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Improve hyperopt Tests

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ensure scikit-learn has to generate new random points by reducing initial points
this will uncover a failure in newer scikit-learn versions
This commit is contained in:
Matthias
2023-11-22 07:21:07 +01:00
parent 869756d87d
commit 6963a92332
1 changed files with 6 additions and 0 deletions
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tests/optimize/test_hyperopt.py
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@@ -310,6 +310,8 @@ def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
'freqtrade.optimize.hyperopt.get_timerange', 'freqtrade.optimize.hyperopt.get_timerange',
MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13))) MagicMock(return_value=(datetime(2017, 12, 10), datetime(2017, 12, 13)))
) )
# Dummy-reduce points to ensure scikit-learn is forced to generate new values
mocker.patch('freqtrade.optimize.hyperopt.INITIAL_POINTS', 2)
parallel = mocker.patch( parallel = mocker.patch(
'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel', 'freqtrade.optimize.hyperopt.Hyperopt.run_optimizer_parallel',
@@ -860,6 +862,8 @@ def test_simplified_interface_failed(mocker, hyperopt_conf, space) -> None:
def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmp_path, fee) -> None: def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmp_path, fee) -> None:
patch_exchange(mocker) patch_exchange(mocker)
mocker.patch(f'{EXMS}.get_fee', fee) mocker.patch(f'{EXMS}.get_fee', fee)
# Dummy-reduce points to ensure scikit-learn is forced to generate new values
mocker.patch('freqtrade.optimize.hyperopt.INITIAL_POINTS', 2)
(tmp_path / 'hyperopt_results').mkdir(parents=True) (tmp_path / 'hyperopt_results').mkdir(parents=True)
# No hyperopt needed # No hyperopt needed
hyperopt_conf.update({ hyperopt_conf.update({
@@ -904,6 +908,8 @@ def test_in_strategy_auto_hyperopt_with_parallel(mocker, hyperopt_conf, tmp_path
mocker.patch(f'{EXMS}.markets', mocker.patch(f'{EXMS}.markets',
PropertyMock(return_value=get_markets())) PropertyMock(return_value=get_markets()))
(tmp_path / 'hyperopt_results').mkdir(parents=True) (tmp_path / 'hyperopt_results').mkdir(parents=True)
# Dummy-reduce points to ensure scikit-learn is forced to generate new values
mocker.patch('freqtrade.optimize.hyperopt.INITIAL_POINTS', 2)
# No hyperopt needed # No hyperopt needed
hyperopt_conf.update({ hyperopt_conf.update({
'strategy': 'HyperoptableStrategy', 'strategy': 'HyperoptableStrategy',