MRG: Avoid pytest 10 warnings in sklearn estimator checks

doc/changes/dev/14283.other.rst

@@ -0,0 +1 @@
+Avoid pytest 10 deprecation warnings when parametrizing scikit-learn estimator checks, by :newcontrib:`Deepesh Sonar`.

doc/changes/names.inc

@@ -101,6 +101,7 @@
 .. _David Julien: https://github.com/Swy7ch
 .. _David Sabbagh: https://github.com/DavidSabbagh
 .. _Deep Kaur: https://github.com/Dpereaptkhamur-13
+.. _Deepesh Sonar: https://github.com/Deepnar
 .. _Denis Engemann: https://denis-engemann.de
 .. _Desislava Petkova: https://github.com/dipetkov
 .. _Dev Parikh: https://github.com/devparikh0506

mne/conftest.py

@@ -220,7 +220,6 @@ def pytest_configure(config: pytest.Config):
     # sklearn
     ignore:Python binding for RankQuantileOptions.*:RuntimeWarning
     ignore:.*The `disp` and `iprint` options of the L-BFGS-B solver.*:DeprecationWarning
-    ignore:Passing a non-Collection iterable to parametrize[.\n]*:
     # matplotlib<->nilearn
     ignore:[\S\s]*You are using the 'agg' matplotlib backend[\S\s]*:UserWarning
     # matplotlib<->pyparsing

mne/decoding/tests/_sklearn.py

@@ -0,0 +1,38 @@
+# Authors: The MNE-Python contributors.
+# License: BSD-3-Clause
+# Copyright the MNE-Python contributors.
+
+from functools import partial
+
+import pytest
+from sklearn.utils.estimator_checks import (
+    parametrize_with_checks as _sklearn_parametrize_with_checks,
+)
+
+
+# TODO VERSION: Remove once scikit-learn 1.10.0 is the minimum supported version
+# scikit-learn/scikit-learn#34448
+def _materialize_parametrize_mark(sklearn_decorator, func):
+    """Materialize generated argvalues in sklearn's pytest mark."""
+    marked_func = sklearn_decorator(func)
+    marks = marked_func.pytestmark
+    if not isinstance(marks, list):
+        marks = [marks]
+    else:
+        marks = list(marks)
+    for index, mark in enumerate(marks):
+        if mark.name == "parametrize":
+            args = (*mark.args[:1], list(mark.args[1]), *mark.args[2:])
+            marks[index] = pytest.mark.parametrize(*args, **mark.kwargs).mark
+            break
+    marked_func.pytestmark = marks
+    return marked_func
+
+
+def _parametrize_with_checks(estimators):
+    """Parametrize estimator checks with pytest-compatible argvalues."""
+    sklearn_decorator = _sklearn_parametrize_with_checks(estimators)
+    return partial(_materialize_parametrize_mark, sklearn_decorator)
+
+
+parametrize_with_checks = _parametrize_with_checks

mne/decoding/tests/test_base.py

@@ -40,7 +40,6 @@
 from sklearn.multiclass import OneVsRestClassifier
 from sklearn.pipeline import make_pipeline
 from sklearn.preprocessing import StandardScaler
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne import EpochsArray, create_info
 from mne.decoding import GeneralizingEstimator, Scaler, TransformerMixin, Vectorizer
@@ -52,6 +51,7 @@
     get_coef,
 )
 from mne.decoding.search_light import SlidingEstimator
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.utils import check_version
 
 

mne/decoding/tests/test_csp.py

@@ -19,11 +19,11 @@
 from sklearn.model_selection import StratifiedKFold, cross_val_score
 from sklearn.pipeline import Pipeline, make_pipeline
 from sklearn.svm import SVC
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne import Epochs, compute_proj_raw, io, pick_types, read_events
 from mne.decoding import CSP, LinearModel, Scaler, SPoC, get_coef, read_csp, read_spoc
 from mne.decoding.csp import _ajd_pham
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.utils import catch_logging, check_version
 
 data_dir = Path(__file__).parents[2] / "io" / "tests" / "data"

mne/decoding/tests/test_ems.py

@@ -11,10 +11,10 @@
 pytest.importorskip("sklearn")
 
 from sklearn.model_selection import StratifiedKFold
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne import Epochs, io, pick_types, read_events
 from mne.decoding import EMS, compute_ems
+from mne.decoding.tests._sklearn import parametrize_with_checks
 
 data_dir = Path(__file__).parents[2] / "io" / "tests" / "data"
 raw_fname = data_dir / "test_raw.fif"

mne/decoding/tests/test_ged.py

@@ -14,7 +14,6 @@
 
 from sklearn.model_selection import ParameterGrid
 from sklearn.utils._testing import assert_allclose
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne import Epochs, compute_rank, create_info, pick_types, read_events
 from mne._fiff.proj import make_eeg_average_ref_proj
@@ -29,6 +28,7 @@
 )
 from mne.decoding._mod_ged import _no_op_mod
 from mne.decoding.base import _GEDTransformer
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.io import read_raw
 
 data_dir = Path(__file__).parents[2] / "io" / "tests" / "data"

mne/decoding/tests/test_receptive_field.py

@@ -13,7 +13,6 @@
 pytest.importorskip("sklearn")
 
 from sklearn.linear_model import Ridge
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne.decoding import ReceptiveField, TimeDelayingRidge
 from mne.decoding.receptive_field import (
@@ -22,6 +21,7 @@
     _delays_to_slice,
     _times_to_delays,
 )
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.decoding.time_delaying_ridge import _compute_corrs, _compute_reg_neighbors
 
 data_dir = Path(__file__).parents[2] / "io" / "tests" / "data"

mne/decoding/tests/test_search_light.py

@@ -20,9 +20,9 @@
 from sklearn.multiclass import OneVsRestClassifier
 from sklearn.pipeline import make_pipeline
 from sklearn.svm import SVC
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne.decoding.search_light import GeneralizingEstimator, SlidingEstimator
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.decoding.transformer import Vectorizer
 from mne.utils import check_version, use_log_level
 

mne/decoding/tests/test_ssd.py

@@ -12,13 +12,13 @@
 pytest.importorskip("sklearn")
 
 from sklearn.pipeline import Pipeline
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne import Epochs, create_info, io, pick_types, read_events
 from mne._fiff.pick import _picks_to_idx
 from mne.decoding import CSP
 from mne.decoding._mod_ged import _get_spectral_ratio
 from mne.decoding.ssd import SSD, read_ssd
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.filter import filter_data
 from mne.time_frequency import psd_array_welch
 

mne/decoding/tests/test_time_frequency.py

@@ -10,8 +10,8 @@
 pytest.importorskip("sklearn")
 
 from sklearn.base import clone
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.decoding.time_frequency import TimeFrequency
 
 

mne/decoding/tests/test_transformer.py

@@ -19,7 +19,6 @@
 from sklearn.kernel_ridge import KernelRidge
 from sklearn.pipeline import make_pipeline
 from sklearn.preprocessing import StandardScaler
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne import Epochs, EpochsArray, create_info, io, pick_types, read_events
 from mne.decoding import (
@@ -31,6 +30,7 @@
     UnsupervisedSpatialFilter,
     Vectorizer,
 )
+from mne.decoding.tests._sklearn import parametrize_with_checks
 from mne.defaults import DEFAULTS
 from mne.utils import use_log_level
 

mne/decoding/tests/test_xdawn.py

@@ -7,9 +7,9 @@
 from numpy.testing import assert_array_almost_equal
 
 pytest.importorskip("sklearn")
-from sklearn.utils.estimator_checks import parametrize_with_checks
 
 from mne.decoding import XdawnTransformer, read_xdawn_transformer
+from mne.decoding.tests._sklearn import parametrize_with_checks
 
 
 @pytest.mark.filterwarnings("ignore:.*Only one sample available.*")