BUG: Fix largest culprit in speed issue

mne_gui_addons/_core.py

@@ -357,10 +357,11 @@ def _plot_images(self):
             plot_x_idx, plot_y_idx = self._xy_idx[axis]
             fig = self._figs[axis]
             ax = fig.axes[0]
-            img_data = np.take(self._base_data, self._current_slice[axis], axis=axis).T
             self._images["base"].append(
                 ax.imshow(
-                    img_data,
+                    self._base_data[
+                        (slice(None),) * axis + (self._current_slice[axis],)
+                    ].T,
                     cmap="gray",
                     aspect="auto",
                     zorder=1,
@@ -623,8 +624,9 @@ def _draw(self, axis=None):
     def _update_base_images(self, axis=None, draw=False):
         """Update the base images."""
         for axis in range(3) if axis is None else [axis]:
-            img_data = np.take(self._base_data, self._current_slice[axis], axis=axis).T
-            self._images["base"][axis].set_data(img_data)
+            self._images["base"][axis].set_data(
+                self._base_data[(slice(None),) * axis + (self._current_slice[axis],)].T
+            )
             if draw:
                 self._draw(axis)
 

mne_gui_addons/_ieeg_locate.py

@@ -996,16 +996,21 @@ def _update_ch_images(self, axis=None, draw=False):
     def _update_ct_images(self, axis=None, draw=False):
         """Update the CT image(s)."""
         for axis in range(3) if axis is None else [axis]:
-            ct_data = np.take(self._ct_data, self._current_slice[axis], axis=axis).T
+            ct_data = (
+                self._ct_data[(slice(None),) * axis + (self._current_slice[axis],)]
+                .copy()
+                .T
+            )
             # Threshold the CT so only bright objects (electrodes) are visible
             ct_data[ct_data < self._ct_min_slider.value()] = np.nan
             ct_data[ct_data > self._ct_max_slider.value()] = np.nan
             self._images["ct"][axis].set_data(ct_data)
             if "local_max" in self._images:
-                ct_max_data = np.take(
-                    self._ct_maxima, self._current_slice[axis], axis=axis
-                ).T
-                self._images["local_max"][axis].set_data(ct_max_data)
+                self._images["local_max"][axis].set_data(
+                    self._ct_maxima[
+                        (slice(None),) * axis + (self._current_slice[axis],)
+                    ].T
+                )
             if draw:
                 self._draw(axis)
 
@@ -1014,7 +1019,9 @@ def _update_mri_images(self, axis=None, draw=False):
         if "mri" in self._images:
             for axis in range(3) if axis is None else [axis]:
                 self._images["mri"][axis].set_data(
-                    np.take(self._mr_data, self._current_slice[axis], axis=axis).T
+                    self._mr_data[
+                        (slice(None),) * axis + (self._current_slice[axis],)
+                    ].T
                 )
                 if draw:
                     self._draw(axis)
@@ -1150,14 +1157,13 @@ def _toggle_show_max(self):
                 self._update_ct_maxima()
             self._images["local_max"] = list()
             for axis in range(3):
-                ct_max_data = np.take(
-                    self._ct_maxima, self._current_slice[axis], axis=axis
-                ).T
                 self._images["local_max"].append(
                     self._figs[axis]
                     .axes[0]
                     .imshow(
-                        ct_max_data,
+                        self._ct_maxima[
+                            (slice(None),) * axis + (self._current_slice[axis],)
+                        ].T,
                         cmap="autumn",
                         aspect="auto",
                         vmin=0,
@@ -1182,13 +1188,18 @@ def _toggle_show_brain(self):
         else:
             self._images["mri"] = list()
             for axis in range(3):
-                mri_data = np.take(
-                    self._mr_data, self._current_slice[axis], axis=axis
-                ).T
                 self._images["mri"].append(
                     self._figs[axis]
                     .axes[0]
-                    .imshow(mri_data, cmap="hot", aspect="auto", alpha=0.25, zorder=2)
+                    .imshow(
+                        self._mr_data[
+                            (slice(None),) * axis + (self._current_slice[axis],)
+                        ].T,
+                        cmap="hot",
+                        aspect="auto",
+                        alpha=0.25,
+                        zorder=2,
+                    )
                 )
             self._toggle_brain_button.setText("Hide Brain")
         self._draw()

mne_gui_addons/_segment.py

@@ -320,7 +320,9 @@ def _update_img_scale(self):
     def _update_base_images(self, axis=None, draw=False):
         """Update the CT image(s)."""
         for axis in range(3) if axis is None else [axis]:
-            img_data = np.take(self._base_data, self._current_slice[axis], axis=axis).T
+            img_data = self._base_data[
+                (slice(None),) * axis + (self._current_slice[axis],)
+            ].T.copy()
             img_data[img_data < self._img_min_slider.value()] = np.nan
             img_data[img_data > self._img_max_slider.value()] = np.nan
             self._images["base"][axis].set_data(img_data)
@@ -335,10 +337,11 @@ def _plot_vol_images(self):
         for axis in range(3):
             fig = self._figs[axis]
             ax = fig.axes[0]
-            vol_data = np.take(self._vol_img, self._current_slice[axis], axis=axis).T
             self._images["vol"].append(
                 ax.imshow(
-                    vol_data,
+                    self._vol_img[
+                        (slice(None),) * axis + (self._current_slice[axis],)
+                    ].T,
                     aspect="auto",
                     zorder=3,
                     cmap=_CMAP,
@@ -438,8 +441,9 @@ def _mark_all(self):
     def _update_vol_images(self, axis=None, draw=False):
         """Update the volume image(s)."""
         for axis in range(3) if axis is None else [axis]:
-            vol_data = np.take(self._vol_img, self._current_slice[axis], axis=axis).T
-            self._images["vol"][axis].set_data(vol_data)
+            self._images["vol"][axis].set_data(
+                self._vol_img[(slice(None),) * axis + (self._current_slice[axis],)].T
+            )
             if draw:
                 self._draw(axis)
 

mne_gui_addons/_vol_stc.py

@@ -306,7 +306,6 @@ def __init__(
         ]
         src_coord = self._get_src_coord()
         for axis in range(3):
-            stc_slice = np.take(self._stc_img, src_coord[axis], axis=axis).T
             x_idx, y_idx = self._xy_idx[axis]
             extent = [
                 corners[0][x_idx],
@@ -318,7 +317,7 @@ def __init__(
                 self._figs[axis]
                 .axes[0]
                 .imshow(
-                    stc_slice,
+                    self._stc_img[(slice(None),) * axis + (src_coord[axis],)].T,
                     aspect="auto",
                     extent=extent,
                     cmap=self._cmap,
@@ -507,7 +506,7 @@ def _apply_vector_norm(self, stc_data, axis=1):
             # if self._data.dtype in (COMPLEX_DTYPE, BASE_INT_DTYPE):
             #    stc_data = stc_data.round().astype(BASE_INT_DTYPE)
         else:
-            stc_data = np.take(stc_data, 0, axis=axis)
+            stc_data = stc_data[(slice(None),) * axis + (0,)]
         return stc_data
 
     def _apply_baseline_correction(self, stc_data):
@@ -541,9 +540,9 @@ def _pick_stc_vertex(self, stc_data):
 
     def _pick_stc_tfr(self, stc_data):
         """Select the frequency and time based on GUI values."""
-        stc_data = np.take(stc_data, self._t_idx, axis=-1)
+        stc_data = stc_data[..., self._t_idx]
         f_idx = 0 if self._f_idx is None else self._f_idx
-        stc_data = np.take(stc_data, f_idx, axis=-1)
+        stc_data = stc_data[..., f_idx]
         return stc_data
 
     def _configure_ui(self):
@@ -1381,10 +1380,13 @@ def _plot_stc_images(self, axis=None, draw=True):
         for axis in range(3):
             # ensure in bounds
             if src_coord[axis] >= 0 and src_coord[axis] < self._stc_img.shape[axis]:
-                stc_slice = np.take(self._stc_img, src_coord[axis], axis=axis).T
+                self._images["stc"][axis].set_data(
+                    self._stc_img[(slice(None),) * axis + (src_coord[axis],)].T
+                )
             else:
-                stc_slice = np.take(self._stc_img, 0, axis=axis).T * np.nan
-            self._images["stc"][axis].set_data(stc_slice)
+                self._images["stc"][axis].set_data(
+                    self._stc_img[(slice(None),) * axis + (0,)].copy().T * np.nan
+                )
             if draw and self._update:
                 self._draw(axis)
 

mne_gui_addons/tests/test_segment.py

@@ -37,9 +37,10 @@ def test_segment_display(renderer_interactive_pyvistaqt):
 
     # test no seghead, fsaverage doesn't have seghead
     with pytest.warns(RuntimeWarning, match="`seghead` not found"):
-        gui = VolumeSegmenter(
-            subject="fsaverage", subjects_dir=subjects_dir, verbose=True
-        )
+        with pytest.warns(RuntimeWarning, match="`pial` surface not found"):
+            gui = VolumeSegmenter(
+                subject="fsaverage", subjects_dir=subjects_dir, verbose=True
+            )
 
     # test functions
     gui.set_RAS([25.37, 0.00, 34.18])

mne_gui_addons/tests/test_vol_stc.py

@@ -57,7 +57,7 @@ def _fake_stc(src_type="vol"):
     ) + 1j * rng.integers(
         -1000, 1000, size=(n_epochs, len(info.ch_names), freqs.size, times.size)
     )
-    epochs_tfr = mne.time_frequency.EpochsTFR(info, data, times=times, freqs=freqs)
+    epochs_tfr = mne.time_frequency.EpochsTFRArray(info, data, times=times, freqs=freqs)
     nuse = sum([this_src["nuse"] for this_src in src])
     stc_data = rng.integers(
         -1000, 1000, size=(n_epochs, nuse, 3, freqs.size, times.size)