fix, change to calling dipy directly

mne/gui/_ieeg_locate_gui.py

@@ -126,7 +126,7 @@ def __init__(self, info, trans, aligned_ct, subject=None,
         self._subject_dir = _check_subject_dir(subject, subjects_dir)
         self._load_image_data(aligned_ct)
 
-        self._radius = int(_CH_PLOT_SIZE // 100)
+        self._radius = int(_CH_PLOT_SIZE // 50)
         # initialize channel data
         self._ch_index = 0
         # load data, apply trans
@@ -304,6 +304,7 @@ def _plot_images(self):
         self._ct_cutoff = int(round(ct_min))
         text_kwargs = dict(fontsize=3, color='#66CCEE', family='monospace',
                            weight='bold', ha='center', va='center')
+        xyz = apply_trans(self._ras_vox_t, self._ras)
         for axis in range(3):
             self._plts[axis]._ax.clear()
             ct_data = np.take(self._ct_data, self._current_slice[axis],
@@ -319,13 +320,11 @@ def _plot_images(self):
                     cmap=_CMAP, alpha=self._ch_alpha, vmin=0, vmax=_N_COLORS))
             self._images['cursor'].append(
                 self._plts[axis]._ax.plot(
-                    (self._ras[axis], self._ras[axis]),
-                    (0, self._voxel_sizes[axis]),
+                    (xyz[axis], xyz[axis]), (0, self._voxel_sizes[axis]),
                     color=[0, 1, 0], linewidth=0.25, alpha=0.5)[0])
             self._images['cursor2'].append(
                 self._plts[axis]._ax.plot(
-                    (0, self._voxel_sizes[axis]),
-                    (self._ras[axis], self._ras[axis]),
+                    (0, self._voxel_sizes[axis]), (xyz[axis], xyz[axis]),
                     color=[0, 1, 0], linewidth=0.25, alpha=0.5)[0])
             # label axes
             self._plts[axis]._fig.text(0.5, 0.05, _IMG_LABELS[axis][0],
@@ -457,7 +456,7 @@ def make_slider(smin, smax, sval, sfun=None):
         ch_slider_vbox = QVBoxLayout()
         self._alpha_slider = make_slider(0, 100, self._ch_alpha * 100,
                                          self._update_ch_alpha)
-        ch_plot_max = int(np.mean(_CH_PLOT_SIZE) // 50)
+        ch_plot_max = _CH_PLOT_SIZE // 25  # max 1 / 25 of plot size
         ch_slider_vbox.addWidget(self._alpha_slider)
         self._radius_slider = make_slider(0, ch_plot_max, self._radius,
                                           self._update_radius)
@@ -596,7 +595,7 @@ def _update_ch_selection(self):
         self._group_selector.setCurrentIndex(self._groups[name])
         self._update_group()
         if not np.isnan(self._chs[name]).any():
-            self._ras = self._chs[name]
+            self._ras[:] = self._chs[name]
             self._move_cursors_to_pos()
             self._draw()
 
@@ -672,7 +671,7 @@ def _color_list_item(self, name=None):
     @pyqtSlot()
     def _mark_ch(self):
         """Mark the current channel as being located at the crosshair."""
-        self._chs[self._ch_names[self._ch_index]] = self._ras
+        self._chs[self._ch_names[self._ch_index]][:] = self._ras
         self._color_list_item()
         self._update_ch_images(draw=True)
         self._save_ch_coords()
@@ -696,8 +695,8 @@ def _update_ch_images(self, axis=None, draw=False):
         for axis in range(3) if axis is None else [axis]:
             self._images['chs'][axis].set_data(
                 self._make_ch_image(axis))
-        if draw:
-            self._draw(axis)
+            if draw:
+                self._draw(axis)
 
     def _update_ct_images(self, axis=None, draw=False):
         """Update the CT image(s)."""
@@ -708,8 +707,8 @@ def _update_ct_images(self, axis=None, draw=False):
             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 draw:
-            self._draw(axis)
+            if draw:
+                self._draw(axis)
 
     def _update_images(self, axis=None, draw=True):
         """Update CT and channel images when general changes happen."""

tutorials/clinical/10_ieeg_localize.py

@@ -35,7 +35,7 @@
 
 import nibabel as nib
 import nilearn.plotting
-from dipy.align import resample
+from dipy.align import resample, 
 
 import mne
 from mne.datasets import fetch_fsaverage
@@ -127,8 +127,12 @@ def plot_overlay(image, compare, title, thresh=None):
 # This takes a while (~10 minutes) to execute so we skip actually running it
 # here::
 #
-#    reg_affine, _ = mne.transforms.compute_volume_registration(
-#        CT_orig, T1, pipeline='rigids', verbose=True)
+#    from dipy.align import center_of_mass, translation, rigid
+#    reg_data, reg_affine = dipy.align.affine_registration(
+#         moving=np.array(CT_orig.dataobj), moving_affine=CT_orig.affine,
+#         static=np.array(T1.dataobj), static_affine=T1.affine,
+#         pipeline=[center_of_mass, translation, rigid])
+#    CT_aligned = nib.MGHImage(reg_data.astype(np.float32), T1.affine)
 #
 # And instead we just hard-code the resulting 4x4 matrix: