[MAINT] Pytest fixture to ignore internal deprecation warnings (#4043)

* Ignore internal deprecation warnings

* More internal deprecations

* improve warnings and their tests

* fix typo (#4062)

---------

Co-authored-by: Remi Gau <remi_gau@hotmail.com>

nilearn/conftest.py

@@ -112,6 +112,23 @@ def warnings_as_errors():
         yield
 
 
+@pytest.fixture(autouse=True)
+def suppress_specific_warning():
+    """Ignore internal deprecation warnings."""
+    with warnings.catch_warnings():
+        messages = (
+            "The `darkness` parameter will be deprecated.*|"
+            "`legacy_format` will default to `False`.*|"
+            "In release 0.13, this fetcher will return a dictionary.*|"
+        )
+        warnings.filterwarnings(
+            "ignore",
+            message=messages,
+            category=DeprecationWarning,
+        )
+        yield
+
+
 # ------------------------   RNG   ------------------------#
 
 

nilearn/datasets/atlas.py

@@ -138,7 +138,7 @@ def fetch_atlas_difumo(
     labels = pd.read_csv(files_[0])
     labels = labels.rename(columns={c: c.lower() for c in labels.columns})
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         labels = labels.to_records(index=False)
 
     # README
@@ -355,7 +355,7 @@ def fetch_atlas_destrieux_2009(
     params = dict(maps=files_[1], labels=pd.read_csv(files_[0], index_col=0))
 
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         params["labels"] = params["labels"].to_records()
 
     params["description"] = Path(files_[2]).read_text()
@@ -935,7 +935,7 @@ def fetch_coords_power_2011(legacy_format=True):
         columns={c: c.lower() for c in params["rois"].columns}
     )
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         params["rois"] = params["rois"].to_records(index=False)
     return Bunch(**params)
 
@@ -1539,7 +1539,7 @@ def fetch_coords_dosenbach_2010(ordered_regions=True, legacy_format=True):
     )
 
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         params["rois"] = params["rois"].to_records(index=False)
 
     return Bunch(**params)
@@ -1623,7 +1623,7 @@ def fetch_coords_seitzman_2018(ordered_regions=True, legacy_format=True):
         rois = rois.sort_values(by=["network", "y"])
 
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         rois = rois.to_records()
 
     params = dict(

nilearn/datasets/func.py

@@ -899,7 +899,7 @@ def _is_valid_path(path, index, verbose):
         subjects_indices.append(subject_names.index(name))
     csv_data = csv_data.iloc[subjects_indices]
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         csv_data = csv_data.to_records(index=False)
     return Bunch(ext_vars=csv_data, description=fdescr, **files)
 
@@ -1195,7 +1195,7 @@ def fetch_abide_pcp(
         pheno = pheno[:n_subjects]
 
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         pheno = pheno.to_records(index=False)
 
     results = {

nilearn/datasets/struct.py

@@ -852,7 +852,7 @@ def fetch_oasis_vbm(
     fdescr = _get_dataset_descr(dataset_name)
 
     if legacy_format:
-        warnings.warn(_LEGACY_FORMAT_MSG)
+        warnings.warn(_LEGACY_FORMAT_MSG, DeprecationWarning)
         csv_data = csv_data.to_records(index=False)
 
     return Bunch(

nilearn/decoding/tests/test_decoder.py

@@ -265,20 +265,23 @@ def test_wrap_param_grid(param_grid):
     ],
 )
 def test_wrap_param_grid_warning(param_grid, need_wrap):
-    param_name = "alphas"
     expected_warning_substring = "should be a sequence of iterables"
 
-    with warnings.catch_warnings(record=True) as raised_warnings:
-        _wrap_param_grid(param_grid, param_name)
-    warning_messages = [str(warning.message) for warning in raised_warnings]
-
-    found_warning = any(
-        expected_warning_substring in x for x in warning_messages
-    )
-
     if need_wrap:
-        assert found_warning
+        with pytest.warns(UserWarning, match=expected_warning_substring):
+            _wrap_param_grid(param_grid, param_name="alphas")
+
     else:
+        with warnings.catch_warnings(record=True) as raised_warnings:
+            _wrap_param_grid(param_grid, param_name="alphas")
+        warning_messages = [
+            str(warning.message) for warning in raised_warnings
+        ]
+
+        found_warning = any(
+            expected_warning_substring in x for x in warning_messages
+        )
+
         assert not found_warning
 
 

nilearn/decomposition/tests/test_canica.py

@@ -1,7 +1,5 @@
 """Test CanICA."""
 
-import warnings
-
 import numpy as np
 import pytest
 from nibabel import Nifti1Image
@@ -150,18 +148,9 @@ def test_percentile_range(canica_data):
     # stess thresholding via edge case
     canica = CanICA(n_components=edge_case, threshold=float(edge_case))
 
-    with warnings.catch_warnings(record=True) as warning:
+    with pytest.warns(UserWarning, match="obtained a critical threshold"):
         canica.fit(canica_data)
 
-        # ensure a single warning is raised
-        # filter out deprecation warnings
-        warning_messages = [
-            "obtained a critical threshold" in str(w.message)
-            for w in warning
-            if not issubclass(w.category, (DeprecationWarning, FutureWarning))
-        ]
-        assert sum(warning_messages) == 1
-
 
 def test_canica_square_img(mask_img):
     data, components, rng = _make_canica_test_data(n_subjects=8)

nilearn/reporting/tests/test_glm_reporter.py

@@ -1,5 +1,3 @@
-import warnings
-
 import numpy as np
 import pandas as pd
 import pytest
@@ -92,13 +90,9 @@ def test_check_report_dims():
     expected_warning_text = (
         "Report size has invalid values. Using default 1600x800"
     )
-    with warnings.catch_warnings(record=True) as raised_warnings:
+    with pytest.warns(UserWarning, match=expected_warning_text):
         actual_output = glmr._check_report_dims(test_input)
-    raised_warnings_texts = [
-        str(warning_.message) for warning_ in raised_warnings
-    ]
     assert actual_output == expected_output
-    assert expected_warning_text in raised_warnings_texts
 
 
 def test_coerce_to_dict_with_string():

nilearn/tests/test_masking.py

@@ -223,10 +223,8 @@ def test_compute_background_mask(affine_eye):
     # Check that we get a useful warning for empty masks
     mean_image = np.zeros((9, 9, 9))
     mean_image = Nifti1Image(mean_image, affine_eye)
-    with warnings.catch_warnings(record=True) as w:
+    with pytest.warns(MaskWarning, match="Computed an empty mask"):
         compute_background_mask(mean_image)
-    assert len(w) == 1
-    assert isinstance(w[0].message, masking.MaskWarning)
 
 
 def test_compute_brain_mask():