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Optimize tests speed #495

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Merged
j-adamczyk merged 1 commit into from
Sep 25, 2025
Merged

Optimize tests speed #495

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4 changes: 2 additions & 2 deletions skfp/applicability_domain/knn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -199,12 +199,12 @@ def score_samples(self, X: np.ndarray) -> np.ndarray:

return self._get_agg_dists(k_nearest)

def _get_agg_dists(self, k_nearest) -> np.ndarray[float]:
def _get_agg_dists(self, k_nearest) -> np.ndarray:
if self.agg == "mean":
agg_dists = np.mean(k_nearest, axis=1)
elif self.agg == "max":
agg_dists = np.max(k_nearest, axis=1)
elif self.agg == "min":
else: # "min"
agg_dists = np.min(k_nearest, axis=1)

return agg_dists
22 changes: 11 additions & 11 deletions tests/applicability_domain/knn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -17,9 +17,9 @@
@pytest.mark.parametrize("agg", ALLOWED_AGGREGATIONS)
def test_inside_knn_ad(metric, agg):
if "binary" in metric:
X_train, X_test = get_data_inside_ad(binarize=True)
X_train, X_test = get_data_inside_ad(n_train=100, n_test=10, binarize=True)
else:
X_train, X_test = get_data_inside_ad()
X_train, X_test = get_data_inside_ad(n_train=100, n_test=10)

ad_checker = KNNADChecker(k=3, agg=agg)
ad_checker.fit(X_train)
Expand All @@ -39,9 +39,9 @@ def test_inside_knn_ad(metric, agg):
@pytest.mark.parametrize("agg", ALLOWED_AGGREGATIONS)
def test_outside_knn_ad(metric, agg):
if "binary" in metric:
X_train, X_test = get_data_outside_ad(binarize=True)
X_train, X_test = get_data_outside_ad(n_train=100, n_test=10, binarize=True)
else:
X_train, X_test = get_data_outside_ad()
X_train, X_test = get_data_outside_ad(n_train=100, n_test=10)

ad_checker = KNNADChecker(k=3, metric=metric, agg=agg)
ad_checker.fit(X_train)
Expand All @@ -60,9 +60,9 @@ def test_outside_knn_ad(metric, agg):
@pytest.mark.parametrize("agg", ALLOWED_AGGREGATIONS)
def test_knn_different_k_values(metric, agg):
if "binary" in metric:
X_train, X_test = get_data_inside_ad(binarize=True)
X_train, X_test = get_data_inside_ad(n_train=100, n_test=10, binarize=True)
else:
X_train, X_test = get_data_inside_ad()
X_train, X_test = get_data_inside_ad(n_train=100, n_test=10)

# smaller k, stricter check
ad_checker_k1 = KNNADChecker(k=1, metric=metric, agg=agg)
Expand All @@ -84,9 +84,9 @@ def test_knn_different_k_values(metric, agg):
def test_knn_pass_y_train(metric, agg):
# smoke test, should not throw errors
if "binary" in metric:
X_train, _ = get_data_inside_ad(binarize=True)
X_train, _ = get_data_inside_ad(n_train=100, n_test=10, binarize=True)
else:
X_train, _ = get_data_inside_ad()
X_train, _ = get_data_inside_ad(n_train=100, n_test=10)

y_train = np.zeros(len(X_train))
ad_checker = KNNADChecker(k=3, metric=metric, agg=agg)
Expand All @@ -97,9 +97,9 @@ def test_knn_pass_y_train(metric, agg):
@pytest.mark.parametrize("agg", ALLOWED_AGGREGATIONS)
def test_knn_invalid_k(metric, agg):
if "binary" in metric:
X_train, _ = get_data_inside_ad(binarize=True)
X_train, _ = get_data_inside_ad(n_train=100, n_test=10, binarize=True)
else:
X_train, _ = get_data_inside_ad()
X_train, _ = get_data_inside_ad(n_train=100, n_test=10)

with pytest.raises(
ValueError,
Expand All @@ -110,7 +110,7 @@ def test_knn_invalid_k(metric, agg):


def test_knn_invalid_metric():
X_train, _ = get_data_inside_ad()
X_train, _ = get_data_inside_ad(n_train=100)
ad_checker = KNNADChecker(k=3, metric="euclidean")
with pytest.raises(KeyError):
ad_checker.fit(X_train)
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