGi0YRl/iwdJRSMNAWpqD8gZAhbtT783UIgqIiIiIiIiIiKdxjAMtlR4WFdaT7LDRrLDSjQS7mij2Gq34qheT9iRhmFt4WT7H4QiBo8v9fPhphAAFw61c+lwB+YfZpg6K1bRfdF9WIO1hJyZFB05jUD6gI6Ns8mYodITIDPJTs9u7t2vzjeiUFcEyTmQOxSsjsT1Lx2iEFVERERERERERDpF4wA1xWEjyZGYKMrmKcRRvZaIPQXD5m61vCdkcM+XXpaVRDCb4PrDnZw68MeZqynbPiXnmycwR8P40wdSOPoOIq7MhIwVAAMqPAGSnVZ6Z7ixWXazNYBhQG0RuLMgZxjYXInrXzpMIaqIiIiIiIiIiCScYRhsLm8IUFOdiQtQrZ5iHFUFRK1OovbkVsuXeaPc/rmXjdVRnFa4fYyL0fk/LpFP2zCbnOVPA1DffQzFh98Y18zWtqj0BEmyW+mXnYSruYOk6kvAmQa5w8DR+uuSPUshqoiIiIiIiIiIJFQ0arCp3MOGsnrSXDbc9sREUBZfOc6qAgyThagjrdXyG6oi3P65l3KfQYbTxH3j3AzK+DHETF//NtkrngGgasAvKT/oV2Da3Tr79qvyBHHYzPTNSiK5ufehvhSsroYA1Zma0P4lMRSiioiIiIiIiIhIwnRagOqvxlm5BowIEVdWq+WXFoW5d74Xbxj6pJq5f7yb3KQfA9L0dW+QvfI/AFQOPpeKA6eCaTfL7Dug2hvCZjHTPyuZFGcz74O3AsxWyDsI3BkJ7V8SRyGqiIiIiIiIiIgkRDRqsLG8ng2l9aS77QkLUM3BOhyVqzGF/YSTclot//7GII8v8RMxYESOhbvGukm2/xiQdlv7GlmrZgBQccAFVA65KOEBao03hMVsol9WEqmuZt4HXzVEo9D9YEhqPRiWrqMQVUREREREREREOmxngLq+tJ4Mt6P5vT/byBzy4KxYjSVYSygpr8WyhmEwc0WAmSuDABzXx8aNRzixNzrIqVvBK2StnglAxZCLqBxyYULG2VidLwwm6JvlJt1t232hQB2E/ZA3HFJafl3S9RSiioiIiIiIiIhIh0SiBhvL6tlY7klsgBqsx1m5GkugilBSbouzRUMRg8eW+PlocwiAyUPtXDrcgalRnYw1L5G55iUAyg+8mKoDzk/IOBur94eJGFH6ZyeT4bbvvlDQ0xCi5gyFtJ4JH4MknkJUERERERERERFpt0jUYENpQ4CamWTHaUtQgBqo+SFArfkhQG3+wCdP0ODu+V6+KYlgNsFvRzo5ZUCjANMwyFjzIpkFLwNQPvRSqgafk5BxNhmHP0woGqVfVhKZSc0EqCFfwzL+nAOhW9+Ej0E6h0JUERERERERERFpl84KUC3+KpwVqzGF6xuW8LcwA7XUE+W2z71sronissLtY1wckd9oCb1hkLl6JhlrXwWgbNjlVA86KyHjbMwXiBAIR+mb5SY72bH7QuEAeCogaxB065fwfVil8yhEFRERERERERGRNgtFomworWdLpYfMJEfiAlRfeUOAGg0Qdre8hH9DVYTbPvdS4TPIcJq4f7ybgd0ajcMwyFw1g4x1rwNQdtCVVA/8ZULG2Zg/GMEbitAn001OinP3hYL14K2GjH4NIaq5+Zm1svdRiCoiIiIiIiIiIm3iC0ZYW1JHUY2frGQHDmtiAlSrpxhn1RoMI0rYndNi2aVFYe6d78Ubhr5pZu4f5yYnqVEwaRhkrfg33Ta8BUDpwVdR0//0hIyzMX8oQn0wTJ8MN3mpzl0z32gY6svBYoXsIZDRF8yJeb9kz1GIKiIiIiIiIiIicavxhVhbUkdFfYDcFCdWS2JmVNrqC3FUrcEwWYi4slos+/7GII8t8RM14JAcC3eOdZNsb5ReGgZZy/9Ft42zASgd8Rtq+p2SkHE2FghFqfeH6Nktie5prl0DVH9NwwFSyXmQOQDcGQkfg+wZClFFROT/s3ffcXbVdf7HX+fcXqb3SU9ICCQEAgQQBBawICCr2ECURBTUdUWXXdtvlVV0dRF3YV0LljUSELCLuoj0HkINYCAkhEySmWR6uf2e+vvjJkN6JsmdzCR5Px+PPLjlnPP93CG5M/O+n+/3KyIiIiIiMiLd6QKrOtMUbI+WqhhmOdb09H1C6fVEBlbhB6O4kardHOpz89+K/GKFBcBbpoa4ekGUUGDrANWj4cUfUb32/wDoOu4fSU09d//r3I7leKQKNpNq4kyo3i5AdW3IdkMwBk1zoWpSqRNVDlr6vyciIiIiIiIiIrvl+z7tAzlWd2cwMWiq3MW6n3t9YY9wagPhwdV4oSReOLnLQ23X54anC9zbZgNw6dFhFh4TwTC2DVAbX/gBVW1342PQPf/TpKa8rTy1bl2L45EqWEyojtNaHX9jeVPfh8IgWDmomgC10yG661BYDh4KUUVEREREREREZJcc12Ntb5a1vVmSkSAV0VDZrh1KtRFJrcWNVOKFErs8Lmv5fPWxHMu7XUwDPntilHfMCG97kO/RuPx7VK27Bx+DruM/S3ryOWWrdQvH9RnMW7RURZlYE2d4NQOnCJkeiFRAy7FQ2aq1Tw8hClFFRERERERERGSnCrbLa90Z2gdy1CUiRENlCgU9B4Do4Os48Rr8YGyXh3ZnPf71kRxtQx6xIHzltDgLWraLtHyXpuf/h8r19+Fj0nXCP5GedFZ5at2K4/oM5CyaK6NMqk2UAlTfh3x/KUStmQq10yCy645aOTgpRBURERERERERkR2kCzavdqbpTRdprIwSKtMGUoZrER5cDYAdrcHcTYC6dtDlSw/n6Mv71MUMvnFGnCNqtgtyfZem526kcsOD+IZJ5wn/TGbimWWpdWuu6zOQK9JYEWVSXYKgaYCdh2wfxKqhcQ4km3hjbr8cShSiioiIiIiIiIjINnozRVZ1pskUHZqrYgTMMmwgBRhukUj/q5jpjUAUP7jrtVVf7nX414dzZGyYWmXy72fEaUxsF1B6Lk3P/ReV7Q+XAtQTP09mwpvLUus2w3jQnytSn4wyuS5OyPBLU/c9r7Tuad10CO06DJaDn0JUEREREREREREBShtIbRwqsLorje9Dc2V0242b9oPhFIj0rySc3UQ+3gADmV0e+2ynw1cfzVFwYU59gG+cEScZ3q4Oz6X52e9Q0fEovhFg04IvkG09tSy1bjOMB33ZInWJCFPq4oTdPKT7IV4P9UdAogHK9DWS8UshqoiIiIiIiIiI4Ho+bb1ZXu/NEgsFqIqVbwMp084S6V9JMNeDlWgGdj3l/dENNt9cmsfxYEFLgGtOixMNbh+gOjQ/cz0VGx/HN4JsOumLZFtOKVu9W/g+9OcK1MQjTK2NEsl3gRGEhtlQMwWCkbKPKeOTQlQRERERERERkcNc0XFZ051hfX+OmniYeLh8kZFppYn2vUKg0I+dbAIjAJ6/02Pvft3ihqcLeD6cMSnIF0+JEQpsH6DatDz9bZKbluKZQTpP+n9km08qW71b+H6pA7UqGmZqhUsk1wkVTVB7BCTqyj6ejG8KUUVEREREREREDmPZosOqrjRd6QINySjhYPk2RjKLg6UA1UphJ5vB2PW1f/tqkZueLwLwjukhPnNidIe1WA3Xpvnpb5HsfArPDLHppP9HrnlB2eodtjlArQz7TIsMETPj0DQXqidBoHwdunLwUIgqIiIiIiIiInKYGshavNqVZihn01xZvg2kAAKFfqJ9r2A4OexE8y7XDfV9n5v/VuQXKywA3j87zMeOjeywFqvhWrQ89U0SXc/gmWE2nfyv5JpOKFu9bxQE/VmLKrJMi/rEaiZB3QyIVZd/LDloKEQVERERERERETkMdQ4VeLUrheP4tFSVbwMpgGCum0j/SgzPwkk07fI4z/f54fNF7lxtA3D5vAgXHxXeeYC67N9JdD+LF4iw8eSvkG88rmz1bm0glaHK62diUyOx1iOhcgKYgVEZSw4eClFFRERERERERA4jnuezvj/La91ZwkGTxsrybo4UzHYS7X8FH3Dijbs8zvXgO08VeGCdgwF8+oQo75wZ3uE4wy3S8uQ3SPQ8XwpQT/k38g3zylozAL5PZqCHpFGkdeqRJFuPhEhF+ceRg5JCVBERERERERGRw4TleLzek6GtL0t1LEwiUsZoyPcJZTcS6X8V3wzgRmt2XYfr87NVJn8bcAgY8PlTYpw9Zce1Rg2nQOuT1xLvfREvEKXjTV+lUD+3fDVvGce1yfdvJBCtpGXmCVQ2TgazfGvDysFPIaqIiIiIiIiIyGEgZzms7sqwaahAfTJCJFjGKeq+Tyi1nsjgKrxgFC9Stes6bJ9rHs3ztwGTcACuOS3Gya07BqimlaH1ya8R638FLxgrBah1c8pX82aGWyTX34lVOZGps46lpmbX4a8cvhSiioiIiIiIiIgc4oZyNq92pejPWjRVRAkGythl6XuEU21EBlfjhirwwsld11H0+H8P51jV7xEJ+Hz99Djzm3cMUAOFASY88RUiqTbcUIKNb/oqhdqjylfzFnaBbH8nTu00ph45n/rKRPnHkEOCQlQRERERERERkUNYd6rAqq40BdujpSqGWcYNpPBcwkNriAytxY1U4YXiuzy0N+fxxYdyrEt5VIYNrjzSYV7jjtFUMNvFhCe+TDi7CSdSTcepX8eqmla+mjfzrQKZ/o0EG2dyxJHzqUrEyj6GHDoUooqIiIiIiIiIHII8z6d9IMfqngxBw6SpMlrW6xt2rtSBmlqHHavDD+76+hvTHl94KEtn1qchZvDvZ8bID9k7HBdOraf1ia8QKvRhx5voOPXr2MnWstYN4BZz5Aa7iLYcxZRZx5KIlXdzLTn0KEQVERERERERETnEWI5HW2+Wtr4sFZEQyWg5N5DyCOa6iAy+jmmlseMN+IHwLg9fO+jyxYdy9Bd8WpMm3z4rTn3M4NWhbY+LDKxiwtKvErBSFCsm03Hqtbix+vLVvZlTyJAb6qFi4hwmz5xHNLzjcgIi21OIKiIiIiIiIiJyCOnLFFnbm6U3Y1GXCBMNlW8DKdNKE06tI5TpwAtGsZMtsJvlAV7udfjyIznSFkyvNvmPv4tTEzVxPX+b42I9L9K67OuYTp5CzSw63vRVvHBl2erewsqlKKb7qJkyj0lHzCUUVDQmI6O/KSIiIiIiIiIihwDL8djQn2Ndfxbfg+bKKAGzTOufeg6h7CbCQ2sxnRxOrAE/sPsOzmc7Hb76aI6CC0fXB/j3M+IkwzvWk9j0JM1PX4fp2eTq57Hx5C/j72Zt1X1VSA/iFNI0TJ/PhOlzMMu5uZYc8hSiioiIiIiIiIgc5PqzFq/3ZOjNWNTEQ8TD5Yt8zOIgkaG1hHJdOKHEiNYofXSDzbeW5rE9OKE5wL+9OU4suGOAWrnhAVqW/zeG75FpOYXOEz+/26UB9lV2aADTydB8xHE0T5mNYSpAlb2jEFVERERERERE5CC1pft0fX8Wr+zdpzbhdAfh1FoMz8aKN4K55yjpr69b/NfTBTwfTp8U5IunxAgHdqxpevc9tHbcCkBq0jl0zb8KzPItPQCAD+mBPsJGgeaZJ1A/adZulx8Q2RWFqCIiIiIiIiIiB6H+rMXa3gw96SLVsTCJSPlinkC+j3CqjWC+GzdchRerG9F5v3u1yA+fLwJw7vQQnz1xJ6Gu71P36u00dNwGwMD0C+k95mNglLc71PdhaKCbpOnROmsBVa0zynp9ObwoRBUREREREREROYjY7ua1T/uyuB40V8bK1n1qOAVC6Q2E0xsADzvRDMaeu0N93+fmvxX5xQoLgPfNDnPFsRGM7bs+fY/6l35Czet/AqDnyEsZnH1x2btDXdcnPdhDVcSnddYCko1Ty3p9OfwoRBUREREREREROUgMZC1eH43uU98nmO8hPPQ6gcIATrRmxJs7eb7PD58r8ofVpQD1I8dEuOTo8I4BqufS9Px/U7nhAQBenPghwkd+gECZA1TH8ckMdlEbDzLhyBOJ1k0q6/Xl8KQQVURERERERERknLNdj/b+HOv6cri+X+bu0zzh1DpC6fVgBrGTLSOeWu96Pt95qsB9bTYAnz4hyoUzd9wYynAtmp/+NsnOJ/ENk03HfZa1HMeRZXkFbyjaHvmhThororTMWkC4Zs+bYImMhEJUEREREREREZFxbPS6Tz2CuS4ig2sJWEPYsTr8YHTEp1uuz78/keeJDgfTgM+fHOOcqaEdjjPsHK3LvkG890U8M0Tngi+SajoJNgyU53Vsli+62OkuWqvjNM9aQKCyuazXl8PbqIaohUKBu+++m8cee4wNGzYwMDCA67rcf//92xzn+z75fB6AUChEKLTjPzgRERERERERkcOJ7Xp0DORo683heOXtPjWtDOFUG6FMB14wipVs3at1SdOWz1cfzfFij0s4AF8+NcabJuyY55hWiglP/BvRwdW4wRibTv4K+YZ54PlleR3D9RQcjEwXE+uqaJx5AkaysazXFxm1EPU73/kO3/72t+nr6xt+zPf9HdfDAPr7+5k8eTKFQoGTTz6ZJ554YrTKEhEREREREREZ9wZzFq/3ZOlOF6iKhakrV/ep5xLKbiI89DqmncOJ1+MHdpx+vzudGY9/fSTH+pRHPATXvjnOsU071hfI9zLhiWuIpNfjhivpeNPXKNbMLM/r2MpgxiJq9dDaVEvd9BMgUVf2MURGtsDFXrBtm/PPP58vfOEL9PX14fv+8J9dqaurY+HChfi+z7Jly3jttdfKXZaIiIiIiIiIyLhnux5tvRmWbxikP2vRXBkjWaYA1SwOEu19iWjfCjAM7IrWvQ5QX+13ueq+LOtTHg0xgxvPSew0QA1lNjLpkc8TSa/Hjtax4fTryh6g+j70p4sk7F4mN9VRN+NEBagyasoeon7yk5/kL3/5C77vE4lE+PjHP84vf/lL/v7v/363533oQx8avn3XXXeVuywRERERERERkXFtMGfxt44hVnamiQQDNFVGyzN937MJD7UR71lOKN+NHW/AjVTt9WWe7LD5l/uzDBR8plebfPetCaZVB3Y4Ljz0OhMf/TyhfDdWooX2M67Hrpi0/69jK54HfZk81V4fk1obqZp+IsRryzqGyNbKOp3/2WefZfHixRiGwYQJE7jnnnuYPXs2AI888shuzz311FOpqqoilUrx6KOPctVVV5WzNBERERERERGRcclxPToG86ztzeK45V37NFDoJzy0lmCuGzdShRfdt6DxT6stvvdcAc+HE5sDfPm0OInQjjVG+16h9cmvErCzFCun0XHqtbjRmv19GdtwXJ+BbJ5mBmlpbSY28ViIVZd1DJHtlTVEXbx48fC6p7fccstwgDpSxx13HA8//DCvvPJKOcsSERERERERERmXhnI2a3szdKYKVEXD1CXKE9UYrkUovZ5waj34LnaiGcwdu0b3xPN9/veFIr9aaQFw7vQQnzkxSnAnIW+861lanvomplskX3s0G0+5Bi+c3O/XsjXL8RjKFZgQGKKlpZVw67EQrSzrGCI7U9YQ9cEHHwRg7ty5nHnmmXt9/sSJEwHo6OgoZ1kiIiIiIiIiIuPKlu7Ttt4sdtm7TweIDK0hkOvFjVbjheL7dB3L9bl+WZ6H1jsALDomwgePDu900/Bkx6M0P/OfGL5DtvEENp30JfxgdL9ex/YKlkumUGBKKE1T8wSCrfMgUlHWMUR2pawh6saNGzEMg/nz5+/T+clk6dOJbDZbzrJERERERERERMaNLd2nXekClZEwtWXqPsVzCKU7iKReB8/FTjaBsffdpwCpos+/PZrjb70uQROuXhDlrdN2vglVZdvdNC7/PgY+6Qmn03nC1WCG9ueV7CBTcLBsm+nhFA0tkzGb50KkvF2uIrtT1hC1UCgAEI3u2ycNmUwGeCNMFRERERERERE5VNiuR8dAjra+HLbr0ZiMEgyUZ89v00oTHlxDOLsJJ1KFF9v3bGVTxuNfH86xIe2RCMG/vTnO/KadR0g1q39D/YqfAzA09Vy6j/3kPge3O+XDYN4Gz2FGLE1d0xSMprkQTpRvDJERKGuI2tDQQEdHB52dnft0/sqVK4evIyIiIiIiIiJyqOjPWqztzdCbLlIZDVOXiJTnwr5HKNtJePA1TCePlWgCc9/jnlf7XL78SI7Bok9D3OCbZ8aZWrVjKGo4BepX/IzqtXcB0D/zvfQdvRB2MtV/Xzmuz0CuSEXIYFIkTXXTFGiaA6FY2cYQGamyhqizZ8+mvb2dpUuX4rougcDIP3nYsGEDy5cvxzAMFixYUM6yRERERERERETGRNFx2dCfY31/Dt+DpjKufWo4ecJDrxNOt+OFYtjJlv263hMdNt98Ik/RhSNqTL5+Rpz62I6dstG+FTQ9dyPh7CYAeucsYmDme/dr7O3liy4Zy6ExEWJicJBo7dTNAWp511kVGany9Ixvdu655wLQ29vLkiVL9urcr3zlK7iuC8Db3/72cpYlIiIiIiIiInJA+b5Pd7rACxsGea07QyIcpLEyWp4A1fcJ5rqJdT9POLUBJ1aHG6ner0veudria4+VAtQFLQH+8+zEDgGq4Rapf+knTHz0i4Szm7Bj9XScem1ZA1Tfh4GMheV6TKuNMi2SIlo7UQGqjLmyhqiLFi2iqqoKgKuvvppnnnlmROdde+21LFmyBMMwaG1t5eKLLy5nWSIiIiIiIiIiB0zecnm1M82LG4bIFl1aqmLEw+WZDGy4RcKDq4n2vIDhFrCTLfiBnW/4NBKe7/Oj5wt879kCng/nTQ/x9dPjxEPbhr3R/pVMfvAqatbciYHP0OS3sP6s75FrPH5/X9Iw2/HozRRIRIPMakzQYg4SqGxSgCrjQlmn89fW1vKNb3yDT3/606RSKU4//XQ+9alPcckll1AsFoePS6VSbNq0iccff5wf/vCHPPfcc8PP3XDDDYRC5dnBzbIsfvnLX3L77bezYsUKurq6qKmpYdq0aVx00UUsWrSI+vr6soy1vaVLl3LLLbfw5JNP0tbWRjqdJhaL0dTUxPz583nXu97Fe97zHiKRMq2BIiIiIiIiIiJjyvN8utNF1vZmGMrZ1CUjREPl22QpUBggMvgagXwvTqwWP7h/a4Nars91T+Z5ZIMDwOXzIlx8VBhjq3VNDdeiduVt1Kz+HQYeTrSWruM+Ta65vEsxZgoOBcelpSpKa1WUSK4L4vXQNFdroMq4YPi+75f7op/97Gf57ne/u80/Oii1sgO7fPyaa67hq1/9allqWLlyJZdccgnLly/f5TGNjY0sXryY8847ryxjAvT19fHRj36UO++8c4/Hzpgxg5tvvpnTTjttn8ZKpVJUVVXR29tLXV3dPl1DREREZGds2+auu+7ivPPOK9sH3CIiIoeyTNGhrTfLxsE80WCA6nhoh/xjn3kO4XQ74dRa8ByceD0Y+xfOpooe1zyaZ0WvS9CEz50U4+yp237Pjwyspum5G4ik15fOmXgWPfM+jhdO7tfYAK7n8+qGAWZOqCFVsAgHA0yqiVEXD2NmNkKsFlrmQWT/xxLZnS352tDQEJWVlbs8rqydqFvceOONzJs3j3/5l39hcHAQKAWnW948ts9tq6urueGGG1i4cGFZxm9vb+ecc85h48aNw2OfccYZzJgxg56eHu677z7y+Tzd3d28613v4u677+bss8/e73Hz+TxvectbtgluGxoamD9/PhMnTqSnp4cVK1bw+uuvA7BmzRre9ra38cADD3DyySfv9/giIiIiIiIicmC5ns+moTxtvVmylkN9Iko4WL7VE00rRXjwdULZTtxIJV5s/5uoNqY9/t8jOTrSHskQfPXNcY5t2ioi8mxqV95B7epfY/geTqSa7mM/Rbb1Tfs99vb6c0XqkxEm1MSoCAcg3QnRKmieqwBVxpVRCVEBLr/8ct7//vfzs5/9jLvuuoulS5eSTqeHn49EIpx00klccMEFfPzjH99t0ru3PvjBDw4HqFOmTOHOO+/k2GOPHX6+t7eXiy++mPvvvx/btnnf+97HmjVrqK6u3q9xr7vuuuEA1TAMvv71r3P11VcTi73Rdu77Pr/85S/5xCc+wdDQELlcjiuuuIIXX3xxv8YWERERERERkQNrKG/T1pulM1UgEQ7SWhUv38V9j1B2E+HBNZhOHjvRCOb+xziv9Dlc80iewaJPU9zg38+MM6Xqja7W8ODrND/3X0RSbQCkJ5xO97xP4EWq9nvsYT6kcjYAE6ujTKhJEAoYkN4E4SQ0HwPR8uVEIuUwKtP5dyWbzTI0NEQikRjegKrc7rrrLs4//3wAwuEwzzzzDMccc8xOa5k3b95wV+iXvvQlvvnNb+7X2FOnTmXdunUAfOYzn+HGG2/c5bG/+c1veN/73jd8/8UXX9xpnbuj6fwiIiIyWjSdX0REZNds12PjYKn7tOh41CcjhALl6z417Bzh1FrC6Xa8UBy3TAHm4+0231qap+jCzBqTb5wRpza2uW7PoXbVr6l99Q4M38UJV9Jz7D+QmfDmsoy9heP6DOSKRIMBNnSnecf8iaXO3UwXBGOlADVeW9YxRXZnpNP5y/cvfAQSiQStra2jFqACfP/73x++vXDhwl0Gk4lEgmuvvXb4/o9+9CMcx9nncVOp1HCACnDJJZfs9vh3vetdxONvfEK1atWqfR5bRERERERERA6M/qzFi+2DvLIpRTgQoKUqVr4A1fcJ5rqI9SwnnFqPE6srW4D6+1VFvvZYKUA9uTXIf56dGA5Qw6k2Jj38z9St/AWG75JpOZX15/yg7AFq3nIZzBdpqIgys7E0Vd8wgEw3mJHSJlIKUGWcOqAh6mjLZDLcf//9w/c/8pGP7Pb497znPSSTpX+0/f39PPLII/s19tZqamp2e3wwGNwm3fY8b5/HFhEREREREZHRVXRcXutO88KGAQZzNs2VMZLR8q2SaLhFIgOrifa8gOEWsZOt+IHwfl/X831uer7AD54r4gMXHBHia2+OEQsZ4LnUrPoVkx76LNGhNbihJJtO/BybTvoSbqR6v8fewvdhIGtRdFym1CaYVp8gGt68hECuv7RMQfNcSGiWrYxfh1SI+sQTT1AsFoFSp+mCBQt2e3w0GuVNb3pjUeQHHnhgn8duaGggGo0O31+xYsVuj+/p6aG7u3v4/tZrtoqIiIiIiIjI+OD7Pj3pIi9sGOS17izxcJDGiigB0yjbGIFCP7HuFwgPrcGNVOHG6ja3aO6fouPz9cfz/PZVC4CPHRvhqhNKtYfSG5j06Oeof3kJpueQaVrAunN+QGbimWUZewvH8elNF4iFA8xsrKC1OkZw66+d75c6UJMNZRtTZDSM2sZSW8tms6RSKWzbHvE5kydP3utxXnnlleHbxxxzDMHgnl/e8ccfz7333rvD+XsrFArxjne8g9///vcAfOMb3+Dtb3/7NlP2t/aFL3xhuPv0nHPOYdasWfs8toiIiIiIiIiUX95yWd+fY0N/joBp0FIVxSxjwIjnEE63E069Dr6HnWwGI7Dn80ZgsODxb4/mebnPJWTC506OcdaUEPgu1avvpO6VWzA9GzeYoGfelaQnnV3W8BQgU3Ao2A7NVVEm1MSJBLfq5csPlf7beBRUNJV1XJHRMCohqud53Hbbbdxxxx089dRT9PX17dX5hmHs0/qkr7766vDtKVOmjOicrcPalStX7vWYW/vmN7/JvffeSyaT4bnnnmPevHl85Stf4bTTTmPixIn09PTw4osv8h//8R889thjABx99NEsXrx4v8YVERERERERkfLxPJ/udJG23iyDeYu6RIRoqDzh5hamlSIyuIZgthM3UoUXTpblur7v89B6h58sL9CT96kIw1ffHGdeY5BQpoOm524k1l9qIss2nkD3/E/jxOrLMvYWngeDOYtg0GB6Q5KGZBRz67nQhSFwCqXbFc1lHVtktJQ9RF2zZg0XXXQRf/vb34DSP94DZeuwtqlpZJ9iNDe/8Y+1v79/v8afPXs2jz/+OO985ztZv349a9asYdGiRTs9trq6mg9/+MP8+7//OxUVFSO6frFYHF6uAEqbWUFp99y96fIVERER2ZMtP1voZwwRETnc5CyH9f05Ng3mCQcCNCdDGIaP5+77ZtRbM1yLQK6HSKoNwylQiDeW1gT19j8/WdXvctPyIi/3ugC0JA2+9uYYkysMKl+7k4ZXbsZ0LdxgjO45H2No8ltL3adlGHsL2/EYKlhUx8JMqC6tG+v6Hq67+YBiBopZ7LojgRX6WUPG3Ej/DpY1RB0cHOTv/u7v2Lhx4zbhaTwep6amZkTT6/fH1ps7xWKxEZ2z9XHbbw61L+bNm8eqVav46U9/yhe+8AWy2exOj3v729/OJZdcMuIAFeBb3/oWX/va13Z4/MEHH9zlsgEiIiIi+2PLskciIiKHozwwNKojRGAgvd9XGbLgz+tNnu4x8DEImz5vmeBxVouP0d1B/TM/oT5Tmr3bkzya56d8jLxZD+2D+z32rvQN5FmzcTdfvddKe8noZw0Za7lcbkTHlTXVvO666+jo6MAwDBKJBF/60pe45JJLmDZtWjmH2aVCoTB8Oxwe2Q52kUhk+HY+n9/vGnp7e/n85z/Prbfeim3bNDc3c+qpp1JfX8/g4CDLli1j3bp1/PKXv+SXv/wlV155JT/4wQ8IBPY8LeBLX/oSV1999fD9VCrFpEmTOOuss6ir0w52IiIiUj62bXPvvffy1re+lVAoNNbliIiIjCrP89k4mGdtbwYwqE2EMcq1PqjnEsj3Ek63EywO4AajuJEqMPZ/r2/L9fndKotfvmKR39woe/aUIJcfE6E+BtVtd9P46mJMt4AXiNI953IGp5zL5DKvfeq6PoN5i2gowITq2Oav3/bF5iA/CA2zoWYKtuPoZw0ZF7bM9N6Tsoaod955JwCmafKXv/yFN7/5zeW8/B5Fo9Hh25ZljeicrafHj7R7dVdWr17N2WefTXt7O5FIhO9973t8/OMf36YD1/d97rjjDj7xiU+QSqX48Y9/TCAQ4Ac/+MEerx+JRLYJfbcIhUJ6wxEREZFRoZ8zRETkUGc5Hmv7M6zvz5OMRKiIlun7nu8RzPcSSm8gmO/FC4RxK5rACLC/q6v6vs9j7Q4/Xl6gM1uaCTy7LsAn50c4uj5IZHAN9U/8hHhfaanFXN1cuo7/LE6ieb/H3l7BdkkXbBoqokysiREP72QEOwfWEDTNhvojSksIbE5Z9bOGjLWR/v0ra4i6bt06DMPg9NNPP+ABKkAy+cYizCPtKt36uK3P31uO43DRRRfR3t4OwE033bTT9VANw+CSSy6hvr6et73tbQD88Ic/ZNGiRZx00kn7PL6IiIiIiIiI7J1M0eG1rjSdqSL1yTCRYBkiRt8nUOgjnN5AMN+NbwSx4w2ldU/LYM2Ayw+fL/BCd2mR0bqYwceOjXD2lBChQh/1z95CxYYHMPDxAhF6j17I0PQLytL5ur1MwcFyPCbVJGipjhI0d9Lh6hQg2w8NR0LdDHZsURU5OJQ1RE0kEhQKBWbNmlXOy47Y1lPau7q6RnROZ2fn8O3a2tp9Hvu3v/3t8GZaRx55JAsXLtzt8W9961t5y1vewn333QfA4sWLFaKKiIiIiIiIHCC9mSKru9KkCg7NlVECOwsA94bvEygOljpPc52AgR2rB7M8XZaDBY+fv1TkL6/beD6EA/C+I8N84KgIcaNAzcpfUfPa7zHd0ozb9MQz6T3qMpzEyDbe3lvpvIPre0xrSNCQjOw8G3WKkO0tdZ/WzQCz/EGuyIFS1hB12rRp9PX1jXgtgXI78sgjh2+vW7duROesX79++Pbs2bP3eey77757+PZZZ501orVTzj777OEQ9ZlnntnnsUVERERERERkZDzPp30gx5qe0vqnLZXR/V7/1CwOEsp0EMp2gu/iRmvxAyPbq2VPbNfnztUWt64okt28ifiZk4JccVyUprhP5bp7qHvlVoLFAQDytUfTM/ejFGuP3M1V989g1sYMwIz6JLWJXbxO14JMN9ROh/pZYJZ7IQGRA6usIeq73/1unn76aR5//PFyXnbEjjrqqOHbL730Eo7jbLMe6c4899xzOz1/b3V0dAzfHukmT/X19cO3h4ZGd78/ERERERERkcOd5Xi83pNhfX+OZCS43+ufmlZ6c3i6EcO1caI1+MHonk8cAd/3WbbR4UfLi7SnPQCOqDH5h/lRjmkMEu9+jvplPyOSagPASrTQd/QiMq2njt6UeR/6sxaRkMnUugTV8V18/Vwb0l1QM620kZQCVDkElDVEvfLKK7nuuutob2/nJz/5CVdccUU5L79Hp556KpFIhGKxSDab5ZlnnuGUU07Z5fHFYpEnn3xy+P7ZZ5+9z2NvvSlVf3//iM7p6+sbvl1dXb3PY4uIiIiIiIjI7m29/mldIkw0tO/BnmlnCWY2Es52YDhFnEgVfixetlrXDbnc9HyBZzpL655WRwwunxfhbdNCxDLrqX/iZyS6nwXADSXpP/Jihqadjx8YvQ2aPA/6c0WSkSBT6xNURHYRKXkOpDuhego0zoZAWaMnkTFT1r/JtbW1/OIXv+Dd7343n/70p4lGo3z4wx8u5xC7lUwmOeecc7jrrrsA+PnPf77bEPV3v/sd6XQaKNV+xhln7PPYkydPHr794IMPjuicBx54YPj2EUccsc9ji4iIiIiIiMiu9WaKvNaVYShv79f6p4aTJ5TdRDjdjmlncaLVeNF9319le6mizy1/K/LH1yw8H4ImXDQrzAfnRKh0B6l78RdUtt2DgYdvBBmcfj79R16MF64oWw0743nQmy1QEwsztT5BPLyLANpzILUJqidB41EwiqGuyIFW9o8DzjvvPO655x4uu+wyFi1axI033sh73/te5syZQ1VV1YjXGdnXQPMf/uEftglRP/3pTzNnzpwdjsvlclxzzTXD96+88so9Tv3fnbe85S1873vfA2DlypXccsstuw2QH3jgAe69997h+29/+9v3eWwRERERERER2ZHn+XQM5nite/P6p1X7tv6p4RQI5roIpzdgWmncSBVOxYSy1el6Pn9eY3PzS0XSlg/AqROCXHlclIlxm+rXfkXt6t9gOnkAMi2n0jtnEXaytWw17Irj+vRnizRURJlcGyca2sXmUJ5b6kCtnAANR0GwPGvCiowXo9JTffzxx3PxxRdz/fXXs3z5cpYvX75X5xuGgeM4+zT2+eefz+mnn86jjz5KsVjkggsu4M4772TevHnDx/T19XHJJZfw2muvAaUu1C984Qs7vV5bWxvTpk0bvr948WIWLVq003FnzZrFqlWrgFIom81mueKKKwgE3viExvd9fv3rX3PllVcOPzZp0iQuvvjifXq9IiIiIiIiIrIjy/FY25tlXV92n9c/NVyLYK6bcGo9pp3CDSVKwWUZ1xx9ttPhpucLtA2V1j2dWmXyyflRjm8yqdjwEHVPLCGU7wWgUD2TnrkfpVA/t2zj747teAzmLZoqo0yuixMO7CJA9b1SB2pFMzQdDaHyrAsrMp6UPURdvnw55557Lj09PcOf7vi+X+5hduu2227jpJNOYtOmTbS1tXHcccdx5plnMmPGDHp6erjvvvvI5XIABINBfvWrX+33mqTBYJAlS5Zw9tlnk8vlKBQKfPKTn+Taa6/l1FNPpb6+nqGhIZ588kna2tqGz4tEItx2221EIpH9Gl9ERERERERESvZ7/VPPIZjvIZxaR6AwgBeKYyeawdhFiLgP2tMuP3q+yJMbS01klWGDRcdEOG9GiGT/36h/+H+JDpaav+xYA31HLyQ98Yyy1rA7RdsjVbBpqYoxsTZOaFdLIGwJUJMN0DQHQrGdHydykCtriNre3s4555zDwMDA8GPhcJgjjjiCmpqa/ZouvzcmTpzIAw88wCWXXMLy5cvxfZ+HHnqIhx56aJvjGhoaWLx4Meecc05Zxj355JN58MEH+fCHPzzckbpp0yZ++9vf7vT4adOmccstt3DaaaeVZXwRERERERGRw91+rX/qe6XO0/QGAoV+vGAEO9kMRvl2l8/aPr9YUeT3qywcDwIGXDgzzIfnRqi1NlL/1GKSnaVNsN1gjIFZ72dwxoX4gQPXfJW3XLKWw6SaGK3VcXbVgIprQ6Yb4nXQNBfC5dtcS2S8KWuq+a1vfYuBgQEMw6CpqYnvfOc7XHTRRUSjB76Ne/bs2Sxbtow77riD22+/nRUrVtDV1UV1dTXTp0/noosu4iMf+Qj19fVlHfekk05ixYoV/PGPf+QPf/gDzzzzDBs3biSTyZBIJGhqauKEE07gwgsv5L3vfS+hkBZZFhEREREREdlfpfVP86zpzuDD3q1/6vsEigOEUusJ5brwAyHseCOY5QtPAZ5ot/mfZwv05kszdhe0BPnE/AhTo1nqVt5M1dq7MHwX3zAZmnou/bM/iBupLmsNe5IpOFiOx9S6BM2V0Z2vXOD7kO8HpwiVrVA/EyLJA1qnyIFW1hD17rvvBiAUCnHfffdx9NFHl/Pyey0cDnPZZZdx2WWX7fM1pk6dutfLEQSDQS666CIuuuiifR5XREREREREREZmf9Y/Na00ofQGQpmNgI8drwezvA1PvTmP7z1X4PH20tT91qTBPxwf5ZQmqHr9Tmpf/SUBJwtAtmkBPXMvx66YVNYaRiKdd3B9j2kNCRqSkZ0HqFYOcn0QqyltIFXRAuaBWWJAZCyVfTq/YRicddZZYx6gioiIiIiIiMihL1t0WL0P658aToFQpoNwZgOGXcCJ1eIHyzuT1vV8/rzG5mcvFMg5pan775sd5kNHh6nrfpz6+39OKNcFQLFyGj3HfJR8w3FlrWGkBrM2ZgBm1CepTYR3PMBzINNb6s6tnwU1U7T+qRxWyhqiVldX09vby5QpU8p5WRERERERERGRHezT+qeeTSjbSTi1noCVwolU4VXUlr22tYMuNzxd4JU+F4DZdQGuXhDlSGMdjUt/QKx/JQBOtJa+oz5MavLZZV17dcR86M9aREImU+sSVMe368L1fSgMljpQK5qhdjrEy//1EhnvyhqiTp8+nd7eXvr7+8t5WRERERERERGRYVuvf+r5I1z/1HMJ5ntK4WmhDy+cxEq2svM56/uu6PjcuqLIr1dauD7Eg3D5sVEumGZSv+Y31K28HcN38AIRBma+h4EjLip7B+xIeR7054okI0Gm1iWoiG4XE9l5yPZCtApaji2tf1rmdWJFDhZlDVHf+973smzZMh5++GEcxyEYLOvlRUREREREROQwZzkebb1Z2vqyJMJBKmN7WL90u02jvEAIO9k8Kl2fz3U6/PczeTZmSnurnDYxyD8eH6XF7aD58RuIDqwCINNyCt3zPokbqyt7DSPledCbLVATCzO1PkE8vNXXw3NK4SlA7QyonQrhxJjUKTJelDXl/NjHPsb3vvc91q9fzze/+U2uueaacl5eRERERERERA5je7v+qWmlCKXbR3XTKIChosePni9yb5sNQH3M4B9PiHLahADVa/5E3cs3Y3oWbjBBz7yPk550Vtk7YPeG4/oM5Io0JKNMro0TDW21MVRhEIoZSDaWAtR43ZjWKjJelDVEraqq4ne/+x3nnnsuX/va1/A8j3/9138lFCr/G5SIiIiIiIiIHD4GcxYrO9MM5fa8/qnh5AllNpY2jXIKONHybxoF4Ps+97XZ3PR8kZTlYwAXzgzxkXlRqqwumh67kXjf3wDINs6ne/5ncGL1Za9jb9iOx2DeorEiyuS6OOHA5gDVKZQ2jgonofkYqJwAAeU5IluUNURdsmQJAFdddRXf+MY3+PrXv86PfvQj3vnOdzJ37lyqqqr2vEbJZpdddlk5SxMRERERERGRg9RgzmLFxhR5y939+qfDm0atI2ClcaLVeNHR2QSpI+3x38/keb6rtHHUtCqTzy6IcnRdgMp1f6XhpZ9iugW8QJSeuR8lNfXcMe/oLNoeqYJNS1WMibVxQqYBngu5vtJ/a6dBzVSIJMe0TpHxqKwh6qJFi7Z5I/N9n66uLv73f/93r65jGIZCVBERERERERHZJkBtqtxFN+kB2jQKwPF8fr3S4tYVRSwXwgH48JwI750dJlLso2npd0l0PwdAvm4Oncf/E06iuex17K285ZK1HCbVxGitjhMwgUIKCkOQaIC6GaX/auq+yE6Vfecn3/dH9JiIiIiIiIiIyO7sMUA9gJtGAbzc63Dj0wXWDnkAHN8U4DMnxmhNGlS0P0TDizcRsLN4Zoi+oxcyOONCMMw9XHX0ZQoOluMxtS5BU0UU0ytCuhdCsTem7gfDY12myLhW1hB14cKF5byciIiIiIiIiBymBrIWL29KUdhFgFraNGoDocwmgFHbNAoga/v87MUCf1pt4wNVEYOPHxfhLVNDBK0hGp/6PslNSwEoVM+k84SrsSsmjUoteyudd3B9j2kNCRoSIYx8D7g2VE0qTd+PVo51iSIHhbKGqIsXLy7n5URERERERETkMLR1gNq4XYBa2jSqg3CmfVQ3jdrisXab7z1boC9fmmX71qkhPj4/QlXEJLHxCRqXf4+glcI3gvTNvoSBme8Fc3Q6YfeG78NQzsYMwIz6JLXBIqS6IV4LzUdAohHMse+SFTlYlH06v4iIiIiIiIjIvtplgOo5hLKbDsimUQA9OY/vP1vg8Q4HgNakyWdOjHJ8cxDTytDwzE1Utj8EQLFyKp3HX41VPX3U6hkp34ds0SFvOyQjISZXBal2eoAINBwFNZMhGBnrMkUOOgpRRURERERERGRc2FWAalopIoNrCGa78MKJUds0CsD1fP70ms3iFwvkHAgY8P6jwlx6dIRI0CDe9SxNz/83wUI/PiYDs95L/5GX4AdGZymBkdo6PE2Eg0yvi1EbyBH2s1DRAnXTIVYzpjWKHMwUooqIiIiIiIjImBvIWqzYlKK4dYDqe4SynYQHX8N0CtiJRjBHL8pYO+jyX08XWNnnAnBUXYB/WhBlWnUAw87RsPxnVLXdDYCVnEDn8VdTrD1y1OoZiW06T8MmMyp9aoIZwqYJkSqomVYKUTV1X2S/KEQVERERERERkTG1swDVcAqEh9YSTq/HC8Wwk82jNr7r+fz6VYslLxWxPYiH4KPzolxwRAjTMIj1vkTTczcSynWV6p3x9/Qd9eFRXYt1T4bDU8umMmAxMWZTHQ0QilVCxWRI1EO0GgKKfkTKoaz/kpYsWVK2a1122WVlu5aIiIiIiIiIjE87C1AD+V4ig68TLPRhx+vxA6O3hmd72uX6Jwu8vLn79JTWIJ85MUp93MRwi9S9vISaNXcCYMeb6Jr/GfIN80atnj3xfcgUHex8miqzyMS4QVVlFeGqqZBoKE3ZD4bHrD6RQ1VZQ9RFixZhlGFNEsMwFKKKiIiIiIiIHOJ2CFA9h3B6A+GhtYCHlWwBY3SmoXu+zx9X2/z0hQJFF+JB+OTxUd4+LYRhGET6X6X5uRsIZ9oBGJrydnrmfhQ/FB+VevbE9yGby+LlBkkGXGprqqiqm0a4urUUnIZiY1KXyOGi7D3dvu/v1fGGYez1OSIiIiIiIiJycOvfvIlU0S4FqKaVJjy4hlB2E260Gi+UGLWxu7Me33kqz/Ndpe7T4xoD/MvJMZoSJoZrU/vq7dSs+g0GHk60lq75V5FrOnHU6tkd37UpZAZx8hlisRi1EyZQ3TSZSLIOIskxqUnkcFTWEHXhwoUjOs7zPIaGhnjppZdYu3YtANFolPe9732YWuhYRERERERE5JC2TYCaDBPKbCQ8uAbTyWEnmkZt8yjf9/nrWpsfPl8gZ0MkAB87NsqFM0trn0YGX6PpuRuJpNoASE38O3rmfQIvfIDDSs/FtDLks0MUXYgma2mYfBS1Dc1EEtVQhlnAIrJ3yvqutHjx4r0+55lnnuEzn/kMS5cupbOzk1//+tdUVlaWsywRERERERERGSe2DlCbYhDuf3WrzaNaRm/cvMcNTxd4cqMDwNF1AT53SpSJFQEChQHqXl5C5fr7MPBxwpX0HPspMhNOG7V6duB7mHYWs5gma7lkjTjh2lk0N7dSX99IJBQ6cLWIyA7GfIu2E088kUceeYTzzz+fe++9l8suu4w//OEPY12WiIiIiIiIiJTZ1gFqSzBLpGfNAdk86uH1Nv/9TIG05RMy4bJjIrzvyDABHKpX30ntq7cTcPJAqfu095iP4UaqR62eYb6P6eQwrTS+55H2IqRCrcRampjQ1ExjVZJwUDN2RcaDMQ9RAQKBAD/96U854ogj+NOf/sTvfvc7LrroorEuS0RERERERETKZEuAahWLTKSXcO/r4I/u5lGposf/PFvgofWl7tMZ1SZfOCXGtCqTRNfT1L/0U8LZjQAUqmfSM+9KCrVHjUotWzNci0BxEMN1cEMx+gONDEVqSFTVM62+msaKqMJTkXFmXISoABMnTuS0007jwQcfZPHixQpRRURERERERA4RWwJUJzfEJKedULYTN1I5qmuNLtto819PFegv+JgGXHJ0mEuPjhDPtdOw9Cckup8DwInU0DtnEelJZ41amLs108oQsNJYsUb6zVrSgQoqkpUcWRunIRlReCoyTo2bEBVgxowZPPjgg7zwwgtjXYqIiIiIiIiIlEF/1uLljkFIb2KyvWHz5lGNo7Z5VNb2uen5Ane/bgMwqdLkCyfHOKoiT+2KJVSv/TOG7+GZQQZnvIv+We/HD8VHpZbtBQr9GK5Dd2w6A5EWquJRjlZ4KnJQGFchaqFQAKC7u3uMKxERERERERGR/dWftXhlQzfBgddp9jrxAtFR3TxqeZfDd5bl6cr5GMBFR4b5yNwgje1/pW7ZrQSsFACZ5lPonXs5drJ11GrZhu8RzPWQ84J0R48gWj2BObVxTdsXOYiMmxDV8zweeeQRAKqqqsa4GhERERERERHZH/1Zi1Wvv05kYA0NRho7VocfjI7KWAXH539fLPKHVRYAzQmDfzk5xinGyzQ8+mMiqTYAihWT6T3mCnKN80eljp3yHEh10u1X4NQfyeSmFibUxIiGAgeuBhHZb+MmRP3yl7/M+vXrMQyD448/fqzLEREREREREZF91J/O8fqqFUQH11IVC2DFRm/zqJd7Ha5fVqA97QFw/owQn5o1xKRXv0fFxscBcEMJ+mZ/iKFp54F54MJLr5inONRFPt5M5eRjmNBYR2U0dMDGF5HyKWuIun79+hEf6zgOfX19LF++nJtvvpmlS5cOP7dw4cJyliUiIiIiIiIiB0h/Xy/rVr9AOL2JRFUdzihtHmW5Prf8rcivVlp4PtTFDD5/gsFbUr+h5uHfYXo2PiZD095B3+wP4kUO3KxX34d8ehC3MESkcRYzps2hrjKBYRgHrAYRKa+yhqhTp07d7zeE8847j4svvrhMFYmIiIiIiIjIAeH7DHS20bH6BQLFDLG6CXijtHnUmgGXby/L8/pgqfv0nMlBvtyyjIl/+zmhQh8Aufp59BxzJVbV1FGpYVfyRZdiuptkyKB21onUTTyCYHDcTAQWkX00Kv+Kfd/f63NM0+STn/wk//mf/zkKFYmIiIiIiIjIqLHzDLa/yqa1L+MQJdkwZVSGcT2fO16xuHVFEceDqojBtUe187bu/yX2wspSKfEmeuZ+lGzLm+AAdn5ajkcqXyBp9zOhtpraqfOI1k44YOOLyOgqa4g6efLkEXeihkIhKisrmTp1KieffDIf+MAHmDx5cjnLEREREREREZHR5LkUBjpIb1xFd3cnhVAdlZWjM31/fcrl+ifzrOwvdZ+e15Lha/Ff0rDy/lIpgSj9R76fwRnvwg+ER6WGnXFdn6G8jeE7TDAGqJs0kcTEuRCrOWA1iMjoK2uI2tbWVs7LiYiIiIiIiMg45Ps+qf5uhjpWke7dQM4LEoi3UhkfnU2THt1gc92TeYouVIdsfjDxPk7p/g3mQB6A1KSz6D16IW6sflTG3xnfh3TBwXIcaiM+LcEsFU2zMBpmQzh+wOoQkQNDi3KIiIiIiIiIyIgUHZeBoRT9Ha9R7FmL59qEKxqpjkZhFGbO+35p+v7PXiwCPlfWLuef/FuIbeoEoFAzi55jrqRQO7v8g+9GvuiSsRwqokGmVECNaRGoPwrqjoDA6ATJIjK2FKKKiIiIiIiIyC75vk+q4NA7lKO/az1e3+vE3BTxZANmLDFq41quz41PF7i3zaaZPhZX/y9H5ZYD4ERq6J2ziPSks8AwR62GHWpyPFIFi3AwwNS6OHVmmogJ1M+B6ilgHrhaROTAUogqIiIiIiIiIjuwXY+BrMWmoQJD/V0Eh9ZR7fQSiSXxolNGddOmwYLH1x7L87del3MDT3Nj9CdECxk8M8jgjHfRP+v9+KEDN2V+y7qnGNBcGaWpIkK82AuhODQeBRVNB6wWERkbClFFREREREREZFi6YNOXKdI5VCSdSZHMb6TJ7iQc8HCSzXjm6E5XXzfk8uVHcgxmC1wXvpUPmPeDC4XqmXSe+C/YyQO34/02654mIjRXxagM+RjZLojXlwLUWPUBq0dExs5eh6jr168fjTp2MHny5AMyjoiIiIiIiMjhznE9BnI2XakCvekiBdui1u1narGDsD2EE63BOQCdn09vcvjGEzmmOOu4I/o/TGUjAP0z30PfUR+CUQ5wt5YrOmQtt7TuaV0lNfEwATcPmV6ongQNsyEUO2D1iMjY2usQderUqRij2LIPYBgGjuOM6hgiIiIiIiIih7ts0aE/a9ExmCeVtzEMgzoyTLDbCeW68IJRrGTrqE7d3+KPqy2+/1yehebd/L/I7YRwcKK1dB5/NfnG40Z9/C0sx2MobxENBZlaF6e+IkI4YEIhBcU01M/UBlIih6F9ns7v+3456xARERERERGRA8D1fAZzFl3pAj3pInnLJR4O0hSDaHY94Uw7eA52vP6AdH66ns9Nzxd5dHUP/xu6ibMCLwCQaT6J7vmfwY1UjXoN8Ma6p4YJLVUxmiqjxMOB0pPZXvA9aJ5b2kDqAITKIjK+7HWIOnny5FHvRBURERERERGR8spbLn3ZIpuGCgzmbMCnMhqiNhoklOsi3NNGwBrCjtYcsE2bspbPvy/NEet6jrsjN9FgDOGZIXrnfpShaecfmLDSh3TRoWC71CbCNFdGqYqFSkP7HqQ7IZTQBlIih7m9DlHb2tpGoQwRERERERERKTfPK3VX9qSLdKULZIsOsVCQ+kSYYMAkUBgg3NtGMNd9QKfuA2zKeHz9kSHen7udK8J3AVCsnELniZ/Dqpx6QGoo2C7pgk08HOSIxiS1iTBBc/Prd+1SgJpohMbZ2kBK5DC3z9P5RURERERERGR8KtguAzmLjYN5BrI2rl/qOm2timEYBoaTJzSwgXC6HfwDN3V/ixW9DosfXcMN/v8wN9gGwOC08+mdezl+IDLq4zuuTypvY5owsSZOY0WUaMh84wA7D9k+bSAlIsMUooqIiIiIiIgcAnzfJ1Vw6E0X2ZQqkC3ahAMBahNhQoHNAaHnEsp2ER468FP3t7h/rcX6Z//C7YElxM0idqiCnuM/S7bl5FEf2/chXXCwHIe6ZJSWqigV0e2ikcIQFDNbbSCl6EREFKKKiIiIiIiIHNRs12Mga7FpqEBftojleFREQjRXxjC3mpofKAwQTrURzHbhhWIHdOo+gOf7/Gp5H8e//gM+EXwKgHT9sfSccDVurG7Uxy9YLumiTUUkxOS6CmrjEQJbNZ/iWpDtgWAMWuZB1SRtICUiww5oiJrJZEin01RUVJBMJg/k0CIiIiIiIiKHlEzRoS9TZNNggaG8RdA0qYyFiCYD2xxnOHnCqQ2EMu3gu9iJRjAPbE9VwfG589HnuHzwu0wI9OESoO/oyxia+W4wzD1fYD84rs9g3iIUMJlUk6CxMkIkuNWYvg/5fnCKUDkBaqdDtGpUaxKRg8+ovmuuW7eOH//4xzz44IM8//zzWJY1/Fw4HGb+/PmcffbZXHnllUyePHk0SxERERERERE56Lmez0DOojtVoDtdpGC7JMJBmipjBMztuiY9uzR1P7WOgJUak6n7AH1ZmzUP3sKX7N8TMHwGwy2k3vR5ijUzR3Vc34dU3sb2POqTEZqrolREtotB7Fxp7dNoNbQcBRUtYI5uqCsiB6dRCVEty+Lzn/883//+9/E8DyitzbK1YrHIsmXLWLZsGddddx3/+I//yHXXXUc4HB6NkkREREREREQOWnnLpS9bZONgnqG8jYFBRTRIXWInmzD5HsF8D+GhdQQK/Xjh+AGfur9Fx6aN1C67nktZDQa0NZ6Dc9In8IOju1FTvuiSsRwqokGmVSeoiYW3zUY9F3K9paS1fiZUT4HwgQ+YReTgUfYQNZ/P89a3vpWlS5fuEJxub8vzruvy3e9+l6effpr77ruPaDRa7rJEREREREREDiqe5zOUt+lOF+hKFclZLvFQgPpEhGBg592SgcIgofR6QrlN+GYIO9kERmCnx462jS8+wAlrfkiFkSdDjPVzPkVo5t+N6pi24zGUtwmHTKbWxamviBDe/mtVSJU2j0o2Qu0MSNRr7VMR2aOyh6hXXHEFTzzxBMbmN6A5c+Zw+eWXc9pppzF16lQSiQTZbJa2tjaeeOIJFi9ezEsvvYTv+yxdupQrrriCW265pdxliYiIiIiIiBwUCrbLQM5i42CegayN6/tURUNUV4WGf9fenmHnCKfbCWXbMTwHJ1qPHwgd4Mo3s7LkH/shZ6YeAgNWBmbhnP55ItXNozak55Wm7nu+T0NFhJbqKInwdpHH8MZRUWg+Bqomwlh9jUTkoFPWEPWpp57itttuwzAMTNPk+uuv5zOf+cwOb/KJRILGxkZOOukkPvOZz/A///M//PM//zOu63Lbbbdx1VVXsWDBgnKWJiIiIiIiIjJu+b5PquDQky7QmSqSLdpEAgFqE2FCu+g6BTBci2B2E+HUegJ2ZszWPd0i0PcqySeuZ6bbiesb3F35XqafeSmR4OhtyZItOORsh6pYmJbqKDWx8LaNpdo4SkTKoKzvYlt3kF5//fV89rOf3eM5hmFw1VVX4fs+//RP/wTAkiVLFKKKiIiIiIjIIc92PQayFpuGCvRli9iuR0UkRHNlDHN3U8w9t7TuaWo9gWIfbig5ZuueAuB7xFb+juZXbyGIy0a/jgenfpYFxx23y+7Z/WU5HkN5i1goyLT6JPUVEULbb65l5yHbWwpNtXGUiOyHsoaoDz30EACtra0jClC3dtVVV/Gd73yHjRs38uCDD5azLBEREREREZFxwfd9spZLpuAwmLPoz1qkCzbBgElVLEQkuIf1S32fQHGAUGo9oVwXXiCEnWges3VPAUKZDiqf/T61Ay8CcLd3MqkT/5GTJteMynieB0M5C9+AlqooTZUx4uHtXv/WG0fVzoDaado4SkT2S1lD1I6ODgzD4PTTT9/rc7ecd8cdd7Bx48ZyliUiIiIiIiIyZgq2S6bokM7b9GYtsgWHoutiGibxUICmyhiB7Tsod8K0MoQy7YQyHeB72PF6MMduTU/TSlP9yu1Ur/0/Arjk/Aj/ZS7kpLPOY37NKEzf9yFTdMjbLjXxEM1VMapjoR2bb4tpyA9CohHqtHGUiJRHWd/V8vk8AMlkcp/O33LeluuIiIiIiIiIHGxczydTcEgXbfoyFqmCTd5y8X2IhQIkIkHqQpERX89wi4Qymwin12M4OZxoLX4wOoqvYE/12FS8/meqXrmDqJcF4EH3WH6RXMSVZ86gJjoK0+V96M9ahIMmMxoS1CUjBLcPnl0bMt0QikLT3NLGUcFw+WsRkcNSWUPU+vp6Nm7cyGuvvbZP569Zs2b4OiIiIiIiIiIHA9/3yVmlbtOhXCk4zdoOjucRNgPEwwEqK0O7X+N0ZzyXYL6b8FAbgeIQbqQCL9k6Oi9iJHyf+MbHSb6wmCqrC4BXvEl8z/wQRxy7gH+eHtox2CzLuDCQs4iFTabVJ6mIbhdl+D7kB0rrn1ZNgJppEKsufx0iclgra4g6Z84cOjo6eOyxx1i7di3Tpk0b8blr167l0UcfxTAM5syZU86yRERERERERMqq6JTWNU0XbHozFpmiQ8H2CBgGsXCA2niYUGAfOzJ9n0Chj3B6A8FcN14wgp1sBmPsNkSK9K0k8vxPacqsBKDbr+YHvJ/Y0W/hk0fEiARHabr85g7UaGgXAerWG0e1zoeKZjDHbn1YETl0lTVEPe+887jnnntwXZdLL72Uv/71r1RUVOzxvGw2y4c+9CEcx8EwDC644IJyliUiIiIiIiKyX1zPJ1N0yBQd+rNFhnI2edvF832iwSCJcJDauLnfO9GbVopQegOhzEYwDOx4A5ijsL7oCAWyXQSe+zmT+x4FIO+HWexfwODMi3j37CriodFda7Q/axEJmUxv2C5A3bJxlKeNo0TkwCjrO/FHP/pR/uM//oOuri6WLVvGiSeeyPXXX88FF1yAae74iZnv+/zf//0fn/vc51i1ahWGYdDU1MTll19ezrJERERERERE9lreckkXbIbyNn1Zi6zl4Dg+wYBBPBykIRka0YZQI2E4BUKZDsKZDRhOYczXPTXtLO4Lv2Ri+58IY+P5Bn/wT2fllEt5+9xWKiOjv1HTQKYUoM7YPkAd3jiqAeqO0MZRInJAlDVETSQS/PjHP+bd7343nuexevVq3v3ud1NfX89JJ53ElClTSCQSZLNZ1q9fz1NPPUVPTw9QClSDwSA//elPicf16ZGIiIiIiIiMDd/36RjMs7Y3S85yMQ2IhYLUxPZjiv6ueA6hXBfhoXWY1hBupAovWVveMfaqHhfr5buYtOY2Kv00AEu9o3msdRFnHjebY0Zj06idGMhYhEMm07eewu9akOnRxlEiMibKPifgggsu4NZbb+WKK64gk8ng+z49PT3cddddOxzr+/7w7WQyyU9/+lPOO++8stViWRa//OUvuf3221mxYgVdXV3U1NQwbdo0LrroIhYtWlS2TaweeughzjrrrH0+f/HixSxatKgstYiIiIiIiMi+cVyPtb1Z1vZmiYeDtFRG93uK/s4YrlVa9zS1gWCxHzcYw062jl1Hpe+TXbuMxhWLmel2ALDGa+Gv9Zdx7PGn8q7kgVtndCBrEdocoFbGgqWp+/l+cCyobIXa6do4SkQOuFFZWOUDH/gACxYs4Gtf+xq/+tWvKBaL2wSmW4tEInzgAx/gmmuuYfr06WWrYeXKlVxyySUsX758m8c7Ozvp7Oxk6dKlXH/99SxevLiswe2+am5uHusSREREREREDmt5y2V1d5qNg3nqEhGiofIHh4aTJ5jrJpTpIGilcANhrHjTmG6GlNr0GvHnf8px1t8A6PMr+Evl+5h44vm8tSpyQGsZyFqEglsFqIUhKKQgXg9N0yDZBDtZLlBEZLTtU4h6+eWX85GPfITTTz99l8dMnz6dm2++me9+97s88cQTPP/88/T09JDJZEgmkzQ0NDB//nxOPfVUqqqq9vkF7Ex7ezvnnHMOGzduBMAwDM444wxmzJhBT08P9913H/l8nu7ubt71rndx9913c/bZZ+/XmBMmTOBTn/rUiI+/5557WL16NQBNTU285S1v2a/xRUREREREZN8N5WxWdafpy1g0VkTLPm3ftNIEc12EMhsx7RxeOI6VaAZj7ALB1EAP9tM3c1L2YUzDp+gH+WvsPJInXszJ9ZUHvJ6BrEUoUApQq4I2DHZCOAnNx0DlBE3dF5ExtU8h6s9//nNuvvlmpkyZwsKFC/nwhz+8yy7Sqqoq3vGOd/COd7xjvwrdGx/84AeHA9QpU6Zw5513cuyxxw4/39vby8UXX8z999+Pbdu8733vY82aNVRXV+/zmDNnzuR73/veiI51XZeJEycO37/00ksJBsdut0UREREREZHDWXeqwKquNAXbo6UqilmuKfW+T6A4SDDbSSjXieEUcSOV2MmWMd0IKZ3N0fvUr3nz4B+JG0Uw4LHQmygc9xGOmtA6JjUNZu1SgFoXpcruBccoTduvmQKR5JjUJCKytf36yKutrY1rr72WmTNncsYZZ/Czn/2MdDpdrtr2yV133cWjjz4KQDgc5k9/+tM2ASpAfX09d95553Dw29/fz7e//e0DVuNf//pXOjs7h+8vXLjwgI0tIiIiIiIiJZ7ns64vy0sbh3A9aKosU4DquQRzPUR7XiDW9Szh9IbSmqcVrXjh5JgFqNmiw0uP/x8T77mStw39mrhR5GVzFg/MvY6m8/+VKWMYoAZNn+nxAlVOHyQbYOICaDpaAaqIjBv7FKKecMIJw2uc+r6P7/s8/vjjXHHFFTQ3N/OhD32Ie+65Z5froI6m73//+8O3Fy5cyDHHHLPT4xKJBNdee+3w/R/96Ec4jjPq9QHcfPPNw7fnz5/PvHnzDsi4IiIiIiIiUmI5Hqu60qzclCIeClKb2P+p4oZrEcxuIt7zPLGe5wjme3CjVdjJZvxQvAxV75uC4/PUM08RveszXNTzQxqNQTYZjTxyxL8QvOA7TDpizpjVNpiziXhZZkQGqapIQuv80p9E3Zh264qIbG+fQtSnn36aFStW8PnPf354WvqWMDWfz3P77bfzjne8g0mTJvGlL32JV155paxF70omk+H+++8fvv+Rj3xkt8e/5z3vIZksfarV39/PI488Mqr1AQwODvLHP/5x+L66UEVERERERA6sbNHh5Y1DrO3LUpeMkIzs3/JqhlMglF5PrOsZ4j0vYFgp7FgDTqIJP3BgN2ba2mDB48HnX2Xwz9dwafu1zDbWkSbOsomLSJ9/Ey1z/w5jDDdpGkpniBc2Mbk6SOXkY0vdp1UTxnSTLRGRXdnnd8ujjjqK//iP/2DdunXce++9fOhDHyKRSABvBKobN27k29/+NnPnzuWkk07iBz/4Af39/WUrfntPPPEExWIRKHWaLliwYLfHR6NR3vSmNw3ff+CBB0atti1+9atfUSgUAAiFQnzwgx8c9TFFRERERESkpD9r8VLHEJ2pAi2VMSLBfQ/sTCtNeHAN8c6nifa+jOE7WIkm3Fg9mGOz74Xv+7zcY3Pnw0+Rv+vLXLnunzmd53EI8EL9+Ww69yfUnvhejLHcpMlzyfdtJGIP0TplNtUzT4P6IyAUHbuaRET2YL/f1Q3D4JxzzuGcc84hl8vxm9/8hltuuYUHH3wQz/OGp/Q/++yzPPvss1x99dWcf/75LFy4kPPPP59AoHyfMG3d8XrMMceMaLOm448/nnvvvXeH80fL1lP5zzvvPBoaGkZ9TBERERERkcOd7/tsGiqwuiuN4/m0VsUw9mW6+E43i6oY882i8o7PQ20Fhl59jL8v/pG/N9eCCS4Ga6pOxTz+w8SrJu75QqNp89cul0nhxhqYdMQcahonaNq+iBwUyvrRWDwe57LLLuOyyy6jo6ODW265hVtvvZWXX355OEy1LIs//OEP/OEPf6C+vp4PfvCDXHbZZcyfP3+/x3/11VeHb0+ZMmVE50yePHn49sqVK/e7ht1ZvXo1TzzxxPB9TeUXEREREREZfa7n09ab5fXeLLFQgNpEaO8v4rkEC/0Es5sI5nswPBcnUokfqyt/wXuhPeVy96oMifX3sZD/Y4rZDSZYhNnY8hb8uRdhJJo58DuWbMu0swQLg/S7UYp1c5kxfSb1VYkxrkpEZORGbX7BhAkT+OIXv8gXv/hFnn32WW6++WbuuOMOent7hwPVnp4evvvd7/Ld736XOXPmsGjRIi699FKampr2acy+vr7h2yO9RnNz8/Dt0VxqAGDJkiXDt+vq6jj//PP36vxisTi8XAFAKpUCwLZtbNsuT5EiIiIiMPyzhX7GEJGDXdF2eb03y8ahPFXREPGwgeeOfFNhw7UwC/2Es5sIFPrxMbGiVW+sdeod+HjS9Xye3Ojw0OoBju2/m88F/0q9Wfr9MGcmGZh2AbkjLsCNVI1ZjVsYrkUwP4AfCLExNAm7upWZExupjof1PeYwp581ZLwY6d/BA7JIywknnMAJJ5zAf/3Xf3HXXXexZMkS/vznP2NZ1nCg+re//Y3Pfe5zfPGLX+Rtb3sbf/7zn/d6nEwmM3w7FouN6Jytj9v6/HLzfZ9bb711+P4HP/hBwuG9W4PmW9/6Fl/72td2ePzBBx8kHh+7nR5FRETk0LVl2SMRkUNB935fYcsmUbnNfw6slAVLuw3WdvXxPu9ubgo8SCJUarQZCtTT1nwuG+rOxA1EoNsDBg54jTu35XffXqCXp14fy1pkvNHPGjLWcrmRvZ8f0JWug8EgF154IRdeeCGDg4Pcfvvt3HLLLTz55JMYhoHv+ziOw1/+8pd9uv6WDZuAEQeUkcgbOyXm8/l9GnckHn74Ydra2obv78tU/i996UtcffXVw/dTqRSTJk3irLPOoq5ubKeQiIiIyKHFtm3uvfde3vrWtxIK7cO0VxGRMdabsXitO03OcmhIRgmYu19303AKmFYG004TzPdi2nkMz8ILRnEjlWCMzY7xvu/zt16XP79m09PxOh8L/JkLzScIBj0AMslpDM16D+nWNxMxAxwxJlVuxfcxrRQBO4sbqcWqnEyvVwGGwayWShqSkT1fQw4L+llDxostM733ZGy2CwSqq6v55Cc/ybvf/W6++tWv8uMf/3g4SN1X0egbO/lZljWic7aeHj/S7tV9sfWGUnPnzuWEE07Y62tEIpFtQt8tQqGQ3nBERERkVOjnDBE52HieT8dgjte6MxiYtFQnd76BlOdi2hkCdoZAvpdAcQjTKTXWeKEYXqwSL1BqzhmL+DRn+9zfZvPH1UWaMyv4ROBP/F34heHnM/XHMjTrPeQa5oNhjEmN2zPsHKHCAG4oiVU/BzvZQn/eB9Pn6JZKGiuje76IHHb0s4aMtZH+/RuTELVQKPD73/+eJUuWcP/99+O67r7tiridZDI5fHukXaVbH7f1+eWUy+X47W9/O3xfG0qJiIiIiIiUn+16rO3JsrYvS0UkSEV021+MDadAwEphWimCuR5MJ4fh2viBEF4ojh2pBMMco+pL2oZc/rja4oG2Imd4T3Nj8E8cFy7Nf/cxyUw4jYGZ76FYPeY9p8NMO0egOIRvhihWzcCqmIgfijOQtfBRgCoih4YDGqI+9NBDLFmyhN/+9rfD649u33n65je/eZ9Dxq2ntHd1dY3onM7OzuHbtbW1+zTunvzud78jnU4DEAgEuPTSS0dlHBERERERkcNV3nJZ1Z1m02CeukSEaCiwuds0TcAqdZsGrRTGcLdpHDdSjR8Y+w442/V5osPhj6stXu3J857Ao/w58GemBUu/13pmmNSUtzJ4xLuwEy1jXO1mvodppQlaGbxQDKtyCk68GTdaDcBA1sLzfY5qVYAqIoeGUQ9RX331VZYsWcIvfvELNmzYAOwYnE6dOpXLLruMyy67jOnTp+/zWEceeeTw7XXr1o3onPXr1w/fnj179j6PvTtbT+V/29veRkvLOPmmJyIiIiIicggYzFms6krTn7VojvlE7F7MzNDmtU1zGL6DHwjjBeN446DbdIvevMefX7P4yxobt5DmQ4H7+FnkbuqN0vp8bijJ4PQLGJp+AW6kemyL3cJzNi99UMQLV1CoPQon3oAXSgwfMpB7I0BtUoAqIoeIUQlR+/r6uOOOO1iyZAnPPPMMsGNwWlFRwXvf+14WLlzIGWecUZZxjzrqqOHbL730Eo7jEAzu/iU+99xzOz2/XNrb23nggQeG7y9atKjsY4iIiIiIiByuOgcyrO3YhJtPMd1MEcqkMZwCGAZuMIYTqwFz7LtNt9ad9bjjlSJ3v27T4PXyqeBfuCT6AHFKe3bYsQYGj3gXQ1Pehh8cvb079obhFAgUhzDwcMM1FGqOxInV4Qe23bdjIGfheh5HtVQpQBWRQ0rZQlTbtvnTn/7EkiVLuPvuu7FtG9g2PDVNk7PPPpuFCxdy0UUXlX0jp1NPPZVIJEKxWCSbzfLMM89wyimn7PL4YrHIk08+OXz/7LPPLms9ALfeeiueV9o1sbq6mgsvvLDsY4iIiIiIiBxWrBxufpDOzo1s2tRO0i1QGTZwg2HcYBw/Ug1l2Hej3DZlPO54ucg9bTa13gBfD/6a94YfJYgLQLFyKgMz30N6wulgjtk+0NswrQwBK4VvhnHiTTiJFpxoLZg7bmU1uFWA2lylAFVEDi37/a68dOlSlixZwq9+9SsGBweBHbtOjzzySBYuXMiHP/xhJkyYsL9D7lIymeScc87hrrvuAuDnP//5bkPUrdcqra2tLVtH7Na2nsr/gQ98gGhU30hERERERET2mu9DYRDSnVgD7XT19tOTtYnHKwlVNmGNk9BxZzrSHre/XOTeNpuIX+BTgf/jk9E/E93ceZqrn8fAzPeQazx+fIS/vrd5A64sfiiBVTkdO9GIF67aaX2O6zGQszEMn9ktlQpQReSQtE/fZdauXcstt9zCLbfcwuuvb94lcLvgtKamhosvvpiFCxdy0kkn7X+lI/QP//AP24Son/70p5kzZ84Ox+VyOa655prh+1deeeUep/7vraeeeoqVK1cO39dUfhERERERkb3kOpDrwxvqIDuwkVy+QK8bZcitoaY2SjA4DkLHXVifcrlthcWD623wPd4TeIQvhX9NrT8AQL52Nr1zPkqhrvxLy+0TzyZYHMJ0LZxwJYXao3HiDfih+E4Pt12PwZyN43nUJcNMrk3QUBHZ6bEiIge7fUoNZ8yYgWEYOwSnwWCQc889l4ULF/LOd76TcDhcliL3xvnnn8/pp5/Oo48+SrFY5IILLuDOO+9k3rx5w8f09fVxySWX8NprrwGlLtQvfOELO71eW1sb06ZNG76/ePHiEYehW3ehzpo1a7ddsSIiIiIiIrIVu4CX6SbbvY78UDcDBZchkrhGNZFQgLpkEHN87A+1g7Yhl1+sKPLwegcfOM18iW/Gb2OKuw58sONN9M75CJnW08ZF52lpvdNBANxoHYVkK260Dj+w89/pbdfbvPapT10yzKSaOHXJCAFz7F+LiMhoKUvr5bHHHsvChQu59NJLaWhoKMcl98ttt93GSSedxKZNm2hra+O4447jzDPPZMaMGfT09HDfffeRy+WAUvD7q1/9iurq6rLWYFkWd9xxx/D9hQsXlvX6IiIiIiIihyIvP0S2byPZ3jZSgwNkvBCFQCXRSJiKUIBgYPwGdWsGSuHpo+0OADONdq5P3s5x9vPgghtK0D/rAwxNfyd+YIw3u/J9TDtbWu80EMZJtGInmnGjtWDsPJ3eEp56vk99MsKEmhh1CYWnInJ42OcQtaGhgUsvvZSFCxdu0+U5HkycOJEHHniASy65hOXLl+P7Pg899BAPPfTQNsc1NDSwePFizjnnnLLX8Oc//5n+/n6gtKHWZZddVvYxREREREREDgWe65IZ6CbTu4FUzwYK+RxWMEkw2kwsEqRiHAenAKv6S+HpEx2l8LSeIa6r/i1nFx7AsD18I8DgtPPpn30xXrhybIv1XQLFFKadxwvFKVYfgRNrKNW1i65Y2/UYyFp4+DQkI7TWxKhPRDAVnorIYWSfQtQ//elPnHvuuQQC2+7G9+KLLw7fnjNnzg7PH0izZ89m2bJl3HHHHdx+++2sWLGCrq4uqqurmT59OhdddBEf+chHqK+vH5Xxt57Kf/bZZzNx4sRRGUdERERERORg5Hk+6WyOdP8mUl1tFFPdeK5PIF5DpK6BxDgPTgFe7nX4xQqLpzaVwtMoFt+ou5t3Ff5AsFAAINPyJnrnLMJOjt4myyNhuDaB4iCGa+NGqijUT8eJ1eMHY7s8x3Y9+rMWPtCQDDOhJk5dIqzwVEQOS/sUop5//vk7ffy4447DMAymTJkyvOHUWAqHw1x22WX71QU6derUHdZ+HYk777xzn8cUERERERE5FHmeT7roMDQ0yEB3B87AeozCEKFwlFhlE4Ex2FdjX/ytx+HWFUWe7XQBCBgeX2p8kg8Vbiea7QOgUD2TnrkfpVA/dyxLxXAKBIuD+IAba8BOtODE6sDc9XICllOatg/QUFGatl8bV3gqIoe3sm5HHwqFcBxHGyiJiIiIiIgI8EZwmspZ9PR2UxzoIJjpJEaBWLwSo3ISGGM3i3GkfN/nxW6XW1cUWd5dCk9NA/6hZRUft2+lYqi0cbEda6Dv6MtITzxzl2uLHgiGnSNYHMI3Q9iJVuxkK26kerc1KTwVEdm1soaozc3NtLe3k0wmy3lZEREREREROYgMB6d5m87BDIWhbgLpTVQ4A1QGPIyqarxg47jYmX5PfN/n+a5SePpSTyk8DZrw4YndfMq7jfrepwBwgzEGZr2fwRkX4gciY1avaWU2bxYVwaqcgp1oxgtX7fZrXXRcBnM2AI2VESZUx6hReCoiso2yhqizZ89mw4YNrFu3rpyXFRERERERkXGuYLvkLJds0aEzVSCTzWBke6gqdtHipQmEgriJWvxAhL1fMO3A832fpzc53LrC4pW+UngaMuE9U/JcFfwdLe13Y/guvmEyNPVc+md/sNTpOTbFYtoZgsU0XihGsWo6TqJ5j5tYDYenxhvhaW0ijHEQhNsiIgdaWUPU97///dx777089thj9PX1UVdXV87Li4iIiIiIyDhRsEuBabbo0p+1SBdt8paLYWWocvpotbuJeDm8UBQ33IRjjv8p+1usHXS54enCcHgaDsDfT4d/jN7DxLW/JuBkAcg0LaB37uXYFZPGplDfI2ClMa0MXihJoXYWTrwJL5TY7WkF22Uwb2EYBk1VESZUx6mJhxSeiojsRllD1EsvvZQbbriBV155hU996lPccccd5by8iIiIiIiIjAHf9ynYHpmiQ7Zo05+zyBRcCraLj08kECBJlnq7i2ihE8Mp4kaS2KGWg2LK/haO53PHyxa/eLmI40E0ABfMCPHx6qeY+toSQrkuAApV0+mdezn5huPGplDfJVBMYTo5vFAlhdqjcRKN+MHYbk/bEp6apkFLVYwJ1TGqFZ6KiIxIWUPUaDTKb37zG84991x+/etfk0qluPHGG5k1a1Y5hxEREREREZFR5Ps+edsthaYFh76sRbboUHQ8fB8iQZNYOEBVNEjIShHMdhDKdWG4Fk6kGj928M1KfG3A5TvL8qwZ9AB404Qg/2/GWo5Y/TNi618FwInW0nvUZaQnnzU2m2F5LoHiIAG3iBOuolA3AydWjx+M7va0vFUKTwMBhaciIvuqrCHqtddeC8CFF17ITTfdxF//+leOOuoo5s2bxwknnEBDQwOx2O4/GdvimmuuKWdpIiIiIiIisgueVwpNs0WHdMGhP7c5NLVdMAyiwQCxUJCauFkK3nyfQHGAUP9GgrkuDM/BiVbjx+rH+qXsNdv1ue3lIre/bOH60BLO8/VpKzil+BjJp0qbRnmBKAMz38PAEe/eY2A5KjyHYHEQw7VxIzXka44shaeB8C5PsV2PTMEh5zhEAwEm1sRorY5RFVN4KiKyL8oaon71q1/d4c3Y931efPFFXnzxxb26lkJUERERERGR0eF5PlnLIWe5pPI2/VmLvOVSdD0MIBoKkAgHqY1vt8mQ7xHI9xHKlMJT8HEj1WMTLJbB6n6X7zyVZ2hwgPcFnuXi+LPMc17CXOcA4GOSmvIW+o76EG609oDXZ7g2geIAhu/iROuxkxNwYvVg7vxXec/3S0F40SFgGFTGgkxrqKI6HiIZCSo8FRHZD2UNUaEUmo7ksd3RG7uIiIiIiEj5uFtC0+Lm0DRnkbccLNfHNCAaDJCIBKkNmjv/fcxzCRb6CWY6COa7S9eM1u62E3I8s1yf/1u+AWvtE3zLfIYFkVcxDR/szc8nJ5JpfRPpiWdhVU4+4PUZbpFAYRDwcWKNOMkJONFa2MXmXHnLJV2wcXyfRCTI9PoEdckIVbEQAVO/X4uIlENZQ9R/+7d/K+flREREREREZB84rkfWcslZDkM5m4GsTd5xsB0P0yitZ1oRDREJ7mFdT88lWOgllG4nWOjFNwK40Tr8QOjAvJBy8n3C6Q3k1zxOcP0TfN5fu81vxIXqmWRa3kSm9U3YFZPGpETDyRMsDOKbQZx4E3ZyAm60Bgxzh2Nt1yNdcMjbDtFQgIbKCE2VUarjI/j/KiIie00hqoiIiIiIyEHOdj1yRZeM5TCUtxjM2uQdF8f1MQ2DWChAVTRMOLhjGLdTnkMw30s4004g34dvBrFj9WAeZOGp7xMZXEVy41ISG5cSyXYMP+X6Bt0VRxOYdhrZllNw4o1jVqZp5wgUh/ADIayKiTiJCbiRKtiuK9j1StP1M0WHgGlQFQ8xvSFBTSJMMlL2iaYiIrIVvcuKiIiIiIgcZCzHI2eVwrTBnMVQ3iFvubieT9A0iIYC1MTChAIjDE03M1yLYL7UeRoo9OMFw9jxhl2uwTkueS6xvhUkNz5BovNJQvne4aeKfpDHvGNYV30yxy84jURlzRgWWpq2H8z14YeiWJXTsBNNeJGqHY7LWaUNv1zPIxkNMaMxQV2iNF3f1HR9EZED4iD6TigiIiIiInJ4Kjou2aJLtujQn7VIFx0KlovrewRNk3goSF0iTHAvQ9MtSmFeD6H0BoLWEG4wip1o2uUanOON4VrEu58nsWkpyc6nCFip4ecKRpT7nOO4213A8vBxfOzkWk6fOMYdtb5PoDiI6RawKqdgV0zCCye3OcR2PVJ5m4LjEQuZNFdFaayIUB3fi45iEREpG4WoIiIiIiIi40zBLgWmOculP2uRKtgULA8Pn5BZWtO0PhnZ702DDKdAMN9DOLUB0xrCC8WxEk1gjP/w1LRzxLueLk3V734W08kPP+eGK9lQvYAf9B3Pndk5FAnzlqkh/nt+lMrI2HZuGq5NMN+DF6ogX38sTrxpeNq+6/lkig6Zok0wYFIdCzGzOkZNPEQ8rF/fRUTG0qi+CxcKBe6++24ee+wxNmzYwMDAAK7rcv/9929znO/75POlb3ihUIhQ6CBbZ0dERERERGQ/FB2XdMEhU7AZyNmkCw5Fx8XzIBI0iYYCVFSUb6d1w8kTzHYTzrRj2mm8UBw72bLTDYzGE9PKkNy0lOTGx4n1LMf0nOHn7Fg92ZY30d/4Jn7QMYPfrnbxgbqYwZdPjHLKhLH/PTNQHMK0c9jJiVhV0/BCidLvw1um6/s+FZEgs5oqqEtEqIgGNV1fRGScGLUQ9Tvf+Q7f/va36evrG37M930MY8dvAP39/UyePJlCocDJJ5/ME088MVpliYiIiIiIjBsF26U7VWDDQJ5M0QF8IoEAsXCgtN7lTn5/2h+GnSOU6yKUbse0M7jhJHaiZYcNjMYTwymQ6HyKio5HiHc9s01waiUnkml9E5mWN1GsnsmLPS7/+VSejRkXgLdNC/GJ+VEqwmP8+jybUK4XLxijUD9389fcJFt0GMzbxMImrTVRGpJRquOhvV7LVkRERl/ZQ1TbtnnXu97F3XffDZSC0z2pq6tj4cKF3HTTTSxbtozXXnuNI444otyliYiIiIiIjAtbh6fpgkMyEqS5Mlr20BRKXacBK0WgMEAo141pZ3EildjJ1vEbnno2ie7nSbY/THLTMky3MPxUsWIymQmnk57wZuyKSQDkHZ+fPVfkD6stAOpjBv+0IMpJrWPffWpaKYJWBivejFU9Ay9cgev59KYLBEyY2ZiktTpGLDz+l1AQETmclT1E/eQnP8lf/vIXAKLRKAsXLuTss8/mtttu484779zleR/60Ie46aabALjrrru46qqryl2aiIiIiIjImNpZeNpaFd3pjL195nuYdoaAlSaQ6yFoDWE4BXzDwAslcSomlG+scvJdYr1/o6L9YZIbnyBgZ4afsuNNpCeeQXrCmVhVU7c5bXmXw38+laczW2rgecf0EB8/LkpizLtPXUL5HvxAmHztUdjJiWAGNnefWjRURJhen6QmER7bOkVEZETKGqI+++yzLF68GMMwmDBhAvfccw+zZ88G4JFHHtntuaeeeipVVVWkUikeffRRhagiIiIiInLIGO3w1HAtTCtNwEoRzPVg2hkM18IPhnGDcfxI9fjsOvV9ogOvkmx/mIqOxwgWB4afciI1pCecTnrimRRrZu1Qf872+ekLBf70mg1AQ9zg6gUxTmwZ+w2YTCtDoDiEk2imWDUNL1Jd6j5NlbpPZzVVMLEmTjioafsiIgeLsn53Wbx48fC6p7fccstwgDpSxx13HA8//DCvvPJKOcsSEREREREZE6MZnhp2rjRNvzhAMN+H6WTB9/GCMdxIJX5g/HY4hofaqOh4mIr2RwjluoYfd0NJMq2nkZ54Jvn6OWDsfIr7c50O//VUnq5cqfv0/BkhrjguSiI0xkGx7xLM9YIZpFh7FFbFBDBD6j4VETkElDVEffDBBwGYO3cuZ5555l6fP3HiRAA6OjrKWZaIiIiIiMgBNSrhqe9t7jZNE8iXpumbTgHPMPFCCex44y5Dx/EglNlIsuMRKtofIZJeP/y4F4iSaTmZzMQzyTbOB3Pn65j6vs/LfS6/e9XikQ2lzaWaEwb/tCDG8c1j331q2DmChUHceD3Fqhm40Rpcz6cvXSBgGMxqqmBSbVybRomIHKTK+p1m48aNGIbB/Pnz9+n8ZDIJQDabLWdZIiIiIiIiB0S5w9PSNP0UgeIQwXwPpp3F8Gy8QBg3lMCJ1IzPafqbBfK9VHQ8SkX7I0QHVw8/7plBck0nkp54JtmmBfjB6C6vYbk+D6+3+f0qi9UD3vDjF84M8bF5UWJj3n3qEcz3AVCsOQK7YjJ+IEym6DCk7lMRkUNGWUPUQqG0Y2I0uutvgLuTyZQWDt8SpoqIiIiIiBwMCrZLV6pA+/6Gp76P6eRKHaeF/s3T9HMAeKEYbqQaPzD2O87vjmmlSHY8TkX7w8T6VmBQmnLvGya5hmNJTziTbMspeOHd/97Xn/f482sWf15jM1AoXSNkwtlTQrx7VpgZNWPfdWs4BUL5PpxoHcXq6bix+uG1T4OmwZFNFUxU96mIyCGhrCFqQ0MDHR0ddHZ27tP5K1euHL6OiIiIiIjIeFeO8NRwCphOHtPOEMz1ELCGMJwivhkoTdNPjO9p+gB4LonuZ6ls+yuJrmcwfHf4qXzt0aQnnkFmwptxI9V7vNSqfpffr7J4aL2Ns7nxtC5m8M4jwpw/I0R1dBwEkr5PoNCP4dkUq2ZgVU7GD0bVfSoicggra4g6e/Zs2tvbWbp0Ka7rEgiM/Bv9hg0bWL58OYZhsGDBgnKWJSIiIiIiUlZbwtMNA3kyexOeejamnXsjNC0OYto5cAuYnocbjOCGEvjR2nE9TX+LYK6bynX3ULnuXkKFvuHHC1UzNgenp+PEG/d4Hcfzebzd4XerLF7ufSOAPaouwLtnhTl9UpCgOT6+HoZbJJjrw41UUqw7GifWiOuj7lMRkUNcWUPUc889l/vuu4/e3l6WLFnCRz7ykRGf+5WvfAXXdTEMg7e//e3lLEtERERERKQs9io89ZxSWOrkMO08ZnGAgJ3FcAoYvgOGiRcI4wWieJGK8d9tuoXnkOh8iqq2vxLvfm54ur4TriQ9+RyGprwNu2LSiC6VKnr83xqbP6226MmXrhM04cxJId41K8zsunH0NfF9AsVBTKeAVTkJq2o6fjBGpuiQyls0VESZ3pCgOq7uUxGRQ1FZQ9RFixbx9a9/nVQqxdVXX80xxxzDiSeeuMfzrr32WpYsWYJhGLS2tnLxxReXsywREREREZH9ssfw1PcwnTzG5tA0UBwiUExjuAUMzwbAC4TwA1HcWC2YY7+b/N4KZTdR2fZXKtffR7A4OPx4ruFYhqa8nWzLm0a8XuvawdKU/fvX2VibG0+rIwbnHxHinUeEqYuNry5Ow7UJ5nvxQgnyDfNw4k24vvFG92lzBRNq1H0qInIoK+t37traWr7xjW/w6U9/mlQqxemnn86nPvUpLrnkEorF4vBxqVSKTZs28fjjj/PDH/6Q5557bvi5G264gVBofC+ULiIiIiIihz7b9UgXHIZyFh1DhTfC08oIplfELKZLU/OtFIHiEKZbwHAtwMc3Q3jBKF6kEj9w8HYmGq5NYtMTpa7T3heHH3ci1aSmvJXUlLdhJ1pGdC3X81m20eH3qyyWd78xZf+IGpN3zwrzd5NDhAPjY8r+1gLFIUw7h52cgFU1DS+UGF77tFHdpyIih42yf/z5qU99itWrV/Pd734Xy7K44YYbuOGGG4af932fmpqabc7x/dK0ja985Su8973vLXdJIiIiIiIiI5K3XNIFm/6sRV/WIldwwCtQYTpMCViYhSzBwUFMN795Wr6PFwjiBQ6utUz3JJTeQFXbX6nc8AABKwWAj0Gu6fhS12nzSSPups1YPne/bnHnaovObOl3P9OA0yYGuWhWmDn1gb3aiOtAMZwCwcIAXjBGoW4OdqIFF7PUfRowmK3uUxGRw8qozCG58cYbmTdvHv/yL//C4OAgAIZhDH9j3BKablFdXc0NN9zAwoULR6McERERERGRnfI8n3TRIZ3NMjCUJp3NYBUKBD2LJHkayRPEAbeA4Xn4pokfiOAGo/iRKjAOnQDNcIskOx6nat1fifWtGH7cjtWTmvxWUlPeOqJNorbYkHL5w2qLe9baFJzSYxVheMf0MH8/M0xjYhx+7TyHgJUmYOfwglHsRAtW1VS8cCWZgsNQIU9TZZRp9eo+FRE53IzaQjyXX34573//+/nZz37GXXfdxdKlS0mn08PPRyIRTjrpJC644AI+/vGPU1lZOVqliIiIiIiIgOuAW6RYyJHNZklnsgwN9WPlU3h2gYjvUhdwCQdMDMPAD4TwzBCuGcYPV4A5jjY5KqPwUBtV6/5KxYYHCNhZAHzDJNu0gKGp55JrOn7Em155vs+znS6/X1Xk6U1vTNmfWmXyrplhzpkaIhocZ12nvodp5whYaXzDwAtXk6+ahhupwQslcX3UfSoiIqMXogIkk0muuuoqrrrqKgCy2SxDQ0MkEgmqqqpGc2gRERERETkceR64RXAK4BTBKeJbWQqZIXK5DOlslmwuj+W4+L5POByhMhIlEE3gm2F8M4gzDqeWl5vh5Klof5TKdX8lNvDq8ON2vImhKW8jNfktuLG6PV4nZ/u82u/ycq/LK30ur/S6pKzSzEMDOLk1yLtnhZnfNP6m7BtOgYCVwvQc3GCCYtU03Fg9brhqODAvdZ9a6j4VEZHRDVG3l0gkSCQSB3JIERERERE5FDnbBqXYebAypT+uhWNbFIpF8rbHUMEl65oUvABGIEI0Xkk8HMLcqpnQG7tXckBFBl+jqu1uku0PE3DyAPhGgEzLKaSmvp1cw3G7XKLA933a094bgWmfS9uQh7ftam3EQ3DutNKU/daKcdaxud10fSfWgBNvwo1U4wejw4e5nk9vpqjuUxERGXZAQ1QREREREZER8/3NQWnhjdC0mIFiGuxCqePU27zYpmFQ9APkvAAZ22QgHyHvRnB9n3DAJBYLUBs8/EIw00oR63uFaP8rxLufJzq0Zvg5K9FCaurbSU06Bzdas8O5WctnZX+pu/TlPpeVfQ5pa8cxmuIGR9UHOKouwNH1QaZXm4QD46jrdA/T9bffCKxgu/Rli9QnI8xoSFKTUPepiIgc4BA1k8mQTqepqKggmUweyKFFRERERGS88tw3glI7X7pdSA13leJY4G9eX9MMQCAMwQheKEHeN8gVXQbzNumCQ9F2MAyfSDBAVSxAYDyFeaPN9win24n2l0LTWP9Kwpn2bQ7xzCDZ1tMYmvJ28vXHDAeInu+zIbVtl+m6IY/tmkwJB2BWTYCj6wPDwWldbHyG0yOZrr813/cZyNlYrsf0+iRT6uNEgofmOrgiIrL3RjVEXbt2LT/96U958MEHWb58OcVicfi5SCTCcccdx1lnncVHP/pRpk+fPpqliIiIiIjIWHOsbbtK7TwUU2BlS2GpWyx1n2JAIATBMISiEK0EM0jR8SjaHgXHJZtzyBRzFGwX2/UJmgaxUIBkMrp9Y+Ehy3AKRAdWbQ5MXyHav5KAndnhuGLFJAq1R1GonU2m5RS8cCVpy2dlp8srvc7mLlOXrL3jGM0JoxSY1gU5qj7AjGqToDmOv8DbT9eP1uMkmneYrr892/XoSRdJRoMc2VxFU2Vk3K3hKiIiY2tUQtRMJsPnPvc5fvKTn+D7pc8ut/x3i0KhwLJly1i2bBnXXXcdH/vYx7j++uupqKgYjZL+P3v/HWdZdd95v5+dT65TuaqbzoRuQoNIAgxICGtsBcsykrCQFUAysmSPrq81M4/Hr3sfe6x5xmGe6zBOjy1LwFgSkmVZBiFj2QiBhQCJ2IQGGppuOlcOJ+641v1jV1V30bn7VFf6vV+vetWps9M6pwtq17d+a/2EEEIIIYQQZ4rWU1Pup6pKw3oalkbNqbB0Kq0zjLSq1HLBK4DVMbMeZ6w0QZzgh4pmGFH1G/iRIowVCQoLE9c2ybs2zjKZpm83hmYqTDNjL+NN7sDQs1dzVZaH334ufscmmlPBqXKLjPuKx/fFvPxswkujNXZXDl8FNmPBuR1phen5nenn9swieG9npuvX0IDyyjRLa0kyHUecrv9mtSBmshnSX86yobtAwZNV74QQQhyu5T8dhoeH+emf/mlefPHFw4LTNzs0YP3bv/1bHn30UR588EF6enpaPSwhhBBCCCHEXNI6nX7fnIDqAPgTacUpgGmC5aWVpW4OTGdWsKU1BLHCbyb4cUjNj6kHMWGiiKe6FrmWhWsb5Fx3VkOoJUvFeJM7ZipMM2Mv4zRHDtstynbjd2xMA9PO8wlKa8FMf81rRpof7Y34wa46zwwmhzWAWlEwp9YxTT/WtZlYC7nK9E3ePF0/LK0lzh19uv6bKa0ZqQaYJmzsK3JWew5bmkcJIYQ4ipaGqFpr3v/+9/PCCy/MTH247LLL+PjHP87VV1/N6tWryefz1Ot19uzZw+OPP85XvvIVnnzySQC2bt3KL/zCL/Doo4+2clhCCCGEEEKIuRLWoTkO1UFojqXVpk4GvCLku454SJRo/CjGjxOaYULFjwgiRZgotAbHNHFtg4LnYC+TNU3NsDJTYZoZfZnMxGuYSTBrH22YBG0baHZsnJqev4k41z1rn1hpnt4f8eAbEY/tiwmSg9vO6zC5tM/m/E6LjZ0W5cVQZfomRuxjRjXMJERb3glP13+z6eZRHXmXs3uKdEjzKCGEEMfR0hD1q1/9Ko8//jiGYeA4Dn/1V3/FJz/5ycP2y+fz9PT0cNlll/Ef/+N/5K677uIzn/kMYRjy4x//mK985St87GMfa+XQhBBCCCGEEK0SNtLgtD4EjVEIm2mV6RGCU6XAj5P0I0yo+gmNMCaMFQqNgYFrm2Qci2LGWfLrmRqxj1vdjVvZjVfdjVvZhVvdjdMcPmzfxCkcnJbfuQm/fM4Rg0KtNS+NJjz4RsQP98RMBgdLTlcWTW5c43DDGpuziouwSZLWGHETK6pjqAhteSReO2G2i8Qrn9B0/Tcbb4T4UcKazhzrugpknEX4vgghhDjjWh6iTjtagHokt956K1prPvWpT82cR0JUIYQQQgghFpComU7Vrw1BYwSiRtr8yS1CtgMMA6UgiBKCSBHECfUwpuYnBHFClCgMDBwrXcu0LetgLeEqUyMJcKt7pwLTXbiVXXjV3TiNwaMeExbOmlrHdBPNzk1EhZUza8Qeya7JhB/sivjBroiB+sHgtOwZ3LDG4cY1Dud2mIuvQdLUGqdmVMfQCm1niLNdJNluEreEcvInHZwCxIliqBaQdy0uOquNvlJm8b03Qggh5k1LQ9Tnn38egLVr155wgDrttttu43/8j//Bjh07Zs4jhBBCCCGEmEdxMFVxOgK14XTNU8sCr4Ty2gmUSgNTP6ARJtSCtMI0nZavsQ0TZ7r5k2XCUsyrVIRb3Ydb3TVVXZp+duoDGBzevAkg9sqExdWEpTUEU5/D4mqUWzju5UaaioengtPXxg+eP2vDT53l8I41Dpf2WotqbVMAdIIZ1bGiBmiNsnNEhRUkmU4Srw1tZ0/r9PUgZqIZ0lfKsKGnQDHjtGjgQgghlouWhqgTExMYhsE111xzSsdfffXV7Nixg4mJiVYOSwghhBBCCHGi4vBgcFofgrCOwiSwcwROD0GiqFdi6kGFIFZESRrkWRg4S3lavkpw6vvxpqbfT0/Dd2v7MXRyxEMSp0hQWkNYWk1YTD8HxdUor+2kLl0PNY/sTYPTLYMJ0zWnlgFX9Nu8Y43D1SttMvYie9NVjBXVMaMGGKDsAmFxLUmmTOKWTmqN06NeQmtGayHa0JzTU2R1Zy4N9IUQQoiT1NIQtbe3lz179uB53ikdP31cb29vK4clhBBCCCGEOJYkSqfqN0ZQlQFCv0oYa5pmlrouUg/1VGBaBQ4GplnHorQUA9MpZtSgbcd9FPc9glPbi6niI+6X2LmZatKwtDoNTotrSLzyKU07h7T51pMHYh7cFfH4vpjokKLW87ssblzj8LbVNm3e4goEjSTEjOqYcRNtWCinQFA+m8Qrk3glMFtXIRrGiuGqTznvcnZPga7Cqf2eKoQQQkCLQ9SLL76Y3bt389JLL53S8S+//DKGYbB58+ZWDksIIYQQQgjxZkmMaowTVEcIxvcRNSo0o5iaztIwskQqDf8s4mURmB7KjOq07biP9u33YEW1meeVlZmpJp2ejh+W1hBnOk85LD2U0poXh9N1Tn+4J6IaHty2umTyjjXpdP3+wiILTmMfM6phJiHadNPgdCpkTtwimK1v7DTZjGiEMas7c6zvluZRQgghTl9LQ9RPfOIT3HfffTzxxBM8++yzvOUtbznhY5999ll+/OMfz5xHCCGEEEII0WJJhF8bZ2J0gObYPoJ6hSiK8c0ckZ3HNu00MLVN2pbqGqbHYEZ1yq9/h/Lr92BFdSBt9jR27ododl5InOs+ZqOnU6G15vUJxb/vTqfrDzUONojqyKQNon56rcOG8iJqEKU1RtzEiuoYKkJbHolbJsxNNYZyiy1/H6clSjNc8/FsiwtWttFfymAutvVhhRBCLEgtDVFvuukm3ve+9/Gd73yHm2++mQceeIC1a9ce97hdu3Zx8803o7Xmve99Lx/4wAdaOSwhhBBCCCGWrzgEf5KwOszE0F5GxkZphjGGk8fIdOLmHcrLMDA9lBnWKO+4b1Z4GhRXMXbeh6mtvBaM1lYxKq3ZNpbwyJ6YH+2JOFA/GJzmHLhuqkHUxT2LqEGU1phxEzOqYSQx2skSZ7tIslPBqZNvSbXusTTCmPFGSG8pw/ruAm1ZaR4lhBCidVoaogJ89atf5dZbb+Xb3/42mzdv5j/9p//Exz72MdavX3/Yvjt37uQrX/kKf/zHf0y1WuWmm27irrvuavWQhBBCCCGEWF4iH/xJqI8Q14aYnJxguOpTSVycbDelsresQ9NpaXj6Hcrb78WK5zY8TZRm60jCI3tjHt0TMdw8GJx6Flw+1SDqrf023mJpEHVocKoStJ0lzvWl4anXhrazZ2gYmrF6SKw0Z/cUWN2Rx7UX15IHQgghFr6WhqjveMc7Zh67rkutVuMLX/gCX/jCF+jq6mL16tXkcjkajQZ79uxheHgYSH/oeZ7H2NgY73vf+455DcMwePDBB1s5bCGEEEIIIRa/sDETnFIfIQlrVH3FgG8xnuRwvTLljL0s1jQ9HjOsUX79Xsqvf+eQ8HT1VHj6Uy0LT2OleX4o4ZG9EY/ujRn3DwanWRveusLmulUOV/TbZCU4PSVRohiq+pSzLut78nQXvMWz7IEQQohFpaUh6sMPPzzrB9b0Y601w8PDjIyMzGzTWs/sYxgGYRjy7//+78c8v9ZafiAKIYQQQggxLahNBafD0BiDsI42LSZVhsFmkbFmjG2adOQdTCnMOyQ8vRcrbgBT4enGW6it+KmWrNMZJppnB2Me2RPz2L6YangwOC04cPVKh2tX2VzeZ+Nai+R3G60x4wZmWMPUCcrOHRKcltF2Zl6GVWlGVP/2XkAAAMTNSURBVIOIs9pzrO/Ok3NbPtFSCCGEmNHynzLT4eiJbjvW/kIIIYQQQohDaA1hDZoTUBsCfzytQLVdtFOg6hYYrAWM1UIMEspZF3uxBHVzKA1P75mqPD00PP0ItRXXnHZ46seapwZifrQn5vH9EY3o4LayZ3DNSptrVzlc0mPhLJZ/jyMFp/n+eQ9OAfwoYbIZ4VgGF6wosaKcWzxrxwohhFi0WhqiPvTQQ608nRBCCCGEEEIpCKtTwelgWnka+2C54BUg20EtShiq+IzUqiilacu42ItlevgcMsMq5e33UN5x38HwtLSGsfNuOe3wtBFpfrI/5pG9EU/uj/GTg9s6MgbXrrK57iyHi7oXW3OohRmcaq2phwmTzRDXNukpeazuyFHOufM2JiGEEMtLS0PUt73tba08nRBCCCGEEMuTSiCopMFpdSB9nIRge+AVId8FQDNMGB5vMlQNiGJFKetIQx3S8LR9+z207fgOVtwEICitnQpPrz7l8LQaan68L+KRvTFPHYiJ1MFtvTmDa1c5XLfKZlOnhblYliE7JDg1tELZ2QUTnELakKviR9TDmLxrs6G7QE8xQylry1JvQgghzihZNEYIIYQQQoj5olQajiYhqDj9HNahegCCavqck4VMWxqgTglixUg1YLAa4EcJxYxNW9aZxxeyMJhhZSo8va9l4elwQ/HkgZhH9kQ8O5iQHLIa2cqiyXVnpVP1z203F0+ot8CDU0gbRk00IsIkoZxzWdtZoqvoybqnQggh5o38BBJCCCGEEGIuaA1JBCqaCkqjg4Fp2ISonk7LT+J0HxXBdEDnZCHXkU7ZP0SYKEZrIYMVn0YYU3Aduove4ddeZsxgkvbX76G847uYh4Snoxs/Qr3/qpMKT4fqiueHY54bSnh+KGZ/bXYPh7VtaXB63SqHtW2LKThNMKMmZlRfsMEpQCOMmWxGmIZBZ8FlRblER97FsaTCWgghxPxqaYj6n//zf+b222/nvPPOa+VphRBCCCGEWHhUcjAUPTQgjXyIGulHEk1VmEagFWAAGkwLLAdMO60wtfJgOnCUQC5Smol6yEDFp+pHZB2b7kImPd0yZgaTtG//J8o7//mQ8HQdoxtvOeHw9HihqWnAOe0m16xMp+qvKllz8lpaTmuMuIkZNzGTEI2BdnJEhRUkmc4FFZwqran6MbUgIutYrOrI0lvKUs46mItlPVkhhBBLXktD1D/+4z/mT/7kT7j66qu5/fbbufnmm8lms628hBBCCCGEEGeW1lAfgbgJcZhWkIaNqSn40VRQmjATkBomWHYailp2WlVq2mlwepISBRPNkIFJn8lmRMa26Cpkjpa1LhtG7NO+/Z9of+0fMRMfAL9tPWPn3UK9/63HDE+H6ornhmKeH0p4bijmQP3IoenFPTabeywu7LbJO4vjDTeSIA1NozRQ1naGxCsTZjpQbhHlFNDWwmnEFCeKyWZEkCQUPIeNfUW6ihkKnkyYFEIIsfDMyU+nxx9/nMcff5xf//Vf55ZbbuFTn/oUl19++VxcSgghhBBCiLkTNWH0dZjYnVaSGqThqGmnlaRODjIOGNZRq0hPhVIw6UcMVnzGGyGOadKZ9zCX+4xmrSjueZjOl/43jj8KTIWnGz9Cve+tR/w3OJHQ9Nx2k809Nhf3WFywiEJTVJyubRo1MXSCtlyUnScor0S5RRK3iLYXXlGLHyVMNiM0mvacy7nlIp0FF89eJFW+QgghlqWWhqgf+9jH+Md//EcajQYAlUqFL37xi3zxi1/koosu4vbbb+eXfumXKJfLrbzsUYVhyN///d/z9a9/na1btzI4OEh7ezvr1q3jpptu4tZbb6Wrq2tOx/DMM8/wzW9+k+9///vs27ePsbExOjs76evr45JLLuGGG27gne98J319fXM6DiGEEEIIcRK0hvowDG+D5jgUemY1dprLy1b9mMGqz1gtxADKWRfbWiSh3hzKjLxI94tfJjPxGgBRtpuRC26ltvL6WeHpdGj63FRoOrCUQlOt0krTuIkZhyjTQtt5ouJZJF4Z5RRQTv6UGmjNNa019SBh0g/xbJO+tgx9bRnacy6WTNkXQgixCBhaa3383U5ctVrl7rvv5o477uDJJ588eKGpGxvP8/jABz7Apz71Kd7+9re38tKzvPLKK9xyyy1s2bLlqPv09PRw55138u53v7vl1x8aGuLzn/88X/va146776/92q/xF3/xFyd9jUqlQltbGyMjI3R2dp7KMIUQQgghjiiKIu6//37e/e534zjLrOt7HMLYThjfkYZR+e6WVpkeiVJQDWKGqz5jjRCtoJRxsG0Jl5z6ATq33klx/2MAJHaW8XNvZmLD+9CWd2KhaYfF5m5rEYamemqKfgMz9gEDZWdJvDaSTAfKKZK4hbQyeoFKlKbSjGjGCXnXoq8tQ3cxQyljL56mXEKIObGs7zXEgjKdr01OTlIqlY66X8t/2haLRX7lV36FX/mVX+HFF1/kS1/6El/72tcYHZ2abuP73H333dx9992sX7+eT33qU9x6660trcTcu3cvN954I/v37wfSAPf6669nw4YNDA8P8/3vf59ms8nQ0BDvf//7+d73vsc73vGOll1/9+7dvP3tb2fnzp0zz5133nlcdNFFdHZ20mg0eP3119myZctM1a4QQgghhFgAGmMw8irUhiDXCW5uTi+XKKj4EcPVgPF6CEAhY+PaC6+S8Ewzwxodr36Tth3fwVQxGpPdfe/kBx2/yLZmiV2PJewYrzLYOHJoenGPxcU9Nhd0WeQWS2gKGEmEGTfSplBaoSwP5RYJimtJ3EK6rukCaQh1LGGsmGiGJEpTyjqs78nTVfDIODJlXwghxOLU8krUI4miiH/6p3/ijjvu4Pvf/z5KqfTiU395tCyLd7/73fzyL/8y7373uzFPc7Gn66+/nkceeQSANWvWcO+993LxxRfPbB8ZGeHDH/4wDz74IAAdHR28/vrrLVlmYHJykksvvZQdO3YAcMMNN/Cnf/qnbN68+bB9wzDkBz/4AdVqlQ996EMnfS2pRBVCCCHEXFl21SFJDJN7YHQ7qDitPj2FRlAnKlaayWbEUCVtGGViUJTKUwBqfoz52v2c+8Y3yCYVAH7CRfx28Ets06sP23/OQ1MV4zSG3/TkEX6FMoypp6cajGGk6zMcNpSj/PplGKA02nJQdo4424lyS2lDKDs359XQpytKFEGsCKKEIFZYlkF3waO/LUNH3sW25A8DQojZlt29hliwTrQS9YyEqIfas2cPd9xxB3fddRe7du06OJCpm4L+/n5uvfVWPvnJT7J+/fqTPv/999/Pe97zHgBc1+Wpp57ioosuOmy/er3O5s2bZ8LO3/qt3+L3fu/3TuUlzXL77bfzpS99CYBf/MVf5Gtf+xqWNTc34BKiCiGEEGKuLKtfbPxJGNkO1f2QaQOvOGeXihLNRCNksOpTbUbYlkXRs7GW4ZqnE75id0Wxq6LYPanYNRlzVuVZ/l/qq5xj7gNgu1rB/xX/Eg+rSwCDsmewps1kdclkTZvF6pLJeR1zV2lqJAF2Y5SosII4Pz1zburXp8N+jUq/Nmaef/N+h3yees6Y2Wfqk+WQOGm16VyG+KcrShRBpAjihCBJC2Rsy8CzLQquTVvWpj3v0pZ1ZMq+EOKoltW9hljQFmyIeqgHHniAO+64g3vuuYcgCA4OyjAwDIO3v/3tfPazn+X973//CQeR73nPe7j//vuBNND84he/eNR9v/a1r/HRj34USKtRBwcHse1TX+Fgy5YtvOUtbwFg1apVbN26lWJx7m7CJUQVQgghxFxZFr/YKAWVfWmAGteh0Dtna0sGsWK8ETJcCaiFEa5lU/BsTnMC1oKntWbU1+yenA5ME3ZNPZ4MDv4acq6xh/+v/VWut14AYIIC38zczLbu/8CqNncmOC15Z+4NM6IGTjBBUFxDWN6Attwzdu2FJEoU/lR1aRgrNODaU4GplwamOdcm41pkHQtHKk6FECdoWdxriEVh3tZEPRnXXXcdBw4cYNu2bWzZsmXmr5Raa7TWPPTQQzz00EOsXbuW//7f/zsf+chHjnm+Wq02M0Uf4Lbbbjvm/h/4wAf4zGc+Q61WY2xsjB/+8IentTbqX//1X888/rVf+7U5DVCFEEIIIcRpCOtpeDq5B9w8lFbOyWWaUcJ4PWSwGuBHCRnbojOfWegzs09ZPdQ8P5w2eXp5JGFXJaEeHX3/TbkKn3e+xY3BDzBRKMNmZO17qW76MDe4BW44c0OfxQxrWGEVv3w2YWndgq4KbRWtNVGi0+rSqcAUA5ypCtOOvCuBqRBCiGVtXkLUp556ii9/+ct84xvfoFJJ1zkyDAOtNa7rcu211/LEE09Qq9UA2LlzJx/72Me47777uPvuu486JeSxxx6bqWjN5/NcccUVxxxHJpPh6quv5oEHHgDgBz/4wSmHqEmS8PWvf33m6w984AOndB4hhBBCCDGHtIbqAIy8lk7jL3SD7bX8MvUwZqwWMlwL8aOYnGPTlfeOsD7m4lYPNS+OxGwZTHhuKOb1CYV60zw304AVBZM1JZPVbSZrShZrCzEXj3yXnu3fxAqaANT6r2HkwtuI8v3z8EoOsvxxjCTC79hIVFy94NciPRVaa8KZKfmKSCWgwbVNPNuis+BSzrpkXJOskwamsqapEEKI5e6Mhajj4+N85Stf4ctf/jIvvvgikP7wnnbOOedw++23c+utt9LV1UWj0eAb3/gGf/EXf8GWLVvQWvPNb36Ta665hs997nNHvMbLL7888/iiiy46oan5l1566UyIeujxJ+vFF1+cCYTb2trYsGEDcRzzla98ha9+9ats3bqV8fFxurq62Lx5M+973/v45Cc/iee1/qZdCCGEEEIcQeTD+E4YfyOdtt+2sqUBmdZQC2JGagGj9ZAoVuQ9m+7iwu+kfqLqkebF4ZjnhxK2DMVsHz88ND2raHJxj8VF3TbryyYriybu9JqvWlPY/yO6nrkLpzEIgN+2geGLbsfvuvAMv5o30Rq7OQKmhd914SFroC4NUaKoNCP8OMHgYGDaXXJpy7hkXSv9cCwsc+kFx0IIIcTpmvMQ9YEHHuDLX/4y9957L2EYAgfDU8/zuOmmm/j0pz/N2972tlnH5XI5PvnJT/LJT36SP//zP+fXf/3XAbjjjjuOGqJu27Zt5vGaNWtOaHyrVx/s8PnKK6+c+At7kyeffHLm8apVq9i7dy8f/OAHeeKJJ2btt3//fvbv38/3vvc9/uAP/oBvfetbx62YFUIIIYQQp6k+AsOvQmME8l3gZFt2aq2h4scMV33GGyGx0lNrRS7+9d0akWbrSMKWwZjnh2JePUJouqJgckmPxcU9Npt7LLpyR65Y9Ma20f3i35IdS++540wHI+d/guqqG8CY5ypHrbAbQ2g7j9+xkSS7NPoNaK1phAkVP8I0DMo5hw2lAhlHAlMhhBDiZM1JiLp7927uvPNO7rrrLnbv3g3MrjrduHEjt99+O5/4xCfo6Og47vk+97nP8c1vfpNHH32UV1999aj7jY6Ozjzu7e09obH29R38C/PY2NgJHXMke/bsmfX1u971LrZu3Qqkr/eKK67Asiyef/55nnnmGSB9n97+9rfzwx/+kMsuu+y41wiCYFYDrunK1yiKiKJjLDYlhBBCCHGSpu8tFv09RhLB+G6YeAPQUOhPA7upjuKndWoFVT9ipBYyUU+LBQoZG8c2p7bPW//WU9aMNFtHE54fSo4amvYXDDZ321PVphbdbwpN3/y67cYQ3S//HW37/h0AZXmMnv0Bxjb8AtrOpJ3p56/XLagEpzFM5JUJ2s9BuSVI4vkbTwvEiaLmxzTihKxjsrItQ3fRo5RxDglNNSqJUcm8DlUIsYwtmXsNseid6PdgS0PUv//7v+eOO+7gwQcfnAlNpz9nMhk++MEP8ulPf5prr732pM+9efNmHn30UXzfP+o+02uoAmSzJ1ZdcOh+hx5/siYmJmYeTy9XkMvluOuuu/jQhz40a9+HHnqIm2++mZGRERqNBr/4i7/ISy+9hOseu+Pn7//+7/O7v/u7hz3/0EMPkcvlTnnsQgghhBBHM73s0dKxf07PPjSnZ2+9IIGdVYPXKgbbJw1210Hp2ZWJnZ7m7JLmnLb0c7sHkP6yMTaafhyJnTQ5e/CfWTf0L1g63X93x7W83P9BfLcDDjSB5ty9uJPiAU0YeH6+B9JyITAJbJ/vgQghxFEsvXsNsdg0Go0T2q+lIeott9wy0yBq2gUXXMDtt9/Oxz/+ccrl8imf+3gBIzArYD2R/YFZa5I2m6d+E1ev1w977qtf/Sq/8Au/cNjzN9xwA9/5zne49tprUUrx+uuv87WvfY3bbrvtmNf4rd/6LT7/+c/PfF2pVFi1ahU33HADnZ1LY8qREEIIIRaGKIp44IEHeOc734njLLJp6SqByj4Y2wFxkDaPMk//tjdKNJONkOFaQNWPsE2LvGdjW4trOvSrYwmP7Uun528bUyRvKgLtzRts7k6n51/UbdGbP7mp9m51N8X9j9L+xr9gB+MANDovYPCCXyYon82JLbo194zYx/bHiAorCcsb0Nbi7FWQKE3Nj6hHCRnbpKvo0V3MUM46MlVfCLGgLep7DbGkTM/0Pp6WT+fXWpPNZrn55pv59Kc/zdVXX92S837kIx/hkksuOeY+mczBRfun1189nkOnx59o9erxrg1w9dVXHzFAPXT7TTfdxLe+9S0greI9Xojqed4RG1E5jiP/wxFCCCHEnFh09xlBFUa3w+Q+8ApQ7Dql0yQqbcQTJYpIpV3MR6oBtTDCMS26ClnMRdasfHcl4Y7nAh7dN3uqek/O4OKedHr+xT02fYWTfGFa41Z3Udj3KIX9P8KrHlzmKsz3M3LBbdT7rwbDwGrFC2kBM6pjhRXC8gai8noM02axxY1+lDDZjFBaU8q6rOnJ0FnwKHhnrHewEEK0xKK71xBLzol+/7X0J+zmzZu5/fbb+ehHP0pbW1srT80VV1xx3AZMhUJh5vGJVpUeut+hx5+sNx97rAD10H2mQ9THHnvslK8thBBCCLHsaQ2V/TDyGoRVKPSCdewb4lhpokQRJ+nnMFGEsaIexoSRIlaaONEoNGjwHIvOfAZjkaVtI03FV14I+N7OCKXBNOC6s2wu77fT0DRvYJzsi9Iat/IGhX0/orj/Udza3oObDJtGz1uorryW2srr0cf5dzjTzGASM24StJ9LWFoz/02tToLSmqofUwtiMrZJT8mjry1De87FsRbP6xBCCCEWo5aGqFu2bGnl6U7aoVPaBwcHT+iYgYGBmccn0uTqRK4NcP755x/3mE2bNs08rlarVKtVisXiKY9BCCGEEGJZioM0PJ3YBXYGSiuZTjpjpYliRZRoIpVWlvpRQiNICJM0KE0OCUpNw8C2TGwTMo6F7ZmLruJ0Wj3U/P0rAd/eFhJMNQ+6ZqXNJzd7rGk7hZpQrXEnd1Lc/yMK+x/Fre2b2aRMm0bPpdRWXEu970qUe+rFCXPJ8scwtCLovIAov4LFkogHcVp1GitN0bPZ2Fego+BR9OyTD8CFEEIIcUqW1FyP8847b+bxrl27TuiY3bt3zzzeuHHjKV/7zceeSFXrmwNTCVGFEEIIIU6SPwnDr+BPHCBwu4iUQ1QJ8KOEZpgQJIok0cRKo1EAmJg4loltGmQdc1EHpUcSJprvbg/52taQSpgueHp+l8XtF3tc2H2St/9a402+TmHfVHBaPzCzSZkOjZ7LqK38qTQ4dfKtfBmtpTV2cxhtuvid5xPneuZ7RMeltKbmx1SDCNc26SocrDp17SX0DSuEEEIsEksqRD20svOFF14gjmNs+9gv8Zlnnjni8SfrwgsvnPV1rVY77jHVanXW161eAkEIIYQQYkmrDuDvf4mxiTEOqDbCxAd80GBNV5RaBp5rYlvmYik6PGVKax7aFXPXCz4D9TQ8XVUy+eXNHlevPImKRa3xJrZT2P8ohX0/wm0cnLmlTJdG72XUVkwHp7m5eCmtpRVOfZDELRF0bCTJtM/3iI4pjBUVPyJMFHnP5pyeIl1Fj1JGqk6FEEKI+XRKIeo73vGOVo9jFsMwePDBB0/6uGuuuQbP8wiCgHq9zlNPPcVVV1111P2DIODHP/7xzNen87rWrVvHunXr2LlzJwAvvfQS73nPe455zMsvvzzzuKOjg3x+Af/1XgghhBBioVAJ0chOJva8yGAtoWK2UfAcihlryQelR6K15qmBhC8957NjIq227cwafPxCj59Zd4Id2rXGm3iVwr5HKe5/FKdxcGksZXnUp4PT3ivQiyE4naZinPoQSa4Lv/08lLswZ32FcbrMRC2IsSyDzrxLX1uGjryLZy+UdlxCCCHE8nZKIerDDz88Z38F1Vqf8rkLhQI33ngj999/PwB33XXXMUPUb3/72zPVoB0dHVx//fWndN1pN910E3/0R38EwD333MN/+S//5Zj733PPPTOPT/faQgghhBDLgQqbjO/eytje1xgni5PpoNuzWXSt1Vvk1bE0PH12MF30NOfALZs83n+uS8Y+zpuiNd74q+kap/sexWkOzWxKg9PLqa28lnrv5Wg7O5cvY04YSYjdGCbK9xN0bETbmfkeEgBxovBjRRAlBLECA1zLIGPbrO/O0130KGUczBMJv4UQQghxxpzydH6tdSvH0TK/+qu/OitE/dznPscFF1xw2H6NRoPf/u3fnvn605/+9HGn/h/PZz/7Wf7sz/6MKIp47LHH+M53vsP73ve+I+77xBNP8O1vf3vm61tvvfW0ri2EEEIIsdRNjg0zvPM5aqP7ibM9tOXzS2ot05Oxv6q48wWfh3fHADgmvO8cl4+c71LyjvGmqIjM2DYKBx6nsP8xnObwwU2WR73vyqmK08sXTOh4Koy4id0cJyytJiyfg7bceRlHojRBnBBECj9Og27TNMg4FuWcSzlnk/Nscq5N1rFOrGpYCCGEEPPilFLD3/md3zmh/e6//36efPJJDMOYFVjOpfe85z1cd911PPLIIwRBwHvf+17uvfdeNm/ePLPP6Ogot9xyC9u3bwfSKtTf/M3fPOL53njjDdatWzfz9Z133nnUwHPDhg386q/+Kv/rf/0vAD7ykY/wd3/3d9x0002z9vv3f/93PvShD5Ek6Y3UVVddddSwVQghhBBiuasHMQN736Cy5wWIGmQ6VpE/zT9+L1bjvuJrWwO+uz0i0WkB7o1rHT5xoUdf4QjhqVa4lV3khreQG95CdmQrZuLPbFZWhnrflVRXXkuj59JFHZxOM8MaVlglKG8gbFsP5pmZDq+1JohV+hElxFphYuI5JlnPYkV7hoLnkHUtso4lzaGEEEKIRWZOQ9SRkRGefPLJkzqmFe6++26uvPJKDhw4wBtvvMEll1zC2972NjZs2MDw8DDf//73aTQaANi2zTe/+U3K5XJLrv2Hf/iHPPPMMzzyyCPU63U+8IEPsGnTJq644gosy+L555/n6aefntm/v7+fb37zm7JIvBBCCCHEmwRxwsB4naHd2zBGt5PPetjl1fM9rHnRjDTf2hbyD68ENNPiU67ot/jU5gwb2meHhHZ9kNzwc2loOvwcdjg5a3vslmj0vIXaimtp9F6Ktrwz9TLmnBVMYMQhfvtGotJq5nKR3ChJ1zENYkWYJBgYuJZJxrXoLGQpZR2yjkXOtfBsU+73hRBCiEVuSf4J/6yzzuIHP/gBt9xyC1u2bEFrzcMPP8zDDz88a7/u7m7uvPNObrzxxpZd2/M87rvvPj772c/y9a9/HUgbSB3aRGraW9/6Vv7hH/6BVatWtez6QgghhBCLXaI0w9WAXUNjRIOv0BkM4LZ3oJzl14QzVpp/eT3iK1sDxv10Oa1zO0x++eIMb+lNb+XNYJLcyAszoalbPzDrHMryaHZdSKPrYho9lxCW1oKx9Kog7eYIGCZ+1wXE+f6WnjtReiYwDeIEDdiWQca26Cy4tOdcMlOBadaxZD1TIYQQYglakiEqwMaNG/nJT37CN77xDb7+9a+zdetWBgcHKZfLrF+/nptuuonbbruNrq6ull+7ra2Nu+++m8985jP83d/9HT/60Y/Yt28fSZLQ29vLVVddxc0338z73/9++Yu0EEIIIcQUrTVj9ZA9Yw1GR4Zor++ghwmSch/KcuZ7eGeU1ppH9sbc8XzAvqoCYEXB4JObM1zfH5Mfe47si8+RG34Ob3IHBgf7FWjDxG8/j0b3JTS6L8bvOA/MJfz+aY3dGETbOfyOjSTZ07u/n1nHNFYEkUKhsQwDzzEpZi1WZ7PkPJusa5FzLGxr6QXSQgghhDjckg1RAVzX5eMf/zgf//jHT/kca9euPeUmWtdffz3XX3/9KV9bCCGEEGK5qPoRe8Ya7J/0cRuDrA7ewDYD4lw/GGdmTcuF4rnBmC895/PKWBqednqKz6/fwzvdrRR2P0dmy8uYKp51TFBaQ6P7EprdF9PsvBDl5OZj6GeeTnDqgyReO37HeSivfFKHK60JorS61I8VSmtM0sA061r0t2UoZNKmT1nXwrOX1/eiEEIIIQ5a0iGqEEIIIYRY2PwoYd94k73jDZphyIpkgKL/BtpyiTN98z28M0ZpzZbBhG9tC3nyQMTZxj5+2dnKB4pbOTd8CWtnY9b+UbabRvfFNKeqTZNM+zyNfB7pBKc2SJzvJWg/97jLPby58VOkFJY5tY6pY9FT8ihmnEMCU1nHVAghhBAHSYgqhBBCCCHOuDhRDFYDdo3UqfgR7Y5iRbILt7qHONO+bCopq6Hm33aGPP7aIBsaz/Nh60X+wnuRXmMi3WEqO02cAo3uzTOhaZRfMadNkxY8rXHqQyS5LvyOjWg7+6bNmjBR+FNVplGiMQ1w7TQw7SxkKWZscm5aZZpxJDAVQgghxLFJiCqEEEIIIc4YrTXDtYDdow1GaiE512JVJiQz/iq2P0qU60Evg/VPXx+q8vrLz1EY2cJNxgv8V3MfuAe3K9Ol2XkBze60GVTQtm7ZLWtwLHZjiMRrw29PA9RwquGTHykilYAGz06n3/e3ZdIKUzdt/JSxpfGTEEIIIU6ehKhCCCGEEOKMmGxE7BlvcGDSxzIM+ooenj+EN/IqRuITFvqXZNd4AFSCOfoqI9ufJje8hRuT1/hZI4GpXFRj0Gw7G7/3Ehrdl+B3bEJb7rHPuRxpoDZMHYdxbz2NhgXNJq5l4NkW3SWXctYl46SBadaRwFQIIYQQrSEhqhBCCCGEmFONMGbfeJN9403CRNGZ93BNjVvZiTu5I13/NL/E1j/VGqe2j9zwFsz9z5IffYGsbrBhersBQ1Yv9e5L8Fa9hWb3xSi3OJ8jXng0RIkijBVRool1guNPYFsQdZ9PW7mbNVmXjGuSdSxyro0lgakQQggh5oiEqEIIIYQQYk6EsWJgssnusQY1P6Y979Lpehixjze2Hae6lyRTXjLrn1rBBNnh58gNbSE3/CxOc2TW9gmd52njQpo9l7Bq42XkOlYAEM/HYBcYPSswVSRKgwGOaeJaJu15m6IR4xUyOGddTKZjlQSmQgghhDijJEQVQgghhBCnLVGaZpTQCGP8UDHeCKkFMVU/ouA5rChnMQwDM5ggM7Y01j81Yp/s2EtpaDr0LF5l56ztgbZ5Sp3Ho+pCRjsu4aLzzuHyFd6yD/8ODUzDWJFohWEYOJaJZ5u0ZV1yno1nW2RsE9e2sOI6+BH0bob21fP9EoQQQgixDJ1SiPqFL3zhhPZ74oknTvqYab/92799UvsLIYQQQogzQ80Epgl+lDDRDKk2Y4I4IYgVhgGuZeHZJn2lbBoaao1dHyAz/iokweJc/1QneBM7yA0/S25oC5mxlzDV7DrSl9QaHlEX8qi6kFfsTbx9Q4H3nu3SX1hkr7VFlIIwSYgSTRgrFAoDA9cycW2Tcs4j56YNoDzHxLMszDe/VbEPzXHoOR/KEqAKIYQQYn6cUoj63/7bf8MwTuwv6NP7/e7v/u5JXUNCVCGEEEKI+aeUphHGNMKEZphQ9SMmG2lgGiYKpfVMYFrKuDiWcfh9oopxK7twJ19HWx5Jvnd+Xsyp0Ir8gR9T3Pvv5Iafx4qqszZX7U5+pC7iX/wLeUxdwAhtbOq0+LmzHX5ztYNrLa+q0zjW+HEyFZhqDAwc28CzTTryHjk3rTD17LTq9Li/UiQh1Iah6xxoX8fxDxBCCCGEmBunPJ1fa93KccxyogGtEEIIIYRoHa01fqRoRgnVhg/A07vHCZWRhmIanKku6IWMjWuZx71vM2IfbyJd/zTOlNGLZf1TrckNPkXny18lM/n6zNOJnWO07SL+PbmAO0fO5yW/HzDwLHjHeoefO9vlnA5r/sZ9BmlNGqbHmjBJ0Id8f/SUPPKeTWaqwjT9XjnJC6gYqoPQvhY6z+HwElUhhBBCiDPnlELU66+/XoJOIYQQQohFTGtNECuaYUIjSqj5ERONCD9KK0zjOJ2mHieavOfQkTt+YJqeWGGoCEPFGHETb2IHlj9GlO8Gc3Gsf5odfp7Ol79CduxlAJSdZWztu3nUvJw79q/huX0H9z2raPJzZzv8h3UuBXdp3x/HiSacCk0jpTANcG2LrGPSW0qn5Wcci4x9hCn5J0slUB2A0kroPg8saeUghBBCiPl1SncjDz/8cIuHIYQQQgghzoQwVgzXAg5MNKmHMWGkSVDYRjq9OuvYlHMmqIQ3gLasg2lZoGKMJD4YkE59RkUYSYAZ+5hJgJFEoGMMnYCKAJOo0Lco1j/1xrfR9dJXyA1vAUCZLm+seDd/Z7yPe7dnGffTmVimAdestPm5s13e0mstzeICDeFU86cgVmitMM30e6ScdyhmbLKOTcZJn2vttTXUBqDQAz2bwPZae34hhBBCiFMgf9IVQgghhFgGokQxXA3YPdZgohGSsS2yjkHZ0ViAoYI0HI0ijCBGxQEA3vDzODpMt+k4rRBUCQbTSztptGGCaaMNC23aaNNNvzYtMBb+1HZ3ciedL3+NwsCPAVCGzZPFG/n9xs+zZXt5ai9NR8bg3Rsc3r3BpTu38EPhk6EUhFONwcIkwQCcqbVLOwuZdC1TxyTrWNjmHIfG1UHIlNNGUu4iWf5BCCGEEEuehKhCCCGEEEvYm8PTvBGy2qjg1ocxkqngVCdppalWgAYMEqWBDFYwiWGnAamyclPBqL0kGvw4tX10vnI3hb0/xECjMPk36zr+r8YvsLfZk+5jwlUrbG5Y43D1SnvuA8QzJE40fpQQxYoYhYWJa5sUMw6lbDadlu+YZGzrzP5T14bAyULvBeAVz+CFhRBCCCGOTUJUIYQQQoglaFZ4Wvcp6hpr1DgZfxgjaqBsD205aMtFmRbasME8WDWaKA3j4yTZjnT++hJiN4bo2PYNSru/PxUcw3eTt/In8Qd5Xa/EMuCtK2zevtrm6pUOeWfpvH6lYLIRog3I2hZtJZeC55B1DjaAmjeNsfR7sPcCyLbP3ziEEEIIIY5AQlQhhBBCiCXk0PC0Uq1RSiZYn4zghOMYWpN4RZTXvyQqSU+W5Y+Tf/nv6dz9PWydNs56MHkLfxx/iJf0Wi7usfiNNQ7XnmVT8pbWdH2AZphQCyLKWZcV5SzFjMN8Zqaz+BVIIujfDIXu+R6NEEIIIcRhJEQVQgghhFgCZsLT0Tq1yVFK8Tjr1AhOVEfZLkmmA2058z3MeeHXKkTP/QPnD99PhnSt18eS8/n/xTfjd27ihtUO/+cqm87sQkkUW0spmGiEWKbBmo48PaUMjrWAQvSwnn70XgClFfM9GiGEEEKII5IQVQghhBBiEZsOT/eOTFAfH6IUjbBOTWIRk7gFosLyrDr1Y80ze6rkX7uHn6nfR9FoAvCsOpu7M79I27pL+Y1VDn2FpRmcTmsEMY0opj3nsbKcpZhZYLf/sQ/N8bSJVHn1fI9GCCGEEOKoFthdlBBCCCGEOBHT4en+wUHqY4O0RUN0GQ0MyybJthFZ3nwP8YwLE83TAzE/eqPOhoF/4XbzXjqMGhiw3VjNT/o+Qv/Gq/h029K/BY4TzUQzxLVN1nYW6C56C68pVhJCbRi6zoH2dcsy7BdCCCHE4rH07yCFEEIIIZaQKFGMVBocOLCX5ug+ivE4HVYMXoHE7QXDOv5JlpiXR2Pu3x7x471N3qse4gv2PfRZ4wAMOyvYf85HyJ59HVeay+O9qfkxfpzQmffoL2coegvwll/FUB1Mw9POc8Bc2hXBQgghhFj8FuAdlRBCCCGEeLMoUYyOjzFwYB/+yB7yqkLZdVDFNhI7O9/DmxeNSPPl532++1rAL5g/4jv2P7LaGU63ed1UNt1CdfWN5JZJeBonmolGSMaxWN+Vp6uQWTiNow6lEqgOQGkldJ8HlvxKIoQQQoiFT+5YhBBCCCEWsCiOGR0ZYGj/LoKxA2S1T1e+hM70k5jL91buif0Rf/qUzwZ/K/e7/5uN5h4AYq+dsfNuprLmZ5dPIy0N1SAmiBO6ix4rylly7gINjrWG2gAUeqD3fLDd+R6REEIIIcQJWb533kIIIYQQC1gUNBgb3s/Ivp34lWFcA8rFDnB70Mt47chKoPh/ng144Y1B/k/na7zPfRyAxCkyfu4HmFj3XrSdmedRnjlRrJhohuRcm7O7C3TmvYU9M746CJly2kjKWZ4V1EIIIYRYnCREFUIIIYRYQOL6OGNDexjd/wZ+bRLTyVAs92E4y6Sq8ii01vxwT8xfP13jpvh+/tT7JwqGj8Zgct27GN30MZRbnO9hnjkaKn5MlCT0lTL0l7NknQVafTqtNpQGp70XgLeM/q2EEEIIsSRIiCqEEEIIMceU0sRKEyuVfk6mHifp4zBJCJp19MQezIld+IGP4RXJda3BtJZv1em00abiz5/y0Qe28A37Ls529gPQbD+P4Ys/S1A+e55HeGaFsWKyGVL0HNZ2FenIuQu/sX1jDEwrDVCz7fM9GiGEEEKIkyYhqhBCCCHEKVBKE00HoUoTJ4pEaSKlSRJNECc0o4QwVkSxJtbp9lhplNLogyciGwxTqO/GCyeIsx3ku3oX9pTsM0Rrzb/ujLjn2X38Bl/lve5PAIjdNkYvuJXK6hvBWD5vlNYw2YxQStPflmVFOYtnL4LX71cgiaB/MxS653s0QgghhBCnREJUIYQQQogTFMaK8UbIwKRPPYhJdBqYxlOfDWM6HDUwDQPbNLBMA8swcC0T0z74nGEYmMEEbmU3jn8A5XkkpTUs/JLCM+NATfEXT1S4bPS73Gf/EzkjQGMyuf49jG78JZRbmO8hnlF+lFD1I4oZh5XtWdqzi6D6FCCspx+9F0BpxXyPRgghhBDilEmIKoQQQghxHFU/YqQacGDSpxrE2KZB1rFwLRPLMbBNE8s88UTLSAKc6l7c6m6MJCTOdi2fTvLHkSjNva+FvPrCk/y++b/Z4BwAoNFxPsMXf4awbf08j/DMUgommyEYcFZ7jt5SZuFXn2oNOoE4gOYE9GyC8ur5HpUQQgghxGmREFUIIYQQ4gjiRDHWCBms+IxWQ/wooZBx6CtlME+1BFAr7MYQbuUNLH+CxCuhsp2tHfgitmsy4as/3sMv1v43v2k/CUDolhm78JNUV92w7Kp0/TChGsSUsw4rylnKuXkI2rUClaShqEpmP57ZpmYfYxhgWOkaqJ0boH3dsvu3E0IIIcTSIyGqEEIIIcQh6kHMWD1k30STSjPCNAzasg6dBe+0zmuGlXTqfn0fynSJCn3Laj3PY4mV5h+31shv+zb/j3UvWStEYTKx/r2Mb/ollJOf7yGeUUrBRCPEMg1Wtefoa8vgtLLBmEog9kHFB0PRmUBUz97XMNMw1LQAC0wTLA88L/1se2A5YNpT+9mzHzs5CVCFEEIIsSRIiCqEEEKIZS9RmolGyGDVZ7ga0AwTcq5NTzFzUtP0j8RIQpzaftzqLozYJ852oi23RSNf/F4dS/jR44/x6eAu1tmDAEy2X8DEJZ8lbFs7v4M7w8JY0QwTwiShPeexspyllG3R7Xrsp2uTRn4aato5sCxwpoPQ6c/2wSB0uprUtN/0IeG/EEIIIZYfCVGFEEIIsWz5UcJoPWT/RJOJegSGppRx6MidXtUpAFpjN4dxJ9/ACkZJ3DZUof30z7tEBLHmvmd3c/nuO/h962kwoW63U7n4U9TOetuyqF5UCvwophkpNArHssh7Fmfls3QWPJzTCfBVDGEjDU51AnYG3AK0r4dMCbwiWO6yeJ+FEEIIIVpBQlQhhBBCLCtKaSp+xHA1YKDiUw9iMrZFZ8HFsVpTYWeGNZzqLpzafjAtonxfWtUnAHjxQJ3RJ/+B30juJWNFxFgMr30f9QtuQTu5+R7enApjhR8pgjjGNEwyjklvyaOYcci7FhnHOrVcU2uImhDV04ZOhgVuHsprINeehqZuQUJTIYQQQohTJCGqEEIIIZaFIE4Yq4cMTPqM1kOSJK06XdGWxWhVsKSidOp+ZRdm3CTOdqCtFlS1LhH1SPOTH/+Idw3fwWpzGAw4ULyI8IrPEpaWZvd2pSCIEppRgtJptWnOtVhRLpBzbXKedeoVp0mYVptGjXRNUycHmXYodIM3XW06D82ohBBCCCGWIAlRhRBCCLFkaa2p+DEjU1WnVT/GtUzasy6u3cJ1HbXG8kfxKm9gNYZJvCJRob91518Ctu7YTefzf8uv8CyYMG52MHnxLxOtvm7JVUdG09WmSYyBgedYdJdcShmXnGuRPeVqU5UGpmEjrTa13LTatGMDZMtpcOou7UpeIYQQQoj5IiGqEEIIIZacKFGM10MOTPqM1QOCWFH0HPrbMpgtDuyMqIFb3Y1T3QsG6dR9U6buT6s2mux99Bu8q/YdPCMiwmL7ip/HufQWtJ2d7+G1hFJppbMfJiRaYVsmOdemry1PzrXJezaOdYrfd3Ew1RCqmX7t5CHfnX54xfRDvt+EEEIIIeachKhCCCGEWBK01tSCmLGp8LTSjLAMg1LWoaswByGTinHqA7iVNzDDWjp13860/jqLlFaKXS8+ygWvf5lLjREwYFtmM1z1WezyKvR8D/A0xbGmGScEUQIGM+vqlnIOOdci59inXm0a1iGsQZKA7U01hFp7cIq+I99nQgghhBBnmoSoQgghhFjUgjhhohExMOkzXg/x44S8a9NTzGCdTnfzo9EKyx9Pq08bgyROPp26v8SmpJ8qq7KHsVd+RPvAo7xTvQEGDNLJ7k2/TPncaxft+6T1wbVNE62xTYOsa9FbzJH30rVN3dNpTKY1+JMQVNOwtG01ZA9pCGW2cPkJIYQQQghx0iREFUIIIcSio5RmshkxUgsYrAbU/BjHMihlHDoLc9PIyYib2P4YTv0Apj8GmIS5HjCX+e2U1riVXdi7f4Sz51F6wj2sn9oUapvH299Hz9W3UPYW59R9paDqR4RJQtaxac+7lLMOOc8ia9unn21qDUEF/Apk2qD/Yij2pRWoQgghhBBiwVjmd/1CCCGEWEzqU9P1Byo+k42IRGuKnj0na50CadVpMIHdGMZuDGLGdZSVIc52grmMu55rjTf5OoX9j+LueZRCc//MpkhbPMEFDHZfw8oLfooV7e3zONBTpzXU/Bg/TihlbdaW8hQzNl4rG5IFVWhOpNWmvRdCqR+cxRk2CyGEEEIsdRKiCiGEEGJBC2PFRCNkqBowWgvwI0XGsejIuzinM336GGaqTmv7MYNxDA2JWyDKr1i009FPm1ZkxrdR2P8Y+X2P4jaHZjYF2uGHajNbsm+l45yruGp9Oz2n2khpnmmdhvXNKKaYcVjVUaCcd3FauTREWIfGGLh56N4EbSvSx0IIIYQQYsGSEFUIIYQQC45SmoofMVoLGaz4VP0IyzQpZmw68nM0zVklWOEkdmMIpzGEIVWnoBXZkRdoG3ic/P7HcPzRmU0N7fGQupgH9JVEK67kZ89r4/2di7hLvIZaENOMEvKuxYbuAh15D6eVYXDUTMNT24Ouc6DtrLQKVQghhBBCLHgSogohhBBiwWiEMeONiIHJJuONiEQp8q5Dbyk7N02imKo6bY6mVafhBIbWJF4J5S3TqlMVkxt5gdy+R1m77zEycWVmU1VneVC9hX9JruRF9xLeubHIRzY4tGcWcdMjnX7f1cOYrGuzritPR95t7bT9OID6CFgOtK+F8qp0/VMhhBBCCLFoSIgqhBBCiHkVJYqJRsRwzWe4GtAMEzK2RXvWxW1lkHUolaRrnTaHp6pOGyh7+VadGklEdngLhf2PUjjwE6yoOrOtQp5/jS/jX9SV/EhdxMbuDD9/rsv/e6WNPUfB9pnSDBNqQUTWsVnTkaer6LU2PE1CqI+lj9tWpeFprqN15xdCCCGEEGeMhKhCCCGEOOO01lT8mPF6wMBkQMWPMA2DYsamPetizFEFqBE1DlnrdALDgMQtorz+ZVd1asQ+uaFn0jVOB57Aihsz22pmifvjy7kvvpLH1flYls1Pr3P483Nc1pcX8ZT9KX6UUPNjXMdkVXuOrqJH1mnh61JxWnmqNRR60+rTXMey+x4TQgghhFhKJEQVQgghxBnjRwnjjZDBSZ+xRkgYawqeTU8xM2fT9WeqThtDOM0hjKiJcjLEuS4wl9etkBVMkht8ivzAE+QHn8JMgpltDaeDH5pXclf1cp5QG1GYdHqa2zZmeNcGl6K7+APAIFJUgxDHslhRztJd9Mi5LQ5PG2OQRFPh6RrIdYG5iJc7EEIIIYQQgISoQgghhJhjcaKYbEYMVwOGawGNMMYxLUpZB8+eu6rGtOp0FKd2IF3rlOmq0/LyqQjUGrfyBvmBJ8kPPkFmbBsGemZzmO3huexb+dLkFfxbdT2aNOy7ot/ivRtcSnGVTavduQu4z5AwVlT8CNs06Ctl6C5lKLgtvA1WCTTH07VPc11peFroAXPxV+0KIYQQQoiUhKhCCCGEmBN+lDBcDdg30aTqx2itKWYc+kvZOZuuj4oPqTodPlh1ml0+VadGEpIdeT4NTgeewGkOz9rut21gf/kyvtW8lDv2r8IfT/8tcg78zDqX953tcFbJIlGabXvm4xW0ThxrJv0Q0zToLXp0FzMUMy38PtAKmhMQNSDbDj3npxWo1vL4XhNCCCGEWE7kDk8IIYQQLeVHCUMVn73jTSp+RM6x6cq72NZcNYmKsIIKVjCO3RiaaopkkLglVKZ9bq65wFjNUfJT0/Rzw1tmTdNXpkuj+2KqvVfyI+MSvv5GiWe2JTPb15RMfv4clxvXOuScxV1xOi1ONFU/QmvoLHj0ToWnLcvutYZgEvxqGp52nQOFPrDdFl1ACCGEEEIsNBKiCiGEEKIl/ChhcCo8rfoxBc+mvy2LORdVpyrCCiaxggmc+hBmXAUNiZMjyi6DadRa4U28PrW26ZNkJrbP2hxlu6j3XkG970qG2y7kX3aZ3Ls1ZKCugQTTgKtX2Pz8uS6X9FhzVxl8hiWJpuJHKA0deZeeokdb1mnt6g1+BfxJ8ErQdxGUVoDttfACQgghhBBiIZIQVQghhBCnpRkmDFaa7J3wqU2FpyvaMq0P5qaDU38MpzGy7IJTI/bJDW+ZaQpl+2Mz2zQGfvu51PuupN53BWFpHbsqinteC/n+IxH+VOFp0YV3rXf5ubNd+gpLp9mRUlDxI2KlaM+59JYytGWc1vVz0grCejp13y1C7wVpeOpkW3QBIYQQQgix0EmIKoQQQohT0ghjBid99k00qQUxRc9peXhqJCFmWHlTcGqQuMsjOLUbQzNNobLDz2OqaGabsrPUe95CvfdKGr2XkWTaSZTmJwdi7nmmwbODB6fsr2szef+5Lu9Y45Cxl0bV6bRmkFALI9qyLv1tedqyLqe9coRWEDXTtU6jIG1E5uSheyO0rQQ335KxCyGEEEKIxUNCVCGEEEKclEYYMzAVntbDmKLrsKKtdc2ijCTECiYxg3GcxjBmVAMgcfNEuR4wlnBwqhMy46+m1aYDT+JV3pi1Ocr1Uuu7kkbflTQ7L0RbDgDVUPO9VwK+89r0lH3SKfsrbX7hHJfNS2jK/rQ40Uw0Q1zLZG1nnu5iBsc6xdd4xNA0B5l26OwCrwhuAZxMa1+EEEIIIYRYNCREFUIIIcQJqQcHw9NGGFPKOKwotSY8nQ5OLX8cu/mm4DS/xINTwAwrtL3xb7Tt/Gec5vDM8xoTv3MTtb4rqfddSVQ4i0MX+Nw1maRT9ncePmX/fee49OaXzpT9GRqqQUwQxXQWMvSXMxS9k7ylldBUCCGEEEKcJAlRhRBCCHFMtSBmYLLJvokmzSChLeuyspw77fMeMTg1DBJneQSnAO7kTso77qO452FMFQKQOHkavZenjaF6L0O5xVnHzEzZfzVcNlP2p4WxYrIZkXMtzu4p0pH3TmzqvoSmQgghhBDiNEmIKoQQQogjqvoRA5M++yeaNCNFW9aho/30upAbSTDTHMpujmBG9WUXnKIS8gM/ofz6d8iNvjjztN+2gYkN76O28jq05R52WDXUfG9HeNiU/WtW2rx/iU7Zn6YUVJoRSmv62zL0tWXIOsf4XpHQVAghhBBCtJiEqEIIIYSYpeJHDEz4HJhs0owSylmXjvyph6dHCk61YaCWU3AKmGGVtl3/StuOg1P2tWFSW/FTTKz/OfyOTbOm6k878pR9g3etd5bulP1DNMOEWpA2jlpRzlLOOoe/TVpPBaYSmgohhBBCiLkhIaoQQgghAJhsRhyYaDJQ8QniFoSnsY9T24dTP3BIcFogyveCsbSDv0O5k2+kU/b3PoyZBAAkbonJtT/L5Lp3E2e7DjvmaFP215dNfv6cpT1lf1qcaCabIbZlsqYjT0/pTY2jpoPToApJDK6EpkIIIYQQYu4s6RA1DEP+/u//nq9//ets3bqVwcFB2tvbWbduHTfddBO33norXV2H/+Jyqu666y5uu+22kzrmU5/6FF/60pdaNgYhhBDiZE02I/ZPNBicDAiTdNp+52mEp6gEuzmEO7kTK5gk8UrLLjhFJ+QP/ITyjvvIjbww87Tftp7J9T9H9azr0dbh73Et1PzL0absn+uyuXvpTtmfodN1eJtRTFchQ39bhmJm6pb10OBUJWm1aXEFFHog05YGqUIIIYQQQsyBJRuivvLKK9xyyy1s2bJl1vMDAwMMDAzw+OOP83//3/83d955J+9+97vnZ5BCCCHEPKr6EfvGmxyYbBLGmnLOodM9vTVPLX8cp7ILpzGIsjNEhRVHnKK+VJlhldKuf6O8459xmkPA1JT9/muYWP9e/M4Ljvh+hInmvu0hX9saUE37S1F0Dd69weHnzl76U/anTTeOyk41jurMe1iGhrB+hOC0GzJlCU6FEEIIIcQZsSRD1L1793LjjTeyf/9+AAzD4Prrr2fDhg0MDw/z/e9/n2azydDQEO9///v53ve+xzve8Y6WjmHjxo3ceOONx93vmmuuael1hRBCiONphgn7JhrsG2/ixwntWY+uwumtS2rETZzqHtzaXlAxUa4LTKdFI1743MoblHd8l+Keh940Zf9nmFz7buJc9xGP01rzyN6YL23xOTBVebqmZHLTectjyv40rdOKaKU0/W0efaUMWQKoj4OKp4LT/qmK07IEp0IIIYQQ4oxbkiHqRz7ykZkAdc2aNdx7771cfPHFM9tHRkb48Ic/zIMPPkgURXzoQx/i9ddfp1wut2wMb33rW/mLv/iLlp1PCCGEOF1BnDAw6bNnrEEtiGk7zTVPAVAxTmMQd/INrLBKlCmjnWUScOmE/IEnpqbsPz/zdFBax8SGn6N61tuOOGV/2ksjMX+zJeClkXTN046MwW2bPd651sEyl0d4CuCHCdUgppSxWJGHdrOG0ZyQ4FQIIYQQQiwoSy5Evf/++3nkkUcAcF2X++67j4suumjWPl1dXdx7771s3ryZHTt2MDY2xv/8n/+T3/u935uPIQshhBBzKkoUQ9WAPaMNJpohBc9hRVv29NbW1BorGMet7MJuDKGcLGGhf1lM3bf8cYp7HqK8859xGoMAaExqK65iYv37jjplf9qBmuLLz/n8+54YgIwFN2/y+OB5Llln6b9/05JEM9kIcfBZ60Z0Z00ctwA5CU6FEEIIIcTCs+RC1L/8y7+cefyJT3zisAB1Wj6f5wtf+AIf/ehHAfibv/kbvvCFL2DbS+4tEUIIsUwlSjNSC9g91mC0FpJzLPrbspinGXQaUQO3uhuntg+0Isp1g7mEf37qhMz4q+QGnyY/+BSZie0zmxKnmE7ZX/du4lzPMU9TDTV3bw2497WQSIEB/Mx6h09c5NGVXR5rngKgNI1Glbg5SU/GpLu9nULHWRKcCiGEEEKIBW1J/cZTq9V48MEHZ76+7bbbjrn/Bz7wAT7zmc9Qq9UYGxvjhz/8YcvXRhVCCCHONK01Y/WQPWMNhqoBjmXSV8qc/hRxFePUB3And2JGdeJsO9rOtmbQC4wVTJIbeob84FPkBp/Biqqztvvlc5hc+y6qq449ZR8gmmoa9dWtIdUwXff00l6LX3lLhvXl01uLdtHQGiNuovwqtUYDJ1vkrFXr6epbhZVrl+BUCCGEEEIseEsqRH3ssccIgrSZQz6f54orrjjm/plMhquvvpoHHngAgB/84AcSogohhFjUJhsRe8YbDEz6AHQVPBzrNKsctcbyR6em7g+j3DzRUpu6rxXexGvkB54iP/Q03vhrGOiZzYmdp9F7KfWey2j0XkaSaT/+KbXmR3tjvvRcwP6aAmBtm8mnL8lwRf+SugU7KiNuYoVVSCImYwffaadj/YWs7F9BvlCa7+EJIYQQQghxwpbUHfzLL7888/iiiy46oan5l1566UyIeujxp2tiYoJ/+Id/YOvWrUxOTlIqlVixYgVXX301F1100emtQyeEEEK8SS2I2TvW4MBkkyjRdORdPPv0qxzNsIZT3YNT2wuGQZTvBXNpVE+aYYX84DPkBp8mN/Q0dliZtd1vW0+j9zLqvZfjt288qdf9ymjC3zzr8+JU06j2jMGtF3n8zLrl0TTKiH1sfxxtuVTtTkbtMsXeTtb3d9Nd8OQ+SAghhBBCLDpLKkTdtm3bzOM1a9ac0DGrV6+eefzKK6+0bCz33nsv99577xG3nXPOOfzmb/4mn/zkJ+WXCCGEEKelGSbsn2iyd6JBM0zoyHlk3RaEnCrCqe3HrezCjBvEmQ60nTn9884nrfAmXp+aov8UmfFX31RtmqPR85Y0OO25jCTbedKXGKgpvvy8z8O706ZRngUf3Ohy80aP3DJoGmUkIZY/BoZFPbeSYbMHMm2s7shxVke2JcG+EEIIIYQQ82FJhaijo6Mzj3t7e0/omL6+vpnHY2NjLR/Tkbz22mv88i//Mvfccw/f+MY3yOfzZ+S6Qgghlo4gThic9Nk93qTmR7RlXTrKx16b84Rojd0cxp18A8sfJfGKRIUVp3/eeWKG1am1TZ8mN/QMdjAxa3tQWku99/K02rRj4yk3yKqFmq+/FPBPrx5sGvXOdQ63XeTRlVsGTaNUhO2Pg1b4mR6GzF4it0xPW4bVHTnKOXe+RyiEEEIIIcRpWVIhaq1Wm3mczZ5Yo4tD9zv0+FO1evVqPvShD3HjjTdy0UUX0d3dTZIk7N27lwcffJA/+7M/m6l4/e53v8tHPvIR/umf/gnTPP4vWEEQzKz5ClCppNMOoygiiqLTHrsQQoiFL04UI7WQPeMNJpsRedemr+BgGKCS+LTObYY17NoenNoA2jDxc71gWKD08Q9eKLTCm9xBYehp8oNPkx3fhoGa2ZzYWRpdl1CbqjaNs12zjz/J1xorzT+/HvG1rSGVqaZRl/RY3H6xx4b2tOoyWUzv3yGmx33M8asEO5jASCIaXhcjVjeB2053MUN/OUtHzsEwDLlPEUIIIcRhpu8P5D5BzLcT/R5cUiGq7/szj133xCoePO9g1U6z2Tyt67///e/n4x//+BED0XPPPZdzzz2XT33qU3zmM5/hzjvvBOA73/kOd999Nx/96EePe/7f//3f53d/93cPe/6hhx4il5OutkIIsRyFwHjLz+pMfa4cc6+FwFQh5cZOOuqvTX1sx4urs/apZFYyWLqYodJmRvPnoqerTUfgVN89reGFcYPv7DIZ9tNp+r1Zzc+vUZxfjolrAdtO/2+zC8L2fRPH2cMEPKA69QG7pz6EEEIIIY5nuk+NEPOl0Wic0H5LKkTNZA6u1RaG4Qkdc2hl54lWrx5NuVw+7j6u6/KlL32J7du388gjjwDwh3/4hycUov7Wb/0Wn//852e+rlQqrFq1ihtuuIHOzpNft00IIcTCp7VmvBGxf6LJUNXHMU3KOffw5kRagU4wVAJoDJV+jdbp8zoBrTC0etNzMbY/gRWMk7gllFuYl9d5omx/lOzYK2THXiY7/gqZidcx9OwKXGVlqHdfTL3nMmo9lxHnegDonPo4HdVA8/xwzD3bI14YTptGlT2Dj13o8rNLrGlUojTb901w9srywdelNVY4iRk1CJ0SI3Y/TbeDzlKO/nKWzpyLuYTeAyGEEELMnSiKeOCBB3jnO9+J4zjHP0CIOTI90/t4llSIWigc/MXvRKtKD93v0OPnkmma/M7v/A4//dM/DcCLL77I3r17Oeuss455nOd5sypnpzmOI//DEUKIpURraI5TqTXYP1FneLKBgWJlxsLRCUY1xlAxqAhTxaBjDDUVjJJ+Bg1KpcHpTPMkTbpa59Rjw0Bjoi2XpNiPYZgsqLY/KsGrvEFm7GUyYy+THXsFpzF42G6xV8bvOJ9mx0b8zvMJ2jagrYM/F0/nNVUCzQvDMc8NJTw3FLNzQs28m64FHzzP5eZNHvkl3DTKMg0sA8yoihXUiJwig/nzqLuddJQKnNeeo7PgLakAWQghhBBnjmQaYr6d6PffkgpRD63GHBw8/JesIxkYGJh53NHR0fIxHc3111+P4zgz6y68/PLLxw1RhRBCLAzNMKEZJWit0UwVdk5Ha5pZz+mZr9Ptenq3Q7YrrQ+ew69gTe7GqO6n2mgSJ5r+jI1tWRCANgwwTDBMNOljPfWBaaMMEzDAsGbtuxiYYY3M+LapwPRlMuOvYsaz/yiqMQlLa2h2no/fsZFmxybiXC8YrQnwjhWaTltdMrm0z+ZD57n05BfHe3s6zLCGG1UJ7RzDmfVU3W7a20ps6MjRJeGpEEIIIYRYJpZUiHreeefNPN61a9cJHbN798EVuzZu3NjyMR2N4zh0dXVx4MABAEZGRs7YtYUQQpyayWbEUMXnwKRPM0zSrHJq23TQZkxVe86u+Zz6SgOGBm3MOhbATCIyzf3kanuwEp8o04HX1knBsdDAkltuX2uc+n4yU1PzM6Mv4Vb3HFI1m0rsHH7HRvyOTTQ7NhG0n4tyWrcO+ImGphf3WFzcY7O5x6I9s/SDUwAjSteG0nHEoLeGSbeHcrnMRe05ugoutrU83gchhBBCCCFgiYWomzZtmnn8wgsvEMcxtn3sl/jMM88c8fgzoV6vzzzO5/Nn9NpCCCFOjFKa8UbIwKTPUNUnTBSljEu5Le06fvoXSLCbw7j1nVjhJEmxhHJ7T/+8C4yRBHgT28mOvjwzPd8OD197KMz3zwSmfscmwtIqMFq3yEAl0Lx4SGi6Q0LTwxixj+2PE+EAJruy51Fq7+aCjhzdRQ9HwlMhhBBCCLEMLakQ9ZprrsHzPIIgoF6v89RTT3HVVVcddf8gCPjxj3888/U73vGOMzFMAHbs2DFr4doVK1acsWsLIYQ4vjhRjNZD9k80Ga2lzQrbsg4Zp3WBnuWP41R24TQGUbZHVOhbNFPvT4TdGKa84z4yo1uP3ADKdAjK56RrmXZswu/cROKVWzoGCU1PnJFEWP4oWhuMOr2MWV3AdjauWUl/e17CUyGEEEIIsawtqRC1UChw4403cv/99wNw1113HTNE/fa3v021WgXS9VCvv/76MzJOgDvuuGPmcVtbG5dccskZu7YQQoij86OEkVrAvokmE/UQx7LoyLstDZDMqI5T3YNT2wdaEeW6wFxCi+lrTXH3g3S/8EWsuDHz9EwDqM60yvTNDaBaoRpqXhg68dD0om6LjuwyDwdVjO2PgVKMW52Mu33k23o4t81ly77t9LdlJEAVQgghhBDL3pIKUQF+9Vd/dVaI+rnPfY4LLrjgsP0ajQa//du/PfP1pz/96eNO/T+WWq1GoVA4oX0fe+wx/uiP/mjm6w9/+MOndW0hhBCnrx7EDFV89k361P2IrGPTW8q2tGmOkYTY9QO4lV2YUYM42462sy07/0Jg+eP0bPlzCgNPANBsP4/J9e9teQOoQx2oKR7fF/HYvpgXhhPUm1JTCU2PQiVYwThGHDFptTOe7ccr9XBuZ4GekoepFVvme4xCCCGEEEIsEEsuuXvPe97DddddxyOPPEIQBLz3ve/l3nvvZfPmzTP7jI6Ocsstt7B9+3YgrUL9zd/8zSOe74033mDdunUzX995553ceuuth+33rW99i7/6q7/iP/7H/8jP//zP09bWdtg+vu/zxS9+kf/6X/8rvu8DUC6X+Z3f+Z3TeclCCCFOkdaaSjNmoNJkoJI2iyp6Dv1t2dasdzpzIZWuezq5C8sfJXELRMUltoyL1hT2/ZCe5/4aK6qiTJuxjb/E+Nk3gdm6JRAAlNZsG0t4fF/M4/ti3phUs7avKppc3Ds1PV9C05TWGCrCSEKMJMBMQtCaSbPEWGY9blsfGzoL9JQyM0tWRJE6zkmFEEIIIYRYPpZciApw9913c+WVV3LgwAHeeOMNLrnkEt72trexYcMGhoeH+f73v0+jkU4vtG2bb37zm5TL5dO+7pNPPsknPvEJbNtm48aNbNy4kfb2dpIkYd++fTz++OOz1kHNZrPce++99Pf3n/a1hRBCnLhkqlnU/okmI7WAKNa0ZR06yl7Lr2UGE7iV3TiNA2jTmVr3tLWh4nyzgkm6n/srivsfBcBv28DgZb9BWFrbsmsEsWbLUMxje2N+vD9mzD9YbmoasLnb4uqVNlevdOgvLPPQVCVpUKrCqdA0BsNAWw7a9IjcMhWdo6ZdnLY+1ncW6T0kPBVCCCGEEEIcbkmGqGeddRY/+MEPuOWWW9iyZQtaax5++GEefvjhWft1d3dz5513cuONN7b0+nEc8+KLL/Liiy8edZ8rr7ySu+66i02bNrX02kIIIY4uShSjtZB9Ew3G6hEA5axDptD68MiIfZzaXtzqHowkJM52tXz9z4Ugv/9xep77S+xgAm1YjJ33i4ydezOYp3+LMeErfrI/rTZ9eiDGTw5uy9lwRX8aml7Rb1PyWr9MwIKnNcZMUBpgJhGg0YYFloeyPOJsN8opoOwsdWVTiWwSw6KUdVjflqGnmCHrSngqhBBCCCHE8SzJEBVg48aN/OQnP+Eb3/gGX//619m6dSuDg4OUy2XWr1/PTTfdxG233UZXV1dLrnfLLbdw7rnn8thjj/HjH/+Y119/nZGREUZHR1FK0dbWxrp167jqqqv44Ac/yLXXXtuS6wohhDg+P0oYrqbNoiabEa5l0tniZlEzVIzTGMSdfAMrrBBn2lHZztZfZ56ZYY3u5/+G0t6HAAiKqxm87PME5bNP67x7Kgen6b80Ont90+6swVUrba5Z6bC5x8K1llFwqmLMqbDUSEJMlaANA225aNMjyXQSuSWUnUXZGbSVQVsekdJU/ZhmkJB1Tfo7PLqLGdpzDrY0ixJCCCGEEOKELdkQFcB1XT7+8Y/z8Y9//JTPsXbtWrR+c1/fw3mexzXXXMM111xzytcSQgjRWlU/YqgScGCySS1IyLkWvcVMS5tFzdAayx/FrezCaQ6TODnCwoo5aaQ033KDT9H77J9h+2NoTMbPuYmxjb90SpW2idK8PHowON1Tnb0O59ntJlevsLnmLIcNZbO1a9UuUGlQGkyFphFojTYttOWhrSxxrg/l5FF2Fm1nUFZm1rqzWmvqQUK17mMaBm05hw09edpzLnlvSd/6CSGEEEIIMWfkTloIIcSSorVmohExUGkyWAnwI0UpY7OiLTNnAZwZVnGqu3Fq+8EwCHO9LW+mtBCYUYOuF79E265/AyAsrGTw0t/A79h4UudpxppnBmIe2xfzk/0xk8HBP1baJlzcY3H1SoerV9j05Jd+taSRBJhxEzP2MbRCTU/Fz3Sh3BLKzswEpto6+rq9Yayo+BFhkpBzbdZ25ukqerRlnbn5w4EQQgghhBDLiISoQggh5lScKOpBQqI1BmlhpoEBxvRjMAxj1rbprPPQr9+8H1NfT0uUZrQecGDCZ7gWoFTaLKoz3/pmUdOMJMCp7cet7saIm8TZzmOGXItZdvg5ep/5U5zmMBqDiQ3vY3TTx9B25oSOH2sqfjy1vukzgzHhIeubFhx46wqHq1faXN5nk3eXduBnJCFm3MSImxhKoW0XZecISv0or4Sy0yrTEwnilU6n69fDCNsy6ci59JaKdORdaRQlhBBCCCFEC0mIKoQQoqW01jSjhJofM9GIGK2F1KOYJNGHhaSzglQOCVentx0SoDIdoHJ4CGuaBonSVJoRlmHQnnNx7TmsYFQxdnM4Xfc0mCTxSqhC+9xdbx4ZsU/X1rso7/wuAFGul4FLfwO/68JjHqe0ZseE4on9MY/vj3llNJm1vS9vcPVKh2tW2lzYbWEv4UpJI4kw4kYanGqFNl2UnSUqrU0rTZ0CysmBceLfs36UUGlGREpRzDic3V2kq+BRytrLYskDIYQQQgghzjQJUYUQQpy2KFHU/JhaEDNc86k2Y5qRwjYNMo5FRy5t4qS1RgPTS01Pf83Ucxp9yLb064OPgannlD64H4COFYZh0F3wWt8sR0VTU62bmFETM5zECmuYUQ1le0SFvpMKvxaTzOhL9D7zJ7j1AwBMrH0XIxd+Em1nj7j/WFPx9EDM0wMJTw/ETASz1xTf2GFy1VRwurZtCa9vOv09EzUxdII2nTQ0La4h8drS9Uyd/El/3yRKU/Uj6mFMxrboLnn0ljJz/0cDIYQQQgghhISoQgghTp7WmkaYUPVjJhoho/WQZpgQK03GNsm5Nu25w0Oy6en4zDy9sEI0IwkxpgPTuIkZTGBF9XTNShWlAbDloiyPKNcN5tL8MWokIZ0vf4Xy9nsw0ETZLobe8us0et4ya78w0bw4nAamTw3E7JiY3RQqY8MlPTZXrbB560qbruwSDfpUPPM9Y6j4kND0LBKvPNUEKn/K6+Q2wpiqH6O0ppR12NRZoiPvUvCk6lQIIYQQQogzZWn+9ieEEKLlwlhRC2IqzZCRWkgtiAniBNMwybsWXQVvUTWvmRWYRg2scBIzrKWd0VUMBijLRVsZlFcmPoXO84uRN/4qvc/8CV51DwCTq3+akYtuRzl5tNbsqabVpk8dSHh+KMafPUufc9pNLutL1zY9v8vCsRbP98QJ0Uk6PV+FaSOoJEabNtrOEeVXoLwyiZNHOYXTai4WJYqqH9OMErKuyYpyhu5ihvac0/pqayGEEEIIIcRxSYgqhBDiiLTW1IJ0iv54PWSsEdEMEhSKjG2Td+05bdrUSkYSTAWmPmZUwwomMaMGRuJj6AQwpgJTj8RtB3N5BKazqIjOV75B+2v/gKEVsdfO0Fs+x0DHFTw7EPP0gSZPDcQMNWZP0e/IGDOh6aV9FuXMEgj4tEpDdhVjqDANTXVaZasNAywXZbrEuT6STPshoenp31ZFiWKkFmAaBm05hw09eTryLjlXbtmEEEIIIYSYT3JHLoQQYkYQpw2hKs2IkXpIzY8IY4VtplP0u4sLvNpU63TqfexjJE3MqI4dTGBEjTRI1QkY5iGBaeeSnZJ/MtzJHfQ9/Sd4lZ0A7O2+jr/Lf5JHXsixbayKOiQ3dUy4sNvi8j6by/tt1i3WtU21wlDRVFXp9EdCuuquCZaTNoBySqhcHuXkZpZy0JaHNt3TqjQ9kkozohbGrCxnWVHO0pZ1FvZ/b0IIIYQQQiwj8pujEEIsY0ppamFMzY8ZrQdMNiIaYYLWkHUsihkHz25tUHTKVDxVGRiDjjFUkgZfOplak9JPK0wTHxI/7YJumGngZXkkbrHlodeipmLc6m4K+x+n/dV/wNQxFaPIb8ef4p49V07tlM7VX12anqJvsbnHJmMvkmBP64MBaRJOPY6nNhpoy0WbDtrJE081e9Lm1BIOlou23DMSsidKM1ILcCyD8/tLrChnJTwVQgghhBBigZEQVQghlqFmmLB/oslwLaARxoSxxrEMcq5NT/EMVb+9KQQ1VIwxFY4yFXyZiY8RhxgqSENTncD0/loDGrQBhkYbFtpySSwP7RXBkMB0hlY4tX1kxl8jM/Ea3vhruJM7sFQ4s8v3kiv4/0SfZJQ2ii68pdeemabfk18EU/R1ghlPLduQhIAmDUodtOGgrSxJtovEKcwE62llqTuvyzc0wpjxRkR30eXs7iJtuWW4lIQQQgghhBCLgISoQgixzARxwraBCgcmfQqeTVvGxbVbHJKpZGotyQAzCdIqwCSaqhINMKfXm5wVih7a2V2jDRMMC21aaUBqWCjLAcNGm6aEpEejNXZjkMzEa2TGX8ObeA1vYjtW3Dxs14rO8qJax9+rd/Ba+Vre0+9wWZ/FeR3Wgq+EnGkMNtUILK06zqDcNqJMO8rOTFWVpmGpttz5HvIsWmtG6yGJ1pzdk2d1R771/x0KIYQQQgghWkZCVCGEWEYSpXl9qMZAxae/7TSnDB8pKI2bWGEtXZNUh5CEUxWjUw15DBNtWGDaaShqujOPZar9qbGaozPVpZmJ18hMbMcKK4ft5+PyglrLC2o9z6n1vGxsoLdvJdeu9ri136bgLuDQdLrKNPExY5/pClNlZYjyK1BeG8rOTa1buvCbnYWxYrgWUM45bOgu0F1c+GMWQgghhBBiuZMQVQghlgmtNTtHauwZb9BTzJxYgDorKA0PdrmP6lhRcyoond25fHqdSWXl0F6bVIy2kBlMkpnYjjdVZZqZeA3bHztsP2XY7HXW8ES4jp9E63lerWe7XoljWVy5wub6VQ6f6rfJOgszOE0rl9PA1FAJGgPsDIlTIiquQTk5lJ1H2dlFF75PNiMaYczqjizrugpk3cU1fiGEEEIIIZYrCVGFEGKZ2DveZMdwnfash2MdMm1YqzQcPU5Qauo0zDosKHWdRRdkLQZm1MB7U2DqNAYP209jEhRXM5DdwJPReu4dX8MTzVWEzXRtzYwNV62y+cVVDpf322QXWlMonWDEAWbiY8ZB+pTpoOwMcb6fxG1DOWlgqu3MPA/21MVJWn2adS0uWNlGfymDucCXTBBCCCGEEEIcJCGqEEIsA0MVn9eGqhQ8m6xrYYY17Pp+zKiOGTcx1REqSk1nqvGOBKVnkhlW6dny5xT2P46BPmx7WFiJXz6bZts5bGU9/zy+iof224wNH9w3Z8N1Kx2uW5U2hvIWUHBqJBFG0sSMfcwkRhkm2BmUUyAorEa5+XRqvp1bMt9z9SBmohnSV8qwvqdAKSPNo4QQQgghhFhsJEQVQoglbqIRsm2wimWYFDMORuzjjW/Dbgym1X2WS2JLULoQZMZeoe/JP8RpDgMQZXvw288mKJ+L3342jdIGnh3P8sM9EY++GDMRTAenmrwD16x0uH6VzaV9Nq61MIJTIwmnwnofYCqczxDn+ki88tTU/NyirjI9GqU1I7UAw4Dzeouc1ZGbXQUuhBBCCCGEWDQkRBVCiCWsHsS8MlAliBS9pQyoGG9iO05jiLDQL+uVLhRaU379Xrq23omhE8J8PwNX/CZB+WxipXl2MOGRnRGP7o2phI2Zw4quwU+ttLlulc1bem2cBRKcAqA1VjCBGfsk2U6CwlnptHwnv6SqTI/GjxJG6wEdeZcN3QU6C9I8SgghhBBCiMVMQlQhhFiigjjh1cEqk42I/rYMaI07uQOnuocw3yMB6gJhhjV6n/1fFA48DkB1xU+xd/PneHrM44fbmjy+L6IaHty/zZsOTh0u6bWwF+C6mkYSYjdHUE6RZvdm4lwvGMunAnO8HhIkCWs786ztypNx5L81IYQQQgghFjsJUYUQYgmKE8VrgzUGKz59pSyGYeBUduNN7iTOdoApazIuBN74a/Q/+Qc4jUGUYfNAzyf42/o7eeE+RZA0Z/YrewbXrrK5fpXD5m4LawEGp8Cs6tOocBZh2zqUk5/vUZ0xUaIYrgbkMzYX9rXRV8pgGAv030oIIYQQQghxUiREFUKIJUYpzc6ROnvHG/QUM1imgd0YwpvYTuIW0HZ2vocotMZ45busePXL2Dpmn+7mM8Gv88Ku9UDa3KsjczA4vbBrAQenU4wkmqo+zeN3XUSU71tW1ac1P2bSj1hRzrC+u0DBk1ssIYQQQgghlhK5wxdCiCVm73iDnSN1OvMejmViBpN4Y9vQhoFyi/M9vGWrEmieG4p56UCFdx34K27UPwHg35LL+M/RrxDaBd7aY3Npr8Vbem3WtpmLporRCiYwoyZRYeWyqz5NVNo8yrYMNvUXOas9t+ADbyGEEEIIIcTJkxBVCCGWkMGKz2vDNYqeQ8axMOImmbFtGEmTON8338NbVsJE8+JwwrODMc8Mxrw2pthkvMFfOv+LdeYgkba40/sldp/1c/y3PoeNndbCagx1AtLq02GUvTyrT5thwlgjoKvgsaG7QHvene8hCSGEEEIIIeaIhKhCCLFEjNdDtg1UcQyTQsYGFeGNbcMKxtJwS8wppTWvjyueGYx5ZiDmxZGEMJneqrnF+gH/zfk7PCJqbjf7L/8/uKFn03wO+bRYwSRm1CDKryBsW49yC/M9pDMiUZogTmiECYnSrO8qsKYrh2dL8yghhBBCCCGWMglRhRBiCagFMdsGqkSxoqeUAa3wJl7HqQ8Q5XuWVXXgmXSgpnhmIK003TKYUAn1rO0dGYOreyJ+Pfxbzp14BIBa7xUMXvZ5jMW6tIKKcBojKDuL33UhUa4PzKUbIEaJwo8SmlFCrDQGkHEsSlmbVe05uoveoll2QQghhBBCCHHqJEQVQohFzo8Stg1UmPQj+ksZANzKbtzKLuJcJ5jyv/pWUVrz/FDCw7sjnhmIOVCfHZrmbNjcY3Npn8WlvTZns4cVT/4Bbm0v2jAZPf/jjJ9906INtc1gEitqEOX707VPF2sQfBRaa4I4DU39SKG0wrZNMrZFT8mjnHXJezY51yLjLN3gWAghhBBCCHE4+c1aCCEWsShRvDZYY7gS0NeWxTAM7PoA7sR2Eq+Etrz5HuKSMFRX/NvOiH/dGTJwSHBqGbCp0+LSvjQ4Pa/Dwp5qKlTa9QDdz/81ZhIQZToZuOL/wO+8YL5ewumZqj7Vdha/8wKifP+SqD5NlJ4KTBOCWAEaz7HIOhZ9bRkKGZuca5N3LWxrcQbfQgghhBBCiNaQEFUIIRYppTQ7h+vsm2jQU8pgmQaWP05mfBvacpZVh/S5ECaaR/fGfG9HyLODCdPRac6Gt692uOYsm4u6bXLO7KncRuzT8/xfU9r9fQDqPZcyeNl/IvHazvAraA0zrGCHNcJcH2F5PcotzfeQTlmUKJphGppGWmEbJp5j0pZzaM855D2HvJeGqDJFXwghhBBCCHEoCVGFEGKR2jPeYOdIjc68h2OZmFEdb+wVUBFJrme+h7coaa15bVzxvR0hD+2KqEUHt13cY/Ez6xyuW+WQsY8csDnVPfQ/8ft41d1oTEY3/RLj535ocU7fVzFOYxhtZ2h2nE9UWLmoqk+V1gSRwo8TgjhBaY1jmWRtm/5yhlLWIe/a5DxLmkIJIYQQQgghjktCVCGEWIQGJn1eG6xRyrpkHAsjCfDGX8UKJ9Op1uKkTPiKH+yK+NedETsm1Mzz3TmD/7DO4WfWufQXjh2EFvc8RM+Wv8RMfGKvnYHL/wvN7s1zPfQ5YYZV7KBCOL326SKpoo0SRS2IaUYxYJCxTXKezYpyhmLGIeta5F0by5QqUyGEEEIIIcTJkRBVCCEWmbF6yLaBCp5tUvBsUAnuxHbs+gBRvg9kGvIJSZTmqYGYf90R8fj+mHgqO3VM+KmzbH52vcslPdZxAzcjCeh+/ou07fpXABpdmxm4/L+QZNrn+iW0nkpwmsNoy6XZOV19urBvFRKlqQUx9SDGMg0KGZvVHUUKmbTSNOOYMjVfCCGEEEIIcdoW9m9GQgghZqn6EdsGKiQKOoouaI1beQOvspso172oplvPl72VhH/dGfFvOyPG/INNos5pN/nZ9S43rHEouicWujm1ffQ/8Qd4lZ1oDMbO+zBjGz8MxuL7dzDDGlZQIc73ErStQ3nl+R7SUSmtqQcxtSDGMKDgOpzdU6Aj71LKOlJpKoQQQgghhGg5CVGFEGKR8KOEbQNVqn5MXykDgFPfjzv5OlGmHW258zzChasRaX64J+Jfd0S8OJLMPF9yDX56rcPPrHdYXz654LOw7xF6nv0zrLhJ7LYxePl/ptHzllYPfe6pCLs5CqaD37GJqLgwq0+11jTChGoQo5Qin3FY25mno+DSlnVwrEW47qwQQgghhBBi0Vh4vyUJIYQ4TJQoXh2sMlIL6W/LYBgGVnMEb/xVlJ1FO7n5HuKCo7XmxeG06vTf90T4cfq8acDlfTY/u97hqhU2jnXiVYtG7OPW9lLa9W+Ud94PQKPzwnT6frZzLl7G3NBJWnkaNdCGSZLtXrDVp40wpubHxFqTcy1WtmfoKni0ZR1pCCWEEEIIIYQ4YyREFUKIBU4pzetDNfZPNOktZjANAzOskBl7FdCLpunPmTLSUDzwRtokal/1YJOolUWTn13n8NPrHLqyx6ha1BorGMet7sWt7cWt7sGZeuw0h2ftOnbuhxjd+NHFsYyC1phRHSuqgdYop0hQPpsk00HilhbUa/CjhFoQE8QJWceiu+TRU8xQzjlknIUzTiGEEEIIIcTyISGqEEIsYFprdo3WeWO0TlfBw7ZMjNgnM/4qZlRNG0kJwkTz4/0x39sR8fRAjJpa6jRjw9tXpdP1L+iyZjcYUhFOfQC3umcqLJ0KSqt7seLGUa8VuyXC4mrGz/0Qjd7L5viVnT4jbmKFVUwVk9g5wuJqkkwncaYMpjPfw5sRxopaENOMYzzLpJxz6S0Vacs65D25XRFCCCGEEELML/mtRAghFrADkz6vD9cpZ9106rKK8cZfxW4MExb6YRl1HW9GmgN1xf6a4kAt/by/mj4ebOiZ4BTgom6L/7DO4W2rHPK6jlvbhbP7YGWpW9uLUz+AodURr6UxifK9hIWziIqrCAtnERbPIiysXBSVv0YSYoYVzDhE2x5xtoc410PildF2Zr6HNyNOFNUgphEmOLZBW8ZhfXeecs6h4NmzQ28hhBBCCCGEmEcSogohxAIRJQo/SghiRRArGkHMvvEmGcdKK/G0wp3cgVPfT5jvAWNpNdLRWjMR6Fnh6IG6nglNx3191GMNFBdmxripd5DrSgP0RPtw9u3F3bYXO5g46nHKzqYB6VRIGk1/zq9AWwunSvOEqDitOI2aaMsh8cqE5V6STDvKyc/36GYkSlMLYupBjGUaFDI2qzuytOc8ihkb05TgVAghhBBCCLHwSIgqhBBnWBgr/DghiBRBnFAPYqp+jB8rwjghSjRaayzTJOdYlLJpmOdU9+BN7iTOdCyoadgnI1GaocZUUHpIRemBqY/mVPMnA0WZGh1GlS4qrDEqdFoV+q0KZ7lV+qwqXUaFsq6QVxW8qIqBgkHSjzeJMp1ExYNhaThVXZpkOhd3Na9WmFENK6yjMVBeiaC4hjjTjnJLC+a1Ka2pBzG1IMYwoOA6nN1ToCPvUso6WBKcCiGEEEIIIRY4CVGFEGIOaK0JE4U/FZQGUbreYy2ICaKEIFHEsUJjYJsGrmXi2CblrIttGodNY7Ybg3gTr5O4xQU1HftYqqHmpZGYF4cTto9F1GsVkmaFdl2hw6jQaVRYQYULjQqdRpVOo0KHW6HLrFCmisVRKk/jqY830YZNWFgxVVG6amr6fToFXzu5OX2tZ5TWmHEDM6xiaI1yCgRt60iyXSRu27w1iFJaEyeaWCmiRBMnikRpYqUBTT7jsLYzT0fBpS3r4FhLq5JaCCGEEEIIsbRJiCqEEKdBa51Ov58OS2NF1Y+o+jFhkk7LT5QGDbZp4NgmrmWSc+0TDpHMYAJv7FW0aaLcwhy/olOjtWawrnlxJOaVIZ9geAfdje1sNnZwm7mDDcZ+bEOBe3LnTZw8idtG4pVJvNJhj+M3Pb+QOsy3mhH7WGEVI4nQTo6osJIk252uc2qd5Bt7krTWM4FonGgipWYC0+mo28TAtsC2TGzTpOC5ZF2TrGOTcU3ask66rq8QQgghhBBCLEISogohxAlKlKYRxjSjBD9UVPyQWpAQxoowViQ6rbizzTQodW2Tgmtjn0bFnRE1yIy9ipH4xPne1r2Y05Qozc5JxdahkMmB/397dx5nR1Xg/f9Ty917786+EiAkCARh2GQSlrBoIA7Cg0OAMUF4RFEUnRnFBxdgRv25MOLLYQAFgguLG0NEEIQgssgWQiREAiQhG0k66e703nepqvP7o27fdGfp7iS99/f9el3uqapTVed2Ok3l22d5j+jONUzz1vKP9lqutDYRtXzYy4wDnpsiiJXit7+6DEVLhuy0Bb3F8nPYuSZsL41xYnjxSrzUmPwCUYleu08YkLYHo2Ev0lxgCEyAhYUBHNsiYlu4jk0i6pCIhL8MiOZ/MRDJ96aOOGHPai0KJSIiIiIiw4lCVBGRvfADQ1vOpy0bvurbsjSnvUJvU4Co4xB1bWKuTUm8F+d1DHysIIflZ4g2vIeTqSOXGts71z5AbZ7h7ZocW7dsxtS8Q0Xzu8zkPT5rrSdhZcNKHf6PknaLSZcdjl85nUzZ4WRKD8GLl4/4ULTHAo9I6w6M5RBES0iXHoofKyOIFPXKPKd+YGjL+rRmPbzA4NjhtBKuE4akxfEoyahDPOKE4aizqxd1xLE1h6mIiIiIiIw4ClFFZMTrGJimc2Fg2tQWBqZZLwALIrZDPGJTEo8SdQ9yLsfAK4Sktp8Ly0EWO9eC7bVheVkskyvUyyVHg9W/80fubPNZ//422ra9TaL+XSZl13Ku9R4lVltYoUNz0naSxqJDsUZNx6s4nHTZ4XjJ0YNmUaOhxvLSuOlacqkJ5Ionhz1yD/LPv+P3eNb3ce2wN+nY0jhlqSipaHtYGgam6kUqIiIiIiLSmUJUERlRgvYwKR8oNbRlaWrz8z1M/UJgGvYuje5/oGRMPhTNYflhOGr54cv2WrFzrYXQlMDDMsGuU20HY0cwtkvgxDF2BOy+/zFtjGFHTQ1177+DVfMOlS1rmB6s40SraVelfIaXIUpN4hByFYcTHT2dbMV0ckXj+z3kHa7sXAtOppFsyTQyZdMOuOduYAzp/Pd4xguwLEhGHSqLolSkohTHXVKxns/LKyIiIiIiMtIpRBWRoScIwPhgAgj8fHnPldwDEwam6VxAW9YPF3xq88j4PlnfYAy4jkXctSlxbaKJ9nkc/fwF8q99CIPS7K5epblWbK81DE+NB0EOy4SLSmGHq8cb28XYEYJIKh+SDsxCO7Xr3yS9+Q1SDe8yObuW6Vbdbh8OcjhsjUyhueQwImOmEx1zBNniyYU25wag3cOZk6nH8jJkyo8gWzJ5v4JpY0z4fZ4Le1NbFsQjDqXJCFVFMVIxl1TM0cJOIiIiIiIiB0ghqoj0H2PAD3tg7gpAg93C0A5l34cgF758b1c5CMJrmaAQoAZBQDYwZHNhz7vWnE9rxiPnGXImAAO2bZF0bMpci4hlH+Rwc4MVeIQJqYWxLIztgh3BOC6BHQ+3rcEVWmU9n+3P/IQzmh/dtdMC31hsdiawI3k4QeXhlE44AqfyEIwTLawPlR2QFo8AxuC27QA7QrrqaLwezH9rjCHjBYVe1RhDPOKQirlMqUxQFI9QFHOJRwbX95+IiIiIiMhQpRBVRHqfnwMvDV42/56GbDNkmsDLgfF2hacmH4ha1q7epO1lywp74+3t5ThAhEwAO5pz1LflyHgBYZ7k4FpRIpGwd2nCsWG3vNTrjc9pOUNqGPuWnW2Y527hjOAlAF6KnExz+RHExkynauLhuLEkpR3q79m3V3qd8Ym0bMePFpOpmIEfr9hn1WwhNPXwA4i7NsmYw4SyBMUJl+JYhHjE1nymIiIiIiIifUAhqogcmCDYFZD6+bA00wLZJsjl9wXZXUmcEwEnCm4E7PieoegB3L6uNcvW+jaaMjkSEZd4zKZkL4GpwPNrajlm5bc43nqHnHF45bDPM/rouVQOdMNGsiBHtGUHueQoMuXTCaLFnQ7n/IDWbNjTNAgCIq5NMuoytSRFSSLsaZqMOgpNRURERERE+oFCVBHZt/bh914avEz4yrVBphFyrflj2bA3KYRzZbaHpZGS8L0PAp6mtMfWhjS1LRmijkNVUVwLwe9Dm2d48OUNXFn9LQ61t9JMkg0n3sDoCbMGumkjmuWlcdN1ZIsnkik7DOPGC8dyfsDOliyBgaKYy6TyBGXJKKmYQyrqYtv6ZhcREREREelvClFFhjpjds0Piuk8RL7TPrMr7OyuTuCHPUrbh9/7mXAeUwhDUScahqWRJMTL+m1xpIwXsL0xTXVjBi8IKEtEcR0FSvvyXr3Pb55/k2/nvssou5F6t4q6f7yRaNnUgW7aiGZnm3GyTWRLppEpmwZ2+L9iPzDsbM2S8wNGF8eYWJGkPBnFUWgqIiIiIiIy4BSiigx2vhf2/Ew3QFt9uJBSYUEmv8MCS4YwDG1/7xiYdthPsI/JLq3wePt8pB2H38dS4fYA8QOoa82wrT5NUyZHcSxCaXTg2jPYGWP447ocq17/Kz9yfkzSyrAzeQg7Z9+In9AA/oHkpHdiBR7pihnkiieBZRMYQ31rjrTnU5mKMrkiSWVRTOGpiIiIiIjIIKIQVWQw8jJhaNpaBy3bIdMchqFOZFevT8sGrPxweQtsu/O+9v3tizPtcc7QoKH7+6clZ7j11TbGv/8Et7v34FiGhsoPUnvyVzGR5EA3b+QyBrdtB9hR0pUfwEuNxRhDQ2uWlqxHWTLK9LFFjCqK4TpDZ7EyERERERGRkUIhqshgYEw4x2i6AVpqoLU23DYm7AVaNKow5Hek0ND9/fdOnc+3XmjhssyDfDbyewAaJp/F9mM/N+K+fwYV4xNpqcaPlpKpmIEXK6OpLUdTxqMk7nLUhFJGF8eJugpPRUREREREBiv9q1pkoARBOEw/0whN1ZBpCBdtsh2IFkHx2ANatX6o22PofjxCaURD97tijOHhd7MsXtHCt507+Zj7AgC1My6l7ogFQ6rn8XBj+TkirdvJpcaSKZ9OYxCjoaGNVMxlxtgixpYmiEf6Z05hEREREREROXAKUUX6k5+DdCOk6/PBaSMEOXBjEE1BomJEB167D90fVRQPp2qVfWrMGG55pY0332/g7sgP+ZDzd4zlsP3Yz9E45eyBbt6IZnltuG07yZRMoiE5jdoWSER8DhtdxPiyBMmo/hcsIiIiIiIyVOhfcCJ9LZfOLwpVB83bIdscDtOPJCBRFgaoI1z70P1tjWn8wGjofg+tqvH49l/bcFpr+G30u0y3NxM4Cbae9FVaRx830M0b0exsE062mcbiaVTb43B9m6mVCSaUJyiOq2e1iIiIiIjIUKMQVaS3GRMGpelGaNkRLg6Vaw17mEZTUDRa81PmdRy635jOUZKIaGhzDwTG8Ou3sixemeEINvDz+PcYxU68eAXvn3wj2bJpA93EEc1J1+F7Hltjh5KOTmB8aYKJ5UlKkwpPRUREREREhiolOSK9IfDDofnpBmiuDgPUXBrcSH6Y/rgROb9pVwpD95vTxFyX0cUaut8TO9MB332pjde2+fyjvZKfxm4lYdrIFE9myyk34iVHD3QTRy5jsJurqfdcmkqmUzZ6EkdWJClPRrBG8DQdIiIiIiIiw4FCVJED5WXD4LR1J7RUQ6YJfA8icYgVQapqoFvYrVxg8LyArG/I+QE5PyCd88n5BssC2wLbtnAsCwurMMQ+PGZhAZZlYVuABWGt/LH8PtsCOzyIbVkEgaGmOcO2xjRBAGXJmIbu99Dr1R7/34tt1KUNl7h/4VvuXTjGp7XqaLaeeANBtGigmzhiBZ5Ptn4zbW4psQlHc+S4cVSmoti2vrdFRERERESGg2EdomazWX71q1/xwAMPsGrVKqqrqykvL+eQQw7hwgsvZNGiRVRV9V/Q9aUvfYkf/vCHhe0pU6awfv36fru/dMMYCLzdXv6eZS8DXjrf27QFMBBJQrISnME1XNcYyAVhOJrzDLkgwPMNbVmPtlxA1gvwggAvMPkTwLEsbNvC5LeNMZiwiDEm31vU0LnbaH7b5N87BKdW+IaVD10BMp5PcVxD93vKDwy/XJXhvlVZDIZvpB7mk/5vAGiceBrbP3gdZpB9740UxkBLSyumpZpYxUSmTJtFVXkFjsJTERERERGRYWXYhqirV69mwYIFrFixotP+bdu2sW3bNl588UW+//3vs3jxYubNm9fn7XnllVf40Y9+1Of3kbxCILqXELTjqz0Q9bPg58I6xs/X9cF4dAoLLcBywHbAiUHRmLA8gIyBrB+EYaln8PyAjBfQlvNJ53w833QOSgmDUtexidgWcTeC4+R7jvZao6D9doExYRhLPow1UBKPaOh+D9W0BnznxTbe2OHj4vGzisWc2vpnAOqmX0ztzH/RVBEDwUBzxiPT1kS51Uz5ITMpn3IUkVhioFsmIiIiIiIifWBYhqibN29m7ty5bNmyBQh7wM2ZM4dDDz2UHTt28NRTT9HW1sb27du54IILePzxxznzzDP7rD25XI6rrrqKIAj67B69ysuGc3taVhjO7P6ynd329UEaFgRgunjtMxDNgJ/Z/0C0EIw6YEV3fcZBtACUH0Brzsv3Kg17kbblwuH3XhAGpX4QRpUWFq5t49rhEPx4JIJrW/0XXOaH8UO+R2r7TumxNs+wfJvHD19N05AxVLptPFz+30xqeh2DzY5Zn6bhkL7/BZB0YCDt+bRlfXwTUGRamVAUUDb5OKKjDh/wX6iIiIiIiIhI3xk8CVEvuvTSSwsB6pQpU1iyZAmzZs0qHK+pqeGSSy5h6dKl5HI5Lr74YtauXUtZWVmftOe73/0uK1euLLTt/vvv75P7HDRjwtXka9dCa224z7KAfFBqO523OwWrbjiU3XbAcsFxw30dQ1djOgehhaCzYy/R/LYxHeobIOgQrJp9B6Lt9yu8Ip2D0iG4uEvON9S3ZdnemKE544U9OyEflFo4tkXEsUhEIppbdAjJ+obqloBtLYZtLUFYbg4K++ozu3oOn1jWwN2R71PctI7AibHtH75My7iTBrD1w5gxYHwsE4TvQUAmlyWdyREYj6gNo6I2pXGbVCpFbNyRUDppSP5sERERERERkZ4bdiHqY489xnPPPQdANBrlkUce4eijj+5Up6qqiiVLlnDMMcewbt066urq+N73vse3v/3tXm/P6tWr+c///E8ALrvsMs4666zBGaJmW6DuPajfBLYNxWPD4DEfKBQCTUwYZtIhzAwMeG27haT54NPs434WdA5jO4ayHYPbyK5jdKw7NAPR/ZHxAna2ZtnRmKEp4xF1bEriCkqHiqxv2NHaISAthKThvrr0vv5y7JKKwMKJ1VxX/22iTTvwYmVsOfkbZMqn98MnGOIKYagPJsAKfCD/XghJg/y7BZYJf6YYMNhkAmjzwMMmEnEpKS6htCRFUTJJIp4Mf2kUK4FU5UB/UhEREREREekHwy5Eve222wrlhQsX7hGgtkulUtx8881cfvnlANx5553cfPPNuG7vfUmMMVx11VVkMhnKy8v5r//6Lx577LFeu36vCHxo3BL2Ps02hSvKu/Fdxy0r7Fkq/aYt61PXkmV7c4Z0zifmOlSmYtia9nJQ8YLdQtLmsAdpe2Ba22b2+TuEdgkXxqZsxqRsxhbZjE1ZYTn/GtX4JuNe/k+cXAvZogm8f8pNeKmx/fL5hozAw/bS2F4rlu+HYSgWpv2XLvme8MZyMJaNcWMEThTjRDF2FGOHveYDHNp8Q3MOPGMRjUYpSyUYW5KkNJUgGdPCXSIiIiIiIiPZsErHmpubWbp0aWH7iiuu6LL+RRddxKc//Wmam5upq6vj2Wef7dW5UW+//XZeeOEFAL7//e8zevToXrt2r2itC3ufNm2FaBJKJgz73p2DWVPGo645S01LhkzOJxlxqUrFNJXoIFCfDlizM2BNvc/anT5rdgZsaQ4IuklJ4w6MKYSkViEwHR/PMdHZSVmwEzezE7etDiddi9tUh7ujDjddh5Ouw/FaAWirmMmWk79OEC3ph087yAUetteG7bVhBV4YjrpJvORY/FgpJj+Fh7FdTH4aD5Pf3r0HuzGGtpxPc8bDCwLiEYfy0iijimOUJiIko8Pqf5EiIiIiIiJyEIbVvxD/+te/kslkgLCn6QknnNBl/Xg8zimnnMKTTz4JwNNPP91rIeqmTZu4/vrrAZg9ezaf/OQne+W6vcLLwM6NUL8+nJe0eMygWkBpJDEGGtMetc1paluyeEFAUTRCSbF6vQ0EYwzVLYY19T5rdvqs3RmwZqdPTdve09KI3d6T1GJskc2ERI5Dog1MdBoYY9dR6uVD0nRtGIzW5wPSXEuP29Q48TS2f/DzGCfWWx9zaOkqNI2XE7gp/GgqnPqjB/YWnI4qjik4FRERERERkS4Nq38tvvXWW4Xy0Ucf3aOh+ccdd1whRO14/sG65ppraGpqIhqNcuedd2INhh6exkBzNdSuCXuhJsvD4fvS7/wAGtJZapqy7GzJYjAUxyNEXY3Z7y9+YNjUFIaka3YGrN3ps7bepynbuZ6DzyiamFnUxAdSTUxPNDM52shYp4EibyeRfK9Rt7oOJ9fc4/sHTgwvXoEfL8eLV+LFK/LbFZ3KQSTVy598kOsmNPUjqfBr0sPQFBScioiIiIiIyMEbVv9yfPvttwvlKVOm9OicyZMnF8qrV6/ulXY8+OCD/OEPfwDgK1/5CjNnzuyV6x6UTBPUrYeGTeC4UDohv1iT9KdcYGhozbG9MU1DOoeDFS4W5Q6CkH0Yy3iGdQ1hWLquLse2nY20NNZTHDRSaYWv060GLqKRqmgj450mRtuNlNFAws8Hox7QkH91IbCje4ahiQq8WAVeogIvXokfKw+DwMHwy5WB1jE09T2MffChKXQOTv0gIKbgVERERERERA7CsPpXZG1tbaE8ZsyYHp0zduyuRVrq6up6pQ2f//znAZg+fTo33HDDQV+zXSaTKUxXANDY2AhALpcjl8vt/STfC+c8rVsPuZZwJWk3BgHk/yP9IOsF1LdmqWnO0pzxiNg2JbEIjhOGaH53k2vKvhmD7bXhZBtwMg3kWnays34nLU0N5FrqsTL1JL0GDqeRk60mKmjEtQLoKpMzgN9x08aPluDFSvFjpfjRUrxYaacepF48DEp7HI6asO0jTpDLLwSVzvc0dQncOLnEGPxoKUEkRRBJdg5NDeHPsm60B6ctGQ/fGGKuTWUySlVRkpK4S6IQnJp9/8wUkYL2vyf6+yIiIiJ9Qc8aMlj09HtwWIWozc27htImEokendOxXsfzD9QXv/hFduzYAcAdd9xBLNZ78xh+5zvf4aabbtpj/5///GeSyWQPr7Kj19oj0hfsIEvUaybqNRHzmoh6TUT9JqJe867t/PGoH747ppuAbS+drtN2ilykmKxbQsYtIRMpIesWh+X8q3076xZ13XM7nX+RA+oP+LOPLC67/hfkAbX5V+9JE3Yc3tCrVxUZedqnPRIRERHpC3rWkIHW2trao3rDKkRNp9OFcjQa7dE5HUPOtra2g7r/n/70J37xi18AsHDhQs4444yDut7uvvrVr/KlL32psN3Y2MikSZM444wzqKys3FUxl4b6jeHQfROEvU+1cFS/asl67GzJUtucI+15JFyXVMyFkTx62wTEd75DvPE9nGxj+Mo0Fspu/t32091fay9aTIxaU0ItpTTZJfixUpxEGYmiMkpKw3c/XoYfK8WLluxzeHg0/yo+8E86/AU+VpDDCrz8u49lvLDHKGCwwHHD+UxtN+xd6sYxbtjLNByef2A/k3J+QGvWJ53zCYwh4lgkoi5liQgliSglcadDj1MRORi5XI4nn3ySs88+m0hECx6KiIhI79KzhgwW7SO9uzOs/qUZj8cL5Ww220XNXToOj+9p79W9aWlp4eqrrwagsrKSH/zgBwd8rX2JxWJ77dkaiUTCHzhBAM3boHYttO2EZCVEe9pDVQ6WMdCU9qhpSVPXnCPr+xTFIpQmD/z7asgLciRrVpLa8iJF217GTfdsygxjufixEvxoh1eH7Q2ZFL95L86q5iLqTAmjK0o5eXKKw8odDi13GBfdM63OdCg7vfTxhiVjsAIPghyW8fJBafhq/y2AsZx8SBrBRJIEkSS+m8Q4UYwTwdix/Hv42n16g/2Zjbk9NG3L+QRBQMS1SUYjjClLUpqIkow5pKIujj2Sf0Mh0rcKzxkiIiIifUDPGjLQevr9N6xC1KKiokK5p71KO9breP7+uuGGG1i/fj0At9xyC1VV/bzqfboB6t6Dhs0QiUPpRC1a00/8ABrTOXY0ZdjZmiUwhuJYhNLkyPyfgOW1kap+jdTWF0ltW4bjtRSO+W6CdOVRePHyDuFoaYeQtJQgWkLgJvb6/duQCbjrbxkeXxfOV1Ictfi/s2KcOy2Cre/3/RN4OLmWMCwNPCxjCLuSWmHwabsEtksQKSGIJAjaQ9J8MNpe7u1e7nsLTRMRl8kVCUoSEVIxV6GpiIiIiIiI9LthFaJ2HNJeXV3do3O2bdtWKFdUVBzQfZcvX86Pf/xjAM444wwWLlx4QNc5YPUbYWcdeG1QNAqcnk1lIAcnFxgaWnPsaErT0JbDwqI47hJx96ef3fDgZBpIbXuZ1JYXSe5YgR3smpTZi5XRMu5kmsedTFvVLIyz/+FyYAxPrMtx198yNGbDMeMfnhbhqlkxSmMj7+t9sOxcC066Hj9eThAtJYgkMU6sUzjaXu5yLthe0DE0NcbgOhYJ12VSeYLSpEJTERERERERGRyGVYh6xBFHFMobNvRsKZGNGzcWyjNmzDig+77xxhsEQVC43sknn7zPuu2LTgFs3bq1U92vf/3rnHfeeft9/8aNb2KPGksQG4VpA0MGTPvi36Z9msLCQuDGhKFU+zFjDAHh9KkGgzHt/dHAtsCyLCwLbMvCIty28/tgV4fB9mOWBRbt7+EBCwuTb5QhvP++2rh7+3xjMEF+X4fPsbeOhx13Fe7f4Winc3Y73l62OlTa8xa7rrGzNUtzOofrOJQmorjOyAp53JZqira+RGrriyRq/45FUDiWTY6lZfwpNI87hXTFEWAd+AD6dfU+P1qW5u81PgCHlNp8/h/iHDVqWP346h8mwG2rAcsmUzGDbPGkfp8veffQ1HEskgpNRUREREREZJAbVinEzJkzC+WVK1fieR6u2/VHXL58+V7PP1Br165l7dq1PaqbzWZ5+eWXC9sdA9b98W46SXE9QFOHvfkYtD0N3Y1F56CwY9jZqb6hEH4GhV0dUlYDWAZM+3m737C77b1cw+wKMndv275GbJtudpg9a+ylTjfX3E3UsalIxbFHSkdIY4g2bqBo64uktr5EvKHz93m69NB8j9NTyJZMOejpJFpzhp+/meF/38kSGEi48ImjYnxselQB2wGwvDSRtlq8eCWZskPxE5Xdn9QLsl5AWy4/PD/f01ShqYiIiIiIiAw1wypE/dCHPkQsFiOTydDS0sKyZcu67BWayWR46aWXCttnnnlmfzSz11WkkpQWxbuvKLK/TEC8bnUhOI22bN11CJu2yiNpGXcKzeNOxkuN6Z1bGsNzmz1uX56mpi2MsmdPcvnMB+OMSo6UxLp3Oemd2H6aTOkhZEumYty++XlhjCGTD00zXhiaRh2beEShqYiIiIiIiAxtwypELSoqYu7cuTz22GMA3HvvvV2GqA899BBNTWHvzYqKCubMmXNA9120aBGLFi3qUd17772XK664AoApU6YUFqMSGSwsP0ei5m/5ofov4WbqC8cCO0LrqGNpGX8KLWNPwo+V9uq9328K+O/X2li2LRy6P77I4nPHJzhh3LD6UdV/ghyR1h0EkSLaqmbhJcf06oJzgTGkcz7pXEDa88EYYhGHZNRhfFmc4niEZNQhqdBUREREREREhrhhl0xcc801nULUa6+9lg984AN71GttbeUb3/hGYftTn/pUt0P/RYaswMPJNuKk63Gz9TjpepxM+HIzDTjt+7INuOl6LOMVTvXdJC1jT6Bl3Cm0jD4OE0n2evOyvuFXb2V54O8ZcgFEbPjnmVEumRkj5ip8OxB2thk320g2NZ5s6TSCaNFBX9MPwtC0vaepbVnEIjZFcZfJyQSpeNjLNBl1Os0tLCIiIiIiIjLUDbvU8LzzzmP27Nk899xzZDIZzj//fJYsWcIxxxxTqFNbW8uCBQtYs2YNEPZC/cpXvrLX661fv55DDjmksL148eIe9zoV6UuW14aTacDN7MTJNOwKRfNhaOeQtHG/ru3FymkedzIt406mddQxYEf66FPAsq0eP34tzZbmcNbd48Y4XPsPcSYWH/hiVCOa8XFba8B2aSufSa54ItgH9rXM+UEhNM35Aa5tE4/YVKSilCejpGIOqZhLPKI/KxERERERERnehl2ICnD//fdz4oknsnXrVtavX8+xxx7LaaedxqGHHsqOHTt46qmnaG1tBcB1XX79619TVlY2sI0W2Z3xibRsI9bwHtHG9cQaN+Ck63Dz4ajtZ/bvctj4sRL8WBl+rAwvVloo+7FSvFg5fn6fl6gCq2/nH61pDbjj9TR/2RT2eq2IW1xzXJw5k1z1YjxAlpfGbavFT1SRKTsMP16+X+e3LwKVzvn4xuDYFomIw5iSGGXJaNjLNOYQcxWaioiIiIiIyMgyLEPUiRMn8vTTT7NgwQJWrFiBMYZnnnmGZ555plO9UaNGsXjxYubOnTswDRXJs7NNxBrXE21YT6zxvbDcuKHboDRwYh1C0LLdQtGO22X40SKwBj788gPDw+9m+dnKDG0e2BZccHiUTxwdIxVReHpAjMHJ7MTyc2RLDyVbOgXjxLo9LZ0PTNP5RaAijk0i4jKxPEFJIlIITSOOFvQSERERERGRkW1YhqgAM2bM4OWXX+bBBx/kgQceYNWqVVRXV1NWVsa0adO48MILueKKK6iqqhropspIEvhEm98n2vgesYb2sHQ9kbaavVd3YmSLJ+dXVZ9CLjmmU69R4yb6+QPsmxcY2jxIe4a017mc9qEtF+7747os6+rDofszKx0+/w9xDisf+HB3qLL8HG7bDoJICelRM/ESo7tcPCrnBzSlPdpyPnHXJhF1GFsapyShRaBERERERERE9mXYhqgA0WiUT3ziE3ziE5844GtMnToVY0yvtWnRokWaU3WEcDINu8LShjAsjTZtxA5ye62fS44hUzKVTMlUsqWHkCk9hFxqbL/2Ht3eEvC37R71GUM6H4K2efmynw9EC+Eo+WNhSOoFPb9PcRSumhXnw9Mi2Bq6f8DsbCNOtoVc0UQypdP2uehXYAwtGY+mjIdjWZQmIxw6OpUfoq9FoERERERERES6M6xDVJF+EeSINm0i1rA+37M0DE3dzM69V3cTZEqmkC2ZSqZ0WhialkwhiKT6ueFh79A3dngs2+bz2jaPTY37kYTug2NB3IWEaxF3rQ5liDsW44psLp4RpSyuIeIHzPi4rTvAiZKumEmuaMJeF49K53ya0h5ZP6Ao7jKtKkVVUYzSRARbvU1FREREREREekwhqsi+BD6214qda8HJtWDnWrBzzdi5VtzMTqKNG8LQtGkTlvH3ON1gkUuNJVsS9irNlEwlU3oIXnJ0ny/atC9+YFhTH/DaVo/Xtnn8vdbv1IPUtmB6hcOEIjsMPdvDT9ci7lgkdtvXMRxNRCziDkQchXN9ycq14qbr8ZKjyJQdShAr63TcDwxN6RwtWZ+Ya1FZFGNMSZyyZIR4RNMmiIiIiIiIiBwIhagyPBmDFWTzwWfHEDS/7e22nWvBzrXmQ9IWHK8V22vr8e18N0W2dCqZkkPI5N+zJZMHxZyl21sCXtvmsbzaY/k2n8Zs5+kpxqYsjh/rcvxYl2PHuBRHFYIOSsbgpGuxgoBM+WHkiidjnGjhcGvWoyntERhDSTzCjLEJKopiFMdcDdcXEREREREROUgKUWUPTroON733oeh76uF8scYAAZYJwrLJlwv7wv3t5fZjhXKH45afwck1F3qJ2rlmnFzrHqGoZbwD+wLsJnBiBJEUfqSIIJLMl4vJFk/OB6dT8RKjulzMpz91N0Q/6cIHx7gclw9OxxdZCtkGOcvP4rbW4MdKyVQeWvh+67hIVCJqM74szqjisNdpxNF0CSIiIiIiIiK9RSGqFDjpnVS+9UtKNjyJxcHPjTkYGKx88FmEH0kRuGE5iCTD7U7BaFGhbhBJ4bvhfuzB/dekJ0P0j6hwOH6sw/FjXWZUOriaD3PIsDMNOLlWsiWTyJZOw3fie10kqiIVJRkd3N+rIiIiIiIiIkOV/sUtWF6a8jX/S/m7v8P20wB48QoMvRi0WRZgg2VhLBssu/AOFsZywjrt++lwvP0cwu2wZ2iHYLQ9+HR3D0aLCNz4gM0/2pc0RH+YCTysIBe+/Px7YMAKFyJLVx1FU3Q0TW0BWT+tRaJERERERERE+plC1JHMBBRv+jOVf/85kXQtAOny6ew46krSlR8Y4MZJRy05w8rtHq9Va4j+kGB2vZn2fDvwwM92DkoJwtktbAffihDYEQK3DD+RIrBj+E6UNHGavDgxfC0SJSIiIiIiIjJAFKKOUIkdf6PqzbuJN6wDIJcYTc0HFtI8Yfaw7Lk51KQ9w99rfF6v9vjbdp+363yCDp1NNUS/f3m+wQsCPN+Q8wN8YwgjUitMSfOBteV7WCaHHXjYQQ4nyNGeqBrbwdgRjBMhcIvw4imMEw9fdpTAiYYLRVk2WGDle4JHXZsZJTEtEiUiIiIiIiIygBSijjCRpk1UvXkPRdWvAuC7SXYe8XHqp32000rf0r9yvuHtOp/Xq31WVHu8VeuT221a2nEpq9DTVEP0+4AJw9LcbmGphcFxbCK2jWsbyqKQcCFqGWwT9iqFAAsDVgTcCJaTIoiksGJF4CbAjWHcGJYbBTeGZdmFMNRi15pkFlan9cksC1zbxlFALiIiIiIiIjKgFKKOEE6mnorV91O6/nEsE2Asm4ap86idsYAgVjrQzRtx/MCwZmfA69s9VlR7rNrhk/Y716lKWBw7xuXY0Q7HjnEZk1IP4d5gDOT8AM8PyPkGLzAEBFgGIpZPxApIWgGpWEDMNsRsg2tbRB1wXRfLjoAdAScG0RREiyASBzcOThiS4sTA1p+XiIiIiIiIyHChEHWYs/wMZWt/T/k7v8bx2gBoHnsyNR9YRK544gC3buQIjGF9Q8CKao8V233e2O7RkutcpyxmMSsfmB47xmFCka2h2wchCMKwtD0w9f0clvGwA5+I5RPFo9iBeMQiFnGIOBaRSBw3EiXiRsIwNJKCaDIMR50oOJH8K7+tPx8RERERERGREUEh6nBlAoo3/yVcNKptBwDp0kOpOepK2kYdM8CNG/6MMbzfFPD69nB4/t+2+zRkTKc6qQjMGh0GpseOdplSamMrlDsguZxHNpvBz2UJgix24OMYH8cOSNgOsYhDPBElGokSjcZxozGiiWKcWBG40XzP0mjngFQ9SUVEREREREQkTyHqMBSveZNRb95NvP5dAHKJKmqPXEjTxNO0aFQfqm4JeL3aY0W1z4rtHrVtnUPTuANHjWrvaepyWJnmujxgxmD5aUymlZaWZrBtYrE4iVSMeKyCSCJFNFZENJEgEolhR2K7BaRa2V5EREREREREek4h6jASaX6fqlWLKdr6EgCBm6Du8IupP+yfME5sgFs3/NS2BfwtH5iuqPbY2tI5NI3YcGRV2Mv02DEOR1SEQ8blwFh+Bttrw861YUxAkx+hlQTF4z7AuDGjKS8txXLzYamIiIiIiIiISC9SiDoMONlGRr1xH6XvPYZlfAw2DVPPpW7Gpfjx8oFu3n7J+oaWnKEla2jJQXNu13Z7OeeDAYJ8ZhmYcLGgABO+F7bZtZ0vG8wex/esu6uO2e0a7fsbs4bNTUGnttsWzKhwOHaMw6zRLh+ocoi5Ck0PWJDLh6at4WJoTpTATVKXGE29SVJUXMaUMZWMLkmoR6+IiIiIiIiI9CmFqMPA1Ge+QJkbLhrVMuYfqPnAJ8mWTMYYg+cbckEYTobvkAtM53ffkA0g5++qZ0w3N91PuSAMRXcFpOErDEYp7MsF3V9rsLCAQ8vtQk/To0e5JCMK8w6Y8bFzbdheG1aQw1guxk2SK56MHyujxcSpybkkY1GmVSQYV5Yg5mpYvoiIiIiIiIj0PYWow4Djt/KuO5UfWZfxQvXR5LYYskFjocfmUJR0IRW1SEXCV1HUIhWBVMQi6lhYhD0/LYtOZRuwLCvczu+nsJ8O+60O9Xft3/N61q7jHY5FHYsjKhxKYgpND5gxWF4Ymtp+BrAI3CRecjR+rBw/WkQQKSJnbOpastg2TK1KMLEiSVFMP7pEREREREREpP8oiRgGvpZbxB/M2QTYdBWbunY4T2fUsfLvELGtzu/5cm+PjnYs8kGoRbIQjFIISXcFpRYJFw3PHq6CHE62GdtrAyyMG8ePlpJNVBJEiwkiqcL8vX5gqG/NkvVzjCmJM7kiSXkqOrDtFxEREREREZERSSHqMHDMyWdzekkREac9EO0YlIbvESfsfSnS7zoEp8ZyCKLFZIomEkRL8KNFGDfRqboxhsa0R3MmR0UqyszKEkYVxbAVrIuIiIiIiIjIAFGIOgwcO9qltER/lDKI7C04LZ6CHyvDjxaDvfe5TFuzHjtbshQlIhw5roSxpQmirt3PjRcRERERERER6UzJm4j0jgMMTgGyXkBtS4aoY3Po6CImlCdIRvXjSUREREREREQGB6UUInLgDiI4hXDe07qWLL4xjCtNMLkiSWky0k+NFxERERERERHpGYWoIrJ/DjI4hXDe0/q2HK1Zn6qiKJMrk1SlNO+piIiIiIiIiAxOClFFpHv7GZwaYwhM+G6AwBiMCd8939CUyVESj3D0xFJGF8eIOJr3VEREREREREQGL4WoItKJ5xnSno8V5LCzLdi5FgLLIRspIhOfSjZaRi5SBDiQATJZDGBhMIQ9SS3AtiywwLbAxsKywLIsHNvi8NHFTChPEI9032tVRERERERERGSgKUQVEUxgaGtrJZttxQk8kraP7biYRBFB1VScRBmReBmlrotjh0GobYXBqG1Z+VcYktod9lk2hWMd66vnqYiIiIiIiIgMJQpRRUaaIIftZ7H8LF62jbZMDt9ALBansjRFSWkFRSVV2KlyiJf2aI5TEREREREREZHhTCGqyHAV+Fh+BjsIA1Mr8AALH4fWwKE5iGLFJ1IyqoyxZaWUlRYTixcpNBURERERERER2Y1CVJGhzgT5kDRb6GEKYCwHnBiBE8OLV9FKkkbPwXNipJJFjKsopqIoRnHMxbKsAf4QIiIiIiIiIiKDl0JUkaHCGKzAw/IzWO29S40JDznRQlgaREsI3DiBGydHlEbPodXzibsOVUUxRpfEKE9GNS+piIiIiIiIiEgPKUQVGUwCHyvIhWFpkMu/fMAAFsaOhIFppAS/qATjJsPA1IljnBjYDsYY2nI+TWkPg6E47nDIqCLKU1GKYvorLyIiIiIiIiKyv5SoiPQnY/YSkuYgACwwlg1OBGNFMJEUXiRF4CYxThRjR8MA1Y2DHdnj0jk/oLE5Q9oLSERtxpfHGV0cpywRwVWvUxERERERERGRA6YQVaS3dQpIPSw/h2UCCr1J20NSJ4IfLSWIFGHcGMaOEDhRjBPD2NEeLfBkjKEl49OYyeFYFqXJCIeVxqlIRUlG9ddbRERERERERKQ3KGUR6Y4JwBggwDIAwa75SQu9Sr1d1S0HnAiBHSGIlBAkUwSRRKEn6a73CBzggk5ZL6AxnSPr+6SiLodUpqgqjlGWiGDbWiRKRERERERERKQ3KUSVzgIfJ9eEnWsNh5ZjhUGfZWMI37FsjGUBNlhWh3od99sHHBDulTGEPTkJ3/PbljFhyNleLhwLOhwjXMEe0yEQNfntsHdo2EnUIhxXT7ivcLddX4OwjpX/3C7GSeDHkwSRFMaJhT1J7UjYm9SJhuf0Es8PaM36NGdzuI5NRTLK2NJiypNR4pHue62KiIiIiIiIiMiBUYgqAFheG06mAcsY/GgJmbLp4QHjYQceBB4YH9v4+XI+pAx8bMLQshBQ5t+tjqHnrjvRPqx913vPmPa6FuwR1HYMebExlo2xLcDB2C7GdsJzbDsMP20HLDcMfTsEv6ZDUGrygXF4vV312vcb29nr3KQHyxhDzjdkvYCM55PxwwDYtmwSUYfDRhVTVRSjJOFi9WZQLSIiIiIiIiIie6UQdSTL9zp1si0EbhwvNR4vORovXgF2N98a+bDUMn6HnqDtQWpQKIdzgbb3/txNIQDc9W5237fXOvltq0PwWegdGoaevd4Tto8Epj0sDQNTzw97yUZdm6jrUJ6KUhJ3ScZc4q5DIuoQdbVIlIiIiIiIiIhIf1KIOgKFvU4bsUyAHy2hreJI/EQlQbRoPy5igeVg2DWMfC8xqXTg+WFY2h6aBhhsLKKuRSziUJGKUxyPEI+EYWnctXEdBaYiIiIiIiIiIgNNIepIYXycbMdep+PyvU7L+2RIel8xxuAF4cB+y7KwLQbdkPb24fgZzw9DUz/sqevYNnHXJhlzGF8eJxl1SUQc4hGHeMQedJ9DRERERERERERCClGHub33Oq0giBYPdNO6FBhDzg97bWa9gJxvCPKzorqORZBfQyowptAD1srPsRpuh+VC2ArYdrhtW1bYkbZDCGtbu/bbltXjkNYPwuH4WT8gk/PJBQbbgohjEXMdKlJRShMuiagb9jCNaDi+iIiIiIiIiMhQoxB1OCr0Om0lcGODutdp+5ygYVAakAsCAhPOgBp1bKKuTVkySlHcIRl1ibnhPkM4/WpgDIEx+MZgTPs2BEG47QcBXhD2XvWDAD8A3wR4vsEPwl6jfr53a7DbNTqGtO0x6q4pC8K9NhbRSBiYVhYlKIq54VD8fGDq2OpdKiIiIiIiIiIy1ClEHUb27HU6c1D0Om0PJ3P5OUFzfviCsK9oxLWIOeEiSsXxMISMueEQ95jbd0GkybfLN3sGqIExmGDXsT2OBwbHtkjk5y+NuRqOLyIiIiIiIiIyXClEHQacbAPRpsZ8r9OxeMkxe+11avK9Kk2+O2WQLxgDBlPY33G7PTQ0HUJEw65gtL1u4R6EvTZN+4WwwuHxNkRsi6jrUJKIUhwLh7jHXJtYH4el+2K1D99H4aeIiIiIiIiIiOybQtRhoC5taC6aRiZeQRApgpzB5DzAC4NMywKza85PAKxwt0X7y+qwr8OcoYBjh0Go61i4to1tgevYuLaFk391nE/Ubp9j1N5VtiyLqGMTc21sDXEXEREREREREZEhRCHqMDB2ximUV43ZLQDtUCbf65Jd+9sDU3u3/e0ha/sxp8MiTCIiIiIiIiIiIiORQtRhYGx5MZVliYFuhoiIiIiIiIiIyLBkD3QDRERERERERERERAYzhagiIiIiIiIiIiIiXVCIKiIiIiIiIiIiItIFhagiIiIiIiIiIiIiXVCIKiIiIiIiIiIiItIFhagiIiIiIiIiIiIiXVCIKiIiIiIiIiIiItIFhagiIiIiIiIiIiIiXVCIKiIiIiIiIiIiItIFhagiIiIiIiIiIiIiXVCIKiIiIiIiIiIiItIFhagiIiIiIiIiIiIiXXAHugF9KZvN8qtf/YoHHniAVatWUV1dTXl5OYcccggXXnghixYtoqqqqtfuV1NTwwsvvMArr7zCypUrWbt2LVu2bKG5uZlIJEJ5eTlHHXUUp59+Op/4xCeYMGFCr91bRERERERERERE+oZljDED3Yi+sHr1ahYsWMCKFSv2WWf06NEsXryYefPm9co9zz//fB599NEe1Y3FYnz1q1/l61//OrZ9YB2CGxsbKS0tpaamhsrKygO6hoiIiMje5HI5HnvsMebNm0ckEhno5oiIiMgwo2cNGSza87WGhgZKSkr2WW9Y9kTdvHkzc+fOZcuWLQBYlsWcOXM49NBD2bFjB0899RRtbW1s376dCy64gMcff5wzzzyzV9tQVVXFzJkzmTJlCkVFRbS2trJmzRpeeeUVPM8jk8lw4403sm7dOn72s5/16r1FRERERERERESk9wzLEPXSSy8tBKhTpkxhyZIlzJo1q3C8pqaGSy65hKVLl5LL5bj44otZu3YtZWVlB3Xf008/nfnz5zN37lwOO+ywvdaprq7mi1/8Ig888AAAP//5z5k/fz7/5//8n4O6t4iIiIiIiIiIiPSNYbew1GOPPcZzzz0HQDQa5ZFHHukUoELYS3TJkiVMmzYNgLq6Or73ve8d9L3/7d/+jauvvnqfASrAmDFjuO+++zr1fL3zzjsP+t4iIiIiIiIiIiLSN4ZdiHrbbbcVygsXLuToo4/ea71UKsXNN99c2L7zzjvxPK/P2wfh9AJXXHFFYfv111/vl/uKiIiIiIiIiIjI/htWIWpzczNLly4tbHcMKvfmoosuoqioCAh7oz777LN92r6ORo0aVSg3NTX1231FRERERERERERk/wyrEPWvf/0rmUwGCHuannDCCV3Wj8fjnHLKKYXtp59+uk/b19Hf//73Qnnq1Kn9dl8RERERERERERHZP8MqRH3rrbcK5aOPPhrX7X7drOOOO26v5/elLVu28IMf/KCwrUWlREREREREREREBq9hFaK+/fbbhfKUKVN6dM7kyZML5dWrV/d6m9q1trby97//nVtuuYUPfvCDbNmyBYCZM2dy/fXX99l9RURERERERERE5OB031VzCKmtrS2Ux4wZ06Nzxo4dWyjX1dX1Wluef/55Zs+e3WWdefPmcd9991FcXNyja2YymcJ0BQCNjY0A5HI5crncgTdWREREZDftzxZ6xhAREZG+oGcNGSx6+j04rELU5ubmQjmRSPTonI71Op7fl8rLy/mf//kfLrnkkv067zvf+Q433XTTHvv//Oc/k0wme6t5IiIiIgVPPvnkQDdBREREhjE9a8hAa21t7VG9YRWiptPpQjkajfbonFgsVii3tbX1WlvGjx/PZz/7WQCMMTQ1NfH222+zfPlydu7cyYIFC/jJT37CHXfcwfTp03t0za9+9at86UtfKmw3NjYyadIkzjjjDCorK3ut7SIiIiK5XI4nn3ySs88+m0gkMtDNERERkWFGzxoyWLSP9O7OsApR4/F4oZzNZnt0Tsfh8T3tvdoT06ZN47//+7/32L9lyxZuuOEG7r33Xv785z9z8skn88wzz3DMMcd0e81YLNYp9G0XiUT0A0dERET6hJ4zREREpC/pWUMGWk+//4bVwlJFRUWFck97lXas1/H8vjJ+/HgWL17M5z//eQB27tzJJZdcgu/7fX5vERERERERERER2X/DKkTtOKS9urq6R+ds27atUK6oqOj1Nu3Ld77zHUpKSgB46623+OMf/9hv9xYREREREREREZGeG1bD+Y844ohCecOGDT06Z+PGjYXyjBkzer1N+5JMJvnQhz7E448/DsALL7zA+eefv1/XMMYA0NTUpK7vIiIi0qtyuRytra00NjbqOUNERER6nZ41ZLBonxO1PWfbl2EVos6cObNQXrlyJZ7n4bpdf8Tly5fv9fz+UF5eXijX1tbu9/nt5xxyyCG91iYREREREREREZGRpqmpidLS0n0eH1Yh6oc+9CFisRiZTIaWlhaWLVvGySefvM/6mUyGl156qbB95pln9kczC7Zu3VooH8hUAu3nbNy4scs/ZJG+dsIJJ/Dqq68OdDNGJH3tdxluX4uh9HkGW1sHsj39fe++vF9jYyOTJk1i06ZNhSmIRAbKYPs5M5Loa7/LcPtaDKXPM9jaqmeN3qFnDRksjDEcf/zxjB8/vst6wypELSoqYu7cuTz22GMA3HvvvV2GqA899BBNTU1AGEjOmTOnX9oJYS/SF198sbB9IL1gbTuc0ra0tFQ/cGRAOY6j78EBoq/9LsPtazGUPs9ga+tAtqe/790f9yspKRlUf74yMg22nzMjib72uwy3r8VQ+jyDra161uhdetaQwSAajRZytn0ZVgtLAVxzzTWF8r333suqVav2Wq+1tZVvfOMbhe1PfepT3Q7970pdXV2P6wZBwOc+9zkymQwAsVhsv+dDFRlMPvvZzw50E0Ysfe13GW5fi6H0eQZbWweyPf1978H2tRfpK/peHzj62u8y3L4WQ+nzDLa26llDZPjpyfe6ZbqbNXUImjNnDs899xwAU6dOZcmSJRxzzDGF47W1tSxYsIAnn3wSCHuhrl27lrKysj2utX79+k5zji5evJhFixbtUe/WW2/lvvvu49prr+WCCy7Y529R3njjDb785S/zxBNPFPZ97Wtf4z/+4z/2+3M2NjZSWlpKQ0ODfmsjIiIivUrPGSIiItKX9KwhQ82wGs7f7v777+fEE09k69atrF+/nmOPPZbTTjuNQw89lB07dvDUU0/R2toKgOu6/PrXv95rgLq/li1bxsKFC3FdlxkzZnDEEUdQXl6OZVnU1tbyxhtvsGbNmk7nXHTRRXzzm988oPvFYjG++c1vEovFDrrtIiIiIh3pOUNERET6kp41ZKgZlj1RAVavXs2CBQtYsWLFPuuMGjWKxYsXc9555+2zTk97ot5+++2dphLoTnFxMTfeeCNf+MIXcBynx+eJiIiIiIiIiIhI/xqWPVEBZsyYwcsvv8yDDz7IAw88wKpVq6iurqasrIxp06Zx4YUXcsUVV1BVVdUr9/vMZz7D3Llzeeqpp3j55ZdZtWoVGzdupL6+HggnSh43bhzHHnssZ511FhdddBFFRUW9cu+DsW3bNp566imWLVvGsmXLeP3112ltbWXKlCmsX79+oJsnIiIiQ9zKlStZsmQJzz77LCtXrqS2tpZEIsH06dOZP38+1157LeXl5QPdTBERERmCHn30Uf74xz/y2muvsWnTJmpqanAch0mTJnHmmWdy3XXXMX369IFupgwTw7YnqvTMrbfeyhe/+MU99itEFRERkYO1du1aDjvssML2+PHjGT9+PFu3buX9998HYNy4cTzxxBMcffTRA9VMERERGaLOOussli5diuu6jBs3jjFjxrBz5042bNiA53lEo1F+9rOfcckllwx0U2UYsAe6ATKwSkpKmDt3Ll/5ylf4zW9+wy233DLQTRIREZFhwhjDqFGjuPHGG1m7di3vv/8+r776Kps3b+b5559nypQpbN26lQsuuIBMJjPQzRUREZEhZuHChfzpT3+isbGRjRs38uqrr7JmzRrWr1/Pxz72MbLZLJ/85CfZvHnzQDdVhgH1RJVOHnzwQRYsWKCeqCIiInLQ0uk0vu+TSqX2evyFF17gH//xHwFYsmQJH/3oR/uzeSIiIjKMpdNpxo0bR319Pbfffjuf/vSnB7pJMsSpJ6qIiIiI9Il4PL7PABXg1FNPpbS0FIC33nqrv5olIiIiI0A8HmfatGkAtLS0DHBrZDhQiNrHfN/njTfe4O677+Yzn/kM//AP/0A0GsWyLCzL4vTTTz/ga2ezWX7xi18wb948pkyZQjweZ9y4cXzoQx/iBz/4ATU1Nb33QURERGRQGsrPGp7nkcvlALoMW0VERGRgDOXnjJqaGlavXg3ACSeccFDXEgFwB7oBw9nDDz/MZZddRmtra69fe/Xq1SxYsIAVK1Z02r9t2za2bdvGiy++yPe//30WL17MvHnzev3+IiIiMvCG+rPGww8/XGj7aaeddrBNFhERkV40VJ8zduzYwbJly7jhhhtobW3l0ksvZc6cOb3Yehmp1BO1D9XX1/fJD5vNmzczd+7cwg8by7I47bTT+OQnP8n8+fNJJBIAbN++nQsuuICnn36619sgIiIiA28oP2vU19fzr//6rwDMnz+fo48+utfaLyIiIgdvKD1nPPzww4XesaNHj2bevHnU19dz55138stf/rLXP4OMTOqJ2g/GjBnDCSecUHg98cQT/OhHPzrg61166aVs2bIFgClTprBkyRJmzZpVOF5TU8Mll1zC0qVLyeVyXHzxxaxdu5aysrKD/SgiIiIyCA21Zw3P87jkkkvYuHEjo0aN4o477jjgtoqIiEjfGgrPGZWVlZx66qkEQcCWLVvYvHkz69ev5/7772fOnDnMmDHjgNsr0k4hah/68Ic/zIYNG5g8eXKn/S+//PIBX/Oxxx7jueeeAyAajfLII4/s0XOjqqqKJUuWcMwxx7Bu3Trq6ur43ve+x7e//e0Dvq+IiIgMPkPxWSMIAhYuXMgTTzxBcXExjzzyCOPHjz/g9oqIiEjfGErPGbNnz+b5558vbG/dupWvfe1r3HPPPZx00km88cYbTJky5YDbLQIazt+nxo4du8cPm4N12223FcoLFy7c59C3VCrFzTffXNi+88478TyvV9siIiIiA2uoPWsYY7jyyiu5//77SaVSPProo5x00km903ARERHpVUPtOaOjcePGcffdd3POOefQ2NjIt771rQNvtEieQtQhpLm5maVLlxa2r7jiii7rX3TRRRQVFQFQV1fHs88+26ftExERkaGtL581jDF86lOf4t577yWZTPKHP/yB2bNn907DRUREZNAbiExj/vz5ACxbtmy/zxXZnULUIeSvf/0rmUwGCH8rc8IJJ3RZPx6Pc8oppxS2tcCUiIiIdKUvnzU++9nPctddd5FIJPj973/P6aef3ittFhERkaFhIDKN9t6rvu/v97kiu1OIOoS89dZbhfLRRx+N63Y/pe1xxx231/NFREREdtdXzxqf//znuf3224nH4yxZsoS5c+cefGNFRERkSBmITON3v/sdAB/84Af3+1yR3SlEHULefvvtQrmnEyJ3nL9k9erVvd4mERERGT764lnjy1/+Mj/+8Y8LAerZZ5998A0VERGRIae3nzOWLVvG1772tU7Xbbdx40YuvfRSnn/+eRzH4Qtf+MIBtlpkl+5jfxk0amtrC+UxY8b06JyxY8cWynV1dXsc37RpU6ffyGSz2cL+qqqqwv5TTz2VJUuW7HebRUREZOjo7WeNF198ke9///sAlJSUcPPNN3daJKKjefPm8f/+3//b3yaLiIjIENHbzxnNzc1861vf4lvf+haVlZVMnjyZaDTK9u3bWb9+PcYYUqkUd999t3qiSq9QiDqENDc3F8qJRKJH53Ss1/H8dr7vd/pB1i4Igk77Gxoa9qepIiIiMgT19rNG+7xnANu3b2f79u37vM5hhx3W02aKiIjIENTbzxmzZs3ixz/+Mc888wwrV65k3bp1tLS0UFJSwkknncRZZ53F1VdfzcSJE3vnA8iIpxB1CEmn04VyNBrt0TmxWKxQbmtr2+P41KlTMcYcfONERERkyOvtZ43TTz9dzxkiIiIC9P5zRnl5OZ/73Of43Oc+1zsNFOmG5kQdQuLxeKHcPuy+Ox17gPT0Nz0iIiIyMulZQ0RERPqKnjNkqFOIOoQUFRUVynvrVbo3Het1PF9ERERkd3rWEBERkb6i5wwZ6hSiDiGVlZWFcnV1dY/O2bZtW6FcUVHR620SERGR4UPPGiIiItJX9JwhQ51C1CHkiCOOKJQ3bNjQo3M2btxYKM+YMaPX2yQiIiLDh541REREpK/oOUOGOoWoQ8jMmTML5ZUrV+J5XrfnLF++fK/ni4iIiOxOzxoiIiLSV/ScIUOdQtQh5EMf+lBhZbqWlhaWLVvWZf1MJsNLL71U2D7zzDP7tH0iIiIytOlZQ0RERPqKnjNkqFOIOoQUFRUxd+7cwva9997bZf2HHnqIpqYmIJw7ZM6cOX3ZPBERERni9KwhIiIifUXPGTLUKUQdYq655ppC+d5772XVqlV7rdfa2so3vvGNwvanPvUpXNft8/aJiIjI0KZnDREREekres6QoUwh6hBz3nnnMXv2bCDs2n7++efzxhtvdKpTW1vLBRdcwJo1a4DwNzZf+cpX+r2tIiIiMvToWUNERET6ip4zZCizjDFmoBsxnM2bN48tW7Z02rdt2zaqq6sBSKVSHHbYYXuc99hjjzF+/Pi9XnPz5s2ceOKJbN26FQDLsjjttNM49NBD2bFjB0899RStra0AuK7L448/3qnLvIiIiAwfetYQERGRvqLnDJFdFKL2salTp7Jhw4b9Pu+9995j6tSp+zy+evVqFixYwIoVK/ZZZ9SoUSxevJjzzjtvv+8vIiIiQ4OeNURERKSv6DlDZBdNKDFEzZgxg5dffpkHH3yQBx54gFWrVlFdXU1ZWRnTpk3jwgsv5IorrqCqqmqgmyoiIiJDkJ41REREpK/oOUOGIvVEFREREREREREREemCFpYSERERERERERER6YJCVBEREREREREREZEuKEQVERERERERERER6YJCVBEREREREREREZEuKEQVERERERERERER6YJCVBEREREREREREZEuKEQVERERERERERER6YJCVBEREREREREREZEuKEQVERERERERERER6YJCVBEREREREREREZEuKEQVERERERERERER6YJCVBEREREREREREZEuKEQVERERERERERER6YJCVBEREREZlp555hksy8KyLE4//fSBbk6/u/HGGwuf/8Ybbxzo5oiIiIgMaQpRRURERERERERERLqgEFVEREREZJBTr1IRERGRgaUQVURERERERERERKQL7kA3QEREREREet+NN96oXqsiIiIivUQ9UUVERERERERERES6oBBVREREREREREREpAsKUUVERERGqNraWm655RbOPvtsJk2aRDwep6ysjCOPPJLPfvazLFu2bK/nPfTQQ4VFjo444oge32/z5s04joNlWbiuy7Zt2/ao09DQwAMPPMDVV1/NSSedRFVVFdFolJKSEg499FAWLFjAr3/9a4IgOODP3dEzzzxT+Cynn356j85pr29ZVpf1NmzYwO23386CBQs46qijKC0tJRKJUFlZydFHH81nPvMZXnrppS6vcfrpp2NZFjfddFNh30033dSpDe2vRYsWdTp3fxejyuVyLF68mAsuuIApU6aQSCQoKSnhiCOO4Morr+TJJ5/s9hoAU6dOLdx3/fr1QPhn//Wvf51Zs2ZRVlZGKpVixowZXHvttWzYsKFH121ubuaOO+7gvPPOY/LkySSTSSKRCKWlpcyYMYP58+fz7W9/mzfffLNH1xMRERHZH5oTVURERGQEuu2227jhhhtoaGjotD+TydDQ0MBbb73F7bffzhVXXMHtt99ONBot1DnvvPMoKyujvr6ed955h1dffZUTTjih23vef//9hfBz7ty5jB07ttPxhx56iEsvvZRMJrPHublcjqamJtatW8eDDz7IrFmz+N///V8OOeSQA/n4fe7f//3fueWWWzDG7HGsrq6Ouro63nzzTe644w4uueQS7r77bpLJ5AC0NPTyyy9z2WWXsXbt2k770+k0TU1NvPPOO9xzzz2cffbZ3H///VRVVfX42g8//DCLFi3a43vt7bff5u233+buu+/mN7/5Deedd94+r/Hiiy9y8cUX8/777+9xrLGxkcbGRt5++23+8Ic/cMMNN5DL5XBd/VNHREREeo+eLERERERGmOuuu44f/ehHhe2qqipOOeUUxo4dSzqd5vXXX+fNN9/EGMM999zDli1bePTRR7HtcBBTLBbj4osv5qc//SkA9913X49C1Pvuu69Q/pd/+Zc9jm/fvr0QoE6cOJEjjzySsWPHkkwmaW5u5q233mL58uUYY/jb3/7GnDlzWLFiBZWVlQf19egLmzZtwhhT6K17xBFHUFlZSSQSoba2ltdff70QWD744IM0Njbyhz/8YY/erR/72Mc46qijeOWVV3j11VcBOOGEEzjxxBP3uOfJJ598QG199tln+chHPkJraysQ9rQ98cQTOfLII8lms7z00kuFtj755JOceuqpPP/884waNarbaz/11FN8+tOfxvd9Jk+ezCmnnEJJSQnvvfcezzzzDJ7n0dbWxsc//nHefPPNvYbimzZt4txzz6WpqQmASCTCCSecwGGHHUYymaSlpYX169fzt7/9jcbGxgP6GoiIiIh0y4iIiIjIiHH33XcbwACmpKTE/PSnPzXZbHaPek8//bSZMGFCoe53v/vdTsf/8pe/FI6NGTPGeJ7X5X1XrlxZqJ9KpUxzc/MedX7/+9+b73znO+bdd9/d53XWrVtnzj333MK1rrzyyn3W/fOf/1yod9pppx1wnd211+/qUfp73/ueWbx4sdmxY8c+6zz77LPmsMMOK1zrF7/4xT7rfvOb3yzU++Y3v9mjdvbknLq6uk5/zocffrhZtmzZHvV++ctfmkQiUag3f/78fd53ypQphXqxWMykUinzi1/8wgRB0Knem2++2eneV1xxxV6vd9111xXqzJ4927z//vt7rZfL5cwzzzxjLrvssm6/H0VERET2l+ZEFRERERkhmpqa+Nd//VcAotEof/rTn7jqqquIRCJ71D3jjDN48sknicfjAHzve98r9FQEmD17NlOmTAGgurqap556qst7//KXvyyUP/axj5FKpfaoM3/+fK6//noOO+ywfV7nkEMO4ZFHHuGYY44Bwt6tO3fu7PLeA+Hf//3fWbRoUZfD3mfPnt3pa/zjH/+4v5pXcOuttxaGyJeXl7N06VKOP/74PepddtllnXoSP/LIIzz77LPdXj+bzfLb3/6Wyy+/fI9eth/4wAe48847C9u/+c1v8Dxvj2s899xzhfI999zD+PHj93ov13U57bTT+OUvf4njON22TURERGR/KEQVERERGSHuuece6uvrAbjmmms46aSTuqw/c+ZMFi5cCISLUD3++OOFY5ZlcdlllxW2O4akuzPGcP/99xe2L7/88gNpfkEkEincO51O8/zzzx/U9QbS1KlTOeOMMwB49dVX+3U4ujGGn/zkJ4Xtr3/960yaNGmf9T/2sY/xkY98pLB9++23d3uP888/nw9/+MP7PD5v3rzC3LjtUzbsruPXpCdTCIiIiIj0Bc2JKiIiIjJCPPbYY4XypZde2qNzzjzzzEJvweeff54LL7ywcOzyyy/n29/+NhAuHtTa2rrXxZGeffZZNm3aBMDYsWM566yzur1vfX09L730EqtWraK2tpbm5ubColQAq1evLpRXrFjB/Pnze/R5BsLGjRt55ZVXeOedd6ivr6etra3TglPvvfceQGGu19mzZ/dLu9566y22bdsGgOM4fOITn+j2nKuuuoo//vGPADzzzDPd1r/44ou7PG5ZFrNmzSq0Y/369Rx99NGd6kyaNIl3330XgDvuuIOvfOUr3d5XREREpLcpRBUREREZIV588cVC+Sc/+Qk/+9nPuj1n8+bNhXJ7ENpu5syZHHfccSxfvpzm5mYefvjhvYazHXupLliwoMuh1ps3b+b666/nt7/9bWGRqe7U1NT0qF5/e/HFF7n++ut57rnnOoWmXenPz/L6668Xyu0LX3Xn1FNPLZS3bdvGli1b9jm8HtgjEN2bjvfdW0/cj3/84zz99NMAXH/99Tz55JNcdtllnH322UycOLHb64uIiIj0BoWoIiIiIiNAc3NzYXVzgLvuumu/r7G3uUcvv/xyli9fDoTzk+4eomYyGX772992qr8vr7/+OnPnzt3vOU47fq7B4p577uGqq67qcXjarj8/y44dOwrl9vltuzNmzBji8TjpdBoIQ9+uQtTS0tJur9lxTt5cLrfH8auuuorHH3+chx9+GIClS5eydOlSACZPnszs2bM544wz+Kd/+qcu56AVERERORiaE1VERERkBGhoaDjoa+xt0Z+OPUv/9Kc/dQrmAB599NHCPKxHHnkkxx133F6vnclkuOiiiwoB6qhRo/ja177Gn//8ZzZt2kRLSwtBEGCMwRjD4sWLC+d2HOY/GPz973/n6quvLgSoH/jAB/jRj37EK6+8QnV1dWE4f/urfd5Z6N/P0tzcXCjvbaGvfelYt7vQd/fFpA6E4zg89NBD3HXXXRx55JGdjm3cuJH77ruPq666ivHjx3PVVVdRV1d30PcUERER2Z16ooqIiIiMALuHZHV1dZSXlx/0ddvnOH3iiSfwPI9f/epXfO5znysc77iie1e9UH/3u98V5gadMGECr776KuPGjdtn/YHqfdqTkPPWW28tBM7nnnsuv//974lGo/usP1CfpaioqFBuaWnp8Xkd6xYXF/dqm/bFsiyuvPJKrrzySt555x3+8pe/8MILL/Dcc8+xbt06IOzFevfdd/PMM8/w4osvahEqERER6VXqiSoiIiIyApSVlRGLxQrb7Qv59IaO4WjH+U/r6+t59NFHgTAEu+yyy/Z5jfbh2QDXXXddlwEqwIYNGw60uZ10HEq+t562u+tJj96On+U///M/uwxQofc+y/7qGDJu3LixR+ds3769MJQfGJDh89OnT+f//t//y7333svatWt5++23+dKXvlToEb127Vpuuummfm+XiIiIDG8KUUVERERGiBNPPLFQfuGFF3rtuh/72McKPV1ffvll1q5dC9Bpcag5c+YwefLkfV5jy5YthXJPFiN69tlnD6bJBSUlJYVybW1tt/VXrlzZbZ39+SwNDQ288cYb3V6zN4bF7+6DH/xgobx69eoeDYPv+H0zduzYLudD7S/Tp0/nlltu6RSc/v73vx/AFomIiMhwpBBVREREZIQ4//zzC+Xbb799vxc92pdUKsUFF1xQ2G7vjdqxV2pXQ/kBbHvXY2lra2uXdV977TVeffXVA2jpnqZMmVIIKNesWdNpntC9+fWvf93tNffns9x11117XUxpd/F4vFDuSf2emDlzJmPHjgXA9/1Of177cvfddxfKZ5xxRq+0o7d89KMfLZSrq6sHsCUiIiIyHClEFRERERkhrr76asrKygBYvnz5fg15rqmpwff9fR7/l3/5l0L5vvvuY9OmTYXeovF4nIsvvrjL60+bNq1Q7qoXYWtrK5/61Kd62uxulZSUMGPGDCAczt9xDtfdvf766/z0pz/t9po9/Szvvvtuj/8MKisrC+X333+/R+d0x7KsTl/Lm2++uctr//73vy9MzwDw6U9/ulfa0Z2ampoe1du0aVOhPHr06L5qjoiIiIxQClFFRERERojS0lJ++MMfFrZvuukmFi5cuM/5MI0xvPDCC1xzzTVMnjyZtra2fV77rLPOKvRqfPfdd/niF79Y6Ol6/vnnU1pa2mXb5s+fXyj/7Gc/45ZbbtkjtF2zZg3nnHMOy5cv36/V5Ltz6aWXFsrXX389zz///B51/vjHP3LOOef0aFh9x8/ypS99iSeeeGKPOkuXLuX000+nqampR5/lqKOOKpT/9Kc/9Whu1p647rrrmDBhAhBOZzB37lxWrFixR70HH3yQBQsWFLbnz5/PnDlzeqUN3Zk8eTJXX301f/nLX/a5sNeyZcu49tprC9sf+chH+qVtIiIiMnK4A90AEREREek/ixYtYt26dfzHf/wHAD//+c+57777OPbYY5kxYwZFRUU0NzezefNmVqxY0eOwznEcLrnkEm699VYAfve73xWOdeylui/nnHMOc+bM4dlnn8UYw7/9279x2223cdxxx1FaWsq7777LX//6V3zfZ8KECXzhC1/gy1/+8v5/Afbi2muv5fbbb2fLli3U19czZ84cTj31VGbMmEE6nWbZsmWsXr0agHvvvZdFixZ1eb3rrruOu+66ix07dlBXV8eHP/xhjjvuOI488kgsy2L58uWsWrUKgHPPPZfRo0fzi1/8ostrnnjiiUyaNIlNmzaxdetWZsyYwTnnnENVVVUh2D3hhBP453/+5/367OXl5dx///185CMfobW1lbfffpvjjjuOk046iSOPPJJsNstLL73EmjVrCuccfvjhnYb197W2tjZ+8pOf8JOf/ITi4mKOPfZYpkyZQiqVoqamhtWrVxe+nhAumHXjjTf2W/tERERkZFCIKiIiIjLC3HzzzRx11FF88YtfZMuWLfi+z2uvvcZrr722z3NOPPHETivZ783ll19eCFHbVVZW9rhX4K9//WvmzZvH8uXLAXjvvfd47733OtU58sgj+c1vfsMrr7zSo2v2RGlpKY888gjnnnsuNTU1GGN4/vnnO/VIjUaj/PCHP2ThwoXdhqijR49myZIlfPSjHy0MRV++fHnhc7W74IILuPfee/nCF77QbRtt2+Z//ud/uOiii8hms2zbto2f//znneosXLhwv0NUCBf9Wrp0KZdddhnr1q3DGMNLL73ESy+9tEfds846i/vvv59Ro0bt930OVHuwD9DU1MRzzz3Hc889t9e6s2bN4sEHHxwUC16JiIjI8KIQVURERGQE+vjHP84//dM/8eCDD/LEE0/w6quvsmPHDpqbm0mlUkyYMIGZM2cye/Zs5s2bx/Tp07u95vHHH8/MmTN56623Ot2nu/C13ZgxY/jrX//KXXfdxYMPPsibb75Ja2sro0eP5ogjjuCf//mfueyyy0gmk70aogIcd9xxrF69mv/6r//ikUce4b333iMIAiZOnMjZZ5/NNddcw5FHHtnj651yyimsWrWKW2+9lUceeYR169YBMG7cOI4//nguv/zyTsP+e+L8889n2bJl3HbbbTz//PNs3LiR5ubmXlkg7OSTT+att97il7/8JQ8//DArVqxg+/btRCIRxo4dyz/+4z+yYMECzjnnnIO+1/6qra3l2Wef5S9/+Quvvvoq7777LtXV1aTTaZLJJBMnTuT444/noosu4qMf/Winhb1EREREeotlemtZVhEREREREREREZFhSL+mFREREREREREREemCQlQRERERERERERGRLihEFREREREREREREemCQlQRERERERERERGRLihEFREREREREREREemCQlQRERERERERERGRLihEFREREREREREREemCQlQRERERERERERGRLihEFREREREREREREemCQlQRERERERERERGRLihEFREREREREREREemCQlQRERERERERERGRLihEFREREREREREREemCQlQRERERERERERGRLihEFREREREREREREenC/w+thqhuap6LlwAAAABJRU5ErkJggg==", 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", 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" ] @@ -463,12 +463,12 @@ ], "source": [ "df = manager.select(function_ids=[1]).load(False, True)\n", - "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", + "df = iohinspector.metrics.add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", "hv_indicator = iohinspector.indicators.anytime.HyperVolume(reference_point = [1.1, 1.1])\n", "\n", "df_hv = iohinspector.plots.plot_indicator_over_time(\n", " df, ['obj1', 'obj2'], hv_indicator, \n", - " evals_min=10, evals_max=2000, nr_eval_steps=50, free_variable='algorithm_name'\n", + " eval_min=10, eval_max=2000, eval_steps=50, free_var='algorithm_name'\n", ")" ] }, @@ -484,12 +484,12 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 41, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -500,14 +500,14 @@ ], "source": [ "df = manager.select(function_ids=[1]).load(False, True)\n", - "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", + "df = iohinspector.metrics.add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", "ref_set = iohinspector.indicators.get_reference_set(df, ['obj1', 'obj2'], 1000)\n", "\n", "igdp_indicator = iohinspector.indicators.anytime.IGDPlus(reference_set = ref_set)\n", "\n", "df_igdp = iohinspector.plots.plot_indicator_over_time(\n", " df, ['obj1', 'obj2'], igdp_indicator, \n", - " evals_min=10, evals_max=2000, nr_eval_steps=50, free_variable='algorithm_name'\n", + " eval_min=10, eval_max=2000, eval_steps=50, free_var='algorithm_name'\n", ")" ] }, @@ -529,26 +529,26 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 43, "metadata": {}, "outputs": [], "source": [ "df = manager.load(False, True)\n", - "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", + "df = iohinspector.metrics.add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", "evals = iohinspector.metrics.get_sequence(10, 2000, 2000, cast_to_int=True, scale_log=False)\n", "hv_indicator = iohinspector.indicators.anytime.HyperVolume(reference_point = [1.1, 1.1])\n", - "df_hv = iohinspector.indicators.add_indicator(df, hv_indicator, objective_columns = ['obj1', 'obj2'], evals = evals)\n", + "df_hv = iohinspector.indicators.add_indicator(df, hv_indicator, obj_vars = ['obj1', 'obj2'], evals = evals)\n", "df_hv = df_hv.with_columns((pl.col('HyperVolume')/1.21).alias('eaf'))" ] }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 46, "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -558,7 +558,7 @@ } ], "source": [ - "_ = iohinspector.plots.plot_single_function_fixed_budget(df_hv, fval_variable='eaf', maximization=True)" + "_ = iohinspector.plots.plot_single_function_fixed_budget(df_hv, fval_var='eaf', maximization=True)" ] }, { @@ -574,12 +574,36 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 49, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "text/plain": [ + "(,\n", + " obj1 obj2 eaf\n", + " 0 0.000000e+00 0.278460 0.2\n", + " 60 4.928938e-07 0.278460 0.4\n", + " 1 4.928938e-07 0.231651 0.2\n", + " 129 2.007482e-06 0.293080 0.6\n", + " 130 3.474061e-06 0.278460 0.6\n", + " .. ... ... ...\n", + " 192 9.822622e-01 0.015580 0.6\n", + " 128 9.832064e-01 0.004345 0.4\n", + " 59 9.938718e-01 0.000000 0.2\n", + " 277 9.949035e-01 0.027837 1.0\n", + " 193 9.974315e-01 0.009963 0.6\n", + " \n", + " [278 rows x 3 columns])" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" ] @@ -590,8 +614,8 @@ ], "source": [ "df = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False)\n", - "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", - "iohinspector.plots.plot_eaf_pareto(df, 'obj1', 'obj2', scale_xlog=False, scale_ylog=False)" + "df = iohinspector.metrics.add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", + "iohinspector.plots.plot_eaf_pareto(df, 'obj1', 'obj2')" ] }, { @@ -605,7 +629,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 51, "metadata": {}, "outputs": [ { @@ -632,9 +656,23 @@ }, { "data": { - "image/png": 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"text/plain": [ - "
" + "(,\n", + " {'10': ,\n", + " '100': ,\n", + " '1000': ,\n", + " '2000': })" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" ] }, "metadata": {}, @@ -643,7 +681,7 @@ ], "source": [ "df = manager.select(function_ids=[0]).load(False, True)\n", - "df = iohinspector.metrics.add_normalized_objectives(df, obj_cols = ['raw_y', 'F2'])\n", + "df = iohinspector.metrics.add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", "\n", "#The cast-to-int is there to handle data type differences and prevent duplicate values for function evaluation count\n", "evals = [10,100,1000,2000]\n", diff --git a/examples/SO_Examples.ipynb b/examples/SO_Examples.ipynb index 26b8fdb..5e3de89 100644 --- a/examples/SO_Examples.ipynb +++ b/examples/SO_Examples.ipynb @@ -404,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, "outputs": [ { diff --git a/image.png b/image.png deleted file mode 100644 index 7ba9c9f1db0287128136ed72f25d4ae79bc281ad..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 66843 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a/src/iohinspector/indicators/__init__.py b/src/iohinspector/indicators/__init__.py index cf2e4fd..4c8842b 100644 --- a/src/iohinspector/indicators/__init__.py +++ b/src/iohinspector/indicators/__init__.py @@ -8,7 +8,7 @@ from .final import * def add_indicator( - df: pl.DataFrame, indicator: Callable, objective_columns: Iterable, **kwargs + df: pl.DataFrame, indicator: Callable, obj_vars: Iterable, **kwargs ) -> pl.DataFrame: """Adds an indicator to a Polars DataFrame. @@ -39,6 +39,6 @@ def add_indicator( group of data. """ indicator_callable = partial( - indicator, objective_columns=objective_columns, **kwargs + indicator, obj_vars=obj_vars, **kwargs ) return df.group_by("data_id").map_groups(indicator_callable) diff --git a/src/iohinspector/indicators/anytime.py b/src/iohinspector/indicators/anytime.py index 320b085..0745a5e 100644 --- a/src/iohinspector/indicators/anytime.py +++ b/src/iohinspector/indicators/anytime.py @@ -51,8 +51,8 @@ def _r2(weight_vec_set, ideal_point, point_set): class NonDominated: - def __call__(self, group: pl.DataFrame, objective_columns: Iterable): - objectives = np.array(group[objective_columns]) + def __call__(self, group: pl.DataFrame, obj_vars: Iterable): + objectives = np.array(group[obj_vars]) is_efficient = np.ones(objectives.shape[0], dtype=bool) for i, c in enumerate(objectives[1:]): if is_efficient[i + 1]: @@ -82,12 +82,12 @@ def minimize(self): return False def __call__( - self, group: pl.DataFrame, objective_columns: Iterable, evals: Iterable[int] + self, group: pl.DataFrame, obj_vars: Iterable, evals: Iterable[int] ) -> pl.DataFrame: """ Args: group (pl.DataFrame): The DataFrame on which the indicator will be added (should be 1 optimization run only) - objective_columns (Iterable): Which columns are the objectives + obj_vars (Iterable): Which columns are the objectives evals (Iterable[int]): At which evaluations the operation should be performed. Note that using more evaluations will make the code slower. @@ -95,7 +95,7 @@ def __call__( pl.DataFrame: a new DataFrame with columns of 'evals' and corresponding IGD+ """ obj_vals = np.clip( - np.array(group[objective_columns]), None, self.reference_point + np.array(group[obj_vars]), None, self.reference_point ) evals_dt = group["evaluations"] hvs = [ @@ -111,7 +111,7 @@ def __call__( ) .join_asof(group.sort("evaluations"), on="evaluations", strategy="backward") .fill_null(np.inf) - .drop(objective_columns) + .drop(obj_vars) ) @@ -140,12 +140,12 @@ def minimize(self): return True def __call__( - self, group: pl.DataFrame, objective_columns: Iterable, evals: Iterable[int] + self, group: pl.DataFrame, obj_vars: Iterable, evals: Iterable[int] ) -> pl.DataFrame: """ Args: group (pl.DataFrame): The DataFrame on which the indicator will be added (should be 1 optimization run only) - objective_columns (Iterable): Which columns are the objectives + obj_vars (Iterable): Which columns are the objectives evals (Iterable[int]): At which evaluations the operation should be performed. Note that using more evaluations will make the code slower. @@ -153,7 +153,7 @@ def __call__( pl.DataFrame: a new DataFrame with columns of 'evals' and corresponding IGD+ """ obj_vals = np.clip( - np.array(group[objective_columns]), None, self.reference_point + np.array(group[obj_vars]), None, self.reference_point ) evals_dt = group["evaluations"] hvs = [ @@ -172,7 +172,7 @@ def __call__( ) .join_asof(group.sort("evaluations"), on="evaluations", strategy="backward") .fill_null(np.inf) - .drop(objective_columns) + .drop(obj_vars) ) @@ -195,7 +195,7 @@ def var_name(self): return "IGD+" def __call__( - self, group: pl.DataFrame, objective_columns: Iterable, evals: Iterable[int] + self, group: pl.DataFrame, obj_vars: Iterable, evals: Iterable[int] ) -> pl.DataFrame: """ @@ -208,7 +208,7 @@ def __call__( Returns: pl.DataFrame: a new DataFrame with columns of 'evals' and corresponding IGD+ """ - obj_vals = np.array(group[objective_columns]) + obj_vals = np.array(group[obj_vars]) evals_dt = group["evaluations"] igds = [ igd_plus( @@ -226,7 +226,7 @@ def __call__( ) .join_asof(group.sort("evaluations"), on="evaluations", strategy="backward") .fill_null(np.inf) - .drop(objective_columns) + .drop(obj_vars) ) try: @@ -251,7 +251,7 @@ def minimize(self): return True def __call__( - self, group: pl.DataFrame, objective_columns: Iterable, evals: Iterable[int] + self, group: pl.DataFrame, obj_vars: Iterable, evals: Iterable[int] ) -> pl.DataFrame: """ @@ -264,7 +264,7 @@ def __call__( Returns: pl.DataFrame: a new DataFrame with columns of 'evals' and corresponding IGD+ """ - obj_vals = np.array(group[objective_columns]) + obj_vals = np.array(group[obj_vars]) evals_dt = group["evaluations"] igds = [ _r2( @@ -283,7 +283,7 @@ def __call__( ) .join_asof(group.sort("evaluations"), on="evaluations", strategy="backward") .fill_null(np.inf) - .drop(objective_columns) + .drop(obj_vars) ) except ImportError: diff --git a/src/iohinspector/indicators/final.py b/src/iohinspector/indicators/final.py index af25329..44a0c31 100644 --- a/src/iohinspector/indicators/final.py +++ b/src/iohinspector/indicators/final.py @@ -6,8 +6,8 @@ class NonDominated: - def __call__(self, group: pl.DataFrame, objective_columns: Iterable): - objectives = np.array(group[objective_columns]) + def __call__(self, group: pl.DataFrame, obj_vars: Iterable): + objectives = np.array(group[obj_vars]) return group.with_columns( pl.Series(name="final_nondominated", values=is_nondominated(objectives)) ) diff --git a/src/iohinspector/metrics/__init__.py b/src/iohinspector/metrics/__init__.py index a6df82b..6ad6e10 100644 --- a/src/iohinspector/metrics/__init__.py +++ b/src/iohinspector/metrics/__init__.py @@ -3,7 +3,8 @@ from .fixed_target import (aggregate_running_time) from .aocc import (get_aocc) from .ecdf import (get_data_ecdf) -from .eaf import (get_discritized_eaf_single_objective) -from .ranking import (get_tournament_ratings) +from .eaf import (get_discritized_eaf_single_objective, get_eaf_data, get_eaf_pareto_data, get_eaf_diff_data) +from .ranking import (get_tournament_ratings,get_robustrank_over_time, get_robustrank_changes) from .attractor_network import (get_attractor_network) -from .trajectory import (get_trajectory) \ No newline at end of file +from .trajectory import (get_trajectory) +from .single_run import (get_heatmap_single_run_data) diff --git a/src/iohinspector/metrics/aocc.py b/src/iohinspector/metrics/aocc.py index 4ed4db9..92a6e1e 100644 --- a/src/iohinspector/metrics/aocc.py +++ b/src/iohinspector/metrics/aocc.py @@ -1,15 +1,30 @@ import polars as pl +import pandas as pd from typing import Iterable, Callable from functools import partial -def _aocc(group: pl.DataFrame, max_budget: int, fval_col: str = "eaf"): +def _aocc( + group: pl.DataFrame, + eval_max: int, + fval_var: str = "eaf" +) -> pl.DataFrame: + """Internal helper function to calculate AOCC contribution for a single data group. + + Args: + group (pl.DataFrame): A single group DataFrame containing evaluation data for one run. + eval_max (int): Maximum value of evaluations to consider for AOCC calculation. + fval_var (str, optional): Which data column specifies the performance value. Defaults to "eaf". + + Returns: + pl.DataFrame: DataFrame with added 'aocc_contribution' column containing normalized area contributions. + """ group = group.cast({"evaluations": pl.Int64}).filter( - pl.col("evaluations") <= max_budget + pl.col("evaluations") <= eval_max ) new_row = pl.DataFrame( { - "evaluations": [0, max_budget], - fval_col: [group[fval_col].min(), group[fval_col].max()], + "evaluations": [0, eval_max], + fval_var: [group[fval_var].min(), group[fval_var].max()], } ) group = ( @@ -23,9 +38,9 @@ def _aocc(group: pl.DataFrame, max_budget: int, fval_col: str = "eaf"): ( ( pl.col("evaluations").diff(n=1, null_behavior="ignore") - * (pl.col(fval_col).shift(1)) + * (pl.col(fval_var).shift(1)) ) - / max_budget + / eval_max ).alias("aocc_contribution") ) @@ -33,27 +48,32 @@ def _aocc(group: pl.DataFrame, max_budget: int, fval_col: str = "eaf"): def get_aocc( data: pl.DataFrame, - max_budget: int, - fval_col: str = "eaf", - group_cols: Iterable[str] = ["function_name", "algorithm_name"], -): - """Helper function for AOCC calculations + eval_max: int, + fval_var: str = "eaf", + free_vars: Iterable[str] = ["function_name", "algorithm_name"], + return_as_pandas: bool = True, +) -> pl.DataFrame | pd.DataFrame: + """Calculate Area Over Convergence Curve (AOCC) metric for algorithm performance evaluation. Args: - data (pl.DataFrame): The data object to use for getting the performance. - max_budget (int): Maxium value of evaluations to use - fval_col (str, optional): Which data column specifies the performance value. Defaults to "eaf". - group_cols (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["function_name", "algorithm_name"]. + data (pl.DataFrame): The data object containing performance evaluation data. + eval_max (int): Maximum value of evaluations to use for AOCC calculation. + fval_var (str, optional): Which data column specifies the performance value. Defaults to "eaf". + free_vars (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["function_name", "algorithm_name"]. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. Returns: - pl.DataFrame: a polars dataframe with the area under the EAF (=area over convergence curve) + pl.DataFrame or pd.DataFrame: A dataframe with the area under the EAF (=area over convergence curve). """ aocc_contribs = data.group_by(*["data_id"]).map_groups( - partial(_aocc, max_budget=max_budget, fval_col=fval_col) + partial(_aocc, eval_max=eval_max, fval_var=fval_var) ) - aoccs = aocc_contribs.group_by(["data_id"] + group_cols).agg( + aoccs = aocc_contribs.group_by(["data_id"] + free_vars).agg( pl.col("aocc_contribution").sum() ) - return aoccs.group_by(group_cols).agg( + final_df = aoccs.group_by(free_vars).agg( pl.col("aocc_contribution").mean().alias("AOCC") ) + if return_as_pandas: + return final_df.to_pandas() + return final_df diff --git a/src/iohinspector/metrics/attractor_network.py b/src/iohinspector/metrics/attractor_network.py index 9951057..08bee2c 100644 --- a/src/iohinspector/metrics/attractor_network.py +++ b/src/iohinspector/metrics/attractor_network.py @@ -4,7 +4,23 @@ from typing import Iterable, Tuple -def _get_nodeidx(xloc, yval, nodes, epsilon): +def _get_nodeidx( + xloc: np.ndarray, + yval: float, + nodes: pd.DataFrame, + epsilon: float +): + """Internal helper function to find existing node index based on position and function value. + + Args: + xloc (array-like): Position coordinates to search for in the network. + yval (float): Function value to match with existing nodes. + nodes (pd.DataFrame): DataFrame containing existing network nodes. + epsilon (float): Tolerance threshold for considering positions as identical. + + Returns: + int: Index of matching node if found, -1 otherwise. + """ if len(nodes) == 0: return -1 candidates = nodes[np.isclose(nodes["y"], yval, atol=epsilon)] @@ -19,28 +35,29 @@ def _get_nodeidx(xloc, yval, nodes, epsilon): def get_attractor_network( - data, - coord_vars=["x1", "x2"], + data: pl.DataFrame, + coord_vars: Iterable[str] = ["x1", "x2"], fval_var: str = "raw_y", eval_var: str = "evaluations", maximization: bool = False, - beta=40, - epsilon=0.0001, + beta: int = 40, + epsilon: float = 0.0001, eval_max=None, -): - """Create an attractor network from the provided data +) -> Tuple[pd.DataFrame, pd.DataFrame]: + """Create an attractor network from optimization trajectory data. Args: - data (pl.DataFrame): The original dataframe, should contain the performance and position information - coord_vars (Iterable[str], optional): Which columns correspond to position information. Defaults to ['x1', 'x2']. - fval_var (str, optional): Which column corresponds to performance. Defaults to 'raw_y'. - eval_var (str, optional): Which column corresponds to evaluations. Defaults to 'evaluations'. + data (pl.DataFrame): The original dataframe containing performance and position information. + coord_vars (Iterable[str], optional): Which columns correspond to position information. Defaults to ["x1", "x2"]. + fval_var (str, optional): Which column corresponds to performance values. Defaults to "raw_y". + eval_var (str, optional): Which column corresponds to evaluation numbers. Defaults to "evaluations". maximization (bool, optional): Whether fval_var is to be maximized. Defaults to False. - beta (int, optional): Minimum stagnation lenght. Defaults to 40. + beta (int, optional): Minimum stagnation length threshold. Defaults to 40. epsilon (float, optional): Radius below which positions should be considered identical in the network. Defaults to 0.0001. - eval_max (int, optional): Maximum evaluation number. Defaults to the maximum of eval_var if None. + eval_max (int, optional): Maximum evaluation number to consider. Defaults to the maximum of eval_var if None. + Returns: - pd.DataFrame, pd.DataFrame: two dataframes containing the nodes and edges of the network respectively. + tuple[pd.DataFrame, pd.DataFrame]: Two DataFrames containing the nodes and edges of the network respectively. """ running_idx = 0 diff --git a/src/iohinspector/metrics/eaf.py b/src/iohinspector/metrics/eaf.py index a16d713..b2c339e 100644 --- a/src/iohinspector/metrics/eaf.py +++ b/src/iohinspector/metrics/eaf.py @@ -3,22 +3,45 @@ from iohinspector.metrics import transform_fval, get_sequence import numpy as np import pandas as pd +import polars as pl +from moocore import eaf, eafdiff def get_discritized_eaf_single_objective( - data, - fval_var: str = "raw_y", - eval_var: str = "evaluations", - eval_values = None, - eval_min = None, - eval_max = None, - eval_targets = 10, - scale_eval_log: bool = True, - f_min = 1e-8, - f_max = 1e2, - scale_f_log: bool = True, - f_targets = 101, - ): + data: pl.DataFrame, + fval_var: str = "raw_y", + eval_var: str = "evaluations", + eval_values = None, + eval_min = None, + eval_max = None, + eval_targets = 10, + scale_eval_log: bool = True, + f_min = 1e-8, + f_max = 1e2, + scale_f_log: bool = True, + f_targets = 101, + return_as_pandas: bool = True, +) -> pd.DataFrame | pl.DataFrame: + """Generate discretized EAF data for single-objective optimization problems. + + Args: + data (pl.DataFrame): The data object containing optimization trajectory data. + fval_var (str, optional): Which column contains the function values. Defaults to "raw_y". + eval_var (str, optional): Which column contains the evaluation numbers. Defaults to "evaluations". + eval_values (array-like, optional): Specific evaluation values to use. If None, generated from eval_min/max. + eval_min (int, optional): Minimum evaluation value. If None, uses minimum from data. + eval_max (int, optional): Maximum evaluation value. If None, uses maximum from data. + eval_targets (int, optional): Number of evaluation targets to generate. Defaults to 10. + scale_eval_log (bool, optional): Whether to use logarithmic scaling for evaluations. Defaults to True. + f_min (float, optional): Minimum function value for scaling. Defaults to 1e-8. + f_max (float, optional): Maximum function value for scaling. Defaults to 1e2. + scale_f_log (bool, optional): Whether to use logarithmic scaling for function values. Defaults to True. + f_targets (int, optional): Number of function value targets to generate. Defaults to 101. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. + + Returns: + pd.DataFrame: A DataFrame with discretized EAF data for single-objective problems. + """ if eval_values is None: if eval_min is None: @@ -41,7 +64,7 @@ def get_discritized_eaf_single_objective( lb=f_min, ub=f_max, scale_log=scale_f_log, - fval_col=fval_var, + fval_var=fval_var, ) targets = np.linspace(0, 1, f_targets) dt_targets = pd.DataFrame(targets, columns=["eaf_target"]) @@ -49,5 +72,105 @@ def get_discritized_eaf_single_objective( dt_merged = dt_targets.merge(dt_aligned[[eval_var, 'eaf']].to_pandas(), how='cross') dt_merged['ps'] = dt_merged['eaf_target'] <= dt_merged['eaf'] dt_discr = dt_merged.pivot_table(index='eaf_target', columns=eval_var, values='ps') + if return_as_pandas: + return dt_discr + return pl.from_pandas(dt_discr) + + + +def get_eaf_data( + data: pl.DataFrame, + eval_var: str = "evaluations", + eval_min: int = None, + eval_max: int = None, + scale_eval_log: bool = True, + return_as_pandas: bool = True, + )-> pd.DataFrame | pl.DataFrame: + """Generate aligned EAF data for visualization and analysis. + + Args: + data (pl.DataFrame): The data object containing optimization trajectory data. + eval_var (str, optional): Which column contains the evaluation numbers. Defaults to "evaluations". + eval_min (int, optional): Minimum evaluation value. If None, uses minimum from data. + eval_max (int, optional): Maximum evaluation value. If None, uses maximum from data. + scale_eval_log (bool, optional): Whether to use logarithmic scaling for evaluations. Defaults to True. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. + + Returns: + pd.DataFrame or pl.DataFrame: A DataFrame with aligned EAF data. + """ + + if eval_min is None: + eval_min = data[eval_var].min() + if eval_max is None: + eval_max = data[eval_var].max() + + evals = get_sequence(eval_min, eval_max, 50, scale_eval_log, True) + long = align_data(data, np.array(evals, "uint64"), ["data_id"], output="long") + + if return_as_pandas: + return long.to_pandas() + return long + + +def get_eaf_pareto_data( + data: pl.DataFrame, + obj1_var: str, + obj2_var: str, + return_as_pandas: bool = True, +)-> pd.DataFrame | pl.DataFrame: + """Generate EAF data for multi-objective optimization problems using Pareto fronts. + + Args: + data (pl.DataFrame): The data object containing multi-objective optimization data. + obj1_var (str): Name of the column containing first objective values. + obj2_var (str): Name of the column containing second objective values. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. + + Returns: + pd.DataFrame or pl.DataFrame: A DataFrame with EAF data including objective values and EAF percentiles. + """ + data_to_process = np.array(data[[obj1_var, obj2_var, "data_id"]]) + eaf_data = eaf(data_to_process[:,:-1], data_to_process[:,-1] ) + eaf_data_df = pd.DataFrame(eaf_data) + eaf_data_df.columns = [obj1_var, obj2_var, "eaf"] + # scale EAF values from percentages to proportions + eaf_data_df["eaf"] = eaf_data_df["eaf"].astype(float) / 100.0 + if return_as_pandas: + return eaf_data_df + return pl.from_pandas(eaf_data_df) + + +def get_eaf_diff_data( + data1: pl.DataFrame, + data2: pl.DataFrame, + obj1_var: str, + obj2_var: str, + return_as_pandas: bool = True, +)-> pd.DataFrame | pl.DataFrame: + """Calculate EAF difference data between two multi-objective optimization datasets. + + Args: + data1 (pl.DataFrame): First dataset containing multi-objective optimization data. + data2 (pl.DataFrame): Second dataset containing multi-objective optimization data. + obj1_var (str): Name of the column containing first objective values. + obj2_var (str): Name of the column containing second objective values. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. - return dt_discr + Returns: + pd.DataFrame or pl.DataFrame: A DataFrame with EAF difference rectangles and difference values. + """ + x = np.array(data1[[obj1_var, obj2_var, "data_id"]]) + y = np.array(data2[[obj1_var, obj2_var, "data_id"]]) + if np.array_equal(np.sort(x.view(np.void), axis=0), np.sort(y.view(np.void), axis=0)): + cols = ["x_min", "y_min", "x_max", "y_max", "eaf_diff"] + empty_df = pl.DataFrame({c: [] for c in cols}) + if return_as_pandas: + return empty_df.to_pandas() + return empty_df + eaf_diff_rect = eafdiff(x, y, rectangles=True) + eaf_diff_df = pl.DataFrame(eaf_diff_rect, schema=["x_min", "y_min", "x_max", "y_max", "eaf_diff"]) + + if return_as_pandas: + return eaf_diff_df.to_pandas() + return eaf_diff_df diff --git a/src/iohinspector/metrics/ecdf.py b/src/iohinspector/metrics/ecdf.py index c9dc629..80a3240 100644 --- a/src/iohinspector/metrics/ecdf.py +++ b/src/iohinspector/metrics/ecdf.py @@ -1,4 +1,5 @@ import polars as pl +import pandas as pd from typing import Iterable from .utils import get_sequence from ..align import align_data, turbo_align @@ -12,48 +13,50 @@ def get_data_ecdf( fval_var: str = "raw_y", eval_var: str = "evaluations", free_vars: Iterable[str] = ["algorithm_name"], + f_min: int = None, + f_max: int = None, + scale_f_log: bool = True, + eval_values: Iterable[int] = None, + eval_min: int = None, + eval_max: int = None, + scale_eval_log: bool = True, maximization: bool = False, - x_values: Iterable[int] = None, - x_min: int = None, - x_max: int = None, - scale_xlog: bool = True, - y_min: int = None, - y_max: int = None, - scale_ylog: bool = True, - turbo: bool = False -): - """Function to plot empirical cumulative distribution function (Based on EAF) + turbo: bool = False, + return_as_pandas: bool = True, +) -> pd.DataFrame | pl.DataFrame: + """Generate empirical cumulative distribution function (ECDF) data based on EAF calculations. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - eval_var (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_var (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_vars (Iterable[str], optional): Columns in 'data' which correspond to groups over which data should not be aggregated. Defaults to ["algorithm_name"]. - maximization (bool, optional): Boolean indicating whether the 'fval_var' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. - x_values (Iterable[int], optional): List of x-values at which to get the ECDF data. If not provided, the x_min, x_max and scale_xlog arguments will be used to sample these points. - scale_xlog (bool, optional): Should the x-samples be log-scaled. Defaults to True. - x_min (float, optional): Minimum value to use for the 'eval_var', if not present the min of that column will be used. Defaults to None. - x_max (float, optional): Maximum value to use for the 'eval_var', if not present the max of that column will be used. Defaults to None. - scale_ylog (bool, optional): Should the y-values be log-scaled before normalization. Defaults to True. - y_min (float, optional): Minimum value to use for the 'fval_var', if not present the min of that column will be used. Defaults to None. - y_max (float, optional): Maximum value to use for the 'fval_var', if not present the max of that column will be used. Defaults to None. + data (pl.DataFrame): The DataFrame containing the full performance trajectory data. + fval_var (str, optional): Which column contains the performance measure values. Defaults to "raw_y". + eval_var (str, optional): Which column contains the evaluation numbers. Defaults to "evaluations". + free_vars (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["algorithm_name"]. + f_min (int, optional): Minimum value for function value scaling. If None, uses minimum from data. Defaults to None. + f_max (int, optional): Maximum value for function value scaling. If None, uses maximum from data. Defaults to None. + scale_f_log (bool, optional): Whether to use logarithmic scaling for function values. Defaults to True. + eval_values (Iterable[int], optional): Specific evaluation values to use. If None, generated from eval_min/max. Defaults to None. + eval_min (int, optional): Minimum evaluation value. If None, uses minimum from data. Defaults to None. + eval_max (int, optional): Maximum evaluation value. If None, uses maximum from data. Defaults to None. + scale_eval_log (bool, optional): Whether to use logarithmic scaling for evaluations. Defaults to True. + maximization (bool, optional): Whether the performance measure is being maximized. Defaults to False. + turbo (bool, optional): Whether to use turbo alignment for faster processing. Defaults to False. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. Returns: - pd.DataFrame: pandas dataframe of the ECDF data. + pd.DataFrame or pl.DataFrame: A DataFrame containing the ECDF data with aligned evaluation points. """ - if x_values is None: - if x_min is None: - x_min = data[eval_var].min() - if x_max is None: - x_max = data[eval_var].max() - x_values = get_sequence( - x_min, x_max, 50, scale_log=scale_xlog, cast_to_int=True + if eval_values is None: + if eval_min is None: + eval_min = data[eval_var].min() + if eval_max is None: + eval_max = data[eval_var].max() + eval_values = get_sequence( + eval_min, eval_max, 50, scale_log=scale_eval_log, cast_to_int=True ) if turbo: data_aligned = turbo_align( data.cast({eval_var: pl.Int64}), - x_values, + eval_values, x_col=eval_var, y_col=fval_var, maximization=maximization, @@ -61,7 +64,7 @@ def get_data_ecdf( else: data_aligned = align_data( data.cast({eval_var: pl.Int64}), - x_values, + eval_values, group_cols=["data_id"], x_col=eval_var, y_col=fval_var, @@ -70,14 +73,17 @@ def get_data_ecdf( dt_ecdf = ( transform_fval( data_aligned, - fval_col=fval_var, + fval_var=fval_var, maximization=maximization, - lb=y_min, - ub=y_max, - scale_log=scale_ylog, + lb=f_min, + ub=f_max, + scale_log=scale_f_log, ) .group_by([eval_var] + free_vars) .mean() .sort(eval_var) - ).to_pandas() + ) + + if return_as_pandas: + return dt_ecdf.to_pandas() return dt_ecdf \ No newline at end of file diff --git a/src/iohinspector/metrics/fixed_budget.py b/src/iohinspector/metrics/fixed_budget.py index dea4b4d..572694c 100644 --- a/src/iohinspector/metrics/fixed_budget.py +++ b/src/iohinspector/metrics/fixed_budget.py @@ -1,71 +1,71 @@ import polars as pl +import pandas as pd from typing import Iterable, Callable from .utils import get_sequence from ..align import align_data def aggregate_convergence( data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - x_min: int = None, - x_max: int = None, + eval_var: str = "evaluations", + fval_var: str = "raw_y", + free_vars: Iterable[str] = ["algorithm_name"], + eval_min: int = None, + eval_max: int = None, custom_op: Callable[[pl.Series], float] = None, maximization: bool = False, return_as_pandas: bool = True, -): - """Function to aggregate performance on a fixed-budget perspective +) -> pl.DataFrame | pd.DataFrame: + """Aggregate performance data from a fixed-budget perspective with multiple statistics. Args: - data (pl.DataFrame): The data object to use for getting the performance. Note that the fval, evaluation and free variables as defined in - this object determine the axes of the final performance (most data will have 'raw_y', 'evaluations' and ['algId'] as defaults) - evaluation_variable (str, optional): Column name for evaluation number. Defaults to "evaluations". - fval_variable (str, optional): Column name for function value. Defaults to "raw_y". - free_variables (Iterable[str], optional): Column name for free variables (variables over which performance should not be aggregated). Defaults to ["algorithm_name"]. - x_min (int, optional): Minimum evaulation value to use. Defaults to None (minimum present in data). - x_max (int, optional): Maximum evaulation value to use. Defaults to None (maximum present in data). - custom_op (Callable[[pl.Series], float], optional): Custom aggregation method for performance values. Defaults to None. - maximization (bool, optional): Whether performance metric is being maximized or not. Defaults to False. - return_as_pandas (bool, optional): Whether the data should be returned as Pandas (True) or Polars (False) object. Defaults to True. + data (pl.DataFrame): The data object containing evaluation and performance data. + eval_var (str, optional): Which column contains the evaluation numbers. Defaults to "evaluations". + fval_var (str, optional): Which column contains the function values. Defaults to "raw_y". + free_vars (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["algorithm_name"]. + eval_min (int, optional): Minimum evaluation value to include. If None, uses minimum from data. Defaults to None. + eval_max (int, optional): Maximum evaluation value to include. If None, uses maximum from data. Defaults to None. + custom_op (Callable[[pl.Series], float], optional): Custom aggregation function to apply per group. Defaults to None. + maximization (bool, optional): Whether the objective is being maximized. Defaults to False. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. Returns: - DataFrame: Depending on 'return_as_pandas', a pandas or polars DataFrame with the aggregated performance values + pl.DataFrame or pd.DataFrame: A DataFrame with aggregated performance statistics (mean, min, max, median, std, geometric_mean). """ if(data.is_empty()): raise ValueError("Data is empty, cannot aggregate convergence.") # Getting alligned data (to check if e.g. limits should be args for this function) - if x_min is None: - x_min = data[evaluation_variable].min() - if x_max is None: - x_max = data[evaluation_variable].max() - x_values = get_sequence(x_min, x_max, 50, scale_log=True, cast_to_int=True) - group_variables = free_variables + [evaluation_variable] + if eval_min is None: + eval_min = data[eval_var].min() + if eval_max is None: + eval_max = data[eval_var].max() + x_values = get_sequence(eval_min, eval_max, 50, scale_log=True, cast_to_int=True) + group_variables = free_vars + [eval_var] data_aligned = align_data( - data.cast({evaluation_variable: pl.Int64}), + data.cast({eval_var: pl.Int64}), x_values, - group_cols=["data_id"] + free_variables, - x_col=evaluation_variable, - y_col=fval_variable, + group_cols=["data_id"] + free_vars, + x_col=eval_var, + y_col=fval_var, maximization=maximization, ) aggregations = [ - pl.mean(fval_variable).alias("mean"), - pl.min(fval_variable).alias("min"), - pl.max(fval_variable).alias("max"), - pl.median(fval_variable).alias("median"), - pl.std(fval_variable).alias("std"), - pl.col(fval_variable).log().mean().exp().alias("geometric_mean") + pl.mean(fval_var).alias("mean"), + pl.min(fval_var).alias("min"), + pl.max(fval_var).alias("max"), + pl.median(fval_var).alias("median"), + pl.std(fval_var).alias("std"), + pl.col(fval_var).log().mean().exp().alias("geometric_mean") ] if custom_op is not None: aggregations.append( - pl.col(fval_variable).map_batches( + pl.col(fval_var).map_batches( lambda s: custom_op(s), return_dtype=pl.Float64, returns_scalar=True ).alias(custom_op.__name__) ) dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) if return_as_pandas: - return dt_plot.sort(evaluation_variable).to_pandas() - return dt_plot.sort(evaluation_variable) \ No newline at end of file + return dt_plot.sort(eval_var).to_pandas() + return dt_plot.sort(eval_var) \ No newline at end of file diff --git a/src/iohinspector/metrics/fixed_target.py b/src/iohinspector/metrics/fixed_target.py index 2df7ec5..7d0292a 100644 --- a/src/iohinspector/metrics/fixed_target.py +++ b/src/iohinspector/metrics/fixed_target.py @@ -1,91 +1,91 @@ import polars as pl +import pandas as pd from typing import Iterable, Callable from .utils import get_sequence from ..align import align_data def aggregate_running_time( data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], + eval_var: str = "evaluations", + fval_var: str = "raw_y", + free_vars: Iterable[str] = ["algorithm_name"], f_min: float = None, f_max: float = None, - scale_flog: bool = True, - max_budget: int = None, + scale_f_log: bool = True, + eval_max: int = None, maximization: bool = False, custom_op: Callable[[pl.Series], float] = None, return_as_pandas: bool = True, -): - """Function to aggregate performance on a fixed-target perspective +) -> pl.DataFrame | pd.DataFrame: + """Aggregate performance data from a fixed-target perspective with running time statistics. Args: - data (pl.DataFrame): The data object to use for getting the performance. Note that the fval, evaluation and free variables as defined in - this object determine the axes of the final performance (most data will have 'raw_y', 'evaluations' and ['algId'] as defaults) - evaluation_variable (str, optional): Column name for evaluation number. Defaults to "evaluations". - fval_variable (str, optional): Column name for function value. Defaults to "raw_y". - free_variables (Iterable[str], optional): Column name for free variables (variables over which performance should not be aggregated). Defaults to ["algorithm_name"]. - f_min (float, optional): Minimum function value to use. Defaults to None (minimum present in data). - f_max (float, optional): Maximum function value to use. Defaults to None (maximum present in data). - scale_flog (bool): Whether or not function values should be scaled logarithmically for the x-axis. Defaults to True. - max_budget: If present, what budget value should be the maximum considered. Defaults to None. - custom_op (Callable[[pl.Series], float], optional): Custom aggregation method for performance values. Defaults to None. - maximization (bool, optional): Whether performance metric is being maximized or not. Defaults to False. - return_as_pandas (bool, optional): Whether the data should be returned as Pandas (True) or Polars (False) object. Defaults to True. + data (pl.DataFrame): The data object containing performance and evaluation data. + eval_var (str, optional): Which column contains the evaluation numbers. Defaults to "evaluations". + fval_var (str, optional): Which column contains the function values. Defaults to "raw_y". + free_vars (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["algorithm_name"]. + f_min (float, optional): Minimum function value to use. If None, uses minimum from data. Defaults to None. + f_max (float, optional): Maximum function value to use. If None, uses maximum from data. Defaults to None. + scale_f_log (bool, optional): Whether to use logarithmic scaling for function values. Defaults to True. + eval_max (int, optional): Maximum evaluation value to consider. If None, uses maximum from data. Defaults to None. + maximization (bool, optional): Whether the performance metric is being maximized. Defaults to False. + custom_op (Callable[[pl.Series], float], optional): Custom aggregation function to apply per group. Defaults to None. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. Returns: - DataFrame: Depending on 'return_as_pandas', a pandas or polars DataFrame with the aggregated performance values + pl.DataFrame or pd.DataFrame: A DataFrame with aggregated running time statistics (mean, min, max, median, std, success_ratio, ERT, PAR-10). """ # Getting alligned data (to check if e.g. limits should be args for this function) if f_min is None: - f_min = data[fval_variable].min() + f_min = data[fval_var].min() if f_max is None: - f_max = data[fval_variable].max() - f_values = get_sequence(f_min, f_max, 50, scale_log=scale_flog) - group_variables = free_variables + [fval_variable] + f_max = data[fval_var].max() + f_values = get_sequence(f_min, f_max, 50, scale_log=scale_f_log) + group_variables = free_vars + [fval_var] data_aligned = align_data( data, f_values, - group_cols=["data_id"] + free_variables, - x_col=fval_variable, - y_col=evaluation_variable, + group_cols=["data_id"] + free_vars, + x_col=fval_var, + y_col=eval_var, maximization=maximization, ) - if max_budget is None: - max_budget = data[evaluation_variable].max() + if eval_max is None: + eval_max = data[eval_var].max() aggregations = [ - pl.col(evaluation_variable).mean().alias("mean"), - pl.col(evaluation_variable).min().alias("min"), - pl.col(evaluation_variable).max().alias("max"), - pl.col(evaluation_variable).median().alias("median"), - pl.col(evaluation_variable).std().alias("std"), - pl.col(evaluation_variable).is_finite().mean().alias("success_ratio"), - pl.col(evaluation_variable).is_finite().sum().alias("success_count"), + pl.col(eval_var).mean().alias("mean"), + pl.col(eval_var).min().alias("min"), + pl.col(eval_var).max().alias("max"), + pl.col(eval_var).median().alias("median"), + pl.col(eval_var).std().alias("std"), + pl.col(eval_var).is_finite().mean().alias("success_ratio"), + pl.col(eval_var).is_finite().sum().alias("success_count"), ( - pl.when(pl.col(evaluation_variable).is_finite()) - .then(pl.col(evaluation_variable)) - .otherwise(max_budget) + pl.when(pl.col(eval_var).is_finite()) + .then(pl.col(eval_var)) + .otherwise(eval_max) .sum() - /pl.col(evaluation_variable).is_finite().sum() + /pl.col(eval_var).is_finite().sum() ).alias("ERT"), ( - pl.when(pl.col(evaluation_variable).is_finite()) - .then(pl.col(evaluation_variable)) - .otherwise(10 * max_budget) + pl.when(pl.col(eval_var).is_finite()) + .then(pl.col(eval_var)) + .otherwise(10 * eval_max) .sum() - / pl.col(evaluation_variable).count() + / pl.col(eval_var).count() ).alias("PAR-10"), ] if custom_op is not None: aggregations.append( - pl.col(evaluation_variable) + pl.col(eval_var) .map_batches(lambda s: custom_op(s), return_dtype=pl.Float64, returns_scalar=True) .alias(custom_op.__name__) ) dt_plot = data_aligned.group_by(*group_variables).agg(aggregations) if return_as_pandas: - return dt_plot.sort(fval_variable).to_pandas() - return dt_plot.sort(fval_variable) \ No newline at end of file + return dt_plot.sort(fval_var).to_pandas() + return dt_plot.sort(fval_var) \ No newline at end of file diff --git a/src/iohinspector/metrics/multi_objective.py b/src/iohinspector/metrics/multi_objective.py new file mode 100644 index 0000000..b7f5988 --- /dev/null +++ b/src/iohinspector/metrics/multi_objective.py @@ -0,0 +1,70 @@ + +from typing import Iterable +import polars as pl +import pandas as pd +from iohinspector.indicators import final, add_indicator +from iohinspector.metrics import get_sequence + + +def get_pareto_front_2d( + data: pl.DataFrame, + obj1_var: str = "raw_y", + obj2_var: str = "F2", + return_as_pandas: bool = True, +) -> pl.DataFrame | pd.DataFrame: + """Extract the Pareto front from a 2D multi-objective optimization dataset. + + Args: + data (pl.DataFrame): The data object containing multi-objective optimization data. + obj1_var (str, optional): Which column contains the first objective values. Defaults to "raw_y". + obj2_var (str, optional): Which column contains the second objective values. Defaults to "F2". + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. + + Returns: + pl.DataFrame or pd.DataFrame: A DataFrame containing only the non-dominated Pareto front points. + """ + df = add_indicator(data, final.NonDominated(), [obj1_var, obj2_var]) + df = df.filter(pl.col("final_nondominated") == True) + if return_as_pandas: + return df.to_pandas() + return df + + + +def get_indicator_over_time_data( + data: pl.DataFrame, + indicator: object = None, + obj_vars: Iterable[str] = ["raw_y", "F2"], + eval_min: int = 1, + eval_max: int = 50_000, + scale_eval_log: bool = True, + eval_steps: int = 50, + return_as_pandas: bool = True, +) -> pl.DataFrame | pd.DataFrame: + """Calculate multi-objective indicator values over time for performance analysis. + + Args: + data (pl.DataFrame): The data object containing multi-objective optimization trajectory data. + indicator (object, optional): The indicator object to calculate over time. Defaults to None. + obj_vars (Iterable[str], optional): Which columns contain the objective values. Defaults to ["raw_y", "F2"]. + eval_min (int, optional): Minimum evaluation value to consider. Defaults to 1. + eval_max (int, optional): Maximum evaluation value to consider. Defaults to 50_000. + scale_eval_log (bool, optional): Whether to use logarithmic scaling for evaluations. Defaults to True. + eval_steps (int, optional): Number of evaluation steps to generate. Defaults to 50. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. + + Returns: + pl.DataFrame or pd.DataFrame: A DataFrame with indicator values calculated over the specified evaluation timeline. + """ + + + evals = get_sequence( + eval_min, eval_max, eval_steps, cast_to_int=True, scale_log=scale_eval_log + ) + df = add_indicator( + data, indicator, obj_vars=obj_vars, evals=evals + ) + + if return_as_pandas: + return df.to_pandas() + return df \ No newline at end of file diff --git a/src/iohinspector/metrics/ranking.py b/src/iohinspector/metrics/ranking.py index 0005433..1b7fe9a 100644 --- a/src/iohinspector/metrics/ranking.py +++ b/src/iohinspector/metrics/ranking.py @@ -1,3 +1,4 @@ +from iohinspector.indicators import add_indicator from skelo.model.elo import EloEstimator import numpy as np import pandas as pd @@ -11,31 +12,30 @@ def get_tournament_ratings( data: pl.DataFrame, alg_vars: Iterable[str] = ["algorithm_name"], fid_vars: Iterable[str] = ["function_name"], - perf_var: str = "raw_y", + fval_var: str = "raw_y", nrounds: int = 25, maximization: bool = False, -): - """Method to calculate ratings of a set of algorithm on a set of problems. - Calculated based on nrounds of competition, where in each round all algorithms face all others (pairwise) on every function. - For each round, a sampled performance value is taken from the data and used to determine the winner. - This function uses the ELO rating scheme, as opposed to the Glicko2 scheme used in the IOHanalyzer. Deviations are estimated based on the last 5% of rounds. + return_as_pandas: bool = True, +) -> pl.DataFrame | pd.DataFrame: + """Calculate ELO tournament ratings for algorithms competing on multiple problems. Args: - data (pl.DataFrame): The data object to use for getting the performance. - alg_vars (Iterable[str], optional): Which variables specific the algortihms which will compete. Defaults to ["algorithm_name"]. - fid_vars (Iterable[str], optional): Which variables denote the problems on which will be competed. Defaults to ["function_name"]. - perf_var (str, optional): Which variable corresponds to the performance. Defaults to "raw_y". - nrounds (int, optional): How many round should be played. Defaults to 25. + data (pl.DataFrame): The data object containing algorithm performance data. + alg_vars (Iterable[str], optional): Which columns specify the algorithms that will compete. Defaults to ["algorithm_name"]. + fid_vars (Iterable[str], optional): Which columns denote the problems on which competition occurs. Defaults to ["function_name"]. + fval_var (str, optional): Which column contains the performance values. Defaults to "raw_y". + nrounds (int, optional): Number of tournament rounds to play. Defaults to 25. maximization (bool, optional): Whether the performance metric is being maximized. Defaults to False. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. Returns: - pd.DataFrame: Pandas dataframe with rating, deviation and volatility for each 'alg_vars' combination + pd.DataFrame or pl.DataFrame: A DataFrame with ELO ratings, deviations, and algorithm identifiers. """ fids = data[fid_vars].unique() aligned_comps = data.pivot( index=alg_vars, columns=fid_vars, - values=perf_var, + values=fval_var, aggregate_function=pl.element(), ) players = aligned_comps[alg_vars] @@ -81,4 +81,98 @@ def get_tournament_ratings( ] ).transpose() rating_dt_elo.columns = ["Rating", "Deviation", *players.columns] - return rating_dt_elo + if return_as_pandas: + return rating_dt_elo + else: + rating_dt_elo_pl = pl.from_pandas(rating_dt_elo) + return rating_dt_elo_pl + + +def get_robustrank_over_time( + data: pl.DataFrame, + obj_vars: Iterable[str], + evals: Iterable[int], + indicator: object, + +): + """Calculate robust ranking data over multiple time points for multi-objective optimization. + + Args: + data (pl.DataFrame): The data object containing multi-objective optimization trajectory data. + obj_vars (Iterable[str]): Which columns correspond to the objective values. + evals (Iterable[int]): Evaluation time points at which to calculate rankings. + indicator (object): Indicator object from iohinspector.indicators for performance measurement. + + Returns: + tuple: A tuple containing (comparison, benchmark) objects for robust ranking analysis. + """ + from robustranking import Benchmark + from robustranking.comparison import MOBootstrapComparison + + df = add_indicator( + data, indicator, obj_vars=obj_vars, evals=evals + ).to_pandas() + df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] + dt_pivoted = pd.pivot( + df_part, + index=["algorithm_name", "run_id"], + columns=["evaluations"], + values=[indicator.var_name], + ).reset_index() + dt_pivoted.columns = ["algorithm_name", "run_id"] + evals + benchmark = Benchmark() + benchmark.from_pandas(dt_pivoted, "algorithm_name", "run_id", evals) + comparison = MOBootstrapComparison( + benchmark, + alpha=0.05, + minimise=indicator.minimize, + bootstrap_runs=1000, + aggregation_method=np.mean, + ) + + return comparison, benchmark + + +def get_robustrank_changes( + data: pl.DataFrame, + obj_vars: Iterable[str], + evals: Iterable[int], + indicator: object, + ): + """Calculate robust ranking changes across multiple evaluation time points. + + Args: + data (pl.DataFrame): The data object containing multi-objective optimization trajectory data. + obj_vars (Iterable[str]): Which columns correspond to the objective values. + evals (Iterable[int]): Evaluation time points at which to calculate ranking changes. + indicator (object): Indicator object from iohinspector.indicators for performance measurement. + + Returns: + dict: A dictionary of comparison objects for each evaluation time point showing ranking changes. + """ + from robustranking import Benchmark + from robustranking.comparison import BootstrapComparison + + df = add_indicator( + data, indicator, obj_vars=obj_vars, evals=evals + ).to_pandas() + df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] + dt_pivoted = pd.pivot( + df_part, + index=["algorithm_name", "run_id"], + columns=["evaluations"], + values=[indicator.var_name], + ).reset_index() + dt_pivoted.columns = ["algorithm_name", "run_id"] + evals + + comparisons = { + f"{eval}": BootstrapComparison( + Benchmark().from_pandas(dt_pivoted, "algorithm_name", "run_id", eval), + alpha=0.05, + minimise=indicator.minimize, + bootstrap_runs=1000, + ) + for eval in evals + } + + return comparisons \ No newline at end of file diff --git a/src/iohinspector/metrics/single_run.py b/src/iohinspector/metrics/single_run.py new file mode 100644 index 0000000..b3eb06b --- /dev/null +++ b/src/iohinspector/metrics/single_run.py @@ -0,0 +1,37 @@ +import numpy as np +import polars as pl +import pandas as pd +from typing import Iterable, Optional + + + +def get_heatmap_single_run_data( + data: pl.DataFrame, + vars: Iterable[str], + eval_var: str = "evaluations", + var_mins: Iterable[float] = [-5], + var_maxs: Iterable[float] = [5], + return_as_pandas: bool = True, +) -> pl.DataFrame | pd.DataFrame: + """Generate normalized heatmap data showing search space points evaluated in a single optimization run. + + Args: + data (pl.DataFrame): The data object containing single-run optimization trajectory data. + vars (Iterable[str]): Which columns correspond to the search space variable values. + eval_var (str, optional): Which column contains the evaluation numbers. Defaults to "evaluations". + var_mins (Iterable[float], optional): Minimum bounds for normalization of variables. Defaults to [-5]. + var_maxs (Iterable[float], optional): Maximum bounds for normalization of variables. Defaults to [5]. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. + + Returns: + pd.DataFrame or pl.DataFrame: A DataFrame with normalized variable values arranged for heatmap visualization. + """ + assert data["data_id"].n_unique() == 1 + dt = data[vars].transpose().to_pandas() + dt.columns = list(data[eval_var]) + var_mins_arr = np.array(var_mins) + var_maxs_arr = np.array(var_maxs) + dt = (dt.subtract(var_mins_arr, axis=0)).divide(var_maxs_arr - var_mins_arr, axis=0) + if return_as_pandas: + return dt + return pl.from_pandas(dt) diff --git a/src/iohinspector/metrics/trajectory.py b/src/iohinspector/metrics/trajectory.py index 25ea53b..c559432 100644 --- a/src/iohinspector/metrics/trajectory.py +++ b/src/iohinspector/metrics/trajectory.py @@ -1,5 +1,6 @@ import numpy as np import polars as pl +import pandas as pd from typing import Iterable from iohinspector.align import align_data @@ -12,22 +13,23 @@ def get_trajectory(data: pl.DataFrame, evaluation_variable: str = "evaluations", fval_variable: str = "raw_y", free_variables: Iterable[str] = ["algorithm_name"], - maximization: bool = False -) -> pl.DataFrame: - """get the trajectory of the performance of the algorithms in the data - This function aligns the data to a fixed number of evaluations and returns the performance trajectory. + maximization: bool = False, + return_as_pandas: bool = True, +) -> pl.DataFrame | pd.DataFrame: + """Generate aligned performance trajectories for algorithm comparison over fixed evaluation sequences. Args: - data (pl.DataFrame): The DataFrame resulting from loading the data from a DataManager. - traj_length (int, optional): Length of the trajecotry. Defaults to None. - min_fevals (int, optional): Evaluation number from which to start the trajectory. Defaults to 1. - evaluation_variable (str, optional): Variable corresponding to evaluation count in `data`. Defaults to "evaluations". - fval_variable (str, optional): Variable corresponding to function value in `data`. Defaults to "raw_y". - free_variables (Iterable[str], optional): Free variables in `data`. Defaults to ["algorithm_name"]. - maximization (bool, optional): Whether the data is maximizing or not. Defaults to False. + data (pl.DataFrame): The data object containing algorithm performance trajectory data. + traj_length (int, optional): Length of the trajectory to generate. If None, uses maximum evaluations from data. Defaults to None. + min_fevals (int, optional): Starting evaluation number for the trajectory. Defaults to 1. + evaluation_variable (str, optional): Which column contains the evaluation numbers. Defaults to "evaluations". + fval_variable (str, optional): Which column contains the function values. Defaults to "raw_y". + free_variables (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["algorithm_name"]. + maximization (bool, optional): Whether the performance metric is being maximized. Defaults to False. + return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. Returns: - pd.DataFrame: DataFrame: A polars DataFrame with the aligned data, where each row corresponds to a specific evaluation count and the performance value. + pl.DataFrame or pd.DataFrame: A DataFrame with aligned trajectory data where each row corresponds to a specific evaluation and performance value. """ if traj_length is None: max_fevals = data[evaluation_variable].max() @@ -42,4 +44,6 @@ def get_trajectory(data: pl.DataFrame, y_col=fval_variable, maximization=maximization, ) + if return_as_pandas: + data_aligned = data_aligned.to_pandas() return data_aligned \ No newline at end of file diff --git a/src/iohinspector/metrics/utils.py b/src/iohinspector/metrics/utils.py index 4703b7c..0c3af85 100644 --- a/src/iohinspector/metrics/utils.py +++ b/src/iohinspector/metrics/utils.py @@ -10,17 +10,17 @@ def get_sequence( scale_log: bool = False, cast_to_int: bool = False, ) -> np.ndarray: - """Create sequence of points, used for subselecting targets / budgets for allignment and data processing + """Create sequence of points, used for subselecting targets / budgets for alignment and data processing. Args: - min (float): Starting point of the range - max (float): Final point of the range - len (float): Number of steps - scale_log (bool): Whether values should be scaled logarithmically. Defaults to False - version (str, optional): Whether the value should be casted to integers (e.g. in case of budget) or not. Defaults to False. + min (float): Starting point of the range. + max (float): Final point of the range. + len (float): Number of steps in the sequence. + scale_log (bool, optional): Whether values should be scaled logarithmically. Defaults to False. + cast_to_int (bool, optional): Whether the values should be casted to integers (e.g. in case of budget) or not. Defaults to False. Returns: - np.ndarray: Array of evenly spaced values + np.ndarray: Array of evenly spaced values between min and max. """ transform = lambda x: x if scale_log: @@ -51,30 +51,30 @@ def get_sequence( def normalize_objectives( data: pl.DataFrame, - obj_cols: Iterable[str] = ["raw_y"], + obj_vars: Iterable[str] = ["raw_y"], bounds: Optional[Dict[str, tuple[Optional[float], Optional[float]]]] = None, log_scale: Union[bool, Dict[str, bool]] = False, maximize: Union[bool, Dict[str, bool]] = False, prefix: str = "ert", keep_original: bool = True ) -> pl.DataFrame: - """ - Normalize multiple objective columns in a dataframe. + """Normalize multiple objective columns in a dataframe using min-max normalization. Args: - data (pl.DataFrame): Input dataframe. - obj_cols (Iterable[str]): Columns to normalize. - bounds (Optional[Dict[str, tuple(lb, ub)]]): Optional manual bounds per column. - log_scale (Union[bool, Dict[str, bool]]): Whether to apply log10 scaling. Can be a single bool or a dict per column. - maximize (Union[bool, Dict[str, bool]]): Whether to treat objective as maximization. Can be a single bool or dict. - prefix (str): Prefix for normalized column names. - keep_original (bool): Whether to keep original objective columns names. + data (pl.DataFrame): Input dataframe containing the objective columns. + obj_vars (Iterable[str], optional): Which columns contain the objective values to normalize. Defaults to ["raw_y"]. + bounds (Optional[Dict[str, tuple[Optional[float], Optional[float]]]], optional): Optional manual bounds per column as (lower_bound, upper_bound). Defaults to None. + log_scale (Union[bool, Dict[str, bool]], optional): Whether to apply log10 scaling. Can be a single bool or a dict per column. Defaults to False. + maximize (Union[bool, Dict[str, bool]], optional): Whether to treat objective as maximization. Can be a single bool or dict per column. Defaults to False. + prefix (str, optional): Prefix for normalized column names. Defaults to "ert". + keep_original (bool, optional): Whether to keep original objective column names. Defaults to True. + Returns: pl.DataFrame: The original dataframe with new normalized objective columns added. """ result = data.clone() - n_objectives = len(obj_cols) - for col in obj_cols: + n_objectives = len(obj_vars) + for col in obj_vars: # Determine log scaling use_log = log_scale[col] if isinstance(log_scale, dict) else log_scale is_max = maximize[col] if isinstance(maximize, dict) else maximize @@ -107,7 +107,7 @@ def normalize_objectives( if keep_original: norm_expr = norm_expr.alias(f"{prefix}_{col}") else: - idx = list(obj_cols).index(col) + 1 + idx = list(obj_vars).index(col) + 1 norm_expr = norm_expr.alias(f"{prefix}{idx}") else: # If only one objective, use the prefix directly @@ -119,29 +119,29 @@ def normalize_objectives( def add_normalized_objectives( data: pl.DataFrame, - obj_cols: Iterable[str], - max_vals: Optional[pl.DataFrame] = None, - min_vals: Optional[pl.DataFrame] = None -): - """Add new normalized columns to provided dataframe based on the provided objective columns + obj_vars: Iterable[str], + max_obj: Optional[pl.DataFrame] = None, + min_obj: Optional[pl.DataFrame] = None +) -> pl.DataFrame: + """Add new normalized columns to provided dataframe based on the provided objective columns. Args: - data (pl.DataFrame): The original dataframe - obj_cols (Iterable[str]): The names of each objective column - max_vals (Optional[pl.DataFrame]): If provided, these values will be used as the maxima instead of the values found in `data` - min_vals (Optional[pl.DataFrame]): If provided, these values will be used as the minima instead of the values found in `data` + data (pl.DataFrame): The original dataframe containing objective columns. + obj_vars (Iterable[str]): Which columns contain the objective values to normalize. + max_obj (Optional[pl.DataFrame], optional): If provided, these values will be used as the maxima instead of the values found in `data`. Defaults to None. + min_obj (Optional[pl.DataFrame], optional): If provided, these values will be used as the minima instead of the values found in `data`. Defaults to None. Returns: - _type_: The original `data` DataFrame with a new column 'objI' added for each objective, for I=1...len(obj_cols) + pl.DataFrame: The original `data` DataFrame with a new column 'objI' added for each objective, for I=1...len(obj_vars). """ return normalize_objectives( data, - obj_cols=obj_cols, + obj_vars=obj_vars, bounds={ - col: (min_vals[col][0] if min_vals is not None else None, - max_vals[col][0] if max_vals is not None else None) - for col in obj_cols + col: (min_obj[col][0] if min_obj is not None else None, + max_obj[col][0] if max_obj is not None else None) + for col in obj_vars }, maximize=True, prefix="obj", @@ -155,15 +155,25 @@ def transform_fval( ub: float = 1e8, scale_log: bool = True, maximization: bool = False, - fval_col: str = "raw_y", -): - """ - Helper function to transform function values (min-max normalization based on provided bounds and scaling) + fval_var: str = "raw_y", +) -> pl.DataFrame: + """Helper function to transform function values using min-max normalization based on provided bounds and scaling. + + Args: + data (pl.DataFrame): Input dataframe containing function values. + lb (float, optional): Lower bound for normalization. Defaults to 1e-8. + ub (float, optional): Upper bound for normalization. Defaults to 1e8. + scale_log (bool, optional): Whether to apply logarithmic scaling. Defaults to True. + maximization (bool, optional): Whether the problem is a maximization problem. Defaults to False. + fval_var (str, optional): Which column contains the function values to transform. Defaults to "raw_y". + + Returns: + pl.DataFrame: The original dataframe with normalized function values in a new 'eaf' column. """ - bounds = {fval_col: (lb, ub)} + bounds = {fval_var: (lb, ub)} res = normalize_objectives( data, - obj_cols=[fval_col], + obj_vars=[fval_var], bounds=bounds, log_scale=scale_log, maximize=maximization, diff --git a/src/iohinspector/plots/__init__.py b/src/iohinspector/plots/__init__.py index 08171c5..dfc4a5f 100644 --- a/src/iohinspector/plots/__init__.py +++ b/src/iohinspector/plots/__init__.py @@ -13,4 +13,5 @@ from .multi_objective import plot_paretofronts_2d, plot_indicator_over_time from .ranking import plot_tournament_ranking, plot_robustrank_over_time, plot_robustrank_changes from .attractor_network import plot_attractor_network -from .single_run import plot_heatmap_single_run \ No newline at end of file +from .single_run import plot_heatmap_single_run +from .utils import BasePlotArgs, LinePlotArgs \ No newline at end of file diff --git a/src/iohinspector/plots/attractor_network.py b/src/iohinspector/plots/attractor_network.py index 16bf4f7..f2038a7 100644 --- a/src/iohinspector/plots/attractor_network.py +++ b/src/iohinspector/plots/attractor_network.py @@ -1,3 +1,4 @@ +from dataclasses import dataclass import numpy as np import pandas as pd import polars as pl @@ -5,32 +6,86 @@ import matplotlib import matplotlib.pyplot as plt from iohinspector.metrics import get_attractor_network +from iohinspector.plots.utils import BasePlotArgs, _create_plot_args, _save_fig + +@dataclass +class AttractorNetworkPlotArgs(BasePlotArgs): + color_map: str = "viridis" + + def as_dict(self): + """Convert the attractor network plot arguments to a dictionary representation. + + Returns: + Dict[str, Any]: Dictionary containing all attractor network plot configuration parameters including color map. + """ + results = super().as_dict() + results["color_map"] = self.color_map + return results + + def apply(self, ax): + """Apply attractor network plot properties to a matplotlib Axes object. + + Args: + ax: matplotlib Axes instance to apply the attractor network plot properties to. + + Returns: + ax: The modified matplotlib Axes object with attractor network plot properties applied. + """ + return super().apply(ax) + + def override(self, other): + """Update attractor network plot arguments in place with values from another source. + + Args: + other: Attractor network plot arguments to override current values with. + """ + return super().override(other) def plot_attractor_network( - data, - coord_vars: Iterable[str] = ["x1", "x2"], + data: pl.DataFrame, + coord_vars: Iterable[str] = ["x0", "x1"], fval_var: str = "raw_y", eval_var: str = "evaluations", maximization: bool = False, - beta=40, - epsilon=0.0001, - file_name: str = None, + beta: int = 40, + epsilon: float = 0.0001, + *, ax: matplotlib.axes.Axes = None, + file_name: str = None, + plot_args: dict | AttractorNetworkPlotArgs = None, + ): - """Plot an attractor network from the provided data + """Plot an attractor network visualization from optimization algorithm data. + + Creates a network graph where nodes represent attractors (stable points) in the search space + and edges represent transitions between them. Node sizes reflect visit frequency and colors + represent fitness values. Args: - data (pl.DataFrame): The original dataframe, should contain the performance and position information - coord_vars (Iterable[str], optional): Which columns correspond to position information. Defaults to ['x1', 'x2']. - fval_var (str, optional): Which column corresponds to performance. Defaults to 'raw_y'. - eval_var (str, optional): Which column corresponds to evaluations. Defaults to 'evaluations'. - maximization (bool, optional): Whether fval_var is to be maximized. Defaults to False. - beta (int, optional): Minimum stagnation lenght. Defaults to 40. - epsilon (float, optional): Radius below which positions should be considered identical in the network. Defaults to 0.0001. + data (pl.DataFrame): Input dataframe containing optimization algorithm trajectory data. + coord_vars (Iterable[str], optional): Which columns contain the decision variable coordinates. + Defaults to ["x0", "x1"]. + fval_var (str, optional): Which column contains the fitness/objective values. Defaults to "raw_y". + eval_var (str, optional): Which column contains the evaluation counts. Defaults to "evaluations". + maximization (bool, optional): Whether the optimization problem is maximization. Defaults to False. + beta (int, optional): Minimum stagnation length for attractor detection. Defaults to 40. + epsilon (float, optional): Distance threshold below which positions are considered identical. + Defaults to 0.0001. + ax (matplotlib.axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. + Defaults to None. + file_name (str, optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | AttractorNetworkPlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "Attractor Network". + - xlabel (str): X-axis label. Defaults to "MDS-reduced decision vector". + - ylabel (str): Y-axis label. Defaults to "fitness". + - color_map (str): Colormap for node colors based on fitness. Defaults to "viridis". + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other BasePlotArgs parameters (xlim, ylim, xscale, yscale, grid, legend, etc.). Returns: - pd.DataFrame, pd.DataFrame: two dataframes containing the nodes and edges of the network respectively. + tuple[matplotlib.axes.Axes, pd.DataFrame, pd.DataFrame]: The matplotlib axes object + and two dataframes with the nodes and edges of the attractor network. """ try: import networkx as nx @@ -48,6 +103,18 @@ def plot_attractor_network( beta = beta, epsilon = epsilon ) + + plot_args = _create_plot_args( + AttractorNetworkPlotArgs( + title="Attractor Network", + xlabel="MDS-reduced decision vector", + ylabel="fitness", + color_map="viridis" + ), + plot_args + ) + + network = nx.DiGraph() for idx, row in nodes.iterrows(): network.add_node( @@ -81,7 +148,7 @@ def plot_attractor_network( if len(hitcounts) > 1: min_hitcount = min(hitcounts) max_hitcount = max(hitcounts) - # Node sizes and colors based on fitness values (as in your original code) + if len(hitcounts) > 1 and np.std(hitcounts) > 0: node_sizes = [ 100 @@ -95,28 +162,43 @@ def plot_attractor_network( else: node_sizes = [500] * len(hitcounts) fitness_values = y_positions # Reuse y_positions as they represent 'fitness' - norm = plt.Normalize(min(fitness_values), max(fitness_values)) - node_colors = plt.cm.viridis(norm(fitness_values)) + + if(plot_args.yscale == "log"): + norm = matplotlib.colors.LogNorm(min(fitness_values), max(fitness_values)) + else: + norm = plt.Normalize(min(fitness_values), max(fitness_values)) + + # Safely get colormap name or default to 'viridis' if not present on plot_args + cmap_name = getattr(plot_args, "color_map", "viridis") + cmap = plt.get_cmap(cmap_name) + node_colors = cmap(norm(fitness_values)) - # Draw the graph if ax is None: - fig, ax = plt.subplots(figsize=(10, 6)) + fig, ax = plt.subplots(figsize=plot_args.figsize) + else: + fig = None + nx.draw( network, pos=pos, - with_labels=False, + with_labels=True, node_size=node_sizes, node_color=node_colors[:, :3], edge_color="gray", width=2, ax=ax, ) + # ensure the axis frame, ticks and grid are visible + ax.set_axis_on() + ax.set_aspect("auto") # Add colorbar for fitness values - sm = plt.cm.ScalarMappable(cmap="viridis", norm=norm) + sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm) sm.set_array(fitness_values) - ax.set_xlabel("MDS-reduced decision vector") - ax.set_ylabel("fitness") - if file_name: - fig.tight_layout() - fig.savefig(file_name) \ No newline at end of file + plt.colorbar(sm, ax=ax) + + plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args) + + return ax, nodes, edges \ No newline at end of file diff --git a/src/iohinspector/plots/eaf.py b/src/iohinspector/plots/eaf.py index e74f30c..dad9b82 100644 --- a/src/iohinspector/plots/eaf.py +++ b/src/iohinspector/plots/eaf.py @@ -1,3 +1,5 @@ + + import numpy as np import polars as pl import pandas as pd @@ -6,200 +8,330 @@ from matplotlib.patches import Polygon, Rectangle import seaborn as sbs from typing import Optional, Iterable -from iohinspector.metrics import get_sequence -from iohinspector.align import align_data +from iohinspector.metrics import get_eaf_data, get_eaf_pareto_data, get_eaf_diff_data +from iohinspector.plots.utils import HeatmapPlotArgs, _create_plot_args, _save_fig from moocore import eaf, eafdiff def plot_eaf_single_objective( data: pl.DataFrame, - min_budget: int = None, - max_budget: int = None, - scale_xlog: bool = True, - n_quantiles: int = 100, eval_var: str = "evaluations", fval_var: str = "raw_y", + eval_min: int = None, + eval_max: int = None, + scale_eval_log: bool = True, + n_quantiles: int = 100, + *, ax: matplotlib.axes._axes.Axes = None, file_name: Optional[str] = None, + plot_args: dict | HeatmapPlotArgs = None ): - """Plot the EAF for a single objective column agains budget. For the EAF-plot for multiple objective - columns, see 'plot_eaf_pareto'. + """Plot the Empirical Attainment Function (EAF) for single-objective optimization against budget. + + Creates a heatmap visualization showing the probability of attaining different function values + at different evaluation budgets across multiple algorithm runs. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - n_quantiles (int, optional): Number of discrete levels in the EAF. Defaults to 100. - eval_var (str, optional): The variable corresponding to evaluations. Defaults to 'evaluations' - fval_var (str, optional): The variable corresponding to function values. Defaults to "raw_y". - scale_xlog (bool, optional): Whether the evaluations should be log-scaled. Defaults to True. - min_budget (Iterable[float], optional): Minimum bound for the variables. Should be of the same length as 'var_cols'. Defaults to [-5]. - max_budget (Iterable[float], optional): Maximum bound for the variables. Should be of the same length as 'var_cols'.. Defaults to [5]. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + data (pl.DataFrame): Input dataframe containing optimization algorithm trajectory data. + eval_var (str, optional): Which column contains the evaluation counts. Defaults to "evaluations". + fval_var (str, optional): Which column contains the function values. Defaults to "raw_y". + eval_min (int, optional): Minimum evaluation bound for the plot. If None, uses data minimum. Defaults to None. + eval_max (int, optional): Maximum evaluation bound for the plot. If None, uses data maximum. Defaults to None. + scale_eval_log (bool, optional): Whether the evaluations should be log-scaled. Defaults to True. + n_quantiles (int, optional): Number of discrete probability levels in the EAF heatmap. Defaults to 100. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | HeatmapPlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "EAF". + - xlabel (str): X-axis label. Defaults to eval_var value. + - ylabel (str): Y-axis label. Defaults to fval_var value. + - xscale (str): X-axis scale ("log" or "linear"). Defaults to "log" if scale_eval_log=True. + - yscale (str): Y-axis scale. Defaults to "log". + - xlim (Tuple[float, float]): X-axis limits. Defaults to (eval_min, eval_max). + - ylim (Tuple[float, float]): Y-axis limits. Defaults to (1e-8, 1e2). + - heatmap_palette (str): Colormap name. Defaults to "viridis_r". + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other HeatmapPlotArgs parameters. Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot + tuple[matplotlib.axes.Axes, pl.DataFrame]: The matplotlib axes object and the processed + dataframe used to create the plot. """ - if min_budget is None: - min_budget = data[eval_var].min() - if max_budget is None: - max_budget = data[eval_var].max() - evals = get_sequence(min_budget, max_budget, 50, scale_xlog, True) - long = align_data(data, np.array(evals, "uint64"), ["data_id"], output="long") - quantiles = np.arange(0, 1 + 1 / ((n_quantiles - 1) * 2), 1 / (n_quantiles - 1)) + df = get_eaf_data( + data, + eval_var=eval_var, + eval_min=eval_min, + eval_max=eval_max, + scale_eval_log=scale_eval_log, + return_as_pandas=False, + ) + eval_min = df[eval_var].min() + eval_max = df[eval_var].max() + + plot_args = _create_plot_args( + HeatmapPlotArgs( + xlabel= eval_var, + ylabel= fval_var, + title= "EAF", + xscale= "log" if scale_eval_log else "linear", + yscale= "log", + xlim= (eval_min, eval_max), + ylim= (10**-8,10**2), + heatmap_palette= "viridis_r", + ), + plot_args + ) + f_min, f_max = plot_args.ylim + if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) + fig, ax = plt.subplots(figsize=plot_args.figsize) + else: + fig = None + + quantiles = np.arange(0, 1 + 1 / ((n_quantiles - 1) * 2), 1 / (n_quantiles - 1)) + cmap = plt.get_cmap(plot_args.heatmap_palette) + norm = plt.Normalize( + vmin=0, + vmax=1 + ) + colors = [cmap(norm(quant)) for quant in quantiles] + if(not plot_args.use_background_color): + ax.add_patch( + Rectangle( + (eval_min, f_min), + eval_max - eval_min, + f_max - f_min, + facecolor=cmap(norm(0)), + zorder=0, + ) + ) - colors = sbs.color_palette("viridis", n_colors=len(quantiles)) - for quant, color in zip(quantiles, colors[::-1]): + for quant, color in zip(quantiles,colors): poly = np.array( - long.group_by(eval_var).quantile(quant).sort(eval_var)[eval_var, fval_var] + df.group_by(eval_var).quantile(quant).sort(eval_var)[eval_var, fval_var] ) poly = np.append( - poly, np.array([[max(poly[:, 0]), long[fval_var].max()]]), axis=0 + poly, np.array([[max(poly[:, 0]), f_max]]), axis=0 ) poly = np.append( - poly, np.array([[min(poly[:, 0]), long[fval_var].max()]]), axis=0 + poly, np.array([[min(poly[:, 0]), f_max]]), axis=0 ) poly2 = np.repeat(poly, 2, axis=0) poly2[2::2, 1] = poly[:, 1][:-1] ax.add_patch(Polygon(poly2, facecolor=color)) - ax.set_ylim(long[fval_var].min(), long[fval_var].max()) - ax.set_ylim(1e-8, 1) - ax.set_xlim(min(evals), max(evals)) - ax.set_axisbelow(True) - ax.grid(which="both", zorder=100) - ax.set_yscale("log") - if scale_xlog: - ax.set_xscale("log") - - if file_name: - fig.tight_layout() - fig.savefig(file_name) - return long + sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm) + sm.set_array([]) + plt.colorbar(sm, ax=ax) + + plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args) + + return ax, df def plot_eaf_pareto( data: pl.DataFrame, - x_column: str, - y_column: str, - min_y: float = 0, - max_y: float = 1, - scale_xlog: bool = False, - scale_ylog: bool = False, + obj1_var: str, + obj2_var: str, + *, ax: matplotlib.axes._axes.Axes = None, file_name: Optional[str] = None, + plot_args: dict | HeatmapPlotArgs = None ): - """Plot the EAF for two arbitrary data columns. For the EAF-plot for single-objective - optimization runs, the 'plot_eaf_single_objective' provides a simpler interface. + """Plot the Empirical Attainment Function (EAF) for multi-objective optimization with two objectives. + + Creates a heatmap visualization showing the probability of attaining different combinations + of objective values across multiple algorithm runs in the Pareto front space. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - x_column (str, optional): The variable corresponding to the first objective. - y_column (str, optional): The variable corresponding to the second objective. - min_y (float): Minimum value for the second objective. - max_y (float): Maximum value for the second objective. - scale_xlog (bool, optional): Whether the first objective should be log-scaled. Defaults to False. - scale_ylog (bool, optional): Whether the second objective should be log-scaled. Defaults to False. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + data (pl.DataFrame): Input dataframe containing multi-objective optimization trajectory data. + obj1_var (str): Which column contains the first objective values. + obj2_var (str): Which column contains the second objective values. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | HeatmapPlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "Pareto EAF". + - xlabel (str): X-axis label. Defaults to obj1_var value. + - ylabel (str): Y-axis label. Defaults to obj2_var value. + - xlim (Tuple[float, float]): X-axis limits. Defaults to data range. + - ylim (Tuple[float, float]): Y-axis limits. Defaults to data range. + - heatmap_palette (str): Colormap name. Defaults to "viridis_r". + - use_background_color (bool): Whether to use background color. Defaults to True. + - background_color (str): Background color. Defaults to "white". + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other HeatmapPlotArgs parameters. + + Returns: + tuple[matplotlib.axes.Axes, pd.DataFrame]: The matplotlib axes object and the EAF + dataframe used to create the plot. """ - data_to_process = np.array(data[[x_column, y_column, "data_id"]]) - eaf_data = eaf(data_to_process[:,:-1], data_to_process[:,-1] ) - eaf_data_df = pd.DataFrame(eaf_data) + + eaf_data_df = get_eaf_pareto_data(data, obj1_var, obj2_var) + + x_max = eaf_data_df[obj1_var].max() + x_min = eaf_data_df[obj1_var].min() + y_max = eaf_data_df[obj2_var].max() + y_min = eaf_data_df[obj2_var].min() + + min_eaf = eaf_data_df["eaf"].min() + + plot_args = _create_plot_args( + HeatmapPlotArgs( + xlabel= obj1_var, + ylabel= obj2_var, + title= "Pareto EAF", + xlim= (x_min, x_max), + ylim= (y_min, y_max), + heatmap_palette= "viridis_r", + ), + plot_args + ) + + x_min, x_max = plot_args.xlim + y_min, y_max = plot_args.ylim + if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - colors = sbs.color_palette("viridis", n_colors=eaf_data_df[2].nunique()) - eaf_data_df = eaf_data_df.sort_values(0) - min_x = np.min(eaf_data_df[0]) - max_x = np.max(eaf_data_df[0]) - if min_y is None: - min_y = np.min(eaf_data_df[1]) - if max_y is None: - max_y = np.max(eaf_data_df[1]) - for i, color in zip(eaf_data_df[2].unique(), colors[::-1]): - poly = np.array(eaf_data_df[eaf_data_df[2] == i][[0, 1]]) - # poly = np.append(poly, np.array([[max(poly[:, 0]), max(poly[:, 1])]]), axis=0) - # poly = np.append(poly, np.array([[min(poly[:, 0]), max(poly[:, 1])]]), axis=0) - poly = np.append(poly, np.array([[max_x, max_y]]), axis=0) - poly = np.append(poly, np.array([[min(poly[:, 0]), max_y]]), axis=0) + fig, ax = plt.subplots(figsize=plot_args.figsize) + else: + fig = None + + eaf_data_df = eaf_data_df.sort_values(obj1_var) + + cmap = plt.get_cmap(plot_args.heatmap_palette) + norm = plt.Normalize( + vmin=(min_eaf if plot_args.use_background_color else 0), + vmax=1 + ) + _unique_eafs = eaf_data_df["eaf"].unique() + colors = [cmap(norm(v)) for v in _unique_eafs] + + + ax.add_patch( + Rectangle( + (x_min, y_min), + x_max - x_min, + y_max - y_min, + facecolor= (plot_args.background_color if plot_args.use_background_color else cmap(norm(0))), + zorder=0, + ) + ) + + for i, color in zip(eaf_data_df["eaf"].unique(), colors): + poly = np.array(eaf_data_df[eaf_data_df["eaf"] == i][[obj1_var, obj2_var]]) + poly = np.append(poly, np.array([[x_max, y_max]]), axis=0) + poly = np.append(poly, np.array([[min(poly[:, 0]), y_max]]), axis=0) poly2 = np.repeat(poly, 2, axis=0) poly2[2::2, 1] = poly[:, 1][:-1] ax.add_patch(Polygon(poly2, facecolor=color)) - # ax.add_colorbar() - ax.set_ylim(min_y, max_y) - ax.set_xlim(min_x, max_x) - ax.set_axisbelow(True) - sm = plt.cm.ScalarMappable(cmap="viridis", norm=plt.Normalize(vmin=0, vmax=1)) + + sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm) sm.set_array([]) plt.colorbar(sm, ax=ax) - if scale_ylog: - ax.set_yscale("log") - if scale_xlog: - ax.set_xscale("log") - ax.grid(which="both", zorder=100) - if file_name: - fig.tight_layout() - fig.savefig(file_name) + # set a background rectangle behind the EAF polygons + + ax.set_facecolor("white") + ax = plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args) + + return ax, eaf_data_df def plot_eaf_diffs( data1: pl.DataFrame, data2: pl.DataFrame, - x_column: str, - y_column: str, - min_y: float = 0, - max_y: float = 1, - scale_xlog: bool = False, - scale_ylog: bool = False, + obj1_var: str, + obj2_var: str, + *, ax: matplotlib.axes._axes.Axes = None, file_name: Optional[str] = None, + plot_args: dict | HeatmapPlotArgs = None ): - """Plot the EAF differences between two datasets. + """Plot the Empirical Attainment Function (EAF) differences between two algorithms. + + Creates a heatmap visualization showing the statistical differences in attainment probabilities + between two algorithms in the objective space, highlighting regions where one algorithm + performs better than the other. Args: - data1 (pl.DataFrame): The DataFrame which contains the full performance trajectory for algorithm 1. Should be generated from a DataManager. - data2 (pl.DataFrame): The DataFrame which contains the full performance trajectory for algorithm 2. Should be generated from a DataManager. - x_column (str, optional): The variable corresponding to the first objective. - y_column (str, optional): The variable corresponding to the second objective. - min_y (float): Minimum value for the second objective. - max_y (float): Maximum value for the second objective. - scale_xlog (bool, optional): Whether the first objective should be log-scaled. Defaults to False. - scale_ylog (bool, optional): Whether the second objective should be log-scaled. Defaults to False. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + data1 (pl.DataFrame): Input dataframe containing trajectory data for the first algorithm. + data2 (pl.DataFrame): Input dataframe containing trajectory data for the second algorithm. + obj1_var (str): Which column contains the first objective values. + obj2_var (str): Which column contains the second objective values. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | HeatmapPlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "EAF Differences". + - xlabel (str): X-axis label. Defaults to obj1_var value. + - ylabel (str): Y-axis label. Defaults to obj2_var value. + - xlim (Tuple[float, float]): X-axis limits. Defaults to data range. + - ylim (Tuple[float, float]): Y-axis limits. Defaults to data range. + - heatmap_palette (str): Colormap name. Defaults to "viridis". + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other HeatmapPlotArgs parameters. + + Returns: + tuple[matplotlib.axes.Axes, pd.DataFrame]: The matplotlib axes object and the EAF + differences dataframe used to create the plot. + + Note: + The plot shows regions where data1 performs better (positive differences) and regions + where data2 performs better (negative differences) in different colors. """ # TODO: add an approximation version to speed up plotting - x = np.array(data1[[x_column, y_column, "data_id"]]) - y = np.array(data2[[x_column, y_column, "data_id"]]) - eaf_diff_rect = eafdiff(x, y, rectangles=True) + eaf_diff_rect_data = get_eaf_diff_data( + data1, + data2, + obj1_var, + obj2_var, + ) + x_min = eaf_diff_rect_data["x_min"].replace([np.inf, -np.inf], np.nan).min() + x_max = eaf_diff_rect_data["x_max"].replace([np.inf, -np.inf], np.nan).max() + y_min = eaf_diff_rect_data["y_min"].replace([np.inf, -np.inf], np.nan).min() + y_max = eaf_diff_rect_data["y_max"].replace([np.inf, -np.inf], np.nan).max() + + plot_args = _create_plot_args( + HeatmapPlotArgs( + xlabel= obj1_var, + ylabel= obj2_var, + title= "EAF Differences", + xlim= (x_min, x_max), + ylim= (y_min, y_max), + ), + plot_args + ) + eaf_min_diff = eaf_diff_rect_data["eaf_diff"].min() + eaf_max_diff = eaf_diff_rect_data["eaf_diff"].max() + color_dict = { k: v for k, v in zip( - np.unique(eaf_diff_rect[:, -1]), - sbs.color_palette("viridis", n_colors=len(np.unique(eaf_diff_rect[:, -1]))), + np.unique(eaf_diff_rect_data["eaf_diff"]), + sbs.color_palette(plot_args.heatmap_palette, n_colors=len(np.unique(eaf_diff_rect_data["eaf_diff"]))), ) } + if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - for rect in eaf_diff_rect: + fig, ax = plt.subplots(figsize=plot_args.figsize) + else: + fig = None + + for rect in eaf_diff_rect_data.itertuples(index=False): ax.add_patch( Rectangle( - (rect[0], rect[1]), - rect[2] - rect[0], - rect[3] - rect[1], - facecolor=color_dict[rect[-1]], + (rect.x_min, rect.y_min), + rect.x_max - rect.x_min, + rect.y_max - rect.y_min, + facecolor=color_dict[rect.eaf_diff], ) ) - if min_y is None: - min_y = np.min(x[1]) - if max_y is None: - max_y = np.max(x[1]) - ax.set_ylim(min_y, max_y) - ax.set_xlim((0,1000)) - if scale_ylog: - ax.set_yscale("log") - if scale_xlog: - ax.set_xscale("log") - if file_name: - fig.tight_layout() - fig.savefig(file_name) + sm = plt.cm.ScalarMappable(cmap=plot_args.heatmap_palette, norm=plt.Normalize(vmin=eaf_min_diff, vmax=eaf_max_diff)) + sm.set_array([]) + plt.colorbar(sm, ax=ax) + ax = plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args) + + + return ax, eaf_diff_rect_data \ No newline at end of file diff --git a/src/iohinspector/plots/ecdf.py b/src/iohinspector/plots/ecdf.py index e7a94c3..73c7459 100644 --- a/src/iohinspector/plots/ecdf.py +++ b/src/iohinspector/plots/ecdf.py @@ -4,7 +4,7 @@ import polars as pl from typing import Iterable, Optional from iohinspector.metrics import get_data_ecdf - +from iohinspector.plots.utils import LinePlotArgs, _create_plot_args, _save_fig def plot_ecdf( data: pl.DataFrame, @@ -12,56 +12,88 @@ def plot_ecdf( eval_var: str = "evaluations", free_vars: Iterable[str] = ["algorithm_name"], maximization: bool = False, - x_values: Iterable[int] = None, - x_min: int = None, - x_max: int = None, - scale_xlog: bool = True, - y_min: int = None, - y_max: int = None, - scale_ylog: bool = True, + f_min: int = None, + f_max: int = None, + scale_f_log: bool = True, + eval_values: Iterable[int] = None, + eval_min: int = None, + eval_max: int = None, + scale_eval_log: bool = True, + *, ax: matplotlib.axes._axes.Axes = None, file_name: Optional[str] = None, + plot_args: dict | LinePlotArgs = None, ): - """Function to plot empirical cumulative distribution function (Based on EAF) + """Plot Empirical Cumulative Distribution Function (ECDF) based on Empirical Attainment Functions. + + Creates line plots showing the cumulative probability of achieving different performance levels + at various evaluation budgets, allowing comparison between algorithms or configurations. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - eval_var (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_var (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_vars (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. - x_min (float, optional): Minimum value to use for the 'eval_var', if not present the min of that column will be used. Defaults to None. - x_max (float, optional): Maximum value to use for the 'eval_var', if not present the max of that column will be used. Defaults to None. - x_values (Iterable[int], optional): List of x-values at which to plot the ECDF. If not provided, the x_min, x_max and scale_xlog arguments will be used to sample these points. - scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. - y_min (float, optional): Minimum value to use for the 'fval_var', if not present the min of that column will be used. Defaults to None. - y_max (float, optional): Maximum value to use for the 'fval_var', if not present the max of that column will be used. Defaults to None. - scale_ylog (bool, optional): Should the y-values be log-scaled before normalization. Defaults to True. - maximization (bool, optional): Boolean indicating whether the 'fval_var' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + data (pl.DataFrame): Input dataframe containing optimization algorithm trajectory data. + fval_var (str, optional): Which column contains the function/performance values. Defaults to "raw_y". + eval_var (str, optional): Which column contains the evaluation counts. Defaults to "evaluations". + free_vars (Iterable[str], optional): Which columns contain the grouping variables for distinguishing + between different lines in the plot. Defaults to ["algorithm_name"]. + maximization (bool, optional): Whether the optimization problem is maximization. Defaults to False. + f_min (int, optional): Minimum function value bound. If None, uses data minimum. Defaults to None. + f_max (int, optional): Maximum function value bound. If None, uses data maximum. Defaults to None. + scale_f_log (bool, optional): Whether function values should be log-scaled before normalization. Defaults to True. + eval_values (Iterable[int], optional): Specific evaluation points to plot. If None, uses eval_min/eval_max + with scale_eval_log to sample points. Defaults to None. + eval_min (int, optional): Minimum evaluation bound. If None, uses data minimum. Defaults to None. + eval_max (int, optional): Maximum evaluation bound. If None, uses data maximum. Defaults to None. + scale_eval_log (bool, optional): Whether the evaluation axis should be log-scaled. Defaults to True. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | LinePlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "ECDF". + - xlabel (str): X-axis label. Defaults to eval_var value. + - ylabel (str): Y-axis label. Defaults to "eaf". + - xscale (str): X-axis scale ("log" or "linear"). Defaults to "log" if scale_eval_log=True. + - yscale (str): Y-axis scale ("log" or "linear"). Defaults to "log" if scale_f_log=True. + - line_colors (Sequence[str]): Colors for different lines. Defaults to seaborn palette. + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other LinePlotArgs parameters (xlim, ylim, grid, legend, fontsize, etc.). Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot + tuple[matplotlib.axes.Axes, pd.DataFrame]: The matplotlib axes object and the processed + dataframe used to create the plot. """ + + dt_plot = get_data_ecdf( data, fval_var=fval_var, eval_var=eval_var, free_vars=free_vars, maximization=maximization, - x_values=x_values, - x_min=x_min, - x_max=x_max, - scale_xlog=scale_xlog, - y_min=y_min, - y_max=y_max, - scale_ylog=scale_ylog, + f_min=f_min, + f_max=f_max, + scale_f_log=scale_f_log, + eval_values=eval_values, + eval_max=eval_max, + eval_min=eval_min, + scale_eval_log=scale_eval_log, turbo=True ) + plot_args = _create_plot_args( + LinePlotArgs( + xlabel= eval_var, + ylabel= "eaf", + title= "ECDF", + xscale= "log" if scale_eval_log else "linear", + yscale= "log" if scale_f_log else "linear", + ), + plot_args + ) + + + dt_plot.sort_values(free_vars) if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) + fig, ax = plt.subplots(figsize=plot_args.figsize) + if len(free_vars) == 1: hue_arg = free_vars[0] style_arg = free_vars[0] @@ -69,18 +101,19 @@ def plot_ecdf( style_arg = free_vars[0] hue_arg = dt_plot[free_vars[1:]].apply(tuple, axis=1) + sbs.lineplot( dt_plot, - x="evaluations", + x= eval_var, y="eaf", style=style_arg, hue=hue_arg, + palette=plot_args.line_colors, ax=ax, ) - if scale_xlog: - ax.set_xscale("log") - ax.grid() - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) - return dt_plot \ No newline at end of file + + plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args=plot_args) + + return ax, dt_plot \ No newline at end of file diff --git a/src/iohinspector/plots/fixed_budget.py b/src/iohinspector/plots/fixed_budget.py index 018a4a3..537ce9e 100644 --- a/src/iohinspector/plots/fixed_budget.py +++ b/src/iohinspector/plots/fixed_budget.py @@ -4,76 +4,101 @@ import polars as pl from typing import Iterable from iohinspector.metrics.fixed_budget import aggregate_convergence +from iohinspector.plots.utils import LinePlotArgs, _save_fig, _create_plot_args +import matplotlib def plot_single_function_fixed_budget( data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], - x_min: float = None, - x_max: float = None, + eval_var: str = "evaluations", + fval_var: str = "raw_y", + free_vars: Iterable[str] = ["algorithm_name"], + eval_min: float = None, + eval_max: float = None, maximization: bool = False, measures: Iterable[str] = ["geometric_mean"], - scale_xlog: bool = True, - scale_ylog: bool = True, + *, ax: matplotlib.axes._axes.Axes = None, file_name: str = None, + plot_args: dict | LinePlotArgs = None, ): - """Create a fixed-budget plot for a given set of performance data. + """Create a fixed-budget convergence plot showing algorithm performance over evaluation budgets. + + Visualizes how different algorithms converge by plotting aggregate performance measures + (geometric mean, median, etc.) against evaluation budgets, allowing direct comparison + of convergence behavior across algorithms. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. - x_min (float, optional): Minimum value to use for the 'evaluation_variable', if not present the min of that column will be used. Defaults to None. - x_max (float, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. - maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'geometric_mean', 'mean', 'median', 'min', 'max'. Defaults to ['geometric_mean']. - scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. - scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + data (pl.DataFrame): Input dataframe containing optimization algorithm trajectory data. + eval_var (str, optional): Which column contains the evaluation counts. Defaults to "evaluations". + fval_var (str, optional): Which column contains the function/objective values. Defaults to "raw_y". + free_vars (Iterable[str], optional): Which columns contain the grouping variables for distinguishing + between different lines in the plot. Defaults to ["algorithm_name"]. + eval_min (float, optional): Minimum evaluation bound for the plot. If None, uses data minimum. Defaults to None. + eval_max (float, optional): Maximum evaluation bound for the plot. If None, uses data maximum. Defaults to None. + maximization (bool, optional): Whether the optimization problem is maximization. Defaults to False. + measures (Iterable[str], optional): Aggregate measures to plot. Valid options are "geometric_mean", + "mean", "median", "min", "max". Defaults to ["geometric_mean"]. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (str, optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | LinePlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "Fixed-Budget Plot". + - xlabel (str): X-axis label. Defaults to eval_var value. + - ylabel (str): Y-axis label. Defaults to fval_var value. + - xscale (str): X-axis scale. Defaults to "log". + - yscale (str): Y-axis scale. Defaults to "log". + - line_colors (Sequence[str]): Colors for different lines. Defaults to seaborn palette. + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other LinePlotArgs parameters (xlim, ylim, grid, legend, fontsize, etc.). Returns: - pd.DataFrame: The final dataframe which was used to create the plot + tuple[matplotlib.axes.Axes, pl.DataFrame]: The matplotlib axes object and the processed + (melted/filtered) dataframe used to create the plot. """ dt_agg = aggregate_convergence( data, - evaluation_variable=evaluation_variable, - fval_variable=fval_variable, - free_variables=free_variables, - x_min=x_min, - x_max=x_max, + eval_var=eval_var, + fval_var=fval_var, + free_vars=free_vars, + eval_min=eval_min, + eval_max=eval_max, maximization=maximization, ) + dt_molt = dt_agg.melt(id_vars=[eval_var] + free_vars) + dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_vars) - dt_molt = dt_agg.melt(id_vars=[evaluation_variable] + free_variables) - dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) + plot_args = _create_plot_args( + LinePlotArgs( + xlabel=eval_var, + ylabel=fval_var, + title="Fixed-Budget Plot", + xscale="log", + yscale="log", + ), + plot_args + ) if ax is None: - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + fig, ax = plt.subplots(1, 1, figsize=plot_args.figsize) + else: + fig = None + sbs.lineplot( dt_plot, - x=evaluation_variable, + x=eval_var, y="value", style="variable", - hue=dt_plot[free_variables].apply(tuple, axis=1), + hue=dt_plot[free_vars].apply(tuple, axis=1), + palette=plot_args.line_colors, ax=ax, ) - if scale_xlog: - ax.set_xscale("log") - if scale_ylog: - ax.set_yscale("log") - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) + ax = plot_args.apply(ax=ax) - return dt_plot + _save_fig(fig, file_name, plot_args=plot_args) + + return ax, dt_plot def plot_multi_function_fixed_budget(): - # either just loop over function column(s), or more advanced raise NotImplementedError \ No newline at end of file diff --git a/src/iohinspector/plots/fixed_target.py b/src/iohinspector/plots/fixed_target.py index 5532b8f..e7aeef1 100644 --- a/src/iohinspector/plots/fixed_target.py +++ b/src/iohinspector/plots/fixed_target.py @@ -4,82 +4,111 @@ import seaborn as sbs from typing import Iterable from iohinspector.metrics.fixed_target import aggregate_running_time - +from iohinspector.plots.utils import LinePlotArgs, _save_fig, _create_plot_args def plot_single_function_fixed_target( data: pl.DataFrame, - evaluation_variable: str = "evaluations", - fval_variable: str = "raw_y", - free_variables: Iterable[str] = ["algorithm_name"], + eval_var: str = "evaluations", + fval_var: str = "raw_y", + free_vars: Iterable[str] = ["algorithm_name"], f_min: float = None, f_max: float = None, - max_budget: int = None, + scale_f_log: bool = True, + eval_max: int = None, maximization: bool = False, measures: Iterable[str] = ["ERT"], - scale_xlog: bool = True, - scale_ylog: bool = True, + *, ax: matplotlib.axes._axes.Axes = None, file_name: str = None, + plot_args: dict | LinePlotArgs = None, ): - """Create a fixed-target plot for a given set of performance data. + """Create a fixed-target plot showing Expected Running Time (ERT) analysis for algorithm performance. + + Visualizes how much computational budget (evaluations) algorithms need to reach specific target + performance levels, allowing comparison of algorithm efficiency across different difficulty targets. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - evaluation_variable (str, optional): Column in 'data' which corresponds to the number of evaluations. Defaults to "evaluations". - fval_variable (str, optional): Column in 'data' which corresponds to the performance measure. Defaults to "raw_y". - free_variables (Iterable[str], optional): Columns in 'data' which correspond to the variables which will be used to distinguish between lines in the plot. Defaults to ["algorithm_name"]. - f_min (float, optional): Minimum value to use for the 'fval_variable', if not present the min of that column will be used. Defaults to None. - f_max (float, optional): Maximum value to use for the 'fval_variable', if not present the max of that column will be used. Defaults to None. - max_budget (int, optional): Maximum value to use for the 'evaluation_variable', if not present the max of that column will be used. Defaults to None. - maximization (bool, optional): Boolean indicating whether the 'fval_variable' is being maximized. Defaults to False. - measures (Iterable[str], optional): List of measures which should be used in the plot. Valid options are 'ERT', 'mean', 'PAR-10', 'min', 'max'. Defaults to ['ERT']. - scale_xlog (bool, optional): Should the x-axis be log-scaled. Defaults to True. - scale_ylog (bool, optional): Should the y-axis be log-scaled. Defaults to True. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + data (pl.DataFrame): Input dataframe containing optimization algorithm trajectory data. + eval_var (str, optional): Which column contains the evaluation counts. Defaults to "evaluations". + fval_var (str, optional): Which column contains the function/objective values. Defaults to "raw_y". + free_vars (Iterable[str], optional): Which columns contain the grouping variables for distinguishing + between different lines in the plot. Defaults to ["algorithm_name"]. + f_min (float, optional): Minimum function value bound for target range. If None, uses data minimum. Defaults to None. + f_max (float, optional): Maximum function value bound for target range. If None, uses data maximum. Defaults to None. + scale_f_log (bool, optional): Whether function values should be log-scaled for target sampling. Defaults to True. + eval_max (int, optional): Maximum evaluation budget to consider. If None, uses data maximum. Defaults to None. + maximization (bool, optional): Whether the optimization problem is maximization. Defaults to False. + measures (Iterable[str], optional): Running time measures to plot. Valid options are "ERT" (Expected Running Time), + "mean", "PAR-10", "min", "max". Defaults to ["ERT"]. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (str, optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | LinePlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "Fixed-Target Plot". + - xlabel (str): X-axis label. Defaults to fval_var value. + - ylabel (str): Y-axis label. Defaults to "value". + - xscale (str): X-axis scale. Defaults to "log". + - yscale (str): Y-axis scale ("log" or "linear"). Defaults to "log" if scale_f_log=True. + - reverse_xaxis (bool): Whether to reverse x-axis. Defaults to True for minimization, False for maximization. + - line_colors (Sequence[str]): Colors for different lines. Defaults to seaborn palette. + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other LinePlotArgs parameters (xlim, ylim, grid, legend, fontsize, etc.). Returns: - pd.DataFrame: The final dataframe which was used to create the plot + tuple[matplotlib.axes.Axes, pl.DataFrame]: The matplotlib axes object and the processed + (melted/filtered) dataframe used to create the plot. """ + + dt_agg = aggregate_running_time( data, - evaluation_variable=evaluation_variable, - fval_variable=fval_variable, - free_variables=free_variables, + eval_var=eval_var, + fval_var=fval_var, + free_vars=free_vars, f_min=f_min, f_max=f_max, - scale_flog=scale_xlog, - max_budget=max_budget, + scale_f_log=scale_f_log, + eval_max=eval_max, maximization=maximization, ) - dt_molt = dt_agg.melt(id_vars=[fval_variable] + free_variables) - dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_variables) + dt_molt = dt_agg.melt(id_vars=[fval_var] + free_vars) + dt_plot = dt_molt[dt_molt["variable"].isin(measures)].sort_values(free_vars) + + plot_args = _create_plot_args( + LinePlotArgs( + xlabel= fval_var, + title= "Fixed-Target Plot", + xscale= "log", + yscale= "log" if scale_f_log else "linear", + reverse_xaxis= not maximization + ), + plot_args + ) + if ax is None: - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) - + fig, ax = plt.subplots(1, 1, figsize=plot_args.figsize) + else: + fig = None + sbs.lineplot( dt_plot, - x=fval_variable, + x=fval_var, y="value", style="variable", - hue=dt_plot[free_variables].apply(tuple, axis=1), + hue=dt_plot[free_vars].apply(tuple, axis=1), + palette=plot_args.line_colors, ax=ax, ) - if scale_xlog: - ax.set_xscale("log") - if scale_ylog: - ax.set_yscale("log") - if not maximization: - ax.set_xlim(ax.get_xlim()[::-1]) + + + plot_args.apply(ax) + - if ax is None and file_name: - fig.tight_layout() - fig.savefig(file_name) + _save_fig(fig, file_name, plot_args=plot_args) - return dt_plot + return ax, dt_plot def plot_multi_function_fixed_target(): diff --git a/src/iohinspector/plots/multi_objective.py b/src/iohinspector/plots/multi_objective.py index be62692..950088d 100644 --- a/src/iohinspector/plots/multi_objective.py +++ b/src/iohinspector/plots/multi_objective.py @@ -1,93 +1,164 @@ from typing import Iterable, Optional, cast +from iohinspector.metrics.multi_objective import get_pareto_front_2d, get_indicator_over_time_data import numpy as np import polars as pl import matplotlib import matplotlib.pyplot as plt import seaborn as sbs -from iohinspector.indicators import final, add_indicator -from iohinspector.metrics import get_sequence +from iohinspector.plots.utils import ScatterPlotArgs, LinePlotArgs, _save_fig, _create_plot_args def plot_paretofronts_2d( data: pl.DataFrame, - obj_vars: Iterable[str] = ["raw_y", "F2"], + obj1_var: str = "raw_y", + obj2_var: str = "F2", free_var: str = "algorithm_name", + *, ax: matplotlib.axes._axes.Axes = None, file_name: str = None, + plot_args: dict | ScatterPlotArgs = None ): - """Very basic plot to visualize pareto fronts + """Visualize 2D Pareto fronts for multi-objective optimization algorithms. + + Creates a scatter plot showing the non-dominated solutions (Pareto fronts) achieved by + different algorithms in a two-objective space, allowing visual comparison of algorithm + performance and trade-off quality. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_vars (Iterable[str], optional): Which variables (length should be 2) to use for plotting. Defaults to ["raw_y", "F2"]. - free_vars (Iterable[str], optional): Which varialbes should be used to distinguish between categories. Defaults to ["algorithm_name"]. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + data (pl.DataFrame): Input dataframe containing multi-objective optimization trajectory data. + obj1_var (str, optional): Which column contains the first objective values. Defaults to "raw_y". + obj2_var (str, optional): Which column contains the second objective values. Defaults to "F2". + free_var (str, optional): Which column contains the grouping variable for distinguishing + between different algorithms/categories. Defaults to "algorithm_name". + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (str, optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | ScatterPlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "Pareto Fronts". + - xlabel (str): X-axis label. Defaults to obj1_var value. + - ylabel (str): Y-axis label. Defaults to obj2_var value. + - point_colors (Sequence[str]): Colors for different algorithm points. Defaults to seaborn palette. + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other ScatterPlotArgs parameters (xlim, ylim, xscale, yscale, grid, legend, fontsize, etc.). Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot + tuple[matplotlib.axes.Axes, pd.DataFrame]: The matplotlib axes object and the Pareto front + dataframe used to create the plot. """ - assert len(obj_vars) == 2 + df = get_pareto_front_2d( + data, obj1_var=obj1_var, obj2_var=obj2_var + ) + + plot_args = _create_plot_args( + ScatterPlotArgs( + xlabel= obj1_var, + ylabel= obj2_var, + title= "Pareto Fronts", + ), + plot_args + ) - df = add_indicator(data, final.NonDominated(), obj_vars) + df.sort_values(free_var) + if ax is None: - fig, ax = plt.subplots(figsize=(16, 9)) - sbs.scatterplot(df.filter(pl.col("final_nondominated") == True), x=obj_vars[0], y=obj_vars[1], hue=free_var, ax=ax) - if file_name: - fig.tight_layout() - fig.savefig(file_name) - return df + fig, ax = plt.subplots(figsize=plot_args.figsize) + else: + fig = None + + sbs.scatterplot( + df, + x=obj1_var, + y=obj2_var, + hue=free_var, + palette= plot_args.point_colors, + ax=ax + ) + + plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args=plot_args) + + return ax,df def plot_indicator_over_time( data: pl.DataFrame, - obj_columns: Iterable[str] = ["raw_y", "F2"], + obj_vars: Iterable[str] = ["raw_y", "F2"], indicator: object = None, - eval_column: str = "evaluations", - evals_min: int = 1, - evals_max: int = 50_000, - nr_eval_steps: int = 50, - eval_scale_log: bool = True, - free_variable: str = "algorithm_name", + free_var: str = "algorithm_name", + eval_min: int = 1, + eval_max: int = 50_000, + scale_eval_log: bool = True, + eval_steps: int = 50, + *, ax: matplotlib.axes._axes.Axes = None, file_name: Optional[str] = None, + plot_args: dict | LinePlotArgs = None ): - """Convenience function to plot the anytime performance of a single indicator. + """Plot the anytime performance of multi-objective quality indicators over evaluation budgets. + + Creates line plots showing how quality indicators (like hypervolume, IGD, etc.) evolve + over the course of algorithm runs, enabling comparison of convergence behavior and + solution quality improvement across different algorithms. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. - indicator (object): Indicator object from iohinspector.indicators - eval_column (Iterable[str], optional): Which columns in 'data' correspond to the objectives. Defaults to 'evaluations'. - evals_min (int, optional): Lower bound for eval_column. Defaults to 0. - evals_max (int, optional): Upper bound for eval_column. Defaults to 50_000. - nr_eval_steps (int, optional): Number of steps between lower and upper bounds of eval_column. Defaults to 50. - free_variable (str, optional): Variable which corresponds to category to differentiate in the plot. Defaults to 'algorithm_name'. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + data (pl.DataFrame): Input dataframe containing multi-objective optimization trajectory data. + obj_vars (Iterable[str], optional): Which columns contain the objective values for indicator calculation. + Defaults to ["raw_y", "F2"]. + indicator (object, optional): Quality indicator object from iohinspector.indicators module. Defaults to None. + free_var (str, optional): Which column contains the grouping variable for distinguishing + between different algorithms. Defaults to "algorithm_name". + eval_min (int, optional): Minimum evaluation bound for the time axis. Defaults to 1. + eval_max (int, optional): Maximum evaluation bound for the time axis. Defaults to 50_000. + scale_eval_log (bool, optional): Whether the evaluation axis should be log-scaled. Defaults to True. + eval_steps (int, optional): Number of evaluation points to sample between eval_min and eval_max. Defaults to 50. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | LinePlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "Anytime Performance: {indicator.var_name}". + - xlabel (str): X-axis label. Defaults to "evaluations". + - ylabel (str): Y-axis label. Defaults to indicator.var_name value. + - xscale (str): X-axis scale ("log" or "linear"). Defaults to "log" if scale_eval_log=True. + - line_colors (Sequence[str]): Colors for different algorithm lines. Defaults to seaborn palette. + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other LinePlotArgs parameters (xlim, ylim, yscale, grid, legend, fontsize, etc.). + + Returns: + tuple[matplotlib.axes.Axes, pd.DataFrame]: The matplotlib axes object and the indicator + performance dataframe used to create the plot. """ + df = get_indicator_over_time_data( + data, + indicator=indicator, + obj_vars=obj_vars, + eval_min=eval_min, + eval_max=eval_max, + scale_eval_log=scale_eval_log, + eval_steps=eval_steps, + ) - evals = get_sequence( - evals_min, evals_max, nr_eval_steps, cast_to_int=True, scale_log=eval_scale_log + plot_args = _create_plot_args( + LinePlotArgs( + xlabel= "evaluations", + ylabel= indicator.var_name, + title= f"Anytime Performance: {indicator.var_name}", + xscale= "log" if scale_eval_log else "linear", + ), + plot_args ) - df = add_indicator( - data, indicator, objective_columns=obj_columns, evals=evals - ).to_pandas() + if ax is None: - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + fig, ax = plt.subplots(1, 1, figsize=plot_args.figsize) + else: + fig = None sbs.lineplot( df, - x=eval_column, + x="evaluations", y=indicator.var_name, - hue=free_variable, - palette=sbs.color_palette(n_colors=len(np.unique(data[free_variable]))), + hue=free_var, + palette=sbs.color_palette(n_colors=len(np.unique(data[free_var]))), ax=ax, ) - ax.set_xlabel(eval_column) - ax.set_xlim(evals_min, evals_max) - ax.set_xscale("log") - ax.grid() - if file_name: - fig.tight_layout() - fig.savefig(file_name) + + plot_args.apply(ax) - return df + _save_fig(fig, file_name, plot_args=plot_args) + return ax, df diff --git a/src/iohinspector/plots/ranking.py b/src/iohinspector/plots/ranking.py index 1a7acd0..1dd243d 100644 --- a/src/iohinspector/plots/ranking.py +++ b/src/iohinspector/plots/ranking.py @@ -1,4 +1,6 @@ from typing import Iterable, Optional +from iohinspector.metrics.ranking import get_robustrank_changes, get_robustrank_over_time +from iohinspector.plots.utils import BasePlotArgs, _create_plot_args, _save_fig import polars as pl import numpy as np import pandas as pd @@ -13,35 +15,62 @@ def plot_tournament_ranking( data, alg_vars: Iterable[str] = ["algorithm_name"], fid_vars: Iterable[str] = ["function_name"], - perf_var: str = "raw_y", + fval_var: str = "raw_y", nrounds: int = 25, maximization: bool = False, + *, ax: matplotlib.axes._axes.Axes = None, file_name: str = None, + plot_args: dict | BasePlotArgs = None, ): - """Method to plot ELO ratings of a set of algorithm on a set of problems. - Calculated based on nrounds of competition, where in each round all algorithms face all others (pairwise) on every function. - For each round, a sampled performance value is taken from the data and used to determine the winner. + """Plot ELO ratings from tournament-style algorithm competition across multiple problems. + + Creates a point plot with error bars showing ELO ratings calculated from pairwise algorithm + competitions. In each round, all algorithms compete against each other on every function, + with performance samples determining winners and ELO rating updates. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - alg_vars (Iterable[str], optional): Which variables specific the algortihms which will compete. Defaults to ["algorithm_name"]. - fid_vars (Iterable[str], optional): Which variables denote the problems on which will be competed. Defaults to ["function_name"]. - perf_var (str, optional): Which variable corresponds to the performance. Defaults to "raw_y". - nrounds (int, optional): How many round should be played. Defaults to 25. + data (pl.DataFrame): Input dataframe containing algorithm performance trajectory data. + alg_vars (Iterable[str], optional): Which columns contain the algorithm identifiers that will compete. + Defaults to ["algorithm_name"]. + fid_vars (Iterable[str], optional): Which columns contain the problem/function identifiers for competition. + Defaults to ["function_name"]. + fval_var (str, optional): Which column contains the performance values. Defaults to "raw_y". + nrounds (int, optional): Number of tournament rounds to simulate. Defaults to 25. maximization (bool, optional): Whether the performance should be maximized. Defaults to False. - ax (matplotlib.axes._axes.Axes, optional): Existing matplotlib axis object to draw the plot on. - file_name (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (str, optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | BasePlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. Defaults to "Tournament Ranking". + - xlabel (str): X-axis label. Defaults to "Algorithms". + - ylabel (str): Y-axis label. Defaults to "ELO Rating". + - figsize (Tuple[float, float]): Figure size. Defaults to (16, 9). + - All other BasePlotArgs parameters (xlim, ylim, xscale, yscale, grid, legend, fontsize, etc.). Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot + tuple[matplotlib.axes.Axes, pd.DataFrame]: The matplotlib axes object and the ELO ratings + dataframe used to create the plot. """ # candlestick plot based on average and volatility dt_elo = get_tournament_ratings( - data, alg_vars, fid_vars, perf_var, nrounds, maximization + data, alg_vars, fid_vars, fval_var, nrounds, maximization + ) + + plot_args = _create_plot_args( + BasePlotArgs( + title= "Tournament Ranking", + xlabel="Algorithms", + ylabel="ELO Rating", + grid= True + ), + plot_args ) + + if ax is None: - _, ax = plt.subplots(1, 1, figsize=(10, 5)) + fig, ax = plt.subplots(1, 1, figsize=plot_args.figsize) + else: + fig = None sbs.pointplot(data=dt_elo, x=alg_vars[0], y="Rating", linestyle="none", ax=ax) @@ -55,12 +84,13 @@ def plot_tournament_ranking( capsize=5, elinewidth=1.5, ) - ax.grid() + + plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args) + - if file_name: - plt.tight_layout() - plt.savefig(file_name) - return dt_elo + return ax, dt_elo def robustranking(): @@ -82,45 +112,52 @@ def winnning_fraction_heatmap(): def plot_robustrank_over_time( data: pl.DataFrame, - obj_columns: Iterable[str], + obj_vars: Iterable[str], evals: Iterable[int], indicator: object, - filename_fig: Optional[str] = None, + *, + file_name: Optional[str] = None, ): - """Plot robust ranking at distinct timesteps + """Plot robust ranking confidence intervals at distinct evaluation timesteps. + + Creates multiple subplots showing robust ranking analysis with confidence intervals + for algorithm performance at different evaluation budgets, using statistical comparison + methods to handle uncertainty in performance measurements. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. - evals (Iterable[int]): Timesteps at which to get the rankings - indicator (object): Indicator object from iohinspector.indicators - filename_fig (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + data (pl.DataFrame): Input dataframe containing algorithm performance trajectory data. + Must contain data for a single function only. + obj_vars (Iterable[str]): Which columns contain the objective values for ranking calculation. + evals (Iterable[int]): Evaluation timesteps at which to compute and plot rankings. + indicator (object): Quality indicator object from iohinspector.indicators module. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + + Returns: + tuple[np.ndarray, tuple]: Array of matplotlib axes objects and a tuple containing + (comparison, benchmark) data used for the robust ranking analysis. + + Raises: + ValueError: If data contains multiple functions (function_id has more than one unique value). """ - from robustranking import Benchmark - from robustranking.comparison import MOBootstrapComparison, BootstrapComparison - from robustranking.utils.plots import plot_ci_list, plot_line_ranks - - df = add_indicator( - data, indicator, objective_columns=obj_columns, evals=evals - ).to_pandas() - df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] - dt_pivoted = pd.pivot( - df_part, - index=["algorithm_name", "run_id"], - columns=["evaluations"], - values=[indicator.var_name], - ).reset_index() - dt_pivoted.columns = ["algorithm_name", "run_id"] + evals - benchmark = Benchmark() - benchmark.from_pandas(dt_pivoted, "algorithm_name", "run_id", evals) - comparison = MOBootstrapComparison( - benchmark, - alpha=0.05, - minimise=indicator.minimize, - bootstrap_runs=1000, - aggregation_method=np.mean, + from robustranking.utils.plots import plot_ci_list + + if(data["function_id"].n_unique() > 1): + raise ValueError("Robust ranking over time plot can only be generated for a single function at a time.") + + comparison, benchmark = get_robustrank_over_time( + data=data, + obj_vars=obj_vars, + evals=evals, + indicator=indicator, ) - fig, axs = plt.subplots(1, 4, figsize=(16, 9), sharey=True) + + plot_args =BasePlotArgs( + figsize=(5*len(evals), 5), + ) + + + fig, axs = plt.subplots(1, len(evals), figsize=plot_args.figsize, sharey=True) + for ax, runtime in zip(axs.ravel(), benchmark.objectives): plot_ci_list(comparison, objective=runtime, ax=ax) if runtime != evals[0]: @@ -129,58 +166,59 @@ def plot_robustrank_over_time( ax.get_legend().remove() ax.set_title(runtime) - plt.tight_layout() - if filename_fig: - plt.savefig(filename_fig) - plt.close() + _save_fig(fig, file_name, plot_args) + return axs, comparison, benchmark def plot_robustrank_changes( data: pl.DataFrame, - obj_columns: Iterable[str], + obj_vars: Iterable[str], evals: Iterable[int], indicator: object, - filename_fig: Optional[str] = None, + *, + ax: matplotlib.axes._axes.Axes = None, + file_name: Optional[str] = None, ): - """Plot robust ranking changes at distinct timesteps + """Plot robust ranking changes over evaluation timesteps as connected line plots. + + Creates a line plot showing how algorithm rankings evolve over time, with lines + connecting ranking positions across different evaluation budgets to visualize + ranking stability and performance trajectory changes. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - obj_columns (Iterable[str], optional): Which columns in 'data' correspond to the objectives. - evals (Iterable[int]): Timesteps at which to get the rankings - indicator (object): Indicator object from iohinspector.indicators - filename_fig (str, optional): Where should the resulting plot be stored. Defaults to None. If existing axis is provided, this functionality is disabled. + data (pl.DataFrame): Input dataframe containing algorithm performance trajectory data. + obj_vars (Iterable[str]): Which columns contain the objective values for ranking calculation. + evals (Iterable[int]): Evaluation timesteps at which to compute rankings and plot changes. + indicator (object): Quality indicator object from iohinspector.indicators module. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + + Returns: + tuple[matplotlib.axes.Axes, object]: The matplotlib axes object and the ranking + comparisons data used to create the plot. """ - from robustranking import Benchmark - from robustranking.comparison import MOBootstrapComparison, BootstrapComparison - from robustranking.utils.plots import plot_ci_list, plot_line_ranks - - df = add_indicator( - data, indicator, objective_columns=obj_columns, evals=evals - ).to_pandas() - df_part = df[["evaluations", indicator.var_name, "algorithm_name", "run_id"]] - dt_pivoted = pd.pivot( - df_part, - index=["algorithm_name", "run_id"], - columns=["evaluations"], - values=[indicator.var_name], - ).reset_index() - dt_pivoted.columns = ["algorithm_name", "run_id"] + evals - - comparisons = { - f"{eval}": BootstrapComparison( - Benchmark().from_pandas(dt_pivoted, "algorithm_name", "run_id", eval), - alpha=0.05, - minimise=indicator.minimize, - bootstrap_runs=1000, - ) - for eval in evals - } - - fig, ax = plt.subplots(1, 1, figsize=(16, 9)) + from robustranking.utils.plots import plot_line_ranks + + comparisons = get_robustrank_changes( + data=data, + obj_vars=obj_vars, + evals=evals, + indicator=indicator, + ) + + plot_args = BasePlotArgs( + figsize=(max(5 * len(evals), 16), 5), + ) + + + if ax is None: + fig, ax = plt.subplots(1, 1, figsize=plot_args.figsize) + else: + fig = None + plot_line_ranks(comparisons, ax=ax) - plt.tight_layout() - if filename_fig: - plt.savefig(filename_fig) - plt.close() + plot_args.apply(ax) + _save_fig(fig, file_name, plot_args) + + return ax, comparisons diff --git a/src/iohinspector/plots/single_run.py b/src/iohinspector/plots/single_run.py index 340ff7e..650d6d7 100644 --- a/src/iohinspector/plots/single_run.py +++ b/src/iohinspector/plots/single_run.py @@ -4,47 +4,79 @@ import polars as pl from typing import Iterable, Optional import numpy as np - +from iohinspector.plots.utils import HeatmapPlotArgs, _create_plot_args, _save_fig +from iohinspector.metrics.single_run import get_heatmap_single_run_data def plot_heatmap_single_run( data: pl.DataFrame, - var_cols: Iterable[str], - eval_col: str = "evaluations", - scale_xlog: bool = True, - x_mins: Iterable[float] = [-5], - x_maxs: Iterable[float] = [5], + vars: Iterable[str], + eval_var: str = "evaluations", + var_mins: Iterable[float] = [-5], + var_maxs: Iterable[float] = [5], + *, ax: matplotlib.axes._axes.Axes = None, file_name: Optional[str] = None, + plot_args: dict | HeatmapPlotArgs = None ): - """Create a heatmap showing the search space points evaluated in a single run + """Create a heatmap visualization showing search space exploration patterns in a single algorithm run. + + Visualizes how an optimization algorithm explores the search space over time by showing + the density of evaluations across different variable dimensions and evaluation budgets, + revealing search patterns and exploration behavior. Args: - data (pl.DataFrame): The DataFrame which contains the full performance trajectory. Should be generated from a DataManager. - var_cols (Iterable[str]): The variables which correspond to the searchspace variable columns - eval_col (str): The variable corresponding to evaluations. Defaults to 'evaluations' - scale_xlog (bool, optional): Whether the evaluations should be log-scaled. Defaults to True. - x_mins (Iterable[float], optional): Minimum bound for the variables. Should be of the same length as 'var_cols'. Defaults to [-5]. - x_maxs (Iterable[float], optional): Maximum bound for the variables. Should be of the same length as 'var_cols'.. Defaults to [5]. - ax (matplotlib.axes._axes.Axes, optional): Axis on which to create the plot. Defaults to None. - file_name (Optional[str], optional): If ax is not given, filename to save the plot. Defaults to None. + data (pl.DataFrame): Input dataframe containing trajectory data from a single algorithm run. + Must contain data for exactly one run (unique data_id). + vars (Iterable[str]): Which columns contain the decision/search space variables to visualize. + eval_var (str, optional): Which column contains the evaluation counts. Defaults to "evaluations". + var_mins (Iterable[float], optional): Minimum bounds for the search space variables. + Should be same length as vars. Defaults to [-5]. + var_maxs (Iterable[float], optional): Maximum bounds for the search space variables. + Should be same length as vars. Defaults to [5]. + ax (matplotlib.axes._axes.Axes, optional): Matplotlib axes to plot on. If None, creates new figure. Defaults to None. + file_name (Optional[str], optional): Path to save the plot. If None, plot is not saved. Defaults to None. + plot_args (dict | HeatmapPlotArgs, optional): Plot styling arguments. Can include: + - title (str): Plot title. No default title set. + - xlabel (str): X-axis label. Defaults to eval_var value. + - ylabel (str): Y-axis label. Defaults to "Variables". + - figsize (Tuple[float, float]): Figure size. Defaults to (32, 9). + - heatmap_palette (str): Colormap for the heatmap. Defaults to "viridis". + - All other HeatmapPlotArgs parameters (xlim, ylim, xscale, yscale, grid, legend, fontsize, etc.). Returns: - pd.DataFrame: pandas dataframe of the exact data used to create the plot + tuple[matplotlib.axes.Axes, pd.DataFrame]: The matplotlib axes object and the processed + heatmap dataframe used to create the plot. + + Raises: + AssertionError: If data contains multiple runs (data_id has more than one unique value). """ assert data["data_id"].n_unique() == 1 - dt_plot = data[var_cols].transpose().to_pandas() - dt_plot.columns = list(data[eval_col]) - x_mins_arr = np.array(x_mins) - x_maxs_arr = np.array(x_maxs) - dt_plot = (dt_plot.subtract(x_mins_arr, axis=0)).divide(x_maxs_arr - x_mins_arr, axis=0) + + dt_plot = get_heatmap_single_run_data( + data = data, + vars = vars, + eval_var=eval_var, + var_mins=var_mins, + var_maxs=var_maxs, + ) + + plot_args = _create_plot_args( + HeatmapPlotArgs( + figsize= (32, 9), + xlabel= eval_var, + ylabel= "Variables", + ), + plot_args + ) + if ax is None: - fig, ax = plt.subplots(figsize=(32, 9)) - sbs.heatmap(dt_plot, cmap="viridis", vmin=0, vmax=1, ax=ax) - if scale_xlog: - ax.set_xscale("log") - ax.set_xlim(1, len(data)) - - if file_name: - fig.tight_layout() - fig.savefig(file_name) - return dt_plot + fig, ax = plt.subplots(figsize=plot_args.figsize) + else: + fig = None + + sbs.heatmap(dt_plot, cmap=plot_args.heatmap_palette, vmin=0, vmax=1, ax=ax) + + plot_args.apply(ax) + + _save_fig(fig, file_name, plot_args=plot_args) + return ax, dt_plot diff --git a/src/iohinspector/plots/utils.py b/src/iohinspector/plots/utils.py new file mode 100644 index 0000000..fd750b2 --- /dev/null +++ b/src/iohinspector/plots/utils.py @@ -0,0 +1,338 @@ +from dataclasses import dataclass, field +from typing import Optional, Tuple, Sequence, Union, Dict, Any +from dataclasses import fields +from typing import TypeVar, Generic + +T = TypeVar('T', bound='BasePlotArgs') + +@dataclass +class BasePlotArgs: + title: Optional[str] = None + xlabel: Optional[str] = None + ylabel: Optional[str] = None + + xlim: Optional[Tuple[float, float]] = None + ylim: Optional[Tuple[float, float]] = None + + xscale: str = None + yscale: str = None + + figsize: Optional[Tuple[float, float]] = (16,9) + dpi: Optional[int] = None + + grid: Union[bool, str] = False + legend: bool = False + legend_loc: str = "best" + legend_kwargs: Dict[str, Any] = field(default_factory=dict) + + fontsize: Optional[Union[int, str]] = None + title_fontsize: Optional[Union[int, str]] = None + tick_params: Dict[str, Any] = field(default_factory=dict) + + xticks: Optional[Sequence[float]] = None + yticks: Optional[Sequence[float]] = None + + reverse_xaxis: bool = False + reverse_yaxis: bool = False + + tight_layout: bool = True + + def __post_init__(self) -> None: + if self.xlim is not None and not isinstance(self.xlim, tuple): + self.xlim = tuple(self.xlim) # type: ignore + if self.ylim is not None and not isinstance(self.ylim, tuple): + self.ylim = tuple(self.ylim) # type: ignore + if self.xticks is not None and not isinstance(self.xticks, tuple): + self.xticks = tuple(self.xticks) # type: ignore + if self.yticks is not None and not isinstance(self.yticks, tuple): + self.yticks = tuple(self.yticks) # type: ignore + + def as_dict(self) -> Dict[str, Any]: + """Convert the plot arguments to a dictionary representation. + + Returns: + Dict[str, Any]: Dictionary containing all plot configuration parameters. + """ + return { + "title": self.title, + "xlabel": self.xlabel, + "ylabel": self.ylabel, + "xlim": self.xlim, + "ylim": self.ylim, + "xscale": self.xscale, + "yscale": self.yscale, + "figsize": self.figsize, + "dpi": self.dpi, + "grid": self.grid, + "legend": self.legend, + "legend_loc": self.legend_loc, + "legend_kwargs": dict(self.legend_kwargs), + "fontsize": self.fontsize, + "title_fontsize": self.title_fontsize, + "tick_params": dict(self.tick_params), + "xticks": self.xticks, + "yticks": self.yticks, + "tight_layout": self.tight_layout, + } + def apply(self, ax): + """Apply stored plot properties to a matplotlib Axes object. + + Args: + ax: matplotlib Axes instance to apply the properties to. + + Returns: + ax: The modified matplotlib Axes object with properties applied. + + Raises: + RuntimeError: If matplotlib is not available. + """ + try: + import matplotlib.pyplot as plt + except Exception as exc: + raise RuntimeError("matplotlib is required to apply plot properties") from exc + + + # Title and labels with fontsize handling + if self.title is not None: + if self.title_fontsize is not None: + ax.set_title(self.title, fontsize=self.title_fontsize) + elif self.fontsize is not None: + ax.set_title(self.title, fontsize=self.fontsize) + else: + ax.set_title(self.title) + + if self.xlabel is not None: + if self.fontsize is not None: + ax.set_xlabel(self.xlabel, fontsize=self.fontsize) + else: + ax.set_xlabel(self.xlabel) + + if self.ylabel is not None: + if self.fontsize is not None: + ax.set_ylabel(self.ylabel, fontsize=self.fontsize) + else: + ax.set_ylabel(self.ylabel) + + + + # Ticks + if self.xticks is not None: + ax.set_xticks(list(self.xticks)) + if self.yticks is not None: + ax.set_yticks(list(self.yticks)) + + # Limits + if self.xlim is not None: + ax.set_xlim(*self.xlim) + if self.ylim is not None: + ax.set_ylim(*self.ylim) + + # Scales + if self.xscale: + ax.set_xscale(self.xscale) + if self.yscale: + ax.set_yscale(self.yscale) + + + # Grid + if isinstance(self.grid, bool): + ax.grid(self.grid) + elif isinstance(self.grid, str): + ax.grid(True, which=self.grid) + + # Legend + if self.legend: + kwargs = dict(self.legend_kwargs or {}) + if "loc" not in kwargs: + kwargs["loc"] = self.legend_loc + # Only attempt to create legend if there are labeled artists + try: + ax.legend(**kwargs) + except Exception: + # fallback: call without kwargs + ax.legend() + + # Tick params (includes labelsize if provided) + if self.tick_params: + ax.tick_params(**self.tick_params) + elif self.fontsize is not None: + ax.tick_params(labelsize=self.fontsize) + + # Reverse axes if requested + if self.reverse_xaxis: + ax.invert_xaxis() + if self.reverse_yaxis: + ax.invert_yaxis() + + return ax + + + def override(self, other: Optional[Union["BasePlotArgs", Dict[str, Any]]]): + """Update plot arguments in place with values from another source. + + Args: + other (Optional[Union[BasePlotArgs, Dict[str, Any]]]): Plot arguments to override current values with. + Can be either a BasePlotArgs instance or a dictionary. Values from `other` override those + from `self` when they are not None. Dictionary fields (legend_kwargs, tick_params) are merged + with `other` taking precedence for overlapping keys. + + Note: + Works with inheritance - handles fields from both base and derived classes. + For sequence-like fields (xlim, ylim, xticks, yticks) lists/tuples from `other` are converted to tuples. + """ + if other is None: + return + + is_dict = isinstance(other, dict) + + # Use self.__class__ to get fields from the actual class (including subclass fields) + for f in fields(self.__class__): + name = f.name + v2 = other.get(name, None) if is_dict else getattr(other, name, None) + + if v2 is not None: + setattr(self, name, v2) + + + +@dataclass +class LinePlotArgs(BasePlotArgs): + line_colors: Optional[Sequence[str]] = None + + def as_dict(self): + """Convert the line plot arguments to a dictionary representation. + + Returns: + Dict[str, Any]: Dictionary containing all line plot configuration parameters including line colors. + """ + results = super().as_dict() + results["line_colors"] = self.line_colors + return results + + + def apply(self, ax): + """Apply line plot properties to a matplotlib Axes object. + + Args: + ax: matplotlib Axes instance to apply the line plot properties to. + + Returns: + ax: The modified matplotlib Axes object with line plot properties applied. + """ + return super().apply(ax) + + def override(self, other): + """Update line plot arguments in place with values from another source. + + Args: + other: Line plot arguments to override current values with. + """ + return super().override(other) + + +@dataclass +class HeatmapPlotArgs(BasePlotArgs): + heatmap_palette: Optional[str] = "viridis" + use_background_color: bool = True + background_color: str = "white" + + def as_dict(self): + """Convert the heatmap plot arguments to a dictionary representation. + + Returns: + Dict[str, Any]: Dictionary containing all heatmap plot configuration parameters including palette settings. + """ + results = super().as_dict() + results["heatmap_palette"] = self.heatmap_palette + return results + + + def apply(self, ax): + """Apply heatmap plot properties to a matplotlib Axes object. + + Args: + ax: matplotlib Axes instance to apply the heatmap plot properties to. + + Returns: + ax: The modified matplotlib Axes object with heatmap plot properties applied. + """ + return super().apply(ax) + + def override(self, other): + """Update heatmap plot arguments in place with values from another source. + + Args: + other: Heatmap plot arguments to override current values with. + """ + return super().override(other) + + +@dataclass +class ScatterPlotArgs(BasePlotArgs): + point_colors: Optional[Sequence[str]] = None + + def as_dict(self): + """Convert the scatter plot arguments to a dictionary representation. + + Returns: + Dict[str, Any]: Dictionary containing all scatter plot configuration parameters including point colors. + """ + results = super().as_dict() + results["point_colors"] = self.point_colors + return results + + + def apply(self, ax): + """Apply scatter plot properties to a matplotlib Axes object. + + Args: + ax: matplotlib Axes instance to apply the scatter plot properties to. + + Returns: + ax: The modified matplotlib Axes object with scatter plot properties applied. + """ + return super().apply(ax) + + def override(self, other): + """Update scatter plot arguments in place with values from another source. + + Args: + other: Scatter plot arguments to override current values with. + """ + return super().override(other) + +def _save_fig(fig = None, file_name: str=None, plot_args: BasePlotArgs=None): + """Save a matplotlib figure to file with optional plot arguments. + + Args: + fig: matplotlib Figure object to save. Defaults to None. + file_name (str, optional): Path where to save the figure. Defaults to None. + plot_args (BasePlotArgs, optional): Plot arguments containing DPI and layout settings. Defaults to None. + """ + if fig and file_name: + if plot_args.tight_layout: + fig.tight_layout() + fig.savefig(file_name, dpi=plot_args.dpi) + + +def _create_plot_args( + defaults: T, + overrides: Optional[Union[T, Dict[str, Any]]] = None, +) -> T: + """Create plot properties by merging defaults with overrides, preserving the exact type of the defaults object. + + Args: + defaults (T): Default properties object (any BasePlotArgs subclass). + overrides (Optional[Union[T, Dict[str, Any]]], optional): Properties to override (dict or same type as defaults). Defaults to None. + + Returns: + T: New properties object of the same type as defaults with overrides applied. + """ + if overrides is None: + return defaults + + # Create a copy to avoid mutating the input + import copy + result = copy.deepcopy(defaults) + result.override(overrides) + return result \ No newline at end of file diff --git a/tests/test_data.py b/tests/test_data.py index 805dcf2..af51c8c 100644 --- a/tests/test_data.py +++ b/tests/test_data.py @@ -105,7 +105,7 @@ def test_plot_ecdf(self): selection = manager.select(function_ids=[1], algorithms = ['algorithm_A', 'algorithm_B']) df = selection.load(monotonic=True, include_meta_data=True) - dt = plot_ecdf(df) + ax, dt = plot_ecdf(df) self.assertEqual(dt.shape, (66, 14)) diff --git a/tests/test_metrics/test_aocc.py b/tests/test_metrics/test_aocc.py index 511cfa1..2fd1afd 100644 --- a/tests/test_metrics/test_aocc.py +++ b/tests/test_metrics/test_aocc.py @@ -1,5 +1,6 @@ import unittest import polars as pl +import pandas as pd import numpy as np from iohinspector.metrics import get_aocc @@ -16,34 +17,41 @@ def setUp(self): def test_basic_aocc(self): # AOCC should be computed for the group - result = get_aocc(self.df, max_budget=10) + result = get_aocc(self.df, eval_max=10) + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("AOCC", result.columns) aocc_val = result["AOCC"][0] self.assertTrue(aocc_val == 6.5) + + result = get_aocc(self.df, eval_max=10, return_as_pandas=False) + self.assertIsInstance(result, pl.DataFrame) + def test_multiple_groups(self): # Add a second group df = self.df.with_columns([ pl.Series("function_name", ["f1", "f1", "f1", "f2", "f2", "f2"]) ]) - result = get_aocc(df, max_budget=10) + + result = get_aocc(df, eval_max=10) self.assertIn("AOCC", result.columns) - aocc_f1_val = result.filter(pl.col("function_name") == "f1")["AOCC"][0] - aocc_f2_val = result.filter(pl.col("function_name") == "f2")["AOCC"][0] + aocc_f1_val = result[result["function_name"] == "f1"]["AOCC"].iloc[0] + aocc_f2_val = result[result["function_name"] == "f2"]["AOCC"].iloc[0] self.assertTrue(aocc_f1_val == 5.5) self.assertTrue(aocc_f2_val == 7.5) def test_custom_fval_col(self): - # Use a different column for fval_col + # Use a different column for fval_var df = self.df.rename({"eaf": "custom_col"}) - result = get_aocc(df, max_budget=10, fval_col="custom_col") + result = get_aocc(df, eval_max=10, fval_var="custom_col") self.assertIn("AOCC", result.columns) aocc_val = result["AOCC"][0] self.assertTrue(aocc_val == 6.5) - def test_custom_group_cols(self): - # Use only algorithm_name as group col - result = get_aocc(self.df, max_budget=10, group_cols=["algorithm_name"]) + def test_custom_free_vars(self): + # Use only algorithm_name as free var + result = get_aocc(self.df, eval_max=10, free_vars=["algorithm_name"]) aocc_val = result["AOCC"][0] self.assertTrue(aocc_val == 6.5) @@ -56,7 +64,7 @@ def test_aocc_with_missing_evaluations(self): "evaluations": [0, 5, 10, 0, 10], "eaf": [10.0, 8.0, 4.0, 12.0, 6.0], }) - result = get_aocc(df, max_budget=10) + result = get_aocc(df, eval_max=10) self.assertIn("AOCC", result.columns) aocc_val = result["AOCC"][0] @@ -65,7 +73,7 @@ def test_aocc_with_missing_evaluations(self): def test_aocc_zero_budget(self): # Test with max_budget=0 (should handle gracefully) df = self.df - result = get_aocc(df, max_budget=0) + result = get_aocc(df, eval_max=0) self.assertIn("AOCC", result.columns) # AOCC should be nan or 0 aocc_val = result["AOCC"][0] diff --git a/tests/test_metrics/test_eaf.py b/tests/test_metrics/test_eaf.py index f6eec00..2bcec24 100644 --- a/tests/test_metrics/test_eaf.py +++ b/tests/test_metrics/test_eaf.py @@ -1,12 +1,13 @@ -from turtle import pd import unittest import polars as pl +import pandas as pd import numpy as np -import matplotlib -from pathlib import Path -from iohinspector.metrics import get_discritized_eaf_single_objective -matplotlib.use("Agg") # Use non-interactive backend for tests -import matplotlib.pyplot as plt +from iohinspector.metrics.eaf import ( + get_discritized_eaf_single_objective, + get_eaf_data, + get_eaf_pareto_data, + get_eaf_diff_data +) class TestGetDiscritizedEAF(unittest.TestCase): def setUp(self): @@ -25,6 +26,9 @@ def setUp(self): def test_basic_single_data_id(self): result = get_discritized_eaf_single_objective(self.data) + + self.assertIsInstance(result, pd.DataFrame) + self.assertIn('eaf_target', result.index.names) self.assertTrue(len(result.columns) == 10) # default x_targets self.assertEqual(result.shape[0], 101) # default y_targets @@ -33,6 +37,9 @@ def test_basic_single_data_id(self): self.assertEqual(result[1].tolist()[-1], 0) self.assertEqual(result[1000].tolist()[0], 1) + result = get_discritized_eaf_single_objective(self.data, return_as_pandas=False) + self.assertIsInstance(result, pl.DataFrame) + def test_basic_multi_data_id(self): result = get_discritized_eaf_single_objective(self.multi_data) self.assertIn('eaf_target', result.index.names) @@ -69,6 +76,210 @@ def test_scale_eval_log_and_f_log(self): np.testing.assert_allclose(self.budgets, np.linspace(1, 1000, 10)) +class TestGetEAFData(unittest.TestCase): + def setUp(self): + # Simple predictable data: constant improvement + self.simple_data = pl.DataFrame({ + "evaluations": [1, 2, 3, 4, 5], + "raw_y": [5.0, 4.0, 3.0, 2.0, 1.0], # Decreasing linearly + "data_id": [1, 1, 1, 1, 1] + }) + + # Two identical runs for predictable EAF + self.dual_data = pl.DataFrame({ + "evaluations": [1, 2, 3, 1, 2, 3], + "raw_y": [10.0, 5.0, 1.0, 10.0, 5.0, 1.0], # Same values for both runs + "data_id": [1, 1, 1, 2, 2, 2] + }) + + + def test_basic_with_simple_data(self): + """Test with simple predictable data""" + result = get_eaf_data(self.simple_data, eval_min=1, eval_max=5, scale_eval_log=False) + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("evaluations", result.columns) + self.assertIn("raw_y", result.columns) + self.assertIn("data_id", result.columns) + + # Check that we have the expected number of rows (should be same as input) + self.assertEqual(len(result), len(self.simple_data)) + + # Check that data_id is preserved + self.assertEqual(result["data_id"].unique().tolist(), [1]) + + # Check evaluation values are within expected range + self.assertTrue((result["evaluations"] >= 1).all()) + self.assertTrue((result["evaluations"] <= 5).all()) + + def test_dual_runs_predictable_eaf(self): + result = get_eaf_data(self.dual_data, eval_min=1, eval_max=3, scale_eval_log=False) + + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("evaluations", result.columns) + self.assertIn("raw_y", result.columns) + self.assertIn("data_id", result.columns) + + # Should have both data_ids + self.assertEqual(len(result["data_id"].unique()), 2) + self.assertEqual(set(result["data_id"].unique()), {1, 2}) + + # Should have expected number of rows + self.assertEqual(len(result), len(self.dual_data)) + + def test_return_types(self): + """Test different return types""" + # Pandas return + result_pd = get_eaf_data(self.simple_data, return_as_pandas=True) + self.assertIsInstance(result_pd, pd.DataFrame) + + # Polars return + result_pl = get_eaf_data(self.simple_data, return_as_pandas=False) + self.assertIsInstance(result_pl, pl.DataFrame) + + +class TestGetEAFParetoData(unittest.TestCase): + def setUp(self): + # Simple predictable Pareto front data + # Run 1: Points that clearly dominate each other + # Run 2: Same structure but slightly worse + self.simple_mo_data = pl.DataFrame({ + "obj1": [3.0, 2.0, 1.0, 3.5, 2.5, 0.5], # Minimization objective + "obj2": [1.0, 2.0, 3.0, 1.5, 2.5, 3.0], # Minimization objective + "data_id": [1, 1, 1, 2, 2, 2] + }) + + self.simple_results = pl.DataFrame({ + "obj1": [3.0, 2.0, 1.0, 3.5, 2.5, 0.5], + "obj2": [1.0, 2.0, 3.0, 1.5, 2.5, 3.0], + "eaf": [0.5, 0.5, 1.0, 1.0, 1.0, 0.5] + }) + + # Identical runs for predictable EAF = 50% + self.identical_mo_data = pl.DataFrame({ + "obj1": [1.0, 2.0, 3.0, 1.0, 2.0, 3.0], + "obj2": [3.0, 2.0, 1.0, 3.0, 2.0, 1.0], + "data_id": [1, 1, 1, 2, 2, 2] + }) + + def test_simple_pareto_fronts(self): + """Test with simple, predictable Pareto front data""" + result = get_eaf_pareto_data(self.simple_mo_data, "obj1", "obj2") + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("eaf", result.columns) + self.assertIn("obj1", result.columns) + self.assertIn("obj2", result.columns) + # Should have some data points + self.assertGreater(len(result), 0) + + for row in result.itertuples(): + obj1 = row.obj1 + obj2 = row.obj2 + eaf_value = row.eaf + expected_eaf = self.simple_results.filter( + (pl.col("obj1") == obj1) & (pl.col("obj2") == obj2) + )["eaf"].to_list()[0] + + self.assertAlmostEqual(eaf_value, expected_eaf) + + + + def test_identical_runs_eaf(self): + result = get_eaf_pareto_data(self.identical_mo_data, "obj1", "obj2") + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("eaf", result.columns) + self.assertIn("obj1", result.columns) + self.assertIn("obj2", result.columns) + + # Should have some data points + self.assertGreater(len(result), 0) + + max_per_pair = result.groupby(["obj1", "obj2"])["eaf"].max() + self.assertTrue(np.allclose(max_per_pair.values, 1.0)) + + def test_return_types(self): + """Test different return types""" + # Pandas return (default) + result_pd = get_eaf_pareto_data(self.simple_mo_data, "obj1", "obj2") + self.assertIsInstance(result_pd, pd.DataFrame) + + # Polars return + result_pl = get_eaf_pareto_data(self.simple_mo_data, "obj1", "obj2", return_as_pandas=False) + self.assertIsInstance(result_pl, pl.DataFrame) + + +class TestGetEAFDiffData(unittest.TestCase): + def setUp(self): + # Dataset 1: Better performance (lower values for minimization) + self.better_data = pl.DataFrame({ + "obj1": [1.0, 2.0, 3.0], + "obj2": [3.0, 2.0, 1.0], + "data_id": [1, 1, 1] + }) + + # Dataset 2: Worse performance (higher values) + self.worse_data = pl.DataFrame({ + "obj1": [2.0, 3.0, 4.0], + "obj2": [4.0, 3.0, 2.0], + "data_id": [1, 1, 1] + }) + + # Identical datasets for predictable diff = 0 + self.identical_data1 = pl.DataFrame({ + "obj1": [1.0, 2.0], + "obj2": [2.0, 1.0], + "data_id": [1, 1] + }) + + self.identical_data2 = pl.DataFrame({ + "obj1": [2.0, 1.0], + "obj2": [1.0, 2.0], + "data_id": [1, 1] + }) + + def test_clear_performance_difference(self): + """Test with clearly better vs worse datasets""" + result = get_eaf_diff_data(self.better_data, self.worse_data, "obj1", "obj2") + + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("eaf_diff", result.columns) + self.assertIn("x_min", result.columns) + self.assertIn("y_min", result.columns) + self.assertIn("x_max", result.columns) + self.assertIn("y_max", result.columns) + + # Should have some rectangles with differences + self.assertGreater(len(result), 0) + + # Check that rectangle coordinates are valid + self.assertTrue((result["x_min"] <= result["x_max"]).all()) + self.assertTrue((result["y_min"] <= result["y_max"]).all()) + + # Check for no NaN values + self.assertFalse(result.isna().any().any()) + + # Since better_data dominates worse_data, should have positive differences + self.assertGreater(result["eaf_diff"].max(), 0) + + def test_identical_datasets_zero_diff(self): + """Test with identical datasets - should get minimal or no differences""" + result = get_eaf_diff_data(self.identical_data1, self.identical_data2, "obj1", "obj2") + self.assertIsInstance(result, pd.DataFrame) + self.assertIn("eaf_diff", result.columns) + + # Result should be either empty or contain only very small differences + self.assertTrue(len(result) == 0 or abs(result["eaf_diff"]).max() < 0.1) + + def test_return_types(self): + """Test different return types""" + # Pandas return (default) + result_pd = get_eaf_diff_data(self.better_data, self.worse_data, "obj1", "obj2") + self.assertIsInstance(result_pd, pd.DataFrame) + + # Polars return + result_pl = get_eaf_diff_data(self.better_data, self.worse_data, "obj1", "obj2", return_as_pandas=False) + self.assertIsInstance(result_pl, pl.DataFrame) + + if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_ecdf.py b/tests/test_metrics/test_ecdf.py index 0fea6fe..92dc37a 100644 --- a/tests/test_metrics/test_ecdf.py +++ b/tests/test_metrics/test_ecdf.py @@ -15,7 +15,7 @@ def setUp(self): }) def test_basic_ecdf(self): - result = get_data_ecdf(self.df, scale_xlog=False, scale_ylog=False) + result = get_data_ecdf(self.df, scale_eval_log=False, scale_f_log=False) algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() algo1_eaf.sort() np.testing.assert_allclose(algo1_eaf, [0.5, 0.625, 0.75, 0.875, 1]) @@ -24,9 +24,9 @@ def test_basic_ecdf(self): algo2_eaf.sort() np.testing.assert_allclose(algo2_eaf, [0, 0.125, 0.25, 0.375, 0.5]) - def test_ecdf_with_custom_x_values(self): - x_values = [2, 4] - result = get_data_ecdf(self.df, x_values=x_values, scale_xlog=False, scale_ylog=False) + def test_ecdf_with_custom_eval_values(self): + eval_values = [2, 4] + result = get_data_ecdf(self.df, eval_values=eval_values, scale_eval_log=False, scale_f_log=False) algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() algo1_eaf.sort() np.testing.assert_allclose(algo1_eaf, [2/3, 1]) @@ -47,7 +47,7 @@ def test_ecdf_with_maximization(self): def test_ecdf_with_custom_bounds(self): - result = get_data_ecdf(self.df, y_min=0, y_max=100, scale_xlog=False, scale_ylog=False) + result = get_data_ecdf(self.df, f_min=0, f_max=100, scale_eval_log=False, scale_f_log=False) algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() algo1_eaf.sort() np.testing.assert_allclose(algo1_eaf, [90/100, 92/100, 94/100, 96/100, 98/100]) @@ -56,8 +56,8 @@ def test_ecdf_with_custom_bounds(self): algo2_eaf.sort() np.testing.assert_allclose(algo2_eaf, [82/100, 84/100, 86/100, 88/100, 90/100]) - def test_ecdf_with_x_min_x_max(self): - result = get_data_ecdf(self.df, x_min=2, x_max=4, scale_xlog=False, scale_ylog=False) + def test_ecdf_with_eval_min_eval_max(self): + result = get_data_ecdf(self.df, eval_min=2, eval_max=4, scale_eval_log=False, scale_f_log=False) algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() algo1_eaf.sort() np.testing.assert_allclose(algo1_eaf, [2/3, 5/6, 1]) @@ -67,7 +67,7 @@ def test_ecdf_with_x_min_x_max(self): np.testing.assert_allclose(algo2_eaf, [0, 1/6, 1/3]) def test_basic_ecdf_turbo(self): - result = get_data_ecdf(self.df, scale_xlog=False, scale_ylog=False, turbo=True) + result = get_data_ecdf(self.df, scale_eval_log=False, scale_f_log=False, turbo=True) algo1_eaf = result[result["algorithm_name"] == "algo1"]["eaf"].to_numpy() algo1_eaf.sort() np.testing.assert_allclose(algo1_eaf, [0.5, 0.625, 0.75, 0.875, 1]) diff --git a/tests/test_metrics/test_fixed_budget.py b/tests/test_metrics/test_fixed_budget.py index 2939826..d78c4ba 100644 --- a/tests/test_metrics/test_fixed_budget.py +++ b/tests/test_metrics/test_fixed_budget.py @@ -44,9 +44,9 @@ def test_maximization(self): result = aggregate_convergence(self.df, maximization=True, return_as_pandas=True) self.assertIn("mean", result.columns) - def test_x_min_x_max(self): + def test_eval_min_eval_max(self): # Limit to a subset of evaluations - result = aggregate_convergence(self.df, x_min=2, x_max=3, return_as_pandas=True) + result = aggregate_convergence(self.df, eval_min=2, eval_max=3, return_as_pandas=True) self.assertTrue((result["evaluations"] >= 2).all()) self.assertTrue((result["evaluations"] <= 3).all()) @@ -57,7 +57,7 @@ def test_return_polars(self): def test_free_variables(self): # Use a different free variable df = self.df.with_columns(pl.lit("foo").alias("other_var")) - result = aggregate_convergence(df, free_variables=["other_var"], return_as_pandas=True) + result = aggregate_convergence(df, free_vars=["other_var"], return_as_pandas=True) self.assertIn("other_var", result.columns) def test_empty_data(self): diff --git a/tests/test_metrics/test_fixed_target.py b/tests/test_metrics/test_fixed_target.py index 16e3311..10a968a 100644 --- a/tests/test_metrics/test_fixed_target.py +++ b/tests/test_metrics/test_fixed_target.py @@ -73,7 +73,7 @@ def test_with_f_min_f_max(self): self.assertTrue(result["raw_y"].max() <= 0.5) def test_with_different_free_variables(self): - result = aggregate_running_time(self.df, free_variables=["algorithm_name", "data_id"], return_as_pandas=False) + result = aggregate_running_time(self.df, free_vars=["algorithm_name", "data_id"], return_as_pandas=False) self.assertIn("algorithm_name", result.columns) self.assertIn("data_id", result.columns) diff --git a/tests/test_metrics/test_multi_objective.py b/tests/test_metrics/test_multi_objective.py new file mode 100644 index 0000000..aa72b77 --- /dev/null +++ b/tests/test_metrics/test_multi_objective.py @@ -0,0 +1,165 @@ +import unittest +from iohinspector.indicators.anytime import HyperVolume, Epsilon, IGDPlus +import polars as pl +import pandas as pd +import numpy as np +from iohinspector.metrics.multi_objective import ( + get_pareto_front_2d, + get_indicator_over_time_data +) + + +class TestGetParetoFront2D(unittest.TestCase): + def setUp(self): + self.df = pl.DataFrame({ + # For minimization, Pareto front = non-dominated points with lowest values in both objectives + # A: Only (0.1, 0.9) is non-dominated for A + # B: (0.2, 0.8) and (0.4, 0.6) are non-dominated for B + # C: (0.3, 0.7), (0.6, 0.4), (0.7, 0.3) are all non-dominated for C + "raw_y": [0.1, 0.5, 0.9, 0.2, 0.5, 0.9, 0.3, 0.6, 0.9], + "F2": [0.2, 0.5, 0.8, 0.8, 0.2, 0.9, 0.7, 0.4, 0.1], + "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], + "evaluations": [1, 2, 3, 1, 2, 3, 1, 2, 3], + "data_id": [1, 1, 1, 2, 2, 2, 3, 3, 3] + }) + + + def test_basic_call(self): + result = get_pareto_front_2d( + self.df, + return_as_pandas=False + ) + self.assertIn("final_nondominated", result.columns) + + expected = { + ("A", 0.1, 0.2): True, + ("B", 0.2, 0.8): True, + ("B", 0.5, 0.2): True, + ("C", 0.3, 0.7): True, + ("C", 0.6, 0.4): True, + ("C", 0.9, 0.1): True, + } + for row in result.iter_rows(named=True): + key = (row["algorithm_name"], row["raw_y"], row["F2"]) + self.assertEqual(row["final_nondominated"], expected[key]) + + + def test_custom_obj_vars(self): + # Test with custom objective variable names + df_custom = self.df.rename({"raw_y": "obj1", "F2": "obj2"}) + result = get_pareto_front_2d( + df_custom, + obj1_var="obj1", + obj2_var="obj2", + return_as_pandas=False + ) + self.assertIn("final_nondominated", result.columns) + # Check that the correct points are marked as non-dominated for each algorithm, point by point + expected = { + ("A", 0.1, 0.2): True, + ("B", 0.2, 0.8): True, + ("B", 0.5, 0.2): True, + ("C", 0.3, 0.7): True, + ("C", 0.6, 0.4): True, + ("C", 0.9, 0.1): True, + } + for row in result.iter_rows(named=True): + key = (row["algorithm_name"], row["obj1"], row["obj2"]) + self.assertEqual(row["final_nondominated"], expected[key]) + + +class TestGetIndicatorOverTimeData(unittest.TestCase): + def setUp(self): + # Minimal DataFrame with two objectives and a single algorithm + # All points belong to algorithm "A" with 10 evaluations + # The points are constructed to simulate a progression towards the Pareto front + self.df = pl.DataFrame({ + "raw_y": [0.9, 0.7, 0.5, 0.3, 0.1], + "F2": [0.8, 0.6, 0.4, 0.2, 0.1], + "algorithm_name": ["A"] * 5, + "evaluations": [1,10,100, 1000, 10000], + "data_id": [1] * 5 + }) + # Create a dict mapping evaluation to (raw_y, F2) point + self.eval_points = dict(zip(self.df["evaluations"], zip(self.df["raw_y"], self.df["F2"]))) + + def test_plot_indicator_over_time_hypervolume(self): + # Use a simple indicator and check output DataFrame + indicator = HyperVolume(reference_point=[1.0, 1.0]) + result = get_indicator_over_time_data( + self.df, + indicator=indicator, + eval_steps=5, + eval_min=1, + eval_max=10_000, + scale_eval_log=True, + obj_vars=["raw_y", "F2"], + ) + # Make a dict of {evaluation: hypervolume} + hv_dict = dict(zip(result["evaluations"], result["HyperVolume"])) + + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + hv = (1.0 - point[0]) * (1.0 - point[1]) # Since we minimize both objectives + self.assertAlmostEqual(hv_dict[eval], hv, places=5) + + def test_plot_indicator_over_time_epsilon_additive(self): + # Use a simple indicator and check output DataFrame + indicator = Epsilon(reference_point=[1.0, 1.0]) + result = get_indicator_over_time_data( + self.df, + indicator=indicator, + eval_steps=5, + eval_min=1, + eval_max=10_000, + scale_eval_log=True, + obj_vars=["raw_y", "F2"], + ) + # Make a dict of {evaluation: hypervolume} + ae = dict(zip(result["evaluations"], result["Epsilon_Additive"])) + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + eps = max(point[0]-1.0, point[1]-1.0) # Since we minimize both objectives + self.assertAlmostEqual(ae[eval], eps, places=5) + + + def test_plot_indicator_over_time_epsilon_multiplicative(self): + # Use a simple indicator and check output DataFrame + indicator = Epsilon(reference_point=[1.0, 1.0], version="multiplicative") + result = get_indicator_over_time_data( + self.df, + indicator=indicator, + eval_steps=5, + eval_min=1, + eval_max=10_000, + scale_eval_log=True, + obj_vars=["raw_y", "F2"], + ) + # Make a dict of {evaluation: hypervolume} + ae = dict(zip(result["evaluations"], result["Epsilon_Mult"])) + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + eps = max(point[0]/1.0, point[1]/1.0) # Since we minimize both objectives + self.assertAlmostEqual(ae[eval], eps, places=5) + + def test_plot_indicator_over_time_igd_plus(self): + # Use a simple indicator and check output DataFrame + indicator = IGDPlus(reference_set=[[0.0, 0.0]]) + result = get_indicator_over_time_data( + self.df, + indicator=indicator, + eval_steps=5, + eval_min=1, + eval_max=10_000, + scale_eval_log=True, + obj_vars=["raw_y", "F2"], + ) + # Make a dict of {evaluation: hypervolume} + ae = dict(zip(result["evaluations"], result["IGD+"])) + for eval in [1,10,100,1000,10000]: + point = self.eval_points[eval] + idg_plus = np.sqrt((point[0]-0.0)**2 + (point[1]-0.0)**2) # Since we minimize both objectives + self.assertAlmostEqual(ae[eval], idg_plus, places=5) + +if __name__ == "__main__": + unittest.main() diff --git a/tests/test_metrics/test_ranking.py b/tests/test_metrics/test_ranking.py index dc7bdb1..b845722 100644 --- a/tests/test_metrics/test_ranking.py +++ b/tests/test_metrics/test_ranking.py @@ -2,13 +2,14 @@ import numpy as np import polars as pl import pandas as pd -from iohinspector.metrics import get_tournament_ratings +from iohinspector.metrics import get_tournament_ratings, get_robustrank_over_time, get_robustrank_changes +from iohinspector.indicators import HyperVolume class TestGetTournamentRatings(unittest.TestCase): def setUp(self): # Create a simple polars DataFrame for testing self.data = pl.DataFrame({ - "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], + "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], "function_name": ["f1", "f2", "f3", "f1", "f2", "f3", "f1", "f2", "f3"], "raw_y": [1.0, 2.0, 1.7, 1.5, 2.8, 2.1, 0.9, 0.5, 1.6] }) @@ -47,5 +48,128 @@ def test_single_function(self): self.assertTrue(set(result["algorithm_name"]) == {"A", "B"}) +class TestGetRobustRankOverTime(unittest.TestCase): + def setUp(self): + # Create simple polars DataFrame with different targets and ranks + self.data = pl.DataFrame({ + "algorithm_name": ["A"] * 9 + ["B"] * 9 + ["C"] * 9, + "evaluations": [1, 10, 100] * 9, + "f1": [ + # A: best at eval 1, B: best at eval 10, A: best at eval 100 (for run 1) + 0.8, 1.5, 0.7, # A, run 1 + 1.0, 1.6, 0.9, # A, run 2 + 0.9, 1.4, 0.8, # A, run 3 + + 1.0, 0.7, 1.2, # B, run 1 + 1.2, 0.8, 1.3, # B, run 2 + 1.1, 0.6, 1.1, # B, run 3 + + 1.5, 1.5, 0.1, # C, run 1 + 1.6, 1.6, 0.2, # C, run 2 + 1.4, 1.4, 0.3 # C, run 3 + ], + "f2": [ + 1.0, 2.0, 0.9, # A, run 1 + 1.2, 2.1, 1.1, # A, run 2 + 1.1, 2.2, 1.0, # A, run 3 + + 1.3, 0.8, 1.4, # B, run 1 + 1.5, 0.9, 1.5, # B, run 2 + 1.4, 0.7, 1.3, # B, run 3 + + 2.0, 2.0, 0.1, # C, run 1 + 2.1, 2.1, 0.2, # C, run 2 + 1.9, 1.9, 0.3 # C, run 3 + ], + "f3": [ + 2.0, 3.0, 1.8, # A, run 1 + 2.2, 3.1, 2.0, # A, run 2 + 2.1, 3.2, 1.9, # A, run 3 + + 2.3, 1.2, 2.4, # B, run 1 + 2.5, 1.3, 2.5, # B, run 2 + 2.4, 1.1, 2.3, # B, run 3 + + 3.0, 3.0, 0.1, # C, run 1 + 3.1, 3.1, 0.3, # C, run 2 + 2.9, 2.9, 0.2 # C, run 3 + ], + "data_id": [1]*3 + [2]*3 + [3]*3 + [4]*3 + [5]*3 + [6]*3 + [7]*3 + [8]*3 + [9]*3, + "run_id": [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3, + }) + + def test_basic(self): + evals = [1, 10, 100] + comparison, benchmark = get_robustrank_over_time( + self.data, + obj_vars=["f1","f2", "f3"], + evals=evals, + indicator=HyperVolume(reference_point=[5.0,5.0,5.0]), + ) + + +class TestGetRobustRankChanges(unittest.TestCase): + def setUp(self): + self.data = pl.DataFrame({ + "algorithm_name": ["A"] * 9 + ["B"] * 9 + ["C"] * 9, + "evaluations": [1, 10, 100] * 9, + "f1": [ + # A: best at eval 1, B: best at eval 10, A: best at eval 100 (for run 1) + 0.8, 1.5, 0.7, # A, run 1 + 1.0, 1.6, 0.9, # A, run 2 + 0.9, 1.4, 0.8, # A, run 3 + + 1.0, 0.7, 1.2, # B, run 1 + 1.2, 0.8, 1.3, # B, run 2 + 1.1, 0.6, 1.1, # B, run 3 + + 1.5, 1.5, 0.1, # C, run 1 + 1.6, 1.6, 0.2, # C, run 2 + 1.4, 1.4, 0.3 # C, run 3 + ], + "f2": [ + 1.0, 2.0, 0.9, # A, run 1 + 1.2, 2.1, 1.1, # A, run 2 + 1.1, 2.2, 1.0, # A, run 3 + + 1.3, 0.8, 1.4, # B, run 1 + 1.5, 0.9, 1.5, # B, run 2 + 1.4, 0.7, 1.3, # B, run 3 + + 2.0, 2.0, 0.1, # C, run 1 + 2.1, 2.1, 0.2, # C, run 2 + 1.9, 1.9, 0.3 # C, run 3 + ], + "f3": [ + 2.0, 3.0, 1.8, # A, run 1 + 2.2, 3.1, 2.0, # A, run 2 + 2.1, 3.2, 1.9, # A, run 3 + + 2.3, 1.2, 2.4, # B, run 1 + 2.5, 1.3, 2.5, # B, run 2 + 2.4, 1.1, 2.3, # B, run 3 + + 3.0, 3.0, 0.1, # C, run 1 + 3.1, 3.1, 0.3, # C, run 2 + 2.9, 2.9, 0.2 # C, run 3 + ], + "data_id": [1]*3 + [2]*3 + [3]*3 + [4]*3 + [5]*3 + [6]*3 + [7]*3 + [8]*3 + [9]*3, + "run_id": [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3, + }) + + def test_basic(self): + evals = [1, 10, 100] + result = get_robustrank_changes( + self.data, + obj_vars=["f1","f2", "f3"], + evals=evals, + indicator=HyperVolume(reference_point=[5.0,5.0,5.0]), + + ) + for eval in evals: + self.assertIn(str(eval), result.keys()) + + + if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_single_run.py b/tests/test_metrics/test_single_run.py new file mode 100644 index 0000000..ef6369f --- /dev/null +++ b/tests/test_metrics/test_single_run.py @@ -0,0 +1,76 @@ +import unittest +import polars as pl +import numpy as np +import matplotlib.pyplot as plt +from iohinspector.metrics.single_run import get_heatmap_single_run_data + + +class TestPlotHeatmapSingleRun(unittest.TestCase): + def setUp(self): + self.data = pl.DataFrame({ + "data_id": [1]*5, + "evaluations": [1,2,3,4,5], + "x1": np.linspace(-5, 5, 5), + "x2": np.linspace(-5, 5, 5)[::-1], + }) + self.vars = ["x1", "x2"] + self.var_mins = np.array([-5, -5]) + self.var_maxs = np.array([5, 5]) + + def test_basic(self): + dt_plot = get_heatmap_single_run_data( + data=self.data, + vars=self.vars, + eval_var="evaluations", + var_mins=self.var_mins, + var_maxs=self.var_maxs, + ) + self.assertEqual(dt_plot.shape, (2, 5)) + self.assertAlmostEqual(dt_plot.values.min(), 0) + self.assertAlmostEqual(dt_plot.values.max(), 1) + self.assertTrue(np.all((dt_plot.values >= 0) & (dt_plot.values <= 1))) + + def test_asserts_on_multiple_data_ids(self): + data = pl.DataFrame({ + "data_id": [1, 2], + "evaluations": [1, 2], + "x1": [0, 1], + }) + with self.assertRaises(AssertionError): + get_heatmap_single_run_data(data, ["x1"]) + + def test_single_variable(self): + data = pl.DataFrame({ + "data_id": [1]*3, + "evaluations": [1, 2, 3], + "x1": [-5, 0, 5], + }) + dt_plot = get_heatmap_single_run_data( + data=data, + vars=["x1"], + eval_var="evaluations", + var_mins=[-5], + var_maxs=[5], + ) + self.assertEqual(dt_plot.shape, (1, 3)) + np.testing.assert_allclose(dt_plot.values, [[0, 0.5, 1]]) + + def test_non_default_eval_col(self): + data = pl.DataFrame({ + "data_id": [1]*4, + "evals": [1, 2, 3, 4], + "x1": [0, 1, 2, 3], + "x2": [3, 2, 1, 0], + }) + dt_plot = get_heatmap_single_run_data( + data=data, + vars=["x1", "x2"], + eval_var="evals", + var_mins=[0, 0], + var_maxs=[3, 3], + ) + self.assertEqual(dt_plot.shape, (2, 4)) + + +if __name__ == "__main__": + unittest.main() \ No newline at end of file diff --git a/tests/test_metrics/test_trajectory.py b/tests/test_metrics/test_trajectory.py index bce92c2..a775ac6 100644 --- a/tests/test_metrics/test_trajectory.py +++ b/tests/test_metrics/test_trajectory.py @@ -14,7 +14,7 @@ def setUp(self): }) def test_basic_trajectory(self): - result = get_trajectory(self.data) + result = get_trajectory(self.data, return_as_pandas=False) self.assertIsInstance(result, pl.DataFrame) # Should have as many rows as input (since all evaluations present) self.assertEqual(result.shape[0], 40) # 2 algorithms * 20 evaluations @@ -31,19 +31,19 @@ def test_basic_trajectory(self): def test_traj_length(self): # Only first two evaluations should be present - result = get_trajectory(self.data, traj_length=1) + result = get_trajectory(self.data, traj_length=1, return_as_pandas=False) for algo in self.data["algorithm_name"].unique(): evals = result.filter(pl.col("algorithm_name") == algo)["evaluations"].to_list() self.assertEqual(set(evals), set(range(1, 3))) - result = get_trajectory(self.data, traj_length=10) + result = get_trajectory(self.data, traj_length=10, return_as_pandas=False) for algo in self.data["algorithm_name"].unique(): evals = result.filter(pl.col("algorithm_name") == algo)["evaluations"].to_list() self.assertEqual(set(evals), set(range(1, 12))) def test_min_fevals(self): # Start from evaluation 2 - result = get_trajectory(self.data, min_fevals=2) + result = get_trajectory(self.data, min_fevals=2, return_as_pandas=False) for algo in self.data["algorithm_name"].unique(): evals = result.filter(pl.col("algorithm_name") == algo)["evaluations"].to_list() self.assertEqual(set(evals), set(range(2, 21))) @@ -51,12 +51,12 @@ def test_min_fevals(self): def test_custom_free_variables(self): # Use only data_id as free variable - result = get_trajectory(self.data, free_variables=[]) + result = get_trajectory(self.data, free_variables=[], return_as_pandas=False) self.assertIn("data_id", result.columns) self.assertIn("raw_y", result.columns) def test_maximization(self): - result = get_trajectory(self.data, maximization=True) + result = get_trajectory(self.data, maximization=True, return_as_pandas=False) for algo in self.data["algorithm_name"].unique(): raw_y_values = result.filter(pl.col("algorithm_name") == algo).sort("evaluations")["raw_y"].to_list() diff --git a/tests/test_metrics/test_utils.py b/tests/test_metrics/test_utils.py index 856dffb..b22f3cc 100644 --- a/tests/test_metrics/test_utils.py +++ b/tests/test_metrics/test_utils.py @@ -86,25 +86,25 @@ def setUp(self): }) def test_basic_normalization(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"]) + normed = normalize_objectives(self.df, obj_vars=["raw_y"]) self.assertIn("ert", normed.columns) arr = normed["ert"].to_numpy() np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) def test_maximization(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"], maximize=True) + normed = normalize_objectives(self.df, obj_vars=["raw_y"], maximize=True) arr = normed["ert"].to_numpy() np.testing.assert_allclose(arr, [0, 0.25, 0.5, 0.75, 1]) def test_bounds(self): bounds = {"raw_y": (0, 10)} - normed = normalize_objectives(self.df, obj_cols=["raw_y"], bounds=bounds) + normed = normalize_objectives(self.df, obj_vars=["raw_y"], bounds=bounds) arr = normed["ert"].to_numpy() np.testing.assert_allclose(arr, [0.9, 0.8, 0.7, 0.6, 0.5]) def test_log_scale(self): df = pl.DataFrame({"raw_y": [1, 10, 100, 1000, 10000]}) - normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) + normed = normalize_objectives(df, obj_vars=["raw_y"], log_scale=True) arr = normed["ert"].to_numpy() np.testing.assert_allclose(arr, [1, 0.75, 0.5, 0.25, 0]) @@ -112,7 +112,7 @@ def test_log_scale_with_zero_warns(self): df = pl.DataFrame({"raw_y": [0, 1, 10]}) with warnings.catch_warnings(record=True) as w: warnings.simplefilter("always") - normed = normalize_objectives(df, obj_cols=["raw_y"], log_scale=True) + normed = normalize_objectives(df, obj_vars=["raw_y"], log_scale=True) self.assertTrue(any("Lower bound" in str(warn.message) for warn in w)) arr = normed["ert"].to_numpy() self.assertTrue(np.all((arr >= 0) & (arr <= 1))) @@ -122,7 +122,7 @@ def test_multiple_objectives(self): "raw_y": [1, 2, 3], "other": [10, 20, 30] }) - normed = normalize_objectives(df, obj_cols=["raw_y", "other"]) + normed = normalize_objectives(df, obj_vars=["raw_y", "other"]) arr_raw_y = normed["ert_raw_y"].to_numpy() np.testing.assert_allclose(arr_raw_y, [1.0, 0.5, 0.0]) arr_other = normed["ert_other"].to_numpy() @@ -130,14 +130,14 @@ def test_multiple_objectives(self): def test_column_prefix(self): - normed = normalize_objectives(self.df, obj_cols=["raw_y"], prefix="normed") + normed = normalize_objectives(self.df, obj_vars=["raw_y"], prefix="normed") self.assertIn("normed", normed.columns) def test_dict_log_and_maximize(self): df = pl.DataFrame({"a": [1, 10, 100], "b": [3, 2, 1]}) normed = normalize_objectives( df, - obj_cols=["a", "b"], + obj_vars=["a", "b"], log_scale={"a": True, "b": False}, maximize={"a": True, "b": False} ) @@ -152,7 +152,7 @@ def test_add_normalized_objectives_basic(self): "raw_y": [1.0, 2.0, 3.0, 4.0, 5.0], "other": [10, 20, 30, 40, 50] }) - normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"]) + normed = add_normalized_objectives(df, obj_vars=["raw_y", "other"]) self.assertIn("obj1", normed.columns) self.assertIn("obj2", normed.columns) arr_obj1 = normed["obj1"].to_numpy() @@ -165,9 +165,9 @@ def test_add_normalized_objectives_with_bounds(self): "raw_y": [1.0, 2.0, 3.0], "other": [10, 20, 30] }) - min_vals = pl.DataFrame({"raw_y": [0.0], "other": [0]}) - max_vals = pl.DataFrame({"raw_y": [10.0], "other": [40]}) - normed = add_normalized_objectives(df, obj_cols=["raw_y", "other"], min_vals=min_vals, max_vals=max_vals) + min_obj = pl.DataFrame({"raw_y": [0.0], "other": [0]}) + max_obj = pl.DataFrame({"raw_y": [10.0], "other": [40]}) + normed = add_normalized_objectives(df, obj_vars=["raw_y", "other"], min_obj=min_obj, max_obj=max_obj) arr_obj1 = normed["obj1"].to_numpy() arr_obj2 = normed["obj2"].to_numpy() np.testing.assert_allclose(arr_obj1, [0.1, 0.2, 0.3]) @@ -175,14 +175,14 @@ def test_add_normalized_objectives_with_bounds(self): def test_add_normalized_objectives_single_objective(self): df = pl.DataFrame({"raw_y": [1, 2, 3]}) - normed = add_normalized_objectives(df, obj_cols=["raw_y"]) + normed = add_normalized_objectives(df, obj_vars=["raw_y"]) self.assertIn("obj", normed.columns) arr = normed["obj"].to_numpy() np.testing.assert_allclose(arr, [0, 0.5, 1]) def test_add_normalized_objectives_no_min_max(self): df = pl.DataFrame({"raw_y": [5, 10, 15]}) - normed = add_normalized_objectives(df, obj_cols=["raw_y"]) + normed = add_normalized_objectives(df, obj_vars=["raw_y"]) arr = normed["obj"].to_numpy() np.testing.assert_allclose(arr, [0, 0.5, 1]) @@ -225,9 +225,9 @@ def test_transform_fval_custom_bounds(self): expected = [1 - (x / 10) for x in [0, 5, 10]] np.testing.assert_allclose(arr, expected) - def test_transform_fval_column_name(self): + def test_transform_fval_varumn_name(self): df = pl.DataFrame({"score": [1, 10, 100]}) - res = transform_fval(df, lb=1, ub=100, scale_log=True, fval_col="score") + res = transform_fval(df, lb=1, ub=100, scale_log=True, fval_var="score") arr = res["eaf"].to_numpy() expected = [1- (np.log10(x) - np.log10(1)) / (np.log10(100) - np.log10(1)) for x in [1, 10, 100]] np.testing.assert_allclose(arr, expected) diff --git a/tests/test_plots/test_attractor_network.py b/tests/test_plots/test_attractor_network.py index 4d95524..4069c6d 100644 --- a/tests/test_plots/test_attractor_network.py +++ b/tests/test_plots/test_attractor_network.py @@ -1,24 +1,34 @@ import unittest import polars as pl import numpy as np +import matplotlib from iohinspector.plots import plot_attractor_network -class TestGetAttractorNetwork(unittest.TestCase): - def test_basic(self): - data = pl.DataFrame({ +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + + +class TestPlotAttractorNetwork(unittest.TestCase): + def setUp(self): + self.data = pl.DataFrame({ "x1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "x2": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12], "raw_y": [35, 33, 31, 29, 27, 23, 18, 16, 14, 12, 10, 9, 6], "evaluations": [1,42, 81,121,161,201,241,281,321,361,401,442,481], "data_id": [1]*13 }) - plot_attractor_network( - data, + + def test_basic_call_returns_axes_and_data(self): + ax, nodes, edges = plot_attractor_network( + self.data, coord_vars=["x1", "x2"], fval_var="raw_y", eval_var="evaluations", ) - + + self.assertIsNotNone(ax) + self.assertIsNotNone(nodes) + self.assertIsNotNone(edges) diff --git a/tests/test_plots/test_eaf.py b/tests/test_plots/test_eaf.py index 83a1c25..29c27bd 100644 --- a/tests/test_plots/test_eaf.py +++ b/tests/test_plots/test_eaf.py @@ -10,41 +10,50 @@ class TestPlotEAFSingleObjective(unittest.TestCase): - def test_basic_call_returns_dataframe(self): - df = pl.DataFrame({ + def setUp(self): + self.data = pl.DataFrame({ "raw_y": [10, 8, 6, 20, 18, 16], "evaluations": [1, 2, 5, 1, 4, 5], "data_id": [1, 1, 1, 2, 2, 2] }) - dt = plot_eaf_single_objective(df) - self.assertTrue(hasattr(dt, "columns")) - self.assertIn("evaluations", dt.columns) - self.assertIn("raw_y", dt.columns) + + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_eaf_single_objective(self.data) + self.assertIsNotNone(ax) + self.assertIsNotNone(data) + class TestPlotEAFPareto(unittest.TestCase): - def test_basic_call_returns_dataframe(self): - df = pl.DataFrame({ + def setUp(self): + self.data = pl.DataFrame({ "x": [1, 2, 3, 1, 2, 3], "y": [10, 8, 6, 20, 18, 16], "data_id": [1, 1, 1, 2, 2, 2] }) - plot_eaf_pareto(df, x_column="x", y_column="y") + + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_eaf_pareto(self.data, obj1_var="x", obj2_var="y") + self.assertIsNotNone(ax) + self.assertIsNotNone(data) class TestPlotEAFDiffs(unittest.TestCase): - def test_basic_call_returns_dataframe(self): - df1 = pl.DataFrame({ + def setUp(self): + self.data1 = pl.DataFrame({ "x": [1, 2, 3], "y": [10, 8, 6], "data_id": [1, 1, 1] }) - df2 = pl.DataFrame({ + self.data2 = pl.DataFrame({ "x": [1, 2, 3], "y": [9, 7, 5], "data_id": [2, 2, 2] }) - plot_eaf_diffs(df1, df2, x_column="x", y_column="y") + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_eaf_diffs(self.data1, self.data2, obj1_var="x", obj2_var="y") + self.assertIsNotNone(ax) + self.assertIsNotNone(data) if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_ecdf.py b/tests/test_plots/test_ecdf.py index 129d40b..124ef21 100644 --- a/tests/test_plots/test_ecdf.py +++ b/tests/test_plots/test_ecdf.py @@ -1,31 +1,30 @@ import unittest import polars as pl +import matplotlib import os from iohinspector.plots import plot_ecdf from iohinspector.manager import DataManager +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + BASE_DIR = os.path.dirname(__file__) DATA_DIR = os.path.realpath(os.path.join(BASE_DIR, "..", "test_data")) -class TestECDF(unittest.TestCase): + +class TestPlotECDF(unittest.TestCase): def setUp(self): data_folders = [os.path.join(DATA_DIR, x) for x in sorted(os.listdir(DATA_DIR))] data_dir = data_folders[0] manager = DataManager() manager.add_folder(data_dir) - self.df = manager.load(monotonic=True, include_meta_data=True) + self.data = manager.load(monotonic=True, include_meta_data=True) - def test_basic_call_returns_dataframe(self): - dt = plot_ecdf(self.df) - # Check that the result is a DataFrame and has expected columns - self.assertTrue(hasattr(dt, "columns")) - self.assertIn("evaluations", dt.columns) - self.assertIn("eaf", dt.columns) - sorted_dt = dt.sort_values("evaluations", ascending=True) - values = sorted_dt["eaf"].to_numpy() - # Check that as evaluations increases, eaf does not increase (i.e., it decreases or stays the same) - self.assertTrue(all(x <= y for x, y in zip(values, values[1:])), "eaf should increase or stay the same as evaluations increases") + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_ecdf(self.data) + self.assertIsNotNone(ax) + self.assertIsNotNone(data) if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_fixed_budget.py b/tests/test_plots/test_fixed_budget.py index 744aeeb..283b965 100644 --- a/tests/test_plots/test_fixed_budget.py +++ b/tests/test_plots/test_fixed_budget.py @@ -1,33 +1,30 @@ import unittest import polars as pl +import matplotlib import os from iohinspector.plots import plot_single_function_fixed_budget from iohinspector.manager import DataManager +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + BASE_DIR = os.path.dirname(__file__) DATA_DIR = os.path.realpath(os.path.join(BASE_DIR, "..", "test_data")) -class TestSingleObjectiveFixedBudget(unittest.TestCase): + +class TestPlotSingleFunctionFixedBudget(unittest.TestCase): def setUp(self): data_folders = [os.path.join(DATA_DIR, x) for x in sorted(os.listdir(DATA_DIR))] data_dir = data_folders[0] manager = DataManager() manager.add_folder(data_dir) - self.df = manager.load(monotonic=True, include_meta_data=True) - - def test_basic_call_returns_dataframe(self): - dt = plot_single_function_fixed_budget(self.df) - # Check that the result is a DataFrame and has expected columns - self.assertTrue(hasattr(dt, "columns")) - self.assertIn("value", dt.columns) - self.assertIn("variable", dt.columns) - self.assertIn("evaluations", dt.columns) - self.assertIn("algorithm_name", dt.columns) - sorted_dt = dt.sort_values("evaluations", ascending=True) - values = sorted_dt["value"].to_numpy() - # Check that as evaluations increases, value does not increase (i.e., it decreases or stays the same) - self.assertTrue(all(x >= y for x, y in zip(values, values[1:])), "value should decrease or stay the same as evaluations increases") + self.data = manager.load(monotonic=True, include_meta_data=True) + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_single_function_fixed_budget(self.data) + self.assertIsNotNone(ax) + self.assertIsNotNone(data) + if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_fixed_target.py b/tests/test_plots/test_fixed_target.py index d35272e..95c2c6f 100644 --- a/tests/test_plots/test_fixed_target.py +++ b/tests/test_plots/test_fixed_target.py @@ -1,33 +1,30 @@ import unittest import polars as pl +import matplotlib import os from iohinspector.plots import plot_single_function_fixed_target from iohinspector.manager import DataManager +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + BASE_DIR = os.path.dirname(__file__) DATA_DIR = os.path.realpath(os.path.join(BASE_DIR, "..", "test_data")) -class TestSingleObjectiveFixedTarget(unittest.TestCase): + +class TestPlotSingleFunctionFixedTarget(unittest.TestCase): def setUp(self): data_folders = [os.path.join(DATA_DIR, x) for x in sorted(os.listdir(DATA_DIR))] data_dir = data_folders[0] manager = DataManager() manager.add_folder(data_dir) - self.df = manager.load(monotonic=True, include_meta_data=True) + self.data = manager.load(monotonic=True, include_meta_data=True) - def test_basic_call_returns_dataframe(self): - dt = plot_single_function_fixed_target(self.df) - # Check that the result is a DataFrame and has expected columns - self.assertTrue(hasattr(dt, "columns")) - self.assertIn("value", dt.columns) - self.assertIn("variable", dt.columns) - self.assertIn("raw_y", dt.columns) - self.assertIn("algorithm_name", dt.columns) - sorted_dt = dt.sort_values("raw_y", ascending=True) - values = sorted_dt["value"].to_numpy() - # Check that as raw_y decreases, value does not increase (i.e., it decreases or stays the same) - self.assertTrue(all(x >= y for x, y in zip(values, values[1:])), "value should decrease or stay the same as raw_y decreases") + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_single_function_fixed_target(self.data) + self.assertIsNotNone(ax) + self.assertIsNotNone(data) if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_multi_objective.py b/tests/test_plots/test_multi_objective.py index c9c90e9..16d9423 100644 --- a/tests/test_plots/test_multi_objective.py +++ b/tests/test_plots/test_multi_objective.py @@ -13,18 +13,7 @@ class TestPlotParetoFronts2D(unittest.TestCase): def setUp(self): - # Minimal DataFrame with two objectives and a category - # All algorithms with 3 elements in final Pareto, different data_id for each algo - # Construct the DataFrame so that: - # - Algorithm A has only 1 point on the Pareto front - # - Algorithm B has 2 points on the Pareto front - # - Algorithm C has 3 points on the Pareto front - # Both objectives are to be minimized - self.df = pl.DataFrame({ - # For minimization, Pareto front = non-dominated points with lowest values in both objectives - # A: Only (0.1, 0.9) is non-dominated for A - # B: (0.2, 0.8) and (0.4, 0.6) are non-dominated for B - # C: (0.3, 0.7), (0.6, 0.4), (0.7, 0.3) are all non-dominated for C + self.data = pl.DataFrame({ "raw_y": [0.1, 0.5, 0.9, 0.2, 0.5, 0.9, 0.3, 0.6, 0.9], "F2": [0.2, 0.5, 0.8, 0.8, 0.2, 0.9, 0.7, 0.4, 0.1], "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], @@ -32,61 +21,14 @@ def setUp(self): "data_id": [1, 1, 1, 2, 2, 2, 3, 3, 3] }) - def test_basic_call(self): - result = plot_paretofronts_2d( - self.df, - - ) - # Check that the correct points are marked as non-dominated for each algorithm, point by point - # Instead of relying on order, check by (algorithm_name, raw_y, F2) - # Define expected non-dominated points - expected = { - ("A", 0.1, 0.2): True, - ("A", 0.5, 0.5): False, - ("A", 0.9, 0.8): False, - ("B", 0.2, 0.8): True, - ("B", 0.5, 0.2): True, - ("B", 0.9, 0.9): False, - ("C", 0.3, 0.7): True, - ("C", 0.6, 0.4): True, - ("C", 0.9, 0.1): True, - } - for row in result.iter_rows(named=True): - key = (row["algorithm_name"], row["raw_y"], row["F2"]) - self.assertEqual(row["final_nondominated"], expected[key]) - - - def test_custom_obj_vars(self): - # Test with custom objective variable names - df_custom = self.df.rename({"raw_y": "obj1", "F2": "obj2"}) - result = plot_paretofronts_2d( - df_custom, - obj_vars=["obj1", "obj2"], - free_var="algorithm_name" - ) - self.assertIn("final_nondominated", result.columns) - # Check that the correct points are marked as non-dominated for each algorithm, point by point - expected = { - ("A", 0.1, 0.2): True, - ("A", 0.5, 0.5): False, - ("A", 0.9, 0.8): False, - ("B", 0.2, 0.8): True, - ("B", 0.5, 0.2): True, - ("B", 0.9, 0.9): False, - ("C", 0.3, 0.7): True, - ("C", 0.6, 0.4): True, - ("C", 0.9, 0.1): True, - } - for row in result.iter_rows(named=True): - key = (row["algorithm_name"], row["obj1"], row["obj2"]) - self.assertEqual(row["final_nondominated"], expected[key]) + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_paretofronts_2d(self.data) + self.assertIsNotNone(ax) + self.assertIsNotNone(data) class TestPlotIndicatorOverTime(unittest.TestCase): def setUp(self): - # Minimal DataFrame with two objectives and a single algorithm - # All points belong to algorithm "A" with 10 evaluations - # The points are constructed to simulate a progression towards the Pareto front - self.df = pl.DataFrame({ + self.data = pl.DataFrame({ "raw_y": [0.9, 0.7, 0.5, 0.3, 0.1], "F2": [0.8, 0.6, 0.4, 0.2, 0.1], "algorithm_name": ["A"] * 5, @@ -94,94 +36,24 @@ def setUp(self): "data_id": [1] * 5 }) # Create a dict mapping evaluation to (raw_y, F2) point - self.eval_points = dict(zip(self.df["evaluations"], zip(self.df["raw_y"], self.df["F2"]))) + self.eval_points = dict(zip(self.data["evaluations"], zip(self.data["raw_y"], self.data["F2"]))) - def test_plot_indicator_over_time_hypervolume(self): + def test_basic_call_returns_axes_and_data(self): # Use a simple indicator and check output DataFrame indicator = HyperVolume(reference_point=[1.0, 1.0]) - result = plot_indicator_over_time( - self.df, + ax, data = plot_indicator_over_time( + self.data, indicator=indicator, - nr_eval_steps=5, - evals_min=1, - evals_max=10_000, - eval_scale_log=True, - obj_columns=["raw_y", "F2"], - eval_column="evaluations", - free_variable="algorithm_name" - ) - # Make a dict of {evaluation: hypervolume} - hv_dict = dict(zip(result["evaluations"], result["HyperVolume"])) - - for eval in [1,10,100,1000,10000]: - point = self.eval_points[eval] - hv = (1.0 - point[0]) * (1.0 - point[1]) # Since we minimize both objectives - self.assertAlmostEqual(hv_dict[eval], hv, places=5) - - def test_plot_indicator_over_time_epsilon_additive(self): - # Use a simple indicator and check output DataFrame - indicator = Epsilon(reference_point=[1.0, 1.0]) - result = plot_indicator_over_time( - self.df, - indicator=indicator, - nr_eval_steps=5, - evals_min=1, - evals_max=10_000, - eval_scale_log=True, - obj_columns=["raw_y", "F2"], - eval_column="evaluations", - free_variable="algorithm_name" - ) - # Make a dict of {evaluation: hypervolume} - ae = dict(zip(result["evaluations"], result["Epsilon_Additive"])) - for eval in [1,10,100,1000,10000]: - point = self.eval_points[eval] - eps = max(point[0]-1.0, point[1]-1.0) # Since we minimize both objectives - self.assertAlmostEqual(ae[eval], eps, places=5) - - - def test_plot_indicator_over_time_epsilon_multiplicative(self): - # Use a simple indicator and check output DataFrame - indicator = Epsilon(reference_point=[1.0, 1.0], version="multiplicative") - result = plot_indicator_over_time( - self.df, - indicator=indicator, - nr_eval_steps=5, - evals_min=1, - evals_max=10_000, - eval_scale_log=True, - obj_columns=["raw_y", "F2"], - eval_column="evaluations", - free_variable="algorithm_name" - ) - # Make a dict of {evaluation: hypervolume} - ae = dict(zip(result["evaluations"], result["Epsilon_Mult"])) - for eval in [1,10,100,1000,10000]: - point = self.eval_points[eval] - eps = max(point[0]/1.0, point[1]/1.0) # Since we minimize both objectives - self.assertAlmostEqual(ae[eval], eps, places=5) - - def test_plot_indicator_over_time_igd_plus(self): - # Use a simple indicator and check output DataFrame - indicator = IGDPlus(reference_set=[[0.0, 0.0]]) - result = plot_indicator_over_time( - self.df, - indicator=indicator, - nr_eval_steps=5, - evals_min=1, - evals_max=10_000, - eval_scale_log=True, - obj_columns=["raw_y", "F2"], - eval_column="evaluations", - free_variable="algorithm_name" + eval_steps=5, + eval_min=1, + eval_max=10_000, + scale_eval_log=True, + obj_vars=["raw_y", "F2"], + free_var="algorithm_name" ) - # Make a dict of {evaluation: hypervolume} - ae = dict(zip(result["evaluations"], result["IGD+"])) - for eval in [1,10,100,1000,10000]: - point = self.eval_points[eval] - idg_plus = np.sqrt((point[0]-0.0)**2 + (point[1]-0.0)**2) # Since we minimize both objectives - self.assertAlmostEqual(ae[eval], idg_plus, places=5) - + self.assertIsNotNone(ax) + self.assertIsNotNone(data) + if __name__ == "__main__": unittest.main() \ No newline at end of file diff --git a/tests/test_plots/test_ranking.py b/tests/test_plots/test_ranking.py index bf6347c..f8e0880 100644 --- a/tests/test_plots/test_ranking.py +++ b/tests/test_plots/test_ranking.py @@ -1,25 +1,28 @@ import unittest import polars as pl +import matplotlib from iohinspector.plots import plot_robustrank_over_time,plot_tournament_ranking, plot_robustrank_changes from iohinspector.indicators import HyperVolume +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + + class TestPlotTournamentRanking(unittest.TestCase): - def test_basic_call_returns_dataframe(self): - data = pl.DataFrame({ + def setUp(self): + self.data = pl.DataFrame({ "algorithm_name": ["A", "A", "A", "B", "B", "B", "C", "C", "C"], "function_name": ["f1", "f2", "f3", "f1", "f2", "f3", "f1", "f2", "f3"], "raw_y": [1.0, 2.0, 1.7, 1.5, 2.8, 2.1, 0.9, 0.5, 1.6] }) - - dt = plot_tournament_ranking(data) - self.assertTrue(hasattr(dt, "columns")) - self.assertIn("Rating", dt.columns) - self.assertIn("Deviation", dt.columns) - self.assertIn("algorithm_name", dt.columns) + def test_basic_call_returns_axes_and_data(self): + ax, dt = plot_tournament_ranking(self.data) + self.assertIsNotNone(ax) + self.assertIsNotNone(dt) class TestPlotRobustRankOverTime(unittest.TestCase): - def test_basic_call(self): - data = pl.DataFrame({ + def setUp(self): + self.data = pl.DataFrame({ "algorithm_name": ["A"] * 9 + ["B"] * 9 + ["C"] * 9, "evaluations": [1, 10, 100] * 9, "f1": [ @@ -64,20 +67,25 @@ def test_basic_call(self): ], "data_id": [1]*3 + [2]*3 + [3]*3 + [4]*3 + [5]*3 + [6]*3 + [7]*3 + [8]*3 + [9]*3, "run_id": [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3, + "function_id": [1]*9 + [1]*9 + [1]*9 }) - + + def test_basic_call_returns_axes_and_data(self): evals = [1, 10, 100] - plot_robustrank_over_time( - data, - obj_columns=["f1","f2", "f3"], - evals=evals, - indicator=HyperVolume(reference_point=[5.0,5.0,5.0]), - ) + axs, comparison, benchmark = plot_robustrank_over_time( + self.data, + obj_vars=["f1", "f2", "f3"], + evals=evals, + indicator=HyperVolume(reference_point=[5.0, 5.0, 5.0]), + ) + self.assertIsNotNone(axs) + self.assertIsNotNone(comparison) + self.assertIsNotNone(benchmark) class TestPlotRobustRankChanges(unittest.TestCase): - def test_basic_call(self): - data = pl.DataFrame({ + def setUp(self): + self.data = pl.DataFrame({ "algorithm_name": ["A"] * 9 + ["B"] * 9 + ["C"] * 9, "evaluations": [1, 10, 100] * 9, "f1": [ @@ -122,15 +130,19 @@ def test_basic_call(self): ], "data_id": [1]*3 + [2]*3 + [3]*3 + [4]*3 + [5]*3 + [6]*3 + [7]*3 + [8]*3 + [9]*3, "run_id": [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3 + [1]*3 + [2]*3 + [3]*3, + "function_id": [1]*9 + [1]*9 + [1]*9 }) + + def test_basic_call_returns_axes_and_data(self): evals = [1, 10, 100] - plot_robustrank_changes( - data, - obj_columns=["f1","f2", "f3"], + ax, dt = plot_robustrank_changes( + self.data, + obj_vars=["f1","f2", "f3"], evals=evals, - indicator=HyperVolume(reference_point=[5.0,5.0,5.0]), - - ) + indicator=HyperVolume(reference_point=[5.0, 5.0, 5.0]), + ) + self.assertIsNotNone(ax) + self.assertIsNotNone(dt) if __name__ == "__main__": diff --git a/tests/test_plots/test_single_run.py b/tests/test_plots/test_single_run.py index 394fd21..a76a34f 100644 --- a/tests/test_plots/test_single_run.py +++ b/tests/test_plots/test_single_run.py @@ -1,9 +1,13 @@ import unittest import polars as pl import numpy as np -import matplotlib.pyplot as plt +import matplotlib from iohinspector.plots.single_run import plot_heatmap_single_run +matplotlib.use("Agg") # Use non-interactive backend for tests +import matplotlib.pyplot as plt + + class TestPlotHeatmapSingleRun(unittest.TestCase): def setUp(self): self.data = pl.DataFrame({ @@ -12,70 +16,21 @@ def setUp(self): "x1": np.linspace(-5, 5, 5), "x2": np.linspace(-5, 5, 5)[::-1], }) - self.var_cols = ["x1", "x2"] - self.x_mins = np.array([-5, -5]) - self.x_maxs = np.array([5, 5]) + self.vars = ["x1", "x2"] + self.var_mins = np.array([-5, -5]) + self.var_maxs = np.array([5, 5]) - def test_basic(self): - dt_plot = plot_heatmap_single_run( + def test_basic_call_returns_axes_and_data(self): + ax, data = plot_heatmap_single_run( data=self.data, - var_cols=self.var_cols, - eval_col="evaluations", - scale_xlog=False, - x_mins=self.x_mins, - x_maxs=self.x_maxs, + vars=self.vars, + eval_var="evaluations", + var_mins=self.var_mins, + var_maxs=self.var_maxs, ) - self.assertEqual(dt_plot.shape, (2, 5)) - self.assertAlmostEqual(dt_plot.values.min(), 0) - self.assertAlmostEqual(dt_plot.values.max(), 1) - self.assertTrue(np.all((dt_plot.values >= 0) & (dt_plot.values <= 1))) - - def test_asserts_on_multiple_data_ids(self): - data = pl.DataFrame({ - "data_id": [1, 2], - "evaluations": [1, 2], - "x1": [0, 1], - }) - with self.assertRaises(AssertionError): - plot_heatmap_single_run(data, ["x1"]) + self.assertIsNotNone(ax) + self.assertIsNotNone(data) - def test_single_variable(self): - data = pl.DataFrame({ - "data_id": [1]*3, - "evaluations": [1, 2, 3], - "x1": [-5, 0, 5], - }) - dt_plot = plot_heatmap_single_run( - data=data, - var_cols=["x1"], - eval_col="evaluations", - scale_xlog=False, - x_mins=[-5], - x_maxs=[5], - ax=None, - file_name=None, - ) - self.assertEqual(dt_plot.shape, (1, 3)) - np.testing.assert_allclose(dt_plot.values, [[0, 0.5, 1]]) - - def test_non_default_eval_col(self): - data = pl.DataFrame({ - "data_id": [1]*4, - "evals": [1, 2, 3, 4], - "x1": [0, 1, 2, 3], - "x2": [3, 2, 1, 0], - }) - dt_plot = plot_heatmap_single_run( - data=data, - var_cols=["x1", "x2"], - eval_col="evals", - scale_xlog=False, - x_mins=[0, 0], - x_maxs=[3, 3], - ax=None, - file_name=None, - ) - self.assertEqual(dt_plot.shape, (2, 4)) if __name__ == "__main__": unittest.main() \ No newline at end of file From f622e9a87fbc4d66b796599805ad7fc8869e3c5c Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Sun, 9 Nov 2025 20:49:36 +0100 Subject: [PATCH 10/17] small update --- examples/SO_Examples.ipynb | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/examples/SO_Examples.ipynb b/examples/SO_Examples.ipynb index 5e3de89..749471f 100644 --- a/examples/SO_Examples.ipynb +++ b/examples/SO_Examples.ipynb @@ -404,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [ { @@ -495,7 +495,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -559,7 +559,7 @@ "outputs": [ { "data": { - "image/png": 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" ] @@ -581,14 +581,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -636,14 +636,14 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] }, "metadata": {}, From ee31df16d12a7ec5a158f1bf2abc9789cb98cd7b Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Sun, 9 Nov 2025 21:07:50 +0100 Subject: [PATCH 11/17] small --- pyproject.toml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index facad34..4a17d8e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -26,7 +26,8 @@ dependencies = [ "pyarrow", "robustranking", "seaborn", - "skelo" + "skelo", + "networkx" ] [project.optional-dependencies] From df337079dbd4370cb7ddfde8b37efa238201dd26 Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Thu, 20 Nov 2025 17:02:04 +0100 Subject: [PATCH 12/17] function reference --- FUNCTION_REFERENCE.md | 1024 +++++ aux/aggregated_result.csv | 42 - aux/aligned_data.csv | 251 -- aux/ecdf_data.csv | 42 - aux/selected_data.csv | 23 - aux/test_data/HC.zip | Bin 18923 -> 0 bytes aux/test_data/HC/IOHprofiler_f1_Sphere.json | 30 - .../HC/IOHprofiler_f2_Ellipsoid.json | 30 - .../HC/data_f1_Sphere/IOHprofiler_f1_DIM2.dat | 243 -- .../data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat | 185 - 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[AOCC (Area Over Convergence Curve)](#aocc) + - [Attractor Network](#attractor-network) + - [ECDF (Empirical Cumulative Distribution Function)](#ecdf) + - [EAF (Empirical Attainment Function)](#eaf) + - [Fixed Budget](#fixed-budget) + - [Fixed Target](#fixed-target) + - [Multi-Objective](#multi-objective) + - [Ranking](#ranking) + - [Single Run](#single-run) + - [Trajectory](#trajectory) + - [Utils](#metrics-utils) +- [Plotting Functions](#plotting-functions) + - [Attractor Network Plots](#attractor-network-plots) + - [ECDF Plots](#ecdf-plots) + - [EAF Plots](#eaf-plots) + - [Fixed Budget Plots](#fixed-budget-plots) + - [Fixed Target Plots](#fixed-target-plots) + - [Multi-Objective Plots](#multi-objective-plots) + - [Ranking Plots](#ranking-plots) + - [Single Run Plots](#single-run-plots) + - [Plot Utils](#plot-utils) + +--- + +## Metrics Functions + +### AOCC + +#### `get_aocc(data, eval_var="evaluations", fval_var="raw_y", eval_max=None, maximization=False)` +Calculate Area Over Convergence Curve (AOCC) for algorithm performance evaluation. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `fval_var (str, optional)`: Which column contains the function values. Defaults to "raw_y". +- `eval_max (int, optional)`: Maximum evaluation bound for AOCC calculation. If None, uses data maximum. Defaults to None. +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. + +**Returns:** +- `pl.DataFrame`: DataFrame with AOCC values calculated for each algorithm. + +--- + +### Attractor Network + +#### `get_attractor_network(data, coord_vars=["x0", "x1"], fval_var="raw_y", eval_var="evaluations", maximization=False, beta=40, epsilon=0.0001)` +Generate attractor network analysis from optimization algorithm trajectory data. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm trajectory data with position and performance information. +- `coord_vars (Iterable[str], optional)`: Which columns contain the decision variable coordinates. Defaults to ["x0", "x1"]. +- `fval_var (str, optional)`: Which column contains the fitness/objective values. Defaults to "raw_y". +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. +- `beta (int, optional)`: Minimum stagnation length for attractor detection. Defaults to 40. +- `epsilon (float, optional)`: Distance threshold below which positions are considered identical. Defaults to 0.0001. + +**Returns:** +- `tuple[pd.DataFrame, pd.DataFrame]`: Two dataframes containing the nodes and edges of the attractor network. + +--- + +### ECDF + +#### `get_data_ecdf(data, fval_var="raw_y", eval_var="evaluations", free_vars=["algorithm_name"], maximization=False, f_min=None, f_max=None, scale_f_log=True, eval_values=None, eval_min=None, eval_max=None, scale_eval_log=True, turbo=True)` +Generate Empirical Cumulative Distribution Function (ECDF) data for performance analysis. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `fval_var (str, optional)`: Which column contains the function/performance values. Defaults to "raw_y". +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `free_vars (Iterable[str], optional)`: Which columns contain the grouping variables. Defaults to ["algorithm_name"]. +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. +- `f_min (float, optional)`: Minimum function value bound. If None, uses data minimum. Defaults to None. +- `f_max (float, optional)`: Maximum function value bound. If None, uses data maximum. Defaults to None. +- `scale_f_log (bool, optional)`: Whether function values should be log-scaled. Defaults to True. +- `eval_values (Iterable[int], optional)`: Specific evaluation points. If None, uses eval_min/eval_max. Defaults to None. +- `eval_min (int, optional)`: Minimum evaluation bound. If None, uses data minimum. Defaults to None. +- `eval_max (int, optional)`: Maximum evaluation bound. If None, uses data maximum. Defaults to None. +- `scale_eval_log (bool, optional)`: Whether evaluation axis should be log-scaled. Defaults to True. +- `turbo (bool, optional)`: Whether to use optimized computation. Defaults to True. + +**Returns:** +- `pd.DataFrame`: DataFrame containing ECDF data with evaluation points and cumulative probabilities. + +--- + +### EAF + +#### `get_discritized_eaf_single_objective(data, eval_var="evaluations", fval_var="raw_y", eval_min=1, eval_max=None, scale_eval_log=True, n_quantiles=100)` +Generate discretized EAF data for single-objective optimization analysis. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing single-objective optimization trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `fval_var (str, optional)`: Which column contains the function values. Defaults to "raw_y". +- `eval_min (int, optional)`: Minimum evaluation bound. Defaults to 1. +- `eval_max (int, optional)`: Maximum evaluation bound. If None, uses data maximum. Defaults to None. +- `scale_eval_log (bool, optional)`: Whether evaluations should be log-scaled. Defaults to True. +- `n_quantiles (int, optional)`: Number of quantile levels for discretization. Defaults to 100. + +**Returns:** +- `pl.DataFrame`: DataFrame with discretized EAF data for visualization. + +#### `get_eaf_data(data, eval_var="evaluations", eval_min=1, eval_max=None, scale_eval_log=True, return_as_pandas=True)` +Generate Empirical Attainment Function data for algorithm performance analysis. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `eval_min (int, optional)`: Minimum evaluation bound. Defaults to 1. +- `eval_max (int, optional)`: Maximum evaluation bound. If None, uses data maximum. Defaults to None. +- `scale_eval_log (bool, optional)`: Whether evaluations should be log-scaled. Defaults to True. +- `return_as_pandas (bool, optional)`: Whether to return results as pandas DataFrame. Defaults to True. + +**Returns:** +- `pl.DataFrame | pd.DataFrame`: DataFrame containing EAF data with evaluation points and performance values. + +#### `get_eaf_pareto_data(data, obj1_var, obj2_var)` +Generate EAF data for multi-objective optimization in Pareto space. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing multi-objective optimization trajectory data. +- `obj1_var (str)`: Which column contains the first objective values. +- `obj2_var (str)`: Which column contains the second objective values. + +**Returns:** +- `pd.DataFrame`: DataFrame containing EAF data in Pareto space with attainment probabilities. + +#### `get_eaf_diff_data(data1, data2, obj1_var, obj2_var)` +Calculate EAF differences between two algorithm datasets for comparative analysis. + +**Args:** +- `data1 (pl.DataFrame)`: Input dataframe containing trajectory data for the first algorithm. +- `data2 (pl.DataFrame)`: Input dataframe containing trajectory data for the second algorithm. +- `obj1_var (str)`: Which column contains the first objective values. +- `obj2_var (str)`: Which column contains the second objective values. + +**Returns:** +- `pd.DataFrame`: DataFrame containing EAF differences with statistical significance indicators. + +--- + +### Fixed Budget + +#### `aggregate_convergence(data, eval_var="evaluations", fval_var="raw_y", free_vars=["algorithm_name"], eval_min=None, eval_max=None, maximization=False)` +Aggregate algorithm performance data for fixed-budget convergence analysis. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `fval_var (str, optional)`: Which column contains the function/objective values. Defaults to "raw_y". +- `free_vars (Iterable[str], optional)`: Which columns contain the grouping variables. Defaults to ["algorithm_name"]. +- `eval_min (float, optional)`: Minimum evaluation bound. If None, uses data minimum. Defaults to None. +- `eval_max (float, optional)`: Maximum evaluation bound. If None, uses data maximum. Defaults to None. +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. + +**Returns:** +- `pl.DataFrame`: DataFrame with aggregated convergence statistics including geometric mean, mean, median, min, max. + +--- + +### Fixed Target + +#### `aggregate_running_time(data, eval_var="evaluations", fval_var="raw_y", free_vars=["algorithm_name"], f_min=None, f_max=None, scale_f_log=True, eval_max=None, maximization=False)` +Aggregate Expected Running Time (ERT) data for fixed-target performance analysis. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `fval_var (str, optional)`: Which column contains the function/objective values. Defaults to "raw_y". +- `free_vars (Iterable[str], optional)`: Which columns contain the grouping variables. Defaults to ["algorithm_name"]. +- `f_min (float, optional)`: Minimum function value bound for target range. If None, uses data minimum. Defaults to None. +- `f_max (float, optional)`: Maximum function value bound for target range. If None, uses data maximum. Defaults to None. +- `scale_f_log (bool, optional)`: Whether function values should be log-scaled for target sampling. Defaults to True. +- `eval_max (int, optional)`: Maximum evaluation budget to consider. If None, uses data maximum. Defaults to None. +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. + +**Returns:** +- `pl.DataFrame`: DataFrame with ERT statistics including Expected Running Time, mean, PAR-10, min, max. + +--- + +### Multi-Objective + +#### `get_pareto_front_2d(data, obj1_var="raw_y", obj2_var="F2")` +Extract 2D Pareto front data from multi-objective optimization results. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing multi-objective optimization trajectory data. +- `obj1_var (str, optional)`: Which column contains the first objective values. Defaults to "raw_y". +- `obj2_var (str, optional)`: Which column contains the second objective values. Defaults to "F2". + +**Returns:** +- `pd.DataFrame`: DataFrame containing only the Pareto-optimal solutions for visualization. + +#### `get_indicator_over_time_data(data, indicator, obj_vars=["raw_y", "F2"], eval_min=1, eval_max=50_000, scale_eval_log=True, eval_steps=50)` +Calculate multi-objective quality indicator values over evaluation time. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing multi-objective optimization trajectory data. +- `indicator (object)`: Quality indicator object from iohinspector.indicators module. +- `obj_vars (Iterable[str], optional)`: Which columns contain the objective values. Defaults to ["raw_y", "F2"]. +- `eval_min (int, optional)`: Minimum evaluation bound for the time axis. Defaults to 1. +- `eval_max (int, optional)`: Maximum evaluation bound for the time axis. Defaults to 50_000. +- `scale_eval_log (bool, optional)`: Whether the evaluation axis should be log-scaled. Defaults to True. +- `eval_steps (int, optional)`: Number of evaluation points to sample. Defaults to 50. + +**Returns:** +- `pd.DataFrame`: DataFrame with indicator values calculated at different evaluation points. + +--- + +### Ranking + +#### `get_tournament_ratings(data, alg_vars=["algorithm_name"], fid_vars=["function_name"], fval_var="raw_y", nrounds=25, maximization=False)` +Calculate ELO ratings from tournament-style algorithm competition. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance data across multiple problems. +- `alg_vars (Iterable[str], optional)`: Which columns contain the algorithm identifiers. Defaults to ["algorithm_name"]. +- `fid_vars (Iterable[str], optional)`: Which columns contain the problem/function identifiers. Defaults to ["function_name"]. +- `fval_var (str, optional)`: Which column contains the performance values. Defaults to "raw_y". +- `nrounds (int, optional)`: Number of tournament rounds to simulate. Defaults to 25. +- `maximization (bool, optional)`: Whether the performance should be maximized. Defaults to False. + +**Returns:** +- `pd.DataFrame`: DataFrame with ELO ratings and deviations for each algorithm. + +#### `get_robustrank_over_time(data, obj_vars, evals, indicator)` +Generate robust ranking data for algorithms at specific evaluation timesteps. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance trajectory data. +- `obj_vars (Iterable[str])`: Which columns contain the objective values for ranking calculation. +- `evals (Iterable[int])`: Evaluation timesteps at which to compute rankings. +- `indicator (object)`: Quality indicator object from iohinspector.indicators module. + +**Returns:** +- `tuple`: Comparison and benchmark objects for robust ranking analysis. + +#### `get_robustrank_changes(data, obj_vars, evals, indicator)` +Calculate robust ranking changes between evaluation timesteps. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance trajectory data. +- `obj_vars (Iterable[str])`: Which columns contain the objective values for ranking calculation. +- `evals (Iterable[int])`: Evaluation timesteps at which to compute ranking changes. +- `indicator (object)`: Quality indicator object from iohinspector.indicators module. + +**Returns:** +- `object`: Ranking comparisons data for trajectory analysis. + +--- + +### Single Run + +#### `get_heatmap_single_run_data(data, vars, eval_var="evaluations", var_mins=[-5], var_maxs=[5])` +Generate heatmap data for single algorithm run search space exploration analysis. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing trajectory data from a single algorithm run. +- `vars (Iterable[str])`: Which columns contain the decision/search space variables. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `var_mins (Iterable[float], optional)`: Minimum bounds for the search space variables. Defaults to [-5]. +- `var_maxs (Iterable[float], optional)`: Maximum bounds for the search space variables. Defaults to [5]. + +**Returns:** +- `pd.DataFrame`: DataFrame formatted for heatmap visualization of search space exploration. + +--- + +### Trajectory + +#### `get_trajectory(data, traj_length=None, min_fevals=1, evaluation_variable="evaluations", fval_variable="raw_y", free_variables=["algorithm_name"], maximization=False, return_as_pandas=True)` +Generate aligned performance trajectories for algorithm comparison over fixed evaluation sequences. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance trajectory data. +- `traj_length (int, optional)`: Length of the trajectory to generate. If None, uses maximum evaluations from data. Defaults to None. +- `min_fevals (int, optional)`: Starting evaluation number for the trajectory. Defaults to 1. +- `evaluation_variable (str, optional)`: Which column contains the evaluation numbers. Defaults to "evaluations". +- `fval_variable (str, optional)`: Which column contains the function values. Defaults to "raw_y". +- `free_variables (Iterable[str], optional)`: Which columns to NOT aggregate over. Defaults to ["algorithm_name"]. +- `maximization (bool, optional)`: Whether the performance metric is being maximized. Defaults to False. +- `return_as_pandas (bool, optional)`: Whether to return results as pandas DataFrame. Defaults to True. + +**Returns:** +- `pl.DataFrame | pd.DataFrame`: DataFrame with aligned trajectory data where each row corresponds to a specific evaluation and performance value. + +--- + +### Metrics Utils + +#### `get_sequence(min, max, len, scale_log=False, cast_to_int=False)` +Create sequence of points, used for subselecting targets / budgets for alignment and data processing. + +**Args:** +- `min (float)`: Starting point of the range. +- `max (float)`: Final point of the range. +- `len (float)`: Number of steps in the sequence. +- `scale_log (bool, optional)`: Whether values should be scaled logarithmically. Defaults to False. +- `cast_to_int (bool, optional)`: Whether the values should be casted to integers. Defaults to False. + +**Returns:** +- `np.ndarray`: Array of evenly spaced values between min and max. + +#### `normalize_objectives(data, obj_vars=["raw_y"], bounds=None, log_scale=False, maximize=False, prefix="ert", keep_original=True)` +Normalize multiple objective columns in a dataframe using min-max normalization. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing the objective columns. +- `obj_vars (Iterable[str], optional)`: Which columns contain the objective values to normalize. Defaults to ["raw_y"]. +- `bounds (Optional[Dict[str, tuple]], optional)`: Optional manual bounds per column as (lower_bound, upper_bound). Defaults to None. +- `log_scale (Union[bool, Dict[str, bool]], optional)`: Whether to apply log10 scaling. Defaults to False. +- `maximize (Union[bool, Dict[str, bool]], optional)`: Whether to treat objective as maximization. Defaults to False. +- `prefix (str, optional)`: Prefix for normalized column names. Defaults to "ert". +- `keep_original (bool, optional)`: Whether to keep original objective column names. Defaults to True. + +**Returns:** +- `pl.DataFrame`: The original dataframe with new normalized objective columns added. + +#### `add_normalized_objectives(data, obj_vars, max_obj=None, min_obj=None)` +Add new normalized columns to provided dataframe based on the provided objective columns. + +**Args:** +- `data (pl.DataFrame)`: The original dataframe containing objective columns. +- `obj_vars (Iterable[str])`: Which columns contain the objective values to normalize. +- `max_obj (Optional[pl.DataFrame], optional)`: Maximum values for normalization. If None, uses data maximum. Defaults to None. +- `min_obj (Optional[pl.DataFrame], optional)`: Minimum values for normalization. If None, uses data minimum. Defaults to None. + +**Returns:** +- `pl.DataFrame`: The original DataFrame with new 'objI' columns added for each objective. + +#### `transform_fval(data, lb=1e-8, ub=1e8, scale_log=True, maximization=False, fval_var="raw_y")` +Helper function to transform function values using min-max normalization based on provided bounds and scaling. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing function values. +- `lb (float, optional)`: Lower bound for normalization. Defaults to 1e-8. +- `ub (float, optional)`: Upper bound for normalization. Defaults to 1e8. +- `scale_log (bool, optional)`: Whether to apply logarithmic scaling. Defaults to True. +- `maximization (bool, optional)`: Whether the problem is a maximization problem. Defaults to False. +- `fval_var (str, optional)`: Which column contains the function values to transform. Defaults to "raw_y". + +**Returns:** +- `pl.DataFrame`: The original dataframe with normalized function values in a new 'eaf' column. + +--- + +## Plotting Functions + +### Attractor Network Plots + +#### `plot_attractor_network(data, coord_vars=["x0", "x1"], fval_var="raw_y", eval_var="evaluations", maximization=False, beta=40, epsilon=0.0001, *, ax=None, file_name=None, plot_args=None)` +Plot an attractor network visualization from optimization algorithm data. + +Creates a network graph where nodes represent attractors (stable points) in the search space and edges represent transitions between them. Node sizes reflect visit frequency and colors represent fitness values. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `coord_vars (Iterable[str], optional)`: Which columns contain the decision variable coordinates. Defaults to ["x0", "x1"]. +- `fval_var (str, optional)`: Which column contains the fitness/objective values. Defaults to "raw_y". +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. +- `beta (int, optional)`: Minimum stagnation length for attractor detection. Defaults to 40. +- `epsilon (float, optional)`: Distance threshold below which positions are considered identical. Defaults to 0.0001. +- `ax (matplotlib.axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (str, optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | AttractorNetworkPlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, tuple[pd.DataFrame, pd.DataFrame]]`: The matplotlib axes object and a tuple containing two dataframes with the nodes and edges of the attractor network. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_attractor_network +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("SO_Data") + +df = manager.select(function_ids=[1], algorithms=['RandomSearch']).load(True, True) +ax, (nodes_df, edges_df) = plot_attractor_network( + df, + coord_vars=["x0", "x1"], + fval_var="raw_y", + file_name="example_plots/attractor_network.png" +) +``` + +**Generated Plot:** +
+Attractor Network Plot + +*Example attractor network visualization showing nodes (attractors) and edges (transitions) with node sizes representing visit frequency and colors indicating fitness values.* + +--- + +### ECDF Plots + +#### `plot_ecdf(data, fval_var="raw_y", eval_var="evaluations", free_vars=["algorithm_name"], maximization=False, f_min=None, f_max=None, scale_f_log=True, eval_values=None, eval_min=None, eval_max=None, scale_eval_log=True, *, ax=None, file_name=None, plot_args=None)` +Plot Empirical Cumulative Distribution Function (ECDF) based on Empirical Attainment Functions. + +Creates line plots showing the cumulative probability of achieving different performance levels at various evaluation budgets, allowing comparison between algorithms or configurations. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `fval_var (str, optional)`: Which column contains the function/performance values. Defaults to "raw_y". +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `free_vars (Iterable[str], optional)`: Which columns contain the grouping variables for distinguishing between different lines in the plot. Defaults to ["algorithm_name"]. +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. +- `f_min (int, optional)`: Minimum function value bound. If None, uses data minimum. Defaults to None. +- `f_max (int, optional)`: Maximum function value bound. If None, uses data maximum. Defaults to None. +- `scale_f_log (bool, optional)`: Whether function values should be log-scaled before normalization. Defaults to True. +- `eval_values (Iterable[int], optional)`: Specific evaluation points to plot. If None, uses eval_min/eval_max with scale_eval_log to sample points. Defaults to None. +- `eval_min (int, optional)`: Minimum evaluation bound. If None, uses data minimum. Defaults to None. +- `eval_max (int, optional)`: Maximum evaluation bound. If None, uses data maximum. Defaults to None. +- `scale_eval_log (bool, optional)`: Whether the evaluation axis should be log-scaled. Defaults to True. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | LinePlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pd.DataFrame]`: The matplotlib axes object and the processed dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_ecdf +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("SO_Data") + +df = manager.select(function_ids=[1]).load(True, True) +ax, data = plot_ecdf( + df, + file_name="example_plots/ecdf.png" +) +``` + +**Generated Plot:** +
+ECDF Plot + +*Example ECDF plot showing cumulative distribution of performance across different algorithms at various evaluation budgets.* + +--- + +### EAF Plots + +#### `plot_eaf_single_objective(data, eval_var="evaluations", fval_var="raw_y", eval_min=None, eval_max=None, scale_eval_log=True, n_quantiles=100, *, ax=None, file_name=None, plot_args=None)` +Plot the Empirical Attainment Function (EAF) for single-objective optimization against budget. + +Creates a heatmap visualization showing the probability of attaining different function values at different evaluation budgets across multiple algorithm runs. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `fval_var (str, optional)`: Which column contains the function values. Defaults to "raw_y". +- `eval_min (int, optional)`: Minimum evaluation bound for the plot. If None, uses data minimum. Defaults to None. +- `eval_max (int, optional)`: Maximum evaluation bound for the plot. If None, uses data maximum. Defaults to None. +- `scale_eval_log (bool, optional)`: Whether the evaluations should be log-scaled. Defaults to True. +- `n_quantiles (int, optional)`: Number of discrete probability levels in the EAF heatmap. Defaults to 100. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | HeatmapPlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pl.DataFrame]`: The matplotlib axes object and the processed dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_eaf_single_objective +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("SO_Data") + +df = manager.select(function_ids=[1], algorithms=['HillClimber']).load(True, True) +ax, data = plot_eaf_single_objective( + df, + file_name="example_plots/eaf_single_objective.png" +) +``` + +**Generated Plot:** +
+EAF Single Objective Plot + +*Example EAF heatmap showing probability of attaining different function values at various evaluation budgets.* + +#### `plot_eaf_pareto(data, obj1_var, obj2_var, *, ax=None, file_name=None, plot_args=None)` +Plot the Empirical Attainment Function (EAF) for multi-objective optimization with two objectives. + +Creates a heatmap visualization showing the probability of attaining different combinations of objective values across multiple algorithm runs in the Pareto front space. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing multi-objective optimization trajectory data. +- `obj1_var (str)`: Which column contains the first objective values. +- `obj2_var (str)`: Which column contains the second objective values. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | HeatmapPlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pd.DataFrame]`: The matplotlib axes object and the EAF dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_eaf_pareto, + add_normalized_objectives +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("MO_Data") + +df = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False) +df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2']) + +ax, data = plot_eaf_pareto( + df, + obj1_var="obj1", + obj2_var="obj2", + file_name="example_plots/eaf_pareto.png" +) +``` + +**Generated Plot:** +
+EAF Pareto Plot + +*Example EAF plot in Pareto space showing attainment probabilities for multi-objective optimization.* + +#### `plot_eaf_diffs(data1, data2, obj1_var, obj2_var, *, ax=None, file_name=None, plot_args=None)` +Plot the Empirical Attainment Function (EAF) differences between two algorithms. + +Creates a heatmap visualization showing the statistical differences in attainment probabilities between two algorithms in the objective space, highlighting regions where one algorithm performs better than the other. + +**Args:** +- `data1 (pl.DataFrame)`: Input dataframe containing trajectory data for the first algorithm. +- `data2 (pl.DataFrame)`: Input dataframe containing trajectory data for the second algorithm. +- `obj1_var (str)`: Which column contains the first objective values. +- `obj2_var (str)`: Which column contains the second objective values. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | HeatmapPlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pd.DataFrame]`: The matplotlib axes object and the EAF differences dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_eaf_diffs, + add_normalized_objectives +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("MO_Data") + +df1 = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False) +df1 = add_normalized_objectives(df1, obj_vars = ['raw_y', 'F2']) + +df2 = manager.select(function_ids=[0], algorithms=['SMS-EMOA']).load(False, False) +df2 = add_normalized_objectives(df2, obj_vars = ['raw_y', 'F2']) + +ax, data = plot_eaf_diffs( + df1, + df2, + obj1_var="obj1", + obj2_var="obj2", + file_name="example_plots/eaf_diffs.png" +) +``` + +**Generated Plot:** +
+EAF Differences Plot + +*Example EAF differences plot showing statistical significance of performance differences between two algorithms in objective space.* + +--- + +### Fixed Budget Plots + +#### `plot_single_function_fixed_budget(data, eval_var="evaluations", fval_var="raw_y", free_vars=["algorithm_name"], eval_min=None, eval_max=None, maximization=False, measures=["geometric_mean"], *, ax=None, file_name=None, plot_args=None)` +Create a fixed-budget convergence plot showing algorithm performance over evaluation budgets. + +Visualizes how different algorithms converge by plotting aggregate performance measures (geometric mean, median, etc.) against evaluation budgets, allowing direct comparison of convergence behavior across algorithms. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `fval_var (str, optional)`: Which column contains the function/objective values. Defaults to "raw_y". +- `free_vars (Iterable[str], optional)`: Which columns contain the grouping variables for distinguishing between different lines in the plot. Defaults to ["algorithm_name"]. +- `eval_min (float, optional)`: Minimum evaluation bound for the plot. If None, uses data minimum. Defaults to None. +- `eval_max (float, optional)`: Maximum evaluation bound for the plot. If None, uses data maximum. Defaults to None. +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. +- `measures (Iterable[str], optional)`: Aggregate measures to plot. Valid options are "geometric_mean", "mean", "median", "min", "max". Defaults to ["geometric_mean"]. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (str, optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | LinePlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pl.DataFrame]`: The matplotlib axes object and the processed (melted/filtered) dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_single_function_fixed_budget +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("SO_Data") + +df = manager.select(function_ids=[1]).load(True, True) +ax, data = plot_single_function_fixed_budget( + df, + file_name="example_plots/fixed_budget.png" +) +``` + +**Generated Plot:** +
+Fixed Budget Plot + +*Example fixed-budget convergence plot showing algorithm performance over evaluation budgets with geometric mean and median measures.* + +--- + +### Fixed Target Plots + +#### `plot_single_function_fixed_target(data, eval_var="evaluations", fval_var="raw_y", free_vars=["algorithm_name"], f_min=None, f_max=None, scale_f_log=True, eval_max=None, maximization=False, measures=["ERT"], *, ax=None, file_name=None, plot_args=None)` +Create a fixed-target plot showing Expected Running Time (ERT) analysis for algorithm performance. + +Visualizes how much computational budget (evaluations) algorithms need to reach specific target performance levels, allowing comparison of algorithm efficiency across different difficulty targets. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing optimization algorithm trajectory data. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `fval_var (str, optional)`: Which column contains the function/objective values. Defaults to "raw_y". +- `free_vars (Iterable[str], optional)`: Which columns contain the grouping variables for distinguishing between different lines in the plot. Defaults to ["algorithm_name"]. +- `f_min (float, optional)`: Minimum function value bound for target range. If None, uses data minimum. Defaults to None. +- `f_max (float, optional)`: Maximum function value bound for target range. If None, uses data maximum. Defaults to None. +- `scale_f_log (bool, optional)`: Whether function values should be log-scaled for target sampling. Defaults to True. +- `eval_max (int, optional)`: Maximum evaluation budget to consider. If None, uses data maximum. Defaults to None. +- `maximization (bool, optional)`: Whether the optimization problem is maximization. Defaults to False. +- `measures (Iterable[str], optional)`: Running time measures to plot. Valid options are "ERT", "mean", "PAR-10", "min", "max". Defaults to ["ERT"]. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (str, optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | LinePlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pl.DataFrame]`: The matplotlib axes object and the processed (melted/filtered) dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_single_function_fixed_target +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("SO_Data") + +df = manager.select(function_ids=[1]).load(True, True) +ax, data = plot_single_function_fixed_target( + df, + file_name="example_plots/fixed_target.png" +) +``` + +**Generated Plot:** +
+Fixed Target Plot + +*Example fixed-target ERT plot showing expected running time to reach different performance targets for multiple algorithms.* + +--- + +### Multi-Objective Plots + +#### `plot_paretofronts_2d(data, obj1_var="raw_y", obj2_var="F2", free_var="algorithm_name", *, ax=None, file_name=None, plot_args=None)` +Visualize 2D Pareto fronts for multi-objective optimization algorithms. + +Creates a scatter plot showing the non-dominated solutions (Pareto fronts) achieved by different algorithms in a two-objective space, allowing visual comparison of algorithm performance and trade-off quality. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing multi-objective optimization trajectory data. +- `obj1_var (str, optional)`: Which column contains the first objective values. Defaults to "raw_y". +- `obj2_var (str, optional)`: Which column contains the second objective values. Defaults to "F2". +- `free_var (str, optional)`: Which column contains the grouping variable for distinguishing between different algorithms/categories. Defaults to "algorithm_name". +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (str, optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | ScatterPlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pd.DataFrame]`: The matplotlib axes object and the Pareto front dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_paretofronts_2d +) +import os + +os.makedirs("example_plots", exist_ok=True) + +manager = DataManager() +manager.add_folder("MO_Data") + +df = manager.select().load(True, True) + +ax, data = plot_paretofronts_2d( + df, + obj1_var="raw_y", + obj2_var="F2", + file_name="example_plots/pareto_fronts.png" +) +``` + +**Generated Plot:** +
+Pareto Fronts 2D Plot + +*Example 2D Pareto fronts visualization showing non-dominated solutions achieved by different algorithms in objective space.* + +#### `plot_indicator_over_time(data, obj_vars=["raw_y", "F2"], indicator=None, free_var="algorithm_name", eval_min=1, eval_max=50_000, scale_eval_log=True, eval_steps=50, *, ax=None, file_name=None, plot_args=None)` +Plot the anytime performance of multi-objective quality indicators over evaluation budgets. + +Creates line plots showing how quality indicators (like hypervolume, IGD, etc.) evolve over the course of algorithm runs, enabling comparison of convergence behavior and solution quality improvement across different algorithms. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing multi-objective optimization trajectory data. +- `obj_vars (Iterable[str], optional)`: Which columns contain the objective values for indicator calculation. Defaults to ["raw_y", "F2"]. +- `indicator (object, optional)`: Quality indicator object from iohinspector.indicators module. Defaults to None. +- `free_var (str, optional)`: Which column contains the grouping variable for distinguishing between different algorithms. Defaults to "algorithm_name". +- `eval_min (int, optional)`: Minimum evaluation bound for the time axis. Defaults to 1. +- `eval_max (int, optional)`: Maximum evaluation bound for the time axis. Defaults to 50_000. +- `scale_eval_log (bool, optional)`: Whether the evaluation axis should be log-scaled. Defaults to True. +- `eval_steps (int, optional)`: Number of evaluation points to sample between eval_min and eval_max. Defaults to 50. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | LinePlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pd.DataFrame]`: The matplotlib axes object and the indicator performance dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_indicator_over_time, + add_normalized_objectives, + get_reference_set, + IGDPlus +) + +manager = DataManager() +manager.add_folder("MO_Data") + +df = manager.select(function_ids=[1]).load(False, True) +df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2']) +ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000) + +igdp_indicator = IGDPlus(reference_set = ref_set) + +ax, data = plot_indicator_over_time( + df, ['obj1', 'obj2'], igdp_indicator, + eval_min=10, eval_max=2000, eval_steps=50, free_var='algorithm_name', + file_name="example_plots/indicator_over_time.png" +) +``` + +**Generated Plot:** +
+Indicator Over Time Plot + +*Example plot showing hypervolume indicator evolution over evaluation time for multiple multi-objective algorithms.* + +--- + +### Ranking Plots + +#### `plot_tournament_ranking(data, alg_vars=["algorithm_name"], fid_vars=["function_name"], fval_var="raw_y", nrounds=25, maximization=False, *, ax=None, file_name=None, plot_args=None)` +Plot ELO ratings from tournament-style algorithm competition across multiple problems. + +Creates a point plot with error bars showing ELO ratings calculated from pairwise algorithm competitions. In each round, all algorithms compete against each other on every function, with performance samples determining winners and ELO rating updates. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance trajectory data. +- `alg_vars (Iterable[str], optional)`: Which columns contain the algorithm identifiers that will compete. Defaults to ["algorithm_name"]. +- `fid_vars (Iterable[str], optional)`: Which columns contain the problem/function identifiers for competition. Defaults to ["function_name"]. +- `fval_var (str, optional)`: Which column contains the performance values. Defaults to "raw_y". +- `nrounds (int, optional)`: Number of tournament rounds to simulate. Defaults to 25. +- `maximization (bool, optional)`: Whether the performance should be maximized. Defaults to False. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (str, optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | BasePlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pd.DataFrame]`: The matplotlib axes object and the ELO ratings dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_tournament_ranking +) + +manager = DataManager() +manager.add_folder("SO_Data") + +df = manager.select(function_ids=[1]).load(True, True) +ax, data = plot_tournament_ranking( + df, + file_name="example_plots/tournament_rankings.png" +) +``` + +**Generated Plot:** +
+Tournament Ranking Plot + +*Example tournament ranking plot showing ELO ratings with error bars for algorithms competing across multiple benchmark functions.* + +#### `plot_robustrank_over_time(data, obj_vars, evals, indicator, *, file_name=None)` +Plot robust ranking confidence intervals at distinct evaluation timesteps. + +Creates multiple subplots showing robust ranking analysis with confidence intervals for algorithm performance at different evaluation budgets, using statistical comparison methods to handle uncertainty in performance measurements. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance trajectory data. Must contain data for a single function only. +- `obj_vars (Iterable[str])`: Which columns contain the objective values for ranking calculation. +- `evals (Iterable[int])`: Evaluation timesteps at which to compute and plot rankings. +- `indicator (object)`: Quality indicator object from iohinspector.indicators module. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. + +**Returns:** +- `tuple[np.ndarray, tuple]`: Array of matplotlib axes objects and a tuple containing (comparison, benchmark) data used for the robust ranking analysis. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_robustrank_over_time, + IGDPlus, + get_reference_set, + add_normalized_objectives +) + +manager = DataManager() +manager.add_folder("MO_Data") + +df = manager.select(function_ids=[1]).load(True, True) +df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2']) +ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000) + +igdp_indicator = IGDPlus(reference_set = ref_set) +evals = [10,100,1000,2000] + +ax, (comparison, benchmark) = plot_robustrank_over_time( + df, + obj_vars=['obj1', 'obj2'], + evals=evals, + indicator=igdp_indicator, + file_name="example_plots/robustrank_over_time.png" +) +``` + +**Generated Plot:** +
+Robust Rank Over Time Plot + +*Example robust ranking analysis showing confidence intervals for algorithm performance at different evaluation timesteps.* + +#### `plot_robustrank_changes(data, obj_vars, evals, indicator, *, ax=None, file_name=None)` +Plot robust ranking changes over evaluation timesteps as connected line plots. + +Creates a line plot showing how algorithm rankings evolve over time, with lines connecting ranking positions across different evaluation budgets to visualize ranking stability and performance trajectory changes. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing algorithm performance trajectory data. +- `obj_vars (Iterable[str])`: Which columns contain the objective values for ranking calculation. +- `evals (Iterable[int])`: Evaluation timesteps at which to compute rankings and plot changes. +- `indicator (object)`: Quality indicator object from iohinspector.indicators module. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, object]`: The matplotlib axes object and the ranking comparisons data used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_robustrank_changes, + IGDPlus, + get_reference_set, + add_normalized_objectives +) + +manager = DataManager() +manager.add_folder("MO_Data") + +df = manager.select(function_ids=[1]).load(True, True) +df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2']) +ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000) + +igdp_indicator = IGDPlus(reference_set = ref_set) +evals = [10,100,1000,2000] + +ax, comparison = plot_robustrank_changes( + df, + obj_vars=['obj1', 'obj2'], + evals=evals, + indicator=igdp_indicator, + file_name="example_plots/robustrank_changes.png" +) +``` + +**Generated Plot:** +
+Robust Rank Changes Plot + +*Example ranking changes plot showing how algorithm rankings evolve over evaluation time with connected line trajectories.* + +--- + +### Single Run Plots + +#### `plot_heatmap_single_run(data, vars, eval_var="evaluations", var_mins=[-5], var_maxs=[5], *, ax=None, file_name=None, plot_args=None)` +Create a heatmap visualization showing search space exploration patterns in a single algorithm run. + +Visualizes how an optimization algorithm explores the search space over time by showing the density of evaluations across different variable dimensions and evaluation budgets, revealing search patterns and exploration behavior. + +**Args:** +- `data (pl.DataFrame)`: Input dataframe containing trajectory data from a single algorithm run. Must contain data for exactly one run (unique data_id). +- `vars (Iterable[str])`: Which columns contain the decision/search space variables to visualize. +- `eval_var (str, optional)`: Which column contains the evaluation counts. Defaults to "evaluations". +- `var_mins (Iterable[float], optional)`: Minimum bounds for the search space variables. Should be same length as vars. Defaults to [-5]. +- `var_maxs (Iterable[float], optional)`: Maximum bounds for the search space variables. Should be same length as vars. Defaults to [5]. +- `ax (matplotlib.axes._axes.Axes, optional)`: Matplotlib axes to plot on. If None, creates new figure. Defaults to None. +- `file_name (Optional[str], optional)`: Path to save the plot. If None, plot is not saved. Defaults to None. +- `plot_args (dict | HeatmapPlotArgs, optional)`: Plot styling arguments. Defaults to None. + +**Returns:** +- `tuple[matplotlib.axes.Axes, pd.DataFrame]`: The matplotlib axes object and the processed heatmap dataframe used to create the plot. + +**Example:** +```python +from iohinspector import ( + DataManager, + plot_heatmap_single_run +) + +manager = DataManager() +manager.add_folder("SO_Data") + +df = manager.select(function_ids=[1], data_ids=[1], algorithms=["RandomSearch"]).load(True, True) + +ax, data = plot_heatmap_single_run( + df, + vars = ["x0","x1"], + var_mins=[-5,-5], + var_maxs=[5,5], + file_name="example_plots/heatmap_single_run.png" +) +``` + +**Generated Plot:** +
+Heatmap Single Run Plot + +*Example search space exploration heatmap showing algorithm evaluation density across decision variables and evaluation timesteps.* + +--- + +## Notes + +- All functions support both Polars and Pandas DataFrames as input/output +- Plot functions return both the matplotlib axes object and the processed data +- All plotting functions support customizable styling through plot_args parameters + +For more detailed usage examples and tutorials, see the examples directory in the repository. \ No newline at end of file diff --git a/aux/aggregated_result.csv b/aux/aggregated_result.csv deleted file mode 100644 index cd07999..0000000 --- a/aux/aggregated_result.csv +++ /dev/null @@ -1,42 +0,0 @@ -algorithm_name,evaluations,mean,min,max,median,std,geometric_mean -RandomSearch,1.0,25.37419626478,0.3381781111,87.29257597,18.7773250563,26.654265673802346,11.502018372188767 -RandomSearch,2.0,16.54748585314,0.3381781111,65.8452508651,16.6375745911,16.943186158717523,7.78976290607917 -RandomSearch,3.0,13.520373461526667,0.3381781111,63.2635624422,7.6329523355,16.508956324921737,6.14694158841299 -RandomSearch,4.0,8.4873648892,0.3381781111,49.3005667017,5.1561318278,12.440691134151916,3.823310539129448 -RandomSearch,5.0,4.720135515053332,0.3381781111,17.4605156257,3.8073503008,4.806446211476766,2.8843708992589354 -RandomSearch,6.0,4.562541593293332,0.3381781111,17.4605156257,3.8073503008,4.749120587606495,2.811844292473077 -RandomSearch,7.0,4.365324287899999,0.3381781111,17.4605156257,2.9013190535,4.841816568211401,2.549034931662622 -RandomSearch,9.0,2.4608431326266667,0.3381781111,7.2586963891,1.8653159154,2.0322031039970536,1.7030578249654973 -RandomSearch,10.0,2.195116015853334,0.3381781111,7.2586963891,1.1419045605,1.9852196470197634,1.4961367675888084 -RandomSearch,11.0,2.1494421881866668,0.3381781111,7.2586963891,1.1419045605,1.9756696780313219,1.4695093215258777 -RandomSearch,13.0,1.8764338923000001,0.3381781111,6.4796390166,1.1419045605,1.6757619600763036,1.3503589663744642 -RandomSearch,15.0,1.7471870855466667,0.3381781111,4.5409369153,1.1419045605,1.33561120152905,1.318728957883885 -RandomSearch,17.0,1.6903743642933335,0.0439846987,4.1384878772,1.1419045605,1.313898313851048,1.1154659152471742 -RandomSearch,20.0,1.6580646590800003,0.0439846987,4.1384878772,1.0471925892,1.3341517481435354,1.0751360372749006 -RandomSearch,23.0,1.5969243968866669,0.0439846987,4.1384878772,1.0471925892,1.310034649121904,1.0440027388932094 -RandomSearch,27.0,1.5709338847,0.0439846987,4.1384878772,1.0471925892,1.2699653253499321,1.0361365117440462 -RandomSearch,31.0,1.2336675727933335,0.0439846987,4.1384878772,0.8811036262,1.1686310679213523,0.7523852131159497 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-RandomSearch,107.0,0.4919666253533333,0.0439846987,1.322388188,0.3381781111,0.40881284135912277,0.3287773854192266 -RandomSearch,123.0,0.4412842545066667,0.0439846987,1.322388188,0.3381781111,0.3772590604169503,0.304967165399486 -RandomSearch,141.0,0.37017900459333336,0.0439846987,1.322388188,0.1655442064,0.3824210481157437,0.2250848354107555 -RandomSearch,162.0,0.3676972188333334,0.0439846987,1.322388188,0.1655442064,0.38424079688512797,0.21985220990818086 -RandomSearch,186.0,0.24991526115333332,0.0288368794,1.2397783051,0.1629623992,0.3135367527545524,0.14380993492431327 -RandomSearch,213.0,0.23956131468666664,0.0288368794,1.2152065926,0.1629623992,0.3036194089630983,0.1403954162780222 -RandomSearch,245.0,0.16613982642,0.0288368794,0.5078834687,0.160309794,0.14829960740310635,0.11815174697744525 -RandomSearch,281.0,0.12142844984666668,0.0288368794,0.4783761603,0.0806979792,0.11895460621455713,0.08759139358280378 -RandomSearch,323.0,0.11675752864666668,0.0288368794,0.4783761603,0.0806979792,0.11845947682840187,0.08444417961315563 -RandomSearch,370.0,0.10711443982,0.0288368794,0.4783761603,0.0806979792,0.11111965499919756,0.08013507358834494 -RandomSearch,425.0,0.08010812524666668,0.0036469022,0.1655442064,0.0806979792,0.050827062343521585,0.056989832245962435 -RandomSearch,488.0,0.06872605247333334,0.0036469022,0.1395025366,0.0685963845,0.04246932012476472,0.04778723874438876 -RandomSearch,560.0,0.06872605247333334,0.0036469022,0.1395025366,0.0685963845,0.04246932012476472,0.04778723874438876 -RandomSearch,643.0,0.05829997383333333,0.0036469022,0.1203923787,0.0600376563,0.03888572967655927,0.03916393467919352 -RandomSearch,738.0,0.05829997383333333,0.0036469022,0.1203923787,0.0600376563,0.03888572967655927,0.03916393467919352 -RandomSearch,846.0,0.052513254626666665,0.0036469022,0.1203923787,0.049588014,0.03936139901329633,0.03345220688088083 diff --git a/aux/aligned_data.csv 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"best": {"evals": 43, "y": 23.94795041556928, "x": [-2.9256749775245927, 0.4507827499735342]}} - ]} - ] -} diff --git a/aux/test_data/algorithm_B-1/data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat b/aux/test_data/algorithm_B-1/data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat deleted file mode 100644 index c062494..0000000 --- a/aux/test_data/algorithm_B-1/data_f2_Ellipsoid/IOHprofiler_f2_DIM2.dat +++ /dev/null @@ -1,40 +0,0 @@ -evaluations raw_y -1 3528166.0406847419 -4 744814.7493350349 -8 37276.0601619882 -42 21571.0841027235 -43 16160.6522549923 -87 11609.7739768967 -100 12812972.6885809544 -evaluations raw_y -1 15364893.2870349139 -2 4984270.1343410257 -4 40617.2399955599 -7 929.8770978985 -13 657.5361823281 -100 10063638.7089125942 -evaluations raw_y -1 2017251.6716084427 -3 510774.6558958815 -15 63089.7385168056 -16 11364.9563005321 -58 3117.4638045791 -81 178.6280543878 -100 195055.3690568440 -evaluations raw_y -1 10846545.5767801087 -2 2759110.7893186668 -4 1184995.7843317564 -10 23636.8911983180 -32 10168.1942744350 -58 30.5315822697 -100 5304411.0058515267 -evaluations raw_y -1 17706967.6324726678 -2 10410791.1098473761 -3 7602089.6820298862 -5 999728.8128686354 -10 165506.9318883194 -14 1573.0257767019 -43 23.9479504156 -100 10079048.2146880087 diff --git a/aux/test_data/algorithm_B/IOHprofiler_f1_Sphere.json b/aux/test_data/algorithm_B/IOHprofiler_f1_Sphere.json deleted file mode 100644 index dceb8b0..0000000 --- a/aux/test_data/algorithm_B/IOHprofiler_f1_Sphere.json +++ /dev/null @@ -1,20 +0,0 @@ -{ - "version": "0.3.18", - "suite": "unknown_suite", - "function_id": 1, - "function_name": "Sphere", - "maximization": false, - "algorithm": {"name": "algorithm_B", "info": "algorithm_info"}, - "attributes": ["evaluations", "raw_y"], - "scenarios": [ - {"dimension": 2, - "path": "data_f1_Sphere/IOHprofiler_f1_DIM2.dat", - "runs": [ - {"instance": 1, "evals": 100, "best": {"evals": 37, "y": 0.29456573867088964, "x": [-0.17052431245760946, -0.8171497899997968]}}, - {"instance": 1, "evals": 100, "best": {"evals": 24, "y": 0.3519490828283901, "x": [0.42243360688378573, -0.5883164714400362]}}, - {"instance": 1, "evals": 100, "best": {"evals": 51, "y": 0.48023489188889634, "x": [-0.33373309604302204, -1.5258715637042277]}}, - {"instance": 1, "evals": 100, "best": {"evals": 62, "y": 0.446875155274288, "x": [0.8803554890888989, -0.9264757429433876]}}, - {"instance": 1, "evals": 100, "best": {"evals": 53, "y": 0.03062066834897717, "x": [0.4222045538424135, -1.2006493498974602]}} - ]} - ] -} diff --git a/aux/test_data/algorithm_B/data_f1_Sphere/IOHprofiler_f1_DIM2.dat b/aux/test_data/algorithm_B/data_f1_Sphere/IOHprofiler_f1_DIM2.dat deleted file mode 100644 index f52aff4..0000000 --- a/aux/test_data/algorithm_B/data_f1_Sphere/IOHprofiler_f1_DIM2.dat +++ /dev/null @@ -1,33 +0,0 @@ -evaluations raw_y -1 5.6274529163 -2 2.0751885414 -37 0.2945657387 -100 15.7624012302 -evaluations raw_y -1 11.9763916365 -3 0.6855510894 -10 0.3961235617 -24 0.3519490828 -100 37.6045678832 -evaluations raw_y -1 15.8275848238 -5 10.7151568141 -6 4.6825960131 -22 1.8375898614 -51 0.4802348919 -100 2.7173100090 -evaluations raw_y -1 18.0985016267 -3 7.2030475703 -32 2.4516207358 -39 1.3300836641 -62 0.4468751553 -100 7.9788187616 -evaluations raw_y -1 16.1975708999 -2 11.5814621723 -5 9.7435745645 -6 4.7534918694 -10 0.4365425564 -53 0.0306206683 -100 4.4659419085 diff --git a/aux/try.ipynb b/aux/try.ipynb index 396bd6a..4a9015f 100644 --- a/aux/try.ipynb +++ b/aux/try.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 89, "id": "680015a1", "metadata": {}, "outputs": [], @@ -13,526 +13,23 @@ }, { "cell_type": "code", - "execution_count": 3, - "id": "7c8ac34d", + "execution_count": 90, + "id": "18096bb8", "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "shape: (30, 11)\n", - "┌─────────┬──────────────┬──────────────┬──────────────┬───┬──────────┬────────┬───────┬───────────┐\n", - "│ data_id ┆ algorithm_na ┆ algorithm_in ┆ suite ┆ … ┆ instance ┆ run_id ┆ evals ┆ best_y │\n", - "│ --- ┆ me ┆ fo ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", - "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ u16 ┆ u32 ┆ u64 ┆ f64 │\n", - "│ ┆ str ┆ str ┆ ┆ ┆ ┆ ┆ ┆ │\n", - "╞═════════╪══════════════╪══════════════╪══════════════╪═══╪══════════╪════════╪═══════╪═══════════╡\n", - "│ 1 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 1 ┆ 1 ┆ 1000 ┆ 47.150496 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 2 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 2 ┆ 2 ┆ 1000 ┆ 41.120049 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 3 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 3 ┆ 3 ┆ 1000 ┆ 36.072013 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 4 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 4 ┆ 4 ┆ 1000 ┆ 31.407138 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 5 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 5 ┆ 5 ┆ 1000 ┆ 25.438597 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", - "│ 26 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 11 ┆ 11 ┆ 1000 ┆ 0.036231 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 27 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 12 ┆ 12 ┆ 1000 ┆ 0.049588 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 28 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 13 ┆ 13 ┆ 1000 ┆ 0.080143 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 29 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 14 ┆ 14 ┆ 1000 ┆ 0.008005 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "│ 30 ┆ RandomSearch ┆ algorithm_in ┆ unknown_suit ┆ … ┆ 15 ┆ 15 ┆ 1000 ┆ 0.009005 │\n", - "│ ┆ ┆ fo ┆ e ┆ ┆ ┆ ┆ ┆ │\n", - "└─────────┴──────────────┴──────────────┴──────────────┴───┴──────────┴────────┴───────┴───────────┘\n" + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/sklearn/manifold/_mds.py:677: FutureWarning: The default value of `n_init` will change from 4 to 1 in 1.9.\n", + " warnings.warn(\n" ] }, - { - "ename": "AttributeError", - "evalue": "module 'iohinspector' has no attribute 'data_processing'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[3], line 10\u001b[0m\n\u001b[1;32m 7\u001b[0m selection \u001b[38;5;241m=\u001b[39m manager\u001b[38;5;241m.\u001b[39mselect(function_ids\u001b[38;5;241m=\u001b[39m[\u001b[38;5;241m1\u001b[39m], algorithms\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRandomSearch\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m 8\u001b[0m df \u001b[38;5;241m=\u001b[39m selection\u001b[38;5;241m.\u001b[39mload(monotonic\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, include_meta_data\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,)\n\u001b[0;32m---> 10\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43miohinspector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata_processing\u001b[49m\u001b[38;5;241m.\u001b[39maggregate_convergence(df)\n\u001b[1;32m 11\u001b[0m result\u001b[38;5;241m.\u001b[39mto_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maggregated_result.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28mprint\u001b[39m(result)\n", - "\u001b[0;31mAttributeError\u001b[0m: module 'iohinspector' has no attribute 'data_processing'" - ] - } - ], - "source": [ - "manager = iohinspector.DataManager()\n", - "data_folders = [\"test_data/RS\"]\n", - "manager.add_folders(data_folders)\n", - "\n", - "manager.overview\n", - "print(manager.overview)\n", - "selection = manager.select(function_ids=[1], algorithms=['RandomSearch'])\n", - "df = selection.load(monotonic=True, include_meta_data=True,)\n", - "\n", - "result = iohinspector.data_processing.aggregate_convergence(df)\n", - "result.to_csv(\"aggregated_result.csv\", index=False)\n", - "\n", - "print(result)\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3da32d5c", - "metadata": {}, - "outputs": [ { "data": { - "text/html": [ - "
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", 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" ] }, "metadata": {}, @@ -540,149 +37,29 @@ } ], "source": [ - "iohinspector.single_function_fixedtarget(df)" + "from iohinspector import DataManager, plot_attractor_network\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"SO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1], algorithms=['RandomSearch']).load(True, True)\n", + "ax, nodes_df, edges_df = plot_attractor_network(\n", + " df,\n", + " coord_vars=[\"x0\", \"x1\"],\n", + " fval_var=\"raw_y\",\n", + " file_name=\"example_plots/attractor_network.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "028a02af", + "execution_count": 91, + "id": "2fad87f6", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " evaluations algorithm_name data_id algorithm_info suite function_name \\\n", - "0 1.0 RandomSearch 23.0 None None None \n", - "1 2.0 RandomSearch 23.0 None None None \n", - "2 3.0 RandomSearch 23.0 None None None \n", - "3 4.0 RandomSearch 23.0 None None None \n", - "4 5.0 RandomSearch 23.0 None None None \n", - "5 6.0 RandomSearch 23.0 None None None \n", - "6 7.0 RandomSearch 23.0 None None None \n", - "7 9.0 RandomSearch 23.0 None None None \n", - "8 10.0 RandomSearch 23.0 None None None \n", - "9 11.0 RandomSearch 23.0 None None None \n", - "10 13.0 RandomSearch 23.0 None None None \n", - "11 15.0 RandomSearch 23.0 None None None \n", - "12 17.0 RandomSearch 23.0 None None None \n", - "13 20.0 RandomSearch 23.0 None None None \n", - "14 23.0 RandomSearch 23.0 None None None \n", - "15 27.0 RandomSearch 23.0 None None None \n", - "16 31.0 RandomSearch 23.0 None None None \n", - "17 35.0 RandomSearch 23.0 None None None \n", - "18 41.0 RandomSearch 23.0 None None None \n", - "19 47.0 RandomSearch 23.0 None None None \n", - "20 54.0 RandomSearch 23.0 None None None \n", - "21 62.0 RandomSearch 23.0 None None None \n", - "22 71.0 RandomSearch 23.0 None None None \n", - "23 81.0 RandomSearch 23.0 None None None \n", - "24 93.0 RandomSearch 23.0 None None None \n", - "25 107.0 RandomSearch 23.0 None None None \n", - "26 123.0 RandomSearch 23.0 None None None \n", - "27 141.0 RandomSearch 23.0 None None None \n", - "28 162.0 RandomSearch 23.0 None None None \n", - "29 186.0 RandomSearch 23.0 None None None \n", - "30 213.0 RandomSearch 23.0 None None None \n", - "31 245.0 RandomSearch 23.0 None None None \n", - "32 281.0 RandomSearch 23.0 None None None \n", - "33 323.0 RandomSearch 23.0 None None None \n", - "34 370.0 RandomSearch 23.0 None None None \n", - "35 425.0 RandomSearch 23.0 None None None \n", - "36 488.0 RandomSearch 23.0 None None None \n", - "37 560.0 RandomSearch 23.0 None None None \n", - "38 643.0 RandomSearch 23.0 None None None \n", - "39 738.0 RandomSearch 23.0 None None None \n", - "40 846.0 RandomSearch 23.0 None None None \n", - "\n", - " function_id dimension instance run_id evals best_y raw_y \\\n", - "0 1.0 2.0 8.0 8.0 1000.0 0.050848 25.374196 \n", - "1 1.0 2.0 8.0 8.0 1000.0 0.050848 16.547486 \n", - "2 1.0 2.0 8.0 8.0 1000.0 0.050848 13.520373 \n", - "3 1.0 2.0 8.0 8.0 1000.0 0.050848 8.487365 \n", - "4 1.0 2.0 8.0 8.0 1000.0 0.050848 4.720136 \n", - "5 1.0 2.0 8.0 8.0 1000.0 0.050848 4.562542 \n", - "6 1.0 2.0 8.0 8.0 1000.0 0.050848 4.365324 \n", - "7 1.0 2.0 8.0 8.0 1000.0 0.050848 2.460843 \n", - "8 1.0 2.0 8.0 8.0 1000.0 0.050848 2.195116 \n", - "9 1.0 2.0 8.0 8.0 1000.0 0.050848 2.149442 \n", - "10 1.0 2.0 8.0 8.0 1000.0 0.050848 1.876434 \n", - "11 1.0 2.0 8.0 8.0 1000.0 0.050848 1.747187 \n", - "12 1.0 2.0 8.0 8.0 1000.0 0.050848 1.690374 \n", - "13 1.0 2.0 8.0 8.0 1000.0 0.050848 1.658065 \n", - "14 1.0 2.0 8.0 8.0 1000.0 0.050848 1.596924 \n", - "15 1.0 2.0 8.0 8.0 1000.0 0.050848 1.570934 \n", - "16 1.0 2.0 8.0 8.0 1000.0 0.050848 1.233668 \n", - "17 1.0 2.0 8.0 8.0 1000.0 0.050848 1.176390 \n", - "18 1.0 2.0 8.0 8.0 1000.0 0.050848 1.110986 \n", - "19 1.0 2.0 8.0 8.0 1000.0 0.050848 0.955180 \n", - "20 1.0 2.0 8.0 8.0 1000.0 0.050848 0.772736 \n", - "21 1.0 2.0 8.0 8.0 1000.0 0.050848 0.557273 \n", - "22 1.0 2.0 8.0 8.0 1000.0 0.050848 0.539598 \n", - "23 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", - "24 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", - "25 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", - "26 1.0 2.0 8.0 8.0 1000.0 0.050848 0.441284 \n", - "27 1.0 2.0 8.0 8.0 1000.0 0.050848 0.370179 \n", - "28 1.0 2.0 8.0 8.0 1000.0 0.050848 0.367697 \n", - "29 1.0 2.0 8.0 8.0 1000.0 0.050848 0.249915 \n", - "30 1.0 2.0 8.0 8.0 1000.0 0.050848 0.239561 \n", - "31 1.0 2.0 8.0 8.0 1000.0 0.050848 0.166140 \n", - "32 1.0 2.0 8.0 8.0 1000.0 0.050848 0.121428 \n", - "33 1.0 2.0 8.0 8.0 1000.0 0.050848 0.116758 \n", - "34 1.0 2.0 8.0 8.0 1000.0 0.050848 0.107114 \n", - "35 1.0 2.0 8.0 8.0 1000.0 0.050848 0.080108 \n", - "36 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", - "37 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", - "38 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", - "39 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", - "40 1.0 2.0 8.0 8.0 1000.0 0.050848 0.052513 \n", - "\n", - " x0 x1 eaf \n", - "0 -0.344009 0.512334 0.201003 \n", - "1 -1.339305 1.030883 0.239653 \n", - "2 -0.852911 0.122410 0.263143 \n", - "3 0.031484 -0.732846 0.310235 \n", - "4 -0.327776 -0.388880 0.338184 \n", - "5 -0.061125 -0.570694 0.340710 \n", - "6 0.039378 -0.727321 0.350441 \n", - "7 -0.279667 -0.614688 0.390438 \n", - "8 -0.170377 -0.543626 0.403285 \n", - "9 -0.099207 -0.475165 0.405066 \n", - "10 -0.184409 -0.356682 0.413452 \n", - "11 -0.019840 -0.479648 0.415803 \n", - "12 -0.054411 -0.533827 0.432404 \n", - "13 -0.034062 -0.619582 0.436056 \n", - "14 -0.225230 -0.604956 0.438971 \n", - "15 -0.363783 -0.500821 0.439721 \n", - "16 -0.307221 -0.517126 0.471457 \n", - "17 -0.377140 -0.559536 0.486837 \n", - "18 -0.430195 -0.451153 0.490702 \n", - "19 -0.498781 -0.168115 0.502124 \n", - "20 -0.695775 -0.191861 0.523181 \n", - "21 -0.657877 -0.232111 0.541659 \n", - "22 -0.587752 -0.351059 0.547855 \n", - "23 -0.537835 -0.350695 0.553562 \n", - "24 -0.537835 -0.350695 0.553562 \n", - "25 -0.537835 -0.350695 0.553562 \n", - "26 -0.604819 -0.302447 0.561017 \n", - "27 -0.589226 -0.287474 0.591139 \n", - "28 -0.596643 -0.308843 0.593472 \n", - "29 -0.645870 -0.187600 0.635569 \n", - "30 -0.618717 -0.262432 0.637952 \n", - "31 -0.579345 -0.186999 0.655059 \n", - "32 -0.555937 -0.238782 0.684741 \n", - "33 -0.510889 -0.238044 0.688370 \n", - "34 -0.523574 -0.239427 0.693564 \n", - "35 -0.511887 -0.309281 0.727367 \n", - "36 -0.493136 -0.268471 0.744833 \n", - "37 -0.493136 -0.268471 0.744833 \n", - "38 -0.531623 -0.244816 0.764570 \n", - "39 -0.531623 -0.244816 0.764570 \n", - "40 -0.550382 -0.230939 0.780203 \n" - ] - }, { "name": "stderr", "output_type": "stream", @@ -693,965 +70,7 @@ }, { "data": { - "text/html": [ - "
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evaluationsalgorithm_namedata_idalgorithm_infosuitefunction_namefunction_iddimensioninstancerun_idevalsbest_yraw_yx0x1eaf
01RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.05084825.374196-0.3440090.5123340.433702
12RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.05084816.547486-1.3393051.0308830.444280
23RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.05084813.520373-0.8529110.1224100.450709
34RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508488.4873650.031484-0.7328460.463598
45RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508484.720136-0.327776-0.3888800.471247
56RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508484.562542-0.061125-0.5706940.471938
67RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508484.3653240.039378-0.7273210.474602
79RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508482.460843-0.279667-0.6146880.485548
810RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508482.195116-0.170377-0.5436260.489064
911RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508482.149442-0.099207-0.4751650.489552
1013RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.876434-0.184409-0.3566820.491847
1115RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.747187-0.019840-0.4796480.492490
1217RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.690374-0.054411-0.5338270.497034
1320RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.658065-0.034062-0.6195820.498034
1423RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.596924-0.225230-0.6049560.498831
1527RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.570934-0.363783-0.5008210.499036
1631RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.233668-0.307221-0.5171260.507722
1735RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.176390-0.377140-0.5595360.511932
1841RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508481.110986-0.430195-0.4511530.512990
1947RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.955180-0.498781-0.1681150.516116
2054RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.772736-0.695775-0.1918610.521879
2162RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.557273-0.657877-0.2321110.526936
2271RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.539598-0.587752-0.3510590.528632
2381RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.491967-0.537835-0.3506950.530194
2493RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.491967-0.537835-0.3506950.530194
25107RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.491967-0.537835-0.3506950.530194
26123RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.441284-0.604819-0.3024470.532234
27141RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.370179-0.589226-0.2874740.540478
28162RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.367697-0.596643-0.3088430.541117
29186RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.249915-0.645870-0.1876000.552638
30213RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.239561-0.618717-0.2624320.553290
31245RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.166140-0.579345-0.1869990.557972
32281RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.121428-0.555937-0.2387820.566096
33323RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.116758-0.510889-0.2380440.567089
34370RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.107114-0.523574-0.2394270.568511
35425RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.080108-0.511887-0.3092810.577763
36488RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.068726-0.493136-0.2684710.582543
37560RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.068726-0.493136-0.2684710.582543
38643RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.058300-0.531623-0.2448160.587945
39738RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.058300-0.531623-0.2448160.587945
40846RandomSearch23.0NoneNoneNone1.02.08.08.01000.00.0508480.052513-0.550382-0.2309390.592223
\n", - "
" - ], - "text/plain": [ - " evaluations algorithm_name data_id algorithm_info suite function_name \\\n", - "0 1 RandomSearch 23.0 None None None \n", - "1 2 RandomSearch 23.0 None None None \n", - "2 3 RandomSearch 23.0 None None None \n", - "3 4 RandomSearch 23.0 None None None \n", - "4 5 RandomSearch 23.0 None None None \n", - "5 6 RandomSearch 23.0 None None None \n", - "6 7 RandomSearch 23.0 None None None \n", - "7 9 RandomSearch 23.0 None None None \n", - "8 10 RandomSearch 23.0 None None None \n", - "9 11 RandomSearch 23.0 None None None \n", - "10 13 RandomSearch 23.0 None None None \n", - "11 15 RandomSearch 23.0 None None None \n", - "12 17 RandomSearch 23.0 None None None \n", - "13 20 RandomSearch 23.0 None None None \n", - "14 23 RandomSearch 23.0 None None None \n", - "15 27 RandomSearch 23.0 None None None \n", - "16 31 RandomSearch 23.0 None None None \n", - "17 35 RandomSearch 23.0 None None None \n", - "18 41 RandomSearch 23.0 None None None \n", - "19 47 RandomSearch 23.0 None None None \n", - "20 54 RandomSearch 23.0 None None None \n", - "21 62 RandomSearch 23.0 None None None \n", - "22 71 RandomSearch 23.0 None None None \n", - "23 81 RandomSearch 23.0 None None None \n", - "24 93 RandomSearch 23.0 None None None \n", - "25 107 RandomSearch 23.0 None None None \n", - "26 123 RandomSearch 23.0 None None None \n", - "27 141 RandomSearch 23.0 None None None \n", - "28 162 RandomSearch 23.0 None None None \n", - "29 186 RandomSearch 23.0 None None None \n", - "30 213 RandomSearch 23.0 None None None \n", - "31 245 RandomSearch 23.0 None None None \n", - "32 281 RandomSearch 23.0 None None None \n", - "33 323 RandomSearch 23.0 None None None \n", - "34 370 RandomSearch 23.0 None None None \n", - "35 425 RandomSearch 23.0 None None None \n", - "36 488 RandomSearch 23.0 None None None \n", - "37 560 RandomSearch 23.0 None None None \n", - "38 643 RandomSearch 23.0 None None None \n", - "39 738 RandomSearch 23.0 None None None \n", - "40 846 RandomSearch 23.0 None None None \n", - "\n", - " function_id dimension instance run_id evals best_y raw_y \\\n", - "0 1.0 2.0 8.0 8.0 1000.0 0.050848 25.374196 \n", - "1 1.0 2.0 8.0 8.0 1000.0 0.050848 16.547486 \n", - "2 1.0 2.0 8.0 8.0 1000.0 0.050848 13.520373 \n", - "3 1.0 2.0 8.0 8.0 1000.0 0.050848 8.487365 \n", - "4 1.0 2.0 8.0 8.0 1000.0 0.050848 4.720136 \n", - "5 1.0 2.0 8.0 8.0 1000.0 0.050848 4.562542 \n", - "6 1.0 2.0 8.0 8.0 1000.0 0.050848 4.365324 \n", - "7 1.0 2.0 8.0 8.0 1000.0 0.050848 2.460843 \n", - "8 1.0 2.0 8.0 8.0 1000.0 0.050848 2.195116 \n", - "9 1.0 2.0 8.0 8.0 1000.0 0.050848 2.149442 \n", - "10 1.0 2.0 8.0 8.0 1000.0 0.050848 1.876434 \n", - "11 1.0 2.0 8.0 8.0 1000.0 0.050848 1.747187 \n", - "12 1.0 2.0 8.0 8.0 1000.0 0.050848 1.690374 \n", - "13 1.0 2.0 8.0 8.0 1000.0 0.050848 1.658065 \n", - "14 1.0 2.0 8.0 8.0 1000.0 0.050848 1.596924 \n", - "15 1.0 2.0 8.0 8.0 1000.0 0.050848 1.570934 \n", - "16 1.0 2.0 8.0 8.0 1000.0 0.050848 1.233668 \n", - "17 1.0 2.0 8.0 8.0 1000.0 0.050848 1.176390 \n", - "18 1.0 2.0 8.0 8.0 1000.0 0.050848 1.110986 \n", - "19 1.0 2.0 8.0 8.0 1000.0 0.050848 0.955180 \n", - "20 1.0 2.0 8.0 8.0 1000.0 0.050848 0.772736 \n", - "21 1.0 2.0 8.0 8.0 1000.0 0.050848 0.557273 \n", - "22 1.0 2.0 8.0 8.0 1000.0 0.050848 0.539598 \n", - "23 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", - "24 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", - "25 1.0 2.0 8.0 8.0 1000.0 0.050848 0.491967 \n", - "26 1.0 2.0 8.0 8.0 1000.0 0.050848 0.441284 \n", - "27 1.0 2.0 8.0 8.0 1000.0 0.050848 0.370179 \n", - "28 1.0 2.0 8.0 8.0 1000.0 0.050848 0.367697 \n", - "29 1.0 2.0 8.0 8.0 1000.0 0.050848 0.249915 \n", - "30 1.0 2.0 8.0 8.0 1000.0 0.050848 0.239561 \n", - "31 1.0 2.0 8.0 8.0 1000.0 0.050848 0.166140 \n", - "32 1.0 2.0 8.0 8.0 1000.0 0.050848 0.121428 \n", - "33 1.0 2.0 8.0 8.0 1000.0 0.050848 0.116758 \n", - "34 1.0 2.0 8.0 8.0 1000.0 0.050848 0.107114 \n", - "35 1.0 2.0 8.0 8.0 1000.0 0.050848 0.080108 \n", - "36 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", - "37 1.0 2.0 8.0 8.0 1000.0 0.050848 0.068726 \n", - "38 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", - "39 1.0 2.0 8.0 8.0 1000.0 0.050848 0.058300 \n", - "40 1.0 2.0 8.0 8.0 1000.0 0.050848 0.052513 \n", - "\n", - " x0 x1 eaf \n", - "0 -0.344009 0.512334 0.433702 \n", - "1 -1.339305 1.030883 0.444280 \n", - "2 -0.852911 0.122410 0.450709 \n", - "3 0.031484 -0.732846 0.463598 \n", - "4 -0.327776 -0.388880 0.471247 \n", - "5 -0.061125 -0.570694 0.471938 \n", - "6 0.039378 -0.727321 0.474602 \n", - "7 -0.279667 -0.614688 0.485548 \n", - "8 -0.170377 -0.543626 0.489064 \n", - "9 -0.099207 -0.475165 0.489552 \n", - "10 -0.184409 -0.356682 0.491847 \n", - "11 -0.019840 -0.479648 0.492490 \n", - "12 -0.054411 -0.533827 0.497034 \n", - "13 -0.034062 -0.619582 0.498034 \n", - "14 -0.225230 -0.604956 0.498831 \n", - "15 -0.363783 -0.500821 0.499036 \n", - "16 -0.307221 -0.517126 0.507722 \n", - "17 -0.377140 -0.559536 0.511932 \n", - "18 -0.430195 -0.451153 0.512990 \n", - "19 -0.498781 -0.168115 0.516116 \n", - "20 -0.695775 -0.191861 0.521879 \n", - "21 -0.657877 -0.232111 0.526936 \n", - "22 -0.587752 -0.351059 0.528632 \n", - "23 -0.537835 -0.350695 0.530194 \n", - "24 -0.537835 -0.350695 0.530194 \n", - "25 -0.537835 -0.350695 0.530194 \n", - "26 -0.604819 -0.302447 0.532234 \n", - "27 -0.589226 -0.287474 0.540478 \n", - "28 -0.596643 -0.308843 0.541117 \n", - "29 -0.645870 -0.187600 0.552638 \n", - "30 -0.618717 -0.262432 0.553290 \n", - "31 -0.579345 -0.186999 0.557972 \n", - "32 -0.555937 -0.238782 0.566096 \n", - "33 -0.510889 -0.238044 0.567089 \n", - "34 -0.523574 -0.239427 0.568511 \n", - "35 -0.511887 -0.309281 0.577763 \n", - "36 -0.493136 -0.268471 0.582543 \n", - "37 -0.493136 -0.268471 0.582543 \n", - "38 -0.531623 -0.244816 0.587945 \n", - "39 -0.531623 -0.244816 0.587945 \n", - "40 -0.550382 -0.230939 0.592223 " - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - 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U5wHJngleUL1QMABQombNmlnav/zyS4lxR48etSzoeqXs7Ow0depUy/acOXN07ty5EuPff//9IiMBSvLPf/7T0l66dKlWrVpVYuyJEyf08ssvFzm3qj/x7+vra2mfPn26Sq+Nsln7u3H27Fk9+uijVZHSFbv55pvVvHlzSVJUVJQeeOABy4LnZUlNTS3X+iAAAAAAUKO4+Uh+7STP+tKkr6VbvjVPJwRUQxQMAJToxhtvtLQfe+yxYm+yr1mzRoMHD1ZKSorc3d0r5LqPP/64fHx8JJnXJxgxYoT+/vvvIjGGYeiDDz7QY489Jmdn5zL7DA4O1qhRoyzbEyZM0Pfff39J3F9//aWhQ4cqMTFRkhQQEKCHH374Cp7N5WnfvmCRo99//90ytzyuDoV/N1599VV98803l8Ts2rVLgwYNUmRkZIX9blQme3t7ffjhh7K3t5ckzZ8/X9dff70OHTpU4jl79uzRU089pYCAAIWHh1dVqgAAAABgW4Yh7flWOr6uYN8Nc6UZ26S2N0lMM4xqjDExAEo0c+ZMffbZZzp79qzOnTunkSNHqmvXrmrbtq1MJpN27dqlgwcPSpJGjBihevXq6euvv77i6/r5+enjjz/W5MmTlZ+fr507d6p169YaMGCAmjdvrrS0NG3cuFGRkZGSpLlz5+qhh8wLCBWeKuZi8+fPV79+/XTs2DGlpqZq0qRJatGihXr16iUnJyeFhoZq27Ztlk9Vu7u7a9GiRapVq9YVP6fy6tmzpwICAhQZGamoqCi1bt1aw4cPV506dSyjHXr06KHJkydXeW6Qpk6dqv/85z86cuSIsrKy9I9//EOvvPKKOnXqJBcXFx04cEA7d+6UJHXq1EkjRozQG2+8YeOsyzZ06FB9+OGHmj59uvLy8vTbb79p5cqVatu2rTp27CgvLy+lp6crKipKe/fu1dmzZ22dMgAAAABUrbi/pV9nShEbpNpNpOlbJCc3yb2OrTMDKgQFAwAlqlevnpYtW6abbrpJcXFxksyfmt61a1eRuLFjx2rBggV65JFHKuzaEyZM0Ndff61//vOfSk1NVV5entauXau1a9daYpydnfXee+9p8ODBln1eXl4l9unn56dNmzbptttuU0hIiCTzdEpHjx69JLZ58+b69ttv1aNHjwp7TuVhZ2enDz74QDfffLOys7MVHR2tr776qkjM1KlTKRjYiLOzs5YvX65Ro0bp+PHjksyLdF/8afx+/fppyZIl+vTTT22R5mW599571bx5c/3zn//U0aNHZRiGDh48aCkOFqddu3aWUUEAAAAAUCPlZkmb/iutf0vKy5IcXKVud0n2jrbODKhQFAwAlKpPnz46ePCg5s6dq+XLl1tujtavX1/dunXTlClTikzPUpFuu+02DRgwQO+9957+97//6eTJkzKZTGrUqJGGDx+u+++/X61bt9a2bdss55Q1GsDPz09r1qzRypUrtWTJEm3cuFHR0dHKyclRvXr11KVLF40dO1ZTpkyRo6Nt/9G/4YYbtHPnTs2bN08bN27UyZMnlZqaavW88qhcLVu21O7duzVv3jz99NNPCgsLU3Z2tvz9/dWhQwfddtttmjRpkmWKn+okODhYhw4d0s8//6z//e9/2rp1q6Kjo5WcnCw3Nzf5+fmpdevW6tu3r0aNGqXOnTvbOmUAAAAAqDwnNkvLZ0pxYebtoOuk6/8j+TS1aVpAZTAZ3HkClJycLG9vbyUlJZX6CfXSZGZmKjw8XE2bNpWLi0sFZ4jSfPrpp7rvvvskSffff78+/PBDG2cEoLrjPR0AAACAJGnlM9LWD8xt97rSyNek9jezTgGqlfLc+2SEAYBqb8mSJZa2raYQAgAAAAAANZB3gPlr16nS0DmSG9OxomajYACgWvvpp5+0Zs0aSZKLi4vGjRtn44wAAAAAAEC1lRAhRe6QOk40b/f6pxTQS2rUzaZpAVXFztYJAEBxNm/erHvvvVd79uwp9nhWVpbmzp2rW2+91bLvvvvuU+3atasoQwAAAAAAUGPk5Ugb35Hm9ZZ+ni6dPb9egZ09xQJcUxhhAOCqlJ2drc8++0yfffaZAgIC1LlzZ/n5+ckwDJ0+fVpbtmxRUlKSJb5t27Z65ZVXbJgxAAAAAAColk7tlJY/IsUcMG83GSDZO9o2J8BGKBgAuOpFRkYqMjKyxOMjRozQt99+K3d39yrMCpXl3LlzmjVr1hX388gjj6hFixYVkBEAAAAAoMaJPyYdC5EiNkihv0gyJFcfacTLUqdbWdQY1ywKBgCuSgMHDlRISIhWrFihHTt2KCoqSnFxcUpOTpaXl5caNGig/v3765ZbbtGgQYNsnS4qUHJysubNm3fF/UyYMIGCAQAAAABAyk6TTv8leTWUfIPM+/Yukta/WRDT6VZp+MuSu69tcgSuEhQMAFyV7OzsFBwcrODgYFunAgAAAAAAqpOUGClyq3Ty/CNqr2TkSQOekK77P3NM04HmqYga95GaD2WdAuA8CgYAgKtKkyZNZBiGrdMAAAAAAFQ3a1+T9i6WEsIvPebZQHJwKdhuOtD8AFAEBQMAAAAAAAAA1UNOpnRmt3RyixS5TRr8jNSgs/lYWtz5YoFJ8msnBfQyjyBo3EvyDmBdAsAKFAwAAAAAAAAAXJ3S4gumF4rcZi4W5GUXHG8yoKBg0G2q1HKk1Ki75FrLFtkC1R4FAwAAAAAAAAC2lZ9vHh0Qc0Bqdb1kf/625RfDpfi/i8a61zOPGmjcR2oxvGC/fwfzA8Blo2AAAAAAAAAAoOpkpUgxoVLMfin6gBRzUIoNlbJTzcdnbJfqtjK3/dpLJvuCAkFAL8mnGdMLAZWEggEAAAAAAACAimcYUuJJKe2seZogybw9t4RRAPbOUr02UlZqwb6bPy8YbQCg0vHbhmvavHnzNG/ePOXl5dk6FQAAAAAAgOorO12KPWSeUijmQMHIgawkybux9Oh+c5xXI8nJQ3L2NI8e8G9//msHySfo0uIAxQKgSvEbh2vajBkzNGPGDCUnJ8vb29vW6QAAAAAAAFy9MpOllGgp5Yzk5luwXsDeJdLP90tG/qXn2DlKrt5Sbpbk4CzZ2UmPhUou3IcBrkYUDAAAAAAAAIBrWW62lBojefhJDk7mfTs+k05uk1Kizj+iC9YYkKQu/5DGvG9u12psLha41Sk6YsCvvVSnZUGfF1AsAK5aFAwAAAAAAACAmi4zWTr4k5QcVagIcL4QkHbWHPPP9VL9TuZ2+HopdNml/Th7SZ7+knvdgn0Nu0qPh5kLDixGDFRrFAwAAAAAAACA6iw3W4o/KsWEnl9D4KAUFyZ5B0h3rTgfkyUtf6TkPuydpPRzBdvtJ0gNukpeDcwFAs/zX509Lj3Xwdl8DEC1R8EAAAAAAAAAqA4MQ8rPlewdzdv7vpc2zZXOhkn5OZfG5xdaU8DNV2o1WvKoJ3nWL3h41TcXA9x8io4OaHtTpT4VAFcnCgYAAAAAAADA1SY7TYo9XDBiIPb86IH+j0r9zo8UyM8x75PMUwXVayv5tTM/6rWVagUU9GdnJ926qOqfB4BqhYIBAAAAAAAAYCsXRgHY2Zm/rnxWOvKbdC5cknFpfMzBgnazYOnWxeYCgXcA6wcAuGIUDAAAAAAAAIDKkp8nxR2VMhLMj8xEKT1eijtyfuTAIemeNZJfW3N8arR07ri57V6vYMTAhUedVgV9e52fUggAKggFAwAAAAAAAKAkhmGeHsjOXnJ0Ne+LOShFbjff/L9QCMhIkDISzQ93X+mOZebY3Ezpg16lXyPmQEHBoPcMqesdUr12kkfdSnpSAFA8CgYAAAAAAAC4thmGdGh5wXoBaWeLFgHyc6Tr/yP1uMcc//dq6Y9ZJffn4V/QdnSTPPwkJ3fJtbbkUsv81afp+bUG2kk+zQriG3WrjGcIAFahYAAAsNrgwYO1bt06SdKff/6pwYMH2zYh1FgRERFq2rSpJCkwMFARERG2TQgAAAA1Q06mdPaQFL1fOhsmDX/JPO+/yST99pSUcqbkczMSC9p1W0utRhctALhe+FpbcvMtiDWZpCeOVNITAoCKRcEAwDWv8E3w4nh4eKh27dpq27atBg4cqKlTp6phw4ZVmCGuJpGRkfrqq6+0fv16hYaG6ty5c8rOzpa7u7v8/f3VrFkzdenSRb1791ZwcLA8PDxsnTIAAABwbcpOM08bFL3f/Ig5YC4SGHkFMb3ul2oFmNvtxkpZyZJfe8mrYcHN/wvFAEe3gvNajjA/AKCGoWAAAGVITU1VamqqIiMjtWrVKs2ZM0f//ve/NWvWLJlMJlunhyqSmZmp5557TnPnzlVeXt4lx5OSkpSUlKSwsDD99ttvkiRHR0etW7dOffr0qep0AQAAgGtHfr55keCY/ZKRL7W/2bw/IUL6euyl8a4+kn8H88NkV7B/5KtVkS0AXNUoGABAIT169FDPnj2L7EtKStLevXu1f/9+SVJOTo7mzJmjxMREvfPOO7ZIE1UsOztbY8aM0e+//27Z5+TkpO7duysoKEhubm5KTk5WRESE9uzZo4yMDEnmn5W0tDRbpQ0AAADUPNnpUmyoFL3v/MiB82sO5Jz/f3fd1gUFgzotzdt1W50vEHQ0f/Wsb54mCABwCQoGAFDI6NGjNWfOnGKPbd68WbfeeqtOnjwpSZo7d65uv/12de/evQozhC289tprlmKByWTSk08+qaefflq1atW6JDYnJ0dr167Vd999p0WLFlVxpgAAAEANkJ8vJZ+W4o9KcX9L9TtKjXubj/21QFr1zKXnOLiYFxCu39m8gLHJJNk7SjO2VWXmAFDtUTAAACv17dtXy5YtU9euXWUYhiTpk08+oWBQw+Xk5BQZSfLCCy/oueeeKzHe0dFRw4YN07Bhw/Tmm28WO30RAAAAgEIOr5DO7C4oEMT/LeVmFBzvPaOgYODbXHKvVzCl0IWHT5Bkz20uALhSvJMCQDl07txZgwcP1p9//ilJWr9+vY0zQmXbvn27EhMTJZmLAY888ojV5xY3AgEAAAC4puTnSYknzhcCjkpxR80FgXEfS94NzTHbP5GO/1n0PDsHyaeZ5NvCPHLgghbDpH8drbr8AeAaY1d2CACgsM6dO1vaZ86cKTEuJydHq1at0pNPPqng4GA1aNBALi4ucnV1VaNGjTRq1CjNnTtXqampZV4zIiJCJpNJJpNJTZo0sezfuXOn7rnnHrVs2VJubm6qXbu2evbsqVdeeaVcc+fn5+fryy+/1LBhw+Tv7y8XFxc1adJEY8aM0c8//2x1Pxc7ceKEZs2apd69e8vPz09OTk7y8/NT7969NXv2bEVGRpbZx9q1ay3PffDgwZb9v/76q8aPH68mTZrIxcVFvr6+GjVqlFasWFHs81u2bJluuOEGNW3aVC4uLqpfv74mTpyorVu3lnr906dPW9o+Pj7y9PS0/gUohx07dujRRx9V586dVbduXTk5Ocnf31+DBg3S66+/roSEBKv6iY2N1fz58zV16lR16dJFPj4+cnR0VK1atdS6dWvdddddWrVqlVV9zZkzx/LaX5iqKyMjQ59//rmGDx+uxo0by8nJSSaTSXv27Cm2j40bN+qRRx5Rly5dVK9ePTk6OsrLy0sdOnTQ1KlTtWjRIsuaD9aoqJ95AAAAlFNejpSZJKXFSynRUmKkFH9MOht2fh2B0ILYtHhp8e3SvF7Sy/7Su12kbydKq56V/povRWyQ4sIK4luOlLreIQ17Ubp1ifTQLunfMdKDO6Rbv5W63F4Qy9oDAFCpGGEAAOXk6upqaWdmZhYbExkZqS5duig+Pr7Y46dPn9bp06e1cuVKvfTSS1q0aJGGDRtmdQ6GYWjOnDl66aWXlJ+fb9mfkZGhHTt2aMeOHfrss8+0evVqNWvWrNS+oqOjNXbsWG3bVnRuzxMnTujEiRP65ZdfNG7cOH355ZdW5ydJL7/8sl566aVLXqPY2FjFxsZq27ZteuONNzRnzhw99dRTVvebnp6uu+++W4sXLy6yPysrSytXrtTKlSs1e/Zsyw3us2fPauzYsdq8eXOR+OjoaP3www/68ccf9e677+rBBx8s9np2dgW19djYWKWlpcnd3d3qfMuSkJCge++9Vz/++OMlx2JiYhQTE6P169frtdde06effqoJEyaU2Ne7776rxx57rNhpkJKSkpSUlKSwsDAtWLBAQ4YM0XfffSdfX1+rcz106JAmTpyogwcPlhl76tQpTZs2TX/88cclx1JSUnTgwAEdOHBAX331lXr16lVm4aYif+YBAACuGYZhXiD4+Drp5GYpN0u6/fuC4wtukFJjpfwcc0EgL+d8O9f8dfiLUo97zLFbP5D+mFXytbwaSY+d/3+is4cUtkIyzv+/zcHFPGVQnebmEQN1Wkj1Co0a6H1/xT5vAMBlo2AAAOVUeFSBn59fsTFpaWmWYkHt2rXVrl07BQYGysPDQ9nZ2QoPD9fWrVuVmZmp+Ph4jR49WuvWrVPfvn2tyuH555/XCy+8IMk84qFDhw5ydHTUnj17tGvXLklSeHi4xo4dq127dsnBofi3+8TERA0ZMkSHDh2y7GvatKn69OkjZ2dnHTx4UNu3b9fSpUuL3Dgvy4MPPqh58+ZZtj08PBQcHCx/f39FR0frzz//VGpqqjIzM/X0008rOjq6yDoBpblQLHBwcFC/fv3UvHlzpaenKyQkRDExMZbXp1WrVho7dqyGDx+uPXv2yMXFRQMHDlTjxo2VmJioNWvWKCEhQYZh6OGHH1a3bt3Up0+fS64XFBRkaRuGoTfeeEPPP/+81a9FaaKjoy95/du1a6dOnTrJw8NDsbGx2rBhg+Lj45WYmKhJkybp66+/1u23315sf2fOnLEUC5o1a6Y2bdqobt26cnFxUWJiovbv32+52R8SEqKhQ4dq69atcnZ2LjPX+Ph4jRw5UidPnpSLi4v69++vwMBApaamXnKz/+DBgxo2bJiioqIs++rVq6e+ffuqbt26yszM1LFjx7R7925lZGSUWHgrrKJ+5gEAAGq8hBNS+DpzkSB8nZR2tuCYnWPR2LijUmp0yX3lZhV/rsnOvG1//mHnKLkX+iCKg7N003uSp7+5QOAdIJXj7wkAgA0ZAIykpCRDkpGUlHTZfWRkZBihoaFGRkZGBWaGqjBo0CBDkiHJmD17dqmxOTk5RkBAgCV+woQJxcZFREQYDz30kLFt2zYjLy+v2JikpCTj8ccft/TVsmXLEmPDw8MtcU5OTobJZDKCgoKMbdu2XRL73XffGY6Ojpb4L7/8ssTnM23atCL9fv7555fEbNu2zQgMDLTEXIj/888/i+1zyZIllhhJxp133nnJ71ZSUpIxZcqUInE//vhjsf39+eeflhhnZ2dDktG3b1/j2LFjReLS09ONiRMnWmJbtGhhPPTQQ4YkY9y4cUZMTEyR+HPnzhkDBw60xAcHBxd7/fz8fKNJkyaWOJPJZEyZMsXYsmWLkZ+fX9JLW6a8vDwjODjY0m/Pnj2NXbt2XRKXkZFhzJkzxzCZTIYkw93d3Th+/HixfX7++efGe++9Z5w6darE6+7du9fo3r275bovvvhiibGzZ8+2xDk4OFh+5mNjYy95LtnZ2YZhmL+3LVq0sJxXp04d49tvvy32tUpNTTUWLlxo3HXXXZccq6yfeWvxng4AAKqN3OyC9t8hhjHbq+jjJX/D+GqcYWx4xzD2fV/03IhNhnF8vWGc2GIYp3Yaxpm9hhETahhnjxrGuXDDyEgqep2cTMMo4W8WAMDVqzz3PikYAAYFg2tdeQoGL774YpGb3L///vsVX//++++39LdixYpiYwrfPJVk+Pr6GqdPny6xzyeeeMISO3LkyGJjwsLCLDehJRkLFiwosb+wsDDDzc2tSA7FFQzy8vKMpk2bWmImTpxY4k31/Px8Y8yYMZbYoKCgYgsmhQsGkoxWrVoZqampxfaZnJxs+Pj4FIkfMmRIiYWYiIgIw97e3lIIiIqKKjbuhx9+KNJn4e/D6NGjjVmzZhnLly83zp07V8IreKmvvvrK0k/v3r2N9PT0UuML37y///77rb5OcRITEw1/f39DklG/fn0jNze3zGtKMoYPH17ia3nBv//9b0u8t7e3cfjw4cvKsTJ+5suD93QAAHDVyko1jCN/GMbKZw3jw36GseDGgmOZyYbxop9hfDbMMNa8ZBjhG803+QEA17Ty3PtkPBhgI4ZhKD07l8dFD8MwbP2tuURycrI2bNig2267Tf/3f/9n2f/oo4+Wa92Bktx1112W9urVq60659lnn1WDBg1KPD5t2jRLe8eOHcXGfP7555bXu2fPnpo6dWqJ/bVs2VIzZ84sM6/ff/9d4eHhkiQnJye9++67MpWwKJnJZNK8efPk6Gge2nzs2LFi57u/2GuvvVbiGgKenp66/vrri+x7++23S5xOKTAw0DINlGEY2rlzZ7FxN998sz777DO5uLgU2R8fH68VK1bohRde0I033ihfX1/16tVL77//fpnT7Lz99tuW9kcffVRkbYziPP3006pVq5YkadGiRUXm8S8vb29vjRs3TpIUFRWl0NDQMs4wmzt3bqlTU2VlZRWZiuq1115Tq1atLjvPwiriZx4AAKBaysuRTm6V1r4mfTFKei1QWniztOV9KXq/FLlNyjn/f09nT+mpcOnu36Uh/5aa9DNPDwQAgJWY4BewkYycPLWdtcrWaVx1Ql8YITcn2701Pf/882XOT+/r66t//etfVi/Um5OTo23btmnv3r2Kjo5WSkqKcnNzLcdTUlIs7T179ljV58SJE0s93rp1a7m6uiojI0Px8fFKSUmRp6dnkZg///zT0v7HP/5R5jWnTp2qV155pdSYkJAQS3v06NHy9/cvNb5hw4YaOXKkli9fbslpxIgRJca7urpeUhC4WIcOHSzt5s2bq1OnTqXGt2/fXhs2bJAkS7GjOHfffbeGDRum119/XYsWLVJCQsIlMYZhaPv27dq+fbtef/11ff311xo8ePAlcVFRUZbvddu2bcvMUZJcXFzUp08f/fbbb0pKStKBAwfUsWPHEuNjY2O1detWHTp0SAkJCUpLSytSkCtcHNmzZ0+R1604HTt2VJs2bUqN2bp1qxITEyWZizelFaHKqyJ+5gEAAKoFw5AykyTXWubtgz9LP91TNMa7sdRskNRssNR0oORY6IMtjqV/EAUAgNJQMACAcrC3t9frr7+uu+++u8zYjIwMvfLKK/roo48UFxdnVf/WxHl7eysgIKDUGJPJpNq1aysjI0OSeZRE4ZunhmFo7969lu3iFvu9WMuWLeXj46Nz586VGLN7925L29oFnPv162cpGFxYvLa0HC6MSChJ7dq1Le127dqVeX0fHx9LOzk5udTYxo0ba968eXrnnXe0bds2bdiwQTt27NBff/2lyMjIIrGnTp3SsGHD9L///U/Dhw8vcmzLli2WdkZGhh588MEy85TMozAuiIyMLLZgEBoaqqeeekq//fabZQHksljzc9etW7cyYwovfty7d+8yR01YqyJ+5gEAAK5qloWK10rh66WAXtItC83Hmg2S3HylJgPMBYJmg6TaTaUSRvICAHAlKBgANuLqaK/QF0r+JPW1ytXR3qbX79Gjh3r27GnZTk1N1cmTJ7V582ZlZWUpLy9P99xzj44fP66XX365xH4SEhI0ZMgQq0cMXFB4tEFJvL29reqr8I31nJycIseSkpKUnZ1t2W7cuLFVfTZu3LjUgsHZs2ct7cDAQKv6bNKkiaVd1o1ra567g0PBP23ljb/4dSqJk5OTBgwYoAEDBlj2RURE6IcfftDcuXN1+vRpSVJubq7uuOMOHT9+XG5ubpbYM2fOWNrh4eFFpvGxVnEjHFatWqUxY8YoKyurXH1Z83NXt27dMmNiYmIs7WbNmpUrh9JUxM88AADAVSUxUvr7D+nEFunEZin5VNHjp3eZRxqYTJJHPelfxygQAACqBAUDwEZMJpNNp95B8UaPHq05c+Zcsj86OlqPPfaYFi1aJEl65ZVX1KlTJ02aNKnYfmbMmGEpFjg5OemOO+7QjTfeqDZt2qh+/fpydXWVvb25OBIREaGmTZtKklXz0pe0JkB5pKamFtkufDO7NCWtHVBcv2XFFhdX1o3r8j73initrNWkSRM98cQTuu+++zRmzBitXbtWkvkm+pIlS4qsVZGUlHTF1ys8rZVkLtZMnjzZUiwIDAzU/fffrwEDBqhZs2aqVauWXFxcLK/JnDlzLNNvWfNzZ81ogcLfPw8PD6ufS1mq8vsIAABQ4fJypZj9kr2z5NfWvO/vP6RfHy2IsXOQGnY3jx5oOkhq1KNogYD/DwEAqgh3KwHACv7+/vrmm2907tw5rVplXnti+vTpGjZsWJEpcCTp9OnTWrx4sSTJzs5OK1euVHBwcIl9W/Pp7op28c3c9PR0q27wp6WlWd1vWbHFxdWEKWS8vLz09ddfq0mTJpYpgTZs2FCkYFD4tb7pppu0bNmyK77up59+ailEdOrUSevXr5eXl1eJ8ZXxc1f4+3dxUQoAAOCakZtlHiFwYpN59EDkdik7Rep0qzTuI3NMkwHmR2A/KbCPuUDgZN0HbgAAqEwUDADASnZ2dvrss8/UunVrpaWl6dy5c3rllVf05ptvFokLCQmxLC47atSoUosFknTixIlKy7kk3t7ecnJyskxLdPLkSaumnLl4nv6LFe7j5MmTVuUSERFhadepU8eqc652jRo1Urt27bRv3z5J5kWOC/Pz87O0o6OjK+Saa9assbSfe+65UosFUuX83BV+XqUtIA0AAFAj7ftO+muBdGqnlHfRFJHO3pKDc8F2nRbSnb9WaXoAAFjDztYJAEB10qhRI82cOdOy/f77719yw7fw/PQdOnQos8/169dXWH7WMplM6tSpk2W78GK1JTl69Kji4+NLjenSpYulvXnzZqtyKRzXtWtXq86pDlxcXCxtZ2fnIsd69eplae/Zs8fq0RilKc/PXV5enjZt2nTF17xY7969Le0tW7ZYFiAGAACoUdLipUO/Sqv+LR1fV7A/+bR5VEFeluReT2o7Vhr1hnT/RumpcOnG/9osZQAArEXBAADK6fHHH7dMvZKZmak33nijyHE7u4K31vT09FL7Sk9P11dffVXxSVqh8MiHb775psx4a/IcMmSIpb1ixQrFxsaWGn/mzBn99ttvxZ5fnWVlZenw4cOW7YsXlW7WrJnatGkjScrOztbnn39+xdcsz8/dzz//XGEjGwrr3bu3ZYqulJQUm/1sAwAAVKjUWGnf9+Y1B+b1kt5sJi25XdryvhS2oiCu9Q3STe9JD+2SnjgiTfpS6vVPyb+DZGdvu/wBACgHCgYAUE61a9fWQw89ZNn++OOPdfbsWct2s2bNLO0VK1ZY5rEvzuOPP66YmJjKSbQMd999t6W9devWUosGf//9t955550y+xw+fLhlAeesrKwiozEuZhiGHnroIeXk5EiSgoKCNHToUCuzrzrbtm3TW2+9VeZN+MLeeOMNJScnW7ZHjhx5ScxTTz1laT/33HPav3+/1f0Xd7O/8M/dL7/8UuK5Z8+e1aOPPlri8Svh7OysBx54wLL91FNPKSwsrFKuBQAAUCVWz5Hebiv9dI+08wvp7PkPhdRtI3WfJrUYVhBbp4XU9Q7JN4hFigEA1RYFAwC4DI899phlgd/09HT95z//sRwbMmSI3NzcJJlvtE+dOlWJiYlFzk9OTtZ9992njz76yKrFhitDy5Ytdeedd1q277nnHn355ZeXxO3cuVPDhg1TWlqanJycSu3Tzs5Or732mmV70aJFuvfeey9ZADclJUV33XWXfvrpJ8u+N954o8in5K8WCQkJ+te//qUmTZroscce065duyxrVFwsLi5Ojz76qGbNmmXZ16VLl2ILBlOmTLGMqEhJSVH//v318ccfW9aVuFhycrIWLlyowYMHFylYXXDjjTda2q+++mqxBaBdu3Zp0KBBioyMrLSfuyeffFJBQUGSpKSkJPXv31+LFy8u9jVLT0/XokWLNG3atErJBQAA4IrZO0v5OeZRAn0elCYvlP51XJqxVbrhHan51feBFwAArgSLHqNai46O1urVq7Vz507t3LlTu3fvVnp6ugIDA4sspApUNF9fX82YMUOvv/66JGnevHl68skn5ePjo9q1a+uJJ57QCy+8IElauHChfvvtN/Xq1UsNGzZUVFSU1q5dq7S0NDk4OOiDDz7Q1KlTbfI83n77bW3ZskVhYWHKysrSnXfeqRdeeEF9+vSRs7OzDh48qO3bt8swDI0fP17x8fFat25dqX1OmjRJ69ev17x58yRJn332mZYsWaLg4GD5+fkpNjZWa9asKVJEmDlzpsaPH1+pz/VKnT17Vu+8847eeecdeXt7q1u3bqpfv748PT2Vmpqqo0eP6q+//lJubq7lHD8/Py1cuLDYQoi9vb2+++47DRs2TLt371ZycrLuv/9+Pfnkk+rTp48aNmwoe3t7JSQkKCwsTIcOHbL0ffPNN1/S39SpU/Wf//xHR44cUVZWlv7xj3/olVdeUadOneTi4qIDBw5o586dkqROnTppxIgRl0ynVRG8vLz0008/adiwYYqNjVVcXJxuvfVWzZw5U3379lXdunWVmZmpY8eOadeuXcrIyCiyngYAAIDNpMZKG+dK7nWkAY+Z9/WeLjXpLzUdYNPUAACoKhQMUK0tXry40qbWAMry+OOP6/3331daWppSU1P1zjvv6MUXX5QkzZo1SxEREZY53M+dO1dkrn5JqlWrlubPn6/OnTtXdeoWtWvXVkhIiMaMGWO5mXz8+HEdP368SNxNN92kBQsWFPkUe2nef/99+fv766WXXlJWVpZSUlKKnSbHxcVFs2bN0jPPPHPlT6aSNG3aVIMGDdLGjRst00slJSUpJCSk1PNGjRqlefPmWaZoKo6vr682bdqkxx57TJ999plyc3OVnJysVatWlXiOq6urunXrdsl+Z2dnLV++XKNGjbJ8/w4dOqRDhw4VievXr5+WLFmiTz/9tNT8r0THjh21fft23XHHHZZFvWNiYrR06dJi4y+M1gEAALCJtDhp01xp+2dSbobk7GWebsi1lvlBsQAAcA2hYIBqzcvLS9ddd526d++u7t276+TJk3r88cdtnRauEXXr1tX06dP11ltvSZLee+89Pf7446pVq5bs7e315ZdfauLEifrkk0+0bds2JSQkqHbt2mrcuLHGjBmjadOmqUGDBjYfDdOgQQNt3bpVX331lRYuXKh9+/YpKSlJfn5+6tSpk6ZOnaqbb75ZpnLOw/rcc8/pH//4hz777DOtWrVK4eHhSkxMVK1atdSsWTONGDFC99xzzyULAl9tWrVqpbVr1youLk5r167Vxo0btX//fv3999+Kj49XZmam3NzcVLt2bbVu3Vo9e/bUpEmT1KFDB6v6d3V11YcffqinnnpK33zzjUJCQnTkyBHFx8crPz9f3t7eatasmTp16qTrrrtOI0eOlJeXV7F9tWzZUrt379a8efP0008/KSwsTNnZ2fL391eHDh102223adKkSbK3r/xF9wIDA7Vu3TqtWbNG33//vTZs2KCoqCglJyfL3d1dgYGB6tatm66//nrddNNNlZ4PAADAJdLPSZvflbZ9IuWkmfc17C4FPyO5eNs2NwAAbMRklDQRM1ANLV68WLfeemu5pyRKTk6Wt7e3kpKSSrwRV5bMzEyFh4eradOmcnFxuaw+AABXB97TAQCowXKzpHVvSNs+krLPT5NZv7MU/G/zIsYsWAwAqGHKc++TEQYAAAAAAODaYecoHVllLhb4dzAXClqOpFAAAICuoYLBrl279N1332n16tU6ffq0zp07J19fX/n7+6tz584KDg7WsGHD5O/vb+tUr0heXp4OHjyoHTt2aOfOndqxY4f27dunnJwcSdKgQYO0du3ay+o7OztbS5Ys0aJFi3Tw4EHFxMSodu3aatq0qcaPH68777xTderUqcBnAwAAAADAFcpMNo8maDlCqt9JsrOTRr4iZSZJrW+gUAAAQCE1vmAQGxurxx57TAsXLrzkWFRUlKKiorR7927Nnz9fM2bM0Pvvv2+DLCvGzz//rNtvv13p6ekV3vfhw4d16623as+ePUX2R0dHKzo6Wlu2bNGbb76p+fPna/To0RV+fQAAAAAAyiUrRdr2sbTlfSkjQTq9S7ptsflY04G2zQ0AgKtUjS4YnDx5UoMHD1Z4eLhlX6tWrdShQwf5+voqPT1dx44d0549eyrlJntVS0xMrJTncerUKV133XU6c+aMJMlkMmngwIEKCgrS2bNntXr1amVkZCg2NlZjx47VypUrNWTIkArPAwAAAACAMmWnSds/lTb9V8o4Z95Xp6XUcaJt8wIAoBqosQWDpKQkBQcHW4oFwcHBmjt3rjp27HhJbHZ2tkJCQpSSklLVaVYKPz8/9ejRw/JYtWqV/vvf/152f7fddpulWBAYGKhly5apU6dOluNxcXG65ZZbtGbNGuXk5GjixIk6duyYatWqdaVPBQAAAAAA62SnSzs/lzbOldLjzPt8m0uDnpbaj5fs7G2aHgAA1UGNLRg88cQTOn78uCRp8uTJWrhwoezti//PgZOTk0aOHHnF10xLS5O7u/tlnZuamioPD48ruv7IkSN14sQJNW7cuMj+bdu2XXafK1as0IYNGySZX6fly5erQ4cORWLq1KmjZcuWqWPHjjp+/LjOnTunN954Q6+88kqxfc6ZM0fPP//8ZeUTHh6uJk2aXNa5AAAAAIAaLCVK+mO2ZORJtZtKg5+W2k+Q7GvsrQ8AACqcna0TqAx79uzRZ599JkkKCAjQp59+WmKxoKJs2rRJTZs21bp168p97h9//KFmzZpd0Y19SfL397+kWHCl5s2bZ2lPnTr1kmLBBe7u7nrhhRcs2x9//LFyc3OLjXVzc5Ovr+9lPSr7+wgAAAAAqCYyk6W/Fkh5OeZt3yCp/6PSmHnSgzulTrdQLAAAoJxq5L+cH330kaU9Y8YMeXp6Vur1Dh06pNGjRys5OVnXX3+9Vq5cqf79+1t1bkhIiMaMGaOMjAyNHDlS27ZtU8uWLSs1X2ulpqZqzZo1lu277rqr1Pibb75Z999/v1JTU3Xu3DmtX7++2LUMnnzyST355JMVni8AAAAAoIbLz5dObJR2L5RCl0m5GZLJTup6h/n4df9n2/wAAKjmatwIg7y8PC1atMiyffPNN1f6NZs3b66BAwdKMk9LNGrUKG3evLnM89auXasbb7xRGRkZkszrLDRr1qxScy2PzZs3KysrS5J5BEGPHj1KjXdxcVGfPn0s2yEhIZWaHwAAAADgGpFwQlr7mvRuJ+nLG6V9i83FAt8WkqObrbMDAKDGqHEFgwMHDig5OVmS5O3traCgIOXm5mr+/Pm67rrr5O/vL2dnZzVs2FCjRo3Shx9+aLkpfrkcHR31ww8/WNZBSE1N1ahRo0qdYmjDhg264YYblJ6eLkm64YYbtGTJEjk4XD2DPg4dOmRpd+jQwarcunbtWuz5AAAAAABclt+ekv7bUVr7qpR4UnL2krrdKd29Wnpwh9Rhgq0zBACgxqhxBYMdO3ZY2gEBATp16pT69eunadOmKSQkRDExMcrOztaZM2e0cuVKPfDAA2rZsmWR8y6Hs7Ozli5dqqFDh0qSkpOTNWLEiGL73bRpk0aPHq20tDRJ0qhRo/TDDz/I0dHxinKoaGFhYZZ2YGCgVecUXkPh8OHDFZ4TAAAAAKAGMwzp5DYpttDfk3VaSjJJTQdJ4z+VHg+TbvyvFNBDMplslioAADXR1fNx9goSGRlZZHvUqFE6ePCgJKl169bq0aOH7O3ttW/fPu3atUuSdPLkSQ0ePFjr169Xt27dLvvaLi4uWrZsmUaPHq1169YpKSlJw4cP15o1ayyfvN+yZYtGjRql1NRUSdKwYcP0008/ydnZ+bKvW1ni4+MtbT8/P6vO8ff3t7TPnTtX4TldLDIyUl26dLFsZ2dnW/bXqVPHsr9fv35atmxZpecDAAAAALgMyWekvYukPd9K8X9LHW+Rxn9sPtZxktRimFSrcel9AACAK1bjCgaJiYmW9oEDByRJbm5uWrBggSZOnFgk9s8//9SkSZMUFxen9PR0TZ48WaGhoXJycrrs67u5uel///ufRowYoU2bNikxMVFDhw5VSEiIsrOzNXLkSKWkpEgyr1mwbNkyubi4XPb1KtOFooYkubq6WnVO4bjC51eWvLy8IoWNC/Lz84vsT0pKqvRcAAAAAADlkJMphf3PvIDx8T8lI9+839FNcnIviHP2ND8AAEClq3EFgwvT/BT2zTffaNy4cZfsDw4O1i+//KL+/fsrPz9fx44d08KFC3XXXXddUQ7u7u767bffNHz4cG3dulUJCQkaOnSo8vLyLOsrDBgwQMuXL7f6RrwtZGZmWtrWFlEKj5S4sJhzZWrSpIkMw7js8+fNm6d58+YpLy+vArMCAAAAAJTq8Arp5+lSZmLBvsZ9pS63S23HUCAAAMBGatwaBhd/Wr9Pnz7FFgsKHx8/frxle8mSJRWSh6enp1auXKnu3btLMk/vc2H0Q9++fbVixQq5u7uX0oPtFX4tL0z1U5bCC0hfzcWQC2bMmKHQ0NArXsMCAAAAAFCK1FjpxJaC7TotzcUCr4bSgCekh3ZJ036TukyhWAAAgA3VuIKBh4dHke3SigXFxWzevLnCcvH29tbbb799yf65c+dekufVqHCO1o4WKBxXHZ4jAAAAAKCS5GZLh36VFt0qvd1G+vFuKf/86O46zaW7V0sz90vX/Z/kG2TbXAEAgKQaOCWRr69vke22bduWeU6bNm0s7ZSUFKWkpMjT88o/0RAaGqoJEyZcsn/s2LFau3atWrRoccXXqEyFX8uYmBirzomOjra0fXx8KjwnAAAAAMBVLC9XOrFJOvyrdOBHKb3QmnOe9c0jDbzqm7cDetgmRwAAUKIaVzBo3bp1kW1rPuV+cXGgIgoGYWFhuu666xQbGytJ6tmzp7Kzs7Vnzx6dOXNGwcHBWrdunYKCrt5PUbRq1crSPnHihFXnnDx50tK++HsBAAAAAKjBEk9KHw+UMhIK9nn4SR0nS51vl+rxNyIAAFe7GlcwaN++fZHt1NTUMs9JSUkpsu3t7X1FORw9elRDhgyxfNq+W7duWrVqlfLy8jRkyBDt27dPp0+fthQNmjZtekXXqyyFR17s379fubm5cnAo/Udm165dxZ4PAAAAAKhB0s9JR1ZKp3dJ179l3ucdIDm4Sq4mqdVoqe1NUtB1kn2Nu/UAAECNVePWMGjatGmRG/ChoaFlnnPo0CFL28fH54oWIz527JiGDBmiM2fOSJK6dOmiP/74Q7Vq1ZKvr69Wr15tKWpERkYqODjY6k/vV7W+ffvK2dlZkpSWlqadO3eWGp+VlaWtW7datocMGVKp+QEAAAAAqlDiSWnrR9KCG6Q3m0s/T5d2fCrFHTUfN5mku/4nPXFUGjtPajmCYgEAANVMjSsYSNL48eMt7Z9//rnM+MIxAwcOvOzrhoeHa8iQITp16pQkqVOnTlq9erVq165tialbt67WrFljWVvhxIkTCg4OVmRk5GVft7J4eHjouuuus2wvWLCg1PiffvrJMlrDx8fnil5LAAAAAMBVICtFWveGeaqhuR2klU9JERskI0/yay8NelpyKjQVsE8zigQAAFRjNbJgMH36dDk6OkqSNm/erF9++aXE2O3bt+unn36ybN95552Xdc2TJ09qyJAhljn8O3TooNWrVxe78G+9evW0Zs0ayxoB4eHhCg4O1unTpy/r2pXpgQcesLQXLFiggwcPFhuXnp6uWbNmWbbvu+++MqcvAgAAAABcZfLzpOj9Bdv2ztLm96WovZJMUuO+0ohXpIf3SNM3ScHPFCxiDAAAqr0aWTAICgoqcqP7tttuK1IUuGDdunW64YYblJeXJ0nq3bu3brrppnJf79SpUwoODlZERIQkqV27dlqzZo3q1KlT4jn+/v76888/1bJlS0nmqYyCg4MVFRVV7utXpuuvv14DBgyQZJ5y6IYbbtC+ffuKxMTHx2vs2LH6+++/JZlHFzz11FNVnitwtWrSpIlMJpNMJpPlfeJid955pyWmpNE8CxYssMRcbnHzSlXUc7kaWPNcAAAArgm5WdKR36VfHpb+01r6aICUEmM+5uAkDXpSuuk981RD036T+syQfK7OtfgAAMCVqbEfAX/99de1a9cubdiwQWlpabr55pvVpk0b9ejRQ/b29tq3b5/++usvS3z9+vX13XffyWQylftarq6ulnUP2rRpozVr1qhu3bplnle/fn2FhIRo8ODB+vvvv+Xh4SEXF5dyX7+w0aNHW9ZPuODC4suStHPnTnXu3PmS81asWKEGDRoU2+e3336rnj17KioqShEREercubMGDRqkoKAgnT17VqtXr1Z6erokycHBQd99951q1ap1Rc8DqEqDBw/WunXrJEmzZ8/WnDlzrD53zpw5ev755yVJgwYN0tq1ayshwyt38uRJ/e9//9Mff/yhw4cPKy4uTomJiXJ3d5evr686duyoXr16aeLEiWrWrJmt0wUAAEBly0ySjv4hHf7V/DU7teCYs7d09rDk6Wfe7vugbXIEAABVrsYWDJydnbV8+XJNnz5dixYtkmRe3LjwAscX9OrVS99//70CAgIu61q+vr76448/dO+99+qTTz6Rn5+f1ec2bNhQISEhmjFjhr744osi6x1cjtDQ0FIXUU5LS9PevXsv2Z+dnV3iOY0aNVJISIhuvfVW7dmzR4ZhaO3atZfcGK1bt67mz59fZN0DALYVGRmpF154QQsWLFBubu4lxxMTE5WYmKhjx45p6dKlevrppzVkyBC98sor6tWrlw0yBgAAuIZlJEiuhf4mXP/W+amADMkwzPsMo2C72WCp9/3m/dH7pdVzih6/+OstCyUXbyknU3q7bdEigWd9qdVoqc0NUmB/88gCAABwzamxBQNJ8vb21rfffqv7779fX331lTZu3KjTp08rLy9Pfn5+6t27tyZNmqSxY8de1siCwvz8/EpdK6E0AQEBl31uVWndurW2bdumxYsXa9GiRTp48KBiYmJUq1YtNWvWTOPHj9ddd91V6jRMAKrWn3/+qZtvvlkJCQmWfSaTSR07dlRQUJB8fX2VkpKiqKgo7dy5U2lpaZKkkJAQ9e7dW1u3bqVoAAAAUNmSTps/5X9ouXRik/TQX+aFgyXp5Bbp79Uln+tWaM289HOlx0pS3vkPkDi6SI17S4knpdbXS61vlBp0kexq5KzFAACgHGp0weCCgQMHauDAgbZOo0pU5jzcTk5OuuOOO3THHXdU2jWAmsgW8+MvX75cN998s3JyciRJ7u7ueuyxxzRjxoxiR0FlZWVp9erVeu2117Rx40ZJUkZGxmVde8GCBVf12gUAAAA2F3/MXCA4tFw6vbPosRObCwoGPe6VWo6UTCZJpku/+jYvOK9uK2nsh8XHXfiAnJN7Qfykr4puAwAA6BopGADAteT48eO64447LMWCwMBArVq1Sq1atSrxHGdnZ11//fW6/vrrtXTpUt19991VlS4AAMC1wzCkL0ZIkdsK7TSZP+3f5kap9Q1S7cCCQ61GWt+3p7/U+Tbr4ykWAACAYlAwAIAa5r777lNiYqIkycPDQyEhIeVayHjcuHHq1KmTjAvz5AIAAKD88vOl039Jh36R+s2U3H3Nn/T3aiDZOUhNB5qLBK2uL1hcGAAAwMaYoBAAKlmTJk1kMplkMpkqfXqinTt3as2aNZbtV155pVzFgguaNWumoKCgy8rhzjvvtDzfkqYmmjNnjiVmzpw5kqTMzEx9/PHHGjx4sOrXry8nJyc1atRId9xxh0JDQy/pIzU1VfPmzVP//v1Vv359ubi4KCgoSDNmzNCpU6cuK/fDhw9r5syZatu2rby8vOTl5aWOHTvqueeeU3R0dLn6MgxDS5cu1dSpU9WyZUt5e3vLxcVFAQEBGjt2rL788stiF6IuLCIiwvI6NWnSxLJ/48aNuueee9S6dWt5e3vLZDJp5syZl/GMAQBAhcrLlY6vk/73hPROW+nzodLmd6WwFQUxQ5+X/vW39I+lUvdpFAsAAMBVhREGAFCDfPjhh5a2t7d3tZla6Pjx4xo/frz27t1bZP/p06f19ddf67vvvtOyZcs0YsQISdKOHTs0btw4nT59+pJ+PvjgA33zzTdatWqVevfubXUOn376qR566CFlZWUV2b9//37t379fH3zwgRYsWKCbbrqpzL727dunqVOnas+ePZccO3XqlE6dOqVly5bp1Vdf1U8//aS2bdtalWN2drYefvhhffzxx1bFAwCAKnJ0tRS6VDq8Qso4V7DfyVNqOVzyLfRBjMJTDgEAAFxlKBgAQA0SEhJiaY8ZM0Zubm42zMY6ycnJGjVqlI4cOSIvLy8NGjRI/v7+io6O1po1a5Senq6srCyNGzdO+/fvV05OjoYOHark5GTVqVNHAwcOlK+vr06ePKmQkBDl5OQoOTlZY8eOVVhYmLy9vcvMYdmyZZZP6Dds2FD9+/eXh4eHjhw5ok2bNik/P18JCQmaMGGCli9fbilcFGf9+vW68cYblZycLElydHRUjx491KJFCzk6OioiIkIbN25UZmamwsLC1LdvX23ZskVt2rQpM89HH33UUizo0KGDOnXqJEdHRx05ckR2dgwaBACgymSlSvZOkoOTeXvLe9Lxtea2q4/UerTUZozUbJDk4GyzNAEAAMqLggEA1BCnTp0qMuVRr169bJdMOXzwwQfKysrSvffeq//85z/y9PS0HDt16pSGDRumw4cPKyMjQy+++KIOHDiglJQUzZkzR88884ycnJws8QcPHtTQoUMVHR2tmJgY/fe//9WsWbPKzOHJJ5+UnZ2d3nzzTc2cObPIzffQ0FBNmjRJBw8eVE5Oju68806Fhoaqdu3al/QTHR2tiRMnWooFd9xxh1577TXVr1+/SFxMTIymT5+upUuXKikpSZMnT9bu3btlb29fYo6nTp3SBx98oICAAC1cuFADBgwocvzikREAAKACZadJUXul07ukE5ukYyHShC+k1tebj3eeItVpaV6ToHFfyZ4/tQEAQPXE/2IAoJAVK1YoLi7O6vjt27dXYjblc/H6CO3atbNNIuWUlZWlKVOm6JNPPrnkWKNGjfTZZ5+pf//+kqQvv/xSkjR79mzNnj37kvh27drprbfe0pQpUyRJixcvtqpgkJ2drddee02PPfbYJcfatm2r1atXq0OHDoqLi1N0dLTeeecdvfDCC5fE/vvf/1ZsbKwk6eGHH9Z///vfYq/n5+en77//XsOHD1dISIj279+vH374QZMnTy4xx7y8PLm5uWn16tVq2bLlJcednfn0IgAAFWr3QnNx4PQuKS5MMvKLHo/YVFAw6DjR/AAAAKjmKBgAQCE7duzQjh07bJ3GZTl37lyR7Vq1atkmkXJycnLSW2+9VeLxfv36qXHjxjp58qQk8832Z599tsT48ePHy8nJSdnZ2Tp8+LBSUlKKjFooTtOmTfX444+XeNzf31+zZs3Sww8/LEn6/PPP9fzzz8tkMllizp49q2+++cYS//rrr5d6TXt7e7388svq06ePJGnhwoWlFgwk6cEHHyy2WAAAAC5TXq509pB0Zre5MHDdLMnNx3xs7yIpYkNBrGcDqWFX86PlSKmedWsQAQAAVCcUDABby04r/bi9c8GQ5txsKT+n5FiTneToam4bhpSTXnrfDi6S3fkpUHKzpPzcUvq2lxxdzO38fCk3o4y+XaUL07rkZEpGXsmxdg7M7VoBUlJSimx7eHjYKJPyGTBggPz8/EqNad++vaVgcOONNxaZhuhirq6uCgoK0qFDh2QYhiIiItShQ4dS+7/tttvk4FD6P4lTpkzRo48+qry8PJ05c0ZhYWFq3bq15fjq1auVnZ0tyVy0cHFxKbU/yTxtlLu7u9LS0rRx48Yy42+55ZYyYwAAQAny86X4v6UzuwoKBNH7pNzMgpg2N0jNh5rbnW6RGvcxFwgadJE8/W2TNwAA14jE9GytPxqnqMQy7jlVkHsHNJOdnanswGsMBQPA1l5pUPrxiQukduPM7ZAXpM3vlRzboIt031pzOz1eejOo9L6n/io1PT8P+vKZ0t5vS45tMVy6/XtzOy5M+qB36X0/sFWqd34R1+/+IR39veTYTrdJ4z4svb8qMnv2bM2ZM8fq+Dlz5uj555+vvITK4eJP0aemptook/Jp3759mTGF1wuwZqolHx8fS/vCegKlufAp/7JyaNWqlUJDQyVJu3fvLlIw2LJli6W9b98+Pfjgg2X2WVhCQoLS0tLk7u5e7HFHR8cyCx8AAOA8w5AST0jnjktBQ8z7cjOkD3pdOrWQs5fUoLP5/9JejQr2d5lSZekCAHAtMgxDx86mas2hWK05HKu/TiQoL9+osuvf3b+p7ETB4GIUDACghih8k1ySEhMTbZNIOXl7e5cZU/jT/+WNz8kpZVTOeY0bNy4z5kLchYLB2bNnixw7c+aMpb1x40arRgxcLCEhocSCQe3atcscBQEAwDUrP8+8EHHkNvPIgTO7pYxz5tG6z5ySHJwkJ3dzUcDOQWrQtWDkgE9QwchYAABQqbJz87U9/JzWHI5RyOFYnYgvOjtGKz9PtWvgpaq4j194mmEU4M4DYGvPnin9uH2hqXqGzJIGP1NyrKnQHzpuvmX37VBoypQb50rXlzyPvEz2Be06razo27WgPenrsqckwhVr0qRJke3Q0FANGjTINsmUQ3n/ga6Mf9Dd3Nysiit8M//iKaCSkpKuOI/c3JKnBXN1dS3xGAAA17Tj66RV/5Zi9hfdb+doHvGadlbybmjed88aiZsDAABUqbjULK0NO6uQwzFafyROqVkFf/s62dupd5Cvhrapp+BW9RTgY93f56g83KUDbM2p+E8TF8vBSVLJc7cXYTKVs29nSVauI2BnV76+Hcueyx1XrlGjRgoMDNSJEyckSdu2bdP06dNtnFX1kJ5exnof56WlFaw5cvEUUIWLCW+//bYeffTRikkOAACULP6Y9NVN5razt3kNggZdzKMH/Npfuk4WxQIAACqdYRg6HJ2ikMOxWn0oRnsiE2UUmmmojoezrmtdT0Pa1FP/5nXk7swt6qsJ3w0AqEGGDBmi+fPnS5KWLVum9PR0qz89fy07efKkVesDREZGWtp16tQpcqzwws3R0dEVlxwAACgq/ZzkWtt88983SOo8xfxhlkFPSe6+ts4OAIBrUmZOnrYcj1fIoViFHI7V6YsWLm7XwEvXtfHTda3rqUNDbxYbvopRMACAGmT69OmWgkFiYqK++OKLci++ey3aunWrrr/++lJjEhMTdfjwYct2165dixzv1auXPvnkE0nSpk2bKj5JAACudblZ0vZPpfVvSNe/LXWYYN4/5n1GDgAAYAMxyZn683CsVh+K1aa/45SRUzAdtYujnfo3r6Mhrf00pHU9+Xsz+0R1QcEAAGqQHj16aMiQIQoJCZEkPfvss7rhhhsuWd+gLMePH5dhGAoKCqqELK8+ixYt0pw5c2Rvb19izMKFC5WXZ/7PT/369dWqVasix0eMGCEHBwfl5uZq8+bN2rt3rzp16lSpeQMAcE0wDOnQcumPWVJCuHnf/h8KCgYUCwAAqBL5+YYOnknW6kPmBYv3ny66ll99bxcNaV1P17Wppz7N6sjVqeS/sXH1omAAADXMJ598oq5duyo5OVkpKSkaMmSIVq1apRYtWlh1/s8//6xp06bpp59+umYKBseOHdM777yjJ554otjjMTExeuGFFyzbd9999yWLLzds2FBTpkzRggULZBiG7rjjDm3YsEFeXl5lXj8/P1/x8fGqW7fulT0RAABqmjO7zQsanzg/es/DTxryf1Ln22ybFwAANmQYhiLPZSg0KkmhZ5J18EyyQqOSFZWUWaV5mExSp0a1LOsRtK3vdcnfyqh+KBgAQA0TFBSkL7/8UhMnTlRubq7Cw8PVtWtXPf7445o+fXqRufYvyMrK0po1a/Taa69pw4YNNsjatpycnPTUU0/J0dFRDz30kOzs7CzHDh06pMmTJys2NlaSea2CkhY0fvnll7Vq1SpFRUVp37596tmzp959910NHz682PhTp07p+++/1wcffKBHHnmE6aMAALggLV76/d/S3kXmbQcXqe9DUr9HJGdP2+YGAEAVys7N19HYFHNR4Hxh4NCZZKVk5dokH3cnew1oUVdD2tRTcKt6quvpbJM8UHkoGABADTR27Fj99ttvmjhxohITE5Wamqrnn39eL7zwgjp16qSgoCD5+voqJSVFUVFR2rFjh9LS0izn29nZyd3d3YbPoGq98cYbmjlzpmbOnKm33npL/fv3l4eHh44cOaKNGzcqPz9fkuTg4KAvvvhCPj4+xfbToEEDLVu2TKNHj1ZcXJzCwsI0YsQINWzYUD179lTdunWVk5OjuLg4HThwQOHh4VX5NAEAqD7sHaSjf5jbHSdL182SvBvZNicAACpZUkaODkUVFAYOnknW37EpyskzLol1srdTS38Pta3vZX408FaTOm6yr+RP+Hu5OsrR3q7sQFRbFAwAoIYaOnSo9u7dqzlz5uirr75SXl6eDMPQnj17tGfPnmLPsbOz06hRo/Tyyy9fU/PvjxkzRs7OznrkkUd06tQpLV68+JKYWrVq6YsvvtDo0aNL7atHjx7auXOn7r77bq1Zs0aSdPr0aS1durTEc/z8/KyeMgoAgBopP0/au1hqOVJy95VcvKWb3pM8/aSG3WydHQAAFcowDEUlZRaaTihJoVHJijyXUWy8l4uD2jXwVtsGF4oDXgqq6yEnB27co+JRMACAGqxx48b64osvNHv2bP36669avXq1Dh06pLi4OCUlJcnDw0N16tRRp06d1LdvX02aNEmNGl2bn967//77NWDAAH300UdavXq1Tp06JUlq0qSJbrzxRj300EOqX7++VX0FBgZq9erV2rJli77//nutX79ekZGRSkhIkIODg3x9fdWiRQt1795dw4cP1+DBg+XgwD/JAIBr1PF15umHovdLPe+TRr9p3t+69CI9AADVQUZ2no7HpepITEqR9QYS03OKjW9Yy1VtG3ipXaHiQMNarqwNgCpjMgzj0jEtwDUmOTlZ3t7eSkpKsmqB0uJkZmYqPDxcTZs2lYuLSwVnCACoSrynA0AViDsq/TFLClth3nb2lgY/LfV5wLZ5AQBQToZh6Gxqlo7FpunY2dTzjzQdi03V6cTiRw042JnUvJ6HZdRAuwbealvfS95ujlWcPa4F5bn3yccZAQAAAABVJ/2ctO51acdnUn6uZLKXetwtDXraPB0RAABXqZy8fJ08l65jseaCwN+xqZYCQUpmyYsQ+7g7qXldjyJTCjWv5yEXR/sqzB6wDgUDAAAAAEDVSDwpfdRfykwyb7cYIQ1/UarbyrZ5AQBQSFJGjo5fGCVwNvV8gSBVJ+LTlZtf/GQtdiYpwMdNQXU9FFTX3fy1noeC6nrIx92pip8BcPkoGAAAAAAAKo9hSBfmXfYOkOp3ktLipREvSUFDbJsbAOCalp9vaO+pRO0+mVhkKqGzKVklnuPmZF9sUSDQ140RA6gRKBgAAAAAACqeYUjh66X1b0qDn5Ga9DMXDibMl1xrS3bcVAEAVL2cvHxtO35OKw9G6feDMYotoTjg5+V8vjBwvjhwvjBQ39uFBYhRo1EwAAAAAABUnNws6cCP0pYPpJj95n0hudK0lea2ex3b5QYAuCZlZOdp/dGzWnUgWmsOxyopI8dyzMPZQX2CfNXSz8NSIGhW112eLiw+jGsTBQMAAAAAwJVLi5d2fiHt+FRKjTHvc3STOt8m9Ztp09QAANeepIwchRyO0coD0Vp35Kwyc/Itx3zdnTS8nZ+Gt/NX3yBfOTsw6g24gIIBAAAAAODKhK2Uvp8q5Waatz0bSL3uk7pOldx8bJsbAOCaEZucqd9DY7TqYLS2HIsvskBxw1quGtneXyPa+atbYG3Z2zGtEFAcCgYAAAAAgPIxDCkhXPJpZt5u2M28r35nqc+DUruxkj1TOQAAKt+J+DStOhitVQdjtOtkgoyCGoFa+nloZDt/DW/nr3YNvFh7ALACBQMAAAAAgHVyMqX930tbP5CST0uPhkrOHpJHXemBLeYCAjdjAACVyDAMHYpKOV8kiNbh6JQixzsH1LKMJGhax91GWQLVFwUDAAAAAEDpUs9KOz+XdnwmpZ0173N0l6L3SYF9zdu+QbbLDwBQo+XnG9p1MsEykuDkuXTLMXs7k3o389HIdv4a1tZf/t4uNswUqP4oGAAAAAAAihcTKm2dJ+37XsrLMu/zalSwPoFrLZumBwCo2f6OTdEXmyL0R2iMzqZkWfY7O9hpYMu6GtnOX9e1qadabk42zBKoWSgYAAAAAAAuZRjS0vuk6P3m7YbdpN4PSG3HsD4BAKBSZebk6YO1x/Th2r+Vk2delMDTxUHXta6nke39NbBlXbk5cVsTqAz8ZgEAAAAApJwMad8SqUEXqX4n81oEfR6SDv9qXsg4oCfrEwAAKt224/F6Zul+HT+bJkka0rqe7uzbRL2b+crJwc7G2QE1HwUDoIIZhmHrFAAAV4j3cgDXlJQYacen0s4vpPR4qd04aeIC87FOk80PAAAqWVJ6jl797ZAW74iUJNX1dNbzN7XTqPb+MlGwBqoMBQOggtjZmavc+fn5Ns4EAHClLryXX3hvB4AaKfqAtPUDaf/3Ul62eZ93Yymgt23zAgBcUwzD0K/7ovT88lDFpZrXKbitV2M9NbK1vF2ZAg+oahQMgAri4OAgk8mkzMxMubu72zodAMAVyMzMlMlkkoMD/1UCUAMZhrT+LenPlwr2BfQyr0/Q+gbJnvc+AEDVOJWQrlnLDirkcKwkKaiuu14d31E9m/rYODPg2sX/BIEKYmdnJw8PDyUnJ8vX19fW6QAArkBycrI8PDwYYQCgZoraK/35srnddozU92GpUXfb5gQAuKbk5RtasDlC//k9TOnZeXKyt9MDwUGaPjhIzg72tk4PuKZRMAAqkJeXl06fPq20tDRGGQBANZWWlqbMzEyKvwBqrgadpdFvSka+1Oufts4GAHCNOXA6Sc8u3a99p5IkST2b+OiV8e3VvJ6njTMDIFEwACqUh4eH3N3dFRkZqYCAAIoGAFDNpKWlKTIyUu7u7vLw8LB1OgBQcTKTpdhQqfH59Ql63mvbfAAA15yM7DzNXX1En20MV16+IU8XBz07uo0mdw+QnR2LGgNXCwoGQAWys7NTo0aNdOrUKZ08eVIuLi7y8vKSi4uL7OzsZDLxDyAAXE0Mw1B+fr4yMzOVnJxsWYemUaNGTEcEoOZIjZUWTpDOHpGm/iIF9LR1RgCAa8z6I2f175/3K/JchiTp+o71NfuGtqrn5WLjzABcjIIBUMEuFA1SU1OVnJyss2fPyjAMW6cFACiFyWSSh4eHfH19WbsAQM1yLlz6epyUEC651ZHs+BMQAFB14lKz9NKvofp5zxlJUgNvF704tr2ua+Nn48wAlIT/LQKVwM7OTl5eXvLy8lJ+fr5yc3OVn59v67QAAMWws7OTg4MDRQIANU/UPumbm6W0WKlWoPSPpZJvkK2zAgBcAwzD0A9/ndLLKw4pMT1Hdibpzr5N9fjwlnJ35nYkcDXjNxSoZHZ2dnJycrJ1GgAAALiWhK+XFt0mZadIfh2kKT9Inv62zgoAcA2IiEvTs0v3a/OxeElSm/peem18B3UKqGXbxABYhYIBAAAAANQkB3+WfrpXysuWAvtLt34ruXjbOisAQA2Xk5evT9Yf17trjiorN18ujnZ6dGhLTevfVI72jOYFqgsKBrimzZs3T/PmzVNeXp6tUwEAAAAqxpld5mJBmxul8Z9JjiwoCQCoXLtOJujZn/brcHSKJGlAizp6aWx7Bfq62zgzAOVlMliNFVBycrK8vb2VlJQkLy8vW6cDAAAAXD7DkPYuljpOkuzsbZ0NAKAGS8nM0VurwvTV1hMyDMnH3Un/d0Mbje3cUCaTydbpATivPPc+GWEAAAAAANVZfp605nmpyx1SneaSySR1vtXWWQEAagDDMJSYnqPYlCzFJGdavp49//WvEwmKTcmSJN3ctZH+fX0b+bizjiNQnVEwAAAAAIDqKidT+uke6dByKfQXacY2ycHZ1lkBAK5y+fmGEtKzixQCYi1fsxSTkqnY5CydTclSdl5+qX0F+rrplXEd1K95nSrKHkBlomAAAAAAANVRZpK06DbpxEbJ3kka9jzFAgC4huXlG0rJzFFieo4SM3KUkJat2PM3/mMsX7N0NjlTZ1OzlJNn/Szltd0c5eflorqezvLzclE9T2fV83RW/VquGtSyrlwcmQIPqCkoGAAAAABAdZMSLX0zQYrZLzl7Sbd8KzUdYOusAAAVIDcvX0kZ5pv+iek5SsrINhcB0i/sy7a0k9KzLXHJmTkq70qlvu5OqleoAODn5aJ6Xs6q52n+6uflojoeTnJ2oCAAXCsoGAAAAABAdRJ/TPp6nJR4QnKvJ035Uarf0dZZAQCslJWbp4VbT+p4XOr5goD5hn9CeraS0nOUkpV7Rf17ODvI29VRtdwczxcCXOTn5ay6Xi7y83S2FAjqeDjLycGugp4VgJqCggEAAAAAVBdxf0tfjJDS46TaTaV/LJV8mto6KwCAlc4kZmj6N39p76mkMmM9XRxU281JtdwczxcAnFTrfCGg8HZtd0d5uxbEOdpTBABw+SgYAAAAAEB1UStA8m8vpZ8zjyzwqGfrjAAAVtp8LE4Pfbtb8WnZquXmqCm9AuXrYb7RX8vVSd5ujucLAk7ycnGQAzf+AdgABQMAAAAAuNrl5Uj2juZFjSd/IxmG5OJl66wAAFYwDEOfbQjXaysPKy/fULsGXvpoSjcF+LjZOjUAuAQFAwAAAAC4mm37WNq7WJr6i+TsaX4AAKqFtKxcPfnjPv1vX5QkaXzXhnplXAe5OLKIMICrEwUDAAAAALgaGYYU8qK04T/m7X1LpB732DYnAIDVwuPS9M+vd+pITKoc7EyafWNbTekdKJPJZOvUAKBEFAwAAAAA4GqTlyv9OlPa/bV5e8hzUve7bZoSAMB6q0Nj9OiSPUrJylVdT2d9eHtXdW/iY+u0AKBMFAwAAAAA4GqSkyn9cJcUtkIy2Uk3vCN1u9PWWQEArJCfb2jumqN6d81RSVL3wNr64PauquflYuPMAMA6FAwAAAAA4GphGNKKx83FAntnacIXUpsbbJ0VAMAKSek5mrlkt/4MOytJmtonUP++vq2cHOxsnBkAWI+CAQAAAABcLXZ/Y36Y7KRbv5WaD7V1RgAAKxyKStY/v/5LJ8+ly9nBTq+O76DxXRvZOi0AKDcKBgAAAABwtWg6QPLvKLUbS7EAAKqJZXtO66kf9ykzJ1+Narvqoynd1L6ht63TAoDLQsEAAAAAAK4WtZtId/8h2TvZOhMAQBly8vL16orD+mJTuCRpQIs6eveWLqrtzns4gOqLggEAAAAA2FJ+nrTrS6nLHZK9g+TIwpgAcLU7m5KlGd/u0vbwc5KkGcFBemxYK9nbmWycGQBcGQoGAAAAAGBLf74sbfiPFPabdNt3kombTQBwNdt1MkHTv/lLMclZ8nB20FsTO2lke39bpwUAFYKCAQAAAADYyuH/mYsFktRxMsUCALiKGYahb7ef1JxfDionz1BQXXd9/I/ual7Pw9apAUCFoWAAAAAAALYQf0xaer+53Wu61GGCbfMBAJQoMydPs5Yd0Hc7T0mSRrX315sTO8nDmVtrAGoW3tUAAAAAoKplp0lLpkhZyVJAb2n4i7bOCABQgtOJGZr+zV/adypJdibpXyNa6/5BzWRiVBiAGoiCAQAAAABUJcOQfnlYig2VPPykSV9K9o62zgoAUIxNf8fpoUW7dS4tW7XdHPXurV00oEVdW6cFAJWGggEAAAAAVKXtn0gHfpBM9tLEBZInC2UCwNXGMAx9sv64Xl95WPmG1L6hlz68vZsCfNxsnRoAVCoKBgAAAABQlZoMkHyCpB73SIF9bZ0NAOAiqVm5evKHvVqxP1qSNKFbI700tr1cHO1tnBkAVD4KBgAAAABQlfzaSvdvkBz5lCoA2Fp2br5OnktXRFyawuPSFB6fps1/xykiPl2O9ibNurGdpvRqzHoFAK4ZFAwAAAAAoLLl5Uj7v5c63iLZ2UlO7rbOCACuGbl5+TqdmGEuCMSlmYsD8ekKj0vV6YQM5RuXnlPP01kfTumqboE+VZ8wANgQBQMAAAAAqGyr50hb3peOr5PGf2zrbACgxsnPNxSVnKnws+ZRAhEXCgNxaYpMSFdOXjFVgfPcnOzVxNddTeuYH03quOu61vVU292pCp8BAFwdKBgAAAAAQGU68JO5WCBJbW6wbS4AUM3Fp2bpaGzq+VECaQo/m6aI+DSdiE9XVm5+iec5Odipia+bpSDQ1Nf8tVkdd9X1dGbKIQA4j4IBAAAAAFSW2EPSsgfN7f6PSm1utG0+AFAN5eUbWhsWq2+2ntDaI2dllDBYwNHepAAfN0sxoPCIgfpeLrKzoygAAGWhYAAAAAAAlSEzWVoyRcpJk5oOkoKfs3VGAFCtxCZnasmOSC3aflJnkjIt+xv7uFlGBzTxdbMUBxrWcpWDvZ0NMwaA6o+CAQAAAABUNMOQfp4uxf8teTWUJnwh2fPnFwCUJT/f0OZj8Vq47YT+CI1R7vkViWu5OWpit0a6tWdjNavrYeMsAaDm4n+sAAAAAFDRNv1XOvyrZO8kTfpacq9j64wA4Kp2Li1bP/wVqW+3nVREfLplf/fA2rq9d2ONal9fLo72NswQAK4NFAwAAAAAoKIF9pU860uDnpQadbN1NgBwVTIMQztPJGjh1hNasT9a2XnmRYs9nB00vmtD3darsVr7e9k4SwC4tlAwAAAAAICKFtBTmrFNcuZGFwBcLDkzRz/vPq2FW08qLCbFsr99Qy9N6RWoGzs1kLszt6wAwBZ49wUAAACAipCbJYWtkNqOlUwmycXb1hkBwFVl/6kkLdx2Qsv2nFFGTp4kycXRTmM6NdTtvRurY6Natk0QAEDBAAAAAAAqxMqnpZ1fSL0fkEa+autsAOCqkJ6dq+V7z2jhtpPadyrJsr9FPQ9N6R2osV0aytvV0YYZAgAKo2AAAAAAAFdq90JzsUAmKWiIrbMBAJsLi07Rt9tO6Kddp5WSlStJcrK30+gO/rq9d6C6B9aWyWSycZYAgItRMAAAAACAKxG1V/rfY+b24GekFsNsmw8A2EhWbp5+2x+thdtOaEdEgmV/oK+bbuvZWBO6NZKvh7MNMwQAlIWCAQAAAABcrowEack/pNxMqcVwaeC/bJ0RAFS5zJw8fbUlQh+tO65zadmSJHs7k4a18dPtvRurX1Ad2dkxmgAAqgMKBgAAAABwOfLzpZ/ukxJPSLWbSOM/kezsbJ0VAFSZ/HxDv+w9ozdXhel0YoYkqb63i27t2ViTewTIz8vFxhkCAMqLggEAAAAAXI71b0pHf5ccXKRJX0uutW2dEQBUmc3H4vTKikM6cDpZkuTv5aLHh7fUuC4N5WBP8RQAqisKBgAAAABwORp1MxcJRrwq1e9o62wAoEociUnRa78dVsjhWEmSh7ODpg8O0rR+TeXqZG/j7AAAV4qCAQAAAABcjuZDpYd2SW4+ts4EACpdTHKm3vnjiL7bGal8Q3KwM+m2Xo318HUtVIeFjAGgxqBgAAAAAADWyk6TwjdIrUaatykWAKjhUrNy9cm6Y/p0Q7gycvIkSSPb+evJka3UrK6HjbMDAFQ0CgYAAAAAYA3DkJY/Iu3/XhrynDTwX7bOCAAqTW5evhbviNTc1UcVl5olSerauJaeHd1G3ZtQLAWAmoqCAQAAAABYY9tH5mKByV5q3NfW2QBApTAMQ3+Exui1lYd1/GyaJKmJr5ueGtlaI9v7y2Qy2ThDAEBlomAAAAAAAGWJ2CSt+re5PeJlqUk/2+YDAJVgT2SiXllxSNvDz0mSfNyd9PCQ5rqtV6CcHOxsnB0AoCpQMAAAAACA0iSfkb6/UzLypA4TpV732zojAKhQJ+PT9caqw/p1X5QkydnBTnf3b6r7BwfJy8XRxtkBAKoSBQMAAAAAKElulvTdHVJarFSvnXTjfyWm4wBQQySkZeu9kL/19dYI5eQZMpmk8V0a6fHhLdWglqut0wMA2AAFAwAAAAAoycpnpFM7JBdv6ZZvJCd3W2cEAFcsMydPX26O0Pt//q2UzFxJ0oAWdfTMqDZq28DLxtkBAGyJggEAAAAAlKRJP2nfEmn8Z5JPM1tnAwBXJD/f0LK9p/XWqiM6nZghSWrt76lnR7fRwJZ1bZwdAOBqQMEAAAAAAErS/mapWbDk5mPrTACgXPLyDaVl5yotK1epmbk6EZ+uuWuO6MDpZEmSv5eLHh/eUuO7NpK9HVOtAQDMKBgAAAAAQGHp56TofVKzweZtigUAqkhuXr7SsvKUkpWjtKw8pWblKjWr4Ka/pZ1VXLtofHp2XrHX8HB20PTBQZrWr6lcneyr+BkCAK52FAwAAAAA4IL8POmHadLxtdIN70jd77J1RgBquD9CY/TKikM6k5ihrNz8Cu/fwc4kd2cHebo4aGgbPz00pLl8PZwr/DoAgJqBggEAAAAAXBDyknT8T8nRTWrUw9bZAKjBcvPy9fYfR/TB2mOXHHNysJOns4Pczz88nO3lYWk7FG27FI5xlPtFsc4OdjKZmHIIAGAdCgao1qKjo7V69Wrt3LlTO3fu1O7du5Wenq7AwEBFRETYOj0AAABUJ4eWSxvfNrdvek/yb2/bfADUWHGpWXp40W5tPhYvSbqrXxNN69dUnudv/jva29k4QwDAtYqCAaq1xYsX69FHH7V1GgAAAKjuzh6Rlk43t3s/IHWYYNt8ANRYf504pwcW7lJMcpbcnOz/n737jq+qPvw//rrZJCEJe28UUKYsRdmogFitq+ICnFVrW22r7a+ttX67tda2WrVVwY3WhQNRAVEEZMqQKcjeMyEJmff+/rgSpaJCSDgZr+fjcR8559xz7nkHeUhy3ud8Pvz5ws6c26Vx0LEkSQIsDFTJpaWlMXjwYHr06EGPHj3YsGEDP/nJT4KOJUmSpMokfz88fzkU7IcWp8OZdwedSFIVFIlEGDdzHb9/czlF4Qht66fy8BWn0LZ+zaCjSZJUwsJAldrVV1/N1VdfXbI+fvz4ANNIkiSp0olE4NWbYNcqqNkILh4HsfFBp5JUxeTkF3HHS4t5Y/FWAEZ0bsSfL+xMSqKXZSRJFYv/MkmSJEmq3lr3h9VT4JKnILV+0GkkVTGrd+zn+08vYPWObOJiQvzqnA6M6tPSiYglSRVStZxF57bbbiMUCpW8WrZsGXSkMlNcXMzixYt57LHHuPHGG+nRowcJCQkl3+uAAQNK/dkFBQU89dRTDB8+nBYtWpCUlESjRo3o06cP9957L7t27Sq7b0SSJEk6HkIh6Hkt/HgJNOsZdBpJVcxri7bwnQdmsHpHNg3Tknj+hlMZfXorywJJUoVV7Z4wmDNnDn//+9+DjlEuXn31VS6//HJyc3PL/LNXrFjByJEjWbhw4SHbt23bxrZt25g1axb33HMPY8eOZfjw4WV+fkmSJKlM7dsI2duhaY/oekqdYPNIqlIKisL8YeJyxs1cB0CfNnX4x8hu1E1NDDaYJEnfoloVBoWFhVx77bWEw+Ggo5SLffv2lUtZsGnTJgYPHsyWLVsACIVC9OvXjzZt2rBz504mT57MgQMH2LFjB+effz6TJk1i0KBBZZ5DkiRJKhOFefD8FbB9KVz0GJx0XtCJJFUhWzMPcPMzC1iwYR8ANw9sw21ntiM2xqcKJEkVX7UqDP785z+zZMkSAC677DKeffbZgBOVjwYNGtCzZ8+S19tvv31MT1VcdtllJWVBixYtmDBhAl26dCl5f9euXVx66aVMmTKFwsJCLr74YtasWUNGRsaxfiuSJElS2YpEYOJPYOtCqFEbGncLOpGkKmTG6l388LmP2Z1TQM2kOP52SVeGnNQg6FiSJB2xajOHwYoVK/jd734HwOWXX86ZZ55Z5ufIyckp9bHZ2dnHfP6hQ4eyfv16tm3bxuuvv86dd97JsGHDjunC/cSJE5k+fToACQkJvP7664eUBQB169ZlwoQJtG7dGoA9e/bwl7/85Ws/86677jpkDomjea1bt67U34skSZLE/HHw8dMQiok+XZDRPOhEkqqAcDjCg++t5srHZrM7p4CTGqXxxi1nWBZIkiqdalEYRCIRrr32WvLz86lVqxb33XdfmZ9jxowZtGrVivfff/+oj3333Xdp3bo1s2fPPqYMDRs2pHnzsv2F58EHHyxZHjVqFJ06dTrsfikpKdx9990l64888ghFRUWH3Tc5OZk6deqU6hUbG1um358kSZKqkU3zYOLPosuDfg1tHEZT0rHLzC3k+qfmcc/bKwlH4JIeTXn5pj60qJMSdDRJko5atSgMHnroIWbMmAHAPffcQ/369cv085cvX87w4cPZuXMn55xzDh9++OERHzt16lTOO+88du7cydChQ1m1alWZZjsW2dnZTJkypWR9zJgx37j/hRdeSGpqKhB9yuCDDz447H633347u3btKtWrWbNmZfcNSpIkqfrI3gHPXwnhQmg/As64NehEkqqApVsyOfeBD5m8fAcJcTH8+cJO/OWiLiTFe7ObJKlyqvKFwcaNG/n5z38OQN++fbn66qvL/Bxt27alX79+QHRYomHDhjFz5sxvPW7atGmce+65HDhwAICBAweWDOtTEcycOZP8/Hwg+gRBz549v3H/pKQkTjvttJL1qVOnlms+SZIk6YgUF8GLV8P+LVD3RDj/IQg5+aikY/PCvI1c8K+ZbNiTS7PaNXj5xj58r6fDnEmSKrcqXxjcdNNN7N+/n4SEBB555BFC5fCLQXx8PC+++CJDhw4FonfmDxs27BuHGJo+fTojRowgNzcXgBEjRvD8888TF1dx5qFevnx5yXKnTp2OKNspp5xy2OMlSZKkwIRioHV/SEyH7z0DSWlBJ5JUieUVFvPzlxZz+4uLyS8KM6h9fd74QV86NkkPOpokScesShcG48eP54033gDgjjvuoEOHDuV2rsTERF555RWGDBkCQFZWFmeffTZz5879yr4zZsxg+PDhJZMkDxs2jBdffJH4+Phyy1caK1euLFlu0aLFER3z5TkUVqxYUeaZJEmSpKMWEwP9fgY//BjqnRh0GkmV2MY9uVz08EzGz91ITAh+dnY7Hr2qB+nJFev3eUmSSqvKFga7d+/mhz/8IQAnnngiv/zlL8v9nElJSUyYMIH+/fsDkJmZyVlnncWCBQtK9pk1axbDhg0jOzsbgDPPPJOXX36ZxMTEcs93tHbv3l2y3KBBgyM6pmHDhiXLe/bsKfNM/2vjxo3UrVu35HX99dcfdvt5551X7lkkSZJUwexYHn0dlFInuCySKr2pK7Zzzj+m88nmLGqnJPDk1b25eWBbYmIc4kySVHVUnPFvytitt97Kzp07AXj44YeP2wX55ORk3nzzTc4++2xmzJjBvn37GDJkCFOnTqWgoIChQ4eyf/9+IDpnwYQJE0hKSjou2Y7WwVIDoEaNGkd0zJf3+/Lx5aW4uPiQYuOgcDh8yPbMzMxyzyJJkqQK5MA+GH8Z7N8Ol42HVv2CTiSpkioOR7h/8ir+OXU1AN2aZ/DgZafQOOPIfk+WJKkyqZKFwTvvvMNTTz0FwKhRoxg4cOBxPX9KSgpvvfUWZ511Fh999BF79+5lyJAhFBcXk5WVBUQnYH799deP+EJ8EPLy8kqWExISjuiYLxczBydzLk8tW7YkEomU+vgHH3yQBx98kOLi4jJMJUmSpECFw/DKDbDnM0hvBvVPDjqRpAouJ7+IbVl5bC955bMtM48d+/NYvSObVdujN8SN7tOS/ze8AwlxVXbABklSNVflCoOcnBxuuOEGAOrUqcO9994bSI6aNWsyadIkhgwZwrx58w65271Pnz5MnDiRlJSUQLIdqS8/+VBQUHBEx+Tn55csV+Qy5KCbb76Zm2++maysLNLTnaBKkiSpSph+L6yaBLGJ8L2nHIpIqsYKisLszP784n9W3uelQH5JMbAtK48dWflk5xd94+fUiI/lTxd24ryuTY5TckmSglHlCoNf/vKXrFu3DoC//vWv1K1bN7As6enp3HffffTrd+jjz/fffz+pqakBpTpyX854pE8LfHm/yvA9SpIkqQqJRGD+OHjvD9H1EX+Dxt0CjSRVR3mFxWzLzPvWi/BloTgcYXdO/iFPBGzLjJYCO/bnsSv7yG5+A6iZGEf9tEQapifRoGYSDdKTaFAzut61WS0aplfM4YQlSSpLVaowWLBgAf/85z+B6PwAo0aNCjTPsmXLuOiii76y/fzzz2fatGmccMIJAaQ6cnXqfHEn1vbt24/omG3btpUs165du8wzSZIkSYdVkANv/gQWPRdd73kddLs82ExSFROJRNiXW8jWzC/uzt+W+fnr8zv2t2bmkXmgMOioh4iPDVG/ZlK0CEhLpEFaEg3SkmiYlhQtCD5fT0msUpdIJEkqlSr1r+HixYsJh8MAbNiwgVNPPfVr9z04ITLA1q1bD9n317/+Neecc84xZVm5ciWDBw9mx44dAPTq1YuCggIWLlzIli1bGDhwIO+//z5t2rQ5pvOUp3bt2pUsr1+//oiO2bBhQ8ly+/btyzyTJEmSdFgr34qWBaEYGHwn9PlR0ImkSqWwOMyO/flfKQD+dz2/KHxEn5ecEEtaUjyhUPnmDgG1UhI+v/gfLQQOFgANPl+vnZJAqLyDSJJURVSpwuDL1qxZw5o1a45o34KCAmbPnl2y/uUyoTQ+/fRTBg0aVHK3fffu3Xn77bcpLi5m0KBBLF68mM2bN5eUBq1atTqm85WXDh06lCwvWbKEoqIi4uK++a/MggULDnu8JEmSVK46XgibF0C7YdCqb9BppOMmHI6QXxQmr7CYA5+/8j5/HSg4dHv+519zC4rZlZ3Ptsz8kicFdmXnE4kc2TnrpCTQMD16h36Dz782/PLX9CRqJsZ5kV6SpEqoyhYGQVmzZg2DBg1iy5YtAHTr1o13332XjIwMACZPnsygQYP45JNP2LhxY0lp0KJFiwBTH16fPn1ITEwkPz+fnJwc5s2b941PbeTn5/PRRx+VrA8aNOh4xJQkSVJ1VJQP794ZLQqa9YJQCIb+IehU0jH7eMNeXlu0hawDReQVFZNX8EUJcKAw/EUZUFjMgYLiI77j/0jEx4ZKhuo5WAQ0Sv98+J70L4bwSYyLLbNzSpKkiqVKFQajR49m9OjRR7TvuHHjGDNmDAAtWrQomSj5WKxdu5ZBgwaxadMmALp06cLkyZOpVatWyT716tVjypQpDBw4kGXLlrF+/fqS0qBZs2bHnKEspaamMnjwYCZOnAhE/8y+qTB4+eWX2b9/PxCdv+B/J3uWJEmSysS+DfDCKNiyAFa8CT+YB/FORqrKKxKJ8NFne3jwvdV8uHpXqT8nITaGpPgYaiTEkhQfS4346Nek+BhqxMdGt8fFkhgfS93UhJJy4OBTAbWTE4iJ8akASZKqsypVGARpw4YNDBo0qGQM/06dOjF58uTDTvxbv359pkyZwoABA1i5ciVr164tKQ2aNGlyvKN/o5tuuumQwuCWW27h5JNP/sp+ubm53HnnnSXr119//bcOXyRJkiQdtVVvw8vXQ94+SMqAc/5qWaBKKxKJMG3VTh6cupp56/cCEBsT4jtdGnNig5rU+NLF/y8XANGL/zEkxkVLgIPbY73YL0mSjpFXdMvApk2bGDhwYMlTCieffDJTpkyhbt26X3tMw4YNee+99xgwYACrVq1izZo1JaVBo0aNjlPyb3fOOefQt29fpk+fTn5+PiNGjGDChAl07ty5ZJ/du3czcuRIVq9eDUSfLrjjjjuCiixJkqSqqLgI3vs9fHhfdL3xKXDJE5DRPNhcUimEwxHeWbaNB95bzSebs4Do0wGX9GzKDf3a0Kx2csAJJUlSdWVhUAZq1KhBSkoKEJ3od8qUKdSrV+9bj2vUqBFTp05lwIABrF69mtTUVJKSju3uqOHDh5fMn3DQwcmXAebNm0fXrl2/ctzEiRNp3LjxYT/z2WefpVevXmzdupV169bRtWtX+vfvT5s2bdi5cyeTJ08mNzcXgLi4OF544YWSORskSZKkY7Z/O7x0DaybHl3vdT2c9TuISww2l3SUiorDvLF4Kw++t5pPd2QDUCM+lst7N+e6fq1pkObTMpIkKVgWBmWgTp06vPvuu1x33XX8+9//pkGDBkd8bJMmTZg6dSo333wzjz/++CHzHZTGwXkRvk5OTg6LFi36yvaCgoKvPaZp06ZMnTqVkSNHsnDhwuhjs9OmMW3atEP2q1evHmPHjmXw4MGlzi9JkiR9xScvRsuChFT4zj+iEx1LlUhBUZiXF2zioffXsH539GarmolxjOrTkqvPaEXtlISAE0qSJEVZGJSRBg0a8Nprr5Xq2GbNmpX62OOlffv2zJ49m/Hjx/Pcc8+xdOlStm/fTkZGBq1bt+aCCy5gzJgx3zgMkyRJklQqvW+EzE3QfQzUOzHoNNIRyyssZvycDTzywWdszcwDoFZyPNec0YorT2tJeo34gBNKkiQdKhSJRCJBh5CClpWVRXp6OpmZmaSlpQUdR5IkqXrL3QNv3gb9bocGJwWdRjpq2flFPP3Reh6d/hm7sqNPc9evmcj1/VpzWe/mJCd4754kSTp+jubapz+lSJIkSao4Ni+AF0ZB5gbYvRqu/wBiYoJOJR2RfbkFjJ2xjnEz15F5oBCAprVq8P3+bbioe1OS4mMDTihJkvTNLAwkSZIkBS8SgbmPwtv/D4oLoFYrOO9BywJVCjv35/Poh5/x9Kz15BQUA9C6Xgo3DWjLeV0bEx/r32NJklQ5WBhIkiRJClZ+Nrz+Q/jkpeh6+xFw/r8gKT3YXNK32LLvAP/+4DOem7OB/KIwAO0b1uQHg9oyrGMjYmNCASeUJEk6OhYGkiRJkoKzYzm8cBXsWgUxcTDkt3DazRDyQqsqrvW7c3ho2hpeWrCJwuLotIBdm2Vwy6C2DGpfn5B/fyVJUiVlYSBJkiQpOIufj5YFNRvDxeOgee+gE0lfEYlE2LzvAJ9szmTSJ9t4bdEWwtGegFNb1+aWQSfQp00diwJJklTpWRhIkiRJOr6KCiAuIbo88JcQCUOfH0JK3WBzSUTLgS2ZeSzZlMmSzftYsjmLTzZnsien4JD9BrSrxw8GtqVHy9oBJZUkSSp7FgaSJEmSjo/iQpj3OEz/K4x5C+q0gdh4OPPuoJOpmopEImzNzGPJ5szPC4Lo63/LAYC4mBDtGtakS7MMLuvVnI5NnGNDkiRVPRYGkiRJksrf6skw6f/BrpXR9Tn/gWF/CjaTqpVIJMK2rDwWb8rkk8+LgSWbMtn9NeXAiQ1q0qlJOp2aptOpSTrtGtYkKT42gOSSJEnHj4WBJEmSpPKzazW880tYNSm6nlwHBv0KThkVbC5VaQfLgSWflwOLN0e/7sr+ajkQW1IOpNGpaQadmqTT3nJAkiRVUxYGkiRJkspeXia8/xeY/QiECyEmDnrdAP1vhxoZQadTFVMcjvDBpzv5eMM+lmyKzjuwKzv/K/vFxoQ4oX4qnT9/aqBjk3Q6NEqzHJAkSfqchYEkSZKksrd7Ncx6ILp8wllw9h+g7gnBZlKVE4lEmLpiB3+etIJV27MPee9gOXBwWKGOTdI5yXJAkiTpG1kYSJIkSSobm+dD41MgFIIm3aH/HdC0J5xwZtDJVAUt2LCXP721gjlr9wCQXiOeIR0aRJ8eaJpOh4Zp1EiwHJAkSToaFgaSJEmSjs3e9fDur2HZBLjwMeh0UXT7wP8XbC5VSWt2ZnPv2yt565NtACTExTDm9Jbc1L8t6cnxAaeTJEmq3CwMJEmSJJVOfjZ8+DeY+U8ozodQTHQoIqkc7MjK4/4pn/L83I0UhyPEhODCU5py65kn0jijRtDxJEmSqgQLA0mSJElHJxyGJS/A5Ltg/9botlb9YOifoMHJgUZT1bM/r5B/f/AZj05fy4HCYgAGt6/P7UPb065hzYDTSZIkVS0WBpIkSZKO3J7P4KXrYPO86HqtlnDW76H9OdG5C6QyUlAU5pnZ6/nn1NXsySkAoFvzDH4+tD29W9cJOJ0kSVLVZGEgSZIk6cgl14G96yAhFfr9FE69CeISg06lKiQcjvDGkq3c+/ZKNuzJBaB13RRuH9qOs09uSMhiSpIkqdxYGEiSJEn6eoUH4KOHoPtoSK4NSelwyRNQpy3UbBh0OlUxM1bv4k9vrWDJ5kwA6tVM5MdDTuCSHs2Ij40JOJ0kSVLVZ2EgSZIk6asiEVj2KrxzJ2RugKwtcM690fdanhFoNFU9S7dk8qe3VjD9010ApCbGcUO/1lzTtxXJCf7aKkmSdLz4k5ckSZKkQ21dBG/9HDbMjK6nNYEWpwWbSVXSxj25/PWdlby6cAsA8bEhLu/dglsGtaVOqkNdSZIkHW8WBpIkSZKiIhF451cw60EgAnE14IwfQ58fQkJy0OlUhezJKeCBqat5+qP1FBSHAfhOl8b85KwTaVEnJeB0kiRJ1ZeFgSRJkqSo2Y/ArAeiyx0vgjN/C+lNg82kKuVAQTGPz1jLw9PWsD+/CIAz2tbl58Pa07FJesDpJEmSZGEgSZIkCcLh6JwFAGf/EU67KdA4qlqKisP8d/4m/vbuKnbszwfgpEZp/HxYe/qdWC/gdJIkSTrIwkCSJEkSxMTAVRNg8QvQ7Yqg06iKyCssZtrKndzz9grW7MwBoGmtGvz0rHZ8p0tjYmJCASeUJEnSl1kYSJIkSdVZuBgiYYiNh7hEOOXKoBOpktqTU8CyLVks25r5+dcs1uzMoTgcAaBWcjw/GHQCV5zanMS42IDTSpIk6XAsDCRJkqTq7L0/wLrpcPE4SGscdBpVAuFwhA17clm2NaukGFi2JYttWXmH3b92SgIjezXjhv5tSEuKP85pJUmSdDQsDCRJkqTqatXbMP3e6PKGj6DjBcHmUYWTV1jMqu37DykGlm/NIqeg+LD7t6yTzEmN0+jQMI2TGkdfDdOSCIUcekiSJKkysDCQJEmSqqO96+Dl66PLva63LBC7s/NZvnX/1w4p9GUJcTG0b1iTkxp9Xgw0SqNdw5rU9AkCSZKkSs3CQJIkSapuCvPghasgbx806QFn/T7oRDrOdmTlMX/9XpYewZBCtZLjOblxekkxcFLjNFrXTSEuNuY4p5YkSVJ5szCQJEmSqptJd8DWRVCjdnTugriEoBOpHEUiEdbtzmXu2j3MWbeHuev2sH537mH3PTik0BdPDqTTIC3RIYUkSZKqCQsDSZIkqTpZ+CzMHweE4MJHIaNZ0IlUxorDEZZvzWLu5+XA3HV72bk//5B9QiFo3zCNLk2/eHKgfaM0UhP9FVGSJKk686dBSZIkqboIh2H2I9HlAb+AtoODzaMykVdYzOJNmcxdt4c5a/ewYP1e9ucXHbJPQmwMXZql07NlbXq2qk33FrVIc74BSZIk/Q8LA0mSJKm6iImB0W/CvMfgtFuCTqNSysorZP76vcxdG32CYNHGTAqKw4fsk5oYR/cWtejVqjY9W9amc9N0kuJjA0osSZKkysLCQJIkSarqIpHoKyYGElPh9B8FnUhHYcf+POau3VvyBMGKbVmEI4fuUzc1kV6takWfIGhZmw6N0oiNcd4BSZIkHR0LA0mSJKmqm/lPWPsBXPBvSK4ddBp9i/15hbyzdDsffbabuev2sO4wExS3qJNMz5a16fX5EEMt6yQ7MbEkSZKOmYWBJEmSVJWtmwGT74JIMax8C7pdHnQiHUYkEmH22j28MG8jE5dsJa/wiyGGDk5Q3KtlLXp+PsRQg7SkANNKkiSpqrIwkCRJkqqq/dvgxTHRsqDz96DrZUEn0v/YmnmAl+Zv4r/zN7H+S08StK2fypknNaBXy9qc0qIW6TWcoFiSJEnlz8JAkiRJqoqKi+DFqyF7O9Q/CUb8LXqrugKXX1TMlOU7eH7uRqZ/urNkPoLUxDjO7dKIi3s0o1uzDIcYkiRJ0nFnYSBJkiRVRVPvhvUzIKEmXPIUJKQEnajaW7Yli//O38irH29mb25hyfberWpzSY9mDOvUkOQEf0WTJElScPxpVJIkSapqlr8BM/4eXT7vAajbNtg81VhmbiGvLdrMC/M2sWRzZsn2hmlJXNS9KRd1b0rLupY5kiRJqhgsDCRJkqSqJByGaX+MLp96M5x8fqBxqqNwOMLMNbt5Yd5GJi3dRkFRdALj+NgQZ53UkIt7NKXvCfWIjXHIIUmSJFUsFgaSJElSVRITA6Nejz5hMOhXQaepVjbuyeXF+Zt4cf4mNu87ULK9fcOaXNKjGed3a0LtlIQAE0qSJEnfzMJAkiRJqgoin8+cGwpBcm0487fB5qkm8gqLeXvpNl6Yt5EZq3eXbK+ZFMf5XZtwSY9mdGyS5gTGkiRJqhQsDCRJkqSqYMGTsG46jLgfElODTlPl5RYUce/bq3hx/kay8opKtp/Rti4X92jK2Sc3JCk+NsCEkiRJ0tGzMJAkSZIquy0LYeLPoDgfmp8GPa8JOlGVtj0rj2ufmFcyiXGTjBolExg3q50ccDpJkiSp9CwMJEmSpMrswF544cpoWXDiMOg+JuhEVdonmzO59ol5bMvKo3ZKAn+5sDOD2tcnxgmMJUmSVAVYGEiSJEmVVTgMr3wf9m2AjBbw3Yeikx6rXLy9dBs/Hr+QA4XFnFA/lcdG9aR5HZ8okCRJUtVhYSBJkiRVVh/eB6smQWwifO8pqFEr6ERVUiQS4ZEPPuPPk1YQiUDfE+ry4OWnkJYUH3Q0SZIkqUxZGEiSJEmV0WfT4L3fR5fPuRcadQk0TlVVUBTml68s4b/zNwFw1WktuHPEScTF+iSHJEmSqh4LA0mSJKmyCYfhrZ9DJAxdr4BTrgo6UZW0N6eA7z89n9lr9xATgt+cezKj+rQMOpYkSZJUbiwMJEmSpMomJgaueAmm/RGG3xN0mippzc5srh43l/W7c0lNjOOBy7oxoF39oGNJkiRJ5crCQJIkSaqM0pvAeQ8EnaJKmrF6Fzc+PZ+svCKa1qrB46N7cmKDmkHHkiRJksqdA29KkiRJlcXSV2Diz6CoIOgkVdazszcw6vE5ZOUV0b1FLV69+XTLAkmSJFUbPmEgSZIkVQY7V8GEH0BBNtRpC71vCDpRlVIcjvCHict57MO1AJzftTF/urAzSfGxASeTJEmSjh8LA0mSJKmiy8+GF66MlgUtzoAe1wSdqErJzi/iR899zJQVOwD4yZkn8oNBbQmFQgEnkyRJko4vCwNJkiSpIotE4I0fw84VkNoQLnocYv0xvqxs3neAa8bNZcW2/STGxfDXS7owonPjoGNJkiRJgfA3DUmSJKkim/soLPkvhGLh4rFQs0HQiaqMjzfs5bon57MrO5+6qYk8OqoHXZtlBB1LkiRJCoyFgSRJklRRbZoPk34RXT7zt9CiT7B5qpDXF23hp/9dRH5RmPYNa/LY6J40yagRdCxJkiQpUBYGkiRJUkUUDsNrP4BwIXQ4F077QdCJqoRIJMI/pqzmb5NXATCkQ33uv7QbqYn+aiRJkiQd1U/FH3zwAQBNmjShTZs25RJIkiRJEhATA5c8BZN/A+f9C5yA95jlFRZzx0uLmbBwCwDX9W3Fz4d1IDbGP1tJkiQJIBSJRCJHunNMTAyhUIibb76Zf/zjH4e8d/fddwPQq1cvhg4dWrYppXKWlZVFeno6mZmZpKWlBR1HkiRVZ+FwtBywIChTu7Lzuf7JeSzYsI+4mBD/d35HRvZqHnQsSZIkqdwdzbXPMnvu9q677iopEywMJEmSpFIIh+HN2yAuCYb+0dKgjKzctp+rx81l874DpCXF8fAV3enTtm7QsSRJkqQK56gKg9Dnv7CEw+FyCSNJkiRVW5EITPwpzB8LoRjofDE06R50qkrvvZU7uOXZj8nOL6JlnWQeH92T1vVSg44lSZIkVUhHVRjUrFmT/fv3s3379vLKI0mSJFU/B8uCeY8BITj/IcuCYxSJRHhi5jrufmMZ4Qic2ro2D13enVopCUFHkyRJkiqsmKPZuVWrVkQiEaZOncrevXvLK5N0xLZt28bTTz/Nj3/8Y8444wxSUlIIhUK0bNky6GiSJElHJhKBt26HuY9SUhZ0uTToVJVaUXGYOycs5a7Xo2XBJT2a8uTVvS0LJEmSpG9xVE8YDBkyhEWLFrFv3z46dOjAeeedR6NGjYiJ+aJ3mDNnTskEyKV15513HtPxqj7Gjx/PrbfeGnQMSZKk0olEYNLPYc6/iZYF/4KuI4NOVa5yC4pYvnU/y7ZmsS+noFzOMeuz3cxcs5tQCH4xrD3X9W1dMryqJEmSpK8XikQikSPdedOmTXTu3JnMzMyvvHfwY8riB/Hi4uJj/gxVD48//jjPPvssPXr0oEePHmzYsIGf/OQntGjRgnXr1h3x5xzNTOGSJEll5t3fwIz7gRCc9wB0uyLoRGVqX24BS7dksXRL5udfs/hsZzbhI/4NpPRqxMfy90u7ctbJDcv/ZJIkSVIFdjTXPo/qCYOmTZvy1ltvcdVVV/Hpp58edp+j6B8Oyzt/dDSuvvpqrr766pL18ePHB5hGkiTpKLUZGH26YNifK3VZEIlE2JaVx9LNWYcUBJv3HTjs/vVqJtKxcRoN05OAsv/5PzEuhkt7NaN9Q28EkSRJko7GURUGAL1792blypXMnj2bBQsWsHfvXgoLC/ntb39LKBSiZ8+eDBs2rDyySpIkSVVL6wHww4VQs0HQSY5YOBxh/Z5cPtmcWVIOLNuSxe6vGV6oee1kOjZJ4+TG6ZzUOI2TG6dRv2bScU4tSZIk6UgcdWFwUO/evendu3fJ+m9/+1sAevXqxW9+85tjT3YMdu3axYwZM5gzZw5LlixhzZo1bNmyhezsbOLj46lVqxYdO3ZkwIABXHXVVTRp0iTQvGWpuLiYpUuXMnfuXObNm8fcuXNZvHgxhYWFAPTv359p06aV6rMLCgp4/vnnee6551i6dCnbt2+nVq1atGrVigsuuIDRo0dTt27dMvxuJEmSqphIBCbfBfXaQdfLotsqcFlQWBzm0+3ZfPJ5KbB0SybLt+4nO7/oK/vGxoRoWy+Vkz8vB05unMZJjdNIS4oPILkkSZKk0ih1YXA4xzocUVkZPXo0b7755mHfKyoq4sCBA2zZsoV33nmH3/72t/ziF7/g17/+9SGTN1dGr776Kpdffjm5ubll/tkrVqxg5MiRLFy48JDt27ZtY9u2bcyaNYt77rmHsWPHMnz48DI/vyRJUqUXicDk38CMv0MoBpr2hLonHHbXrLxCXpy3icwDhcc5JESA7Zl5LN2ayapt2RQUh7+yT2JcDO0bRZ8W6Ph5OdCuYU2S4mOPe15JkiRJZafMCoOxY8cC0KFDh7L6yDJRt25dOnToQIsWLUhNTSU3N5fVq1czZ84cioqKyM/P56677uKzzz7jiSeeCDruMdm3b1+5lAWbNm1i8ODBbNmyBYjOM9GvXz/atGnDzp07mTx5MgcOHGDHjh2cf/75TJo0iUGDBpV5DkmSpEorEoEpv42WBQDD/nLYsiASiTBxyTbuen0pO/fnH+eQh1czKY6TG0efGjg4tFDruinExVbum20kSZIkfVWZFQajRo0qq486ZgMGDODcc89l8ODBtG3b9rD7bN++nVtvvZXnnnsOgCeffJJzzz2Xiy666HhGLRcNGjSgZ8+eJa+3336bv//976X+vMsuu6ykLGjRogUTJkygS5cuJe/v2rWLSy+9lClTplBYWMjFF1/MmjVryMjIONZvRZIkqfKLRGDq/8GHf4uuD7sHel33ld027c3lzglLmbpiBwCt66ZwettghnvMSI7npEZpdGySTtNaNQiFyn5iYkmSJEkVT5kOSVRR/PSnP/3WfRo0aMAzzzzD9u3bmTp1KgCPPPLIMRUGOTk5pKSklOrY7OxsUlNTS31ugKFDh7J+/XqaN29+yPbZs2eX+jMnTpzI9OnTAUhISOD111+nU6dOh+xTt25dJkyYQOfOnfnss8/Ys2cPf/nLX/jDH/5w2M+86667Sua8OFpr166lZcuWpTpWkiTpuItE4L3fw/S/RteH/hl6X3/ILkXFYcbOWMd9767iQGExCbEx3DigDTcOaOMQP5IkSZKOq2r9HHEoFGLMmDEl6x9//HGpP2vGjBm0atWK999//6iPfffdd2nduvUxXdgHaNiw4VfKgmP14IMPliyPGjXqK2XBQSkpKdx9990l64888ghFRV+dDA8gOTmZOnXqlOoVG+svzZIkqRKZ9if44J7o8tl/hFO/f8jbizft47wHZ/D7ics5UFhMr1a1mfijvtx65omWBZIkSZKOu3J7wuDtt99m8uTJLFy4kF27drF//37C4a9OmPa/QqEQa9asKa9YX1GvXr2S5f3795fqM5YvX87w4cPJysrinHPOYdKkSZxxxhlHdOzUqVM577zzOHDgAEOHDmX27NmceOKJpcpR1rKzs5kyZUrJ+pfLlcO58MIL+f73v092djZ79uzhgw8+OOxcBrfffju33357meeVJEmqcGpkRL+e/Qc47aaSzdn5Rfz1nZU8MXMd4Qik14jn/w1vz8XdmxET4/A/kiRJkoJR5oXBRx99xJgxY1i1alXJtkgkAnDI2KcHtx0UCoWIRCLHfXzUZcuWlSyXdqibtm3b0q9fP9544w1ycnIYNmwYb7/9Nn369PnG46ZNm8a5557LgQMHABg4cCCtW7cuVYbyMHPmTPLzo5PtpaSk0LNnz2/cPykpidNOO413330XiJYhTn4sSZKqtVNvhBZ9oNEX8z+9s3Qbv3ltKVsz8wA4v2tjfjXiJOqmJgaVUpIkSZKAMh6SaPLkyfTv359Vq1YRiURKXvBFIfC/2w4WBP9bIBwPW7Zs4d577y1ZL+38BfHx8bz44osMHToUiN6ZP2zYsG8cYmj69OmMGDGC3NxcAEaMGMHzzz9PXFzFmVZi+fLlJcudOnU6omynnHLKYY+XJEmqNmb8AzbO/WL987Jga+YBrn9yHtc/NZ+tmXk0r53Mk1f34v5Lu1kWSJIkSaoQyqwwyMnJYeTIkRQWFhKJRPj+97/P7Nmzueqqq0r2Wbt2LYsXL+b111/nZz/7GfXr1ycSiZCamsqTTz7J2rVr+eyzz8oq0mHl5uaybNky/vrXv9KtWze2bNkCQIcOHfj5z39e6s9NTEzklVdeYciQIQBkZWVx9tlnM3fu3K/sO2PGDIYPH05OTg4Aw4YN48UXXyQ+Pr7U5y8PK1euLFlu0aLFER3z5TkUVqxYUeaZJEmSKrQP7oV3fw1PXwD7twFQHI4wbsZazrzvA95Ztp24mBA3DWjDO7f2o9+J9b7lAyVJkiTp+Cmz29kfffRRdu/eTSgU4ic/+Ql/+ctfAKhZs2bJPgcvOnfs2JFzzjmHu+66i9tuu41HHnmEa665hhdffJFzzz23rCIB8OGHH9K3b99v3Gf48OE888wzh2QtjaSkJCZMmMDw4cN5//33yczM5KyzzmLKlCkld97PmjWLYcOGkZ2dDcCZZ57Jyy+/TGJixburbPfu3SXLDRo0OKJjGjZsWLK8Z8+eMs/0vzZu3Ei3bt1K1gsKCkq2161bt2T76aefzoQJE8o9jyRJqsam3wdT/y+6fMatULMhS7dk8v9eXsKiTZkAnNI8gz9c0In2DdMCDCpJkiRJh1dmhcHbb78NRC+a33nnnUd0TI0aNXjooYcoLi7m0UcfZfTo0SxduvSQi87lqVatWvzrX//i0ksvLbPPTE5O5s033+Tss89mxowZ7Nu3jyFDhjB16lQKCgoYOnRoyeTKAwcOZMKECSQlJZXZ+cvSwVIDov+tjsSX9/vy8eWluLj4kGLjoHA4fMj2zMzMcs8iSZKqsQ/vhym/jS4P+jW5vX/I/ROX89iHaykOR6iZGMcdw9pzWa/mTmosSZIkqcIqs8JgyZIlhEIhTj31VFJTUw+7z9dNavzXv/6V5557jn379jF27Fh+8YtflFUsGjduzM0331xy/v3797Ny5UoWLFjA3r17GTlyJP/+9795+OGHOfHEE8vknCkpKbz11lucddZZfPTRR+zdu5chQ4ZQXFxMVlYWAH379uX1118/4gvxQcjLyytZTkhIOKJjvvykxMHJnMtTy5Ytj2n+iwcffJAHH3yQ4uLiMkwlSZKqlRn/gMm/iS4P/BXv1b+KX933AZv3RX8WOqdTI35z7knUT6uYN4lIkiRJ0kFlNofBwbu5W7Vqdcj2L0+U+3UXkGvWrMmAAQOIRCK8+uqrZRUJgNatW/PAAw/wwAMP8OCDD/Lkk08ye/Zs1q9fz+jRowF47733OPXUU1m8eHGZnbdmzZpMmjSJHj16ANE/n3379gHQp08fJk6cSEpKSpmdrzx8+cmHg0P9fJv8/PyS5Ypchhx08803s2zZssPONSFJkvStZj4QnbMAyD7tdm7ePJgx4+ayed8BmmTU4PHRPXjw8lMsCyRJkiRVCmVWGBy8y/t/70T/8rwAW7du/drjGzVqBMCGDRvKKtI3aty4MWPHjuWHP/whAHv37uXSSy8t0zvN09PTue+++76y/f777//apzAqki9nPNKnBb68X2X4HiVJkkotEoEdywBY3Ob7nDarB28u3kpsTIjr+rbi3dv6Maj9kc0DJUmSJEkVQZkVBrVr1wa+Om79l+cjWL58+dcev3nzZiB64f54+uMf/0haWnTSueXLl/PWW2+V2WcvW7aMiy666Cvbzz//fD799NMyO095qVOnTsny9u3bj+iYbdu2lSwf/DshSZJUJYVCrOz1B/6c/mu+s7Qv+/OK6Nw0nQk3n84vzzmJ5IQyG/1TkiRJko6LMisM2rVrRyQSYf369Yds79KlS8nyG2+8cdhjMzMzmT17NhCdiPh4Sk5Opk+fPiXrM2bMKJPPXblyJYMHD2bHjh0A9OrVi65duwKwZcsWBg4cyJo1a8rkXOWlXbt2Jcv/+9/163z5CZH27duXeSZJkqQgFefuJeuZ0bzxwWzueHEx5zwwk4e2dyAlIY7fnHsSr9x0Oh2bpAcdU5IkSZJKpcwKg549ewKwdOnSQ7b37t2bunXrEolEeOKJJ/jggw8OeT8SifCDH/yAPXv2EAqF6N27d1lFOmJfLikOzsVwLD799FMGDRpUcrd99+7defvtt5k8eTKdO3cGok9UDBw4kLVr1x7z+cpLhw4dSpaXLFlCUVHRtx6zYMGCwx4vSZJU2UQiETbszuX1RVv4/ZvLuOXBl1j35z6kffoKjSffxPPzNlAUjnDmSQ1497b+jDm9FbExoaBjS5IkSVKpldlz0oMHD+aee+5h7969zJ8/n+7du0dPEBfHDTfcwO9//3sKCgoYPHgww4YNo1OnTuTm5jJx4kRWr15d8jnXX399WUU6Yl+eW+FYh9FZs2YNgwYNYsuWLQB069aNd999l4yMDAAmT57MoEGD+OSTT9i4cSMDBw7k/fffp0WLFsd03vLQp08fEhMTyc/PJycnh3nz5nHqqad+7f75+fl89NFHJeuDBg06HjElSZLKxM79+SzetI9FG/exaFMmizftY29uIQC9Q8t5OOFv1AplszVSh+fr/5jrW7eh3wn1OOOEugEnlyRJkqSyUWaFwaBBg6hduzZ79uzhqaeeKikMAH75y1/yxhtvsGjRIsLhMG+++SZvvvnmVz7jqquuYvjw4WUV6Yjs3r2bWbNmlawfy13xa9euZdCgQWzatAmIDsc0efLkQ55gqFevHlOmTGHgwIEsW7aM9evXl5QGzZo1K/03Ug5SU1MZPHgwEydOBGDcuHHfWBi8/PLL7N+/H4gWL/369TsuOSVJko5WVl4hn2zKZNGmTBZt3MfiTfvYkpn3lf3iY0P8sNYsbsz5F3GRIg7U70r9y8fz5/RGAaSWJEmSpPJVZoVBXFwcCxcuJCcnhxo1ahzyXlJSEu+99x433XQTzz//PJFI5JD3k5OT+elPf8qdd955zDn27NlzxE8JhMNhfvCDH5Cfnw9AYmIiI0aMKNV5N2zYwKBBg0rG8O/UqROTJ08+bJb69eszZcoUBgwYwMqVK1m7dm1JadCkSZNSnb+83HTTTYcUBrfccgsnn3zyV/bLzc095L/f9ddfT1ycE/1JkqTg5RUWs2xrFos37mPxpkwWbdrHmp05X9kvFIK29VLp3DSDrs3S6dy4Jicv/ytxHz0Y3eHkC6hx/r8gvsZXjpUkSZKkqqBMr+g2bdr0a9/LyMjg2Wef5d5772Xq1Kls2bKFmJgYWrduzaBBg0qG7DlWTz75JM888wy33HIL559/PmlpaYfdb/Hixdx+++28/fbbJdt+9rOfUadOnaM+56ZNmxg4cCDr1q0D4OSTT2bKlCnUrfv1j6c3bNiQ9957jwEDBrBq1SrWrFlTUho0alRx7lg755xz6Nu3L9OnTyc/P58RI0YwYcKEkrkYIPqUxsiRI0uGlqpduzZ33HFHUJElSVI1VhyO8OmO/SzemMnCTdEnB1Zs3U9ROPKVfZtk1KBrsww6N02nc9MMOjVNJzXxSz8ez3wADpYFA34B/e+ItgqSJEmSVEUd91vAGzduzBVXXFGu55g3bx6jRo0iLi6O9u3b065dO2rVqkUoFGL37t0sXrz4kHkTAC688EJ+85vflOp8NWrUICUlBYgOaTRlyhTq1av3rcc1atSIqVOnMmDAAFavXk1qaipJSUmlynDQ8OHDS+ZPOOjg5MsQ/bPp2rXrV46bOHEijRs3PuxnPvvss/Tq1YutW7eybt06unbtSv/+/WnTpg07d+5k8uTJ5ObmAtEnTV544YUyK4AkSVL1lldYzJ6cAvbkFLA3t+CL5ZwCdn++bXf2wfcK2ZtbQPFhyoE6KQklxUDXZtFyoG5q4jefvOc1sGoS9BgDHS8sp+9QkiRJkiqOUOR/xweq5B566CFuuummI96/Zs2a3HXXXfzoRz8iNja21Ofdvn071113Hf/+979p2LDhUR27ceNGbr75Zh5//PFvfCrhSLRs2ZL169cf9XFr166lZcuWX/v+ihUrGDlyJAsXLvzaferVq8fYsWM555xzjvr8QcvKyiI9PZ3MzMyvfSpFkiQdm+JwhMwDhSUX/f+3BPjytoMlQG5B8VGfJyUhlk5N0+nSNIPOTTPo0iydJhk1CB3J0wEb50LtVpDy+c9kkYhPFUiSJEmq1I7m2me5FQZ5eXlMmjSJDz/8kI0bN7J3716Ki4uZMmXKIftFIhEOHDgAQHx8PPHx8cd87lWrVjF58mRmz57N0qVL2bBhA/v27QMgLS2NRo0a0bVrV4YMGcKFF15IamrqMZ+zoiivwgCgoKCA8ePH89xzz7F06VK2b99ORkYGrVu35oILLmDMmDHHXHgExcJAkqRjty+3gNcXbWFbVt5hSoBC9uUWcJib/79VXEyIWikJ1ElJoFZyArVToq9aKQnUTo6ndmoitZMTqJUST+2UBOrXTCI2phQX+ReNh9dugSbd4aoJEPctTyBIkiRJUiUQeGFw77338pe//IXdu3eXbItEIoRCIYqLD71LbPfu3TRv3py8vDx69+7NzJkzyzqO9K0sDCRJKr2i4jDPzN7A3yavYl9u4bfun5YUR53URGolx//Pxf9Dy4A6n3+tmRh3ZE8HlFY4DFP/Dz68L7refgRc8B9ISC6/c0qSJEnScXI01z7LdA6DwsJCzj//fCZNmgRES4JvU6dOHUaNGsXDDz/M7NmzWb16NW3bti3LWJIkSSonH6zayf+9sYxPd2QDcGKDVPq0qVty4b/2508F1EmNfs1Ijic+Nibg1F9SkAMvXw8r3oiu9/0JDPwVxFSgjJIkSZJ0nJRpYXDjjTfy1ltvAZCUlMSoUaMYNGgQzz77LBMmTPja46644goefvhhIDr57g9/+MOyjCVJkqQy9tnObH7/5nKmrNgBQK3keG47qx0jezYjriIVAt8kczM8dylsWwyxCfCdf0KXS4NOJUmSJEmBKbPCYP78+YwdO5ZQKESTJk145513aN++PQAffPDBNx7bp08f0tPTycrKYvr06RYGkiRJFVTmgUL+OeVTnpi1jsLiCHExIa46rSU/GnwC6cnHPhfVcbN9GTx1PmRvh+S6cOkz0PzUoFNJkiRJUqDKrDAYO3ZsyTwFTz31VElZcKS6du3K+++/z/Lly8sqkiRJkspIcTjC+LkbuO+dVezOKQBgYLt6/PKck2hbPzXgdKWQ1hgS0yC5DowcD7VaBJ1IkiRJkgJXZoXBe++9B0DHjh3p37//UR/ftGlTADZv3lxWkSRJklQGZq3Zzd1vLGP51iwA2tRL4VcjTmJgu/oBJztKkQgU5UN8EtTIgCtfhqQMSPrmSb8kSZIkqboos8Jgy5YthEIhunXrVqrjU1Ojd6bl5OSUVSRJkiQdgw27c/nDxOVMWroNgLSkOH485ESuPK1FxZq4+EgUHoAJN0e/fu9piImFjOZBp5IkSZKkCqXMCoO8vDwgOtlxaWRnZwNfFAeSJEkKRnZ+EQ++t5rHpq+loDhMTAgu792CW888kdopCUHHO3r7t8FzI2HLAoiJhy0LoWn3oFNJkiRJUoVTZoVBvXr12Lx5M9u2bSvV8StWrCj5HEmSJB1/4XCEFxds4p63V7Jzfz4Ap7etw50jTqZdw5oBpyulrYuiZUHWZqhRK/p0gWWBJEmSJB1WmRUG7du3Z9OmTcyaNYvi4mJiY2OP+NiNGzeycOFCQqEQPXv2LKtIkiRJOkLz1u3ht68vY8nmTABa1Enml8M7cOZJDQiFQgGnK6Xlr8PL10NhLtQ9ES57Hmq3DjqVJEmSJFVYZTb47NChQwHYtWsXTz755FEd++tf/5ri4mIAzj777LKKJEmSpG+xc38+P3zuYy56eBZLNmeSmhjHL4a1551b+3HWyQ0rZ1kQicD0++D5K6JlQZtBcO1kywJJkiRJ+hZlVhiMHj2a9PR0AG677TbmzZt3RMfdfffdPPnkk4RCIRo3bsyll15aVpEkSZL0NSKRCC/M28iQ+97ntUVbCIXg0p7NeO+nA7ihfxsS4478adEKJ28fzH00utzrBrjsv5CUHmgkSZIkSaoMymxIotq1a/O73/2OW265haysLPr27cvNN9/MyJEjyc/PL9kvKyuLrVu3MmPGDB566CEWLFhQ8t7f/vY34uPjyyqSJEmSDmP97hx+8fISZq7ZDcDJjdP44wWd6Nw0I9hgZaVGLRj5HGyaBz2vCTqNJEmSJFUaoUgkEinLD/zxj3/MP/7xj688vn7wNF+3/c477+Suu+4qyyjSEcvKyiI9PZ3MzEzS0tKCjiNJUrkoKg7z6Idr+du7q8gvCpMYF8NtZ57INWe0Ii62zB48Dcaez2Dxf6H/7VAZh1GSJEmSpHJyNNc+y+wJg4Puv/9+OnfuzE9/+lP27dsHREuCg0XB//YTGRkZ/O1vf2PUqFFlHUWSJEmf+2RzJne8tJilW7IA6NOmDn/4bida1k0JOFkZ2DwfnrkEcndBjQzofUPQiSRJkiSpUirzJwwOys7O5vHHH2fixInMmjWL/fv3l7yXmJhIr169GDFiBDfccIN3dCtwPmEgSaqqDhQU87fJq3h0+meEI5BeI55fndOBi7o3rZwTGv+vVW/Df0dHJzdu2AkufxFqNgw6lSRJkiRVGEdz7bPcCoP/lZOTQ2ZmJikpKSWTI0sVhYWBJKkq+vDTXfy/V5awYU8uACM6N+I3555MvZqJAScrI/OfgDduhUgxtBkElzwJiTWDTiVJkiRJFUqgQxJ9nZSUFFJSqsAj75IkSRXc3pwCfj9xOS/O3wRAo/Qk/u+8jgw5qUHAycpIJALT/gjv/zm63uUy+M4/IDY+2FySJEmSVMkdt8JAkiRJ5SsSifD64q389rWl7M4pIBSCq05twU/PbkfNpCp0MX3SL2D2Q9Hlfj+Dgb90omNJkiRJKgMWBpIkSVXA5n0H+PWrnzB1xQ4ATqifyp8u7Ez3FrUCTlYO2g+H+eNg6B+gx9VBp5EkSZKkKsPCQJIkqRIrDkd4atY67nl7JTkFxcTHhvjBwBP4/oDWJMbFBh2v7BTkQkJydLlVP/jRIqhZRYZYkiRJkqQKwsJAkiSpklq1fT93vLSYjzfsA6B7i1r86YJOnNCgik38u+tTePpC6H8HdLs8us2yQJIkSZLKnIWBJElSJZNfVMyD763hoWmrKSyOkJoYxx1D23F57xbExFSxsfw3fATPXQoH9sKMv0OniyEuIehUkiRJklQlWRhIkiRVIvPX7+X2FxexZmcOAEM61Of/zu9Io/QaAScrB8teg5euheJ8aNIdLnvBskCSJEmSypGFgSRJUiXxztJt/ODZjykoDlM3NZHffudkhndqSChUxZ4qAJj9CLx1BxCBE4fBRY9BQkrQqSRJkiSpSrMwkCRJqgQmLNzMbS8sojgc4cyTGnDvRV1IT44POlbZC4dh8m9g5j+i693HwPB7IdYfWyVJkiSpvPmblyRJUgU3fs4GfvHKEiIRuKBbE/5yUWfiYmOCjlU+Ns35oiwY9Gvo+xOoik9QSJIkSVIFZGEgSZJUgT06/TN+9+ZyAK44tTl3f6dj1ZvY+Muanwpn/wFq1IauI4NOI0mSJEnVioWBJElSBRSJRPjn1NXc9+4qAG7o15qfD2tfNecryNwEez6DVv2i66fdHGweSZIkSaqmLAwkSZIqmEgkwp/eWsEjH3wGwE/OPJEfDGpbNcuC7Uvh6YsgLxPGvAmNuwWdSJIkSZKqLQsDSZKkCiQcjvDrCZ/wzOwNAPx6xElcc0argFOVk8/eh+evgPwsqNsOkusEnUiSJEmSqjULA0mSpAqiqDjM7S8u5uWPNxMKwR+/24lLezUPOlb5WPxfePVGCBdC8z5w6TOQXDvoVJIkSZJUrVkYSJIkVQD5RcX86LmFTFq6jdiYEPdd0oXzujYJOlbZi0Rgxt9h8m+i6yedB9/9N8QnBZtLkiRJkmRhIEmSFLQDBcXc8PR8Pli1k4TYGB68/BTOPKlB0LHKXiQCb90Oc/4dXT/1Jjjr9xATE2wuSZIkSRJgYSBJkhSo/XmFXPPEPOas3UON+Fj+c1UPzjihbtCxykcoBDHx0eWz/wCn3RxsHkmSJEnSISwMJEmSArI3p4DRY+ewaFMmNRPjGDumJz1aVsFx/CORaFkAcNbvoMO50OK0YDNJkiRJkr7C578lSZICsGN/Hpf++yMWbcqkVnI8z11/atUsC/ashbHDo18hOvyQZYEkSZIkVUgWBpIkScfZ5n0H+N4jH7Fy+37q10zkhRtOo2OT9KBjlb0tH8NjZ8KGmfD6j4JOI0mSJEn6Fg5JJEmSdByt3ZXDFY/OZvO+AzTJqMGz1/WmRZ2UoGOVvU/fhRdGQWEONOgE330k6ESSJEmSpG9hYSBJknScrNy2nysem83O/fm0rpvC09f2pnFGjaBjlb0FT8LrP4ZIMbQeAJc8BUlpQaeSJEmSJH0LCwNJkqTjYPGmfVz1+Bz25RbSvmFNnrqmN/VqJgYdq2xFIjDtT/D+n6LrnS+F7/wT4hKCzSVJkiRJOiIWBpIkSeVszto9XD1uLtn5RXRtlsG4MT3JSK6CF9Hnj/uiLOj7Exj0awiFAo0kSZIkSTpyFgaSJEnl6INVO7n+qXnkFYY5tXVtHh3Vk9TEKvojWJeRsGwCdBgBPa8NOo0kSZIk6ShV0d9WJUmSgvf20m3c8uzHFBSHGdCuHg9f0Z2k+NigY5WtogIozIUaGRCfBFe8DDExQaeSJEmSJJWCv81JkiSVg1c/3sxNzyygoDjM8E4N+feVPapeWVCQC+NHwtMXQv7+6DbLAkmSJEmqtPyNTpIkqYw9M3s9t76wkOJwhAtPaco/Lu1GQlwV+7ErLwueuQhWT4btS2HHiqATSZIkSZKOkUMSSZIklYHMA4W8s3QbbyzeyvurdgJw1WktuOvck4mJqWIT/+buiT5VsGUBJKbBZS9As55Bp5IkSZIkHSMLA0mSpFLKyS9i8vLtvL5oKx+s2klBcbjkvZsGtOFnZ7cjFKpiZUH2DnjyfNixFGrUhitfhsbdgk4lSZIkSSoDFgaSJElHIa+wmPdW7OCNxVuZsmI7eYVflAQn1E/l3C6NGdG5Ea3rpQaYspxkboInvgN71kBqQ7jqVajfIehUkiRJkqQyYmEgSZL0LQqKwkz/dCevL9rCu8u2k1NQXPJeyzrJjOjcmHO7NKZdw5oBpjwOXv9xtCxIbx4tC+q0CTqRJEmSJKkMWRhIkiQdRlFxmJlrdvPG4i1M+mQbWXlFJe81yajBiM6NGNG5MR2bpFW9YYe+znf+Aa/9EM69H9KbBp1GkiRJklTGLAwkSZI+VxyOMGftHt5YvIW3PtnGnpyCkvfq10xkeKdGnNulMd2aZVS9iYy/zq7VULsVxMRCWmO44sWgE0mSJEmSyomFgSRJqtYikQgLNuzj9UVbmLhkKzv255e8VzslgWEdGzKic2N6tapNbHUpCQ5aPwuevQQ6nAvfeQBiYoJOJEmSJEkqRxYGkiSp2olEInyyOYs3Fm/hjcVb2bzvQMl7aUlxnH1yQ87t0pg+beoQF1tNL5KvmQrPXQZFB2DveijKg4TkoFNJkiRJksqRhYEkSao2Vm7bz+uLtvDG4i2s251bsj0lIZYzT2rAiM6N6XtiXRLjYgNMWQGseBP+OxqKC6DtmfC9pyC+RtCpJEmSJEnlzMJAkiRVeoXFYfbmFrAvt5A9OQXsyy1gT04he3ML2JtTwJ7cAj7ZnMmq7dklxyTGxTC4Q33O7dyYge3rkxRfzUuCgxb/F165ASLF0OE7cOFjEJcQdCpJkiRJ0nFgYSBJkiqU/KLikgv/0Qv+X1z435v7+fKX13MK2J9fdESfHR8bov+J9Tm3SyMGd2hAaqI/Ch1i3lh441YgAl0ug+/8E2L9M5IkSZKk6sLfACVJUrnbnZ3Pim37v3r3f+4XF/0PlgA5BcWlOkcoBBk14qmVkkCt5IOveGqnJJCRnEDjjCQGtKtPeo34Mv7uqojcPTD5LiACPa+FYfc4ybEkSZIkVTMWBpIkqdxEIhH+O28Tv3ltKQcKj7wIiI0Jfenif/wXBcDB9ZQEaicnUCvli/fSasQTGxMqx++mikuuDZe/CJ++AwP/X7SBkSRJkiRVKxYGkiSpXGQeKOT/vbKENxdvBaBZ7Ro0Sq/xlQv9tVISqJ0ST0by5yVAcgI1k+KI8eL/8desZ/QlSZIkSaqWLAwkSVKZm7duDz8av5DN+w4QFxPitrNO5IZ+bXwCoCJ6749QXAA9r4H0pkGnkSRJkiQFyMJAkiSVmeJwhAemrubvU1YRjkDz2sn8Y2Q3ujbLCDqaDqcgFz76F+RnQau+FgaSJEmSVM1ZGEiSpDKxed8Bbh2/kDnr9gDw3W5NuPu8k6mZ5CTDFdbSV6JlQa2W0GpAwGEkSZIkSUGzMJAkScfsrSVbueOlxWTlFZGSEMv/nd+RC07xbvUKb/646NdTRkFMTKBRJEmSJEnBszCQJEmldqCgmLvfWMpzczYC0KVpOn+/tBst66YEnEzfavtS2DQHYuKg6+VBp5EkSZIkVQAWBpIkqVSWbcnih+M/ZvWObEIhuKFfG24780QS4rxTvVI4+HRBu+FQs0GgUSRJkiRJFYOFgSRJOiqRSIRxM9fxx4krKCgOU79mIn/7XldOb1s36Gg6UgW5sOj56HL30YFGkSRJkiRVHBYGkiTpiO3OzudnLy5m6oodAAxuX5+/XNSZOqmJASfTUVn1FuRnQkYLaD0w6DSSJEmSpArCwkCSJB2R6Z/u5LYXFrFzfz4JcTH8cngHrjqtBaFQKOhoOlonXwAp9SB/v5MdS5IkSZJKWBhIkqRvVFAU5q/vrOSRDz4DoG39VP45shsdGqUFnEylFgpBq35Bp5AkSZIkVTAWBpIk6Wut25XDD8d/zOJNmQBc1rs5vz7nJGokxAacTKWWvQNS6wedQpIkSZJUAVkYSJKkr4hEIry0YDO/mfAJOQXFpNeI588XdmJox0ZBR9OxKMiFB3pAnRPg0megZsOgE0mSJEmSKhALA0mSdIisvEJ+9convLZoCwC9WtXm/u91pXFGjYCT6ZgtmwB5mZCzA1J8ykCSJEmSdCgLA0mSVGLBhr38aPzHbNxzgNiYED8efAI3DWxLbIwTG1cJ88dFv54yysmOJUmSJElfYWEgSZIoDkd4+P013PfuKorDEZpk1OAfI7vSvUXtoKOprOxYDhs/glAsdLsi6DSSJEmSpArIwkCSpGpuW2YeP37+Yz76bA8AIzo34vff7UR6jfiAk6lMHXy6oN0w5y6QJEmSJB2WhYEkSdXYO0u3cftLi9mXW0hyQiy//c7JXNS9KaGQQxBVKYUHYNFz0eXuY4LNIkmSJEmqsCwMJEmqhvIKi/ndm8t4+qMNAHRsksY/Lu1G63qpASdTuTg42XF6c2gzMOg0kiRJkqQKysJAkqRqZuW2/dzy3AJWbc8G4Lq+rfjZ2e1JiHMS3CordzckpMIpV0FMbNBpJEmSJEkVlIWBJEnVRCQS4amP1vO7N5dTUBSmbmoif72kC/1PrBd0NJW3026GU0ZBpDjoJJIkSZKkCszCQJKkamBPTgG3v7iYycu3AzCgXT3uvbgLdVMTA06m4ybR4aYkSZIkSd/MwkCSpCpu5ppd3Pr8QrZn5ZMQG8Mdw9ozpk9LYmKc2LjKK8yD+WOh8/cguXbQaSRJkiRJFZyFgSRJVVRhcZi/vbuKh95fQyQCreul8I9Lu9GxSXrQ0XS8LJsAk34Ocx+DH8yFkCWRJEmSJOnrWRhIklQFbdidyw/Hf8zCjfsAuLRnM+489ySSE/ynv1qZPy76tfP3LAskSZIkSd/KqwaSJFUxr368mV+9+gnZ+UXUTIrjTxd05pzOjYKOpeNt50rYMBNCsdDt8qDTSJIkSZIqAQsDSZKqiOz8Iu589RNe/ngzAD1a1OL+S7vStFZywMkUiPlPRL+eOBTSGgebRZIkSZJUKVgYSJJUBazesZ9rnpjH+t25xITglkEncMugtsTFxgQdTUEozINFz0aXu48ONIokSZIkqfKwMJAkqZLbuCeXyx+dzfasfBqnJ3H/pd3o1ap20LEUpOWvw4G9kN4M2g4OOo0kSZIkqZKwMJAkqRLbkZVXUhac2CCV8defRu2UhKBjKWjzx0a/nnIVxMQGm0WSJEmSVGlYGEiSVEntyy3gysfmsGFPLs1rJ/PUNb0tCwSRCPS8FmLjodsVQaeRJEmSJFUiFgaSJFVCOflFjB47l5Xb91O/ZiJPX9ObBmlJQcdSRRAKQccLoi9JkiRJko6CMyFKklTJ5BcVc/1T81i4cR8ZyfE8dU1vmtdJDjqWJEmSJEmq5CwMJEmqRIqKw/zwuY+ZsXo3KQmxjBvTi3YNawYdSxXFJy/Bs9+Dz6YFnUSSJEmSVAlZGEiSVEmEwxHueGkJby/dTkJcDP+5qgddm2UEHUsVydzHYdUk2PBR0EkkSZIkSZWQhYEkSZVAJBLh/95cxksLNhEbE+KBkd3o07Zu0LFUkez6FNZ/CKEYJzuWJEmSJJWKhYEkSZXA36d8ytgZ6wD4y4WdOevkhsEGUsUzf1z06wlnQXrTQKNIkiRJkionCwNJkiq4xz9cy/2TPwXgrnNP4sLuXgzW/yjKh4XPRpe7jwk2iyRJkiSp0rIwkCSpAntx/ibufmMZALedeSKjT28VcCJVSMtfhwN7IK0JtB0SdBpJkiRJUiVlYSBJUgU16ZNt3P7iIgCuOaMVtwxqG3AiVVgHhyPqdiXExgUaRZIkSZJUeVkYSJJUAX346S5++NzHhCNwcfem/OqcDoRCoaBjqSLavx02zHKyY0mSJEnSMfMWNEmSKpgFG/Zy/VPzKCgOM/Tkhvzxgk6WBfp6NRvArUth3YeQ0SzoNJIkSZKkSswnDCRJqkBWbMtizNi55BYU0/eEuvx9ZFfiYv3nWt+iZkPodFHQKSRJkiRJlZxXICRJqiDW787hysfmkHmgkG7NM3j4iu4kxsUGHUsV2b4NUJgXdApJkiRJUhVhYSBJUgWwLTOPKx6bzc79+bRvWJNxo3uRkujIgfoWE26Gv7aDT98NOokkSZIkqQrwSoQqtW3btjF58mTmzZvHvHnz+Pjjj8nNzaVFixasW7cu6HiSdET25hRw5WOz2bjnAC3rJPPkNb1IT44POpYqut1rYO0HQAjqtQ86jSRJkiSpCrAwUKU2fvx4br311qBjSFKpZecXMXrsHD7dkU3DtCSeuqY39WsmBR1LlcH8cdGvJ5zpZMeSJEmSpDJhYaBKLS0tjcGDB9OjRw969OjBhg0b+MlPfhJ0LEk6InmFxVz3xDwWbcqkVnI8T1/bi2a1k4OOpcqgKB8WPhNd7j4m2CySJEmSpCrDwkCV2tVXX83VV19dsj5+/PgA00jSkSssDvODZz9m1me7SU2M44mre9G2fs2gY6myWPEm5O6Gmo3ghLOCTiNJkiRJqiKc9FiSpOMsHI5w+4uLmbx8OwlxMfznqh50bpoRdCxVJvPHRr92uxJivf9DkiRJklQ2qmxhsG7dOv7zn/9wxRVX0KVLF2rVqkV8fDy1a9emc+fO3HDDDbz//vtBxyxzxcXFLF68mMcee4wbb7yRHj16kJCQQCgUIhQKMWDAgFJ/dkFBAU899RTDhw+nRYsWJCUl0ahRI/r06cO9997Lrl27yu4bkaQqKhKJcNfrS3nl483ExYR46PJTOK1NnaBjqTL58mTHp1wZdBpJkiRJUhVS5W5J+/jjj/n+97/PnDlzDvv+3r172bt3L0uWLOHf//43AwYM4IknnqB58+bHOWnZe/XVV7n88svJzc0t889esWIFI0eOZOHChYds37ZtG9u2bWPWrFncc889jB07luHDh5f5+SWpqrjv3VU8OWs9oRD89ZIuDO7QIOhIqmxydkH9kyGtMWRU/p9fJEmSJEkVR5UrDFauXPmVsuDEE0+kY8eO1K1bl3379jFz5kw2bdoEwLRp0zjttNOYPn06rVu3DiJymdm3b1+5lAWbNm1i8ODBbNmyBYBQKES/fv1o06YNO3fuZPLkyRw4cIAdO3Zw/vnnM2nSJAYNGlTmOSSpsnt0+mf8c+pqAO4+ryPndW0ScCJVSs17w40zIH9/0EkkSZIkSVVMlSsMDmrbti3XXnstV1xxBU2aHHpBJhwOM27cOG655RZyc3PZsmULl19+OTNnziQUCgWUuOw0aNCAnj17lrzefvtt/v73v5f68y677LKSsqBFixZMmDCBLl26lLy/a9cuLr30UqZMmUJhYSEXX3wxa9asISMj41i/FUmqMl6Yu5HfvbkcgJ+d3Y4rT20RcCJVOvs2QFIGJKVBKBT9KkmSJElSGapycxg0atSIsWPHsmLFCu64446vlAUAMTExXH311Tz99NMl2z766CPeeeedYzp3Tk5OqY/Nzs4+pnMDDB06lPXr17Nt2zZef/117rzzToYNG3ZMF+4nTpzI9OnTAUhISOD1118/pCwAqFu3LhMmTCh5QmPPnj385S9/+drPvOuuu0rmVDja17p160r9vUhSUCYu2crPX14MwPX9WnPTgDYBJ1Kls387PHFu9JW9M+g0kiRJkqQqqsoVBv3792f06NHExsZ+677f/e536dWrV8n6m2++Werzzpgxg1atWpVqIuV3332X1q1bM3v27FKfH6Bhw4ZlPhfDgw8+WLI8atQoOnXqdNj9UlJSuPvuu0vWH3nkEYqKig67b3JyMnXq1CnV60j+u0pSRfL+qp38aPzHhCNwac9m/GJY+yrxNJuOowP74OkLYe86OLAXIsVBJ5IkSZIkVVFVrjA4WqeffnrJcmnvXl++fDnDhw9n586dnHPOOXz44YdHfOzUqVM577zz2LlzJ0OHDmXVqlWlylAesrOzmTJlSsn6mDFjvnH/Cy+8kNTUVCD6lMEHH3xw2P1uv/12du3aVapXs2bNyu4blKRyNn/9Hr7/1HwKiyOc07kRv/9uJ8sCHZ3CA/DcSNi+BFLqw1WvQs2GQaeSJEmSJFVR1b4w+PKFm+Li0t2x17ZtW/r16wdEhyUaNmwYM2fO/Nbjpk2bxrnnnsuBAwcAGDhwYIWaeHnmzJnk5+cD0ScIevbs+Y37JyUlcdppp5WsT506tVzzSVJFtmxLFqPHzuVAYTH9T6zH3y7pSmyMZYGOQnER/HcMbJgJiWlwxUtQu+L8nCBJkiRJqnqqfWGwZMmSkuXS3r0eHx/Piy++yNChQ4HonfnDhg37xiGGpk+fzogRI8jNzQVgxIgRPP/888TFVZx5qJcvX16y3KlTpyPKdsoppxz2eEmqTtbuyuGqx2ezP6+IHi1q8fAV3UmIq/b/5OpohMPw2i2w6i2IS4KR46FR56BTSZIkSZKquGp99WLDhg2H3AU/ZMiQUn9WYmIir7zySslnZGVlcfbZZzN37tyv7DtjxgyGDx9eMknysGHDePHFF4mPjy/1+cvDypUrS5ZbtGhxRMd8eQ6FFStWlHkmSarotmYe4IpHZ7Mru4CTGqXx2Oie1Ehw/hUdpRn3w6JnIRQLF4+Dlqd/2xGSJEmSJB2zal0Y3HbbbSXDEDVv3pxzzz33mD4vKSmJCRMm0L9/fwAyMzM566yzWLBgQck+s2bNYtiwYWRnZwNw5pln8vLLL5OYmHhM5y4Pu3fvLllu0KDBER3TsOEX4yrv2bOnzDP9r40bN1K3bt2S1/XXX3/Y7eedd165Z5Gk3dn5XPHobDbvO0Cruik8cXUv0mtUrDJYlUTXy6BBJzjvAWg3LOg0kiRJkqRqouKMf3OcPfHEE7z00ksl63/84x/L5KJ9cnIyb775JmeffTYzZsxg3759DBkyhKlTp1JQUMDQoUPZv38/EJ2zYMKECSQlJR3zecvDwVIDoEaNGkd0zJf3+/Lx5aW4uPiQYuOgcDh8yPbMzMxyzyKpesvKK2TU2Dms2ZlD4/Qknr62N/VqVrwyWJVEzYZw/XsQa+EkSZIkSTp+qmVhMG/ePL7//e+XrI8cOZLLLruszD4/JSWFt956i7POOouPPvqIvXv3MmTIEIqLi8nKygKgb9++vP7660d8IT4IeXl5JcsJCQlHdMyXS5eDkzmXp5YtWxKJREp9/IMPPsiDDz5Y6gmvJQkgr7CYa5+Yxyebs6iTksBT1/amSUbF/f+7Kqhlr8GqSXDu36NFgWWBJEmSJOk4q3ZDEq1du5Zzzz235GJ4586defjhh8v8PDVr1mTSpEn06NEDiA7vs2/fPgD69OnDxIkTSUlJKfPzlqUvP/lQUFBwRMfk5+eXLFfkMuSgm2++mWXLlh12rglJOhKFxWFuemYBc9buoWZiHE9c3Ys29VKDjqXKZu0H8NI1sPAZmD8u6DSSJEmSpGqqWhUGW7du5cwzz2Tbtm0AtG7dmkmTJpGWllYu50tPT+e+++77yvb777+f1NSKfzHpyxmP9GmBL+9XGb5HSToWxeEIP3lhEVNX7CAxLobHRvekY5P0oGOpstmyEJ67DIoLoP0I6D4m6ESSJEmSpGqq2hQGu3fv5swzz2TNmjUANGrUiMmTJ9OoUaNyO+eyZcu46KKLvrL9/PPP59NPPy2385aVOnXqlCxv3779iI45WMYA1K5du8wzSVJFEYlEuHPCJ7y2aAtxMSEevqI7vVr5/z0dpV2r4ekLoWA/tOwLFz4GsdVyxEhJkiRJUgVQLQqDrKwszj77bJYuXQpA3bp1mTx5Mq1atSq3c65cuZLBgwezY8cOAHr16kXXrl0B2LJlCwMHDiwpLyqqdu3alSyvX7/+iI7ZsGFDyXL79u3LPJMkVRT3vL2SZ2ZvIBSCv32vKwPb1w86kiqbrC3w1PmQuwsadYFLn4X4pG89TJIkSZKk8lLlC4OcnByGDx/O/PnzgegwQZMmTeKkk04qt3N++umnDBo0qORu++7du/P2228zefJkOnfuDMDmzZsZOHAga9euLbccx6pDhw4ly0uWLKGoqOhbj1mwYMFhj5ekquTh99fwr2nR0vf353fi3C6NA06kSid3Dzz1XcjcCLXbwOUvQVL5DJEoSZIkSdKRqtKFQV5eHt/5zneYMWMGAMnJybz55pt079693M65Zs0aBg0axJYtWwDo1q0b7777LhkZGdSpU4fJkyfTsWNHADZu3MjAgQOP+O79461Pnz4kJiYC0eJl3rx537h/fn4+H330Ucn6oEGDyjWfJAXh2dkb+NNbKwD4+bD2XNa7ecCJVCllboLs7VCzEVz5CqTWCzqRJEmSJElVtzAoLCzkwgsvZOrUqQAkJiYyYcIETj/99HI759q1axk0aBCbNm0CoEuXLkyePJlatWqV7FOvXj2mTJlS8oTD+vXrGThwIBs3biy3XKWVmprK4MGDS9bHjRv3jfu//PLL7N+/H4jOX9CvX7/yjCdJx93ri7bwy1eXAHDjgDZ8v3+bgBOp0mrUGcZMgitehlotgk4jSZIkSRJQRQuD4uJiLrvsMiZOnAhAXFwcL7zwAkOGDCm3c27YsIFBgwaVjOHfqVMnJk+efNiJf+vXr8+UKVNK5ghYu3YtAwcOZPPmzeWWr7RuuummkuVx48aVzAPxv3Jzc7nzzjtL1q+//nri4py0UVLV8d7KHdz6/EIiEbi8d3NuP7vdtx8kfVk4DJ9O/mK9fntoUH5DJEqSJEmSdLSqXGEQiUS45pprePHFFwGIiYnhqaee4jvf+U65nXPTpk0MHDiQdevWAXDyySczZcoU6tat+7XHNGzYkPfee48TTzwRiA5lNHDgQLZu3VpuOUvjnHPOoW/fvkB0yKERI0awePHiQ/bZvXs3559/PqtXrwaiTxfccccdxz2rJJWXOWv3cOPT8ykKRzi3S2PuPq8joVAo6FiqTCIRmHQHPHMhTPtz0GkkSZIkSTqsKncL+EMPPcQTTzxRst6mTRs+/PBDPvzwwyM6/oEHHjjqc9aoUYOUlBQgOtHvlClTqFfv28cibtSoEVOnTmXAgAGsXr2a1NRUkpKSjvr8XzZ8+PCS+RMOOjj5MsC8efPo2rXrV46bOHEijRsfftLOZ599ll69erF161bWrVtH165d6d+/P23atGHnzp1MnjyZ3Nxc4IunOTIyMo7p+5CkiuKTzZlcM24ueYVhBrarx32XdCE2xrJAR+n9v8CcfwMhqONQVpIkSZKkiikUiUQiQYcoS3fddRe//e1vS318af84tm/fznXXXce///1vGjZseFTHbty4kZtvvpnHH3/8G59KOBItW7Ys1STKa9eupWXLll/7/ooVKxg5ciQLFy782n3q1avH2LFjOeecc476/EHLysoiPT2dzMxM0tLSgo4jqYJYszObSx6exe6cAnq1qs0TY3pRIyE26FiqbOb8Byb+NLo87B7ofX2weSRJkiRJ1crRXPusck8YBKVBgwa89tprpTq2WbNmpT72eGnfvj2zZ89m/PjxPPfccyxdupTt27eTkZFB69atueCCCxgzZswxFx6SVFFs3neAKx+dze6cAjo2SeOxUT0sC3T0lrwIE38WXe7/c8sCSZIkSVKFVuWeMJBKwycMJH3Zrux8Lnl4Fp/tyqFNvRReuOE06qQmBh1Llc3qyfDspRAuhJ7XwfB7wLkvJEmSJEnH2dFc+6xykx5LknQsMg8UctVjc/hsVw5NMmrw1DW9LQt09HL3wH/HRMuCky+AYX+xLJAkSZIkVXgWBpIkfe5AQTHXjJvLsq1Z1E1N4Olre9M4o0bQsVQZJdeG8x+CdufAdx+BGH/kkiRJkiRVfP72KkkSUFAU5vtPz2fe+r3UTIrjyat706puStCxVJnkZcLCZ79Y7zACLn0G4hKCyyRJkiRJ0lFw0mNJUrVXHI5w6/MLeX/VTmrExzJ2dE9Oaux8JjpCkQgsfRkm/QKyt0NaY2g9IPqewxBJkiRJkioRCwNJUrUWiUT45StLeHPJVuJjQzx8ZXd6tKwddCxVFnvWwps/gTVTout12kJcUrCZJEmSJEkqJQsDSVK1FYlE+NNbKxg/dyMxIfj7pd3of2K9oGOpMigqgJn/gA/ugaI8iE2Avj+BM26FOCfJliRJkiRVThYGkqRq50BBMa98vJlxM9eyans2AH+8oBPDOzUKOJkqhW1L4KVrYeeK6HqrfnDO36Bu22BzSZIkSZJ0jCwMJEnVxqa9uTz10XrGz9lI5oFCAJITYvnFsPZ8r2fzgNOp0kjKgH0bIbkunP0H6HyJcxVIkiRJkqoECwNJUpUWiUSYs3YP42au4+2l2whHotub107mqtNacEnPZqQlxQcbUhVbJAJLX4F2wyE+CTKawaVPQ6OukOx8F5IkSZKkqsPCQJJUJeUVFvPaoi2Mm7GOZVuzSraf3rYOY/q0YmD7+sTGeFe4vsWuT+GNW2HddBjwCxjw8+j2NoOCzSVJkiRJUjmwMJAkVSnbMvN4+qP1PDtnA3tyCgBIio/hu92aMrpPS9o1rBlwQlUKhXnw4X3w4d+guADiakCif3ckSZIkSVWbhYEkqdKLRCIs2LCPcTPX8daSrRR9Pu5Qk4waXHlaCy7t2YyM5ISAU6rS+GwavHEb7FkTXT/hLBh+D9RqGWQqSZIkSZLKnYWBJKnSKigK8+aS6LBDizZllmzv1ao2V5/ekiEdGhAXGxNgQlUqeVnw5k9gyQvR9dSGMOzPcNJ5TmosSZIkSaoWLAwkSZXOjv15PDt7A8/M3sDO/fkAJMTFcF6Xxow+vSUnN04POKEqpfgasGMZEIJe18GgX0GSf5ckSZIkSdWHhYEkqdJYvGkf42as4/XFWygsjg471CAtkatOa8mlPZtRJzUx4ISqdLYvjRYFtVtDbDyc9yBEiqFJ96CTSZIkSZJ03FkYSJIqtMLiMJM+2ca4meuYv35vyfZTmmcw5vRWDO3YkHiHHdLRKsiB9/8Msx6EFqfDVROiww417hp0MkmSJEmSAmNhIEmqkHZn5zN+7kaemrWebVl5AMTHhhjRuTGj+7SkS7OMYAOq8lr1Nrz5U8jcEF1PrAmFuZCQEmwuSZIkSZICZmEgSapQlm3JYtzMtby6cAsFRWEA6qYmcnnv5lx+anPq10wKOKEqrawt8NYdsPy16Hp6Mxh+D7QbFmwuSZIkSZIqCAsDSVLgiorDTF6+nbEz1jF77Z6S7Z2bpjPm9JYM79SIxLjYABOq0vvoIZj6eyjYD6FYOO0m6P9zSEwNOpkkSZIkSRWGhYEkKTCZuYWMn7uBJ2etZ/O+AwDExoQY1rEhY05vxSnNMwiFQgGnVKUUiUBxIcQlRNczN0XLgqY9YcTfoGGnYPNJkiRJklQBWRhIko67Vdv3M27mOl5ZsJkDhcUA1E5J4LJe0WGHGqXXCDihKq28TFj0PMx7DDpeBP1/Ft3e81po1CW6LcZJsiVJkiRJOhwLA0nScREOR5i6YgfjZq7jw9W7SrZ3aJTGmNNb8p0ujUmKd9ghldLWxTD3UVjyIhTmRLcteQH6/RRCIajdKvqSJEmSJElfy8JAklSusvIK+e+8TTw5ax3rd+cCEBOCs09uyOg+LenVqrbDDql0CvNg2avRomDT3C+212sPPa6BLt+LlgWSJEmSJOmIWBhIksrFZzuzeWLmOl6cv4mcguiwQ+k14rm0VzOuPLUFTWslB5xQld7a9+GVG6LLMXHQ4TvQ8xpocbpFgSRJkiRJpWBhIEkqM+FwhA8+3cm4meuYtnJnyfYTG6Qyuk8rzu/WmOQE/+lRKYSLYdXb0ScJhvwmuq3tEGjeB9oOgm5XQc0GwWaUJEmSJKmS86qNJOmY5eQX8dKCTYybuY7PdkbHjw+FYHD7+ow5vRV92tRx2CGVzv7t8PGTMP8JyNwY3dZlJNQ7EWJi4eq3gs0nSZIkSVIVYmEgSSq1DbtzeWLWOl6Yu5H9+UUA1EyM45KezbjqtBa0qJMScEJVSpEIrJ8Bcx+D5a9BOPp3ixq1odsVkFgz2HySJEmSJFVRFgaSpKMSiUSYuWY3Y2esY8qK7UQi0e2t66Yw+vSWXHBKU1IT/edFpRQuhv8Mgq0Lv9jWtFd0boKTzof4pKCSSZIkSZJU5XlFR5J0RA4UFPPKx5sZN3Mtq7Znl2wf0K4eo/u0pN8J9YiJcdghlcLWxVC7VfTJgZhYqN8Bdq2CzpdAj2ugUeegE0qSJEmSVC1YGEiSvtGmvbk89dF6xs/ZSOaBQgCSE2K5uHtTrurTkjb1UgNOqEqpMA+WvRoddmjTHDjnvuhTBACD74Rhf4ak9EAjSpIkSZJU3VgYSJK+IhKJMGftHsbNXMfbS7cR/nzYoea1kxnVpyUX92hKWlJ8sCFVOe1ZC/Meh4+fhgN7otti4iBr8xf7pDUOJpskSZIkSdWchYEkqUReYTGvLdrCuBnrWLY1q2T76W3rMKZPKwa2r0+sww6pNNZOhxl/h9WTgc8bqLSm0GM0dLsKajYIMp0kSZIkScLCQJIEbMvM4+mP1vPsnA3sySkAICk+hgtOacroPi05sUHNgBOq0tuzBla/G11uOyQ6N8EJZ0GsP4pIkiRJklRR+Fu6JFVTkUiEBRv2MW7mOt5aspWiz8cdapJRg6tOa8H3ejYjIzkh4JSqlCIRWDUJdiyDvj+JbutyGWRthS7fg9qtg80nSZIkSZIOy8JAkqqZgqIwby6JDju0aFNmyfberWoz5vSWDOnQgLjYmAATqtKKRGDlW/D+n2DrIgjFwskXQO1WEJcAA38RdEJJkiRJkvQNLAwkqZrYsT+PZ2dv4JnZG9i5Px+AhLgYzu/amFF9WnJy4/SAE6rSOlgUTPsjbFsc3RafAr2ugyT/XkmSJEmSVFlYGEhSFffJ5kwe/3Atry/eQmFxdNihhmlJXHlaCy7t2Yw6qYkBJ1SltmLiV4uC3tfDabdASp1gs0mSJEmSpKNiYSBJVVAkEuGjz/bwr2mrmf7prpLt3VvUYnSflgzt2JB4hx1SWZg/NloWJKRCr+vhtB9YFEiSJEmSVElZGEhSFRIOR5i6YgcPTlvNxxv2ARAbE+Lczo0Yc3orujTLCDSfKrlIBFa8CTUyoOUZ0W0Dfg4NOloUSJIkSZJUBVgYSFIVUFQc5s0lW/nXe2tYuX0/AIlxMXyvZzOu69uaZrWTA06oSi0chpVvwvt/hm1LoFEXuP59CIWgSffoS5IkSZIkVXoWBpJUieUVFvPSgk088v5nbNiTC0BqYhxXntaCq09vRb2azk+gY3CwKJj2Z9i+JLotoSa0PROKCyDOv1+SJEmSJFUlFgaSVAll5xfx7Oz1/Gf6WnbuzwegTkoCV5/RiitObUF6jfiAE6pSC4dhxRvRJwq2fxLdllATTv0+nHoTJNcONp8kSZIkSSoXFgaSVInszSlg7Mx1PDFzHZkHCgFonJ7E9f1a872ezamREBtwQlUJ+Znw6k1QsN+iQJIkSZKkasTCQJIqga2ZB/jPB2t5bs4GDhQWA9C6Xgo39m/DeV2bkBAXE3BCVWrhMKx4HVoPgKR0qFEL+t4GhQfg1BstCiRJkiRJqiYsDCSpAlu7K4eHp63h5Y83UVgcAaBjkzRuHtCWs05uSGxMKOCEqtTCYVj+WnTooR3LYOAvof/t0ff63hZsNkmSJEmSdNxZGEhSBbR0Syb/mraGt5ZsJRztCejdqjY3D2xL3xPqEgpZFOgYhMOwfAK8/5doUQCQmAZxScHmkiRJkiRJgbIwkKQKZO66PTz43mqmrdxZsm1w+/rcNLAN3Vs4LIyO0cGiYNqfYefy6LbE9OiwQ6d+PzoUkSRJkiRJqrYsDCQpYJFIhGmrdvKv91Yzd91eAGJCcG6Xxtw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" ] @@ -1661,381 +80,65 @@ } ], "source": [ - "data = iohinspector.get_data_ecdf(\n", - " df\n", - ")\n", - "print(data)\n", - "data.to_csv(\"ecdf_data.csv\", index=False)\n", - "iohinspector.plot_ecdf(\n", + "from iohinspector import DataManager, plot_ecdf\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"SO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1]).load(True, True)\n", + "ax, data = plot_ecdf(\n", " df,\n", - " y_min = 1.0,\n", - " y_max = 1.0,\n", + " file_name=\"example_plots/ecdf.png\"\n", ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "be98d83c", + "execution_count": 92, + "id": "a06cd442", "metadata": {}, "outputs": [ { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n", - "thread '' panicked at crates/polars-python/src/dataframe/general.rs:351:73:\n", - "called `Result::unwrap()` on an `Err` value: PyErr { type: , value: KeyboardInterrupt(), traceback: Some(\"Traceback (most recent call last):\\n File \\\"/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/_utils/wrap.py\\\", line 12, in wrap_df\\n def wrap_df(df: PyDataFrame) -> DataFrame:\\n\") }\n", - "note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace\n" - ] - }, - { - "ename": "PanicException", - "evalue": "called `Result::unwrap()` on an `Err` value: PyErr { type: , value: KeyboardInterrupt(), traceback: Some(\"Traceback (most recent call last):\\n File \\\"/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/_utils/wrap.py\\\", line 12, in wrap_df\\n def wrap_df(df: PyDataFrame) -> DataFrame:\\n\") }", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mPanicException\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43miohinspector\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43maggegate_convergence\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfree_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43malgorithm_name\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m result\u001b[38;5;241m.\u001b[39mto_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124maggregated_result.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(result)\n", - "File \u001b[0;32m~/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/metrics.py:94\u001b[0m, in \u001b[0;36maggegate_convergence\u001b[0;34m(data, evaluation_variable, fval_variable, free_variables, x_min, x_max, custom_op, maximization, return_as_pandas)\u001b[0m\n\u001b[1;32m 92\u001b[0m x_values \u001b[38;5;241m=\u001b[39m get_sequence(x_min, x_max, \u001b[38;5;241m50\u001b[39m, scale_log\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, cast_to_int\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[1;32m 93\u001b[0m group_variables \u001b[38;5;241m=\u001b[39m free_variables \u001b[38;5;241m+\u001b[39m [evaluation_variable]\n\u001b[0;32m---> 94\u001b[0m data_aligned \u001b[38;5;241m=\u001b[39m \u001b[43malign_data\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 95\u001b[0m \u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcast\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[43mevaluation_variable\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mpl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mInt64\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 96\u001b[0m \u001b[43m \u001b[49m\u001b[43mx_values\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 97\u001b[0m \u001b[43m \u001b[49m\u001b[43mgroup_cols\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdata_id\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mfree_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 98\u001b[0m \u001b[43m \u001b[49m\u001b[43mx_col\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mevaluation_variable\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 99\u001b[0m \u001b[43m \u001b[49m\u001b[43my_col\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfval_variable\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 100\u001b[0m \u001b[43m \u001b[49m\u001b[43mmaximization\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmaximization\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 101\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 103\u001b[0m aggregations \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 104\u001b[0m pl\u001b[38;5;241m.\u001b[39mmean(fval_variable)\u001b[38;5;241m.\u001b[39malias(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmean\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 105\u001b[0m pl\u001b[38;5;241m.\u001b[39mmin(fval_variable)\u001b[38;5;241m.\u001b[39malias(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmin\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 111\u001b[0m \u001b[38;5;241m.\u001b[39malias(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgeometric_mean\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 112\u001b[0m ]\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m custom_op \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", - "File \u001b[0;32m~/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/align.py:58\u001b[0m, in \u001b[0;36malign_data\u001b[0;34m(df, evals, group_cols, x_col, y_col, output, maximization)\u001b[0m\n\u001b[1;32m 55\u001b[0m merged \u001b[38;5;241m=\u001b[39m merged\u001b[38;5;241m.\u001b[39mwith_columns(pl\u001b[38;5;241m.\u001b[39mlit(group[col][\u001b[38;5;241m0\u001b[39m])\u001b[38;5;241m.\u001b[39malias(col))\n\u001b[1;32m 56\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m merged\n\u001b[0;32m---> 58\u001b[0m result_df \u001b[38;5;241m=\u001b[39m \u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroup_by\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mgroup_cols\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmap_groups\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmerge_asof_group\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 60\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m output \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlong\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 61\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m result_df\n", - "File \u001b[0;32m~/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/dataframe/group_by.py:313\u001b[0m, in \u001b[0;36mGroupBy.map_groups\u001b[0;34m(self, function)\u001b[0m\n\u001b[1;32m 309\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot call `map_groups` when grouping by an expression\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 310\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(msg)\n\u001b[1;32m 312\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdf\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m_from_pydf(\n\u001b[0;32m--> 313\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_df\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgroup_by_map_groups\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 314\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mby\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunction\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaintain_order\u001b[49m\n\u001b[1;32m 315\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 316\u001b[0m )\n", - "\u001b[0;31mPanicException\u001b[0m: called `Result::unwrap()` on an `Err` value: PyErr { type: , value: KeyboardInterrupt(), traceback: Some(\"Traceback (most recent call last):\\n File \\\"/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/polars/_utils/wrap.py\\\", line 12, in wrap_df\\n def wrap_df(df: PyDataFrame) -> DataFrame:\\n\") }" - ] + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ + "from iohinspector import DataManager, plot_eaf_single_objective\n", + "import os\n", "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", "\n", - "result = iohinspector.aggegate_convergence(df, free_variables=[\"algorithm_name\"])\n", - "result.to_csv(\"aggregated_result.csv\", index=False)\n", + "manager = DataManager()\n", + "manager.add_folder(\"SO_Data\")\n", "\n", - "print(result)\n" + "df = manager.select(function_ids=[1], algorithms=['HillClimber']).load(True, True)\n", + "ax, data = plot_eaf_single_objective(\n", + " df,\n", + " file_name=\"example_plots/eaf_single_objective.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "3ec53f22", + "execution_count": 93, + "id": "433832c8", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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evaluationsalgorithm_namevariablevalue
1701.0RandomSearchgeometric_mean11.502018
20182.0RandomSearchgeometric_mean0.328777
20075.0RandomSearchgeometric_mean0.344017
19968.0RandomSearchgeometric_mean0.349327
19862.0RandomSearchgeometric_mean0.370701
19756.0RandomSearchgeometric_mean0.425972
19651.0RandomSearchgeometric_mean0.462630
19547.0RandomSearchgeometric_mean0.552266
19442.0RandomSearchgeometric_mean0.619678
19339.0RandomSearchgeometric_mean0.619678
19235.0RandomSearchgeometric_mean0.644307
19132.0RandomSearchgeometric_mean0.676764
19029.0RandomSearchgeometric_mean0.768394
18926.0RandomSearchgeometric_mean1.044003
18824.0RandomSearchgeometric_mean1.044003
18722.0RandomSearchgeometric_mean1.044003
18620.0RandomSearchgeometric_mean1.075136
18518.0RandomSearchgeometric_mean1.115466
1712.0RandomSearchgeometric_mean7.789763
1723.0RandomSearchgeometric_mean6.146942
1734.0RandomSearchgeometric_mean3.823311
1745.0RandomSearchgeometric_mean2.884371
1756.0RandomSearchgeometric_mean2.811844
1767.0RandomSearchgeometric_mean2.549035
20291.0RandomSearchgeometric_mean0.328777
1778.0RandomSearchgeometric_mean1.989434
17910.0RandomSearchgeometric_mean1.496137
18011.0RandomSearchgeometric_mean1.469509
18112.0RandomSearchgeometric_mean1.449580
18213.0RandomSearchgeometric_mean1.350359
18315.0RandomSearchgeometric_mean1.318729
18416.0RandomSearchgeometric_mean1.115466
1789.0RandomSearchgeometric_mean1.703058
20399.0RandomSearchgeometric_mean0.328777
\n", - "
" - ], - "text/plain": [ - " evaluations algorithm_name variable value\n", - "170 1.0 RandomSearch geometric_mean 11.502018\n", - "201 82.0 RandomSearch geometric_mean 0.328777\n", - "200 75.0 RandomSearch geometric_mean 0.344017\n", - "199 68.0 RandomSearch geometric_mean 0.349327\n", - "198 62.0 RandomSearch geometric_mean 0.370701\n", - "197 56.0 RandomSearch geometric_mean 0.425972\n", - "196 51.0 RandomSearch geometric_mean 0.462630\n", - "195 47.0 RandomSearch geometric_mean 0.552266\n", - "194 42.0 RandomSearch geometric_mean 0.619678\n", - "193 39.0 RandomSearch geometric_mean 0.619678\n", - "192 35.0 RandomSearch geometric_mean 0.644307\n", - "191 32.0 RandomSearch geometric_mean 0.676764\n", - "190 29.0 RandomSearch geometric_mean 0.768394\n", - "189 26.0 RandomSearch geometric_mean 1.044003\n", - "188 24.0 RandomSearch geometric_mean 1.044003\n", - "187 22.0 RandomSearch geometric_mean 1.044003\n", - "186 20.0 RandomSearch geometric_mean 1.075136\n", - "185 18.0 RandomSearch geometric_mean 1.115466\n", - "171 2.0 RandomSearch geometric_mean 7.789763\n", - "172 3.0 RandomSearch geometric_mean 6.146942\n", - "173 4.0 RandomSearch geometric_mean 3.823311\n", - "174 5.0 RandomSearch geometric_mean 2.884371\n", - "175 6.0 RandomSearch geometric_mean 2.811844\n", - "176 7.0 RandomSearch geometric_mean 2.549035\n", - "202 91.0 RandomSearch geometric_mean 0.328777\n", - "177 8.0 RandomSearch geometric_mean 1.989434\n", - "179 10.0 RandomSearch geometric_mean 1.496137\n", - "180 11.0 RandomSearch geometric_mean 1.469509\n", - "181 12.0 RandomSearch geometric_mean 1.449580\n", - "182 13.0 RandomSearch geometric_mean 1.350359\n", - "183 15.0 RandomSearch geometric_mean 1.318729\n", - "184 16.0 RandomSearch geometric_mean 1.115466\n", - "178 9.0 RandomSearch geometric_mean 1.703058\n", - "203 99.0 RandomSearch geometric_mean 0.328777" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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"text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -2043,210 +146,76 @@ } ], "source": [ - "iohinspector.single_function_fixedbudget(\n", + "from iohinspector import DataManager, plot_eaf_pareto, add_normalized_objectives\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"MO_Data\")\n", + "\n", + "df = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False)\n", + "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", + "ax, data = plot_eaf_pareto(\n", " df,\n", - " x_min = 1,\n", - " x_max = 100,\n", - " \n", + " obj1_var=\"obj1\",\n", + " obj2_var=\"obj2\",\n", + " file_name=\"example_plots/eaf_pareto.png\"\n", ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "b5441187", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "shape: (15,)\n", - "Series: 'data_id' [u64]\n", - "[\n", - "\t16\n", - "\t17\n", - "\t18\n", - "\t19\n", - "\t20\n", - "\t…\n", - "\t26\n", - "\t27\n", - "\t28\n", - "\t29\n", - "\t30\n", - "]\n", - "shape: (1,)\n", - "Series: 'run_id' [u32]\n", - "[\n", - "\t1\n", - "]\n" - ] - } - ], - "source": [ - "print(df[\"data_id\"].unique())\n", - "df_one_run = df.filter(df[\"data_id\"] == 16)\n", - "print(df_one_run[\"run_id\"].unique())\n", - "# iohinspector.heatmap_single_run(\n", - "# df_one_run,\n", - "# var_cols=[\"x1\"],\n", - "# x_mins=[-5]*len(df_one_run[\"x1\"]),\n", - "# x_maxs=[5]*len(df_one_run[\"x1\"])\n", - "# )\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "429e1ce2", + "execution_count": 94, + "id": "bcb34ed4", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "['data_id', 'algorithm_name', 'algorithm_info', 'suite', 'function_name', 'function_id', 'dimension', 'instance', 'run_id', 'evals', 'best_y']\n", - "shape: (327, 15)\n", - "┌─────────┬────────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n", - "│ data_id ┆ algorithm_ ┆ algorithm ┆ suite ┆ … ┆ evaluatio ┆ raw_y ┆ x0 ┆ x1 │\n", - "│ --- ┆ name ┆ _info ┆ --- ┆ ┆ ns ┆ --- ┆ --- ┆ --- │\n", - "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ --- ┆ f64 ┆ f64 ┆ f64 │\n", - "│ ┆ str ┆ str ┆ ┆ ┆ u64 ┆ ┆ ┆ │\n", - "╞═════════╪════════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n", - "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 1 ┆ 23.543464 ┆ 4.758863 ┆ 0.642882 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 3 ┆ 14.131865 ┆ 2.082703 ┆ 2.126997 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 4 ┆ 0.856332 ┆ 1.118578 ┆ -0.830057 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.174824 ┆ -0.096888 ┆ -1.386022 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 16 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 179 ┆ 0.17166 ┆ -0.129436 ┆ -0.996938 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 25 ┆ 1.521586 ┆ -5.0 ┆ -3.120021 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 27 ┆ 0.03135 ┆ -3.802689 ┆ -2.502291 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.029183 ┆ -3.781128 ┆ -2.828955 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 42 ┆ 0.00491 ┆ -3.831461 ┆ -2.740264 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 81 ┆ 0.004026 ┆ -3.853244 ┆ -2.736186 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘\n", - " run_id raw_y mean min max median std success_ratio \\\n", - "0 7 0.000065 inf 566.0 inf inf NaN 0.5 \n", - "1 12 0.000065 inf inf inf inf NaN 0.0 \n", - "2 11 0.000065 inf inf inf inf NaN 0.0 \n", - "3 9 0.000065 inf inf inf inf NaN 0.0 \n", - "4 15 0.000065 inf inf inf inf NaN 0.0 \n", - ".. ... ... ... ... ... ... ... ... \n", - "745 5 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", - "746 11 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", - "747 8 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", - "748 13 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", - "749 2 87.292576 1.0 1.0 1.0 1.0 0.0 1.0 \n", - "\n", - " success_count ERT PAR-10 \n", - "0 1 1561.0 5258.0 \n", - "1 0 inf 9950.0 \n", - "2 0 inf 9950.0 \n", - "3 0 inf 9950.0 \n", - "4 0 inf 9950.0 \n", - ".. ... ... ... \n", - "745 2 1.0 1.0 \n", - "746 2 1.0 1.0 \n", - "747 2 1.0 1.0 \n", - "748 2 1.0 1.0 \n", - "749 2 1.0 1.0 \n", - "\n", - "[750 rows x 11 columns]\n" - ] + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "manager = iohinspector.DataManager()\n", - "data_folders = [\"test_data/RS\", \"test_data/HC\"]\n", - "manager.add_folders(data_folders)\n", + "from iohinspector import DataManager, plot_eaf_diffs, add_normalized_objectives\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", "\n", + "manager = DataManager()\n", + "manager.add_folder(\"MO_Data\")\n", "\n", - "print(manager.overview.columns)\n", - "selection = manager.select(function_ids=[1])\n", - "df = selection.load(monotonic=True, include_meta_data=True,)\n", + "df1 = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False)\n", + "df1 = add_normalized_objectives(df1, obj_vars = ['raw_y', 'F2'])\n", "\n", - "print(df)\n", - "result = iohinspector.aggegate_running_time(df, free_variables=[\"run_id\"])\n", - "result.to_csv(\"aggregated_result.csv\", index=False)\n", + "df2 = manager.select(function_ids=[0], algorithms=['SMS-EMOA']).load(False, False)\n", + "df2 = add_normalized_objectives(df2, obj_vars = ['raw_y', 'F2'])\n", "\n", - "print(result)\n" + "ax, data = plot_eaf_diffs(\n", + " df1,\n", + " df2,\n", + " obj1_var=\"obj1\",\n", + " obj2_var=\"obj2\",\n", + " file_name=\"example_plots/eaf_diffs.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "7bf5c582", + "execution_count": 95, + "id": "b7c6fdf1", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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"text/plain": [ - " Rating Deviation algorithm_name\n", - "0 1481.847229 6.719253 RandomSearch\n", - "1 1518.152771 6.719253 HillClimber" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" ] }, "metadata": {}, @@ -2254,219 +223,63 @@ } ], "source": [ - "iohinspector.plot_tournament_ranking(df)\n" + "from iohinspector import DataManager, plot_single_function_fixed_budget\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"SO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1]).load(True, True)\n", + "ax, data = plot_single_function_fixed_budget(\n", + " df,\n", + " file_name=\"example_plots/fixed_budget.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "1c8dbaf3", + "execution_count": 96, + "id": "acb246b8", "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "['data_id', 'algorithm_name', 'algorithm_info', 'suite', 'function_name', 'function_id', 'dimension', 'instance', 'run_id', 'evals', 'best_y']\n", - "shape: (599, 15)\n", - "┌─────────┬────────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n", - "│ data_id ┆ algorithm_ ┆ algorithm ┆ suite ┆ … ┆ evaluatio ┆ raw_y ┆ x0 ┆ x1 │\n", - "│ --- ┆ name ┆ _info ┆ --- ┆ ┆ ns ┆ --- ┆ --- ┆ --- │\n", - "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ --- ┆ f64 ┆ f64 ┆ f64 │\n", - "│ ┆ str ┆ str ┆ ┆ ┆ u64 ┆ ┆ ┆ │\n", - "╞═════════╪════════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n", - "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 1 ┆ 8.2124e6 ┆ -0.530698 ┆ -2.494956 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 5 ┆ 3.5690e6 ┆ 0.781847 ┆ -1.365995 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 9 ┆ 143888.77 ┆ 1.231167 ┆ 0.847804 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ 7772 ┆ ┆ │\n", - "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 24 ┆ 69448.892 ┆ -1.347449 ┆ 0.709334 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ 009 ┆ ┆ │\n", - "│ 1 ┆ RandomSear ┆ algorithm ┆ unknown_s ┆ … ┆ 102 ┆ 27086.700 ┆ -4.78153 ┆ 0.293066 │\n", - "│ ┆ ch ┆ _info ┆ uite ┆ ┆ ┆ 878 ┆ ┆ │\n", - "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 25 ┆ 1.521586 ┆ -5.0 ┆ -3.120021 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 27 ┆ 0.03135 ┆ -3.802689 ┆ -2.502291 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.029183 ┆ -3.781128 ┆ -2.828955 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 42 ┆ 0.00491 ┆ -3.831461 ┆ -2.740264 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 81 ┆ 0.004026 ┆ -3.853244 ┆ -2.736186 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘\n" - ] + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "manager = iohinspector.DataManager()\n", - "data_folders = [\"test_data/RS\", \"test_data/HC\"]\n", - "manager.add_folders(data_folders)\n", + "from iohinspector import DataManager, plot_single_function_fixed_target\n", + "import os\n", "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", "\n", - "print(manager.overview.columns)\n", - "selection = manager.select()\n", - "df = selection.load(monotonic=True, include_meta_data=True,)\n", + "manager = DataManager()\n", + "manager.add_folder(\"SO_Data\")\n", "\n", - "print(df)\n", - "result = iohinspector.aggegate_running_time(df, free_variables=[\"run_id\"])\n", - "result.to_csv(\"aggregated_result.csv\", index=False)\n" + "df = manager.select(function_ids=[1]).load(True, True)\n", + "ax, data = plot_single_function_fixed_target(\n", + " df,\n", + " file_name=\"example_plots/fixed_target.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "08998b29", + "execution_count": 97, + "id": "68d3bb56", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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15825.233434e+06RandomSearch2ERT2.800000
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" - ], - "text/plain": [ - " raw_y algorithm_name function_id variable value\n", - "1401 6.490770e-05 HillClimber 1 ERT 14496.000000\n", - "1404 1.134130e-04 HillClimber 1 ERT 14496.000000\n", - "1410 1.981660e-04 HillClimber 1 ERT 14496.000000\n", - "1415 3.462546e-04 HillClimber 1 ERT 4688.333333\n", - "1418 6.050093e-04 HillClimber 1 ERT 2686.000000\n", - "... ... ... ... ... ...\n", - "1582 5.233434e+06 RandomSearch 2 ERT 2.800000\n", - "1585 9.144358e+06 RandomSearch 2 ERT 2.133333\n", - "1588 1.597790e+07 RandomSearch 2 ERT 1.733333\n", - "1595 2.791812e+07 RandomSearch 2 ERT 1.200000\n", - "1597 4.878121e+07 RandomSearch 2 ERT 1.066667\n", - "\n", - "[200 rows x 5 columns]" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" ] @@ -2476,163 +289,33 @@ } ], "source": [ - "iohinspector.single_function_fixedtarget(\n", + "from iohinspector import DataManager, plot_paretofronts_2d\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"MO_Data\")\n", + "\n", + "df = manager.select().load(True, True)\n", + "\n", + "ax, data = plot_paretofronts_2d(\n", " df,\n", - " free_variables=[\"algorithm_name\",\"function_id\"],)" + " obj1_var=\"raw_y\",\n", + " obj2_var=\"F2\",\n", + " file_name=\"example_plots/pareto_fronts.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "0d489441", + "execution_count": 98, + "id": "a5fcfc56", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
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evaluationsalgorithm_namefunction_idvariablevalue
8431.0HillClimber1geometric_mean17.691640
8472.0HillClimber1geometric_mean14.095624
8513.0HillClimber1geometric_mean11.517027
8554.0HillClimber1geometric_mean8.645013
8575.0HillClimber1geometric_mean7.502348
..................
991566.0RandomSearch2geometric_mean48.534221
995652.0RandomSearch2geometric_mean39.839912
996750.0RandomSearch2geometric_mean36.944067
1002864.0RandomSearch2geometric_mean27.835512
1005995.0RandomSearch2geometric_mean27.789929
\n", - "

168 rows × 5 columns

\n", - "
" - ], - "text/plain": [ - " evaluations algorithm_name function_id variable value\n", - "843 1.0 HillClimber 1 geometric_mean 17.691640\n", - "847 2.0 HillClimber 1 geometric_mean 14.095624\n", - "851 3.0 HillClimber 1 geometric_mean 11.517027\n", - "855 4.0 HillClimber 1 geometric_mean 8.645013\n", - "857 5.0 HillClimber 1 geometric_mean 7.502348\n", - "... ... ... ... ... ...\n", - "991 566.0 RandomSearch 2 geometric_mean 48.534221\n", - "995 652.0 RandomSearch 2 geometric_mean 39.839912\n", - "996 750.0 RandomSearch 2 geometric_mean 36.944067\n", - "1002 864.0 RandomSearch 2 geometric_mean 27.835512\n", - "1005 995.0 RandomSearch 2 geometric_mean 27.789929\n", - "\n", - "[168 rows x 5 columns]" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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"text/plain": [ "
" ] @@ -2642,68 +325,36 @@ } ], "source": [ - "iohinspector.single_function_fixedbudget(\n", - " df,\n", - " free_variables=[\"algorithm_name\",\"function_id\"],)" + "from iohinspector import DataManager, plot_indicator_over_time, add_normalized_objectives, get_reference_set, IGDPlus\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"MO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1]).load(False, True)\n", + "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", + "ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000)\n", + "\n", + "igdp_indicator = IGDPlus(reference_set = ref_set)\n", + "\n", + "ax, data = plot_indicator_over_time(\n", + " df, ['obj1', 'obj2'], igdp_indicator, \n", + " eval_min=10, eval_max=2000, eval_steps=50, free_var='algorithm_name',\n", + " file_name=\"example_plots/indicator_over_time.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "311d1389", + "execution_count": 102, + "id": "891e6be7", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
\n", - "shape: (2_520, 15)
evaluationsdata_idalgorithm_namealgorithm_infosuitefunction_namefunction_iddimensioninstancerun_idevalsbest_yraw_yx0x1
f64i32strstrstrstrf64f64f64f64f64f64f64f64f64
1.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019158.635203-4.8888233.862607
2.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019148.239593-3.8185795.0
3.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019145.920072-3.6389264.993428
4.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019139.832259-3.3830654.335506
5.053"HillClimber""algorithm_info""unknown_suite""Sphere"1.02.08.08.01000.00.0019133.091874-2.6180864.776682
………………………………………
566.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
652.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
750.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
864.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
995.040"HillClimber""algorithm_info""unknown_suite""Ellipsoid"2.02.010.010.01000.02.5325312.5325310.9995271.384652
" - ], - "text/plain": [ - "shape: (2_520, 15)\n", - "┌────────────┬─────────┬────────────┬────────────┬───┬──────────┬───────────┬───────────┬──────────┐\n", - "│ evaluation ┆ data_id ┆ algorithm_ ┆ algorithm_ ┆ … ┆ best_y ┆ raw_y ┆ x0 ┆ x1 │\n", - "│ s ┆ --- ┆ name ┆ info ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n", - "│ --- ┆ i32 ┆ --- ┆ --- ┆ ┆ f64 ┆ f64 ┆ f64 ┆ f64 │\n", - "│ f64 ┆ ┆ str ┆ str ┆ ┆ ┆ ┆ ┆ │\n", - "╞════════════╪═════════╪════════════╪════════════╪═══╪══════════╪═══════════╪═══════════╪══════════╡\n", - "│ 1.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 58.635203 ┆ -4.888823 ┆ 3.862607 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 2.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 48.239593 ┆ -3.818579 ┆ 5.0 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 3.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 45.920072 ┆ -3.638926 ┆ 4.993428 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 4.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 39.832259 ┆ -3.383065 ┆ 4.335506 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 5.0 ┆ 53 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 0.00191 ┆ 33.091874 ┆ -2.618086 ┆ 4.776682 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", - "│ 566.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 652.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 750.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 864.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "│ 995.0 ┆ 40 ┆ HillClimbe ┆ algorithm_ ┆ … ┆ 2.532531 ┆ 2.532531 ┆ 0.999527 ┆ 1.384652 │\n", - "│ ┆ ┆ r ┆ info ┆ ┆ ┆ ┆ ┆ │\n", - "└────────────┴─────────┴────────────┴────────────┴───┴──────────┴───────────┴───────────┴──────────┘" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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QeAAgXbWerCPorL3mCAUAgG6gIhQAAAAAKDwVoQDQBVq14pyySyO1rEPorOHsFhIq9ab0XO5OpxsAAEiSilAAAAAAoPAkQgEAAACAwpMIBQAAAAAKTyIUAAAAACi84qy80OVa5YhWJesoAAAAAKCYJEIBEtboKWUdwjE1azmIb0/WAQAAAFB0hsYDAAAAAIWnIhQAOqxV6fx1xlI0Ot4mAADAZCIRmhOt6v4fiq/Zk3UE+VdqZh1Bh/VlHcCxNQezHxqfi+H5HdSsdX7S51KjOG+M1nC6k2KXRiSRAQAAiVCASS8Pyfm051Gt1Fup9gcAAED2JEIByFzRKkJzkFsGAADgXSRCc6LV04pmjwqlyaCZ8xXE6bxWzpelG+mbfH+T5crke8wAAACTXc6/ngMAAAAATJxEKAAAAABQeBKhAAAAAEDhmSMUADqsWev8dcbysGuXAAAAE+FbFQAAAABQeBKhAAAAAEDhGRoPADARtZ7s+t7byK5vAADoMipCAQAAAIDCkwgFAAAAAApPIhQAAAAAKDyJUAAAAACg8CyWBAAd1uhL4jpjhgvydFjl7b1ZhwAAAExCEqGQslYl6wjyr5l1AJNMMwf5tUajlHKPrURbb/R0/vGUh9N+jpLTqhXr40cpatl1PlxPpZtSNQf/KHKuNZLOawEAwPgV65sIAABkQLJ4fCSQAYA0SYQCQIc1a52v3mzWC1QR2ptuaXxpeCTV/gAAgHySCAWADmtWOp+0TGK4fVZalXTXaizaUPyDlWrpVCGW+npT6aebtfYNZR0CAADHYdV4AAAAAKDwJEIBAAAAgMKTCAUAAAAACq+4k2YBABRdrZZ1BAAA0DVUhAIAAAAAhScRCgAAAAAUnkToGHzuc5+LUql0zJ/f+73fyzpMAAAAAOBdzBE6Dj/xEz8R/+7f/bsj/u7ss89ONxgAAAAA4LgkQsfhl37pl2LZsmVZhwEAAAAAjJJEKJA7rUrWEXRWM+sAjqOZgzNBwV5yAAAAcigHX38BIF2NnlLCPbQ63mKzkXTM6WnW0k19lxp5vxwxfqWRRtYhAABA18hVIrTRaMS6deviueeeizVr1sRzzz0XL7zwQtTr9YiIWLhwYaxevXpcbQ8PD8fXv/71ePjhh2PdunWxdevWOOmkk+Kcc86J6667Lj72sY/FrFmzRtXWD37wg7j55ptjy5Yt0d/fH+95z3vihhtuiEsuuWRcsQEAAAAAycpNIvSxxx6Lm2++OQYHBzve9vr162PJkiWxdu3aQ+4fGBiIgYGBeOaZZ+Kee+6JBx98MBYvXnzc9tauXXtIW48//nj84R/+YXzsYx+LP/7jP46+vr4OPwIAAAAAYCJykwh9++23E0mCvvHGG7Fo0aLYvHlzRESUSqVYsGBBnHfeebFt27Z48sknY+/evfHmm2/GtddeG9/61rfiqquuOmJbp59+enzuc5+LX/zFX4xzzz03ZsyYEa+99losW7YsvvKVr8SyZcuiXq/H1772tY4/DoCktMpZR1C8eWEbUZxh7Elo9BXrBS9XsnsTlYZH0umnt5ZY262h4cTaBgCAg+UmEXrA7NmzY/78+e2fJ554Iu69995xt3fTTTe1k6Bz5syJ5cuXx0UXXdT+/VtvvRU33nhjrFy5Mur1etxwww3x6quvxowZMw5r6/bbbz/svrlz58Yf/uEfxsUXXxxLliyJv/zLv4zf+I3fiMsuu2zcMQMAAAAAnZWbROiHPvSh2LhxY5x11lmH3P/ss8+Ou80VK1bEU089FRERtVotHn/88Zg3b94h+8yaNSuWL18eF154Ybz22muxY8eO+PKXvxxf/OIXx9TXjTfeGF/96lfjn/7pn+J//+//LREKdI1mT9YR5COGTkqkPrCeRKMAAACTRw4GRO536qmnHpYEnaj77ruvvX3rrbcelgQ9YNq0aXH33Xe3b99///0xMjL2oWZXXHFFRET8y7/8y5iPBYDJolkrpfxTTvQHAADoDoX99L579+5YuXJl+/bSpUuPuf/1118f/f39ERGxY8eO+M53vjPmPmu1/fNnHVjlHgAAAADIh9wMje+0p59+OoaGhiJif8Xn/Pnzj7l/X19fXHbZZfHtb387IiJWrVp11EWTjubFF1+MiIgzzzxzHBEDAIxNq5bOR7lSJbkFrpJciIn8a+1WQAAApKewFaEvvfRSe3vevHlRrR7/i8Ill1xyxONHY+3atfHEE09ERMQv/uIvjulYAAAAACBZha0Iffnll9vbc+bMGdUxB89Run79+kN+t27durj33nvjE5/4RLz3ve895Hff/OY349d+7dei0WjEJZdcEh/5yEcmEDkAFFujp5Rqf+XhZPtr1pKrljyeUqOZTke1BFc0G06u6cM0Gil2BgBA3hQ2Ebp9+/b29uzZs0d1zKmnntre3rFjxyG/q9fr8Sd/8ifxJ3/yJzFjxow455xzoqenJ370ox/Ftm3bIiLiwgsvjOXLl0e5fPRC26GhofaQ/YiInTt3jio2AAAAAGD8Cjs0fvfu3e3tKVOmjOqYg/c7+PiIiLPPPjv+4A/+IK655pqYOXNmvPrqq/H9738/IiJ+/ud/Pu6///74p3/6pzjjjDOO2ceXvvSlOPHEE9s/5hMFAAAAgOQVtiJ037597e0Dq7kfT29vb3t77969h/xuxowZ8dnPfnbCcX3mM5+JT33qU+3bO3fulAwFAAAAgIQVNhHa19fX3h4eHt3kUwcPWR9tFelY9fb2HpJwBQAAAACSV9ih8f39/e3td1d3Hs3B+x18PAAAAADQ3QqbCJ05c2Z7e+vWraM6ZmBgoL198skndzwmAAAAACAbhU2Enn/++e3tjRs3juqYTZs2tbfnzp3b8ZgAAAAAgGwUNhF6wQUXtLdffPHFGBkZOe4xzz///BGPBwAAAAC6W2EToZdffnl7UaI9e/bEmjVrjrn/0NBQfO9732vfvuqqqxKNDwAAAABIT2ETof39/bFo0aL27WXLlh1z/0cffTR27doVEfvnB12wYEGS4QEAAAAAKSpsIjQi4o477mhvL1u2LNatW3fE/QYHB+Ouu+5q37799tujWq0mHh8AAAAAkI5CZ/uuvvrquPLKK+Opp56KoaGhuOaaa2L58uVx4YUXtvfZvn17LFmyJF555ZWI2F8Neuedd2YVMgDA5FLrSa+v4eSaLvXWkmu8wEr7Unz9yZ3WSD3rEACYZHKVCF28eHFs3rz5kPsGBgba22vWrImLL774sONWrFgRp59++hHbfOihh+LSSy+NLVu2xIYNG+Liiy+OhQsXxnnnnRfbtm2LJ598MgYHByMiolqtxje+8Y2YMWNGxx4TQKuSdQTH1sw6gIho5upsNHFl3+sAAAByJ1dfPX/4wx/Gxo0bj/r7PXv2xA9+8IPD7h8ePvrl/TPOOCNWrVoVS5YsibVr10ar1YrVq1fH6tWrD9nvlFNOiQcffPCQeUUBAPKsVUlplqNagtWOx/gcBwAAnZSrRGhS5s6dG88++2w88sgj8fDDD8e6deti69atMWPGjDj33HPjuuuui6VLl8asWbOyDhUAIHda1eRK20tRkCHlaeRzG40UOgEAKK5cJUI3bNiQWNu1Wi1uueWWuOWWWxLrAwAAAADIp1wlQgEAuk2zltLw9CMoD6sQBACA0ZIIBYAOayawCHKjUep8oxlp1tJ9LM16sv1V9rUSbR8AAOgMiVAA6LBmAmfXcnJTNAIAAEwKEqEAZK6V3cjirpFElWlWRvrSrQgtDyfbX9LtH0uzlk6GvFwrxkfGUpILGtVSeJOmsSBTykp9vVmHQIZau+tZhwDAJOOrJwAAAABQeBKhAAAAAEDhFWOcEwAAXamV6rD7KSn21XnFWTLt35QajaxD6DqtoQLOkQAAKVERCgAAAAAUnopQACBVjZ5069qatWT7a9azq9MrNdO5pt3qTWdRJo6tNFLLOoTOG7ZYzliVepP/O1B1CkBRqQgFAAAAAApPRSgAQJdqlYs4ayQAACRDIhQAgGNqVQoyiKg3uaZLQxb9AQDIu4J8qgUAAAAAODoVoQAAAN2iYvEyABgviVAAIFWtlL/DNyvJzqPZ6Cn+PJ3NWnIvWnnYkHIAANJhaDwAAAAAUHgSoQAAAABA4UmEAgAAAACFZ45QAKDQmj0Jt98o/hyh5b7k5ght1tK7Ll/dXU+u8d7kmm4bTKEPSFGpmvA/6BS1RhL8/wJAx6gIBQAAAAAKTyIUAAAAACg8iVAAAAAAoPDMEQoAwKTQrCU312l5OLGm21rV5OLPSqlWnDkii6TUaGQdQke19g1lHQIAOaEiFAAAAAAoPIlQAAAAAKDwDI0HAOhSzVopnX7qyfVT2ddKrG0AADiYRCgAAJCNWi3rCDiS4Xoq3ZR6C/T670unm9ZIOq8NQFEZGg8AAAAAFJ5EKAAAAABQeBKhAAAAAEDhSYQCAAAAAIUnEQoAAAAAFJ5V4wHIXLMn6wjyr9TMOoLu1WiUEm2/nOECvuVGK7vOAQCgy0iEAkAXaBVoDEcz5U8flXS7g8S0aum9eUrDI6n1BQCQlgJ9rQIAAAAAODIVoQBAobUSLgnNdmqHZIf9H9DoSa6f8nA6jyEiolnr7hqAUsMcGaSjVEvpH9twOt0AwAHd/WkQAAAAAGAUJEIBAAAAgMKTCAUAAAAACs8coQAAAPybWi3rCDqq1GhkHULn7Eu+i9ZIPflOADIiEQpA5rJdbIa0lVP+fjUyJeke0lvs592q0Uqln2YjucfYrKf3/FX2pfN8AQCQTxKhAAAAtLWqlVT6KUVKlad7UyijBKArSIQCAJCZRk96FaHl4QQrW2vJT71f2Zt4FwAAhWaxJAAAAACg8CRCAQAAAIDCMzQeAEhV2otjJb04U5aLfTUSXMToYIk+hykuTp3kwkzl4cSabmtVUqxh6E2nm9LwSDodAQCERCgAAJCRVs3XkbGSPAaA8TM0HgAAAAAoPIlQAAAAAKDwJEIBAAAAgMKTCAUAAAAACk8iFAAAAAAoPMs0AgAAkLpWtZJKP6VK8v2UemuJ95GW1u561iEAJEYiFFLW8q4DxqGZdQAcVSnDF6ecTg4BAAAKwdB4AAAAAKDwJEIBAAAAgMIzSBcAYAJaGV5WbvYUoZ9Sko0fotGTXl9JaNbSmwuhPJxSR70p9cOkVqql8M8yrfcMABMiEZoTrcr+H4qvGa2sQ4BDlFNMQkAWijy/alrzkyabQEzvvNhsdPf/u5Ty3gAAhSURCgAAQHHVirOie6nRSL6PfS675E1rpJ51CFAYEqEAAF0qrWH5SY5aaaRYlV7dZ1QGAMBkZrEkAAAAAKDwVIQCADApNCsJVp+mMPK2WSteDUNqizIViQWmxqw1nPxiDKU0/glEROzdl04/AAUlEQowyTV7DBXtBha1yq8iL8Z0QJKrxhcvtQcAQF5JhAIAAMAEtKrJV51GRJQqKVS39iVfdtzaN5R4HwBHIhEKAAAAkFOlaoJDMw5idXomA6ORAAAAAIDCkwgFAAAAAArP0HgAAAAKq1UrztfeUi35IdKlRiPxPtJiLlLg3VSEAgAAAACFV5xLYwAAkJFmpZR4H42+4tUwlIeLU3kGAOSfRCgAAHCIVjn5xG5ERLNWSaWfIqnsbWYdAgB0reJdVgYAAAAAeBcVoQDQBZo9raxD6FrlSKeyLQvqwgAAYPRUhAIAAAAAhaciFACAzDR7itlXEho96VU3l4dVoQMAxSMRCgAAZKJZK9YAtfKwCSsAIM+K9ckDAAAAAOAIVIQCAEAXaNbSGxrfrKfTV2WfIfgAQHokQgEAAID9KpXEuyj11hLvIyKitW8olX6A7mFoPAAAAABQeCpCAQAAukSropZlzHqT76I01Ei+EwAmzFkUAAAAACg8iVAAAAAAoPAkQgEAAACAwpMIBQAAAAAKTyJ0DL75zW/GJz/5ybjsssvijDPOiL6+vpg2bVrMnTs37rjjjvjnf/7nrEMEAAAAAI7AqvFj8NWvfjVWrlwZ1Wo1TjvttJg3b178+Mc/jldffTVefvnleOCBB+LP//zP48Ybb8w6VACAjmkW5BNjo6eUdQgTUq5nHQEAQHdTEToGt956a/zd3/1d7Ny5MzZt2hTPPfdcvPLKK7Fhw4b4yEc+EsPDw3HbbbfFG2+8kXWoAAAAAMBBJELH4Fd+5Vfigx/8YEyZMuWQ+3/yJ38yHnrooZgxY0bs3bs3/uZv/iajCAEAAACAIynIQKfs9fX1xbnnnhvPP/987NmzJ+twAAAAYOxqPcn3MZx8FxERpb7exPto7RtKvA+gc3JVEdpoNOKFF16IBx54ID7xiU/E+973vqjValEqlaJUKsUHPvCBcbc9PDwcf/EXfxGLFy+OOXPmRF9fX5x22mlx+eWXx1e+8pV46623JhT7W2+9FevXr4+IiPnz50+oLQAAAACgs3JTEfrYY4/FzTffHIODgx1ve/369bFkyZJYu3btIfcPDAzEwMBAPPPMM3HPPffEgw8+GIsXLx5T29u2bYs1a9bEZz/72RgcHIybbropFixY0MHoAQAAAICJyk1F6Ntvv51IEvSNN96IRYsWtZOgpVIpFi5cGLfddlt8+MMfbs/3+eabb8a1114bq1atOm6bjz32WLtK9Sd+4idi8eLF8fbbb8f9998fX/va1zr+GAAAAACAiclNRegBs2fPjvnz57d/nnjiibj33nvH3d5NN90UmzdvjoiIOXPmxPLly+Oiiy5q//6tt96KG2+8MVauXBn1ej1uuOGGePXVV2PGjBlHbXPmzJlxxRVXRLPZjM2bN8cbb7wRGzZsiIceeigWLFgQc+fOHXe8AAAAAEDn5SYR+qEPfSg2btwYZ5111iH3P/vss+Nuc8WKFfHUU09FREStVovHH3885s2bd8g+s2bNiuXLl8eFF14Yr732WuzYsSO+/OUvxxe/+MWjtnvllVfGd7/73fbtLVu2xO///u/Hn/3Zn8X73//+eOGFF2LOnDnjjhsAAAAA6KzcDI0/9dRTD0uCTtR9993X3r711lsPS4IeMG3atLj77rvbt++///4YGRkZdT+nnXZaPPDAA/ELv/ALsXPnzvjCF74w/qABAAAAgI7LTSK003bv3h0rV65s3166dOkx97/++uujv78/IiJ27NgR3/nOd8bc54c//OGIiFizZs2YjwUAAAAAkpObofGd9vTTT8fQ0FBE7K/4nD9//jH37+vri8suuyy+/e1vR0TEqlWr4qqrrhpTnweqSBuNxjgiBgCAo2v2pNdXo6eUSj/l4XT6SUuzVtg6k65WHk6hk94U+oiIqNWS72M4jScMIBuFPVO/9NJL7e158+ZFtXr8nO8ll1xyxONH66/+6q8iIuK9733vmI8FAAAAAJJT2IrQl19+ub092oWLDp6jdP369Yf8bs2aNfHYY4/Fr/zKr8T5559/yO82bdoUv/d7vxff/e53o1KpxG/91m9NIHIAgHxpFeTSeauSdQQT04j0qiebtXT6ataLVRGaRuVhGlWn5eFm4n0AQBYKmwjdvn17e3v27NmjOubUU09tb+/YseOQ3+3evTu+8IUvxBe+8IWYOXNmnHXWWVGr1eLNN9+MDRs2RKvVimnTpsUDDzygIhQAAAAAcqawidDdu3e3t6dMmTKqYw7e7+DjIyIuuuii+KM/+qNYvXp1vPjii/Haa6/Fnj17Yvr06fH+978/fv7nfz4+/vGPxxlnnHHMPoaGhtpzl0ZE7Ny5c1SxAQC8W1oVjmnOTZmkbn8caRbmNivpVGqmNRdpkRSl6rRoUpmHNCJa1eT/8ZcihXlIU1KyfsfY7Ms6AN6tNVLPOoTCKWwidN++f3sH10Y5oXRv77/NcL13795DfnfSSSfFJz/5yfjkJz85obi+9KUvxec///kJtQEAAJCUVjmdBHWp2UqlHwA4oLCJ0L6+vvb28ChXvTu4UnO0VaRj9ZnPfCY+9alPtW/v3LkzzjzzzET6AgAAmOyKVOHa5VMdA2SusInQ/v7+9va7qzuP5uD9Dj6+k3p7ew+pPAUAAAAAklecS2PvMnPmzPb21q1bR3XMwMBAe/vkk0/ueEwAAAAAQDYKmwg9//zz29sbN24c1TGbNm1qb8+dO7fjMQEAAAAA2Sjs0PgLLrigvf3iiy/GyMhIVKvHfrjPP//8EY8HAIDJpNmTUj+NdBblKQ9blAcAKHBF6OWXX96ei3PPnj2xZs2aY+4/NDQU3/ve99q3r7rqqkTjAwAAAADSU9hEaH9/fyxatKh9e9myZcfc/9FHH41du3ZFxP75QRcsWJBkeAAAAABAigqbCI2IuOOOO9rby5Yti3Xr1h1xv8HBwbjrrrvat2+//fbjDqMHAAAAALpHoROhV199dVx55ZURsX/o+zXXXBMvvPDCIfts3749rr322njllVciYn816J133pl6rAAAAABAcnJV9rh48eLYvHnzIfcNDAy0t9esWRMXX3zxYcetWLEiTj/99CO2+dBDD8Wll14aW7ZsiQ0bNsTFF18cCxcujPPOOy+2bdsWTz75ZAwODkZERLVajW984xsxY8aMjj0mAAAAACB7uUqE/vCHP4yNGzce9fd79uyJH/zgB4fdPzw8fNRjzjjjjFi1alUsWbIk1q5dG61WK1avXh2rV68+ZL9TTjklHnzwwUPmFQUAAAAAiiFXidCkzJ07N5599tl45JFH4uGHH45169bF1q1bY8aMGXHuuefGddddF0uXLo1Zs2ZlHSoAAAAAkIBcJUI3bNiQWNu1Wi1uueWWuOWWWxLrAwAAAADIp0IvlgQAAAAAECERCgAAAABMArkaGg8AAEwezUopnY5q6XTD2JSPvuZtR5WarXQ6AiD3VIQCAAAAAIWnIhQAgEmh6ZPvqDUa6VRqlusq9QDyotTXm3gfrX1DifcBx6IiFAAAAAAoPIlQAAAAAKDwDBACAOCYmj1ZR9AZ5XrWEUxMmkP7y5X0+gIASItEKAAAAADkTKlakKvREdEayccVaUPjAQAAAIDCkwgFAAAAAApPIhQAAAAAKDxzhAIAcEytgiyck+SiT92+EBPQHVq15L/Cl0YaifcBkBWJUAAAIBNJJqcPVUqnm1ryXVTqreQ7AYCCkggFAAAOkVaCstFIKUEZaSUPk388jZ60nrPiKA8n30ezls6sc63e5Ev0W8PJ91FK46pBRMRw8uX6pd7kH0trKIU/YpgkzBEKAAAAABSeilAAACATac0/20hraHwKlafN1KpoGYs0qk4jIlqV5GuZ0piHNC3eLflT6utNvI/WvqHE+6B7Fec/HAAAHEN681EmI80FmZoF+5aQ1jC4NBKuhVqYK6XR0QBwgKHxAAAAAEDhSYQCAAAAAIUnEQoAAAAAFJ5EKAAAAABQeAWbBh0AAAAYr1ZvJesQOqZUS2GVvOHkuyj1WlmMAtiXbPOlViuicfz9JEIBAACA1KSWbK2lkEBMo4/hFLKtERF7E85UQQ4YGg8AAAAAFJ6KUAAAAJiARk8plX6ateQrKctpDPVuNJPvBOAIJEIBAACgCzRrxRjUmUayNSKiObU3nY4SVqqmM5VAKun84XriXaQ1p2prKKU/ZDpKIhQAYAJaPk0REUWrbSon/z01IiKaBXv/pJGiaqaw9kt60qmijAKtM9MqJ/+cpZFsLQ+PYkUTiqkgC1jRvYpxOQkAAAAA4BgkQgEAAACAwpMIBQAAAAAKTyIUAAAAACi8gk1PDgAAAMCY1VJYWWzYSkZkS0UoAAAAAFB4KkIBAAC6RKOnlHUIHdRKqZ/kn7NyI63HAsBEqAgFAAAAAApPIhQAAAAAKDyJUAAAAACg8CRCAQAAAIDCkwgFAAAAAApPIhQAAAAAKDyJUAAAAACg8CRCAQAAAIDCkwgFAAAAAAqvmnUAAABAvjR70umnXE+nn2aBvvUUqZKlEaWUemol3kO5kXgXAHRAkc6jAAAAAABHVKBrowAAAFBczVryVbTl4cS7iGatknwnEVFqNFPph9ErRS3rEDomrZr2xDXSKWlv7RtKpZ/jkQgFAAAAUtOspTM4tTxckEGwvVkH0DmlEfNIkC2J0JxoVlsRPcnPXUP2Ko3CXDcCAAAA6BoFuTwCAAAAAHB0KkJzolVtRauqInRyUBEKAAAAkDaJUAAAmKBWGut+1FPoAwCgwAyNBwAAAAAKT0UoAAAAUDjNWvLl+uVhq6BDN1ERCgAAAAAUnopQSFkqc4h1uZKLqgAAdJFmJZ0FURs9yfdTHi7OIr7NWjFqv8rDKXXUm3wXreHkvxCXopZ4H4WS1t9XTkiEArlTtGSxxC4AAABkrxiXRwAAAAAAjkFFaF6UQ1oaAAAAABIiEQoAAACkplVOZ07VNBRlHtKIFOcihQxJhOZEq6cZrZ5m1mGQgmYKE5yTL+Xwmh+PeVQBAABImkRoTpR6mlGSCJ0UWtXiXDFMSmlE4hAAAADoLInQnCiVWlEqt7IOgxS05EGPq1Ut1nuhkfPHk4fEs6pZktSMfL8HSU+3/69p9mQdQfcq19Ppp+nb1Zik9bG4kcp7P51zTbOR/GNp1rv7f2Xa0hhOXqjh97Xi/KMsRS3rELpKqa832fZbpYih4+9XnL9A6BKmQDi+0lBxTvQAAADdII2Ea6u3kngfjE1aCd1Sb7L9lEaZapEIzYlKTyPKPSbJmwyaQ/7xH1fR8qBy38fV7ClWxV5ZJQUAAEDuSITmRKXajEpVtmQyaPRKeB9P0d4JpXrRMrsAAADQfSRCAaDDkqhwVWUKAADHZ/h9PpUqCb8updG1LxGaE5VKKyqVotXBwfiUCjaPau4HfTezr1jNw4JNeVe06QPSlPQCOSWF/gCTXqOnOJ9lysPFeSxFkcaCTGlpVbL/7tExya79Uzil/mnJdtAYXYpTIhQgYblP7FqcCgAAgElAIhRgspMHBQAAYBKQCAVyp1Qu1hDgVtPwIiiylmmoJsTUAgD50qz57EpymrXifHAqzJQFKQ3xbw0n+9q3zBEKAEDepZpIrqfYF0CXalaKkwgtN4pVYAFMnERoTvT2jESlpzhXRji6QTMqTzp5r3BtTR3JOoRo9qQ7Pr+U8LyoFn8CAADIH4lQSFmlxxjAyaZRd5HjeFJfUKpuYlQAAIDJRiI0J2qVkahWJUsAAAA4skZP8qNOyvV8j2YCOqtVSadIpHlCsqNjmyOj+98lEZoTlXIzKuWUK6IAAADgIPWpySdbK6klW1OYrqiWfBdFUqkln3QrD8utcHQSoQBMOq2Eh+KXEl4REQAAoJskXXnaao2ufYnQnJhSrUe1as66yaBadXXqeEZGvBfobq2qIWXHYjEpAJjc0hjiv18an8lUnY5Fq5z889VMoeo0IqI8bP2PbiQRCgCdlsRnL9dQxq3ZIzHNfqUu/75SxIsIRfvXVq4n30fTN7gxc4l98mqkkaQsSrI1Jc1aCvPcDifeRURENGtGgeVJszy618M5AQAAAAAoPNcTIWWVStFqHzrP0HgAktDq8sKNlk/u49ZI6bVv9iTfRxpVp2kZ5XRuE6aKdvIqj6TRS1GqTmFycErIiWk99ehJbZ4UsjR9yr6sQ8i9HzemZh3CpNKod3lmYDwSXiwpiY+qpXpxLhC0ail/mHf9if+PP4X86fbpCt6tXE/+83y3J/QPlkbiOKJYyWPGJo1kexp/X+kM8U9HevPDJq/ULM7n8zSUh/PxSUwiNCeqpWZUS/n4owCAQkn6M6rTNykp4ny35QJ9uY+IaKZQtVW05ywN/k2TpFQqwZPvIiKKd3EKjkQiFFJWKfsodjxFmz7AUH8AAIB0FktKS3k4+cdSahbvImjWJEIBoAu0Ojicv0jD7AEAAEZLIhQAOqyUwBykrQ4mLzuZVB0PiVgAoCiKtBhXGp/QmpUUKkJryXcREdFMYV7o8nDiXaSmWUv2L6xZHl37BXrLJm9gYCCefPLJWLNmTaxZsya+//3vx+DgYMyZMyc2bNiQdXgAAAAAkDutcrKJ49G2LxE6Bo888kj8zu/8TiJtT6kMR82rAQAA0FGtStYRkJU0xsCksWp8kapO01hcKlJaVK7RU5z5TougWZII7bjp06fHokWL4n3ve1+8733vi02bNsXv/u7vdqTtadXhqFVNgjsZTKmmcKbscoM9I1mH0FGNRr6HATfqvh2QrqyH5ndaaSjf73EAAGA/idAxuO222+K2225r337kkUc61va0ylD0FmylbI6sv6dAk3wkZHe1N+sQOmqoku9/tZWeRtYhFM7IUL5fcwAAOiONCsc0qk5hsvBNDVI2vWdf1iHk3rbytKxDAAAAAAomV4nQRqMR69ati+eeey7WrFkTzz33XLzwwgtRr++//LFw4cJYvXr1uNoeHh6Or3/96/Hwww/HunXrYuvWrXHSSSfFOeecE9ddd1187GMfi1mzZnXw0QDjVbTpA/I+1D/vQ/e70chQ1hEAAADwbrlJhD722GNx8803x+DgYMfbXr9+fSxZsiTWrl17yP0DAwMxMDAQzzzzTNxzzz3x4IMPxuLFizvePwAAQCc0e4qzrkA5pQVNIElFmuCulMKDSWeBoXT+TzYb/oflSWOU55TcJELffvvtRJKgb7zxRixatCg2b94cERGlUikWLFgQ5513Xmzbti2efPLJ2Lt3b7z55ptx7bXXxre+9a246qqrOh4HHDCtqlTseIo2j2re5zwdjFrWITAKpYItMJSmVl3VMwAAkKNE6AGzZ8+O+fPnt3+eeOKJuPfee8fd3k033dROgs6ZMyeWL18eF110Ufv3b731Vtx4442xcuXKqNfrccMNN8Srr74aM2bMmOhDGZPe8kj0ll1NgIiIahqXIgEAAIBJJTeJ0A996EOxcePGOOussw65/9lnnx13mytWrIinnnoqIiJqtVo8/vjjMW/evEP2mTVrVixfvjwuvPDCeO2112LHjh3x5S9/Ob74xS+Ou18AAAAAIF9ykwg99dRTO97mfffd196+9dZbD0uCHjBt2rS4++6746Mf/WhERNx///1x9913R7Wam6cHIDGVigpcAAAAiq+wk2bt3r07Vq5c2b69dOnSY+5//fXXR39/f0RE7NixI77zne8kGh8AAAAAkJ7Cljw+/fTTMTS0f1GaadOmxfz584+5f19fX1x22WXx7W9/OyIiVq1aleqiSf2VoeirNFLrjyz1ZR1A7k2tFmuxpEo53xWXvT0jWYdQOEO9nX9OR4YKe8oGAICu06yksM6LdW1HrVnqslXjO+2ll15qb8+bN29Uw9wvueSSdiL04OOBdE2rDmUdQkdNqdazDuGYBoedXTutWu188nukWG8LAACA1BV2aPzLL7/c3p4zZ86ojjl4oab169d3PCYAAAAAIBuFrQjdvn17e3v27NmjOubgBZt27Nhx2O9ff/31eO9739u+PTw83L5/1qxZ7fuvuOKKWL58+ZjinVbZF1MqhX05OMiuhqHxAABF1KpkHUF3aVRaWYfQMSWznOVSOZIfuuy1H5s0/k82Unjd90vjf1haj6X7tRqTfGj87t2729tTpkwZ1TEH73fw8Qc0Go1DEqwHNJvNQ+5/5513jtrH0NBQe+7SiIidO3eOKjYAACiaZk9xEmFMbmkk3NIisTc2aST20lpxoJzCjF7NnuT7SGvocxoJ13LdebLTCpsI3bdvX3u7Vhvd/He9vb3t7b179x72+7PPPjtarYn9EX7pS1+Kz3/+8xNqAwAAAAAYm8ImQvv6/m348YEh7MdzcKXmaKtIx+ozn/lMfOpTn2rf3rlzZ5x55pmJ9AVAcZTKxbka3GoWp2qG7tKqJvc+Ko34uwaAPEij6jQioqJ6uisVNhHa39/f3j5SdeeRHLzfwcd3Um9v7yGVpwBAlyvs0pMHSWtMHgAAJKiwidCZM2e2t7du3TqqYwYGBtrbJ598csdjAsij3upI1iEUzmCMbkoWiqHVk12WsFSfDFlYAADojMJ+ej7//PPb2xs3bhzVMZs2bWpvz507t+MxAQAAAADZKGxF6AUXXNDefvHFF2NkZCSq1WM/3Oeff/6IxwNA1io9xZmEqFFPYXnVgxRndlUAYDJKY2X6iHTm1iwVabqdvuPvMnHmIB+tRnV0z1VhE6GXX3559Pb2xtDQUOzZsyfWrFkTP/MzP3PU/YeGhuJ73/te+/ZVV12VRphttdJI1Px9AwAAAEAiCpsI7e/vj0WLFsWKFSsiImLZsmXHTIQ++uijsWvXrojYPz/oggULUonzgOnlvTG1km6FDNk4rfZ21iGQsm21E7IO4Zj2jqS0rOIxNJqFnakFAAAooGYKGbWyNNGojbZyurCJ0IiIO+6445BE6G/+5m/Ge97znsP2GxwcjLvuuqt9+/bbbz/uMHoAOJpKpUhjfjov7aHxAAAAEQVeLCki4uqrr44rr7wyIvYPfb/mmmvihRdeOGSf7du3x7XXXhuvvPJKROyvBr3zzjtTjxUAAAAASE6uyh4XL14cmzdvPuS+gYGB9vaaNWvi4osvPuy4FStWxOmnn37ENh966KG49NJLY8uWLbFhw4a4+OKLY+HChXHeeefFtm3b4sknn4zBwcGIiKhWq/GNb3wjZsyY0bHHBDC1Opx1CMc0pVrPOoTUh+d341D8IlWZFmnhp4iIVjPDSb7r3fe3DAAAWclVIvSHP/xhbNy48ai/37NnT/zgBz847P7h4aMnGc4444xYtWpVLFmyJNauXRutVitWr14dq1evPmS/U045JR588MFYtGjRuOOfiBPKe2OayR8mhXdKU7MOASBT1Wq6Sd2k+9u3p5Zo+wAAQGfkKhGalLlz58azzz4bjzzySDz88MOxbt262Lp1a8yYMSPOPffcuO6662Lp0qUxa9asrEMFAAAAABKQq0Tohg0bEmu7VqvFLbfcErfccktifUxET6kRPRmOrCM9J1YGsw4h906o7Ms6BAAOluQI/OLM+gBAzjR7Won3UY7ifJFvpjBbVTn7Wbm6ShqvSVE0R/mZMleJUAAA6EatavJftksjxfmyDcDkJLE3NpV8LzfRlSRCARI2rTqUdQjH1N8z+c6uaS/OBAAAQPYkQgEAAAAgZ5qydqPWbIxuP08pkDsnV3dnHUJH7erpyzqEY9qy98SsQyhcVepgz0jH2xyqO2UDAORNGvOQpiWNKViKNDW4+U67k29VOXF6ZXf0V5JciYC8qLcqWYcAh6iWivRxZHSSTrzurvYm2n63G2zUsg4BAACYhCRCASa5qdViVWPmwe5a5xN9lXLnEtaNZrYX3oYq6X78aDRcaAQAACRCAYCU9SYwdcCxFLkCtdXT/RXdpSGJagAA0uGTJwAAAABQeCpCc6JWakVvqTiTLHN0PaVRLmUGQFcolTM8fxegIjTqrsuPVqtavM+KaSzMAQBwgEQoAACZSXN4f0nSFQBgUpMIBXJnenlv1iF01AmVfVmHcEyze3dmHULqdjeSXdU96VXpJ2rvSE+m/fdW050jNOnFmXqn1BNt/1hGRtJJ7DXqleQaT7OqVSIUSEizpzgV2+VQqT1ZtWSIxqSR4MejIion/JG5NcqPef7MASa53nK6SanJYHpPvpPfWUs7EZv04kxDPk5NSKJJ1ncpTpoCAIDx8MkdADpsWnWo420OjhR35fNul3Si9VgGG/4uAABgtIwPAgAAAAAKT0UoAECXqlTSmV8zrblIk5bmwkxJsNgTAMDESIRCyk4od37IbNHsaia7kE3a+nO+WFIe7Gr0ZR0CAAAABeeyMgAAAABQeCpCASa5yVmx2n0VqHuqnauUHmllex007VXj4YBSgkPjW4atj0ur2kqln9JIKZV+AIB8kwgFAFI1pVpPtb9GM9kE1dCIj1MAAHAszYRrIZqjvN7tkzsAAAAA5EzSycMikQgFyIlaaSTrEHKveMPzOz/0flq1cwutDY7UOtbWePT3DKfaX9JD8XurxX+PNxrJVdU26pXE2gYAgINJhAIAANlIaWpVc5ECHF+zJ/n/leXwf5JkjHYZBLO6AwAAAACFJxEKAAAAABSeofEAQKqqpVHOZN4hSa9Sn/QcpMeS1vykQ5XkPjJWehqJtf1uic5H2pPC33VdDQMAwERIhAIk7MTKYNYh5N47jalZhwAAAEDBuawMAAAAABSeRCgAAAAAUHiGxufECeVKnFCWl54MhlrDWYeQfwV7K9RbCc5Jx7gMt7rv9DfU7FzMe6q9HWurG4y0CvZP5SBpzU/a25PcXKSNRnqvT6JzhAIAkHvF/WYAAAAAAPD/6b6SGACAMUh6lfr+nuJX+g8O17IOAQAAJkwiFFLWW2plHULuTY9iJRV2hBXRge7WW01uaPxQJb2Po5WeRmJtjwz5WA0AkHc+sQEAcEyVcrJVtUVQKid/obPZU7zXoVQ3UxcAkB6JUACg0KZWk60yHxzJbth4EYblN6bsS62vHze6u0K/1SxlHULHpTVOJq2Ea6tajJE/pZHi/a0BQIREKACTUK2U3DDfiIj+SucTO2/V+zveJgAApKnZU4wLRmkphwtTo9UaZYZTIhQgYT2l5OakK4rp5b1Zh9BR7yRQddZbTjZ5CwAAUHQSoQAAZMb8owAApEUiFAAAgLaizHXKONUNxQWKSyIUAIBJoVJJrvp0ZMTq5wAAeScRCgAAXaBULmCVXk86UyOktjr9kIQ43a9Ii9mUVbcC7yIRCkDm0l5QKunFmZJYLAkAAICJkQgFgA47sTLY8TZPqOzrWFvTqkMda4tsDY7Usg4BAAC6hrEbAAAAAEDhqQiFlJ1QrmQdQv410x0mnbQTyqrv8mZXszfR9pMYet/fwYrQ/oq/ScZmpFWMa+eDPSOJtd1oFOM5SlujntLnopTmIo26vwMAyDNnagAAAACg8FSEAgBwTNVSctV0/T3DibX9bttjWmJtVyopVRwyLmlVnjbTqjxNWEllK0AuNHtaWYfQNVqN0T1XEqEAMMn0lpMbHpxHQ00fd4B0lAqSCDXEf3JrVYuTeCnIOzI15ShlHQKMW2uU1zx9MwBg0kl63tYk5iCtlTqXvOzkCvTdoS/rADiGNFe+761290WAIR/dcy+1OU8T1pra3e+Vd2ulkNhVRQvQHXyaAnKneAtKWZgmb4ZaCV/tTuC70ImVwY61Ndxy+u8sidZuUSmrDQIAmMx8EwIAAAqtWpUEH4uiVLa2pTFlgYpQgK7gvzUAAAAAUHgSoQAAAABA4UmEAgAAAACFJxEKAAAAABSexZIAYJKplUayDiFV/ZV9WYeQICvWj8WUaj2xthtN9QXjMdioZR0CADCJSIQCAHBMveViJM/7e4YTa3v3cG9ibQNAGpo9raxDgHFrjozu71ciNCemlWrRX1JJAIVUTu6LN+PUbCTa/PTo/Gs+vby3421OFu80pibafrErTtOgqhUAgHRIhAIkrL+U72F/u1sStQBko1JpZh1C1xkZUTwBAOMlEQoAAEBbpSfZkRNpa9QriffR7ClOUr80JNkOFJdEKAAAAExAqUCJ0KinkAgt0NMFdBeJUACACaiVirGQEAAAFJ1EKAAAAFA4rWryq6CXRkqJ9wF0jkQoAJPOCeWE5wpLYFX6s6tvd6ytna3BjrU1Hruavan2N728N9H2X6/PTLR9ukOlbJwnUAytFIb5m4cUyIpEKAB0WBKJ1qGGJAtMVLWU3PtoSrWeWNsHNJrpJQ6GRnxNyKtq1fkgj9JYkCk1acx3msY8pClJo+q0SFTQkjWfcAAAACgsyeOxSSOpK3UIZEUiFABgAk6sZDfVwHDLR7mxmFodTqztt4f7EmsboGjSGH6fFsP8obv49AwwyfWXalmHwCjsKnVunsvpkVwyaFRS/r6Q9JykSc9BeizbYnpmfQMAQLdx6QIAAAAAKDyJUAAAAACg8CRCAQAAAIDCM0coAEwyvaWM12q1VCwAAJABiVAAADLTX9mXWl/TqkOJtd3fk/wiZLuHk134CwCg6CRCc6I88/9G78yZWYdBwur1eqxYsSIWL14cPT09WYeTS0V7jvL+ePIQX9oxJN1fEu3X6/U47a3zO9JWHgy10kt8RUTiEwElvSr9sdRKI5n13Y36K8klQqulZmJtH1ApJ9/HAb1Vf1vjMeTr1aQ1MmLWOYBu4EwNAAAApKbUk86FnVZdgho4lP8KAAAAAEDhSYQCAAAAAIUnEQoAAAAAFJ45QgGAVPWWWqn2Nz0SXs07w8vKJ1YGU+nnncbUVPoBAIAkSYQCADAp9JaTWwl9ajXhhHtETKnWE+/jgL0jPan1BZCUVBZlKtKCTOmsYQWZKtA7FgAAAADgyCRCAQAAAIDCMzQeAAAmaFp1KOsQAAA4DolQAACYoP6KRCgAQN4ZGg8AAAAAFJ5EKAAAAABQeBKhAAAAAEDhmSN0DAYGBuLJJ5+MNWvWxJo1a+L73/9+DA4Oxpw5c2LDhg1ZhwcAAAAAHIVE6Bg88sgj8Tu/8ztZhwEAAAAAjJFE6BhMnz49Fi1aFO973/vife97X2zatCl+93d/N+uwAADIWG95JPE++nuGE+8jbY2mmboohkajOH/LjXol6xAAEiMROga33XZb3Hbbbe3bjzzySIbRAACT3fTy3qxD6ConVPZlHcKEVEvNrEMAJoFKTyPxPoqUbG1lHQAwJhKhAADQBaZW06sIHWmlU922d6QnlX7SMrVWvKpdSMJQvTipiMEU+mg1Syn0EtGqp/C/v5x8H6XhdJ4vutOE/vs0Go1Yt25dPPfcc7FmzZp47rnn4oUXXoh6vR4REQsXLozVq1ePq+3h4eH4+te/Hg8//HCsW7cutm7dGieddFKcc845cd1118XHPvaxmDVr1kTCBwBgEunv8orQadWhrEMAjmJb1gF0kCkrxmYwerMOARiDcSdCH3vssbj55ptjcLDz1z/Wr18fS5YsibVr1x5y/8DAQAwMDMQzzzwT99xzTzz44IOxePHijvcPAAAAABTLuBOhb7/9diJJ0DfeeCMWLVoUmzdvjoiIUqkUCxYsiPPOOy+2bdsWTz75ZOzduzfefPPNuPbaa+Nb3/pWXHXVVR2PAwAAAAAojglPzDF79uyYP39+++eJJ56Ie++9d9zt3XTTTe0k6Jw5c2L58uVx0UUXtX//1ltvxY033hgrV66Mer0eN9xwQ7z66qsxY8aMiT4UAAAAABLS6klh4b+UpncojZiLtBuNOxH6oQ99KDZu3BhnnXXWIfc/++yz4w5mxYoV8dRTT0VERK1Wi8cffzzmzZt3yD6zZs2K5cuXx4UXXhivvfZa7NixI7785S/HF7/4xcPa+9znPhef//znxxXLj370ozj77LPHdSwAAHRafyW9OULT6mtnvS+VfgAAIiaQCD311FM7GUdERNx3333t7VtvvfWwJOgB06ZNi7vvvjs++tGPRkTE/fffH3fffXdUq4c+nKlTp8bMmTPHFUulUhnXcQAAkITe8kjWIXRctZRCZVBEjLQs/gIAdGBofKfs3r07Vq5c2b69dOnSY+5//fXXx6//+q/H7t27Y8eOHfGd73znsLlCP/3pT8enP/3pROIFAAAmZmp1OJV+BkdqqfTD5DWlWk+ln70jPan0A1BUuUmEPv300zE0tH8IzrRp02L+/PnH3L+vry8uu+yy+Pa3vx0REatWrbJoEgBwmN5SK9H2p0c6iZwj2VXqTaWf6eW9qfSTtHdKUxNre7iVm4/VADAupTTm70xBsp/8DlJOYbRBMV6SVLSqo3vlc/OJ7aWXXmpvz5s377Bh7kdyySWXtBOhBx8PAOTXCeWCTT/TbGTW9QnldOZx3NVMJ+GatBMrg4m1/U4juSTrASdU9iXexwG7GubuBACKJzeT5bz88svt7Tlz5ozqmIMXalq/fn3HYwIAAAAAiiE3FaHbt29vb8+ePXtUxxy8YNOOHTs6HtO7vf766/He9763fXt4eLh9/6xZs9r3X3HFFbF8+fIjtjE0NNSeAiAiYufOnRERUa/Xo15PZ14ZsnPgNfZaH13RnqO8P548xJd2DEn3l0T79Xo9ClZDCQAAHE9uyhc7ICfD/HOTCN29e3d7e8qUKaM65uD9Dj4+KY1G45CE7QHNZvOQ+995552jtvGlL30pPv/5zx92/9///d/H1KnJD6kiHw5M6cDRFe05yvvjyUN8aceQdH+dbv9Dl3a0OaAL9ac4ND4t06rpTO9gsSQAICJHidB9+/7tg12tNroPKr29/zZf1d69yU/if/bZZ0erNbFpdz/zmc/Epz71qfbtnTt3xplnnhk/93M/FzNnzpxoiORcvV6Pb3/72/HBD34wenqs+HgkRXuO8v548hBf2jEk3V8S7dfr9YijX2MDAABgFHKTCO3r+7cJ2Q8MOT+eg4eYj7aKNGu9vb2HJHAP6OnpyWWShGR4vY+vaM9R3h9PHuJLO4ak++t0+zkZSQJdbXo5uQvnaSyWVET9lXQqQvdUi7HgV9Go1KUIKj3ZLZrIkTVSWpiz1eMT+pgMJpyCHOU0ArmZbaC/v7+9PdrqzoP3O/h4AAAAAICD5aYi9OBh4Vu3bh3VMQMDA+3tk08+ueMxAQAAyektj6TST1pzkTJ5vT3cd/ydOmBKNfnFJfeOJD9Cp7eazns/DdWqqsDJqlG3nOlYNBOuoG2NjK793FSEnn/++e3tjRs3juqYTZs2tbfnzp3b8ZgAAAAAgGLITUXoBRdc0N5+8cUXY2RkJKrVY4f3/PPPH/F4AIDJYHppdPOqT1huLp1PzK6meSIB6KxKRUUo5EJjdPP15uZj7eWXX95eRGjPnj2xZs2aY+4/NDQU3/ve99q3r7rqqkTjAwAAAAC6V24Sof39/bFo0aL27WXLlh1z/0cffTR27doVEfvnB12wYEGS4QEAAAAAXSw3idCIiDvuuKO9vWzZsli3bt0R9xscHIy77rqrffv2228/7jB6AAAAAGDyylX28Oqrr44rr7wynnrqqRgaGoprrrkmli9fHhdeeGF7n+3bt8eSJUvilVdeiYj91aB33nlnViEDAGPUX6plHUJnlVOap/NImqObC2miTiklt+L2UKuUWNuHyVUJAACQBPO2Tk6lntF9Lp5QInTx4sWxefPmQ+4bGBhob69ZsyYuvvjiw45bsWJFnH766Uds86GHHopLL700tmzZEhs2bIiLL744Fi5cGOedd15s27YtnnzyyRgcHNwffLUa3/jGN2LGjBkTeRgAAECB9VeSS+YfbHfDglwAkGcTSoT+8Ic/jI0bNx7193v27Ikf/OAHh90/PHz0yokzzjgjVq1aFUuWLIm1a9dGq9WK1atXx+rVqw/Z75RTTokHH3zwkHlFAQCA7nFCZV9KPfWl1A95tGdEghqA/XI1NP6AuXPnxrPPPhuPPPJIPPzww7Fu3brYunVrzJgxI84999y47rrrYunSpTFr1qysQwUAgFTUSiOp9dWfWoKyaJJPuA41c/kVbtLr78lwmpQutHekJ+sQOqa3J73/zeTLUD5TapNWozq6KREm9Kpt2LBhIocfU61Wi1tuuSVuueWWxPoAAAAOl1bSdbjlS+RY9ZaTf20kWwEoKlPGAwAAAACFJxEKAAAAABSeMQ8A0AW+9U9fjcWLF0dPz8Tm1KrX67FixYqOtMX/Z8u52fVdLsCcdM1Gal1Nj+SerxMrg4m1nYV3GlOzDgEAoOMkQgEAAGACqqXRLdLRDSz8NDaNpoG2MBqJLy5VaY1qN4lQAACg0Por+1LpZ1cj+VXjoQgkWyevvSPFGZHUW01h8boRabtOc+kCAAAAACg8qWUAgAnoPe217DrPcn7STklzntME5yOdWdmdWNtFVrS5SE9IqfI0eelUtvaWk6+mYuwGR2pZh9BVVLdOXmlUt6ZRdVoUjZ7RPVcSoQAAXep4SdiuWBwrzWRugknXE8pDibWdhXqrknUIZCitqQR2pzSVwFAz+a+9e0Z6E+8DgImTCAUAAIAJmFZN52KIhGv+FGmhrDSkUUG7u66qmaMzRygAAAAAUHgSoQAAAABA4RkaDwBAZlJdbCrB+Uinl4qySM5+u0rpDL+dXt6bSj+MzbaR6VmH0HX6K8WaJzhpFmSiCKZU64n3kcaCTGlJeuGnkcro2lcRCgAAAAAUnkQoAAAAAFB4hsYDAAAAqZlaTX7l8AhD8IHDSYQCADApHGk+0nq9HitWrIjFixdHT88E5uF6/fQJRJY/J5TTme9wVzOduUjTUpQ5T98pTU2ln/5KOnPrvlXvT6UfAPJPIhQAAAAonLQqT5OmshU6RyIUAAAmqLfUyjqEzirYw2Fy6y0nu1JxRMRQszhfradV06kIZ3LaWe/LOgQmueL8twYAgIycUK5kHUJHDbVSqqJKaenWog3BBwDGx6rxAAAAAEDhqQgFAIAJ6i8Va/62XaV0Fv2ZHipP8+jEymAq/bzTSGdRphNSWZQpneG+uxvF+BsDyIqKUAAAAACg8CRCAQAAAIDCMzQeAAAmqPe017IOISIi6vV6rFixIhYvXhw9PT3jbue0Led2MKqj29IwBD+P6q1iLf413Er+a29/KsPvyaOhZnHSKntGTL1A8RXnHQsAAHSVE8opJdyajVS6SS3hmrBdJckQAIqpINcsAQAAAACOTiIUAAAAACg8iVAAAAAAoPAkQgEAAACAwrNYEgAAAG0nlIdS6Wd7oz+VfgDgAIlQAACg0Iq2On3SpsdwOv2U96bSz7aYnko/AOSfRCgAAABATvVX0qnSTsPOel/WITDJSYQCAABQWLXSSNYhdMwJlX1Zh9ARuxqSYUA2LJYEAAAAABSeRCgAAAAAUHiGxgMAAJC6nlI6i0udWBlMvI93GlMT7yMior8gQ+PTYgg+8G4qQgEAAACAwlMRCgAAAEDiqqVm4n309wwn3gdjt3ekJ9H2W+XR/W2pCAUAAAAACk8iFAAAAAAoPEPjAQAASN0J5aFU+qm3Kqn0k4Y0FmUabkkTAMXlPxwAAABMwPTy3qxD6Jg0kq39lX2J95Ge5FemH2pK3UCneDcBAAAAjMMJKSR1h5r9ifdBPln4afRGqvVR7WeOUAAAAACg8CRCAQAAAIDCMzQeAAAAgEKolppZh8ARJD3Mv94zuqHxEqEAAABAREScWBlMvI80FmSKKM6iTLsayS/IlJY91d7E+xgcqSXeB2OXdIK6Ncr2DY0HAAAAAApPIhQAAAAAKDxD4wEAACisnlIj6xA6Znp5b9YhdJW0huAn7YTUhvgnPwR/du/OxPvYncLw+yLZM1KM52u4Mro5SFWEAgAAAACFpyIUAAAAACahadWhrEPoiJ6qVeMBAAAYo95SK5V+psfohjFOWIHGQe5qFmMIqyH+YzPcSid105/CEPwtwzMS7yMtuxvFeD9ONgU6JQAAAAAAHJlEKAAAAABQeIbGAwAAAIVTlCH475SmZh1Cx5xWezvxPoo0/D4Nk22Iv4pQAAAAAKDwVIQCAAAAwBj0lkeyDqGr5KXyVCIUAAAAIKdOrAxmHULHvNMozjB/xqa/MpRo+0OV+qj2kwgFAAAgdb2lVir9TI/hxPvY2aol3gcwOidU9mUdQpfpS6WXoWY+UpD5iAIAAACAwxRl0ae0DLekuvIp4YTrKKcq8NcBAAAAXeCEcrJDS9Oyq5mPuQKByUciFAAAOETvaa8l0m69Xo8VK1bE4sWLo6enJ2LLuYn0k5ly8kOw07Cr2cg6BABIRDnrAAAAAAAAkiYRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFZLAkAAKAD+ku1rEPoiP5K1hF01u5W8otY9TaLsZp7WqaX0llYbGerGO/JIqm3kv8H805pauJ9FEl/ZV8h+tlbGxnVfhKhAAAAADAJ1UqjSyDmXWOUj0MiFAAAAIDE9ZQaifdxYmUw8T7In57y6P62JEIBAACA1PSWWqn0Mz3SGYLPGKSwUk0aw+8jInY2p6TSD50lEQoAAGSi97TXUu2vXq/HihUrYvHixdHT09P1/SXRfifbTPv5Pqot5ybfR1nCLZeayVcfMjZpJKd3lXoT7yMiYnp5byr9MDqVUVaEWjUeAAAAACg8iVAAAAAAoPAkQgEAAACAwpMIBQAAAAAKTyIUAAAAACg8iVAAAAAAoPAkQgEAAACAwpMIBQAAAAAKr5p1AAAAAJCU3tNeS76TLecm3wdjVx7OOgLeZajRTLyPE8pDifcREbGr2ZtKP0VRb1WyDiEiVIQCAAAAAJOARCgAAAAAUHgSoQAAAABA4UmEAgAAAACFJxEKAAAAABSeVePH4Jvf/Gb87d/+bfzf//t/4/XXX4+33norKpVKnHnmmXHVVVfFb//2b8dP//RPZx0mAAAAQO70llqJ93FKKZ1V4xmbXc3eRNvvKTVGtZ9E6Bh89atfjZUrV0a1Wo3TTjst5s2bFz/+8Y/j1VdfjZdffjkeeOCB+PM///O48cYbsw4VAACAlPSe9lrWIeRCvV6PFStWxOLFi6OnpyfrcCK2nJt1BLxbeTjrCDpmqFWcx5KKhMekl8rNPIRRLLfeemv83d/9XezcuTM2bdoUzz33XLzyyiuxYcOG+MhHPhLDw8Nx2223xRtvvJF1qAAAAADAQSRCx+BXfuVX4oMf/GBMmTLlkPt/8id/Mh566KGYMWNG7N27N/7mb/4mowgBAAAAgCORCO2Qvr6+OPfc/WX3e/bsyTgaAAAAAOBgE0qENhqNeOGFF+KBBx6IT3ziE/G+970varValEqlKJVK8YEPfGDcbQ8PD8df/MVfxOLFi2POnDnR19cXp512Wlx++eXxla98Jd56662JhN5xb731Vqxfvz4iIubPn59xNAAAAADAwca9WNJjjz0WN998cwwODnYynoiIWL9+fSxZsiTWrl17yP0DAwMxMDAQzzzzTNxzzz3x4IMPxuLFizve/1hs27Yt1qxZE5/97GdjcHAwbrrppliwYEGmMQEAAAAAhxp3Rejbb7+dSBL0jTfeiEWLFrWToKVSKRYuXBi33XZbfPjDH27Pz/nmm2/GtddeG6tWrep4DMfz2GOPtatef+InfiIWL14cb7/9dtx///3xta99LfV4AAAAAIBjG3dF6AGzZ8+O+fPnt3+eeOKJuPfee8fd3k033RSbN2+OiIg5c+bE8uXL46KLLmr//q233oobb7wxVq5cGfV6PW644YZ49dVXY8aMGRN9KKM2c+bMuOKKK6LZbMbmzZvjjTfeiA0bNsRDDz0UCxYsiLlz56YWCwAAAABwfOOuCP3Qhz4UGzdujIGBgXj88cfjrrvuil/6pV+aUEJyxYoV8dRTT0VERK1Wi8cff/yQJGhExKxZs2L58uXthYl27NgRX/7yl4/Y3uc+97l25eZYfzZs2HDUOK+88sr47ne/G08//XRs2LAhXn/99Vi6dGn8wz/8Q7z//e+PjRs3jvs5AAAAAAA6b9wVoaeeemon44iIiPvuu6+9feutt8a8efOOuN+0adPi7rvvjo9+9KMREXH//ffH3XffHdXqoQ9n6tSpMXPmzHHFUqlURr3vaaedFg888EC88cYb8Xd/93fxhS98If7n//yf4+oXAAAAmLje017LOoTD1Ov1WLFiRSxevDh6enqyDmdCxvVYtpybbFAp2lXam3UIXWV6DCfafrnUHN1+iUYxBrt3746VK1e2by9duvSY+19//fXR398fEfurQr/zne8cts+nP/3peOutt8b1c+aZZ475MXz4wx+OiIg1a9aM+VgAAAAAIDkTniO0U55++ukYGhqKiP0Vn/Pnzz/m/n19fXHZZZfFt7/97YiIWLVqVVx11VWJx3ksIyMjERHRaDQyjQMAAAAgb9Ks0k28+vaN0zrfJonLTUXoSy+91N6eN2/eYcPcj+SSSy454vFZ+au/+quIiHjve9+bcSQAAAAAwMFykwh9+eWX29tz5swZ1TFnnXVWe3v9+vUdj+lga9asid///d8/JM4DNm3aFDfddFN897vfjUqlEr/1W7+VaCwAAAAAwNjkZmj89u3b29uzZ88e1TEHL9i0Y8eOjsd0sN27d8cXvvCF+MIXvhAzZ86Ms846K2q1Wrz55puxYcOGaLVaMW3atHjggQeOWRE6NDTUngIgImLnzp0Rsb9ku16vJ/oYyN6B19hrfXRFe47y/njyEF/aMSTdXxLtd7LNPLzmpMfrfXxFe47y/niyjs85J902s369SZ/X/PiK9Bzl/bHkPT6yUWq1Wq1ONvi5z30uPv/5z0dExMKFC2P16tWjOu7qq6+OFStWRETEnXfeGX/4h3943GP+9m//NhYvXhwREf39/bFr167xBT0KP/7xj+Mv//IvY/Xq1fHiiy/G1q1bY8+ePTF9+vT46Z/+6fj5n//5+PjHPx5nnHHGMds5+Pk52EMPPRRTp05NKnwAAAAAOuSi/9+vZx1CVxlqlRJtf/euZrzvPVvjnXfeienTpx91v9xUhO7bt6+9XavVRnVMb29ve3vv3r0dj+lgJ510Unzyk5+MT37ykxNq5zOf+Ux86lOfat/euXNnnHnmmfFzP/dzMXPmzImGSc7V6/X49re/HR/84AeTmay5AIr2HOX98eQhvrRjSLq/JNrvZJt5eM1Jj9f7+Ir2HOX98WQdn3NOum1m/XqTPq/58RXpOcr7Y0k6vn/d2vEmSUFuEqF9fX3t7eHh4VEdc/AQ8ylTpnQ8piT09vYeksA9oKenJ5f/OEiG1/v4ivYc5f3x5CG+tGNIur8k2u9km3l4zUmP1/v4ivYc5f3xZB2fc066bWb9epM+r/nxFek5yvtjyXt8pCs3iyX19/e3t0db3XnwfgcfDwAAAABwsNwkQg8eFr516+jqiwcGBtrbJ598csdjAgAAAACKITeJ0PPPP7+9vXHjxlEds2nTpvb23LlzOx4TAAAAAFAMuUmEXnDBBe3tF198MUZGRo57zPPPP3/E4wEAAAAADpabROjll1/eXkRoz549sWbNmmPuPzQ0FN/73vfat6+66qpE4wMAAAAAulduEqH9/f2xaNGi9u1ly5Ydc/9HH300du3aFRH75wddsGBBkuEBAAAAAF0sN4nQiIg77rijvb1s2bJYt27dEfcbHByMu+66q3379ttvj2q1mnh8AAAAAEB3ylUi9Oqrr44rr7wyIvYPfb/mmmvihRdeOGSf7du3x7XXXhuvvPJKROyvBr3zzjtTjxUAAAAA6B4TKqNcvHhxbN68+ZD7BgYG2ttr1qyJiy+++LDjVqxYEaeffvoR23zooYfi0ksvjS1btsSGDRvi4osvjoULF8Z5550X27ZtiyeffDIGBwf3B1+txje+8Y2YMWPGRB4GAAAAAFBwE0qE/vCHP4yNGzce9fd79uyJH/zgB4fdPzw8fNRjzjjjjFi1alUsWbIk1q5dG61WK1avXh2rV68+ZL9TTjklHnzwwUPmFQUAAAAAOJJcTqw5d+7cePbZZ+ORRx6Jhx9+ONatWxdbt26NGTNmxLnnnhvXXXddLF26NGbNmpV1qAAAAABAF5hQInTDhg0dCuNwtVotbrnllrjlllsS6wMAAAAAmBxytVgSAAAAAEASJEIBAAAAgMKTCAUAAAAACk8iFAAAAAAoPIlQAAAAAKDwJEIBAAAAgMKrZh0AAAAAAHSTE8qVrEPoLs1Gos0Pl1qj2k9FKAAAAABQeBKhAAAAAEDhSYQCAAAAAIVnjlAAAAAAIDGJz6laLo1ut2SjAAAAAADInkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFVsw4AAAAAALpJf6mWdQgcpFlqjmo/FaEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhScRCgAAAAAUnkQoAAAAAFB4EqEAAAAAQOFJhAIAAAAAhVfNOoDJrtVqRUTErl27oqenJ+NoSFq9Xo/BwcHYuXOn1/soivYc5f3x5CG+tGNIur8k2u9km3l4zUmP1/v4ivYc5f3xZB2fc066bWb9epM+r/nxFek5yvtjSTq+oV3NjrfJ+O3avf/1OJBnOxqJ0Ixt3749IiLOOeecjCMBAAAAgO61a9euOPHEE4/6e4nQjJ188skREbFp06ZjvlAUx/z58+O5557LOoxcK9pzlPfHk4f40o4h6f6SaL9Tbe7cuTPOPPPMeP3112P69OkdiIy8y8N7PO+K9hzl/fFkHZ9zTnptOudMTlm/x7tBkZ6jvD+WPMTnvJNOm61WK3bt2hWnn376MfeTCM1Yubx/mtYTTzzRh4NJolKpeK2Po2jPUd4fTx7iSzuGpPtLov1Otzl9+vTMX3fSkYf3eN4V7TnK++PJOj7nnPTbdM6ZXLJ+j3eDIj1HeX8seYjPeSe9NkdTYGixJEjZb/zGb2QdQu4V7TnK++PJQ3xpx5B0f0m0n4fXie7kb+f4ivYc5f3xZB2fc042bTJ5+Ps5viI9R3l/LHmIz3knmzaPptQ63iyiJGrnzp1x4oknxjvvvJP5VQoAis95B4C0OOcAkDcqQjPW29sb/+W//Jfo7e3NOhQAJgHnHQDS4pwDQN6oCAUAAAAACk9FKAAAAABQeBKhBfLMM8/E9ddfH7Nnz46+vr4455xz4o477oh//dd/zTo0AApkYGAgvva1r8Vv//Zvx8/+7M/GtGnTolQqxdlnn511aAAU0Isvvhh/8Ad/EL/wC78Qp512WtRqtTjxxBNj/vz5cffdd8ePf/zjrEMEoEsYGl8Qf/qnfxof//jHo9lsxqxZs2LOnDnxL//yL7Fz58446aST4u///u/joosuyjpMAArgv//3/x6/8zu/c9j9c+bMiQ0bNqQfEACF9eqrr8ZP/dRPtW+ffvrpcfrpp8eWLVvaBR+nnXZaPPHEEzFv3ryswgSgS6gILYAXX3wxfv3Xfz2azWbceeedsXnz5lizZk1s2bIlbr755vjxj38cH/nIR2JoaCjrUAEogOnTp8eiRYvizjvvjP/1v/5X/Lf/9t+yDgmAgmq1WnHKKafE5z73uXj11VfjX//1X+O5556LN954I7773e/GnDlzYsuWLXHttdf6vgPAcakILYD/8B/+Q/zVX/1VXHHFFfHd7373kN8NDQ3FBRdcED/60Y/ij//4j+PXf/3XM4oSgKJ65JFHYsmSJSpCAei4ffv2RaPRiGnTph3x9//4j/8YP/uzPxsREcuXL49f/uVfTjM8ALqMitAut2fPnvjmN78ZEXHEJGdvb2987GMfi4j9X1QBAAC6RV9f31GToBERV1xxRZx44okREfHSSy+lFRYAXUoidBQajUa88MIL8cADD8QnPvGJeN/73he1Wi1KpVKUSqX4wAc+MO62h4eH4y/+4i9i8eLFMWfOnOjr64vTTjstLr/88vjKV74Sb7311jGP//73vx/79u2LiIgFCxYccZ+FCxdGRMSzzz4bzWZz3LECkI48n3cAKJ5uPu+MjIxEvV6PiDhmwhQAIiKqWQeQd4899ljcfPPNMTg42PG2169fH0uWLIm1a9cecv/AwEAMDAzEM888E/fcc088+OCDsXjx4iO28c///M8REVGr1eLMM8884j7nnXdeROwfVrJx48Y455xzOvcgAOiovJ93ACiWbj/vPPbYY+3YDxSAAMDRqAg9jrfffjuRDwVvvPFGLFq0qP2hoFQqxcKFC+O2226LD3/4wzFlypSIiHjzzTfj2muvjVWrVh2xnR07dkRExEknnRSlUumI+5x88snt7R//+McdfBQAdFrezzsAFEs3n3fefvvt+N3f/d2IiPjwhz9s1XgAjktF6CjNnj075s+f3/554okn4t577x13ezfddFNs3rw5IiLmzJkTy5cvj4suuqj9+7feeituvPHGWLlyZdTr9bjhhhvi1VdfjRkzZhzSzt69eyNif0Xo0fT19bW3k/iQA0Dn5fW8A0Axddt5Z2RkJG688cbYtGlTnHLKKfE//sf/GHesAEweEqHH8aEPfSg2btwYZ5111iH3P/vss+Nuc8WKFfHUU09FxP4E5uOPP37Y1ctZs2bF8uXL48ILL4zXXnstduzYEV/+8pfji1/84iH7HbiSOjw8fNT+DswhGhExderUcccNQPLyft4BoFi68bzTbDbj1ltvjSeeeCJOOOGEePzxx+P0008fd7wATB6Gxh/HqaeeetiHgom677772tu33nrrUYdwTJs2Le6+++727fvvvz9GRkYO2eekk06KiP1D3lut1hHbOTB8/uD9AcinvJ93ACiWbjvvtFqt+NVf/dV46KGHYtq0afHNb34z3v/+93cmcAAKTyI0Zbt3746VK1e2by9duvSY+19//fXR398fEfsTmt/5zncO+f35558fEfsrQjdt2nTENl599dWI2D9Efs6cOeOOHYDu0+nzDgAcS5LnnVarFbfffnssW7Yspk6dGn/zN38TV155ZWcCB2BSkAhN2dNPPx1DQ0MRsf8K6Pz584+5f19fX1x22WXt2++eRPy9731vew7Qo31o+Id/+IeIiLj00kujXPaSA0wmnT7vAMCxJHne+Y3f+I340z/905gyZUr8n//zf+IDH/hAR2IGYPKQFUvZSy+91N6eN29eVKvHn6b1kksuOeLxEfs/XCxevDgi9g8lebehoaFYtmxZRET8x//4H8cTMgBdrNPnHQA4lqTOO//pP/2n+OM//uPo6+uL5cuXx6JFiyYeLACTjkRoyl5++eX29miHqR88Z8/69esP+/1dd90VlUol/vEf/zF+7/d+L+r1ekTsXyH+137t1+JHP/pRzJkzJ371V391gtED0G2SOO8AwNEkcd759Kc/HX/0R3/UToJ+8IMfnHigAExKVo1P2fbt29vbs2fPHtUxp556anv74IWPDrjooovivvvuizvuuCP+63/9r/HAAw/EnDlz4l/+5V9i586dMWPGjPjrv/7r6O3tnfgDAKCrJHHeef311+O9731v+/bw8HD7/lmzZrXvv+KKK2L58uVjjhmA7tXp884zzzwT99xzT0RETJ8+Pe6+++5DFlg62OLFi+M//+f/PNaQAZhEJEJTtnv37vb2lClTRnXMwfsdfPzBPv7xj8e8efPinnvuiX/8x3+MF198MU499dS46aab4rOf/WycccYZEwscgK6UxHmn0Wgc8kX3gGazecj977zzzlhCBaAAOn3eOTDfaETEm2++GW+++eZR2/mpn/qp0YYJwCQlEZqyffv2tbdrtdqojjm4knPv3r1H3e/yyy+Pv/7rvx5/cAAUThLnnbPPPjtardbEgwOgcDp93vnABz7gnANAx5gjNGUHVniP+LehhMdz8FXQ0V5VBYAI5x0A0uW8A0CeSYSmrL+/v719rOrOgx2838HHA8DxOO8AkCbnHQDyTCI0ZTNnzmxvb926dVTHDAwMtLdPPvnkjscEQHE57wCQJucdAPJMIjRl559/fnt748aNozpm06ZN7e25c+d2PCYAist5B4A0Oe8AkGcSoSm74IIL2tsvvvhijIyMHPeY559//ojHA8DxOO8AkCbnHQDyTCI0ZZdffnl7VcQ9e/bEmjVrjrn/0NBQfO9732vfvuqqqxKND4Bicd4BIE3OOwDkmURoyvr7+2PRokXt28uWLTvm/o8++mjs2rUrIvbPl7NgwYIkwwOgYJx3AEiT8w4AeSYRmoE77rijvb1s2bJYt27dEfcbHByMu+66q3379ttvj2q1mnh8ABSL8w4AaXLeASCvJEIzcPXVV8eVV14ZEfuHglxzzTXxwgsvHLLP9u3b49prr41XXnklIvZfHb3zzjtTjxWA7ue8A0CanHcAyKtSq9VqZR1E3i1evDg2b958yH0DAwOxdevWiIiYNm1a/NRP/dRhx61YsSJOP/30I7b5xhtvxKWXXhpbtmyJiIhSqRQLFy6M8847L7Zt2xZPPvlkDA4ORkREtVqNb33rW4cMMQGguJx3AEiT8w4Ak4VE6CicffbZsXHjxjEf96Mf/SjOPvvso/5+/fr1sWTJkli7du1R9znllFPiwQcfjKuvvnrM/QPQnZx3AEiT8w4Ak4UJWDI0d+7cePbZZ+ORRx6Jhx9+ONatWxdbt26NGTNmxLnnnhvXXXddLF26NGbNmpV1qAAUgPMOAGly3gEgb1SEAgAAAACFZ7EkAAAAAKDwJEIBAAAAgMKTCAUAAAAACk8iFAAAAAAoPIlQAAAAAKDwJEIBAAAAgMKTCAUAAAAACk8iFAAAAAAoPIlQAAAAAKDwJEIBAAAAgMKTCAUAAAAACk8iFAAAAAAoPIlQAAAAAKDwJEIBAAAAgMKTCAUAAAAACk8iFAAAAAAovP8/GNpwlLGKa6QAAAAASUVORK5CYII=", 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wwWjVqlXqtb/+9a8ljinogAMOiPvuuy8SiUSxfZo1axb9+vVLtdetWxfjx4/P+Bzbi/z8/Fi4cGG89tprcd5558Vll12W9v6pp54aZ555Zqnz7L777mU679133x0tWrRItZ955pkyjd91111jyJAhkZOTU2yfWrVqRf/+/dNee/vtt8t0noImTpwYRx99dEydOjX12s033xyPPPJIif/tqwg//elP40c/+lGJfU4++eQ46qijUu0PPvggVq1aVWTfGTNmxOuvv55q77777nH//feXOH+DBg1i6NChW/1aAYAdk2AAACAL/POf/0xrX3PNNdGgQYNSx3Xq1CnOOOOMVHvx4sVpN6e2B1dfffUW3/iqU6dO2g354lSpUiV69OiRan/77bexYMGCLTpncQrezF2/fn2hdeNLsscee8RZZ51Var+uXbumtevVqxd9+/Yt87hPPvmkyH65ubkxbNiwVPvUU0+NI488stT5I77fLPfyyy9PtUePHh2rV6/OaOyvf/3rEm84b9KzZ8+0dnHXsb247LLLIpFIpP1Uq1YtmjVrFj179oznnnsurf9JJ50UTz311FappUaNGmn/BiZMmFCm8T/72c8y+m9ORf2Nhg8fHl26dImFCxdGRES1atXi0UcfjRtvvHGL5iura6+9NqN+Ba9348aN8emnnxbZ7/nnn0/bF+IXv/hF1KpVq9T5DzrooLS/GwDAJoIBAIAsMG7cuLT2BRdckPHYCy+8sMS5Ktvpp5++xWOPPvroqF+/fkZ999lnn7T2okWLyny+ZDIZ3333XcybNy9mzJiR9pP8f5vjbvLFF19kPO+JJ55Y4rflN9l8E9Kjjz466tSpU+q4vfbaK61d3LW/8847kZeXl2qfe+65pc5dUMGNZjds2JDxzedMb3xWxN9we3TooYfG448/Hv/5z38y/jwXJy8vL5YuXRqzZs0q9Bkt+Fn56quvCm1gXJJM/0atWrVKO8+W/I0eeeSROPPMM1Pfvq9Tp078+9//jj59+pR5ri3Rrl27jDf8zfQzufnTLeecc07G9ZSlLwCQPapVdgEAAGx9H3zwQeq4RYsW0bp164zHbv6N74JzVbY2bdpEo0aNtnj8vvvum3Hfzb/tvGLFilLH5OfnxxtvvBHPPvtsTJw4Mb744otYv359RudbtmxZxrVtfnOxOJvfNN577723aFxx1/7OO++ktRs3bhwzZszI6BwR3/++CspkbP369WO33XbLaP4t+RvuCHJzc6Nly5YZhUObW7JkSTz77LMxfPjw+OSTT2L27NkZjdu4cWOsWLEidtlll4z6l/Xf2qab+mX9G914441x6623ptq77rprDB8+PDp27Fimecpja/x3ZdKkSanjRo0albo8V0EdOnTIuC8AkD0EAwAAO7m1a9fGypUrU+127dqVaXzr1q2jVq1asWbNmojYvr5l3bRp03KNz2Rpk002X6qm4Dfji/Luu+/Gz372s2KXBilNWW6IZnod1aql/8//LR1X3LXPmTMnrV2epzkiIpYuXVpqn635N6xsd999d9pTFxs3boz58+fHtGnT4tFHH02tvz99+vTo0aNHvPDCCxn/zjdu3Bh//vOf45Zbbkn770NZlCUY2NK/U1n+RrfccktMnz491W7Xrl28/vrrsccee2Q8R0XYGp/JJUuWpI4L7sWRibIEwQBA9hAMAADs5HJzc9PaW7LUSIMGDVLBQFm+yb611a1bt1zjC26sXJFef/31+OEPf1jmDYQLKssyLVt6HRV9/ZncyC+LTG5Yb62/4fagSZMmhb4Zvscee8QxxxwTl1xySTz77LNx4YUXxoYNG2LDhg1x0UUXxQcffFBq+JdMJuMnP/lJDBkypFz1bYvPaFkUDAUiIn73u99t81AgYutc6/Lly1PH9erVK9PY8i4vBQDsnHbe/xUNAACVYOnSpXHxxRenhQJt27aNG264IV577bX48ssvIzc3N9auXRvJZDL1s/lNzR1RRX8Df/N9F0h33nnnxZ133plqf/fddxltJj106NC0UCCRSET37t3j/vvvj3fffTdmz54d3333XWzYsCHtM3rTTTdtjcuoMCeffHLaTfkrr7wybTPsHVn16tVTx2X9d1aegBIA2Hl5YgAAYCe3+VIfW7KuesFvqzZs2LC8JRVSlm8eb+8efPDBtGU/zj///Hj88cfTbuwV5bvvvtvapW11m+/3MHny5DKtt07Z/frXv46nnnoqPvzww4iIGDt2bDzzzDPx4x//uNgxBdfgr1q1ajz33HPxwx/+sNRzbe+f0fPPPz8uvfTSuPTSSyM/Pz82bNiQCul69+5d2eWVS8OGDWP16tURUfantranp7wAgO2HJwYAAHZyNWvWTFty5+uvvy7T+Dlz5qSWEYoofl3/zdeh37BhQ8bn2Hy5ox3Z8OHDU8cNGjSIf/zjH6WGAhERCxYs2JplbRO77rprWnvx4sWVVEn2qFKlStx+++1pr914442FNnLe5Msvv4xvvvkm1b7ssssyCgUidozP6IUXXhjPPPNMau3+jRs3Rp8+fWLQoEGVXFn5tGnTJnU8bdq0tP8ml+bzzz/fGiUBADs4wQAAQBY47LDDUsfz5s0rtElsScaPH1/sXAVtvo51pjf78/LyyhxWbM8KXsuxxx4bderUyWjc5r/nHdGRRx6Z1p4wYUIlVVJ+iUSiskvI2MknnxxHHHFEqv3VV1/F008/XWTfzf+tnXzyyRmfZ0f5jJ5zzjnxwgsvRI0aNSLi+yWprrjiivi///u/Sq5syx1++OGp4/z8/HjnnXcyHjt27NitURIAsIMTDAAAZIGjjz46rf3MM89kPPapp55Kax911FFF9tv8SYIvvvgio/nHjh1bpm+/bu8KLruU6aafyWSy0O95R9S1a9e0G+r/+te/KrGa8tl0U3mT9evXV1IlmRk4cGBa+7bbbityia6Cn8+IzD+j48ePj2nTpm15gdvYaaedFi+//HLUqlUr9dqvfvWruOuuuyqxqi3XpUuXtPbgwYMzGpeXlxdPPvnk1igJANjBCQYAALLAhRdemNa+7777YuXKlaWO+/DDD+Pf//53qt24ceM45ZRTiux78MEHp7Vff/31jGr705/+lFG/HUXBPR2++uqrjMY88cQTGQcp27NmzZqlLUszceLEePbZZyuvoHJo0KBBWnt7X0bnjDPOiAMOOCDVnjJlSjz//POF+m2+50gmn9FkMhnXX399uWvc1rp37x6vvfZa2lJq/fv3T9tjYUdx6qmnRosWLVLtYcOGxbvvvlvquHvuuSdmzZq1NUsDAHZQggEAgCxwwAEHpH3jdO7cufHTn/60xE1/lyxZEhdffHFan5/+9KdRs2bNIvvvs88+0bx581T72WefjSlTppRY1x133BGjRo3K9DJ2CAceeGDq+IMPPoi33367xP7vvfde/OIXv9jaZW0zN954Y1Sp8v//34w+ffqU+jvY3Pz582PEiBEVXVqZ7LHHHmn7ZowePboSqyldIpGIAQMGpL122223RTKZTHut4Ocz4vvNsteuXVvi3Nddd128+eabFVPoNnbCCSfEf/7zn7QnI2688cb4/e9/X4lVlV21atXit7/9baqdTCbjhz/8YXz88cfFjhk6dGjccMMN26A6AGBHJBgAAMgS999/f9pN/aeffjpOO+20IpcHGTt2bBxzzDFpN/b32GOPEm+mValSJXr37p1qr1+/Pk455ZQi15mfN29e/OQnP4nrrrsuIgp/i3lHdu6556a1zznnnHj55ZcL9VuzZk3cd9990a1bt1ixYkU0adJkW5W4VR1yyCHxxz/+MdVeuXJldOvWLX75y1+mbXq7udzc3PjXv/4VP/7xj6Nt27YxdOjQbVFusWrUqJG2bv+YMWOib9++8eabb8bUqVNjxowZqZ/t5WmC888/P37wgx+k2p988km88soraX1at26dtl79lClT4rTTTouZM2cWmm/atGlx3nnnxZ133hkRscN+Ro8++uh48803o2HDhqnXbr/99rjmmmsqsaqy+9WvfhWdOnVKtRcuXBiHH354XHHFFfH666/HlClT4pNPPolhw4bFKaecEr169Yr8/Pw477zzKrFqAGB7Va30LgAA7Az222+/eOCBB6Jv376pbxG/9tprsddee0WHDh1ijz32iLy8vPjss88KbVBav379GDZsWNqSHEW59tprY/DgwfHtt99GRMTMmTPjyCOPjIMOOij22WefSCaTMX369Pjwww9TTyL85je/iffff7/M3yrfXvXp0yfuu+++mDp1akR8/+TFmWeeGbvvvnt06NAhatasGQsWLIgJEybE6tWrIyKiVq1a8dBDD+00N/AGDhwYM2bMiEceeSQivt8s9W9/+1v87W9/ix/84Aexzz77RMOGDSMvLy9yc3NTN9q3N7/4xS/SNnl99NFH49FHHy3U74QTTogxY8Zsw8qKVrVq1bj22mujX79+qdf++Mc/xhlnnJHW77bbbovu3bun/jvw5ptvxp577hkdO3aMPfbYI9atWxfffPNNfPLJJ6kxRx11VHTp0iVuv/32bXMxFaxjx44xevToOOmkk2LRokUR8f2SauvWrYv7779/h9hsumrVqvHiiy9G586dU/+NzsvLi0GDBsWgQYOKHLPnnnvG3//+97QlvXaEawUAtj7BAABAFunTp0/Url07+vTpk9rwN5lMxgcffBAffPBBkWNatmwZr7zyShx66KGlzt+wYcN47rnn4tRTT40VK1akXp80aVJMmjSpUP9+/frF3XffXWhjzR1ZjRo14uWXX46uXbvG/PnzU6/PnDmzyG9l161bN5599tnYZ599tmWZW92gQYPioIMOit/97ndpm0tPnz49pk+fXur4gt/uriw//vGPY8KECXHfffdVdikZu+yyy+Lmm29OPcUwceLEeP3116NHjx6pPieeeGLce++9cc0116TCgfz8/JgwYUKRT/gceeSR8corr8Tf/va3bXMRW8nBBx8cY8a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" ] @@ -2713,329 +364,42 @@ } ], "source": [ - "iohinspector.plot_eaf_singleobj(df)" + "from iohinspector import DataManager, plot_tournament_ranking\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"SO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1]).load(True, True)\n", + "ax, data = plot_tournament_ranking(\n", + " df,\n", + " file_name=\"example_plots/tournament_rankings.png\"\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "d5104b13", + "execution_count": 101, + "id": "411d4473", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/align.py:109: UserWarning: Sortedness of columns cannot be checked when 'by' groups provided\n", - " result_df = x_vals.join_asof(\n" + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + " warnings.warn(\"No results found. Start computations\")\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n" ] }, { "data": { - "text/html": [ - "
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01HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786765.310570e+06-0.3225440.6633830.249110
11RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275416.188412e+06-0.1925980.2011410.268371
22RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275414.848309e+06-1.1319300.4863600.279032
32HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786764.604357e+06-0.2060250.6570470.268522
43RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275413.281761e+06-0.698483-0.0667250.288152
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79750RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275413.813746e+01-0.607788-0.3779450.494987
80864HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786763.565133e+00-0.282064-0.4206760.566046
81864RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275412.194865e+01-0.681759-0.3773160.501213
82995RandomSearch15.5NoneNoneNone1.52.08.08.01000.021.9275412.192754e+01-0.593897-0.3772140.501236
83995HillClimber45.5NoneNoneNone1.52.08.08.01000.02.9786762.978676e+00-0.212480-0.4157080.572082
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"text/plain": [ - " evaluations algorithm_name data_id algorithm_info suite function_name \\\n", - "0 1 HillClimber 45.5 None None None \n", - "1 1 RandomSearch 15.5 None None None \n", - "2 2 RandomSearch 15.5 None None None \n", - "3 2 HillClimber 45.5 None None None \n", - "4 3 RandomSearch 15.5 None None None \n", - ".. ... ... ... ... ... ... \n", - "79 750 RandomSearch 15.5 None None None \n", - "80 864 HillClimber 45.5 None None None \n", - "81 864 RandomSearch 15.5 None None None \n", - "82 995 RandomSearch 15.5 None None None \n", - "83 995 HillClimber 45.5 None None None \n", - "\n", - " function_id dimension instance run_id evals best_y raw_y \\\n", - "0 1.5 2.0 8.0 8.0 1000.0 2.978676 5.310570e+06 \n", - "1 1.5 2.0 8.0 8.0 1000.0 21.927541 6.188412e+06 \n", - "2 1.5 2.0 8.0 8.0 1000.0 21.927541 4.848309e+06 \n", - "3 1.5 2.0 8.0 8.0 1000.0 2.978676 4.604357e+06 \n", - "4 1.5 2.0 8.0 8.0 1000.0 21.927541 3.281761e+06 \n", - ".. ... ... ... ... ... ... ... \n", - "79 1.5 2.0 8.0 8.0 1000.0 21.927541 3.813746e+01 \n", - "80 1.5 2.0 8.0 8.0 1000.0 2.978676 3.565133e+00 \n", - "81 1.5 2.0 8.0 8.0 1000.0 21.927541 2.194865e+01 \n", - "82 1.5 2.0 8.0 8.0 1000.0 21.927541 2.192754e+01 \n", - "83 1.5 2.0 8.0 8.0 1000.0 2.978676 2.978676e+00 \n", - "\n", - " x0 x1 eaf \n", - "0 -0.322544 0.663383 0.249110 \n", - "1 -0.192598 0.201141 0.268371 \n", - "2 -1.131930 0.486360 0.279032 \n", - "3 -0.206025 0.657047 0.268522 \n", - "4 -0.698483 -0.066725 0.288152 \n", - ".. ... ... ... \n", - "79 -0.607788 -0.377945 0.494987 \n", - "80 -0.282064 -0.420676 0.566046 \n", - "81 -0.681759 -0.377316 0.501213 \n", - "82 -0.593897 -0.377214 0.501236 \n", - "83 -0.212480 -0.415708 0.572082 \n", - "\n", - "[84 rows x 16 columns]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
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" ] }, "metadata": {}, @@ -3043,295 +407,63 @@ } ], "source": [ - "iohinspector.plot_ecdf(\n", + "from iohinspector import DataManager, plot_robustrank_over_time, IGDPlus, get_reference_set, add_normalized_objectives\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"MO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1]).load(True, True)\n", + "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", + "ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000)\n", + "\n", + "igdp_indicator = IGDPlus(reference_set = ref_set)\n", + "evals = [10,100,1000,2000]\n", + "\n", + "ax, comparison, benchmark = plot_robustrank_over_time(\n", " df,\n", - " free_vars=[\"algorithm_name\"],)" + " obj_vars=['obj1', 'obj2'],\n", + " evals=evals,\n", + " indicator=igdp_indicator,\n", + " file_name=\"example_plots/robustrank_over_time.png\"\n", + ")" ] }, { "cell_type": "code", "execution_count": null, - "id": "f80aee6b", + "id": "29f63dab", "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "shape: (368, 15)\n", - "┌─────────┬────────────┬───────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n", - "│ data_id ┆ algorithm_ ┆ algorithm ┆ suite ┆ … ┆ evaluatio ┆ raw_y ┆ x0 ┆ x1 │\n", - "│ --- ┆ name ┆ _info ┆ --- ┆ ┆ ns ┆ --- ┆ --- ┆ --- │\n", - "│ u64 ┆ --- ┆ --- ┆ str ┆ ┆ --- ┆ f64 ┆ f64 ┆ f64 │\n", - "│ ┆ str ┆ str ┆ ┆ ┆ u64 ┆ ┆ ┆ │\n", - "╞═════════╪════════════╪═══════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n", - "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 1 ┆ 1.5800e7 ┆ 3.262506 ┆ 4.431918 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 2 ┆ 7.4589e6 ┆ 3.215108 ┆ 3.085552 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 3 ┆ 6.4533e6 ┆ 2.499752 ┆ 2.841361 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 5 ┆ 4828.9966 ┆ 1.761925 ┆ 0.371379 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ 29 ┆ ┆ │\n", - "│ 31 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 26 ┆ 1866.3556 ┆ 2.710169 ┆ 0.407752 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … ┆ … │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 25 ┆ 1.521586 ┆ -5.0 ┆ -3.120021 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 27 ┆ 0.03135 ┆ -3.802689 ┆ -2.502291 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 32 ┆ 0.029183 ┆ -3.781128 ┆ -2.828955 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 42 ┆ 0.00491 ┆ -3.831461 ┆ -2.740264 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "│ 60 ┆ HillClimbe ┆ algorithm ┆ unknown_s ┆ … ┆ 81 ┆ 0.004026 ┆ -3.853244 ┆ -2.736186 │\n", - "│ ┆ r ┆ _info ┆ uite ┆ ┆ ┆ ┆ ┆ │\n", - "└─────────┴────────────┴───────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘\n", - "[[1.00000000e+00 1.57999232e+07 3.10000000e+01]\n", - " [2.00000000e+00 7.45889349e+06 3.10000000e+01]\n", - " [3.00000000e+00 6.45333527e+06 3.10000000e+01]\n", - " ...\n", - " [3.20000000e+01 2.91830493e-02 6.00000000e+01]\n", - " [4.20000000e+01 4.91001460e-03 6.00000000e+01]\n", - " [8.10000000e+01 4.02583880e-03 6.00000000e+01]]\n", - "[[1.00000000e+00 8.21240591e+06 1.00000000e+00]\n", - " [5.00000000e+00 3.56903493e+06 1.00000000e+00]\n", - " [9.00000000e+00 1.43888778e+05 1.00000000e+00]\n", - " [2.40000000e+01 6.94488920e+04 1.00000000e+00]\n", - " [1.02000000e+02 2.70867009e+04 1.00000000e+00]\n", - " [1.29000000e+02 4.72738896e+03 1.00000000e+00]\n", - " [2.08000000e+02 2.33395853e+02 1.00000000e+00]\n", - " [3.57000000e+02 4.71504960e+01 1.00000000e+00]\n", - " [1.00000000e+00 1.63970804e+06 2.00000000e+00]\n", - " [4.00000000e+00 5.89368690e+05 2.00000000e+00]\n", - " [6.00000000e+00 1.58700634e+04 2.00000000e+00]\n", - " [1.80000000e+01 1.02834741e+03 2.00000000e+00]\n", - 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" [1.00000000e+00 4.12717625e+01 2.80000000e+01]\n", - " [2.00000000e+00 1.67405712e+01 2.80000000e+01]\n", - " [3.00000000e+00 1.16493641e+01 2.80000000e+01]\n", - " [5.00000000e+00 3.83936321e+00 2.80000000e+01]\n", - " [7.00000000e+00 8.81103626e-01 2.80000000e+01]\n", - " [1.15000000e+02 4.53110364e-01 2.80000000e+01]\n", - " [2.06000000e+02 3.22372879e-01 2.80000000e+01]\n", - " [2.15000000e+02 2.65806254e-01 2.80000000e+01]\n", - " [3.69000000e+02 1.21159922e-01 2.80000000e+01]\n", - " [6.27000000e+02 1.05123632e-01 2.80000000e+01]\n", - " [8.47000000e+02 8.01431543e-02 2.80000000e+01]\n", - " [1.00000000e+00 3.05068949e+01 2.90000000e+01]\n", - " [2.00000000e+00 2.43567837e+01 2.90000000e+01]\n", - " [3.00000000e+00 5.15632683e+00 2.90000000e+01]\n", - " [5.00000000e+00 2.90131905e+00 2.90000000e+01]\n", - " [1.10000000e+01 2.21621164e+00 2.90000000e+01]\n", - " [3.70000000e+01 1.23513942e+00 2.90000000e+01]\n", - " [6.20000000e+01 9.42613283e-01 2.90000000e+01]\n", - " [8.10000000e+01 8.97071841e-01 2.90000000e+01]\n", - " [1.21000000e+02 5.64829541e-01 2.90000000e+01]\n", - " [1.84000000e+02 4.90358399e-02 2.90000000e+01]\n", - " [4.17000000e+02 8.00472220e-03 2.90000000e+01]\n", - " [1.00000000e+00 1.86531592e+00 3.00000000e+01]\n", - " [2.80000000e+01 1.27798785e+00 3.00000000e+01]\n", - " [3.00000000e+01 9.57680178e-01 3.00000000e+01]\n", - " [8.00000000e+01 5.88392907e-01 3.00000000e+01]\n", - " [1.64000000e+02 1.65869260e-01 3.00000000e+01]\n", - " [2.98000000e+02 9.58054420e-02 3.00000000e+01]\n", - " [8.12000000e+02 9.00465390e-03 3.00000000e+01]]\n" + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + " warnings.warn(\"No results found. Start computations\")\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + " warnings.warn(\"No results found. Start computations\")\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + " warnings.warn(\"No results found. Start computations\")\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", + " warnings.warn(\"No results found. Start computations\")\n", + "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", + " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n" ] }, { "data": { - "image/png": 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", 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"text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -3339,52 +471,72 @@ } ], "source": [ - "# Select HillClimber data\n", - "hc_data = df.filter(df[\"algorithm_name\"] == \"HillClimber\")\n", + "from iohinspector import DataManager, plot_robustrank_changes, IGDPlus, get_reference_set, add_normalized_objectives\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"MO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1]).load(True, True)\n", + "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", + "ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000)\n", "\n", - "# Select RandomSearch data\n", - "rs_data = df.filter(df[\"algorithm_name\"] == \"RandomSearch\")\n", - "print(hc_data)\n", - "iohinspector.eaf_diffs(\n", - " hc_data,\n", - " rs_data,\n", - " x_column=\"evaluations\",\n", - " y_column=\"raw_y\",\n", - " max_y=1\n", - ")\n" + "igdp_indicator = IGDPlus(reference_set = ref_set)\n", + "evals = [10,100,1000,2000]\n", + "\n", + "ax, comparison = plot_robustrank_changes(\n", + " df,\n", + " obj_vars=['obj1', 'obj2'],\n", + " evals=evals,\n", + " indicator=igdp_indicator,\n", + " file_name=\"example_plots/robustrank_changes.png\"\n", + ")" ] }, { "cell_type": "code", "execution_count": null, - "id": "85a93000", + "id": "0b6b6487", "metadata": {}, "outputs": [ { - "ename": "ZeroDivisionError", - "evalue": "float division by zero", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mZeroDivisionError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[2], line 5\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[38;5;28mmax\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m5\u001b[39m \n\u001b[1;32m 4\u001b[0m \u001b[38;5;28mlen\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m3\u001b[39m\n\u001b[0;32m----> 5\u001b[0m x \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43marange\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 6\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mmin\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 7\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mmin\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m2\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 8\u001b[0m \u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mmin\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m/\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 9\u001b[0m \u001b[43m \u001b[49m\u001b[43mdtype\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mfloat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 10\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 11\u001b[0m \u001b[38;5;28mprint\u001b[39m(x)\n", - "\u001b[0;31mZeroDivisionError\u001b[0m: float division by zero" - ] + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ - "import numpy as np\n", - "min = 5\n", - "max = 5 \n", - "len = 3\n", - "x = np.arange(\n", - " min,\n", - " max + (max - min) / (2 * (len - 1)),\n", - " (max - min) / (len - 1),\n", - " dtype=float,\n", - " )\n", - "print(x)" + "from iohinspector import DataManager, plot_heatmap_single_run\n", + "import os\n", + "\n", + "os.makedirs(\"example_plots\", exist_ok=True)\n", + "\n", + "manager = DataManager()\n", + "manager.add_folder(\"SO_Data\")\n", + "\n", + "df = manager.select(function_ids=[1], data_ids=[1], algorithms=[\"RandomSearch\"]).load(True, True)\n", + "\n", + "ax, data = plot_heatmap_single_run(\n", + " df,\n", + " vars = [\"x0\",\"x1\"],\n", + " var_mins=[-5,-5],\n", + " var_maxs=[5,5],\n", + " file_name=\"example_plots/heatmap_single_run.png\"\n", + ")" ] + }, + { + "cell_type": "markdown", + "id": "c562712e", + "metadata": {}, + "source": [] } ], "metadata": { diff --git 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z?;T1c^5oLlnb4XM>KXLH#mk*Y-(U(peAgpCQ`s)6NIr*@K$dEQQrT&siv)ss`s^7W zaxE&sFTfKUqNDUnqqAOFky`pk25AES%| L?QrIy(|`OIHYTzv literal 0 HcmV?d00001 From 8f53479d12a06e72a3d0d07d6260021eec04d506 Mon Sep 17 00:00:00 2001 From: rookj Date: Wed, 26 Nov 2025 11:35:59 +0100 Subject: [PATCH 13/17] Add ND filtering before computing bounds --- src/iohinspector/metrics/utils.py | 27 +++++++++++++++++++++------ 1 file changed, 21 insertions(+), 6 deletions(-) diff --git a/src/iohinspector/metrics/utils.py b/src/iohinspector/metrics/utils.py index 0c3af85..30182ad 100644 --- a/src/iohinspector/metrics/utils.py +++ b/src/iohinspector/metrics/utils.py @@ -3,6 +3,10 @@ import warnings from typing import Iterable, Optional, Union, Dict +from moocore import ( + filter_dominated, +) + def get_sequence( min: float, max: float, @@ -55,6 +59,7 @@ def normalize_objectives( bounds: Optional[Dict[str, tuple[Optional[float], Optional[float]]]] = None, log_scale: Union[bool, Dict[str, bool]] = False, maximize: Union[bool, Dict[str, bool]] = False, + only_nondominated: bool = False, prefix: str = "ert", keep_original: bool = True ) -> pl.DataFrame: @@ -66,6 +71,7 @@ def normalize_objectives( bounds (Optional[Dict[str, tuple[Optional[float], Optional[float]]]], optional): Optional manual bounds per column as (lower_bound, upper_bound). Defaults to None. log_scale (Union[bool, Dict[str, bool]], optional): Whether to apply log10 scaling. Can be a single bool or a dict per column. Defaults to False. maximize (Union[bool, Dict[str, bool]], optional): Whether to treat objective as maximization. Can be a single bool or dict per column. Defaults to False. + only_nondominated (bool, optional): Whether to only consider non-dominated objectives in computing bounds. Defaults to False. prefix (str, optional): Prefix for normalized column names. Defaults to "ert". keep_original (bool, optional): Whether to keep original objective column names. Defaults to True. @@ -74,7 +80,14 @@ def normalize_objectives( """ result = data.clone() n_objectives = len(obj_vars) - for col in obj_vars: + + ndpoints = None + if only_nondominated and len(obj_vars) > 1: + obj_vals = np.array(result[obj_vars]) + ndpoints = filter_dominated(obj_vals) + + + for i, col in enumerate(obj_vars): # Determine log scaling use_log = log_scale[col] if isinstance(log_scale, dict) else log_scale is_max = maximize[col] if isinstance(maximize, dict) else maximize @@ -84,9 +97,9 @@ def normalize_objectives( if bounds and col in bounds: lb, ub = bounds[col] if lb is None: - lb = result[col].min() + lb = result[col].min() if ndpoints is None else ndpoints[i].min() if ub is None: - ub = result[col].max() + ub = result[col].max() if ndpoints is None else ndpoints[i].max() # Log scale if needed if use_log: if lb <= 0: @@ -121,7 +134,8 @@ def add_normalized_objectives( data: pl.DataFrame, obj_vars: Iterable[str], max_obj: Optional[pl.DataFrame] = None, - min_obj: Optional[pl.DataFrame] = None + min_obj: Optional[pl.DataFrame] = None, + only_nondominated: bool = False, ) -> pl.DataFrame: """Add new normalized columns to provided dataframe based on the provided objective columns. @@ -130,7 +144,7 @@ def add_normalized_objectives( obj_vars (Iterable[str]): Which columns contain the objective values to normalize. max_obj (Optional[pl.DataFrame], optional): If provided, these values will be used as the maxima instead of the values found in `data`. Defaults to None. min_obj (Optional[pl.DataFrame], optional): If provided, these values will be used as the minima instead of the values found in `data`. Defaults to None. - + only_nondominated (bool, optional): Whether to only consider non-dominated points for the normalization bounds. Defaults to False.) Returns: pl.DataFrame: The original `data` DataFrame with a new column 'objI' added for each objective, for I=1...len(obj_vars). """ @@ -143,7 +157,8 @@ def add_normalized_objectives( max_obj[col][0] if max_obj is not None else None) for col in obj_vars }, - maximize=True, + maximize=True, + only_nondominated=only_nondominated, prefix="obj", keep_original=False ) From 019c589c1070586e5777cd88f91132c86be0df28 Mon Sep 17 00:00:00 2001 From: rookj Date: Thu, 27 Nov 2025 11:32:14 +0100 Subject: [PATCH 14/17] Fix ND max dimension --- src/iohinspector/metrics/utils.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/iohinspector/metrics/utils.py b/src/iohinspector/metrics/utils.py index 30182ad..0a114a1 100644 --- a/src/iohinspector/metrics/utils.py +++ b/src/iohinspector/metrics/utils.py @@ -97,9 +97,9 @@ def normalize_objectives( if bounds and col in bounds: lb, ub = bounds[col] if lb is None: - lb = result[col].min() if ndpoints is None else ndpoints[i].min() + lb = result[col].min() if ndpoints is None else ndpoints[:,i].min() if ub is None: - ub = result[col].max() if ndpoints is None else ndpoints[i].max() + ub = result[col].max() if ndpoints is None else ndpoints[:,i].max() # Log scale if needed if use_log: if lb <= 0: From 6bd072e989491ffeffd609b439ebeb700032af0d Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Wed, 3 Dec 2025 10:20:47 +0100 Subject: [PATCH 15/17] added aocc log eval --- aux/try.ipynb | 36 ++++++++++++++++---------------- src/iohinspector/metrics/aocc.py | 22 +++++++++++++++---- tests/test_metrics/test_aocc.py | 16 ++++++++++++++ 3 files changed, 52 insertions(+), 22 deletions(-) diff --git a/aux/try.ipynb b/aux/try.ipynb index 4a9015f..a8ddfca 100644 --- a/aux/try.ipynb +++ b/aux/try.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 89, + "execution_count": 103, "id": "680015a1", "metadata": {}, "outputs": [], @@ -13,7 +13,7 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 104, "id": "18096bb8", "metadata": {}, "outputs": [ @@ -56,7 +56,7 @@ }, { "cell_type": "code", - "execution_count": 91, + "execution_count": 105, "id": "2fad87f6", "metadata": {}, "outputs": [ @@ -70,7 +70,7 @@ }, { "data": { - "image/png": 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" ] @@ -97,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 92, + "execution_count": 106, "id": "a06cd442", "metadata": {}, "outputs": [ @@ -130,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 93, + "execution_count": 107, "id": "433832c8", "metadata": {}, "outputs": [ @@ -166,7 +166,7 @@ }, { "cell_type": "code", - "execution_count": 94, + "execution_count": 108, "id": "bcb34ed4", "metadata": {}, "outputs": [ @@ -207,7 +207,7 @@ }, { "cell_type": "code", - "execution_count": 95, + "execution_count": 109, "id": "b7c6fdf1", "metadata": {}, "outputs": [ @@ -240,7 +240,7 @@ }, { "cell_type": "code", - "execution_count": 96, + "execution_count": 110, "id": "acb246b8", "metadata": {}, "outputs": [ @@ -273,13 +273,13 @@ }, { "cell_type": "code", - "execution_count": 97, + "execution_count": 111, "id": "68d3bb56", "metadata": {}, "outputs": [ { "data": { - "image/png": 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WwcMPP5xWHdlKbzef99kVJUkS9913X2r97LPPTjuQqIlggDpp3759ajnddKviuIr7N4dj13fOqubdfr251Fqf33020NuZ620aj75unn39/PPPx5lnnhllZWUREXHKKafEnXfeWac5sp3ebp69XdGgQYNi6tSpcdRRR0VExMyZM+OKK67Y6fmygb7OTF+XlZXFxIkTY8uWLVFYWBh33HFHWnOSPr3d/F+zI7belHPbGWAREU8++WS95mvp9HXz+GwkIuLUU0+tcb78/PxK36yePn16WnVkK73dPF+zX3jhhfjwww9T6w31JQbBAHVS8dsGn376aVr7LFmyJLXcuXPnZnXs+s5Z1bzbfyOjudRan999NtDbmettGo++bn59PWPGjDjllFNSbwpHjBgRDz74YOTnu7pjXejt5tfbVWnTpk3ceuutqfV77rknVq5cWa85WzJ9nZm+vv322+P111+PiIirr7469ttvv7TmJH16e9d4zY6IGDVqVGr5gw8+SPtbsNlIXzePz0Yitt7TqDb7779/avmTTz5Jq45spbeb52t2xZsOH3DAAXHEEUfUaf/qCAaok4pvlOfPn5/WPttuqhgRMWDAgGZ17IpzfvbZZztcJ6y2OTt37hzdunWrtL179+7RsWPHOtW6cePGWLp0adq1NvXvPhvo7cz1No1HXzevvp41a1aceOKJsWbNmoiIGDx4cDz22GM7nIpK7fR28+rtmgwbNizatm0bEVsvTfHqq6/We86WSl9npq9nzpyZWn700UdjyJAh1T623eQyYusNLytuW7x4ca21ZCu9veu8Zm+73Mo2y5cvr/ecLZW+zlxfV3wuJycn2rVrV+u8HTp0SC1vey9O1fR283vN3rBhQzz00EOp9fHjx6e9b20EA9RJxZR11qxZsWXLllr3eeONN6rcvzkce7/99ovc3K3/DJIkiX/+85/1nnP75yv+sZHOnHl5edG/f/96z7lly5aYNWtWrbWyld7OXG/TePR18+nrOXPmxPHHHx8rVqyIiIiDDjoonnzyyUp/pJA+vd18ers2ubm5UVxcnFr3IVP19HXm+3rmzJnxyiuvVPtYtmxZauyyZcsqbdv+esT8i97OfG+na/ubuqbzgWu20teZ6+uBAwemlpMk2aFvq1IxDKj4voQd6e3m95r9yCOPpO7VlZeXF+eee27a+9ZGMECdDBs2LHUX7XXr1sWMGTNqHL9p06Z4+eWXU+sjR45sVsdu3bp1DBkyJLU+bdq0Wut4/vnna5wzIuLYY4/d6Tkr/pzVzfnSSy/Velrna6+9FuvXr4+IrT/n0KFDa60jm+ntzPU2jUdfN4++/uijj2LUqFGpU0z79+8fzzzzjEtr1YPebh69nY7NmzdXCgP0ffX09a7T19SN3t51ervih1vt2rWLoqKies/ZUunrzPX19sd69913a5139uzZqeVevXrVOj6b6e3m95p97733ppaPP/74Hc7uqpcE6mj06NFJRCQRkVx88cU1jv3973+fGtu5c+dk8+bNze7Yt9xyS2rcfvvtV+OcCxYsSPLy8lLjX3/99SrHvfrqq6kxeXl5ycKFC2uct3///qnxP/nJT6ocU1pamhQXF6fG/eEPf6hxzosuuig19pRTTqlxLFvp7cz0dk2GDx+e2v+6666r8/7o60z39ccff5zstddeqfF9+vRJFixYUOM+pEdvN7/X7Ko8/vjjqTkjIpk3b16DzNtS6evm3dfjx49PzTV+/Ph6zZVt9Hbz7u1tjj766NScX/jCFxpkzpZMX2eurw8//PDUuO985zs1zrl58+Zk9913T43/+c9/XuN49HZzes3+5JNPKtVT22eBdSUYoM4q/oFXWFiYvP3221WOW7duXbLPPvukxl511VXN8tiffvpp0q5du9TYO++8s9qxZ599dmrc0KFDa6z1yCOPTI0dN25cteP++7//OzWuQ4cOydKlS6sd+1//9V+psfvuu2+yfv36KsfNmjUrKSgoSI196qmnaqyVrfR25nq7OoKB+tPXmevrTz/9NNlvv/1S43fffffk//7v/2qsg/Tp7cz09rJly2o8XkXLly9PBgwYkJr38MMPT3vfbKWvm997kYoEAztPb2emt9esWVPj8Sr6yU9+kpqzMT58aon0deZes++9997U2KKiohq/eHPrrbemxrZu3TpZvHhxjfWit5vT+5Ef/ehHqX2Li4uTDRs2pL1vOgQD7JRjjjkm1Zh9+/ZN3nzzzUrbly1blhx//PGpMZ07d05WrlxZ5VwfffRRpTcg99xzT5Mde5trrrkmNb5NmzbJAw88UGl7aWlpcuWVV1aqc9q0aTXO+eyzz1Yaf+WVVyalpaWVxjzwwANJmzZtUmNuuOGGGudctmxZ0rFjx9T4448/foc/0N98882kb9++qTHHHntsjXNSmd7OTG9XRzDQMPR10/f1ihUrkkMOOSQ1tmvXrsk777xTYw3Und5u+t4+9dRTk9NOOy158sknq/1WVllZWTJlypRK34yKiOTZZ5+tsVa20tfN671IRYKB+tHbTd/b559/fuo1e/t5tlmyZEnyta99rdJxhwwZkpSXl9dYK1vp68y8ZpeVlSWHHXZYanz//v2Tt956q9KY8vLy5Fe/+lWlb1tfeeWVNc7Lv+jt5vF+5MADD0zte9FFF9Vp33QIBtgpCxcuTHr27JlqzpycnGTEiBHJxIkTkzFjxiRt27ZNbcvPz6/xD8G6vkA05LG3KS0tTUaOHFmpjoMOOigZP358cuaZZ1Y6Xl3+IX/ve9+rtN/uu++enHnmmcn48eOTgQMHVtp2/PHHp3XK1VNPPZXk5+en9mvbtm0yZsyYZOLEicmIESOSnJyc1LY99tgj+eSTT9Kqla30dmZ6+5NPPkkOOeSQHR4VU/0ePXrssP3kk09Oq95sp6+bvq+/8pWvVBo/YsSI5LLLLkvr4fTm9Ontpu/tf/u3f0uNbdeuXTJkyJDkrLPOSi6++OLk/PPPT04++eSke/fuleaMiOSnP/1pWrWirzP5Prs2goH60dtN39sVe3bba/bZZ5+dXHzxxcl5552XDBs2LGnVqlWlOfv165csWbIkrVrR15l8zf7www+THj16pPbLzc1NPve5zyUTJ05Mxo0bl/Tp02eH9+MN8d+CbKG3M/9+ZMaMGZX2f/HFF9PeN12CAXba7Nmzk0MPPXSHP/wqPrp165Y8/vjjNc5T1xeIhjx2RatWrUrOOOOMGuds1apV8oMf/CDtOcvLy5Mbb7xxhzdb2z/OOuusZPXq1WnP+9hjjyVdu3atcc7DDjssee+999Kek3/R27Vr6N7e/neV7qNPnz5p15zt9HXtGrKvK57tUtfH8OHD064ZvZ2Ohuzt2mrb/rH33nsnU6ZMSbtWttLXtWus99k1EQzUn96uXUP2dsWere2Rm5ubjBs3rtZv3bIjfV27xnrNnj17dqX7DVT3mDBhQrJx48a052UrvV27xnw/8o1vfCO1f//+/eu0b7oEA9TLpk2bksmTJycnnXRS0qtXr6SgoCDp3r17MmTIkOSWW25J67pZO/MC0VDHrsozzzyTnHPOOUm/fv2Stm3bJsXFxcnAgQOT//zP/0zefffdnZrz3XffTS6//PJk4MCBSXFxcdK2bdukX79+yTnnnJM888wzOzXnZ599lvzoRz9KhgwZknTv3j0pKChIevXqlZx00knJ5MmTqz1VlPTo7fQ0VG8LBpqGvk5PQ/S1YKBp6e30NERvl5WVJS+99FJy8803J1/+8peTAw88MCkuLk7y8vKS1q1bJz169EiOOuqo5NJLL02efPLJZMuWLTtVK/o6XY3xPrs6goGGobfT0xC9vXLlyuSJJ55IrrnmmuSEE05IDjzwwGS33XZLCgoKkrZt2yZ77LFHMmrUqOS6665zH6R60tfpaYzX7M2bNye///3vkzFjxiR9+/ZNWrdunRQVFSX7779/cumllyYzZszYqXnZSm+np6F7u7S0tNIXgm+66aadqqs2OUmSJAEAAAAAAGSF3EwXAAAAAAAANB3BAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAAAAAZBHBAAAAUKucnJzUY5s333wz/v3f/z0GDhwYnTt3jpycnPjSl760w76vv/563HzzzfHFL34x9t5772jfvn0UFBREjx49YtiwYfHd7343FixYUOPx//jHP6aOf9ZZZ1U7bt68eZVqPf3006sd+/HHH6fG9erVq/ZfQh38+7//e2ruiy++OO397rnnntR+gwYNatCaAABgm/xMFwAAAOx6rr/++rjpppuirKysxnGDBw+O1157rcptn332WXz22Wfx0ksvxY9//OO46aab4tvf/naVY0eMGJFafv7556s93t/+9rdK688//3wkSVIp0KhqbMX5G8JXv/rVuO222yJia6jxs5/9LNq2bVvrfnfddVdq+cILL2zQmgAAYBvBAAAAUCc//vGP44YbboiIiH79+sXgwYOjbdu2MW/evGjVqlWlsdvOBCgsLIwDDzww9tlnnyguLo4kSWLx4sXxyiuvxLJly2Lz5s1x5ZVXRkRUGQ7stttusd9++8WcOXNiyZIlMXv27Nh///13GDdt2rRK68uWLYu33347DjrooBrHNnQwMHDgwBg6dGi89NJLUVJSEg8//HCcd955Ne4zZ86cePHFFyMiok2bNjFu3LgGrQkAALYRDAAAAHXyne98J4qLi2PSpEk7XDpo06ZNlda//OUvxxe/+MU49thjo02bNjvMVVZWFvfdd198/etfj3Xr1sX3vve9+MpXvhJ77bXXDmNHjBgRc+bMiYit3/avKhjYdjZBt27dYunSpam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" ] @@ -309,13 +309,13 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": 112, "id": "a5fcfc56", "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -348,13 +348,13 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": 113, "id": "891e6be7", "metadata": {}, "outputs": [ { "data": { - "image/png": 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V1rWh3YMPPhgdO3ZMHfv9739fYZ+N7bPPPnHvvfdGIpEot03btm3j0ksvTe3n5+fHhAkT0j5HXVFUVBQLFy6MV155JU4//fS44IILSrx//PHHx8knn1zpODvvvHOVznvXXXdF+/btU/v/+Mc/qtR/xx13jCeeeCKys7PLbdOwYcO49tprSxwbM2ZMlc6zsUmTJkXv3r1j2rRpqWM33nhjPPzwwxX+21cTfvKTn8SPf/zjCtscc8wxccghh6T233///Vi1alWZbWfOnBmvvvpqan/nnXeOBx54oMLxmzVrFk8++eQWv1YAYNskGAAAyAB//etfS+xfddVV0axZs0r79erVK0466aTU/uLFi0vcnKoLrrzyys2+8dW4ceMSN+TLk5WVFccee2xq/9tvv40FCxZs1jnLs/HN3HXr1pWaN74iu+66a5xyyimVtjvqqKNK7Ddp0iQuvPDCKvebPHlyme3y8vJi+PDhqf3jjz8+Dj744ErHj1i/WO5FF12U2n/77bdj9erVafX9+c9/XuEN5w0GDBhQYr+866grLrjggkgkEiVe9erVi7Zt28aAAQPimWeeKdH+6KOPjr/97W9bpJYGDRqU+BuYOHFilfpffPHFaf2bU1O/o5EjR8aRRx4ZCxcujIiIevXqxaOPPhrDhg3brPGq6pe//GVa7Ta+3uLi4vjkk0/KbPfss8+WWBfiZz/7WTRs2LDS8ffdd98SvzcAgA0EAwAAGWDcuHEl9s8666y0+5599tkVjlXbTjzxxM3u27t372jatGlabbt161Zif9GiRVU+XzKZjBUrVsT8+fNj5syZJV7J/39x3A2++OKLtMft169fhd+W32DTRUh79+4djRs3rrTf7rvvXmK/vGt/5513oqCgILV/2mmnVTr2xjZeaLawsDDtm8/p3visid9hXdSjR4/4y1/+Eq+99lran+fyFBQUxNKlS2P27NmlPqMbf1amTp1aagHjiqT7O+rYsWOJ82zO7+jhhx+Ok08+OfXt+8aNG8e///3vGDx4cJXH2hx77LFH2gv+pvuZ3PTpllNPPTXteqrSFgDIHPVquwAAALa8999/P7Xdvn376NSpU9p9N/3G98Zj1bbOnTtHy5YtN7v/XnvtlXbbTb/tvHz58kr7FBUVxRtvvBEjRoyISZMmxRdffBHr1q1L63zfffdd2rVtenOxPJveNN5zzz03q1951/7OO++U2G/VqlXMnDkzrXNErP95bSydvk2bNo2ddtoprfE353e4LcjLy4sOHTqkFQ5tasmSJTFixIgYOXJkTJ48OebMmZNWv+Li4li+fHk0b948rfZV/VvbcFO/qr+jYcOGxc0335za33HHHWPkyJHRs2fPKo1THVvi35WPP/44td2yZctKp+fa2AEHHJB2WwAgcwgGAAC2c2vXro2VK1em9vfYY48q9e/UqVM0bNgw1qxZExF161vWbdq0qVb/dKY22WDTqWo2/mZ8WcaPHx8XX3xxuVODVKYqN0TTvY569Ur+5//m9ivv2ufOnVtivzpPc0RELF26tNI2W/J3WNvuuuuuEk9dFBcXxzfffBPTp0+PRx99NDX//owZM+LYY4+N5557Lu2feXFxcfzud7+Lm266qcS/D1VRlWBgc39PVfkd3XTTTTFjxozU/h577BGvvvpq7LrrrmmPURO2xGdyyZIlqe2N1+JIR1WCYAAgcwgGAAC2c3l5eSX2N2eqkWbNmqWCgap8k31Ly83NrVb/jRdWrkmvvvpq/PCHP6zyAsIbq8o0LZt7HTV9/encyK+KdG5Yb6nfYV3QunXrUt8M33XXXePQQw+N8847L0aMGBFnn312FBYWRmFhYZxzzjnx/vvvVxr+JZPJ+J//+Z944oknqlXf1viMVsXGoUBExDXXXLPVQ4GILXOty5YtS203adKkSn2rO70UALB92n7/KxoAAGrB0qVL49xzzy0RCnTp0iV+/etfxyuvvBJffvll5OXlxdq1ayOZTKZem97U3BbV9DfwN113gZJOP/30uOOOO1L7K1asSGsx6SeffLJEKJBIJKJ///7xwAMPxPjx42POnDmxYsWKKCwsLPEZveGGG7bEZdSYY445psRN+csuu6zEYtjbsvr166e2q/p3Vp2AEgDYfnliAABgO7fpVB+bM6/6xt9WbdGiRXVLKqUq3zyu6x588MES036ceeaZ8Ze//KXEjb2yrFixYkuXtsVtut7D559/XqX51qm6n//85/G3v/0tPvjgg4iIGDt2bPzjH/+IM844o9w+G8/Bv8MOO8QzzzwTP/zhDys9V13/jJ555plx/vnnx/nnnx9FRUVRWFiYCukGDRpU2+VVS4sWLWL16tURUfWnturSU14AQN3hiQEAgO1cTk5OiSl3vvrqqyr1nzt3bmoaoYjy5/XfdB76wsLCtM+x6XRH27KRI0emtps1axaPPPJIpaFARMSCBQu2ZFlbxY477lhif/HixbVUSebIysqK2267rcSxYcOGlVrIeYMvv/wyvv7669T+BRdckFYoELFtfEbPPvvs+Mc//pGau7+4uDgGDx4cDz30UC1XVj2dO3dObU+fPr3Ev8mV+eyzz7ZESQDANk4wAACQAb7//e+ntufPn19qkdiKTJgwodyxNrbpPNbp3uwvKCioclhRl218LT/4wQ+icePGafXb9Oe8LTr44INL7E+cOLGWKqm+RCJR2yWk7ZhjjomDDjootT916tT4+9//XmbbTf/WjjnmmLTPs618Rk899dR47rnnokGDBhGxfkqqSy65JP73f/+3livbfAceeGBqu6ioKN555520+44dO3ZLlAQAbOMEAwAAGaB3794l9v/xj3+k3fdvf/tbif1DDjmkzHabPknwxRdfpDX+2LFjq/Tt17pu42mX0l30M5lMlvo5b4uOOuqoEjfU//nPf9ZiNdWz4abyBuvWraulStIzdOjQEvu33nprmVN0bfz5jEj/MzphwoSYPn365he4lZ1wwgnxwgsvRMOGDVPH/t//+39x55131mJVm+/II48ssf/444+n1a+goCCefvrpLVESALCNEwwAAGSAs88+u8T+vffeGytXrqy03wcffBD//ve/U/utWrWK4447rsy2++23X4n9V199Na3afvvb36bVblux8ZoOU6dOTavPU089lXaQUpe1bdu2xLQ0kyZNihEjRtReQdXQrFmzEvt1fRqdk046KfbZZ5/U/pQpU+LZZ58t1W7TNUfS+Ywmk8n41a9+Ve0at7b+/fvHK6+8UmIqtWuvvbbEGgvbiuOPPz7at2+f2h8+fHiMHz++0n533313zJ49e0uWBgBsowQDAAAZYJ999inxjdN58+bFT37ykwoX/V2yZEmce+65Jdr85Cc/iZycnDLbd+vWLdq1a5faHzFiREyZMqXCum6//fZ4/fXX072MbUL37t1T2++//36MGTOmwvbvvvtu/OxnP9vSZW01w4YNi6ys//vfjMGDB1f6M9jUN998Ey+//HJNl1Ylu+66a4l1M95+++1arKZyiUQihgwZUuLYrbfeGslkssSxjT+fEesXy167dm2FY1933XXx5ptv1kyhW9kRRxwRr732WoknI4YNGxbXX399LVZVdfXq1Yurr746tZ9MJuOHP/xhfPTRR+X2efLJJ+PXv/71VqgOANgWCQYAADLEAw88UOKm/t///vc44YQTypweZOzYsXHooYeWuLG/6667VngzLSsrKwYNGpTaX7duXRx33HFlzjM/f/78+J//+Z+47rrrIqL0t5i3ZaeddlqJ/VNPPTVeeOGFUu3WrFkT9957b/Tt2zeWL18erVu33lolblH7779/3HLLLan9lStXRt++feOKK64osejtpvLy8uKf//xnnHHGGdGlS5d48sknt0a55WrQoEGJeftHjx4dF154Ybz55psxbdq0mDlzZupVV54mOPPMM2OXXXZJ7U+ePDlefPHFEm06depUYr76KVOmxAknnBCzZs0qNd706dPj9NNPjzvuuCMiYpv9jPbu3TvefPPNaNGiRerYbbfdFldddVUtVlV1/+///b/o1atXan/hwoVx4IEHxiWXXBKvvvpqTJkyJSZPnhzDhw+P4447LgYOHBhFRUVx+umn12LVAEBdVa/yJgAAbA/23nvv+MMf/hAXXnhh6lvEr7zySuy+++5xwAEHxK677hoFBQXx6aefllqgtGnTpjF8+PASU3KU5Ze//GU8/vjj8e2330ZExKxZs+Lggw+OfffdN7p16xbJZDJmzJgRH3zwQepJhF/84hfx3nvvVflb5XXV4MGD4957741p06ZFxPonL04++eTYeeed44ADDoicnJxYsGBBTJw4MVavXh0REQ0bNow//vGP280NvKFDh8bMmTPj4Ycfjoj1i6Xef//9cf/998cuu+wS3bp1ixYtWkRBQUHk5eWlbrTXNT/72c9KLPL66KOPxqOPPlqq3RFHHBGjR4/eipWVbYcddohf/vKXcemll6aO3XLLLXHSSSeVaHfrrbdG//79U/8OvPnmm7HbbrtFz549Y9ddd438/Pz4+uuvY/Lkyak+hxxySBx55JFx2223bZ2LqWE9e/aMt99+O44++uhYtGhRRKyfUi0/Pz8eeOCBbWKx6R122CH+9a9/RZ8+fVL/RhcUFMRDDz0UDz30UJl9dtttt/jzn/9cYkqvbeFaAYAtTzAAAJBBBg8eHI0aNYrBgwenFvxNJpPx/vvvx/vvv19mnw4dOsSLL74YPXr0qHT8Fi1axDPPPBPHH398LF++PHX8448/jo8//rhU+0svvTTuuuuuUgtrbssaNGgQL7zwQhx11FHxzTffpI7PmjWrzG9l5+bmxogRI6Jbt25bs8wt7qGHHop99903rrnmmhKLS8+YMSNmzJhRaf+Nv91dW84444yYOHFi3HvvvbVdStouuOCCuPHGG1NPMUyaNCleffXVOPbYY1Nt+vXrF/fcc09cddVVqXCgqKgoJk6cWOYTPgcffHC8+OKLcf/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" ] @@ -381,7 +381,7 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": 114, "id": "411d4473", "metadata": {}, "outputs": [ @@ -433,7 +433,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 115, "id": "29f63dab", "metadata": {}, "outputs": [ @@ -497,7 +497,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 116, "id": "0b6b6487", "metadata": {}, "outputs": [ diff --git a/src/iohinspector/metrics/aocc.py b/src/iohinspector/metrics/aocc.py index 92a6e1e..12c4e26 100644 --- a/src/iohinspector/metrics/aocc.py +++ b/src/iohinspector/metrics/aocc.py @@ -2,7 +2,7 @@ import pandas as pd from typing import Iterable, Callable from functools import partial - +import numpy as np def _aocc( group: pl.DataFrame, eval_max: int, @@ -18,13 +18,14 @@ def _aocc( Returns: pl.DataFrame: DataFrame with added 'aocc_contribution' column containing normalized area contributions. """ - group = group.cast({"evaluations": pl.Int64}).filter( + group = group.filter( pl.col("evaluations") <= eval_max ) + # Ensure consistent types for the new_row DataFrame new_row = pl.DataFrame( { - "evaluations": [0, eval_max], - fval_var: [group[fval_var].min(), group[fval_var].max()], + "evaluations": [0.0, float(eval_max)], + fval_var: [float(group[fval_var].min()), float(group[fval_var].max())], } ) group = ( @@ -51,6 +52,7 @@ def get_aocc( eval_max: int, fval_var: str = "eaf", free_vars: Iterable[str] = ["function_name", "algorithm_name"], + scale_eval_log: bool = False, return_as_pandas: bool = True, ) -> pl.DataFrame | pd.DataFrame: """Calculate Area Over Convergence Curve (AOCC) metric for algorithm performance evaluation. @@ -60,11 +62,23 @@ def get_aocc( eval_max (int): Maximum value of evaluations to use for AOCC calculation. fval_var (str, optional): Which data column specifies the performance value. Defaults to "eaf". free_vars (Iterable[str], optional): Which columns to NOT aggregate over. Defaults to ["function_name", "algorithm_name"]. + scale_eval_log (bool, optional): Whether to use logarithmic scaling for evaluations. Defaults to False. return_as_pandas (bool, optional): Whether to return results as pandas DataFrame. Defaults to True. Returns: pl.DataFrame or pd.DataFrame: A dataframe with the area under the EAF (=area over convergence curve). """ + # Ensure consistent data types for evaluations + data = data.with_columns( + pl.col("evaluations").cast(pl.Float64) + ) + + if scale_eval_log: + data = data.with_columns( + pl.col("evaluations").log10().alias("evaluations") + ) + eval_max = np.log10(eval_max) + # Group by without strict=False (invalid argument for polars) aocc_contribs = data.group_by(*["data_id"]).map_groups( partial(_aocc, eval_max=eval_max, fval_var=fval_var) ) diff --git a/tests/test_metrics/test_aocc.py b/tests/test_metrics/test_aocc.py index 2fd1afd..99243ae 100644 --- a/tests/test_metrics/test_aocc.py +++ b/tests/test_metrics/test_aocc.py @@ -79,5 +79,21 @@ def test_aocc_zero_budget(self): aocc_val = result["AOCC"][0] self.assertTrue(np.isnan(aocc_val) or aocc_val == 0) + + def test_aocc_log(self): + self.df = pl.DataFrame({ + "data_id": [1, 1, 1, 2, 2, 2], + "function_name": ["f1", "f1", "f1", "f1", "f1", "f1"], + "algorithm_name": ["alg1", "alg1", "alg1", "alg1", "alg1", "alg1"], + "evaluations": [1, 10, 100, 1, 10, 100], + "eaf": [10.0, 7.0, 4.0, 12.0, 9.0, 6.0], + }) + result = get_aocc(self.df, eval_max=100, scale_eval_log=True) + aocc_val = result["AOCC"][0] + self.assertTrue(aocc_val == 6.5) + + + + if __name__ == "__main__": unittest.main() \ No newline at end of file From 6af8fb058857cddab8b257050a582a9d9ac12eed Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Wed, 3 Dec 2025 10:22:52 +0100 Subject: [PATCH 16/17] Fix gitignore --- .gitignore | 6 +- aux/try.ipynb | 563 -------------------------------------------------- 2 files changed, 3 insertions(+), 566 deletions(-) delete mode 100644 aux/try.ipynb diff --git a/.gitignore b/.gitignore index de5d94e..f612e04 100644 --- a/.gitignore +++ b/.gitignore @@ -3,7 +3,7 @@ __pycache__/ *.py[cod] *$py.class -aux/ + # C extensions *.so @@ -162,5 +162,5 @@ cython_debug/ # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ -data -aux/* \ No newline at end of file +data/ +aux/ \ No newline at end of file diff --git a/aux/try.ipynb b/aux/try.ipynb deleted file mode 100644 index a8ddfca..0000000 --- a/aux/try.ipynb +++ /dev/null @@ -1,563 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 103, - "id": "680015a1", - "metadata": {}, - "outputs": [], - "source": [ - "import iohinspector\n", - "import os" - ] - }, - { - "cell_type": "code", - "execution_count": 104, - "id": "18096bb8", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/sklearn/manifold/_mds.py:677: FutureWarning: The default value of `n_init` will change from 4 to 1 in 1.9.\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_attractor_network\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"SO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1], algorithms=['RandomSearch']).load(True, True)\n", - "ax, nodes_df, edges_df = plot_attractor_network(\n", - " df,\n", - " coord_vars=[\"x0\", \"x1\"],\n", - " fval_var=\"raw_y\",\n", - " file_name=\"example_plots/attractor_network.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 105, - "id": "2fad87f6", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/iohinspector/align.py:109: UserWarning: Sortedness of columns cannot be checked when 'by' groups provided\n", - " result_df = x_vals.join_asof(\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_ecdf\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"SO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1]).load(True, True)\n", - "ax, data = plot_ecdf(\n", - " df,\n", - " file_name=\"example_plots/ecdf.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 106, - "id": "a06cd442", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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rRLbYVHs6gxQ4N9Grr74a1dXVO31/7dq18corr2z39bq6up3eM2DAgJg2bVqMGzcuXn755cjlcjF9+vSYPn16g+t69eoVEydObDBzBQAAAADaiqSsvps30xpyLd+/ENliU+3pDFLgnLGDDjooXnjhhbj33nvjnnvuidmzZ8d7770X3bt3jyFDhsTYsWNj/PjxUVVVlXWpAAAAAEAJ2pMZZJLL5XIp1EwrtGrVqujWrVuMiL+Jdkn7rMsBAAAAaLU25TbG9JgSK1eujK5du2ZdTtHYmk+dXHFW5vnUptzGmFb3335HjdDhDAAAAAAUtySJSMqyLiLj/UtD1r8lAAAAAABaCR3ONKq8W9coTyqyLoMW2rxyZdYlAAAAANBGCJwBAAAAgOJWltSP1chSzkiNpjBSAwAAAACAVOhwplFJ76pIyjtkXQYtVJ51AZACo2EAAADauKQIOpw9NLBJBM40amOvzpFrV5l1GbRQ+6wLKBK5miVZlwAAAADQ6hmpAQAAAABAKnQ4Qyu3sXeXrEsoCu10OAMAAEDJSsrKIkmy7Z1Ncnp3m8JPCQAAAACAVOhwplG1PSuiXfuKrMughSqX1mVdQlFI+vbKuoQWMXu6Xnm3blmX0GIeeAgAAEBbInCmUbV7l0d5RXnWZdBC63t2zLqEotAj6wJaqBgf+igEBwAAYI9Lkvoj2yIy3r80CJwBoIDS7M7WLQ0AAECxEzgDbUJtVamOhSm+hz5m0XWtq7peKY8WKWWCfgAAgKYTOAMUsWIMytsvzroCAAAA2pyysoikLNsachnvXyIEzgA0y8bee77rup0OZwAAACgJAmegTVjfszQffNlx2easSwAAAIDseWhgyRA4AwDsgtnZu2bGNQAAsC2BMwAALVboQF6gDQAApUXgDFDEinMUyJ5/kGHl0CEF36P94tUFWTdn/jQAAMDuS5KIsoxHWmwxUqMpBM40qrZ7RHmHrKugpSqXZ10BrU0WIfj6nh0LvkePAq3rgYcAAAC0JWVZFwAAAAAAQOugwxkAAAAAKGpJUhZJkm3vbNb7lwo/JQAAAAAAUqHDGQAioraqMA9D7FyQVQEAAKA4CZxp1MbuEZsrs64Cdo+HJ5KVpG+vrEsoCjkPTwQAAHZHWVJ/ZCrr/UuDkRoAAAAAAKRChzMAFNDG3l1SW6v94tWprQUAAFBSkqT+yLoGGqXDGQAAAACAVAicAQAAAABIhZEaAAAAAEBxM1KjZAicAYCCS/r2yrqEFsvVLMm6BAAAgJJhpAYAAAAAAKnQ4QwAJWJj7y67vUb7xatTqAQAAGAPKyurP7ItIuP9S4OfEgAAAAAAqdDhDAAFVFtVkdpalUvrdnuNNLqkW0JnNQAAQNsgcAYAAAAAiluS1B9Z10CjjNQAAAAAACAVOpxpVF3PTVHWcVPWZdBi/s+cdFUuz7oCAAAA2pwksu8w1uDcJJIoAKDgspodnYZ2NUuyLgEAAKBkCJwBICLW9ywvyLodl20uyLoAAABQjATOAAAAAEBx89DAkiFwBtqEuh5ZV0Bb1XFZ1hUAAADAnlOWdQEAAAAAALQOOpyhlaur2pR1CUWhYqn/d0fpq62qyLqEola5tC7rEgAAgEIpS+qPTGW9f2mQwABtQqkG74JyAAAAoJQYqQEAAAAAQCq0zgEAAAAAxS1J6o+sa6BROpwBAAAAAEiFDmcAAAAAoLglZfVH1jXQKD8lAAAAAABSocOZRlV0r43yvbKuAtqmDVGZdQk74H86muO9o8pTW6vP7zenthYAAAAUgtQAAAAAAChuZUn9kams9y8NRmoAAAAAAJAKHc40qk+31dGuU13WZdBCNSu6Zl0CAAAAAG2EwBkAAAAAKG5JUn9kXQONMlIDAAAAAIBUCJwBAAAAAEiFkRoAUCLW9yzPuoQW67hsc9YlUKLKu3VLfc3NK1emviYAAIVWBCM1Iuv9S4MOZwAAAAAAUqHDGYBmqavalHUJJaViqf+pLXVJ315Zl5CaXM2SrEsAAICW8dDAkuFfwQAAu7Cxd5c9ul/7xav36H4AAABpEjgDQImo7ZF1Bbuj8POnK5cWfAsAAAAaIXAGAAAAAIpbWVJ/ZClnpEZTCJxp1OAuy6Kic0XWZdBCNSu6Zl0CAAAAAG2EwBlaub7dV2VdAruhJusCdmDD8sqsSwAAAACKlMAZAAAAAChuSVJ/ZF0DjSrLugAAAAAAAFoHgTMAAAAAAKkwUgOgiBXjDO5inCudhlKYTV3XI+sKitvyAzsWZN2OyzYXZN2dab94j24HAAAlIZckkct4pEXW+5cKgTON+ljnRVHZ2R8VStucVVVZlwAUWG2BAvmOywqzLgAAQGskRQQAAAAAiltZZD8cOJfx/iVC4EyjPlY5Pzp1LM+6DGiTdGYDAAAApUTgDADQRiR9e6W+Zq5mSeprAgAApUvgDABAm1LerVvB1t68cmXB1gYAaNOSpP7IugYalfXkEwAAAAAAWgmBMwAAAAAAqTBSAwAAAAAobkZqlAwdzgAAAAAApEKHM40aPuil6Nq1a9Zl0FLzDsy6AnbDnFVVWZfQZnToUVuQdTdEZUHWLT2F/ytHxfKCbwEAAEAjBM4AAAAAQHEzUqNkCJwBAIrIxt5dsi6hWdrVLMm6BAAAoIgInAEAAACAopZLkshl3GGc9f6lwkMDAQAAAABIhQ5nAABaLOnbq6Dr54zsAACAkiJwBgAAAACKW1lkP6shl/H+JULgDACwC+t7lu/hHSsKtnLl0rqCrQ0AABAhcAagmfp2X5V1CSWlJsW1NiyvTHE1AAAASJ/AGQAKKM2APo3wWmjdfLU99ux+HZft2f0AAKAkJEn9kXUNNCrryScAAAAAALQSAmcAAAAAAFJhpAYAQBEp5EMKK5cWbGkAACisJLIfaWGiRpMInKGVG1axNusSikR11gW0yMyu+2RdQlGYs6oq6xIAAACAJhA4AwAAAABFLZckkcu4wznr/UuFwBkAgKKV9O2V+pq5miWprwkAANQTOAMABVdXtange1Qs99caAACArPmXGQDQKtT1KMy6FcsLsy4AANAMSUSUZVzDloz3LxFZ/5oAAAAAAGgldDgDALQRtVUVqa/ZfnHqSwIAACVM4AwAAAAAFLckqT+yroFGGakBAAAAAEAqBM4AAAAAAKTCSA0AAAAAoKjlkiRyGY+0yHr/UqHDGQAAAACAVOhwBihiQzu/m3UJbcacVVVZlwAAAMDOJB8cWddAo3Q4AwAAAACQCoEzAAAAAACpMFIDAAAAAChuSVJ/ZF0DjdLhDAAAAABAKgTOAAAAAACkwkiNVua5556LH/3oR/H000/HypUro1+/fnHqqafGVVddFfvss0/W5QFAwdRVbSrQyq3nr0sdl2VdAQAAtEyurP7IugYa13r+BUXccsst8dWvfjW2bNkSVVVV8bGPfSzefPPNuPHGG+Pee++Nxx9/PIYNG5Z1mexhPfsvyLqEojBs4YCsS2iRV9ZnXQEAAABA0wmcW4lZs2bFxRdfHFu2bIkrr7wyvve970X79u1j3bp1MWHChLjrrrvis5/9bLz22mvRoUOHrMsFADKwvmd56mt2SX1FAACglGkEbyW++93vxubNm+OEE06If/3Xf4327dtHRMRee+0Vt956awwePDjmzp0bEydOzLhSAAAAAGimJCmOg0bpcG4F1q5dGw899FBERFx88cXbvd+hQ4e48MIL4zvf+U7ce++9O7wGAKAlNvYubI9z+8WrC7o+AACQLoFzE23evDlmz54dv//972PGjBnx+9//PmbOnBkbN26MiIjhw4fH9OnTW7R2XV1d3HfffXHPPffE7Nmz47333osePXrE4MGDY+zYsXHhhRdGVVXVTu//4x//GLW1tRERcdJJJ+3wmuHDh0dExAsvvBBbtmyJsjLN7QDb2r/r0qxLaFTNiq5ZlwAAAJCJXFJ/ZF3D7trdHHB3PPfcc3HHHXfE888/H/PmzYvVq1dHx44do0+fPnH44YfHmDFj4swzz9ztcbwC5yaYPHlynHvuubFu3brU13799ddj3Lhx8fLLLzf4ek1NTdTU1MRzzz0XN9xwQ0ycODFGjx69wzX+/Oc/R0RERUVFDBw4cIfX7L///hERUVtbG9XV1TF48OD0vgmgYIZ1rM66BIrInO67/5eO6uWVKVQCAABAc6WRA7bEsmXL4qKLLoopU6Zs997q1atj9erV8dZbb8V///d/x9VXXx233XZbnHDCCS3eT+DcBCtWrChI2LxgwYIYNWpULFy4MCIikiSJk046Kfbff/9YsmRJTJ06NdavXx+LFy+OMWPGxCOPPBInn3zyduu8//77ERHRo0ePSHYyS2bvvffOny9fvlzgDACkoraqoqDrt19c0OUBAGCPSCsHbK7169fHJz7xiQYhd69eveLwww+PAQMGxJIlS2L27Nnx9ttvR0TEnDlz4lOf+lRMmzYtjjnmmBbtKXBuhj59+sRRRx2VPx599NH48Y9/3OL1zjnnnPwfskGDBsWUKVNi2LBh+feXLl0aZ599djz22GOxcePGOOuss2LOnDnRvXv3BuusX78+Iuo7nHemsvIvHW2FCM8BAAAAoGCK4aF9u7F/Wjlgc/3whz/Mh81JksT3vve9uPzyy6Njx475a3K5XNx3331x8cUXx8qVK2PdunXxla98JWbOnNmiPQ3ybYJTTjklqquro6amJh588MG4+uqr49RTT92tX/jDDz8cTz31VETUB8UPPvhggz9kERFVVVUxZcqUGDJkSETUdzJff/3126219Q9IXV3dTvfbOuM5ImKvvfZqcd0AAAAAQNOlmQM216RJk/Lnl112WVx11VUNwuaI+iD67LPPjltuuSX/tVmzZsWsWbNatKfAuQn69u0b++67b6pr/uxnP8ufX3DBBXHooYfu8LpOnTrFtddem3998803x6ZNmxpc06NHj4ioH5WRy+V2uM7WsRvbXg8AAAAAFFaaOWBzrFq1Kqqr//JsqHHjxu3y+jFjxjRoVN363LjmEjhnYM2aNfHYY4/lX48fP36X15955pnRuXPniKgPjp988skG7x944IERUd/hPH/+/B2uMWfOnIioH60xaNCgFtcOAAAAAHtcUiRHM6WdAzZ372011oTarl276Nq1a/71li1bWrSvGc4ZePbZZ2PDhg0RUf/JxVFHHbXL6ysrK+O4446L3/3udxERMW3atAZDww8//PCorKyM2traePLJJ+O8887bbo0nnngiIiKOPvroKCvzOQNQWoZ1rG78oiL1ynof8gEAALRVaeeAzdGrV698ZhgRMXv27DjggAN2ev2SJUti8eK/PLX7w2M/mkrymIHXXnstf37ooYdGu3aN5/5HHHHEDu+PqP/DOnr06Iiob7X/sA0bNuTntXzhC19oSckAAAAAQDOlnQM2R/v27ePUU0/Nv/7+978f69at2+n1V155Zb6redSoUbsMp3dF4JyBN954I3/e1PEW286Qfv3117d7/+qrr47y8vJ45pln4lvf+lZs3LgxIiLWrVsXX/7yl2Pu3LkxaNCguOiii3azegAAAADYs3JJUhRHcxUiB2yOf/mXf8mP6HjppZdi6NChcdttt8Vbb70VtbW18c4778RDDz0UJ554YkycODEiIg455JD8eUsYqZGBZcuW5c/79OnTpHv69u2bP9/2AYBbDRs2LH72s5/FpZdeGj/84Q/j1ltvjUGDBsWbb74Zq1atiu7du8dvfvOb6NChw+5/AwAAAABAowqRAzbHQQcdFM8880ycfvrpMX/+/JgzZ05ceOGFO7y2e/fucd5558UPfvCD6NKlS4v31OGcgW0Hdnfs2LFJ92x73YcHfm/11a9+NZ566qkYM2ZMJEkSs2bNiu7du8fFF18cs2bNisMPP3yXe2zYsCFWrVrV4AAAAACAzJUVyRGxXX62dUbzjhQqB2yOoUOHxp///Of46U9/Gp06ddrpdZ/+9Kdj3LhxuxU2R+hwzsTWQd0RERUVFU26Z9vO5PXr1+/0uuOPPz5+85vftKiu6667Lr773e+26F4AAAAAaAsGDhzY4PV3vvOduOaaa3Z4bSFzwKZaunRpXHHFFXHnnXfGxo0bo2/fvnH88cdHVVVVrFixIl544YWorq6O++67L+67776YMGFC/PznP4/y8vIW7SdwzkBlZWX+vK6urkn3bPtJSVM/DWmub3/723H55ZfnX69atWq7/wMCAEpXbY9CrNqyv4Q21e71VgAAQPreeeed6Nq1a/71rkbYZp0Dvvnmm3HyySfHggULokOHDvHTn/40vvrVrzZ4eGEul4t77703Lr744li1alX84he/iPLy8vj5z3/eoj0FzhnYOqg7oumfUmx73bb3p6lDhw5mPAO0ch161DZ+UYnasLyy8YsAAICS1NKH9qVdQ0RE165dGwTOu5JlDrhp06YYO3ZsLFiwICIibrrpph3Ob06SJMaNGxdVVVXxqU99KiIibrzxxrjwwgvj6KOPbva+ZjhnoGfPnvnz9957r0n31NTU5M/33nvv1GsCAAAAANKVZQ7461//Ov70pz9FRMSBBx4YF1xwwS6v/+QnPxmf+MQn8q8nTpzYon0Fzhk48MAD8+fV1dVNumf+/Pn584MOOij1mgAAAACAdGWZAz7yyCP585EjR0bShA7xk08+OX8+Y8aMFu1rpEYGDj744Pz5rFmzYtOmTQ3mpuzISy+9tMP7gabp2X9B1iW0yLCFA7Iuoc14pW7nT+oFAAAgY8kHR9Y1NFOWOeC7776bP9+203pXqqqq8ucrV65s0b46nDNw/PHH52clr127ttFPCzZs2BDPP/98/vW2nzQAAAAAAMUpyxxw2wcOvv/++026Z9myZfnz7t27t2hfgXMGOnfuHKNGjcq/njRp0i6vf+CBB2L16tURUT+35aSTTipkeQAAAABACrLMAffdd9/8+eOPP96ke6ZNm5Y//8hHPtKifQXOGbn00kvz55MmTYrZs2fv8Lp169bF1VdfnX89YcKERtvuAQAAAKA1ySXFcbREVjngtg8AfP311+OOO+7Y5fXTpk2L3/3ud/nXn/70p1u0r8A5I6eddlqceOKJEVHfKv+Zz3wmZs6c2eCaZcuWxZgxY+Ktt96KiPpPNa688so9XisAAAAA0DJp54Dz5s2LJEnyx866pk877bQ44IAD8q8nTJgQN910U2zevLnBdblcLu6///4YO3Zs/msDBw6Ms88+u9nfa4SHBjbZ6NGjY+HChQ2+VlNTkz+fMWNGHHbYYdvd9/DDD0f//v13uObdd98dRx99dCxatCjmzZsXhx12WAwfPjz233//WLJkSUydOjXWrVsXERHt2rWL+++/v8WzUwAAAACgZCVJ/ZF1DS2URQ7Yrl27uP322+Pkk0+OdevWRW1tbVxyySVx7bXXxvHHHx9VVVWxcuXKeP7552PevHn5+zp06BB33313fvZ0s/fdrarbkFdffTWqq6t3+v7atWvjlVde2e7rdXV1O71nwIABMW3atBg3bly8/PLLkcvlYvr06TF9+vQG1/Xq1SsmTpzYYN4LAAAAAFAassoBjznmmHj88cfjvPPOiz//+c8REbFo0aL49a9/vcPrBw8eHHfccUeccMIJLd5T4Jyxgw46KF544YW4995745577onZs2fHe++9F927d48hQ4bE2LFjY/z48VFVVZV1qQAAAABAC2WVAx599NExe/bs+O1vfxuTJ0+OGTNmxMKFC2PNmjXRqVOn6NOnT3z84x+PM844Iz73uc9F+/btd2u/JJfL5VKqnVZm1apV0a1bt1i5cmV07do163KgTVq2cEDWJbQZr9R1Ksy66welttZvFg7b7TVqVrTe/3++YXllQdatWLpnP5+vWL5Ht9ttlQWut8cb61Nfs93Mt1Nfc6vNK1cWbG0AoHXblNsY02OKHOZDtuZTx3/iu9GufWH+zt9UmzbWxrNTv+N31AgPDQQAAAAAIBUCZwAAAAAAUmGGM0AR69l/QdYlbMeYDwAAAPa45IMj6xpolA5nAAAAAABSIXAGAAAAACAVRmoAAOxCXdWmPbpfxXJ/PQMAgO2UJfVH1jXQKB3OAAAAAACkQgsNAETEsIq1BVq5Or2l+u/+EjO77rP7i7TAnFVVBd+jpkDrblheWaCVAQCApsol9UfWNdA4gTMAFFCaQfYr61NbCtq0pG+vwi2+cmXh1gYAgBJgpAYAAAAAAKnQ4QwAAAAAFLfkgyPrGmiUwBkAoIjU9ci6guJSW1WR+prtF6e+JAAA8AGBMwDN0rP/gqxLaLOG1R2YdQltU/dVe3S7RUtTeDokAABARgTOAAAAAEBRyyX1R9Y10DgPDQQAAAAAIBUCZwAAAAAAUmGkBgAAAABQ3JKk/si6BhqlwxkAAAAAgFTocAaANmRYx+pM9p25Zp9M9gUAAFoHDw0sHQJnAABarK5H1hUAAADFROAMACViWMXarEtosTuyLgAAAIA9QuAMAAAAABS35IMj6xpolIcGAgAAAACQCoEzAAAAAACpMFIDAAAAAChquaT+yLoGGqfDGQAAAACAVOhwBgAKbmjnd7MuoWRUV/Uu2NoVS/3VDwAAKCz/6gAAoGit71me+pqVvbukvuZW7Wq6FWztPWHzypVZlwAAsGNJUn9kXQONMlIDAAAAAIBU6HAGAAAAAIqahwaWDh3OAAAAAACkQoczAABtSm1VRcHW7lywlQEAoDQInAEAaFMK8SDCrQTOAAAFknxwZF0DjTJSAwAAAACAVAicAQAAAABIhZEaAAAAAEBRy5XVH1nXQOP8mAAAAAAASIXAGQAAAACAVBipAQAAAAAUt+SDI+saaJQOZwAAAAAAUqHDGQCgiHToUVuwtTdEZcHWLpTa5aX119Wkb6+Crp+rWVLQ9QEAYHeV1t/gAQAAAIA2J5fUH1nXQOOM1AAAAAAAIBU6nAEAAACA4pYk9UfWNdAoHc4AAAAAAKRC4AwAAAAAQCqM1AAAAAAAip6H9pUGgTMAAKRkY+8uBV2/fUFXj4iVKwu9AwAArZzAGQAASkShA+3kjYIuDwBAGyBwBgCAlNRWVWRdwm7p3K1bQdffrIMaAGip5IMj6xpolIcGAgAAAACQCh3OAECrMLTzu1mXkIo53asKtnZNwVYunLoenVNfs2J56ksCAAAfEDgDAAU3rGN11iWUjJld98m6hKJSXVVZgFUL91fg9T3LC7Z2RETHZZsLuj4AQLHKJfVH1jXQOCM1AAAAAABIhQ5nAAAAAKC4eWhgydDhDAAAAABAKnQ4AwBASmp7FHqHws6I7tK3V0HXj5UrC7s+AACZEzgDAAAAAEXNQwNLh5EaAAAAAACkQoczAABFq0OP2tTXzC3tnPqarcXG3l0Kun67mm4FXZ+GNhthAgBkQOAMAAAAABS35IMj6xpolMAZAACIiIjaqoqCrl/whxLSQGEfMVk4OrMBoLSZ4QwAAAAAQCp0OAMAFJGhnd/NuoRWb1GY4QwAUGpySf2RdQ00ToczAAAAAACp0OEMAAAAABQ3Dw0sGTqcAQAAAABIhQ5nAKDghlWszbqEElKddQGt3qLon3UJAADQagmcAQDaiGEd0w+zX1k/KPU1AQDgw3JJErkk25kWWe9fKgTOAADAHrGxd5eCrd1+8eqCrQ0AQNOZ4QwAAAAAQCp0OAMAABERsb5neYF3qCjg2oXrni5V7Qu4dq5mSQFXB4AdSD44sq6BRgmcAQAgJXU9Snv9iuWFXT+ikIF2YcLsyqV1BVkXAKC1EjgDAADsRG1V4bqyhdkAQGskcAYAAAAAilouqT+yroHGeWggAAAAAACp0OEMAAAAABQ3Dw0sGQJnACgRPfsvyLoE9oBhCwdkXUIzVWddQLNNqzok6xJarGKpv74DAFDcjNQAAAAAACAVWiQAAIA9orZH4dbuuKxwawMARcBIjZKhwxkAAAAAgFQInAEAAAAASIWRGgAARaTUHg5Z+Iccpv9QwkGDF6e+5p5SHb0LvEPp/vNg+UfKsy6h2Sp7dizo+h2rKgq2dpeCrRwRK1cWcnUASlQuqT+yroHGle7fKAEAAGh1yrt1K9jam4XZAFBwRmoAAAAAAJAKHc4AAAAAQHFLPjiyroFG6XAGAAAAACAVOpwBAGixQj/ksBAPJdy/69LU19xTanp0Lej6G6KyoOsXVun906ZyedYVFKekb6+CrV16j5asZ/Y0gIcGlhIdzgAAAAAApELgDAAAAABAKkrvvzsDAACANqS8W7eCrW1cB1AyPDSwZOhwBgAAAAAgFTqcAQAoWgV5KOG749Nfcw/p231VQdevKejqhVWKDzysXV7of44V7hF5XQq2MgBQ6gTOAAAA0EYVclxHoRgDAm1TLqk/sq6BxgmcAQBoU4Z2fjfrElpszqqqrEsAAIBdEjgDAADQLBt7F26oRvvFqwu2NgBQeAJnAADalGEdq7MuocVmdt0n6xJ2S82KrlmXAACUMiMtSkJZ1gUAAAAAANA66HAGAKBNGVaxNusSWuyVEp4/XWg1WRfQAnU9OmddQovVVlUUcPXCjetoV7OkYGsDUGBJZN/hnPX+JUKHMwAAAAAAqRA4AwAAAACQCiM1AAAAAICilkvqj6xroHECZwAA2pSe/RdkXUKLnR8DCrr+7QVdnQ+rrqos8A6F++fe+p7lBVy7Y8HW7hFDCrY222u/eHVB1i3cn76IzStXFnB1gLZB4AwAAERExLCO1VmX0KbU9Oha0PVzS0v3oYQAQOkSOAMAAAAAxS354Mi6BhrloYEAAAAAAKRC4AwAAAAAQCqM1AAAAAAAilrugyPrGmicDmcAAAAAAFKhwxkAACADfbuvKuj6i6JzQdcHgD3KQwNLhg7nVmTWrFnx/e9/Pz71qU9Fv379oqKiIrp16xZHHXVUXHvttbF8+fKsSwQAAAAAWjEdzq3EnDlzYujQofnX/fv3j2HDhsWiRYtixowZMWPGjLjpppvi0UcfjUMPPTTDSgEAaKuGdazOuoQ2pbqqd+EWf9s/JclO0rdXwdYuL9jKEZtXrizg6gDFw98SWolcLhe9evWKr33ta3HeeefFkCFD8u8988wzce6550Z1dXWMGTMmXn311ejQoUOG1QIAAKWstkfWFQDQ5hipUTIEzq3EgAEDYu7cudGpU6ft3jvhhBPirrvuir/+67+Ot99+Ox599NE444wzMqgSAAAgO7VVFVmX0CKVS+uyLgEAmswM51aisrJyh2HzVieccEJ069YtIiJee+21PVUWAAAAANCGtOrAefPmzTFz5sy49dZb45JLLokjjzwyKioqIkmSSJIkRowY0eK16+rq4o477ojRo0fHoEGDorKyMvr16xfHH398/OhHP4qlS5em942kYNOmTbFx48aIiF0G0wAAAABQbHJJcRy7qxgyxZdeeim+9a1vxZFHHhn9+vWLDh06RP/+/eOII46IL33pS3HHHXdETU1Ni9dvtSM1Jk+eHOeee26sW7cu9bVff/31GDduXLz88ssNvl5TUxM1NTXx3HPPxQ033BATJ06M0aNHp75/S0yePDn/sxg+fHjG1QAAAABA25J1prh48eK4/PLL46677truvUWLFsWiRYvij3/8Y0ycODG+9rWvxU9/+tMW7dNqA+cVK1YUJGxesGBBjBo1KhYuXBgREUmSxEknnRT7779/LFmyJKZOnRrr16+PxYsXx5gxY+KRRx6Jk08+OfU6mmPFihXx93//9xERcfrpp8ehhx6aaT0AAEDhdehRW7C163p0LtjaFcsLtnSs71leuMULqnCzp82HBtgzss4U58+fHyNGjIi5c+fmv3bggQfGoYceGj179ox169bFnDlz4uWXX97tTLXVBs5b9enTJ4466qj88eijj8aPf/zjFq93zjnn5P9gDBo0KKZMmRLDhg3Lv7906dI4++yz47HHHouNGzfGWWedFXPmzInu3bvv7rfSIps2bYqzzz475s+fH7169YqbbropkzoAAACgLSv/4LlKsDO5XF3EyqyrKGLJB0fWNbRQlpniypUrY+TIkfmweeTIkfGf//mfMXTo0O2urauri2nTpsXq1atbvF+rneF8yimnRHV1ddTU1MSDDz4YV199dZx66qm79Ut6+OGH46mnnoqIiIqKinjwwQcb/MGIiKiqqoopU6bEkCFDIiLi/fffj+uvv36H611zzTX5edLNPebNm9dovVu2bIkLLrggHn300ejSpUs8+OCD0b9//xZ//wAAAABA86SdKTbXN7/5zXj77bcjIuILX/hC/O53v9th2Ly1vlNOOSXOOuusFu/XagPnvn37xr777pvqmj/72c/y5xdccMFOR1N06tQprr322vzrm2++OTZt2rTddXvttVf07NmzRUd5+a7/U7BcLhcXXXRR3H333dGpU6d46KGH4phjjmnhdw4AAAAA2cn6YYG789DAtDPF5nj55ZfjlltuiYiIgQMHxn/91381mivurlYbOKdtzZo18dhjj+Vfjx8/fpfXn3nmmdG5c/1cs/fffz+efPLJ7a654oorYunSpS06Bg4cuNO9c7lcTJgwISZNmhR77bVX/M///E+ceOKJLfzOAQAAAICWKESm2Bzbjtf92te+Fl26dNmt9ZpC4NxEzz77bGzYsCEi6j9tOOqoo3Z5fWVlZRx33HH519OmTStofdv62te+Frfcckt07Ngxfvvb38aIESP22N4AAAAAQL0sM8XNmzfHPffck3995plntnit5mj1Dw1My2uvvZY/P/TQQ6Ndu8Z/dEcccUT87ne/2+7+QrrsssvixhtvjMrKypgyZUqMGjVqj+wLAAAUl77dVxVs7eqqyoKtXVdVsKWjbmnh/glcsbxgS0dEIf/T54oCrl2YLrr2i1v+ICughJXoQwOzzBT/9Kc/xapV9X8f6NatW+y///6xadOmuOOOO+LOO++M2bNnx/Lly6OqqiqGDh0aZ5xxRnzpS1+KDh06tHjPCIFzk73xxhv580GDBjXpnm1nSL/++uup1/RhV1xxRfzkJz/Jh82f/OQnC74nAAAAALBjWWaKv//97/PnAwcOjAULFsTnPve5ePHFFxtct3Dhwli4cGE88sgj8a//+q/xq1/9qtFO7F0RODfRsmXL8ud9+vRp0j19+/bNn7///vup17St5557Lm644YaIiOjatWtce+21DYaMb2v06NHxj//4jwWtBwAAgLattqow3dPtFxdkWYCCyDJTfOeddxq8PvXUU2P27NkREXHQQQfFUUcdFeXl5TFz5sx46aWXIiJi/vz5MWLEiHjyySfj4x//eIv2FTg30Zo1a/LnHTt2bNI921637f2FsHUWTETE4sWLY/Hinf8v8Ec+8pGdrrHtOltb7gEAAAAgU0U0UuPDmVmHDh12OoYiy0xxxYoV+fM//elPERGx1157xaRJk+Kss85qcO3jjz8en//852Pp0qWxbt26+MIXvhCvvvpqVFQ0/8NDDw1sotra2vx5U3/Q2/5BW79+feo1bWvEiBGRy+WadEyaNGmHa1x33XXRrVu3/DFw4MCC1gwAAAAApWbgwIENMrTrrrtup9dmmSmuXbt2u6/deeed24XNEREjR46M3/72t1FWVh8Xz5kzJ+66664W7StwbqLKyr88FKOurq5J92zbLdzUTzCy9O1vfztWrlyZPz7cdg8AAAAAbd0777zTIEP79re/vdNrs8wUt907IuK4446Lz372szu9/rjjjouxY8fmX993330t2tdIjSbq3Llz/rypnyxse9229xerXbX/AwAAsHN1PbKuoKXKsy6g2Sp7dynY2u0LtnJh5WqWZF0CFFwuqT+yriGi/vlpXbt2bdI9WWaKH753V2Hzttf86le/ioiIZ599tkX76nBuop49e+bP33vvvSbdU1NTkz/fe++9U68JAAAAACheWWaK2+4dEXHIIYc0es/BBx+cP1+9enWsXr262fsKnJvowAMPzJ9XV1c36Z758+fnzw866KDUawIAAACANiEpkqOZsswUP3xvU7qlu3Rp+F+RCJwLaNt0f9asWbFp06ZG73nppZd2eD8AAAAA0PplmSl+7GMfa/B6zZo1jd7z4YC5W7duzd7XDOcmOv7446NDhw6xYcOGWLt2bcyYMSOOPfbYnV6/YcOGeP755/OvTz755D1RJgAAQMF16FGbdQktsiEqG7+oKPmn+7ZqqyoKuHrh5kMXUqnOni4kc60pFllmioMHD47BgwfH3LlzIyLi1VdfjdNOO22X97z22mv587333js6derU7H11ODdR586dY9SoUfnXkyZN2uX1DzzwQP4Tgb333jtOOumkQpYHAAAAAK1X1qM0WjhSI+tMcezYsfnzyZMnN3r9tte0dG+BczNceuml+fNJkybF7Nmzd3jdunXr4uqrr86/njBhQrRr5xNpAAAAAGhrsswUL7nkkmjfvv6/g3j22Wfjt7/97U6vffHFF+OBBx7Iv77wwgtbtKcUtBlOO+20OPHEE+Opp56KDRs2xGc+85mYMmVKDB06NH/NsmXLYty4cfHWW29FRP0nEVdeeWVWJQMAAEVqaOd3sy6hzanJuoAWKuwokNKLBdb3LC/g6oUb11G5tK5ga7O9pG+vrEtotmTzhoiVWVdBIaSdKc6bNy8GDx6cfz1x4sSdhsP7779/XHrppfHjH/84IiLOOeecuP322xt0PkdEPPHEE3HWWWfF5s2bIyLi2GOPjTPOOKNF32/p/S9LM4wePToWLlzY4Gs1NX/5K8aMGTPisMMO2+6+hx9+OPr377/DNe++++44+uijY9GiRTFv3rw47LDDYvjw4bH//vvHkiVLYurUqbFu3bqIiGjXrl3cf//90b1799S+JwAAAKAwSjXMLuTs6faLVzd+EewBuaT+yLqGlsoyU/zhD38YL730Ujz11FOxdu3aOPPMM+Pggw+Oo446KsrLy2PmzJnxhz/8IX99v3794v77748kadk33KoD51dffTWqq6t3+v7atWvjlVde2e7rdXU7/9RxwIABMW3atBg3bly8/PLLkcvlYvr06TF9+vQG1/Xq1SsmTpzYYEYLAAAAAND2ZJkpdujQIR588MG45JJL4p577omI+ocDbvuAwK2OOeaY+O///u8YOHBgi/dr1YFzoRx00EHxwgsvxL333hv33HNPzJ49O957773o3r17DBkyJMaOHRvjx4+PqqqqrEsFAAAAAIpAlplit27d4u67746LL744br/99nj66afj3Xffjc2bN0efPn3i2GOPjc9//vMxZsyYFnc2b9WqA+d58+YVbO2Kioo4//zz4/zzzy/YHgAAAFBIdVWbsi6h2WqXl2aUUdujcOM6epTouI5CMgqkFUo+OLKuYTelkSnut99+kcvlWnTvSSedFCeddFKL926KsoKuDgAAAABAm1GaHwsCAAAAAG1GqT80sC0ROAMAAACwQ7VVhRzXUUiFGwViXAfsmsAZAAAAKBl1PbKugLZuY+/ChNmbNrWPeLMgS8MeJXAGAABohYZ2fjfrElpkzqqqrEuAkrO+Z+EeSFi6CteZXbm0rmBrswut5KGBbYHAGQAAACgZdVWbsi6h6NQuF+9sr5AhfGHC7E0btxRkXdjTyrIuAAAAAACA1sFHYAAAALQJfbuvyrqEFqnJugBSsWF5ZdYlQOkz0qIkCJwBAKBE9Oy/oKDrD1s4oKDrF1Z11gU02yvrB2VdAgBA6ozUAAAAAAAgFTqcAQAAAICilkvqj6xroHE6nAEAAAAASEVqgfORRx4ZN998c6xevTqtJQEAAAAA6h8YWAwHjUotcH7ppZfi0ksvjX79+sX48ePj6aefTmtpAAAAAABKQKoznHO5XKxbty5uv/32uP322+OAAw6IL3/5y3H++edHr1690twKAAAgb1jF2qxLaLZhFa9mXUKLvdKxunBrdx5UsLVL1cyu+xRs7Tmrqgq2Ng3VFHDtuh6dC7g6H1bbo7wg627eUJh1YU9LLXC+9dZb45e//GU888wzkcvlIiLiz3/+c1xxxRVx1VVXxemnnx4XXXRRnHLKKWltCQAAAADbqeuRdQXNt6U26wogHamN1Bg/fnw89dRT8frrr8c3v/nN6NOnT+RyucjlclFXVxcPPPBAnHbaaTFo0KD47ne/G/Pnz09rawAAAAAAikBqgfNWBxxwQFx//fWxYMGCeOCBB+Izn/lMlJeX58PnBQsWxLXXXhtDhgyJT3/60/GrX/0qNm3alHYZAAAAAADsYanOcN5WeXl5jBkzJsaMGROLFi2KSZMmxcSJE+Ott96KiPp5z1OnTo2pU6dGz5494/zzz4+LLrooDj744EKVBAAAACVnaOd3sy6BIlddVVmwtSuWFiw6gmbJJfVH1jXQuCS3deDyHvLkk0/GLbfcEr/+9a9j/fr1fykkqf+NHXvssfGVr3wlPv/5z8dee+21J0vjQ1atWhXdunWLlStXRteuXbMuBwAAKBLLFg4o2Nqv1HUq2Nps75X1HtK4p8xcU7iHPz4zf0jB1t6wvHBhNg1tWV8bCy67Wg7zIVvzqSFX/UuUV2b753FzbW28/YN/9DtqROojNRpz0kknxe233x6LFi2KG2+8MT72sY9FRORHbjz//PNx0UUXRf/+/eNv//Zv489//vOeLhEAAAAAgBbY44HzVn/605/ixRdfjLlz50aSJPlja/C8atWq+PnPfx4f/ehHY8KECbFy5cqsSgUAAAAAspQUyUGj9uggniVLlsRtt90Wv/zlL+ONN97If33rVI/DDjssxo4dG9OmTYsnnngicrlcbN68OW699dZ4+umn49lnn43u3bvvyZIBAAAAAGiignc453K5eOihh2Ls2LExYMCAuPLKK+ONN97IdzJ36tQpvvzlL8eLL74YL730UvzTP/1TTJs2Ld5888247LLLoqKiInK5XLzxxhvxve99r9DlAgAAAADFJuvOZh3OTVawwHnOnDlx1VVXxcCBA+OMM86IKVOmxMaNG/NB88c//vG4+eabY9GiRfGLX/wijjzyyAb3DxkyJP7zP/8znn766Wjfvn1EREyePLlQ5QIAAAAAsJtSHalRW1sbv/rVr+LWW2+NJ598Mv/1rSMzunTpEuecc05MmDAhDj/88CateeSRR8app54av/3tb2PBggVplgsAAAAAQIpSC5wvueSSuPfee2PVqlUR8ZeQOSLi6KOPjgkTJsTZZ58de+21V7PXHjRoUEREbNq0KZ1iAQAAAIDSkUTksh5pkfX+JSK1wPnmm2+OJEnyQXO3bt3i3HPPjQkTJsTQoUN3a+2ysoKPmgYAAAAAYDelOlIjl8vFcccdFxMmTIjPf/7z0bFjx1TWvfrqq+Mb3/hGKmsBAAAAAFAYqQXOl112WXzlK1+Jj370o2ktmdejR4/o0aNH6usCAAAAlLq+3VcVbO2agq1cujYsr8y6hLYpiexHWmS9f4lILXD+z//8z7SW2qFHHnkkXnzxxYio73gGAAAgGz37F+6B7sMWDijY2uxIddYFtBkz1+yTdQkAe0SqIzUK6aGHHoqf/exnkSSJwBkAAAAAoAiVTOAMAAAAALRNuaT+yLoGGleWdQEAAAAAALQOOpwBAAAAgOLmoYElQ4czAAAAAACpEDgDAAAAAJAKIzUAAAAACmxo53dLcu3fxLCCrV2qagq07uYOtQVauZVIcvVH1jXQKIEzAAAARaNn/wVZl9CmDFs4IOsS2pDqrAtokZld98m6hDZjU/sN8XbWRUAKjNQAAAAAACAVOpwBAAAAgKKWS+qPrGugcTqcAQAAAABIhcAZAAAAAIBUGKkBAAAAABS35IMj6xpolA5nAAAAAABSocMZAAAAAChuOpxLhg5nAAAAAABSUTIdzj179oxBgwZlXQYAAAAAADtRMh3O11xzTcydOzfmzp2bdSkAAAAAwB6US4rjoHGpdTgPGjQoRo4cGcOHD48RI0bE4MGD01oaAAAAKICe/RdkXUKbMWzhgKxLaJFXOr+bdQltRl1ZXTyXdRGQgtQC53feeSfuuOOOuOOOOyIiYuDAgTFixIj8sd9++6W1FQAAAAAARSjVGc65XC5//uEAet99920QQJvHDAAAAAA0SfLBkXUNNCrVDufHH388pk+fHtOnT4+33367wfvz58+P22+/PW6//faIqB/BMXz48Bg5cmSMGDEi9t1337RKAQAAACgqJTu+ZOWnsq4AKDGpBc777LNPfPGLX4wvfvGLERGxYMGCBgH0hx/2V11dvV0AvbX7+fzzz0+rLAAAAAAA9pCyQi08YMCAOO+88+LWW2+NOXPmRHV1ddx2221x4YUXxn777Re5XK7BMW/evJg0aVKMHz++UCUBAAAAAKUoKZKDRhUscP6wgQMHxnnnnRe//OUv4+2334558+bFrbfeGh/72MciIiJJ/MYAAAAAAEpZqg8NbIo//vGP+VEbTz31VKxatUrYDAAAAADsXJKrP7KugUYVPHCeOXNmPmB+8sknY8WKFfn3crm//JJ69uyZf4ggAAAAAAClJ/XAefbs2fmA+Yknnoj3338//962AfPee+8dJ510UowcOTJGjBgRhx56aNqlAAAAAACwB6UWOH/+85+PJ554IpYuXZr/2rYBc48ePeLEE0/MB8xDhw41SgMAAAAAaFQuInIZR4kGajRNaoHzr371q0iSJB8yd+vWLU466aQYMWJEjBw5MoYNGyZgBgAAAABoxVIfqZEkSfTq1SsmTJgQo0aNiuOOOy4qKirS3gYAAAAAgCJTluZiuVwucrlcLFmyJH7wgx/EySefHN27d49Ro0bF9773vXj66adj06ZNaW4JAAAAAECRSK3Dee7cuQ0eFlhdXR0REbW1tTF9+vSYPn16XHPNNdGxY8c4/vjj86M2jj766CgvL0+rDAAAAAAAMpJa4Dxo0KC48MIL48ILL4yIiHnz5jUIoOfPnx8REevWrYvHHnssHnvssYiI6NSpUxx//PExcuTIGDlyZBx55JFRVpZq4zUAAAAAAHtA6jOct9pvv/1i/PjxMX78+Iio74CePn16PP744/HEE0/EO++8ExERa9asid/97nfxu9/9LiIiunTpEitWrChUWQAAAABAqUk+OLKugUYVLHD+sMGDB8fgwYPzAfTbb78d06ZNi//7f/9v/OlPf8pft3r16j1VEgAAAAAAKdpjgfNWs2bNyo/aePLJJ2P58uWRJPUfD+RyuT1dDgAAAABQ5HJJ/ZF1DTSu4IHzq6++2mCW87Jlyxq8/+GQ+aMf/WihSwIAAAAAoABSD5zfeOONfMA8ffr0WLJkSYP3PxwwH3LIITFixIj8UVVVlXZJAAAAAADsAakFzuecc0488cQTUVNT0+DrHw6YDz744AYBc69evdIqAQAAAABojZJc/ZF1DTQqtcD53nvvjSRJtguYDzrooAYBc+/evdPaEgAAAACAIpLqSI1cLhcHHnhgjBgxIkaOHClgBgAAAABoQ1ILnO+5554YMWJE9OnTJ60lAQAAAAAikg+OrGugUakFzl/4whfSWgoAAAAAgBJUlnUBAAAAAAC0DqnOcAYAAAAASJ2RGiVjjwTOK1eujNWrV8eWLVuadP2+++5b4IoAAAAAAEhbQQLn6urquOmmm2Lq1Kkxa9as2LhxY5PvTZIkNm3aVIiyAAAAAIBSpMO5ZKQeOP/oRz+Kf/qnf8qHzLlcLu0tAAAAAAAoQqkGzjfccENceeWV+dedO3eOJEli9erVkSRJ7LvvvrF69epYvnx5PohOkiQqKyujd+/eaZYCAAAAAMAeVpbWQu+880780z/9U0TUB8333XdfrFixIs4///z8NXPnzo2lS5fGihUr4qGHHorTTjstcrlcbNy4Mb761a/G3LlzY+7cuWmVBAAAAAC0BkmuOA4alVqH88033xwbN26MJEnipz/9aZx11lk7vbZLly5x6qmnxqmnnhr33XdfnH/++XHVVVdFXV1dXH311WmVBAAAAMBuGNaxOusS2oza8EwzWofUOpwff/zxiIioqqqK8847r8n3feELX4h///d/j1wuF9/73vfilVdeSaskAAAAAAD2oNQC5zlz5kSSJHHMMcdEkuz4kY2bNu34k5pLL700+vXrF1u2bIlf/vKXaZUEAAAAALQGSZEcNCq1wHn58uUREdGvX78GX+/QoUP+fN26dTu8N0mSOPHEEyOXy8W0adPSKgkAAAAAgD0otRnOFRUVsWnTpu26m7t27Zo/X7BgQRxyyCE7vL9z584REfHuu++mVRIAAAAApKpQc63XbtpckHVhT0utw7l3794REbFy5coGX99vv/3y5y+99NJO73/77bcjImL9+vVplQQAAAAAtAK5pDgOGpda4HzIIYdELpeLt956q8HXDz/88Pz5Pffcs8N7//znP8czzzwTSZJE//790yoJAAAAAIA9KLXA+YQTToiIiNmzZ8eGDRvyXz/00EPjgAMOiFwuF4888kj84Ac/iM2b//KfCMybNy/OOeec2LhxY0REjBw5Mq2SAAAAAADYg1ILnD/1qU9FRMSGDRti+vTpDd779re/nT+/+uqro3fv3nHCCSfE4YcfHn/1V38Vf/zjHyMiol27dvF3f/d3aZUEAAAAALQGSa44DhqVWuB8xBFHxJFHHhm9e/eOBx98sMF7F1xwQVx44YWRy+Uil8vF8uXL4/nnn4+ZM2fG5s2bI5fLRVlZWfzkJz+Jj370o2mVBAAAAADAHtQuzcVefPHFnb73y1/+Mo499tj4t3/7t3jzzTcjl6v/RCBJkjj22GPje9/7Xpx88slplgMAAAAAtAbJB0fWNdCoVAPnxkyYMCEmTJgQCxYsiIULF0ZZWVkMHjw4evbsuSfLAAAAAACgAPZo4LzVgAEDYsCAAVlsDQAAAABAgaQWOI8dOzYiItq3bx933nlntG/fPq2lAQAAAIA2LEnqj6xroHGpBc6TJ0+OJEli1KhRwmYAAAAAgDaoLK2FevToERER++23X1pLAgAAAABQQlLrcO7fv3+sWLEi1q1bl9aSAAAAAAARSa7+yLoGGpVah/OoUaMil8vFiy++mNaSAAAAAACUkNQC5y996UtRXl4ec+bMiQcffDCtZQEAAAAAKBGpBc5Dhw6Nq666KnK5XFxwwQXxzDPPpLU0AAAAANCWJUVy0KjUAueIiGuuuSauv/76WLNmTYwYMSLOOeecmDJlSixYsCA2bNiQ5lYAAAAAABSZ1B4aWF5e3uB1LpeL++67L+67775mrZMkSWzatCmtsgAAAACAUlcMHcZZ718iUgucc7lcJMlffurbnudynuAIAAAAANDapRY4RwiWAQAAAADastQC5y1btqS1FAAAAABFYFjF2qxLaDNWV8jWdi33wZF1DTQm1YcGAgAAAADQdgmcAQAAAABIRaoznAEAAAAAUpd8cGRdA43S4dyKvfPOO9G1a9dIkiSSJIl58+ZlXRIAAAAA0IoJnFuxr3zlK7F69eqsywAAAAAA2giBcys1ceLEePTRR+Ozn/1s1qUAAAAAwG5JklxRHDRO4NwKLVq0KC6//PLYb7/94nvf+17W5QAAAAAAbYSHBrZCl1xySaxYsSLuu+++6NSpU9blAAAAAMDu89C+ktBqO5w3b94cM2fOjFtvvTUuueSSOPLII6OioiL/AL0RI0a0eO26urq44447YvTo0TFo0KCorKyMfv36xfHHHx8/+tGPYunSpel9I810zz33xJQpU+KLX/xifOpTn8qsDgAAAACgoWLLFS+//PJ8XpokSey33367vWar7HCePHlynHvuubFu3brU13799ddj3Lhx8fLLLzf4ek1NTdTU1MRzzz0XN9xwQ0ycODFGjx6d+v67smTJkrjsssuiqqoq/uM//mOP7g0AAAAA7Fyx5Yovvvhi/PjHP0593VYZOK9YsaIgYfOCBQti1KhRsXDhwoiISJIkTjrppNh///1jyZIlMXXq1Fi/fn0sXrw4xowZE4888kicfPLJqdexM//n//yfWLp0adx5551RVVW1x/YFAAAAgEIqhof27c7+xZYrbty4Mb785S/Hli1bUl+7VQbOW/Xp0yeOOuqo/PHoo4/uVmp/zjnn5P9QDBo0KKZMmRLDhg3Lv7906dI4++yz47HHHouNGzfGWWedFXPmzInu3bvv7rfSqMmTJ8f9998fp5xySpx77rkF3w8AAAAAaJpiyxV/+MMfxqxZs/K13X333amt3SpnOJ9yyilRXV0dNTU18eCDD8bVV18dp5566m79gh5++OF46qmnIiKioqIiHnzwwQZ/KCIiqqqqYsqUKTFkyJCIiHj//ffj+uuv3+F611xzTYP5KM055s2b12Ct5cuXxyWXXBKdOnWKm266qcXfIwAAAACQrrRzxd31+uuvx/e///2IiDj33HPjk5/8ZKrrt8rAuW/fvrHvvvumuubPfvaz/PkFF1wQhx566A6v69SpU1x77bX51zfffHNs2rRpu+v22muv6NmzZ4uO8vLyBmv9wz/8Q9TU1MT3v//9GDRoUErfMQAAAAAUiaRIjhZIO1fcHblcLr785S/Hhg0bokePHvHv//7vqa4f0UoD57StWbMmHnvssfzr8ePH7/L6M888Mzp37hwR9Z9GPPnkk9tdc8UVV8TSpUtbdAwcOLDBWjNmzIiIiH/5l3+Jvn37NjiOOuqo/HVHHXVU9O3bN77+9a+3+GcBAAAAADRNIXLF3XHjjTfGM888ExERN9xwQ/Tu3TvV9SMEzk3y7LPPxoYNGyKi/pOGbUPcHamsrIzjjjsu/3ratGkFrW+rJUuWxHvvvdfgWLp0af79pUuXxnvvvRcrV67cI/UAAAAAQFtWTLniO++8E9/61rciIuLEE0+ML33pS6mtvS2BcxO89tpr+fNDDz002rVr/FmLRxxxxA7vL4SXX345crncDo+5c+fmr5s7d27kcrmYNGlSQesBAAAAgDQlSXEczVVMueKll14aq1evjoqKirj55psjack31AQC5yZ444038udNnZG87Qzp119/PfWaAAAAAIDiViy54r333hv/8z//ExERV155ZRx88MGprLsjjUfqxLJly/Lnffr0adI9ffv2zZ+///77qdcEAAAAAG1Gkqs/sq6hmYohV1y2bFlcdtllERFxwAEHxFVXXbXba+6KwLkJ1qxZkz/v2LFjk+7Z9rpt7y9mGzZsyM+UiYhYtWpVhtUAAAAAQPH5cGbWoUOH6NChww6vLYZc8e/+7u9iyZIlERFx00037bTWtBip0QS1tbX584qKiibds+0vbv369anX1FT77bdffp7zfvvtt8trr7vuuujWrVv+GDhw4J4pEgAAAABKxMCBAxtkaNddd91Or806V/zf//3fuOOOOyIi4oILLoiRI0fu1npNocO5CSorK/PndXV1Tbpn207hpn56kbVvf/vbcfnll+dfr1q1SugMAAAAQOaSJBdJxiM1tu7/zjvvRNeuXfNf31XHcJa54tq1a+OrX/1qRET07NkzfvSjH7V4reYQODdB586d8+dN/VRh2+u2vb+Y7ar9HwAAAACI6Nq1a4PAeVeyzBWvuuqqmDdvXkRE/Nu//VtUVVW1eK3mMFKjCXr27Jk/f++995p0T01NTf587733Tr0mAAAAAKC4ZZUrvvTSS/GTn/wkIiJGjhwZF1xwQYvWaQkdzk1w4IEH5s+rq6ubdM/8+fPz5wcddFDqNQEAAABAW5Ek9UfWNTRXVrnizJkzY8uWLfn1jj322J1eu/WBghERixYtanDtP//zP8dpp53WrL0Fzk1w8MEH589nzZoVmzZtinbtdv2je+mll3Z4PwAAAADQNhRDrjhnzpyYM2dOk66tq6uLF154If962zC6qYzUaILjjz8+P9t47dq1MWPGjF1ev2HDhnj++efzr08++eSC1gcAAAAAFJ+2mCsKnJugc+fOMWrUqPzrSZMm7fL6Bx54IFavXh0R9XNWTjrppEKWBwAAAACtW5KLJOMjklyzy84qV7zwwgsjl8s16Zg4cWL+vkGDBjV478ILL2z23gLnJrr00kvz55MmTYrZs2fv8Lp169bF1VdfnX89YcKERtvkAQAAAIDWqa3ligLnJjrttNPixBNPjIj61vbPfOYzMXPmzAbXLFu2LMaMGRNvvfVWRNR/CnHllVfu8VoBAAAAoFVJiuRogbRzxXnz5kWSJPmjsa7pPa30IvImGj16dCxcuLDB12pqavLnM2bMiMMOO2y7+x5++OHo37//Dte8++674+ijj45FixbFvHnz4rDDDovhw4fH/vvvH0uWLImpU6fGunXrIiKiXbt2cf/990f37t1T+54AAAAAgNLTlnLFVhs4v/rqq1FdXb3T99euXRuvvPLKdl+vq6vb6T0DBgyIadOmxbhx4+Lll1+OXC4X06dPj+nTpze4rlevXjFx4sQG81kAAAAAgLapLeWKrTZwLpSDDjooXnjhhbj33nvjnnvuidmzZ8d7770X3bt3jyFDhsTYsWNj/PjxUVVVlXWpAAAAANAq5B/cl3ENu6Ot5IpJLpfL9jdF0Vq1alV069YtVq5cGV27ds26HAAAAIBWSw6zY1t/Lvvf8e0o36sy01o2r6uNOedd53fUCA8NBAAAAAAgFUZqAAAAAABFLfngyLoGGqfDGQAAAACAVAicAQAAAABIhZEaAAAAAEBRS5JcJEku8xponA5nAAAAAABSocMZAAAAAChqSZJ9h3HiqYFNosMZAAAAAIBUCJwBAAAAAEiFkRoAAAAAQFGrH6mRfQ00ToczAAAAAACpEDgDAAAAAJAKIzUAAAAAgKJWluSiLMllWkMu4/1LhQ5nAAAAAABSIXAGAAAAACAVRmoAAAAAAEUtSXKRZDzSIuv9S4UOZwAAAAAAUqHDGQAAAAAoajqcS4cOZwAAAAAAUiFwBgAAAAAgFUZqAAAAAABFLUnqj6xroHE6nAEAAAAASIXAGQAAAACAVBipAQAAAAAUtbIkF2VJLtMachnvXyp0OAMAAAAAkAqBMwAAAAAAqTBSAwAAAAAoakmSiyTjkRZZ718qdDgDAAAAAJAKHc4AAAAAQFEri1yURcYPDcx4/1KhwxkAAAAAgFQInAEAAAAASIWRGgAAAABAUUsiIkmyr4HG6XAGAAAAACAVAmcAAAAAAFJhpAYAAAAAUNSSJBdlSS7TGrZkvH+p0OEMAAAAAEAqBM4AAAAAAKTCSA0AAAAAoKglSS6SjEdaZL1/qdDhDAAAAABAKnQ4AwAAAABFrawIHhqY9f6lQoczAAAAAACpEDgDAAAAAJAKIzUAAAAAgKLmoYGlQ4czAAAAAACpEDgDAAAAAJAKIzUAAAAAgKJWluSiLOORFlnvXyp0OAMAAAAAkAqBMwAAAAAAqTBSAwAAAAAoamWRi7LIeKRGxvuXCh3OAAAAAACkQoczAAAAAFDUkiQXScYP7ct6/1KhwxkAAAAAgFQInAEAAAAASIWRGgAAAABAUStLclGW8UiLrPcvFTqcAQAAAABIhcAZAAAAAIBUGKkBAAAAABQ1IzVKhw5nAAAAAABSIXAGAAAAACAVRmoAAAAAAEXNSI3SocMZAAAAAIBU6HAGAAAAAIqaDufSocMZAAAAAIBUCJwBAAAAAEiFkRoAAAAAQFFLIqIssh1pkWS6e+nQ4QwAAAAAQCoEzgAAAAAApMJIDQAAAACgqJUluShLsh2pkfX+pUKHMwAAAAAAqRA4AwAAAACQCiM1AAAAAICiZqRG6dDhDAAAAABAKnQ4AwAAAABFTYdz6dDhDAAAAABAKgTOAAAAAACkwkgNAAAAAKCoGalROnQ4AwAAAACQCoEzAAAAAACpMFIDAAAAAChqZZGLssh4pEbG+5cKHc4AAAAAAKRC4AwAAAAAQCqM1AAAAAAAilpZkouyJOORGhnvXyp0OAMAAAAAkAodzgAAAABAUStLtkRZsiXzGmicDmcAAAAAAFIhcAYAAAAAIBVGagAAAAAARc1DA0uHDmcAAAAAAFIhcAYAAAAAIBVGagAAAAAARS2JXJRFtiMtkoz3LxU6nAEAAAAASIXAGQAAAACAVBipAQAAAAAUtbLIRVmS7UiLrEd6lAodzgAAAAAApEKHMwAAAABQ1MqSLVGWbMm8BhqnwxkAAAAAgFQInAEAAAAASIWRGgAAAABAUStPclGe8UMDs96/VOhwBgAAAAAgFQJnAAAAAABSYaQGAAAAAFDUyiIXZZHtSIus9y8VOpwBAAAAAEiFwBkAAAAAgFQYqQEAAAAAFLWyZEuUJVsyr4HG6XAGAAAAACAVOpwBAAAAgKJWlkSUJRk/NDDJdPuSocMZAAAAAIBUCJwBAAAAAEiFkRoAAAAAQFErj1yUR7YjNbLev1TocAYAAAAAIBUC51bo8ccfj3HjxsXAgQOjQ4cOUVVVFUcccUR84xvfiJqamqzLAwAAAABaKSM1WpEtW7bEJZdcEr/4xS8iIqJfv34xbNiwWLlyZbz++uvxxz/+MT73uc9F3759M64UAAAAAJouSbZEWbIl8xponMC5Ffn6178ev/jFL2LYsGFx8803xzHHHJN/b+PGjfH000/HkCFDMqwQAAAAAGjNBM6txJNPPhk//elPY8CAATF9+vTo3r17g/fbt28fI0eOzKY4AAAAAKBNEDi3Ev/2b/8WERHf/OY3twubAQAAAKCUlSW5KEtymddA41rtQwM3b94cM2fOjFtvvTUuueSSOPLII6OioiKSJIkkSWLEiBEtXruuri7uuOOOGD16dAwaNCgqKyujX79+cfzxx8ePfvSjWLp0aXrfSBNs2LAhHnnkkYiI+OQnPxlvvvlmXHHFFXHKKafE6NGj45vf/Ga8/PLLe7QmAAAAAKChLHLFefPmxX/913/FF7/4xRg2bFj06NEj2rdvH3vvvXcMHTo0vvrVr8YTTzyR2n5JLpdrddH85MmT49xzz41169bt9Jrhw4fH9OnTm73266+/HuPGjdtlgNu7d++YOHFijB49utnrt8QLL7wQxx57bERE3HrrrfG1r30tamtrG1yTJEn84z/+Y3z/+99v8rqrVq2Kbt26xcqVK6Nr166p1gwAAADAX8hhdmzrz+X/PP3Z6NC5faa1bFizMX76179p8e9oT+eKf/zjH+Piiy+OF198sUnXjxgxIm677bbYd999d2vfVtnhvGLFil2GzS21YMGCGDVqVP4PRZIkMXz48PjSl74Up59+enTs2DEiIhYvXhxjxoyJadOmpV7DjixatCh/fvHFF8chhxwSzz77bNTW1sa8efPikksuiVwuFz/4wQ/illtu2SM1AQAAAAD1ssgV33jjje3C5gMOOCDGjh0bEyZMiM9//vMxYMCA/HvTp0+P4447Lt5+++3d2rdVz3Du06dPHHXUUfnj0UcfjR//+MctXu+cc86JhQsXRkTEoEGDYsqUKTFs2LD8+0uXLo2zzz47Hnvssdi4cWOcddZZMWfOnILPVF6zZk3+vEOHDvHII49Er1698nX+/Oc/j/nz58dDDz0U3/nOd2L8+PFRXl5e0JoAAAAAgHpZ5oof+chH4stf/nJ88YtfjH322afBe1u2bIlJkybF3/7t38a6deti4cKFce6558azzz4bSZK0aL9W2eF8yimnRHV1ddTU1MSDDz4YV199dZx66qm79Qt6+OGH46mnnoqIiIqKinjwwQcb/KGIiKiqqoopU6bEkCFDIiLi/fffj+uvv36H611zzTX5edLNPebNm9dgra2fgEREnH/++fmweVv/8A//EBERCxcuNM8ZAAAAgJJSFluK4miJtHPFpurXr19MnDgxXn/99bjyyiu3C5sjIsrKyuJLX/pS3HnnnfmvPf/88/G///u/Ld63VQbOffv23e1ZIx/2s5/9LH9+wQUXxKGHHrrD6zp16hTXXntt/vXNN98cmzZt2u66vfbaK3r27Nmi48PdyXvvvXf+/OCDD95hXYccckj+fO7cuU37pgEAAACA3ZJ2rthUw4cPjwsvvLBJkw4++9nPxtFHH51//dBDD7V431YZOKdtzZo18dhjj+Vfjx8/fpfXn3nmmdG5c+eIqP804sknn9zumiuuuCKWLl3aomPgwIEN1jrooIPy5x06dNhhTdt+ffPmzY1/0wAAAADAbilErlgoJ5xwQv78wxMWmkPg3ATPPvtsbNiwISLqP2k46qijdnl9ZWVlHHfccfnXhX54YL9+/fLt9jsb6j1nzpz8+bbDwAEAAACg2JUluaI4mqvYc8VtbTuzeXcaVgXOTfDaa6/lzw899NBo167xZy0eccQRO7y/UMaNGxcREXfddVf+D/G2brnlloiI6N69exx55JEFrwcAAAAA2rpSyBW3mjVrVv78wxMWmkPg3ARvvPFG/nzQoEFNumfbGdKvv/566jV92OWXXx49e/aMd955Jy6++OJYt25d/r277747/uu//isi6h8euLOxGwAAAABAekohV4yImD9/foNu6k984hMtXqvxSJ1YtmxZ/rxPnz5Nuqdv37758/fffz/1mj5s7733jsmTJ8epp54akyZNil//+tdx0EEHxXvvvRfz58+PiIizzz47vvWtbxW8FgAAAABIU3lsifLYknkNzVUKuWJEfTPr1jEa++67b5x++uktXkuHcxOsWbMmf96xY8cm3bPtddveX0h//dd/HbNnz46LL744evbsGa+88kqsWrUqRo4cGXfffXfcfffdUVa281/5hg0bYtWqVQ0OAAAAAOAvPpyf7Wi87ValkCvedttt8etf/zr/+rrrrtutCQk6nJugtrY2f15RUdGke7b9paxfvz71mnZm3333jRtvvLFF91533XXx3e9+N+WKAAAAAGD3tPShfWnXELH9fOPvfOc7cc011+zwnmLPFWfMmBEXX3xx/vW4cePinHPO2a01Bc5NUFlZmT+vq6tr0j3bfrLR1E8vsvbtb387Lr/88vzrVatW7daAcAAAAABobd55553o2rVr/vWuuoGLOVecO3dunH766flQfOjQoXHTTTft9roC5ybo3Llz/rypnypse9229xezDh06eKAgAAAAAOxC165dGwTOu1KsueKiRYvik5/8ZNTU1ERExJAhQ+KRRx5p8ve1KwLnJujZs2f+/L333mvSPVt/WRH1D/QDAAAAAFqmPNkS5UnGDw1swf7FmCsuW7YsPvnJT8acOXMiIqJfv34xderU6NevXyrre2hgExx44IH58+rq6ibdM3/+/Pz5QQcdlHpNAAAAAEBxK7ZccdWqVfHpT386Zs+eHRERVVVVMXXq1Bg8eHBqewicm+Dggw/On8+aNSs2bdrU6D0vvfTSDu8HAAAAANqGYsoV165dG6NHj44//OEPERHRrVu3eOSRR+KQQw5JbY8IgXOTHH/88fnZxmvXro0ZM2bs8voNGzbE888/n3998sknF7Q+AAAAAGjNkshFWcZHErlm110suWJtbW2cccYZ8cwzz0RExF577RUPPfRQfPzjH09l/W0JnJugc+fOMWrUqPzrSZMm7fL6Bx54IFavXh0R9XNWTjrppEKWBwAAAAAUoWLIFTdu3BhnnnlmTJs2LSIiOnToEFOmTIkTTjhht9feEYFzE1166aX580mTJuXnnHzYunXr4uqrr86/njBhQrRr59mMAAAAANAWZZkrbt68Oc4555x4+OGHIyKiXbt2cf/998cnPvGJ3Vp3VwTOTXTaaafFiSeeGBH1re2f+cxnYubMmQ2uWbZsWYwZMybeeuutiKj/FOLKK6/c47UCAAAAQGtSnmwpiqMl0s4V582bF0mS5I+ddU3ncrm46KKL4le/+lVERJSVlcUdd9wRZ5xxRou+j6Zqta23o0ePjoULFzb4Wk1NTf58xowZcdhhh21338MPPxz9+/ff4Zp33313HH300bFo0aKYN29eHHbYYTF8+PDYf//9Y8mSJTF16tRYt25dRPzl04Lu3bun9j0BAAAAAKUni1zxxhtvjNtuuy3/ev/994+nn346nn766Sbd/9Of/rRF+7bawPnVV1+N6urqnb6/du3aeOWVV7b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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_eaf_single_objective\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"SO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1], algorithms=['HillClimber']).load(True, True)\n", - "ax, data = plot_eaf_single_objective(\n", - " df,\n", - " file_name=\"example_plots/eaf_single_objective.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 107, - "id": "433832c8", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_eaf_pareto, add_normalized_objectives\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"MO_Data\")\n", - "\n", - "df = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False)\n", - "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", - "ax, data = plot_eaf_pareto(\n", - " df,\n", - " obj1_var=\"obj1\",\n", - " obj2_var=\"obj2\",\n", - " file_name=\"example_plots/eaf_pareto.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 108, - "id": "bcb34ed4", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_eaf_diffs, add_normalized_objectives\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"MO_Data\")\n", - "\n", - "df1 = manager.select(function_ids=[0], algorithms=['NSGA2']).load(False, False)\n", - "df1 = add_normalized_objectives(df1, obj_vars = ['raw_y', 'F2'])\n", - "\n", - "df2 = manager.select(function_ids=[0], algorithms=['SMS-EMOA']).load(False, False)\n", - "df2 = add_normalized_objectives(df2, obj_vars = ['raw_y', 'F2'])\n", - "\n", - "ax, data = plot_eaf_diffs(\n", - " df1,\n", - " df2,\n", - " obj1_var=\"obj1\",\n", - " obj2_var=\"obj2\",\n", - " file_name=\"example_plots/eaf_diffs.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 109, - "id": "b7c6fdf1", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_single_function_fixed_budget\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"SO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1]).load(True, True)\n", - "ax, data = plot_single_function_fixed_budget(\n", - " df,\n", - " file_name=\"example_plots/fixed_budget.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "id": "acb246b8", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_single_function_fixed_target\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"SO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1]).load(True, True)\n", - "ax, data = plot_single_function_fixed_target(\n", - " df,\n", - " file_name=\"example_plots/fixed_target.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 111, - "id": "68d3bb56", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_paretofronts_2d\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"MO_Data\")\n", - "\n", - "df = manager.select().load(True, True)\n", - "\n", - "ax, data = plot_paretofronts_2d(\n", - " df,\n", - " obj1_var=\"raw_y\",\n", - " obj2_var=\"F2\",\n", - " file_name=\"example_plots/pareto_fronts.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 112, - "id": "a5fcfc56", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_indicator_over_time, add_normalized_objectives, get_reference_set, IGDPlus\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"MO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1]).load(False, True)\n", - "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", - "ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000)\n", - "\n", - "igdp_indicator = IGDPlus(reference_set = ref_set)\n", - "\n", - "ax, data = plot_indicator_over_time(\n", - " df, ['obj1', 'obj2'], igdp_indicator, \n", - " eval_min=10, eval_max=2000, eval_steps=50, free_var='algorithm_name',\n", - " file_name=\"example_plots/indicator_over_time.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "id": "891e6be7", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_tournament_ranking\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"SO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1]).load(True, True)\n", - "ax, data = plot_tournament_ranking(\n", - " df,\n", - " file_name=\"example_plots/tournament_rankings.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 114, - "id": "411d4473", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", - " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", - " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_robustrank_over_time, IGDPlus, get_reference_set, add_normalized_objectives\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"MO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1]).load(True, True)\n", - "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", - "ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000)\n", - "\n", - "igdp_indicator = IGDPlus(reference_set = ref_set)\n", - "evals = [10,100,1000,2000]\n", - "\n", - "ax, comparison, benchmark = plot_robustrank_over_time(\n", - " df,\n", - " obj_vars=['obj1', 'obj2'],\n", - " evals=evals,\n", - " indicator=igdp_indicator,\n", - " file_name=\"example_plots/robustrank_over_time.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 115, - "id": "29f63dab", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", - " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", - " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", - " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", - " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", - " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", - " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/abstract_comparison.py:45: UserWarning: No results found. Start computations\n", - " warnings.warn(\"No results found. Start computations\")\n", - "/home/dinu/miniconda3/envs/iohinspector/lib/python3.10/site-packages/robustranking/comparison/bootstrap_comparison.py:67: UserWarning: There are only 252 unique samples possible, which is less than the requested 1000 bootstrap samples. Duplicate samples are inevitable. Consider increasing the number of instances or reducing the number of bootstraps.\n", - " warnings.warn(f\"There are only {binom(2*num_instances, num_instances):.0f} unique samples possible, \"\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_robustrank_changes, IGDPlus, get_reference_set, add_normalized_objectives\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"MO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1]).load(True, True)\n", - "df = add_normalized_objectives(df, obj_vars = ['raw_y', 'F2'])\n", - "ref_set = get_reference_set(df, ['obj1', 'obj2'], 1000)\n", - "\n", - "igdp_indicator = IGDPlus(reference_set = ref_set)\n", - "evals = [10,100,1000,2000]\n", - "\n", - "ax, comparison = plot_robustrank_changes(\n", - " df,\n", - " obj_vars=['obj1', 'obj2'],\n", - " evals=evals,\n", - " indicator=igdp_indicator,\n", - " file_name=\"example_plots/robustrank_changes.png\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 116, - "id": "0b6b6487", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from iohinspector import DataManager, plot_heatmap_single_run\n", - "import os\n", - "\n", - "os.makedirs(\"example_plots\", exist_ok=True)\n", - "\n", - "manager = DataManager()\n", - "manager.add_folder(\"SO_Data\")\n", - "\n", - "df = manager.select(function_ids=[1], data_ids=[1], algorithms=[\"RandomSearch\"]).load(True, True)\n", - "\n", - "ax, data = plot_heatmap_single_run(\n", - " df,\n", - " vars = [\"x0\",\"x1\"],\n", - " var_mins=[-5,-5],\n", - " var_maxs=[5,5],\n", - " file_name=\"example_plots/heatmap_single_run.png\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "c562712e", - "metadata": {}, - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "iohinspector", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.18" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 042b878779ed57c769fcd3aa4a6fae63f7644e19 Mon Sep 17 00:00:00 2001 From: Dinu23 Date: Tue, 9 Dec 2025 14:09:57 +0100 Subject: [PATCH 17/17] removed .vscode --- .vscode/settings.json | 11 ----------- 1 file changed, 11 deletions(-) delete mode 100644 .vscode/settings.json diff --git a/.vscode/settings.json b/.vscode/settings.json deleted file mode 100644 index e9e6a80..0000000 --- a/.vscode/settings.json +++ /dev/null @@ -1,11 +0,0 @@ -{ - "python.testing.unittestArgs": [ - "-v", - "-s", - "./tests", - "-p", - "test_*.py" - ], - "python.testing.pytestEnabled": false, - "python.testing.unittestEnabled": true -} \ No newline at end of file

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