MAINT: Deal with pytest 8.0 (mne-tools#12376)

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>

doc/changes/devel/12376.dependency.rst

@@ -0,0 +1 @@
+For developers, ``pytest>=8.0`` is now required for running unit tests, by `Eric Larson`_.

environment.yml

@@ -6,7 +6,7 @@ dependencies:
   - pip
   - numpy
   - scipy
-  - openblas!=0.3.26  # until https://github.com/conda-forge/scipy-feedstock/pull/268 lands
+  - openblas
   - matplotlib
   - tqdm
   - pooch>=1.5

mne/_fiff/tests/test_meas_info.py

@@ -350,9 +350,10 @@ def test_read_write_info(tmp_path):
 @testing.requires_testing_data
 def test_dir_warning():
     """Test that trying to read a bad filename emits a warning before an error."""
-    with pytest.raises(OSError, match="directory"):
-        with pytest.warns(RuntimeWarning, match="foo"):
-            read_info(ctf_fname)
+    with pytest.raises(OSError, match="directory"), pytest.warns(
+        RuntimeWarning, match="does not conform"
+    ):
+        read_info(ctf_fname)
 
 
 def test_io_dig_points(tmp_path):

mne/beamformer/tests/test_lcmv.py

@@ -589,19 +589,20 @@ def test_make_lcmv_sphere(pick_ori, weight_norm):
     fwd_sphere = mne.make_forward_solution(evoked.info, None, src, sphere)
 
     # Test that we get an error if not reducing rank
-    with pytest.raises(ValueError, match="Singular matrix detected"):
-        with pytest.warns(RuntimeWarning, match="positive semidefinite"):
-            make_lcmv(
-                evoked.info,
-                fwd_sphere,
-                data_cov,
-                reg=0.1,
-                noise_cov=noise_cov,
-                weight_norm=weight_norm,
-                pick_ori=pick_ori,
-                reduce_rank=False,
-                rank="full",
-            )
+    with pytest.raises(
+        ValueError, match="Singular matrix detected"
+    ), _record_warnings(), pytest.warns(RuntimeWarning, match="positive semidefinite"):
+        make_lcmv(
+            evoked.info,
+            fwd_sphere,
+            data_cov,
+            reg=0.1,
+            noise_cov=noise_cov,
+            weight_norm=weight_norm,
+            pick_ori=pick_ori,
+            reduce_rank=False,
+            rank="full",
+        )
 
     # Now let's reduce it
     filters = make_lcmv(

mne/conftest.py

@@ -32,6 +32,7 @@
     _assert_no_instances,
     _check_qt_version,
     _pl,
+    _record_warnings,
     _TempDir,
     numerics,
 )
@@ -801,7 +802,9 @@ def src_volume_labels():
     """Create a 7mm source space with labels."""
     pytest.importorskip("nibabel")
     volume_labels = mne.get_volume_labels_from_aseg(fname_aseg)
-    with pytest.warns(RuntimeWarning, match="Found no usable.*t-vessel.*"):
+    with _record_warnings(), pytest.warns(
+        RuntimeWarning, match="Found no usable.*t-vessel.*"
+    ):
         src = mne.setup_volume_source_space(
             "sample",
             7.0,

mne/export/tests/test_export.py

@@ -78,7 +78,9 @@ def test_export_raw_pybv(tmp_path, meas_date, orig_time, ext):
     raw.set_annotations(annots)
 
     temp_fname = tmp_path / ("test" + ext)
-    with pytest.warns(RuntimeWarning, match="'short' format. Converting"):
+    with _record_warnings(), pytest.warns(
+        RuntimeWarning, match="'short' format. Converting"
+    ):
         raw.export(temp_fname)
     raw_read = read_raw_brainvision(str(temp_fname).replace(".eeg", ".vhdr"))
     assert raw.ch_names == raw_read.ch_names
@@ -301,7 +303,9 @@ def test_export_edf_signal_clipping(tmp_path, physical_range, exceeded_bound):
     raw = read_raw_fif(fname_raw)
     raw.pick(picks=["eeg", "ecog", "seeg"]).load_data()
     temp_fname = tmp_path / "test.edf"
-    with pytest.warns(RuntimeWarning, match=f"The {exceeded_bound}"):
+    with _record_warnings(), pytest.warns(
+        RuntimeWarning, match=f"The {exceeded_bound}"
+    ):
         raw.export(temp_fname, physical_range=physical_range)
     raw_read = read_raw_edf(temp_fname, preload=True)
     assert raw_read.get_data().min() >= physical_range[0]

mne/forward/tests/test_forward.py

@@ -37,7 +37,7 @@
 )
 from mne.io import read_info
 from mne.label import read_label
-from mne.utils import requires_mne, run_subprocess
+from mne.utils import _record_warnings, requires_mne, run_subprocess
 
 data_path = testing.data_path(download=False)
 fname_meeg = data_path / "MEG" / "sample" / "sample_audvis_trunc-meg-eeg-oct-4-fwd.fif"
@@ -230,7 +230,9 @@ def test_apply_forward():
     # Evoked
     evoked = read_evokeds(fname_evoked, condition=0)
     evoked.pick(picks="meg")
-    with pytest.warns(RuntimeWarning, match="only .* positive values"):
+    with _record_warnings(), pytest.warns(
+        RuntimeWarning, match="only .* positive values"
+    ):
         evoked = apply_forward(fwd, stc, evoked.info, start=start, stop=stop)
     data = evoked.data
     times = evoked.times
@@ -248,13 +250,14 @@ def test_apply_forward():
         stc.tmin,
         stc.tstep,
     )
-    with pytest.warns(RuntimeWarning, match="very large"):
+    large_ctx = pytest.warns(RuntimeWarning, match="very large")
+    with large_ctx:
         evoked_2 = apply_forward(fwd, stc_vec, evoked.info)
     assert np.abs(evoked_2.data).mean() > 1e-5
     assert_allclose(evoked.data, evoked_2.data, atol=1e-10)
 
     # Raw
-    with pytest.warns(RuntimeWarning, match="only .* positive values"):
+    with large_ctx, pytest.warns(RuntimeWarning, match="only .* positive values"):
         raw_proj = apply_forward_raw(fwd, stc, evoked.info, start=start, stop=stop)
     data, times = raw_proj[:, :]
 

mne/forward/tests/test_make_forward.py

@@ -44,6 +44,7 @@
 from mne.surface import _get_ico_surface
 from mne.transforms import Transform
 from mne.utils import (
+    _record_warnings,
     catch_logging,
     requires_mne,
     requires_mne_mark,
@@ -198,7 +199,7 @@ def test_magnetic_dipole():
     r0 = coils[0]["rmag"][[0]]
     with pytest.raises(RuntimeError, match="Coil too close"):
         _magnetic_dipole_field_vec(r0, coils[:1])
-    with pytest.warns(RuntimeWarning, match="Coil too close"):
+    with _record_warnings(), pytest.warns(RuntimeWarning, match="Coil too close"):
         fwd = _magnetic_dipole_field_vec(r0, coils[:1], too_close="warning")
     assert not np.isfinite(fwd).any()
     with np.errstate(invalid="ignore"):

mne/io/artemis123/tests/test_artemis123.py

@@ -97,7 +97,9 @@ def test_dev_head_t():
     assert_equal(raw.info["sfreq"], 5000.0)
 
     # test with head loc and digitization
-    with pytest.warns(RuntimeWarning, match="Large difference"):
+    with pytest.warns(RuntimeWarning, match="consistency"), pytest.warns(
+        RuntimeWarning, match="Large difference"
+    ):
         raw = read_raw_artemis123(
             short_HPI_dip_fname, add_head_trans=True, pos_fname=dig_fname
         )

mne/io/brainvision/brainvision.py

@@ -344,9 +344,10 @@ def _read_annotations_brainvision(fname, sfreq="auto"):
 
 def _check_bv_version(header, kind):
     """Check the header version."""
-    _data_err = """\
-    MNE-Python currently only supports %s versions 1.0 and 2.0, got unparsable\
-     %r. Contact MNE-Python developers for support."""
+    _data_err = (
+        "MNE-Python currently only supports %s versions 1.0 and 2.0, got unparsable "
+        "%r. Contact MNE-Python developers for support."
+    )
     # optional space, optional Core or V-Amp, optional Exchange,
     # Version/Header, optional comma, 1/2
     _data_re = (
@@ -355,14 +356,15 @@ def _check_bv_version(header, kind):
 
     assert kind in ("header", "marker")
 
-    if header == "":
-        warn(f"Missing header in {kind} file.")
     for version in range(1, 3):
         this_re = _data_re % (kind.capitalize(), version)
         if re.search(this_re, header) is not None:
             return version
     else:
-        warn(_data_err % (kind, header))
+        if header == "":
+            warn(f"Missing header in {kind} file.")
+        else:
+            warn(_data_err % (kind, header))
 
 
 _orientation_dict = dict(MULTIPLEXED="F", VECTORIZED="C")

mne/io/brainvision/tests/test_brainvision.py

@@ -20,7 +20,7 @@
 from mne.datasets import testing
 from mne.io import read_raw_brainvision, read_raw_fif
 from mne.io.tests.test_raw import _test_raw_reader
-from mne.utils import _stamp_to_dt, object_diff
+from mne.utils import _record_warnings, _stamp_to_dt, object_diff
 
 data_dir = Path(__file__).parent / "data"
 vhdr_path = data_dir / "test.vhdr"
@@ -72,6 +72,8 @@
 #      This should be amend in its own PR.
 montage = data_dir / "test.hpts"
 
+_no_dig = pytest.warns(RuntimeWarning, match="No info on DataPoints")
+
 
 def test_orig_units(recwarn):
     """Test exposure of original channel units."""
@@ -473,7 +475,7 @@ def test_brainvision_data_partially_disabled_hw_filters():
 
 def test_brainvision_data_software_filters_latin1_global_units():
     """Test reading raw Brain Vision files."""
-    with pytest.warns(RuntimeWarning, match="software filter"):
+    with _no_dig, pytest.warns(RuntimeWarning, match="software filter"):
         raw = _test_raw_reader(
             read_raw_brainvision,
             vhdr_fname=vhdr_old_path,
@@ -485,7 +487,7 @@ def test_brainvision_data_software_filters_latin1_global_units():
     assert raw.info["lowpass"] == 50.0
 
     # test sensor name with spaces (#9299)
-    with pytest.warns(RuntimeWarning, match="software filter"):
+    with _no_dig, pytest.warns(RuntimeWarning, match="software filter"):
         raw = _test_raw_reader(
             read_raw_brainvision,
             vhdr_fname=vhdr_old_longname_path,
@@ -566,7 +568,7 @@ def test_brainvision_data():
 
 def test_brainvision_vectorized_data():
     """Test reading BrainVision data files with vectorized data."""
-    with pytest.warns(RuntimeWarning, match="software filter"):
+    with _no_dig, pytest.warns(RuntimeWarning, match="software filter"):
         raw = read_raw_brainvision(vhdr_old_path, preload=True)
 
     assert_array_equal(raw._data.shape, (29, 251))
@@ -611,7 +613,9 @@ def test_brainvision_vectorized_data():
 def test_coodinates_extraction():
     """Test reading of [Coordinates] section if present."""
     # vhdr 2 has a Coordinates section
-    with pytest.warns(RuntimeWarning, match="coordinate information"):
+    with _record_warnings(), pytest.warns(
+        RuntimeWarning, match="coordinate information"
+    ):
         raw = read_raw_brainvision(vhdr_v2_path)
 
     # Basic check of extracted coordinates

mne/io/cnt/tests/test_cnt.py

@@ -19,10 +19,13 @@
 fname_bad_spans = data_path / "CNT" / "test_CNT_events_mne_JWoess_clipped.cnt"
 
 
+_no_parse = pytest.warns(RuntimeWarning, match="Could not parse")
+
+
 @testing.requires_testing_data
 def test_old_data():
     """Test reading raw cnt files."""
-    with pytest.warns(RuntimeWarning, match="number of bytes"):
+    with _no_parse, pytest.warns(RuntimeWarning, match="number of bytes"):
         raw = _test_raw_reader(
             read_raw_cnt, input_fname=fname, eog="auto", misc=["NA1", "LEFT_EAR"]
         )
@@ -50,12 +53,12 @@ def test_new_data():
 @testing.requires_testing_data
 def test_auto_data():
     """Test reading raw cnt files with automatic header."""
-    with pytest.warns(RuntimeWarning):
+    with pytest.warns(RuntimeWarning, match="Omitted 6 annot"):
         raw = read_raw_cnt(input_fname=fname_bad_spans)
 
     assert raw.info["bads"] == ["F8"]
 
-    with pytest.warns(RuntimeWarning, match="number of bytes"):
+    with _no_parse, pytest.warns(RuntimeWarning, match="number of bytes"):
         raw = _test_raw_reader(
             read_raw_cnt, input_fname=fname, eog="auto", misc=["NA1", "LEFT_EAR"]
         )
@@ -74,7 +77,7 @@ def test_auto_data():
 @testing.requires_testing_data
 def test_compare_events_and_annotations():
     """Test comparing annotations and events."""
-    with pytest.warns(RuntimeWarning, match="Could not parse meas date"):
+    with _no_parse, pytest.warns(RuntimeWarning, match="Could not define the num"):
         raw = read_raw_cnt(fname)
     events = np.array(
         [[333, 0, 7], [1010, 0, 7], [1664, 0, 109], [2324, 0, 7], [2984, 0, 109]]

mne/io/ctf/tests/test_ctf.py

@@ -113,7 +113,7 @@ def test_read_ctf(tmp_path):
     shutil.copytree(ctf_eeg_fname, ctf_no_hc_fname)
     remove_base = op.join(ctf_no_hc_fname, op.basename(ctf_fname_catch[:-3]))
     os.remove(remove_base + ".hc")
-    with pytest.warns(RuntimeWarning, match="MISC channel"):
+    with _record_warnings(), pytest.warns(RuntimeWarning, match="MISC channel"):
         pytest.raises(RuntimeError, read_raw_ctf, ctf_no_hc_fname)
     os.remove(remove_base + ".eeg")
     shutil.copy(

mne/io/edf/tests/test_edf.py

@@ -38,6 +38,7 @@
 )
 from mne.io.tests.test_raw import _test_raw_reader
 from mne.tests.test_annotations import _assert_annotations_equal
+from mne.utils import _record_warnings
 
 td_mark = testing._pytest_mark()
 
@@ -408,7 +409,7 @@ def test_no_data_channels():
     annot_2 = raw.annotations
     _assert_annotations_equal(annot, annot_2)
     # only annotations (should warn)
-    with pytest.warns(RuntimeWarning, match="read_annotations"):
+    with _record_warnings(), pytest.warns(RuntimeWarning, match="read_annotations"):
         read_raw_edf(edf_annot_only)
 
 

mne/io/edf/tests/test_gdf.py

@@ -153,7 +153,7 @@ def test_gdf2_data():
 @testing.requires_testing_data
 def test_one_channel_gdf():
     """Test a one-channel GDF file."""
-    with pytest.warns(RuntimeWarning, match="different highpass"):
+    with pytest.warns(RuntimeWarning, match="contain different"):
         ecg = read_raw_gdf(gdf_1ch_path, preload=True)
     assert ecg["ECG"][0].shape == (1, 4500)
     assert 150.0 == ecg.info["sfreq"]

mne/io/eeglab/tests/test_eeglab.py

@@ -28,7 +28,7 @@
 from mne.io.eeglab._eeglab import _readmat
 from mne.io.eeglab.eeglab import _dol_to_lod, _get_montage_information
 from mne.io.tests.test_raw import _test_raw_reader
-from mne.utils import Bunch, _check_pymatreader_installed
+from mne.utils import Bunch, _check_pymatreader_installed, _record_warnings
 
 base_dir = testing.data_path(download=False) / "EEGLAB"
 raw_fname_mat = base_dir / "test_raw.set"
@@ -140,7 +140,9 @@ def test_io_set_raw_more(tmp_path):
     shutil.copyfile(
         base_dir / "test_raw.fdt", negative_latency_fname.with_suffix(".fdt")
     )
-    with pytest.warns(RuntimeWarning, match="has a sample index of -1."):
+    with _record_warnings(), pytest.warns(
+        RuntimeWarning, match="has a sample index of -1."
+    ):
         read_raw_eeglab(input_fname=negative_latency_fname, preload=True)
 
     # test negative event latencies
@@ -163,7 +165,7 @@ def test_io_set_raw_more(tmp_path):
         oned_as="row",
     )
     with pytest.raises(ValueError, match="event sample index is negative"):
-        with pytest.warns(RuntimeWarning, match="has a sample index of -1."):
+        with _record_warnings():
             read_raw_eeglab(input_fname=negative_latency_fname, preload=True)
 
     # test overlapping events
@@ -350,9 +352,9 @@ def test_io_set_raw_more(tmp_path):
 def test_io_set_epochs(fnames):
     """Test importing EEGLAB .set epochs files."""
     epochs_fname, epochs_fname_onefile = fnames
-    with pytest.warns(RuntimeWarning, match="multiple events"):
+    with _record_warnings(), pytest.warns(RuntimeWarning, match="multiple events"):
         epochs = read_epochs_eeglab(epochs_fname)
-    with pytest.warns(RuntimeWarning, match="multiple events"):
+    with _record_warnings(), pytest.warns(RuntimeWarning, match="multiple events"):
         epochs2 = read_epochs_eeglab(epochs_fname_onefile)
     # one warning for each read_epochs_eeglab because both files have epochs
     # associated with multiple events

mne/io/eyelink/tests/test_eyelink.py

@@ -12,6 +12,7 @@
 from mne.io import read_raw_eyelink
 from mne.io.eyelink._utils import _adjust_times, _find_overlaps
 from mne.io.tests.test_raw import _test_raw_reader
+from mne.utils import _record_warnings
 
 pd = pytest.importorskip("pandas")
 
@@ -255,7 +256,9 @@ def test_multi_block_misc_channels(fname, tmp_path):
     out_file = tmp_path / "tmp_eyelink.asc"
     _simulate_eye_tracking_data(fname, out_file)
 
-    with pytest.warns(RuntimeWarning, match="Raw eyegaze coordinates"):
+    with _record_warnings(), pytest.warns(
+        RuntimeWarning, match="Raw eyegaze coordinates"
+    ):
         raw = read_raw_eyelink(out_file, apply_offsets=True)
 
     chs_in_file = [