def test_environment_init_metrics(metrics, expected):
env = Environment(**dict(
default_env_params,
**dict(metrics_params=dict(
metrics_map=metrics, in_fold="all", oof="all", holdout="all")),
))
assert env == expected
def env_fixture_1():
return Environment(
train_dataset=get_toy_classification_data(),
results_path=None,
metrics=["roc_auc_score"],
cv_type="StratifiedKFold",
cv_params=dict(n_splits=5, shuffle=True, random_state=32),
)
def test_environment_init_cross_experiment_params(runs, cv_type, _cv_params, expected):
env = Environment(
**dict(
default_env_params,
**dict(runs=runs, cross_validation_type=cv_type, cross_validation_params=_cv_params),
)
)
assert env == expected
def env_fixture_0():
return Environment(
train_dataset=get_toy_classification_data(),
results_path=
"hyperparameter_hunter/__TEST__HyperparameterHunterAssets__",
metrics=["roc_auc_score"],
cv_type="StratifiedKFold",
cv_params=dict(n_splits=5, shuffle=True, random_state=32),
)
def test_environment_repr(env_params):
"""Test that :meth:`Environment.__repr__` returns the expected value"""
env = Environment(**env_params)
assert env.__repr__(
) == f"Environment(cross_experiment_key={env.cross_experiment_key!s})"
def test_environment_init_cv_params(_cv_params, expected):
env = Environment(
**dict(default_env_params, **dict(cross_validation_params=_cv_params)))
assert env == expected
