[pull] main from mne-tools:main

.github/workflows/codeql-analysis.yml

@@ -44,7 +44,7 @@ jobs:
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
-      uses: github/codeql-action/init@v3
+      uses: github/codeql-action/init@v4
       with:
         languages: ${{ matrix.language }}
         # If you wish to specify custom queries, you can do so here or in a config file.
@@ -58,7 +58,7 @@ jobs:
     # Autobuild attempts to build any compiled languages  (C/C++, C#, or Java).
     # If this step fails, then you should remove it and run the build manually (see below)
     - name: Autobuild
-      uses: github/codeql-action/autobuild@v3
+      uses: github/codeql-action/autobuild@v4
 
     # ℹ️ Command-line programs to run using the OS shell.
     # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
@@ -71,4 +71,4 @@ jobs:
     #   ./location_of_script_within_repo/buildscript.sh
 
     - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@v3
+      uses: github/codeql-action/analyze@v4

doc/changes/dev/13445.newfeature.rst

@@ -0,0 +1 @@
+Improve precision of fiducial clicking in ``mne coreg``, by `Eric Larson`_.

doc/install/installers.rst

@@ -17,7 +17,7 @@ Platform-specific installers
         :class-content: text-center
         :name: install-linux
 
-        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.1/MNE-Python-1.10.1_0-Linux.sh
+        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.2/MNE-Python-1.10.2_0-Linux.sh
             :ref-type: ref
             :color: primary
             :shadow:
@@ -31,14 +31,14 @@ Platform-specific installers
 
         .. code-block:: console
 
-            $ sh ./MNE-Python-1.10.1_0-Linux.sh
+            $ sh ./MNE-Python-1.10.2_0-Linux.sh
 
 
     .. tab-item:: macOS (Intel)
         :class-content: text-center
         :name: install-macos-intel
 
-        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.1/MNE-Python-1.10.1_0-macOS_Intel.pkg
+        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.2/MNE-Python-1.10.2_0-macOS_Intel.pkg
             :ref-type: ref
             :color: primary
             :shadow:
@@ -54,7 +54,7 @@ Platform-specific installers
         :class-content: text-center
         :name: install-macos-apple
 
-        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.1/MNE-Python-1.10.1_0-macOS_M1.pkg
+        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.2/MNE-Python-1.10.2_0-macOS_M1.pkg
             :ref-type: ref
             :color: primary
             :shadow:
@@ -70,7 +70,7 @@ Platform-specific installers
         :class-content: text-center
         :name: install-windows
 
-        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.1/MNE-Python-1.10.1_0-Windows.exe
+        .. button-link:: https://github.com/mne-tools/mne-installers/releases/download/v1.10.2/MNE-Python-1.10.2_0-Windows.exe
             :ref-type: ref
             :color: primary
             :shadow:
@@ -156,7 +156,7 @@ To remove the MNE-Python distribution provided by our installers above:
            .. code-block:: bash
 
                $ which python
-               /home/username/mne-python/1.10.1_0/bin/python
+               /home/username/mne-python/1.10.2_0/bin/python
                $ rm -Rf /home/$USER/mne-python
                $ rm /home/$USER/.local/share/applications/mne-python-*.desktop
 
@@ -170,7 +170,7 @@ To remove the MNE-Python distribution provided by our installers above:
            .. code-block:: bash
 
                $ which python
-               /Users/username/Applications/MNE-Python/1.10.1_0/.mne-python/bin/python
+               /Users/username/Applications/MNE-Python/1.10.2_0/.mne-python/bin/python
                $ rm -Rf /Users/$USER/Applications/MNE-Python  # if user-specific
                $ rm -Rf /Applications/MNE-Python              # if system-wide
 

mne/beamformer/tests/test_dics.py

@@ -705,6 +705,7 @@ def test_apply_dics_timeseries(_load_forward, idx):
         apply_dics_epochs(epochs, filters_vol)
 
 
+@pytest.mark.slowtest
 @testing.requires_testing_data
 @pytest.mark.parametrize("return_generator", (True, False))
 def test_apply_dics_tfr(return_generator):
@@ -849,6 +850,7 @@ def test_localization_bias_free(
     assert lower <= perc <= upper
 
 
+@pytest.mark.slowtest
 @pytest.mark.parametrize(
     "weight_norm, lower, upper, lower_ori, upper_ori, real_filter",
     [

mne/beamformer/tests/test_lcmv.py

@@ -809,6 +809,7 @@ def test_lcmv_reg_proj(proj, weight_norm):
         assert_allclose(stc_cov.data.std(), 0.187, rtol=0.2)
 
 
+@pytest.mark.slowtest
 @pytest.mark.parametrize(
     "reg, weight_norm, use_cov, depth, lower, upper",
     [
@@ -851,6 +852,7 @@ def test_localization_bias_fixed(
 
 
 # Changes here should be synced with test_dics.py
+@pytest.mark.slowtest
 @pytest.mark.parametrize(
     "reg, pick_ori, weight_norm, use_cov, depth, lower, upper, lower_ori, upper_ori",
     [
@@ -1044,7 +1046,7 @@ def test_orientation_max_power(
     "weight_norm, pick_ori",
     [
         pytest.param("nai", "max-power", marks=pytest.mark.slowtest),
-        ("unit-noise-gain", "vector"),
+        pytest.param("unit-noise-gain", "vector", marks=pytest.mark.slowtest),
         ("unit-noise-gain", "max-power"),
         pytest.param("unit-noise-gain", None, marks=pytest.mark.slowtest),
     ],

mne/gui/_coreg.py

@@ -918,19 +918,10 @@ def _on_pick(self, vtk_picker, event):
         if not any(mesh is target() for target in self._picking_targets):
             return
         pos = np.array(vtk_picker.GetPickPosition())
-        vtk_cell = mesh.GetCell(cell_id)
-        cell = [
-            vtk_cell.GetPointId(point_id)
-            for point_id in range(vtk_cell.GetNumberOfPoints())
-        ]
-        vertices = mesh.points[cell]
-        idx = np.argmin(abs(vertices - pos), axis=0)
-        vertex_id = cell[idx[0]]
-
         fiducials = [s.lower() for s in self._defaults["fiducials"]]
         idx = fiducials.index(self._current_fiducial.lower())
         # XXX: add coreg.set_fids
-        self.coreg._fid_points[idx] = self._surfaces["head"].points[vertex_id]
+        self.coreg._fid_points[idx] = pos
         self.coreg._reset_fiducials()
         self._update_fiducials()
         self._update_plot("mri_fids")

mne/gui/tests/test_coreg.py

@@ -45,7 +45,6 @@ class TstVTKPicker:
     def __init__(self, mesh, cell_id, event_pos):
         self.mesh = mesh
         self.cell_id = cell_id
-        self.point_id = None
         self.event_pos = event_pos
 
     def GetCellId(self):
@@ -59,12 +58,7 @@ def GetDataSet(self):
     def GetPickPosition(self):
         """Return the picked position."""
         vtk_cell = self.mesh.GetCell(self.cell_id)
-        cell = [
-            vtk_cell.GetPointId(point_id)
-            for point_id in range(vtk_cell.GetNumberOfPoints())
-        ]
-        self.point_id = cell[0]
-        return self.mesh.points[self.point_id]
+        return self.mesh.points[vtk_cell.GetPointId(0)]
 
     def GetEventPosition(self):
         """Return event position."""

mne/minimum_norm/tests/test_inverse.py

@@ -244,6 +244,7 @@ def _compare_io(inv_op, *, out_file_ext=".fif", tmp_path):
     _compare(inv_init, inv_op)
 
 
+@pytest.mark.slowtest
 def test_warn_inverse_operator(evoked, noise_cov):
     """Test MNE inverse warning without average EEG projection."""
     bad_info = evoked.info
@@ -390,12 +391,22 @@ def test_inverse_operator_channel_ordering(evoked, noise_cov):
 @pytest.mark.parametrize(
     "method, lower, upper, depth",
     [
-        ("MNE", 54, 57, dict(limit=None, combine_xyz=False, exp=1.0)),  # DICS def
-        ("MNE", 75, 80, dict(limit_depth_chs=False)),  # ancient MNE default
+        pytest.param(
+            "MNE",
+            54,
+            57,
+            dict(limit=None, combine_xyz=False, exp=1.0),
+            marks=pytest.mark.slowtest,
+        ),  # DICS default
+        pytest.param(
+            "MNE", 75, 80, dict(limit_depth_chs=False), marks=pytest.mark.slowtest
+        ),  # ancient MNE default
         ("MNE", 83, 87, 0.8),  # MNE default
-        ("MNE", 89, 92, dict(limit_depth_chs="whiten")),  # sparse default
-        ("dSPM", 96, 98, 0.8),
-        ("sLORETA", 100, 100, 0.8),
+        pytest.param(
+            "MNE", 89, 92, dict(limit_depth_chs="whiten"), marks=pytest.mark.slowtest
+        ),  # sparse default
+        pytest.param("dSPM", 96, 98, 0.8, marks=pytest.mark.slowtest),
+        pytest.param("sLORETA", 100, 100, 0.8, marks=pytest.mark.slowtest),
         pytest.param("eLORETA", 100, 100, None, marks=pytest.mark.slowtest),
         pytest.param("eLORETA", 100, 100, 0.8, marks=pytest.mark.slowtest),
     ],
@@ -418,11 +429,25 @@ def test_localization_bias_fixed(bias_params_fixed, method, lower, upper, depth)
 @pytest.mark.parametrize(
     "method, lower, upper, depth, loose",
     [
-        ("MNE", 32, 37, dict(limit=None, combine_xyz=False, exp=1.0), 0.2),  # DICS
+        pytest.param(
+            "MNE",
+            32,
+            37,
+            dict(limit=None, combine_xyz=False, exp=1.0),
+            0.2,
+            marks=pytest.mark.slowtest,
+        ),  # DICS
         ("MNE", 78, 81, 0.8, 0.2),  # MNE default
-        ("MNE", 89, 92, dict(limit_depth_chs="whiten"), 0.2),  # sparse default
-        ("dSPM", 85, 87, 0.8, 0.2),
-        ("sLORETA", 100, 100, 0.8, 0.2),
+        pytest.param(
+            "MNE",
+            89,
+            92,
+            dict(limit_depth_chs="whiten"),
+            0.2,
+            marks=pytest.mark.slowtest,
+        ),  # sparse default
+        pytest.param("dSPM", 85, 87, 0.8, 0.2, marks=pytest.mark.slowtest),
+        pytest.param("sLORETA", 100, 100, 0.8, 0.2, marks=pytest.mark.slowtest),
         pytest.param("eLORETA", 99, 100, None, 0.2, marks=pytest.mark.slowtest),
         pytest.param("eLORETA", 99, 100, 0.8, 0.2, marks=pytest.mark.slowtest),
         pytest.param("eLORETA", 99, 100, 0.8, 0.001, marks=pytest.mark.slowtest),
@@ -461,7 +486,7 @@ def test_localization_bias_loose(
 @pytest.mark.parametrize(
     "method, lower, upper, lower_ori, upper_ori, kwargs, depth, loose",
     [
-        (
+        pytest.param(
             "MNE",
             21,
             24,
@@ -470,8 +495,9 @@ def test_localization_bias_loose(
             {},
             dict(limit=None, combine_xyz=False, exp=1.0),
             1,
+            marks=pytest.mark.slowtest,
         ),
-        (
+        pytest.param(
             "MNE",
             35,
             40,
@@ -480,6 +506,7 @@ def test_localization_bias_loose(
             {},
             dict(limit_depth_chs=False),
             1,
+            marks=pytest.mark.slowtest,
         ),  # ancient default
         ("MNE", 45, 55, 0.94, 0.95, {}, 0.8, 1),  # MNE default
         (
@@ -493,7 +520,9 @@ def test_localization_bias_loose(
             1,
         ),  # sparse default
         ("dSPM", 40, 45, 0.96, 0.97, {}, 0.8, 1),
-        ("sLORETA", 93, 95, 0.95, 0.96, {}, 0.8, 1),
+        pytest.param(
+            "sLORETA", 93, 95, 0.95, 0.96, {}, 0.8, 1, marks=pytest.mark.slowtest
+        ),
         pytest.param(
             "eLORETA",
             93,
@@ -567,6 +596,7 @@ def test_apply_inverse_sphere(evoked, tmp_path):
     assert_array_equal(np.argmax(stc.data, axis=0), np.repeat(np.arange(101), 3))
 
 
+@pytest.mark.slowtest
 @pytest.mark.parametrize("loose", [0.0, 0.2, 1.0])
 @pytest.mark.parametrize("lambda2", [1.0 / 9.0, 0.0])
 def test_apply_inverse_eLORETA_MNE_equiv(bias_params_free, loose, lambda2):
@@ -764,6 +794,7 @@ def assert_var_exp_log(log, lower, upper):
     return exp_var
 
 
+@pytest.mark.slowtest
 @pytest.mark.parametrize("method", INVERSE_METHODS)
 @pytest.mark.parametrize("pick_ori", (None, "vector"))
 def test_inverse_residual(evoked, method, pick_ori):
@@ -936,6 +967,7 @@ def test_make_inverse_operator_vector(evoked, noise_cov):
     assert_allclose(stc_diff.data, (stc_vec0 - stc_vec1).magnitude().data, atol=1e-20)
 
 
+@pytest.mark.slowtest
 def test_make_inverse_operator_diag(evoked, noise_cov, tmp_path, azure_windows):
     """Test MNE inverse computation with diagonal noise cov."""
     noise_cov = noise_cov.as_diag()
@@ -1056,6 +1088,7 @@ def test_io_inverse_operator(tmp_path):
 _fast_methods.pop(_fast_methods.index("eLORETA"))
 
 
+@pytest.mark.slowtest
 @testing.requires_testing_data
 @pytest.mark.parametrize("method", _fast_methods)
 @pytest.mark.parametrize("pick_ori", ["normal", None])
@@ -1118,6 +1151,7 @@ def test_apply_inverse_cov(method, pick_ori):
         )
 
 
+@pytest.mark.slowtest
 @testing.requires_testing_data
 def test_apply_mne_inverse_raw():
     """Test MNE with precomputed inverse operator on Raw."""

mne/minimum_norm/tests/test_resolution_matrix.py

@@ -26,6 +26,7 @@
 fname_label = data_path / "subjects" / "sample" / "label" / "lh.V1.label"
 
 
+@pytest.mark.slowtest
 @testing.requires_testing_data
 @pytest.mark.parametrize("src_type", ("surface", "volume"))
 def test_resolution_matrix_free(src_type, fwd_volume_small):
@@ -131,6 +132,7 @@ def test_resolution_matrix_free(src_type, fwd_volume_small):
     assert_array_almost_equal(stc_psf_label_free.data, stc_ctf_label_free.data)
 
 
+@pytest.mark.slowtest
 @testing.requires_testing_data
 def test_resolution_matrix_fixed():
     """Test resolution matrices with fixed orientations."""

mne/minimum_norm/tests/test_time_frequency.py

@@ -271,6 +271,7 @@ def test_tfr_multi_label():
             assert multi_lab_pow.shape == (2, n_freqs, n_times)
 
 
+@pytest.mark.slowtest
 @testing.requires_testing_data
 @pytest.mark.parametrize("method", INVERSE_METHODS)
 @pytest.mark.parametrize("pick_ori", (None, "normal"))  # XXX vector someday?

mne/tests/test_surface.py

@@ -333,6 +333,7 @@ def test_voxel_neighbors():
     assert true_volume.difference(volume) == set()
 
 
+@pytest.mark.slowtest
 @testing.requires_testing_data
 @pytest.mark.parametrize("ret_nn", (False, True))
 @pytest.mark.parametrize("method", ("accurate", "nearest"))