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Update backtester.py #10

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Update backtester.py #10

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59 changes: 25 additions & 34 deletions qnt/backtester.py
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Original file line number Diff line number Diff line change
Expand Up @@ -285,15 +285,7 @@ def backtest(
current_date = pd.to_datetime('today')
data_days_difference = (current_date - checking_start_data_date).days
data = load_data(data_days_difference)
try:
if data.name == 'stocks' and competition_type != 'stocks' and competition_type != 'stocks_long' \
or data.name == 'stocks_nasdaq100' and competition_type != 'stocks_nasdaq100' \
or data.name == 'cryptofutures' and competition_type != 'cryptofutures' and competition_type != 'crypto_futures' \
or data.name == 'crypto' and competition_type != 'crypto' \
or data.name == 'futures' and competition_type != 'futures':
log_err("WARNING! The data type and the competition type are mismatch.")
except:
pass
check_data_type_mismatch(data, competition_type)
data, time_series = extract_time_series(data)

log_info("Run strategy...")
Expand All @@ -309,15 +301,7 @@ def backtest(
days=60)))
else:
data = load_data(lookback_period)
try:
if data.name == 'stocks' and competition_type != 'stocks' and competition_type != 'stocks_long' \
or data.name == 'stocks_nasdaq100' and competition_type != 'stocks_nasdaq100' \
or data.name == 'cryptofutures' and competition_type != 'cryptofutures' and competition_type != 'crypto_futures' \
or data.name == 'crypto' and competition_type != 'crypto' \
or data.name == 'futures' and competition_type != 'futures':
log_err("WARNING! The data type and the competition type are mismatch.")
except:
pass
check_data_type_mismatch(data, competition_type)
data, time_series = extract_time_series(data)

log_info("Run strategy...")
Expand Down Expand Up @@ -418,39 +402,46 @@ def copy_window(data, dt, tail):
output_time_coord = ts[ts >= start_date]
output_time_coord = output_time_coord[::step]

i = 0

sys.stdout.flush()

with progressbar.ProgressBar(max_value=len(output_time_coord), poll_interval=1) as p:
state = None
for t in output_time_coord:
for i, t in enumerate(output_time_coord):
tail = copy_window(data, t, lookback_period)
result = strategy(tail, copy.deepcopy(state))
output, state = unpack_result(result)
if type(output) != xr.DataArray:
log_err("Output is not xarray!")
return
if set(output.dims) != {'asset'} and set(output.dims) != {'asset', 'time'}:
log_err("Wrong output dimensions. ", output.dims, "Should contain only:", {'asset', 'time'})
return
validate_output(output)
if 'time' in output.dims:
output = output.sel(time=t)
output = output.isel(time=-1)
output = output.drop_vars(['field', 'time'], errors='ignore')
outputs.append(output)
if collect_all_states:
all_states.append(state)
i += 1
p.update(i)

sys.stderr.flush()
p.update(i+1)

log_info("Merge outputs...")
output = xr.concat(outputs, pd.Index(output_time_coord, name=qndata.ds.TIME))

return output, all_states if collect_all_states else state


def check_data_type_mismatch(data, competition_type: str):
valid_competition_types = {
'stocks': ['stocks', 'stocks_long'],
'stocks_nasdaq100': ['stocks_nasdaq100'],
'cryptofutures': ['cryptofutures', 'crypto_futures'],
'crypto': ['crypto'],
'futures': ['futures']
}
if competition_type not in valid_competition_types[data.name]:
log_err("WARNING! The data type and the competition type are mismatched.")


def validate_output(output):
if not isinstance(output, xr.DataArray):
raise ValueError("Invalid output type. Expected xarray.DataArray.")
if set(output.dims) not in [{'asset'}, {'asset', 'time'}]:
raise ValueError(f"Wrong output dimensions. {output.dims} Should contain only: {'asset', 'time'}")


def standard_window(data, max_date: np.datetime64, lookback_period:int):
min_date = max_date - np.timedelta64(lookback_period,'D')
return data.loc[dict(time=slice(min_date, max_date))]
Expand Down