Merge branch 'main' of https://github.com/mne-tools/mne-python into e…

…poch_reject

.github/workflows/tests.yml

@@ -116,7 +116,7 @@ jobs:
         run: MNE_SKIP_TESTING_DATASET_TESTS=true pytest -m "not (ultraslowtest or pgtest)" --tb=short --cov=mne --cov-report xml -vv -rfE mne/
         if: matrix.kind == 'minimal'
       - run: ./tools/get_testing_version.sh
-      - uses: actions/cache@v3
+      - uses: actions/cache@v4
         with:
           key: ${{ env.TESTING_VERSION }}
           path: ~/mne_data

doc/changes/devel/12380.bugfix.rst

@@ -0,0 +1 @@
+Fix bug where :func:`mne.preprocessing.compute_proj_ecg` and :func:`mne.preprocessing.compute_proj_eog` could modify the default ``reject`` and ``flat`` arguments on multiple calls based on channel types present, by `Eric Larson`_.

doc/changes/devel/12383.newfeature.rst

@@ -0,0 +1 @@
+Add ability to detect minima peaks found in :class:`mne.Evoked` if data is all positive and maxima if data is all negative.

doc/conf.py

@@ -1344,6 +1344,10 @@ def reset_warnings(gallery_conf, fname):
         r"ast\.NameConstant is deprecated and will be removed in Python 3\.14",
         # pooch
         r"Python 3\.14 will, by default, filter extracted tar archives.*",
+        # seaborn
+        r"DataFrameGroupBy\.apply operated on the grouping columns.*",
+        # pandas
+        r"\nPyarrow will become a required dependency of pandas.*",
     ):
         warnings.filterwarnings(  # deal with other modules having bad imports
             "ignore", message=".*%s.*" % key, category=DeprecationWarning
@@ -1382,6 +1386,7 @@ def reset_warnings(gallery_conf, fname):
         r"iteritems is deprecated.*Use \.items instead\.",
         "is_categorical_dtype is deprecated.*",
         "The default of observed=False.*",
+        "When grouping with a length-1 list-like.*",
     ):
         warnings.filterwarnings(
             "ignore",

environment.yml

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

examples/time_frequency/time_frequency_erds.py

@@ -50,6 +50,7 @@
 # %%
 # First, we load and preprocess the data. We use runs 6, 10, and 14 from
 # subject 1 (these runs contains hand and feet motor imagery).
+
 fnames = eegbci.load_data(subject=1, runs=(6, 10, 14))
 raw = concatenate_raws([read_raw_edf(f, preload=True) for f in fnames])
 
@@ -59,6 +60,7 @@
 
 # %%
 # Now we can create 5-second epochs around events of interest.
+
 tmin, tmax = -1, 4
 event_ids = dict(hands=2, feet=3)  # map event IDs to tasks
 

mne/_fiff/open.py

@@ -268,7 +268,7 @@ def show_fiff(
     return out
 
 
-def _find_type(value, fmts=["FIFF_"], exclude=["FIFF_UNIT"]):
+def _find_type(value, fmts=("FIFF_",), exclude=("FIFF_UNIT",)):
     """Find matching values."""
     value = int(value)
     vals = [

mne/_fiff/pick.py

@@ -259,7 +259,7 @@ def channel_type(info, idx):
 
 
 @verbose
-def pick_channels(ch_names, include, exclude=[], ordered=None, *, verbose=None):
+def pick_channels(ch_names, include, exclude=(), ordered=None, *, verbose=None):
     """Pick channels by names.
 
     Returns the indices of ``ch_names`` in ``include`` but not in ``exclude``.
@@ -706,7 +706,7 @@ def _has_kit_refs(info, picks):
 
 @verbose
 def pick_channels_forward(
-    orig, include=[], exclude=[], ordered=None, copy=True, *, verbose=None
+    orig, include=(), exclude=(), ordered=None, copy=True, *, verbose=None
 ):
     """Pick channels from forward operator.
 
@@ -797,8 +797,8 @@ def pick_types_forward(
     seeg=False,
     ecog=False,
     dbs=False,
-    include=[],
-    exclude=[],
+    include=(),
+    exclude=(),
 ):
     """Pick by channel type and names from a forward operator.
 
@@ -893,7 +893,7 @@ def channel_indices_by_type(info, picks=None):
 
 @verbose
 def pick_channels_cov(
-    orig, include=[], exclude="bads", ordered=None, copy=True, *, verbose=None
+    orig, include=(), exclude="bads", ordered=None, copy=True, *, verbose=None
 ):
     """Pick channels from covariance matrix.
 

mne/channels/tests/test_channels.py

@@ -438,8 +438,8 @@ def test_1020_selection():
     raw = raw.rename_channels(dict(zip(raw.ch_names, montage.ch_names)))
     raw.set_montage(montage)
 
-    for input in ("a_string", 100, raw, [1, 2]):
-        pytest.raises(TypeError, make_1020_channel_selections, input)
+    for input_ in ("a_string", 100, raw, [1, 2]):
+        pytest.raises(TypeError, make_1020_channel_selections, input_)
 
     sels = make_1020_channel_selections(raw.info)
     # are all frontal channels placed before all occipital channels?

mne/commands/mne_setup_source_space.py

@@ -120,7 +120,7 @@ def run():
     subjects_dir = options.subjects_dir
     spacing = options.spacing
     ico = options.ico
-    oct = options.oct
+    oct_ = options.oct
     surface = options.surface
     n_jobs = options.n_jobs
     add_dist = options.add_dist
@@ -130,20 +130,22 @@ def run():
     overwrite = True if options.overwrite is not None else False
 
     # Parse source spacing option
-    spacing_options = [ico, oct, spacing]
+    spacing_options = [ico, oct_, spacing]
     n_options = len([x for x in spacing_options if x is not None])
+    use_spacing = "oct6"
     if n_options > 1:
         raise ValueError("Only one spacing option can be set at the same time")
     elif n_options == 0:
         # Default to oct6
-        use_spacing = "oct6"
+        pass
     elif n_options == 1:
         if ico is not None:
             use_spacing = "ico" + str(ico)
-        elif oct is not None:
-            use_spacing = "oct" + str(oct)
+        elif oct_ is not None:
+            use_spacing = "oct" + str(oct_)
         elif spacing is not None:
             use_spacing = spacing
+    del ico, oct_, spacing
     # Generate filename
     if fname is None:
         if subject_to is None:

mne/cov.py

@@ -310,7 +310,7 @@ def __iadd__(self, cov):
     def plot(
         self,
         info,
-        exclude=[],
+        exclude=(),
         colorbar=True,
         proj=False,
         show_svd=True,

mne/datasets/sleep_physionet/tests/test_physionet.py

@@ -46,12 +46,12 @@ def _check_mocked_function_calls(mocked_func, call_fname_hash_pairs, base_path):
     # order.
     for idx, current in enumerate(call_fname_hash_pairs):
         _, call_kwargs = mocked_func.call_args_list[idx]
-        hash_type, hash = call_kwargs["known_hash"].split(":")
+        hash_type, hash_ = call_kwargs["known_hash"].split(":")
         assert call_kwargs["url"] == _get_expected_url(current["name"]), idx
         assert Path(call_kwargs["path"], call_kwargs["fname"]) == _get_expected_path(
             base_path, current["name"]
         )
-        assert hash == current["hash"]
+        assert hash_ == current["hash"]
         assert hash_type == "sha1"
 
 

mne/decoding/tests/test_ssd.py

@@ -19,7 +19,7 @@
 
 
 def simulate_data(
-    freqs_sig=[9, 12],
+    freqs_sig=(9, 12),
     n_trials=100,
     n_channels=20,
     n_samples=500,

mne/epochs.py

@@ -3684,7 +3684,7 @@ def _is_good(
     reject,
     flat,
     full_report=False,
-    ignore_chs=[],
+    ignore_chs=(),
     verbose=None,
 ):
     """Test if data segment e is good according to reject and flat.
@@ -4685,7 +4685,7 @@ def make_fixed_length_epochs(
     reject_by_annotation=True,
     proj=True,
     overlap=0.0,
-    id=1,
+    id=1,  # noqa: A002
     verbose=None,
 ):
     """Divide continuous raw data into equal-sized consecutive epochs.

mne/event.py

@@ -925,7 +925,13 @@ def shift_time_events(events, ids, tshift, sfreq):
 
 @fill_doc
 def make_fixed_length_events(
-    raw, id=1, start=0, stop=None, duration=1.0, first_samp=True, overlap=0.0
+    raw,
+    id=1,  # noqa: A002
+    start=0,
+    stop=None,
+    duration=1.0,
+    first_samp=True,
+    overlap=0.0,
 ):
     """Make a set of :term:`events` separated by a fixed duration.
 

mne/evoked.py

@@ -549,7 +549,7 @@ def plot_topo(
         scalings=None,
         title=None,
         proj=False,
-        vline=[0.0],
+        vline=(0.0,),
         fig_background=None,
         merge_grads=False,
         legend=True,
@@ -914,6 +914,8 @@ def get_peak(
         time_as_index=False,
         merge_grads=False,
         return_amplitude=False,
+        *,
+        strict=True,
     ):
         """Get location and latency of peak amplitude.
 
@@ -941,6 +943,12 @@ def get_peak(
             If True, return also the amplitude at the maximum response.
 
             .. versionadded:: 0.16
+        strict : bool
+            If True, raise an error if values are all positive when detecting
+            a minimum (mode='neg'), or all negative when detecting a maximum
+            (mode='pos'). Defaults to True.
+
+            .. versionadded:: 1.7
 
         Returns
         -------
@@ -1032,7 +1040,14 @@ def get_peak(
             data, _ = _merge_ch_data(data, ch_type, [])
             ch_names = [ch_name[:-1] + "X" for ch_name in ch_names[::2]]
 
-        ch_idx, time_idx, max_amp = _get_peak(data, self.times, tmin, tmax, mode)
+        ch_idx, time_idx, max_amp = _get_peak(
+            data,
+            self.times,
+            tmin,
+            tmax,
+            mode,
+            strict=strict,
+        )
 
         out = (ch_names[ch_idx], time_idx if time_as_index else self.times[time_idx])
 
@@ -1949,7 +1964,7 @@ def _write_evokeds(fname, evoked, check=True, *, on_mismatch="raise", overwrite=
         end_block(fid, FIFF.FIFFB_MEAS)
 
 
-def _get_peak(data, times, tmin=None, tmax=None, mode="abs"):
+def _get_peak(data, times, tmin=None, tmax=None, mode="abs", *, strict=True):
     """Get feature-index and time of maximum signal from 2D array.
 
     Note. This is a 'getter', not a 'finder'. For non-evoked type
@@ -1970,6 +1985,10 @@ def _get_peak(data, times, tmin=None, tmax=None, mode="abs"):
         values will be considered. If 'neg' only negative values will
         be considered. If 'abs' absolute values will be considered.
         Defaults to 'abs'.
+    strict : bool
+        If True, raise an error if values are all positive when detecting
+        a minimum (mode='neg'), or all negative when detecting a maximum
+        (mode='pos'). Defaults to True.
 
     Returns
     -------
@@ -2008,12 +2027,12 @@ def _get_peak(data, times, tmin=None, tmax=None, mode="abs"):
 
     maxfun = np.argmax
     if mode == "pos":
-        if not np.any(data[~mask] > 0):
+        if strict and not np.any(data[~mask] > 0):
             raise ValueError(
                 "No positive values encountered. Cannot " "operate in pos mode."
             )
     elif mode == "neg":
-        if not np.any(data[~mask] < 0):
+        if strict and not np.any(data[~mask] < 0):
             raise ValueError(
                 "No negative values encountered. Cannot " "operate in neg mode."
             )

mne/export/_export.py

@@ -211,9 +211,9 @@ def _infer_check_export_fmt(fmt, fname, supported_formats):
 
     if fmt not in supported_formats:
         supported = []
-        for format, extensions in supported_formats.items():
+        for supp_format, extensions in supported_formats.items():
             ext_str = ", ".join(f"*.{ext}" for ext in extensions)
-            supported.append(f"{format} ({ext_str})")
+            supported.append(f"{supp_format} ({ext_str})")
 
         supported_str = ", ".join(supported)
         raise ValueError(

mne/gui/_coreg.py

@@ -1907,7 +1907,7 @@ def _configure_dock(self):
             func=self._save_trans,
             tooltip="Save the transform file to disk",
             layout=save_trans_layout,
-            filter="Head->MRI transformation (*-trans.fif *_trans.fif)",
+            filter_="Head->MRI transformation (*-trans.fif *_trans.fif)",
             initial_directory=str(Path(self._info_file).parent),
         )
         self._widgets["load_trans"] = self._renderer._dock_add_file_button(
@@ -1916,7 +1916,7 @@ def _configure_dock(self):
             func=self._load_trans,
             tooltip="Load the transform file from disk",
             layout=save_trans_layout,
-            filter="Head->MRI transformation (*-trans.fif *_trans.fif)",
+            filter_="Head->MRI transformation (*-trans.fif *_trans.fif)",
             initial_directory=str(Path(self._info_file).parent),
         )
         self._renderer._layout_add_widget(trans_layout, save_trans_layout)

mne/inverse_sparse/mxne_optim.py

@@ -799,7 +799,7 @@ def __call__(self, x):  # noqa: D105
         else:
             return np.hstack([x @ op for op in self.ops]) / np.sqrt(self.n_dicts)
 
-    def norm(self, z, ord=2):
+    def norm(self, z, ord=2):  # noqa: A002
         """Squared L2 norm if ord == 2 and L1 norm if order == 1."""
         if ord not in (1, 2):
             raise ValueError(

mne/io/bti/bti.py

@@ -78,7 +78,7 @@ def __init__(self, target):
     def __enter__(self):  # noqa: D105
         return self.target
 
-    def __exit__(self, type, value, tb):  # noqa: D105
+    def __exit__(self, exception_type, value, tb):  # noqa: D105
         pass
 
 

mne/io/curry/curry.py

@@ -197,10 +197,10 @@ def _read_curry_parameters(fname):
             if any(var_name in line for var_name in var_names):
                 key, val = line.replace(" ", "").replace("\n", "").split("=")
                 param_dict[key.lower().replace("_", "")] = val
-            for type in CHANTYPES:
-                if "DEVICE_PARAMETERS" + CHANTYPES[type] + " START" in line:
+            for key, type_ in CHANTYPES.items():
+                if f"DEVICE_PARAMETERS{type_} START" in line:
                     data_unit = next(fid)
-                    unit_dict[type] = (
+                    unit_dict[key] = (
                         data_unit.replace(" ", "").replace("\n", "").split("=")[-1]
                     )
 

mne/io/edf/edf.py

@@ -1454,7 +1454,9 @@ def _read_gdf_header(fname, exclude, include=None):
 
 
 def _check_stim_channel(
-    stim_channel, ch_names, tal_ch_names=["EDF Annotations", "BDF Annotations"]
+    stim_channel,
+    ch_names,
+    tal_ch_names=("EDF Annotations", "BDF Annotations"),
 ):
     """Check that the stimulus channel exists in the current datafile."""
     DEFAULT_STIM_CH_NAMES = ["status", "trigger"]

mne/io/fieldtrip/tests/helpers.py

@@ -185,7 +185,7 @@ def get_epochs(system):
         else:
             event_id = [int(cfg_local["eventvalue"])]
 
-        event_id = [id for id in event_id if id in events[:, 2]]
+        event_id = [id_ for id_ in event_id if id_ in events[:, 2]]
 
     epochs = mne.Epochs(
         raw_data,