Merge branch 'channel_specific_epoch_rejection' of github.com:CarinaF…

…o/mne-python into channel_specific_epoch_rejection

.pre-commit-config.yaml

@@ -1,7 +1,7 @@
 repos:
   # Ruff mne
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.2.1
+    rev: v0.2.2
     hooks:
       - id: ruff
         name: ruff lint mne
@@ -32,7 +32,7 @@ repos:
 
   # yamllint
   - repo: https://github.com/adrienverge/yamllint.git
-    rev: v1.34.0
+    rev: v1.35.1
     hooks:
       - id: yamllint
         args: [--strict, -c, .yamllint.yml]

azure-pipelines.yml

@@ -104,7 +104,7 @@ stages:
           - bash: |
               set -e
               python -m pip install --progress-bar off --upgrade pip
-              python -m pip install --progress-bar off "mne-qt-browser[opengl] @ git+https://github.com/mne-tools/mne-qt-browser.git@main" pyvista scikit-learn pytest-error-for-skips python-picard "PyQt6!=6.5.1,!=6.6.1" "PyQt6-Qt6!=6.6.1" qtpy nibabel sphinx-gallery
+              python -m pip install --progress-bar off "mne-qt-browser[opengl] @ git+https://github.com/mne-tools/mne-qt-browser.git@main" pyvista scikit-learn pytest-error-for-skips python-picard "PyQt6!=6.5.1,!=6.6.1,!=6.6.2" "PyQt6-Qt6!=6.6.1,!=6.6.2" qtpy nibabel sphinx-gallery
               python -m pip uninstall -yq mne
               python -m pip install --progress-bar off --upgrade -e .[test]
             displayName: 'Install dependencies with pip'
@@ -183,7 +183,7 @@ stages:
             displayName: 'Get test data'
           - bash: |
               set -e
-              python -m pip install "PyQt6!=6.6.1" "PyQt6-Qt6!=6.6.1"
+              python -m pip install "PyQt6!=6.6.1,!=6.6.2" "PyQt6-Qt6!=6.6.1,!=6.6.2"
               LD_DEBUG=libs python -c "from PyQt6.QtWidgets import QApplication, QWidget; app = QApplication([]); import matplotlib; matplotlib.use('QtAgg'); import matplotlib.pyplot as plt; plt.figure()"
           - bash: |
               mne sys_info -pd

doc/changes/devel/12443.newfeature.rst

@@ -0,0 +1 @@
+Add option to pass ``image_kwargs`` to :class:`mne.Report.add_epochs` to allow adjusting e.g. ``vmin`` and ``vmax`` of the epochs image in the report, by `Sophie Herbst`_.

doc/changes/devel/12444.bugfix.rst

@@ -0,0 +1 @@
+Fix validation of ``ch_type`` in :func:`mne.preprocessing.annotate_muscle_zscore`, by `Mathieu Scheltienne`_.

doc/changes/devel/12445.newfeature.rst

@@ -0,0 +1 @@
+Add support for multiple raw instances in :func:`mne.preprocessing.compute_average_dev_head_t` by `Eric Larson`_.

doc/changes/devel/12446.newfeature.rst

@@ -0,0 +1 @@
+Support partial pathlength factors for each wavelength in :func:`mne.preprocessing.nirs.beer_lambert_law`, by :newcontrib:`Richard Scholz`.

doc/changes/devel/12451.bugfix.rst

@@ -0,0 +1 @@
+Fix errant redundant use of ``BIDSPath.split`` when writing split raw and epochs data, by `Eric Larson`_.

doc/changes/devel/12451.dependency.rst

@@ -0,0 +1 @@
+``pytest-harvest`` is no longer used as a test dependency, by `Eric Larson`_.

doc/changes/devel/12454.newfeature.rst

@@ -0,0 +1 @@
+Completing PR 12453. Add option to pass ``image_kwargs`` per channel type to :class:`mne.Report.add_epochs`.

doc/changes/devel/12456.bugfix.rst

@@ -0,0 +1 @@
+Disable config parser interpolation when reading BrainVision files, which allows using the percent sign as a regular character in channel units, by `Clemens Brunner`_.

doc/changes/names.inc

@@ -474,6 +474,8 @@
 
 .. _Richard Koehler: https://github.com/richardkoehler
 
+.. _Richard Scholz: https://github.com/scholzri
+
 .. _Riessarius Stargardsky: https://github.com/Riessarius
 
 .. _Roan LaPlante: https://github.com/aestrivex

mne/channels/channels.py

@@ -839,6 +839,8 @@ def interpolate_bads(
             - ``"meg"`` channels support ``"MNE"`` (default) and ``"nan"
             - ``"eeg"`` channels support ``"spline"`` (default), ``"MNE"`` and ``"nan"
             - ``"fnirs"`` channels support ``"nearest"`` (default) and ``"nan"``
+            - ``"ecog"`` channels support ``"spline"`` (default) and ``"nan"``
+            - ``"seeg"`` channels support ``"spline"`` (default) and ``"nan"``
 
             None is an alias for::
 

mne/conftest.py

@@ -10,6 +10,7 @@
 import shutil
 import sys
 import warnings
+from collections import defaultdict
 from contextlib import contextmanager
 from pathlib import Path
 from textwrap import dedent
@@ -900,11 +901,8 @@ def protect_config():
 
 
 def _test_passed(request):
-    try:
-        outcome = request.node.harvest_rep_call
-    except Exception:
-        outcome = "passed"
-    return outcome == "passed"
+    report = request.node.stash[_phase_report_key]
+    return "call" in report and report["call"].outcome == "passed"
 
 
 @pytest.fixture()
@@ -931,7 +929,6 @@ def brain_gc(request):
     ignore = set(id(o) for o in gc.get_objects())
     yield
     close_func()
-    # no need to warn if the test itself failed, pytest-harvest helps us here
     if not _test_passed(request):
         return
     _assert_no_instances(Brain, "after")
@@ -960,16 +957,12 @@ def pytest_sessionfinish(session, exitstatus):
     if n is None:
         return
     print("\n")
-    try:
-        import pytest_harvest
-    except ImportError:
-        print("Module-level timings require pytest-harvest")
-        return
     # get the number to print
-    res = pytest_harvest.get_session_synthesis_dct(session)
-    files = dict()
-    for key, val in res.items():
-        parts = Path(key.split(":")[0]).parts
+    files = defaultdict(lambda: 0.0)
+    for item in session.items:
+        report = item.stash[_phase_report_key]
+        dur = sum(x.duration for x in report.values())
+        parts = Path(item.nodeid.split(":")[0]).parts
         # split mne/tests/test_whatever.py into separate categories since these
         # are essentially submodule-level tests. Keeping just [:3] works,
         # except for mne/viz where we want level-4 granulatity
@@ -978,7 +971,7 @@ def pytest_sessionfinish(session, exitstatus):
         if not parts[-1].endswith(".py"):
             parts = parts + ("",)
         file_key = "/".join(parts)
-        files[file_key] = files.get(file_key, 0) + val["pytest_duration_s"]
+        files[file_key] += dur
     files = sorted(list(files.items()), key=lambda x: x[1])[::-1]
     # print
     _files[:] = files[:n]
@@ -999,7 +992,7 @@ def pytest_terminal_summary(terminalreporter, exitstatus, config):
             writer.line(f"{timing.ljust(15)}{name}")
 
 
-def pytest_report_header(config, startdir):
+def pytest_report_header(config, startdir=None):
     """Add information to the pytest run header."""
     return f"MNE {mne.__version__} -- {str(Path(mne.__file__).parent)}"
 
@@ -1122,7 +1115,6 @@ def run(nbexec=nbexec, code=code):
     return
 
 
-@pytest.mark.filterwarnings("ignore:.*Extraction of measurement.*:")
 @pytest.fixture(
     params=(
         [nirsport2, nirsport2_snirf, testing._pytest_param()],
@@ -1160,8 +1152,7 @@ def qt_windows_closed(request):
     if "allow_unclosed_pyside2" in marks and API_NAME.lower() == "pyside2":
         return
     # Don't check when the test fails
-    report = request.node.stash[_phase_report_key]
-    if ("call" not in report) or report["call"].failed:
+    if not _test_passed(request):
         return
     widgets = app.topLevelWidgets()
     n_after = len(widgets)

mne/datasets/__init__.pyi

@@ -66,7 +66,7 @@ from . import (
 )
 from ._fetch import fetch_dataset
 from ._fsaverage.base import fetch_fsaverage
-from ._infant.base import fetch_infant_template
+from ._infant import fetch_infant_template
 from ._phantom.base import fetch_phantom
 from .utils import (
     _download_all_example_data,

mne/datasets/_infant/__init__.py

@@ -0,0 +1 @@
+from .base import fetch_infant_template

mne/epochs.py

@@ -2240,7 +2240,14 @@ def save(
         )
 
         # check for file existence and expand `~` if present
-        fname = str(_check_fname(fname=fname, overwrite=overwrite))
+        fname = str(
+            _check_fname(
+                fname=fname,
+                overwrite=overwrite,
+                check_bids_split=True,
+                name="fname",
+            )
+        )
 
         split_size_bytes = _get_split_size(split_size)
 

mne/fixes.py

@@ -31,9 +31,8 @@
 ###############################################################################
 # distutils
 
-# distutils has been deprecated since Python 3.10 and is scheduled for removal
-# from the standard library with the release of Python 3.12. For version
-# comparisons, we use setuptools's `parse_version` if available.
+# distutils has been deprecated since Python 3.10 and was removed
+# from the standard library with the release of Python 3.12.
 
 
 def _compare_version(version_a, operator, version_b):

mne/io/base.py

@@ -1694,7 +1694,13 @@ def save(
         endings_err = (".fif", ".fif.gz")
 
         # convert to str, check for overwrite a few lines later
-        fname = _check_fname(fname, overwrite=True, verbose="error")
+        fname = _check_fname(
+            fname,
+            overwrite=True,
+            verbose="error",
+            check_bids_split=True,
+            name="fname",
+        )
         check_fname(fname, "raw", endings, endings_err=endings_err)
 
         split_size = _get_split_size(split_size)

mne/io/brainvision/brainvision.py

@@ -447,7 +447,7 @@ def _aux_hdr_info(hdr_fname):
         params, settings = settings.split("[Comment]")
     else:
         params, settings = settings, ""
-    cfg = configparser.ConfigParser()
+    cfg = configparser.ConfigParser(interpolation=None)
     with StringIO(params) as fid:
         cfg.read_file(fid)
 

mne/io/fiff/tests/test_raw_fiff.py

@@ -675,6 +675,34 @@ def test_split_files(tmp_path, mod, monkeypatch):
     assert not fname_3.is_file()
 
 
+def test_bids_split_files(tmp_path):
+    """Test that BIDS split files are written safely."""
+    mne_bids = pytest.importorskip("mne_bids")
+    bids_path = mne_bids.BIDSPath(
+        root=tmp_path,
+        subject="01",
+        datatype="meg",
+        split="01",
+        suffix="raw",
+        extension=".fif",
+        check=False,
+    )
+    (tmp_path / "sub-01" / "meg").mkdir(parents=True)
+    raw = read_raw_fif(test_fif_fname)
+    save_kwargs = dict(
+        buffer_size_sec=1.0, split_size="10MB", split_naming="bids", verbose=True
+    )
+    with pytest.raises(ValueError, match="Passing a BIDSPath"):
+        raw.save(bids_path, **save_kwargs)
+    bids_path.split = None
+    want_paths = [Path(bids_path.copy().update(split=ii).fpath) for ii in range(1, 3)]
+    for want_path in want_paths:
+        assert not want_path.is_file()
+    raw.save(bids_path, **save_kwargs)
+    for want_path in want_paths:
+        assert want_path.is_file()
+
+
 def _err(*args, **kwargs):
     raise RuntimeError("Killed mid-write")
 

mne/preprocessing/artifact_detection.py

@@ -25,7 +25,15 @@
     apply_trans,
     quat_to_rot,
 )
-from ..utils import _mask_to_onsets_offsets, _pl, _validate_type, logger, verbose
+from ..utils import (
+    _check_option,
+    _mask_to_onsets_offsets,
+    _pl,
+    _validate_type,
+    logger,
+    verbose,
+    warn,
+)
 
 
 @verbose
@@ -94,16 +102,13 @@ def annotate_muscle_zscore(
             ch_type = "eeg"
         else:
             raise ValueError(
-                "No M/EEG channel types found, please specify a"
-                " ch_type or provide M/EEG sensor data"
+                "No M/EEG channel types found, please specify a 'ch_type' or provide "
+                "M/EEG sensor data."
             )
-        logger.info("Using %s sensors for muscle artifact detection" % (ch_type))
-
-    if ch_type in ("mag", "grad"):
-        raw_copy.pick(ch_type)
+        logger.info("Using %s sensors for muscle artifact detection", ch_type)
     else:
-        ch_type = {"meg": False, ch_type: True}
-        raw_copy.pick(**ch_type)
+        _check_option("ch_type", ch_type, ["mag", "grad", "eeg"])
+    raw_copy.pick(ch_type)
 
     raw_copy.filter(
         filter_freq[0],
@@ -289,27 +294,68 @@ def annotate_movement(
     return annot, disp
 
 
-def compute_average_dev_head_t(raw, pos):
+@verbose
+def compute_average_dev_head_t(raw, pos, *, verbose=None):
     """Get new device to head transform based on good segments.
 
     Segments starting with "BAD" annotations are not included for calculating
     the mean head position.
 
     Parameters
     ----------
-    raw : instance of Raw
-        Data to compute head position.
-    pos : array, shape (N, 10)
-        The position and quaternion parameters from cHPI fitting.
+    raw : instance of Raw | list of Raw
+        Data to compute head position. Can be a list containing multiple raw
+        instances.
+    pos : array, shape (N, 10) | list of ndarray
+        The position and quaternion parameters from cHPI fitting. Can be
+        a list containing multiple position arrays, one per raw instance passed.
+    %(verbose)s
 
     Returns
     -------
     dev_head_t : instance of Transform
         New ``dev_head_t`` transformation using the averaged good head positions.
+
+    Notes
+    -----
+    .. versionchanged:: 1.7
+       Support for multiple raw instances and position arrays was added.
     """
+    # Get weighted head pos trans and rot
+    if not isinstance(raw, (list, tuple)):
+        raw = [raw]
+    if not isinstance(pos, (list, tuple)):
+        pos = [pos]
+    if len(pos) != len(raw):
+        raise ValueError(
+            f"Number of head positions ({len(pos)}) must match the number of raw "
+            f"instances ({len(raw)})"
+        )
+    hp = list()
+    dt = list()
+    for ri, (r, p) in enumerate(zip(raw, pos)):
+        _validate_type(r, BaseRaw, f"raw[{ri}]")
+        _validate_type(p, np.ndarray, f"pos[{ri}]")
+        hp_, dt_ = _raw_hp_weights(r, p)
+        hp.append(hp_)
+        dt.append(dt_)
+    hp = np.concatenate(hp, axis=0)
+    dt = np.concatenate(dt, axis=0)
+    dt /= dt.sum()
+    best_q = _average_quats(hp[:, 1:4], weights=dt)
+    trans = np.eye(4)
+    trans[:3, :3] = quat_to_rot(best_q)
+    trans[:3, 3] = dt @ hp[:, 4:7]
+    dist = np.linalg.norm(trans[:3, 3])
+    if dist > 1:  # less than 1 meter is sane
+        warn(f"Implausible head position detected: {dist} meters from device origin")
+    dev_head_t = Transform("meg", "head", trans)
+    return dev_head_t
+
+
+def _raw_hp_weights(raw, pos):
     sfreq = raw.info["sfreq"]
     seg_good = np.ones(len(raw.times))
-    trans_pos = np.zeros(3)
     hp = pos.copy()
     hp_ts = hp[:, 0] - raw._first_time
 
@@ -349,19 +395,7 @@ def compute_average_dev_head_t(raw, pos):
     assert (dt >= 0).all()
     dt = dt / sfreq
     del seg_good, idx
-
-    # Get weighted head pos trans and rot
-    trans_pos += np.dot(dt, hp[:, 4:7])
-
-    rot_qs = hp[:, 1:4]
-    best_q = _average_quats(rot_qs, weights=dt)
-
-    trans = np.eye(4)
-    trans[:3, :3] = quat_to_rot(best_q)
-    trans[:3, 3] = trans_pos / dt.sum()
-    assert np.linalg.norm(trans[:3, 3]) < 1  # less than 1 meter is sane
-    dev_head_t = Transform("meg", "head", trans)
-    return dev_head_t
+    return hp, dt
 
 
 def _annotations_from_mask(times, mask, annot_name, orig_time=None):