Scripts used to generate the mappings to surface.

scripts/compute_fsaverage_mapping_part1.py

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+import os
+import numpy as np
+
+from brainplotlib3d import ValuesIcoorder, Surface, plot_to_file
+
+
+if __name__ == '__main__':
+    # nv = 1175  # 588 + 587
+    nv = 4**7 * 10 + 2
+    v = np.arange(nv * 2, dtype=int)
+    c1 = v // 256 **2
+    c2 = (v // 256) % 256
+    c3 = v % 256
+    c = np.stack([c1, c2, c3], axis=1) / 255.
+    v = np.array_split(c, 2, axis=0)
+    values = ValuesIcoorder(v[0], v[1], fill_nan=0.8, space='fsaverage', icoorder=7)
+
+    for surf_type in ['inflated', 'pial', 'midthickness', 'white']:
+        out_fn = f'fsaverage_{surf_type}.npy'
+        if os.path.exists(out_fn):
+            continue
+
+        zoom = 0.015
+        if surf_type == 'inflated':
+            zoom = 0.013
+
+        surf = Surface(surf_type, 'FS')
+        surf.add_colors(values)
+        actors = surf.get_actors(ambient=1, diffuse=0, specular=0)
+
+        img = plot_to_file([actors[0]], [actors[1]],
+                    surf.focal_points, out_fn=None,
+                    zoom=zoom, magnification=1, aa_frames=1)
+        np.save(out_fn, img)
+        exit(0)

scripts/compute_fsaverage_mapping_part2.py

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+import cv2
+import numpy as np
+
+
+if __name__ == '__main__':
+    for surf_type in ['inflated', 'pial', 'midthickness', 'white']:
+        img = np.load(f'fsaverage_{surf_type}.npy')
+        nv = 4**7 * 10 + 2
+        mask = (img[:, :, 3] == 0.0)
+        img = np.round(img[:, :, :3] * 255).astype(int)
+        v = ((img[:, :, 0] * 256**2) + (img[:, :, 1] * 256) + img[:, :, 2])
+        print(v.shape, mask.shape)
+        v[mask] = -1
+        np.save(f'fsaverage_to_{surf_type}_image.npy', v)
+        print(v.max(), v.min(), np.unique(v).shape)