FIX: Some

environment.yml

@@ -47,7 +47,7 @@ dependencies:
   - qdarkstyle !=3.2.2
   - qtpy
   - scikit-learn
-  - scipy >=1.11.1
+  - scipy >=1.11
   - sip
   - snirf
   - statsmodels

mne/commands/mne_flash_bem.py

@@ -95,17 +95,6 @@ def run():
             "been registered with the T1.mgz file."
         ),
     )
-    parser.add_option(
-        "-n",
-        "--noconvert",
-        dest="noconvert",
-        action="store_true",
-        default=False,
-        help=(
-            "[DEPRECATED] Assume that the Flash MRI images "
-            "have already been converted to mgz files"
-        ),
-    )
     parser.add_option(
         "-u",
         "--unwarp",
@@ -139,15 +128,6 @@ def run():
         help="Use copies instead of symlinks for surfaces",
         action="store_true",
     )
-    parser.add_option(
-        "-p",
-        "--flash-path",
-        dest="flash_path",
-        default=None,
-        help="[DEPRECATED] The directory containing flash5.mgz "
-        "files (defaults to "
-        "$SUBJECTS_DIR/$SUBJECT/mri/flash/parameter_maps",
-    )
 
     options, _ = parser.parse_args()
 

mne/report/report.py

@@ -3415,6 +3415,7 @@ def _add_raw(
             init_kwargs.setdefault("fmax", fmax)
             plot_kwargs.setdefault("show", False)
             with warnings.catch_warnings():
+                # SciPy warning about too short a data segment given the window size
                 warnings.simplefilter(action="ignore", category=FutureWarning)
                 fig = raw.compute_psd(**init_kwargs).plot(**plot_kwargs)
             self._add_figure(

mne/time_frequency/tests/test_spectrum.py

@@ -306,8 +306,6 @@ def test_unaggregated_spectrum_to_data_frame(raw, long_format, method, output):
     pytest.importorskip("pandas")
     from pandas.testing import assert_frame_equal
 
-    from mne.utils.dataframe import _inplace
-
     # aggregated spectrum → dataframe
     orig_df = raw.compute_psd(method=method).to_data_frame(long_format=long_format)
     # unaggregated welch or complex multitaper →
@@ -329,7 +327,7 @@ def test_unaggregated_spectrum_to_data_frame(raw, long_format, method, output):
     orig_df = orig_df.loc[subset(orig_df["freq"])]
     # sort orig_df, because at present we can't actually prevent pandas from
     # sorting at the agg step *sigh*
-    _inplace(orig_df, "sort_values", by=grouping_cols, ignore_index=True)
+    orig_df.sort_values(by=grouping_cols, ignore_index=True)
     # aggregate
     df = df.drop(columns=drop_cols)
     gb = df.groupby(grouping_cols, as_index=False, observed=False)

mne/utils/dataframe.py

@@ -8,7 +8,6 @@
 
 from ..defaults import _handle_default
 from ._logging import logger, verbose
-from .check import check_version
 
 
 @verbose
@@ -48,17 +47,6 @@ def _convert_times(times, time_format, meas_date=None, first_time=0):
     return times
 
 
-def _inplace(df, method, **kwargs):
-    _meth = getattr(df, method)  # used for set_index() and rename()
-
-    # TODO: deprecation in Pandas 3.0, can remove once we require 3+
-    if check_version("pandas", "3.0"):
-        return _meth(**kwargs)
-    else:
-        # "copy" in signature(_meth).parameters
-        return _meth(**kwargs, copy=False)
-
-
 @verbose
 def _build_data_frame(
     inst,
@@ -86,16 +74,16 @@ def _build_data_frame(
         df.insert(i, k, v)
     # build Index
     if long_format:
-        df = _inplace(df, "set_index", keys=default_index)
+        df.set_index(keys=default_index)
         df.columns.name = col_kind
     elif index is not None:
-        df = _inplace(df, "set_index", keys=index)
+        df.set_index(keys=index)
         if set(index) == set(default_index):
             df.columns.name = col_kind
     # long format
     if long_format:
         df = df.stack().reset_index()
-        df = _inplace(df, "rename", columns={0: "value"})
+        df.rename(columns={0: "value"})
         # add column for channel types (as appropriate)
         ch_map = (
             None
@@ -113,7 +101,7 @@ def _build_data_frame(
             df.insert(col_index, "ch_type", ch_type)
         # restore index
         if index is not None:
-            df = _inplace(df, "set_index", keys=index)
+            df.set_index(keys=index)
         # convert channel/vertex/ch_type columns to factors
         to_factor = [
             c for c in df.columns.tolist() if c not in ("freq", "time", "value")

pyproject.toml

@@ -27,7 +27,7 @@ dependencies = [
   "numpy >= 1.25,<3",  # 2023/06/17
   "packaging",
   "pooch >= 1.5",
-  "scipy >= 1.11.1",  # 2023/06/25
+  "scipy >= 1.11",  # 2023/06/25
   "tqdm",
 ]
 description = "MNE-Python project for MEG and EEG data analysis."

tools/environment_old.yml

@@ -5,7 +5,7 @@ channels:
 dependencies:
   - python =3.10
   - numpy =1.25
-  - scipy =1.11.1
+  - scipy =1.11
   - matplotlib =3.7
   - pandas =2.0
   - scikit-learn