WIP add integration test for py-MUVR feature selection

tests/test_feature_selector_integration.py

@@ -0,0 +1,43 @@
+import pytest
+
+from sklearn.datasets import make_classification
+from sklearn.svm import SVC
+
+from py_muvr.feature_selector import FeatureSelector
+
+
+@pytest.fixture()
+def artificial_data():
+    return make_classification(
+        n_features=10,
+        n_informative=2,
+        n_redundant=2,
+        n_samples=100,
+        n_classes=2,
+        random_state=0,
+        shuffle=False,
+    )
+
+
+@pytest.mark.parametrize(
+    "estimator", ["RFC", "XGBC", "PLSC", SVC(kernel="linear", random_state=1)]
+)
+def test_feature_selection_artificial_data_plsc(artificial_data, estimator):
+
+    fs = FeatureSelector(
+        n_outer=5,
+        n_repetitions=5,
+        random_state=0,
+        estimator=estimator,
+        metric="accuracy",
+        features_dropout_rate=0.05,
+    )
+
+    X, y = artificial_data
+    fitted_fs = fs.fit(X, y)
+    selected_features = fitted_fs._selected_features
+
+    assert set(selected_features["min"]) == set([0, 1])  # first two features
+    assert set(selected_features["max"]) == set(
+        [0, 1, 2, 3]
+    )  # thirds and fourth feature