Merge remote-tracking branch 'upstream/main' into muscle

* upstream/main:
  Correct documented default number of CV splits [skip azp][skip actions] (mne-tools#10548)
  MRG: Add error checking to prevent the creation of montage with invalid [x, y, z] (mne-tools#10547)

doc/changes/latest.inc

@@ -47,6 +47,8 @@ Bugs
 
 - Fix reading of fiducial locations in :func:`mne.io.read_raw_eeglab` (:gh:`10521` by `Alex Gramfort`_)
 
+- Prevent creation of montage with invalid ``[x, y, z]`` coordinates with :func:`mne.channels.make_dig_montage` (:gh:`10547` by `Mathieu Scheltienne`_)
+
 API and behavior changes
 ~~~~~~~~~~~~~~~~~~~~~~~~
 - When creating BEM surfaces via :func:`mne.bem.make_watershed_bem` and :func:`mne.bem.make_flash_bem`, the ``copy`` parameter now defaults to ``True``. This means that instead of creating symbolic links inside the FreeSurfer subject's ``bem`` folder, we now create "actual" files. This should avoid troubles when sharing files across different operating systems and file systems (:gh:`10531` by `Richard Höchenberger`_)

mne/channels/tests/test_montage.py

@@ -1654,3 +1654,12 @@ def test_read_dig_localite(tmp_path):
     s = '<DigMontage | 0 extras (headshape), 0 HPIs, 3 fiducials, 15 channels>'
     assert repr(montage) == s
     assert montage.ch_names == [f'ch{i:02}' for i in range(1, 16)]
+
+
+def test_make_wrong_dig_montage():
+    """Test that a montage with non numeric is not possible."""
+    make_dig_montage(ch_pos={'A1': ['0', '0', '0']})  # converted to floats
+    with pytest.raises(ValueError, match="could not convert string to float"):
+        make_dig_montage(ch_pos={'A1': ['a', 'b', 'c']})
+    with pytest.raises(TypeError, match="instance of ndarray, list, or tuple"):
+        make_dig_montage(ch_pos={'A1': 5})

mne/decoding/base.py

@@ -382,7 +382,7 @@ def cross_val_multiscore(estimator, X, y=None, groups=None, scoring=None,
         Determines the cross-validation splitting strategy.
         Possible inputs for cv are:
 
-        - None, to use the default 3-fold cross validation,
+        - None, to use the default 5-fold cross validation,
         - integer, to specify the number of folds in a ``(Stratified)KFold``,
         - An object to be used as a cross-validation generator.
         - An iterable yielding train, test splits.

mne/io/_digitization.py

@@ -425,12 +425,22 @@ def _make_dig_points(nasion=None, lpa=None, rpa=None, hpi=None,
                         'kind': FIFF.FIFFV_POINT_EXTRA,
                         'coord_frame': coord_frame})
     if dig_ch_pos is not None:
-        try:  # use the last 3 as int if possible (e.g., EEG001->1)
-            idents = []
-            for key in dig_ch_pos:
-                _validate_type(key, str, 'dig_ch_pos')
+        idents = []
+        use_arange = False
+        for key, value in dig_ch_pos.items():
+            _validate_type(key, str, 'dig_ch_pos')
+            try:
                 idents.append(int(key[-3:]))
-        except ValueError:  # and if any conversion fails, simply use arange
+            except ValueError:
+                use_arange = True
+            _validate_type(value, (np.ndarray, list, tuple), 'dig_ch_pos')
+            value = np.array(value, dtype=float)
+            dig_ch_pos[key] = value
+            if value.shape != (3, ):
+                raise RuntimeError(
+                    "The position should be a 1D array of 3 floats. "
+                    f"Provided shape {value.shape}.")
+        if use_arange:
             idents = np.arange(1, len(dig_ch_pos) + 1)
         for key, ident in zip(dig_ch_pos, idents):
             dig.append({'r': dig_ch_pos[key], 'ident': int(ident),