MAINT: Post-release deprecations

mne/conftest.py

@@ -34,6 +34,7 @@
     _pl,
     _record_warnings,
     _TempDir,
+    check_version,
     numerics,
 )
 
@@ -636,21 +637,15 @@ def _use_backend(backend_name, interactive):
 
 def _check_skip_backend(name):
     from mne.viz.backends._utils import _notebook_vtk_works
-    from mne.viz.backends.tests._utils import (
-        has_imageio_ffmpeg,
-        has_pyvista,
-        has_pyvistaqt,
-    )
+    from mne.viz.backends.tests._utils import has_imageio_ffmpeg
 
-    if not has_pyvista():
-        pytest.skip("Test skipped, requires pyvista.")
+    pytest.importorskip("pyvista")
     if not has_imageio_ffmpeg():
         pytest.skip("Test skipped, requires imageio-ffmpeg")
     if name == "pyvistaqt":
         if not _check_qt_version():
             pytest.skip("Test skipped, requires Qt.")
-        if not has_pyvistaqt():
-            pytest.skip("Test skipped, requires pyvistaqt")
+        pytest.importorskip("pyvistaqt")
     else:
         assert name == "notebook", name
         if not _notebook_vtk_works():
@@ -660,10 +655,8 @@ def _check_skip_backend(name):
 @pytest.fixture(scope="session")
 def pixel_ratio():
     """Get the pixel ratio."""
-    from mne.viz.backends.tests._utils import has_pyvista
-
     # _check_qt_version will init an app for us, so no need for us to do it
-    if not has_pyvista() or not _check_qt_version():
+    if not check_version("pyvista", "0.32") or not _check_qt_version():
         return 1.0
     from qtpy.QtCore import Qt
     from qtpy.QtWidgets import QMainWindow

mne/datasets/eegbci/eegbci.py

@@ -9,7 +9,7 @@
 from os import path as op
 from pathlib import Path
 
-from ...utils import _url_to_local_path, logger, verbose, warn
+from ...utils import _url_to_local_path, logger, verbose
 from ..utils import _do_path_update, _downloader_params, _get_path, _log_time_size
 
 EEGMI_URL = "https://physionet.org/files/eegmmidb/1.0.0/"
@@ -94,10 +94,9 @@ def data_path(url, path=None, force_update=False, update_path=None, *, verbose=N
 
 @verbose
 def load_data(
-    subjects=None,
-    runs=None,
+    subjects,
+    runs,
     *,
-    subject=None,
     path=None,
     force_update=False,
     update_path=None,
@@ -117,9 +116,6 @@ def load_data(
         The subjects to use. Can be in the range of 1-109 (inclusive).
     runs : int | list of int
         The runs to use (see Notes for details).
-    subject : int
-        This parameter is deprecated and will be removed in mne version 1.9.
-        Please use ``subjects`` instead.
     path : None | path-like
         Location of where to look for the EEGBCI data. If ``None``, the environment
         variable or config parameter ``MNE_DATASETS_EEGBCI_PATH`` is used. If neither
@@ -170,22 +166,6 @@ def load_data(
     """
     import pooch
 
-    # XXX: Remove this with mne 1.9 ↓↓↓
-    # Also remove the subject parameter at that point.
-    # Also remove the `None` default for subjects and runs params at that point.
-    if subject is not None:
-        subjects = subject
-        warn(
-            "The ``subject`` parameter is deprecated and will be removed in version "
-            "1.9. Use the ``subjects`` parameter (note the `s`) to suppress this "
-            "warning.",
-            FutureWarning,
-        )
-        del subject
-    if subjects is None or runs is None:
-        raise ValueError("You must pass the parameters ``subjects`` and ``runs``.")
-    # ↑↑↑
-
     t0 = time.time()
 
     if not hasattr(subjects, "__iter__"):

mne/decoding/csp.py

@@ -18,7 +18,6 @@
     _verbose_safe_false,
     fill_doc,
     pinv,
-    warn,
 )
 
 
@@ -304,7 +303,6 @@ def plot_patterns(
         info,
         components=None,
         *,
-        average=None,
         ch_type=None,
         scalings=None,
         sensors=True,
@@ -342,7 +340,6 @@ def plot_patterns(
             :func:`mne.create_info`.
         components : float | array of float | None
            The patterns to plot. If ``None``, all components will be shown.
-        %(average_plot_evoked_topomap)s
         %(ch_type_topomap)s
         scalings : dict | float | None
             The scalings of the channel types to be applied for plotting.
@@ -391,9 +388,6 @@ def plot_patterns(
         if components is None:
             components = np.arange(self.n_components)
 
-        if average is not None:
-            warn("`average` is deprecated and will be removed in 1.10.", FutureWarning)
-
         # set sampling frequency to have 1 component per time point
         info = cp.deepcopy(info)
         with info._unlock():
@@ -403,7 +397,6 @@ def plot_patterns(
         # the call plot_topomap
         fig = patterns.plot_topomap(
             times=components,
-            average=average,
             ch_type=ch_type,
             scalings=scalings,
             sensors=sensors,
@@ -438,7 +431,6 @@ def plot_filters(
         info,
         components=None,
         *,
-        average=None,
         ch_type=None,
         scalings=None,
         sensors=True,
@@ -525,9 +517,6 @@ def plot_filters(
         if components is None:
             components = np.arange(self.n_components)
 
-        if average is not None:
-            warn("`average` is deprecated and will be removed in 1.10.", FutureWarning)
-
         # set sampling frequency to have 1 component per time point
         info = cp.deepcopy(info)
         with info._unlock():
@@ -537,7 +526,6 @@ def plot_filters(
         # the call plot_topomap
         fig = filters.plot_topomap(
             times=components,
-            average=average,
             ch_type=ch_type,
             scalings=scalings,
             sensors=sensors,

mne/decoding/ems.py

@@ -188,7 +188,7 @@ def compute_ems(
             data[:, this_picks] /= np.std(data[:, this_picks])
 
     # Setup cross-validation. Need to use _set_cv to deal with sklearn
-    # deprecation of cv objects.
+    # changes in cv object handling.
     y = epochs.events[:, 2]
     _, cv_splits = _set_cv(cv, "classifier", X=y, y=y)
 

mne/decoding/tests/test_base.py

@@ -320,7 +320,7 @@ def test_get_coef_multiclass(n_features, n_targets):
     ],
 )
 # TODO: Need to fix this properly in LinearModel
-@pytest.mark.filterwarnings("ignore:'multi_class' was deprecated in.*:FutureWarning")
+@pytest.mark.filterwarnings("ignore:'multi_class' was depr.*:FutureWarning")
 @pytest.mark.filterwarnings("ignore:lbfgs failed to converge.*:")
 def test_get_coef_multiclass_full(n_classes, n_channels, n_times):
     """Test a full example with pattern extraction."""

mne/fixes.py

@@ -22,12 +22,10 @@
 from math import log
 
 import numpy as np
+from packaging.version import parse
 
 ###############################################################################
-# distutils
-
-# distutils has been deprecated since Python 3.10 and was removed
-# from the standard library with the release of Python 3.12.
+# distutils LooseVersion removed in Python 3.12
 
 
 def _compare_version(version_a, operator, version_b):
@@ -48,8 +46,6 @@ def _compare_version(version_a, operator, version_b):
     bool
         The result of the version comparison.
     """
-    from packaging.version import parse
-
     mapping = {"<": "lt", "<=": "le", "==": "eq", "!=": "ne", ">=": "ge", ">": "gt"}
     with warnings.catch_warnings(record=True):
         warnings.simplefilter("ignore")

mne/io/base.py

@@ -3187,7 +3187,7 @@ def concatenate_raws(
 
 
 @fill_doc
-def match_channel_orders(insts=None, copy=True, *, raws=None):
+def match_channel_orders(insts, copy=True):
     """Ensure consistent channel order across instances (Raw, Epochs, or Evoked).
 
     Parameters
@@ -3196,30 +3196,13 @@ def match_channel_orders(insts=None, copy=True, *, raws=None):
         List of :class:`~mne.io.Raw`, :class:`~mne.Epochs`,
         or :class:`~mne.Evoked` instances to order.
     %(copy_df)s
-    raws : list
-        This parameter is deprecated and will be removed in mne version 1.9.
-        Please use ``insts`` instead.
 
     Returns
     -------
     list of Raw | list of Epochs | list of Evoked
         List of instances (Raw, Epochs, or Evoked) with channel orders matched
         according to the order they had in the first item in the ``insts`` list.
     """
-    # XXX: remove "raws" parameter and logic below with MNE version 1.9
-    #      and remove default parameter value of insts
-    if raws is not None:
-        warn(
-            "The ``raws`` parameter is deprecated and will be removed in version "
-            "1.9. Use the ``insts`` parameter to suppress this warning.",
-            DeprecationWarning,
-        )
-        insts = raws
-    elif insts is None:
-        # both insts and raws is None
-        raise ValueError(
-            "You need to pass a list of Raw, Epochs, or Evoked to ``insts``."
-        )
     insts = deepcopy(insts) if copy else insts
     ch_order = insts[0].ch_names
     for inst in insts[1:]:

mne/io/egi/tests/test_egi.py

@@ -57,9 +57,6 @@
 egi_pause_w1337_events = None
 egi_pause_w1337_skips = [(21956000.0, 40444000.0), (60936000.0, 89332000.0)]
 
-# TODO: Remove once complete deprecation / FutureWarning about events_as_annonations
-pytestmark = pytest.mark.filterwarnings("ignore:.*events_as_annotation.*:FutureWarning")
-
 
 @requires_testing_data
 @pytest.mark.parametrize(

mne/io/fiff/tests/test_raw_fiff.py

@@ -479,14 +479,6 @@ def test_concatenate_raws_order():
         match_channel_orders(insts=raws, copy=True)
         raw_concat = concatenate_raws(raws)
 
-    # XXX: remove in version 1.9
-    with pytest.warns(DeprecationWarning, match="``raws`` parameter is deprecated"):
-        match_channel_orders(raws=raws)
-
-    # XXX: remove in version 1.9
-    with pytest.raises(ValueError, match="need to pass a list"):
-        match_channel_orders()
-
     # Now passes because all raws have the same order
     match_channel_orders(insts=raws, copy=False)
     raw_concat = concatenate_raws(raws)

mne/io/neuralynx/neuralynx.py

@@ -77,7 +77,7 @@ def read_raw_neuralynx(
     )
 
 
-# Helper for neo deprecation of exclude_filename -> exclude_filenames in 0.13.2
+# Helper for neo change of exclude_filename -> exclude_filenames in 0.13.2
 def _exclude_kwarg(exclude_fnames):
     from neo.io import NeuralynxIO
 

mne/source_estimate.py

@@ -3918,22 +3918,6 @@ def stc_near_sensors(
     _validate_type(src, (None, SourceSpaces), "src")
     _check_option("mode", mode, ("sum", "single", "nearest", "weighted"))
     if surface == "auto":
-        if src is not None:
-            pial_fname = op.join(subjects_dir, subject, "surf", "lh.pial")
-            pial_rr = read_surface(pial_fname)[0]
-            src_surf_is_pial = (
-                op.isfile(pial_fname)
-                and src[0]["rr"].shape == pial_rr.shape
-                and np.allclose(src[0]["rr"], pial_rr)
-            )
-            if not src_surf_is_pial:
-                warn(
-                    "In version 1.8, ``surface='auto'`` will be the default "
-                    "which will use the surface in ``src`` instead of the "
-                    "pial surface when ``src != None``. Pass ``surface='pial'`` "
-                    "or ``surface=None`` to suppress this warning",
-                    DeprecationWarning,
-                )
         surface = "pial" if src is None or src.kind == "surface" else None
 
     # create a copy of Evoked using ecog, seeg and dbs

mne/tests/test_source_estimate.py

@@ -1711,8 +1711,7 @@ def test_stc_near_sensors(tmp_path):
     for s in src:
         transform_surface_to(s, "head", trans, copy=False)
     assert src[0]["coord_frame"] == FIFF.FIFFV_COORD_HEAD
-    with pytest.warns(DeprecationWarning, match="instead of the pial"):
-        stc_src = stc_near_sensors(evoked, src=src, **kwargs)
+    stc_src = stc_near_sensors(evoked, src=src, **kwargs)
     assert len(stc_src.data) == 7928
     with pytest.warns(RuntimeWarning, match="not included"):  # some removed
         stc_src_full = compute_source_morph(

mne/time_frequency/tfr.py

@@ -1187,9 +1187,6 @@ def __init__(
                 f'{classname} got unsupported parameter value{_pl(problem)} '
                 f'{" and ".join(problem)}.'
             )
-        # shim for tfr_array_morlet deprecation warning (TODO: remove after 1.7 release)
-        if method == "morlet":
-            method_kw.setdefault("zero_mean", True)
         # check method
         valid_methods = ["morlet", "multitaper"]
         if isinstance(inst, BaseEpochs):
@@ -2946,48 +2943,6 @@ class EpochsTFR(BaseTFR, GetEpochsMixin):
     %(picks_good_data_noref)s
     %(proj_psd)s
     %(decim_tfr)s
-    %(events_epochstfr)s
-
-        .. deprecated:: 1.7
-            Pass an instance of :class:`~mne.Epochs` as ``inst`` instead, or use
-            :class:`~mne.time_frequency.EpochsTFRArray` which retains the old API.
-    %(event_id_epochstfr)s
-
-        .. deprecated:: 1.7
-            Pass an instance of :class:`~mne.Epochs` as ``inst`` instead, or use
-            :class:`~mne.time_frequency.EpochsTFRArray` which retains the old API.
-    selection : array
-        List of indices of selected events (not dropped or ignored etc.). For
-        example, if the original event array had 4 events and the second event
-        has been dropped, this attribute would be np.array([0, 2, 3]).
-
-        .. deprecated:: 1.7
-            Pass an instance of :class:`~mne.Epochs` as ``inst`` instead, or use
-            :class:`~mne.time_frequency.EpochsTFRArray` which retains the old API.
-    drop_log : tuple of tuple
-        A tuple of the same length as the event array used to initialize the
-        ``EpochsTFR`` object. If the i-th original event is still part of the
-        selection, drop_log[i] will be an empty tuple; otherwise it will be
-        a tuple of the reasons the event is not longer in the selection, e.g.:
-
-        - ``'IGNORED'``
-            If it isn't part of the current subset defined by the user
-        - ``'NO_DATA'`` or ``'TOO_SHORT'``
-            If epoch didn't contain enough data names of channels that
-            exceeded the amplitude threshold
-        - ``'EQUALIZED_COUNTS'``
-            See :meth:`~mne.Epochs.equalize_event_counts`
-        - ``'USER'``
-            For user-defined reasons (see :meth:`~mne.Epochs.drop`).
-
-        .. deprecated:: 1.7
-            Pass an instance of :class:`~mne.Epochs` as ``inst`` instead, or use
-            :class:`~mne.time_frequency.EpochsTFRArray` which retains the old API.
-    %(metadata_epochstfr)s
-
-        .. deprecated:: 1.7
-            Pass an instance of :class:`~mne.Epochs` as ``inst`` instead, or use
-            :class:`~mne.time_frequency.EpochsTFRArray` which retains the old API.
     %(n_jobs)s
     %(verbose)s
     %(method_kw_tfr)s
@@ -3031,11 +2986,6 @@ def __init__(
         picks=None,
         proj=False,
         decim=1,
-        events=None,
-        event_id=None,
-        selection=None,
-        drop_log=None,
-        metadata=None,
         n_jobs=None,
         verbose=None,
         **method_kw,

mne/utils/linalg.py

@@ -190,7 +190,7 @@ def _sym_mat_pow(A, power, rcond=1e-7, reduce_rank=False, return_s=False):
     return out
 
 
-# SciPy deprecation of pinv + pinvh rcond (never worked properly anyway)
+# SciPy pinv + pinvh rcond never worked properly anyway so we roll our own
 def pinvh(a, rtol=None):
     """Compute a pseudo-inverse of a Hermitian matrix.