Final commit

Signed-off-by: Adam Li <adam2392@gmail.com>

sktree/conftest.py

@@ -1,22 +1,10 @@
-# import pytest
+import pytest
 
-
-# def pytest_addoption(parser):
-#     parser.addoption(
-#         "--runslow", action="store_true", default=False, help="run slow tests"
-#     )
+# With the following global module marker,
+# monitoring is disabled by default:
+pytestmark = [pytest.mark.monitor_skip_test]
 
 
 def pytest_configure(config):
     """Set up pytest markers."""
     config.addinivalue_line("markers", "slowtest: mark test as slow")
-
-
-# def pytest_collection_modifyitems(config, items):
-#     if config.getoption("--runslow"):
-#         # --runslow given in cli: do not skip slow tests
-#         return
-#     skip_slow = pytest.mark.skip(reason="need --runslow option to run")
-#     for item in items:
-#         if "slow" in item.keywords:
-#             item.add_marker(skip_slow)

sktree/stats/tests/meson.build

@@ -1,6 +1,7 @@
 python_sources = [
   '__init__.py',
-  'test_forestht.py'
+  'test_forestht.py',
+  'test_coleman.py'
 ]
 
 py3.install_sources(

sktree/stats/tests/test_forestht.py

@@ -372,3 +372,22 @@ def test_small_dataset():
     stat, pvalue = clf.test(X, y, metric="mi")
     assert stat == 0.0
     assert pvalue > 0.05
+
+
+# @pytest.mark.monitor_test
+# def test_memory_usage():
+#     n_samples = 1000
+#     n_features = 5000
+#     X = rng.uniform(size=(n_samples, n_features))
+#     y = rng.integers(0, 2, size=n_samples)  # Binary classification
+
+#     clf = FeatureImportanceForestClassifier(
+#         estimator=HonestForestClassifier(
+#             n_estimators=10, random_state=seed, n_jobs=-1, honest_fraction=0.5
+#         ),
+#         test_size=0.2,
+#         permute_per_tree=False,
+#         sample_dataset_per_tree=False,
+#     )
+
+#     stat, pvalue = clf.test(X, y, covariate_index=[1, 2], metric="mi")