Skip to content

v2.2.0 #3

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
detlefarend wants to merge 2 commits into
base: main
Choose a base branch
from
Draft

v2.2.0 #3

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
ab1e823
BF: Random cloud generator - consolidation and enhancements
detlefarend Nov 6, 2025
f192b3c
BF: Random cloud generator - consolidation and enhancements
detlefarend Nov 6, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 7 additions & 3 deletions src/mlpro/bf/streams/streams/generators/basics.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -6,10 +6,11 @@
## -- History :
## -- yyyy-mm-dd Ver. Auth. Description
## -- 2025-09-21 1.0.0 DA Creation
## -- 2025-11-06 1.0.1 DA Bugfix in StreamGenerator.__next__()
## -------------------------------------------------------------------------------------------------

"""
Ver. 1.0.0 (2025-09-21)
Ver. 1.0.1 (2025-11-06)

This module provides template classes for single and multi-stream data generation in a d-dimensional
feature space.
Expand Down Expand Up @@ -148,7 +149,10 @@ def _get_rescaling_params(self, p_boundaries_rescale : list):

## -------------------------------------------------------------------------------------------------
def set_random_seed(self, p_seed=None):
self._rgen = np.random.default_rng( seed = p_seed )
if self._seed is None:
self._seed = p_seed

self._rgen = np.random.default_rng( seed = self._seed )


## -------------------------------------------------------------------------------------------------
Expand Down Expand Up @@ -183,7 +187,7 @@ def __next__(self) -> Instance:

raise_outlier = False

if self._outlier_appearance and np.random.rand() < self._outlier_rate:
if self._outlier_appearance and self._rgen.random() < self._outlier_rate:
# 1 Generate outlier instance
outlier_data = Element( p_set = self.get_feature_space() )
outlier_values = self._gen_rnd_array( self.C_BOUNDARIES[0], self.C_BOUNDARIES[1], self._num_dim )
Expand Down