Merge remote-tracking branch 'upstream' into metadata

doc/changes/devel.rst

@@ -38,6 +38,7 @@ Enhancements
 - Add support for writing forward solutions to HDF5 and convenience function :meth:`mne.Forward.save` (:gh:`12036` by `Eric Larson`_)
 - Refactored internals of :func:`mne.read_annotations` (:gh:`11964` by `Paul Roujansky`_)
 - Add support for drawing MEG sensors in :ref:`mne coreg` (:gh:`12098` by `Eric Larson`_)
+- Bad channels are now colored gray in addition to being dashed when spatial colors are used in :func:`mne.viz.plot_evoked` and related functions (:gh:`12142` by `Eric Larson`_)
 - By default MNE-Python creates matplotlib figures with ``layout='constrained'`` rather than the default ``layout='tight'`` (:gh:`12050`, :gh:`12103` by `Mathieu Scheltienne`_ and `Eric Larson`_)
 - Enhance :func:`~mne.viz.plot_evoked_field` with a GUI that has controls for time, colormap, and contour lines (:gh:`11942` by `Marijn van Vliet`_)
 - Add :class:`mne.viz.ui_events.UIEvent` linking for interactive colorbars, allowing users to link figures and change the colormap and limits interactively. This supports :func:`~mne.viz.plot_evoked_topomap`, :func:`~mne.viz.plot_ica_components`, :func:`~mne.viz.plot_tfr_topomap`, :func:`~mne.viz.plot_projs_topomap`, :meth:`~mne.Evoked.plot_image`, and :meth:`~mne.Epochs.plot_image` (:gh:`12057` by `Santeri Ruuskanen`_)
@@ -72,6 +73,7 @@ Bugs
 - Fix :func:`~mne.viz.plot_volume_source_estimates` with :class:`~mne.VolSourceEstimate` which include a list of vertices (:gh:`12025` by `Mathieu Scheltienne`_)
 - Add support for non-ASCII characters in Annotations, Evoked comments, etc when saving to FIFF format (:gh:`12080` by `Daniel McCloy`_)
 - Correctly handle passing ``"eyegaze"`` or ``"pupil"`` to :meth:`mne.io.Raw.pick` (:gh:`12019` by `Scott Huberty`_)
+- Fix bug with :func:`mne.time_frequency.Spectrum.plot` and related functions where bad channels were not marked (:gh:`12142` by `Eric Larson`_)
 - Fix bug with :func:`~mne.viz.plot_raw` where changing ``MNE_BROWSER_BACKEND`` via :func:`~mne.set_config` would have no effect within a Python session (:gh:`12078` by `Santeri Ruuskanen`_)
 - Improve handling of ``method`` argument in the channel interpolation function to support :class:`str` and raise helpful error messages (:gh:`12113` by `Mathieu Scheltienne`_)
 - Fix combination of ``DIN`` event channels into a single synthetic trigger channel ``STI 014`` by the MFF reader of :func:`mne.io.read_raw_egi` (:gh:`12122` by `Mathieu Scheltienne`_)

doc/development/governance.rst

@@ -69,7 +69,7 @@ BDFL
 ----
 
 The Project will have a BDFL (Benevolent Dictator for Life), who is currently
-Alexandre Gramfort. As Dictator, the BDFL has the authority to make all final
+Daniel McCloy. As Dictator, the BDFL has the authority to make all final
 decisions for The Project. As Benevolent, the BDFL, in practice, chooses to
 defer that authority to the consensus of the community discussion channels and
 the Steering Council (see below). It is expected, and in the past has been the

doc/overview/people.rst

@@ -22,8 +22,6 @@ Steering Council
 * `Daniel McCloy`_
 * `Denis Engemann`_
 * `Eric Larson`_
-* `Guillaume Favelier`_
-* `Luke Bloy`_
 * `Mainak Jas`_
 * `Marijn van Vliet`_
 * `Mathieu Scheltienne`_

examples/preprocessing/eeg_bridging.py

@@ -10,7 +10,7 @@
 electrode connects with the gel conducting signal from another electrode
 "bridging" the two signals. This is undesirable because the signals from the
 two (or more) electrodes are not as independent as they would otherwise be;
-they are very similar to each other introducting additional
+they are very similar to each other introducing additional
 spatial smearing. An algorithm has been developed to detect electrode
 bridging :footcite:`TenkeKayser2001`, which has been implemented in EEGLAB
 :footcite:`DelormeMakeig2004`. Unfortunately, there is not a lot to be

mne/conftest.py

@@ -92,8 +92,6 @@ def pytest_configure(config):
     # Fixtures
     for fixture in (
         "matplotlib_config",
-        "close_all",
-        "check_verbose",
         "qt_config",
         "protect_config",
     ):
@@ -268,10 +266,7 @@ def matplotlib_config():
     # functionality)
     plt.ioff()
     plt.rcParams["figure.dpi"] = 100
-    try:
-        plt.rcParams["figure.raise_window"] = False
-    except KeyError:  # MPL < 3.3
-        pass
+    plt.rcParams["figure.raise_window"] = False
 
     # Make sure that we always reraise exceptions in handlers
     orig = cbook.CallbackRegistry

mne/epochs.py

@@ -4114,12 +4114,13 @@ def _concatenate_epochs(
     event_id = deepcopy(out.event_id)
     selection = out.selection
     # offset is the last epoch + tmax + 10 second
-    shift = int((10 + tmax) * out.info["sfreq"])
+    shift = np.int64((10 + tmax) * out.info["sfreq"])
     # Allow reading empty epochs (ToDo: Maybe not anymore in the future)
     if out._allow_empty:
         events_offset = 0
     else:
         events_offset = int(np.max(events[0][:, 0])) + shift
+    events_offset = np.int64(events_offset)
     events_overflow = False
     warned = False
     for ii, epochs in enumerate(epochs_list[1:], 1):

mne/io/bti/read.py

@@ -48,12 +48,12 @@ def read_int8(fid):
 
 def read_uint16(fid):
     """Read unsigned 16bit integer from bti file."""
-    return _unpack_simple(fid, ">u2", np.uint16)
+    return _unpack_simple(fid, ">u2", np.uint32)
 
 
 def read_int16(fid):
     """Read 16bit integer from bti file."""
-    return _unpack_simple(fid, ">i2", np.int16)
+    return _unpack_simple(fid, ">i2", np.int32)
 
 
 def read_uint32(fid):
@@ -88,7 +88,13 @@ def read_double(fid):
 
 def read_int16_matrix(fid, rows, cols):
     """Read 16bit integer matrix from bti file."""
-    return _unpack_matrix(fid, rows, cols, dtype=">i2", out_dtype=np.int16)
+    return _unpack_matrix(
+        fid,
+        rows,
+        cols,
+        dtype=">i2",
+        out_dtype=np.int32,
+    )
 
 
 def read_float_matrix(fid, rows, cols):

mne/io/ctf/res4.py

@@ -43,7 +43,7 @@ def _read_ustring(fid, n_bytes):
 
 def _read_int2(fid):
     """Read int from short."""
-    return np.fromfile(fid, ">i2", 1)[0]
+    return _auto_cast(np.fromfile(fid, ">i2", 1)[0])
 
 
 def _read_int(fid):
@@ -208,6 +208,9 @@ def _read_res4(dsdir):
             coil["area"] *= 1e-4
         # convert to dict
         chs = [dict(zip(chs.dtype.names, x)) for x in chs]
+        for ch in chs:
+            for key, val in ch.items():
+                ch[key] = _auto_cast(val)
         res["chs"] = chs
         for k in range(res["nchan"]):
             res["chs"][k]["ch_name"] = res["ch_names"][k]
@@ -216,3 +219,15 @@ def _read_res4(dsdir):
         _read_comp_coeff(fid, res)
     logger.info("    res4 data read.")
     return res
+
+
+def _auto_cast(x):
+    # Upcast scalars
+    if isinstance(x, np.ScalarType):
+        if x.dtype.kind == "i":
+            if x.dtype != np.int64:
+                x = x.astype(np.int64)
+        elif x.dtype.kind == "f":
+            if x.dtype != np.float64:
+                x = x.astype(np.float64)
+    return x

mne/io/edf/edf.py

@@ -1106,7 +1106,7 @@ def _read_gdf_header(fname, exclude, include=None):
                     "Header information is incorrect for record length. "
                     "Default record length set to 1."
                 )
-            nchan = np.fromfile(fid, UINT32, 1)[0]
+            nchan = int(np.fromfile(fid, UINT32, 1)[0])
             channels = list(range(nchan))
             ch_names = [_edf_str(fid.read(16)).strip() for ch in channels]
             exclude = _find_exclude_idx(ch_names, exclude, include)
@@ -1177,7 +1177,7 @@ def _read_gdf_header(fname, exclude, include=None):
             fid.seek(etp)
             etmode = np.fromfile(fid, UINT8, 1)[0]
             if etmode in (1, 3):
-                sr = np.fromfile(fid, UINT8, 3)
+                sr = np.fromfile(fid, UINT8, 3).astype(np.uint32)
                 event_sr = sr[0]
                 for i in range(1, len(sr)):
                     event_sr = event_sr + sr[i] * 2 ** (i * 8)
@@ -1297,7 +1297,7 @@ def _read_gdf_header(fname, exclude, include=None):
                     "Default record length set to 1."
                 )
 
-            nchan = np.fromfile(fid, UINT16, 1)[0]
+            nchan = int(np.fromfile(fid, UINT16, 1)[0])
             fid.seek(2, 1)  # 2bytes reserved
 
             # Channels (variable header)

mne/io/egi/egi.py

@@ -29,7 +29,7 @@ def _read_header(fid):
         )
 
     def my_fread(*x, **y):
-        return np.fromfile(*x, **y)[0]
+        return int(np.fromfile(*x, **y)[0])
 
     info = dict(
         version=version,
@@ -57,8 +57,8 @@ def my_fread(*x, **y):
             dict(
                 n_categories=0,
                 n_segments=1,
-                n_samples=np.fromfile(fid, ">i4", 1)[0],
-                n_events=np.fromfile(fid, ">i2", 1)[0],
+                n_samples=int(np.fromfile(fid, ">i4", 1)[0]),
+                n_events=int(np.fromfile(fid, ">i2", 1)[0]),
                 event_codes=[],
                 category_names=[],
                 category_lengths=[],

mne/io/egi/egimff.py

@@ -79,7 +79,7 @@ def _read_mff_header(filepath):
         # by what we need to (e.g., a sample rate of 500 means we can multiply
         # by 1 and divide by 2 rather than multiplying by 500 and dividing by
         # 1000)
-        numerator = signal_blocks["sfreq"]
+        numerator = int(signal_blocks["sfreq"])
         denominator = 1000
         this_gcd = math.gcd(numerator, denominator)
         numerator = numerator // this_gcd

mne/io/nihon/nihon.py

@@ -207,7 +207,7 @@ def _read_nihon_header(fname):
                 t_datablock["address"] = t_data_address
 
                 fid.seek(t_data_address + 0x26)
-                t_n_channels = np.fromfile(fid, np.uint8, 1)[0]
+                t_n_channels = np.fromfile(fid, np.uint8, 1)[0].astype(np.int64)
                 t_datablock["n_channels"] = t_n_channels
 
                 t_channels = []
@@ -219,14 +219,14 @@ def _read_nihon_header(fname):
                 t_datablock["channels"] = t_channels
 
                 fid.seek(t_data_address + 0x1C)
-                t_record_duration = np.fromfile(fid, np.uint32, 1)[0]
+                t_record_duration = np.fromfile(fid, np.uint32, 1)[0].astype(np.int64)
                 t_datablock["duration"] = t_record_duration
 
                 fid.seek(t_data_address + 0x1A)
                 sfreq = np.fromfile(fid, np.uint16, 1)[0] & 0x3FFF
-                t_datablock["sfreq"] = sfreq
+                t_datablock["sfreq"] = sfreq.astype(np.int64)
 
-                t_datablock["n_samples"] = int(t_record_duration * sfreq / 10)
+                t_datablock["n_samples"] = np.int64(t_record_duration * sfreq // 10)
                 t_controlblock["datablocks"].append(t_datablock)
             controlblocks.append(t_controlblock)
         header["controlblocks"] = controlblocks

mne/io/nsx/nsx.py

@@ -365,7 +365,7 @@ def _get_hdr_info(fname, stim_channel=True, eog=None, misc=None):
 
     stim_channel_idxs, _ = _check_stim_channel(stim_channel, ch_names)
 
-    nchan = nsx_info["channel_count"]
+    nchan = int(nsx_info["channel_count"])
     logger.info("Setting channel info structure...")
     chs = list()
     pick_mask = np.ones(len(ch_names))

mne/preprocessing/realign.py

@@ -28,8 +28,9 @@ def realign_raw(raw, other, t_raw, t_other, verbose=None):
         The second raw instance. It will be resampled to match ``raw``.
     t_raw : array-like, shape (n_events,)
         The times of shared events in ``raw`` relative to ``raw.times[0]`` (0).
-        Typically these could be events on some TTL channel like
-        ``find_events(raw)[:, 0] - raw.first_samp``.
+        Typically these could be events on some TTL channel such as::
+
+            find_events(raw)[:, 0] / raw.info["sfreq"] - raw.first_time
     t_other : array-like, shape (n_events,)
         The times of shared events in ``other`` relative to ``other.times[0]``.
     %(verbose)s
@@ -92,11 +93,11 @@ def realign_raw(raw, other, t_raw, t_other, verbose=None):
         logger.info(f"Cropping {zero_ord:0.3f} s from the start of raw")
         raw.crop(zero_ord, None)
         t_raw -= zero_ord
-    else:  # need to crop start of other to match raw
-        t_crop = zero_ord / first_ord
+    elif zero_ord < 0:  # need to crop start of other to match raw
+        t_crop = -zero_ord / first_ord
         logger.info(f"Cropping {t_crop:0.3f} s from the start of other")
-        other.crop(-t_crop, None)
-        t_other += t_crop
+        other.crop(t_crop, None)
+        t_other -= t_crop
 
     # 3. Resample data using the first-order term
     nan_ch_names = [

mne/report/tests/test_report.py

@@ -877,6 +877,8 @@ def test_survive_pickle(tmp_path):
 def test_manual_report_2d(tmp_path, invisible_fig):
     """Simulate user manually creating report by adding one file at a time."""
     pytest.importorskip("sklearn")
+    pytest.importorskip("pandas")
+
     from sklearn.exceptions import ConvergenceWarning
 
     r = Report(title="My Report")

mne/surface.py

@@ -772,7 +772,7 @@ def _call_old(self, rr, n_jobs):
 
 def _fread3(fobj):
     """Read 3 bytes and adjust."""
-    b1, b2, b3 = np.fromfile(fobj, ">u1", 3)
+    b1, b2, b3 = np.fromfile(fobj, ">u1", 3).astype(np.int64)
     return (b1 << 16) + (b2 << 8) + b3
 
 

mne/time_frequency/tests/test_spectrum.py

@@ -1,9 +1,9 @@
 from contextlib import nullcontext
 from functools import partial
 
-import matplotlib.pyplot as plt
 import numpy as np
 import pytest
+from matplotlib.colors import same_color
 from numpy.testing import assert_allclose, assert_array_equal
 
 from mne import Annotations, create_info, make_fixed_length_epochs
@@ -449,8 +449,16 @@ def test_plot_spectrum(kind, array, request):
         data, freqs = spectrum.get_data(return_freqs=True)
         Klass = SpectrumArray if kind == "raw" else EpochsSpectrumArray
         spectrum = Klass(data=data, info=spectrum.info, freqs=freqs)
+    spectrum.info["bads"] = spectrum.ch_names[:1]  # one grad channel
     spectrum.plot(average=True, amplitude=True, spatial_colors=True)
-    spectrum.plot(average=False, amplitude=False, spatial_colors=False)
+    spectrum.plot(average=True, amplitude=False, spatial_colors=False)
+    n_grad = sum(ch_type == "grad" for ch_type in spectrum.get_channel_types())
+    for amp, sc in ((True, True), (False, False)):
+        fig = spectrum.plot(average=False, amplitude=amp, spatial_colors=sc, exclude=())
+        lines = fig.axes[0].lines[2:]  # grads, ignore two vlines
+        assert len(lines) == n_grad
+        bad_color = "0.5" if sc else "r"
+        n_bad = sum(same_color(line.get_color(), bad_color) for line in lines)
+        assert n_bad == 1
     spectrum.plot_topo()
     spectrum.plot_topomap()
-    plt.close("all")

mne/utils/check.py

@@ -8,7 +8,6 @@
 import os
 import re
 from builtins import input  # no-op here but facilitates testing
-from collections.abc import Sequence
 from difflib import get_close_matches
 from importlib import import_module
 from importlib.metadata import version
@@ -542,7 +541,7 @@ def __instancecheck__(cls, other):
     "path-like": path_like,
     "int-like": (int_like,),
     "callable": (_Callable(),),
-    "array-like": (Sequence, np.ndarray),
+    "array-like": (list, tuple, set, np.ndarray),
 }
 
 

mne/utils/config.py

@@ -205,6 +205,7 @@ def set_memmap_min_size(memmap_min_size):
     "MNE_DATASETS_FNIRS",  # mne-nirs
     "MNE_NIRS",  # mne-nirs
     "MNE_KIT2FIFF",  # mne-kit-gui
+    "MNE_ICALABEL",  # mne-icalabel
 )
 
 

mne/utils/tests/test_check.py

@@ -212,6 +212,11 @@ def test_validate_type():
     _validate_type(1, "int-like")
     with pytest.raises(TypeError, match="int-like"):
         _validate_type(False, "int-like")
+    _validate_type([1, 2, 3], "array-like")
+    _validate_type((1, 2, 3), "array-like")
+    _validate_type({1, 2, 3}, "array-like")
+    with pytest.raises(TypeError, match="array-like"):
+        _validate_type("123", "array-like")  # a string is not array-like
 
 
 def test_check_range():

mne/viz/evoked.py

@@ -679,15 +679,17 @@ def _plot_lines(
                     _handle_spatial_colors(
                         colors, info, idx, this_type, psd, ax, sphere
                     )
+                    bad_color = (0.5, 0.5, 0.5)
                 else:
                     if isinstance(_spat_col, (tuple, str)):
                         col = [_spat_col]
                     else:
                         col = ["k"]
+                    bad_color = "r"
                     colors = col * len(idx)
-                    for i in bad_ch_idx:
-                        if i in idx:
-                            colors[idx.index(i)] = "r"
+                for i in bad_ch_idx:
+                    if i in idx:
+                        colors[idx.index(i)] = bad_color
 
                 if zorder == "std":
                     # find the channels with the least activity

mne/viz/tests/test_evoked.py

@@ -16,6 +16,7 @@
 import pytest
 from matplotlib import gridspec
 from matplotlib.collections import PolyCollection
+from matplotlib.colors import same_color
 from mpl_toolkits.axes_grid1.parasite_axes import HostAxes  # spatial_colors
 from numpy.testing import assert_allclose
 
@@ -134,6 +135,12 @@ def test_plot_evoked():
     amplitudes = _get_amplitudes(fig)
     assert len(amplitudes) == len(default_picks)
     assert evoked.proj is False
+    assert evoked.info["bads"] == ["MEG 2641", "EEG 004"]
+    eeg_lines = fig.axes[2].lines
+    n_eeg = sum(ch_type == "eeg" for ch_type in evoked.get_channel_types())
+    assert len(eeg_lines) == n_eeg == 4
+    n_bad = sum(same_color(line.get_color(), "0.5") for line in eeg_lines)
+    assert n_bad == 1
     # Test a click
     ax = fig.get_axes()[0]
     line = ax.lines[0]