fleshed out review section and added save hooks

Author: noahbenson

config/config.yaml

@@ -112,11 +112,12 @@ targets:
   # from the sections above.
   cortex: |
     # Extract the subject object and the hsmisphere name.
+    sid = target['Subject ID']
     sub = target['subject']
     h = target['Hemisphere'].lower()
     # Load retinotopic mapping data from the label directory, where these data
     # are stored on the NSD repository.
-    label_path = nsd_path.subpath('freesurfer', sub, 'label')
+    label_path = nsd_path.subpath('freesurfer', sid, 'label')
     props = {
         k: ny.load(label_path.subpath(f'{h}.{filename}'))
         for (k,filename) in nsd_prf_files.items()}
@@ -290,42 +291,59 @@ review: |
   #im = watershed_contours(annotations.values(), max_depth=1)
   #axes.imshow(im, cmap='hsv', vmin=0, vmax=1.5*np.max(im))
   import numpy as np
-  from matplotlib.pyplot import Polygon
   # V1:
   v1uvm = annotations['V1 UVM (ventral)']
   v1lvm = annotations['V1 LVM (dorsal)']
   v1per = annotations['V1 Periphery']
-  v1pol = Polygon(
-      np.vstack([v1uvm, v1per, np.flipud(v1lvm)]),
-      closed=True,
-      color='red',
-      alpha=0.5,
-      fill=True)
-  axes.add_patch(v1pol)
+  v1pol = np.vstack([v1uvm, v1per, np.flipud(v1lvm)])
   # V2:
   v2uvm = annotations['V2 UVM (ventral)']
   v2lvm = annotations['V2 LVM (dorsal)']
   v2pev = annotations['V2 Ventral Periphery']
   v2ped = annotations['V2 Dorsal Periphery']
-  v2pol = Polygon(
-      np.vstack(
-          [v2uvm, v2pev, np.flipud(v1uvm), v1lvm, v2ped, np.flipud(v2lvm)]),
-      closed=True,
-      color='cyan',
-      alpha=0.5,
-      fill=True)
-  axes.add_patch(v2pol)
+  v2pol = np.vstack(
+      [v2uvm, v2pev, np.flipud(v1uvm), v1lvm, np.flipud(v2ped), np.flipud(v2lvm)])
   # V3:
   v3uvm = annotations['V3 UVM (ventral)']
   v3lvm = annotations['V3 LVM (dorsal)']
   v3pev = annotations['V3 Ventral Periphery']
   v3ped = annotations['V3 Dorsal Periphery']
-  v3pol = Polygon(
-      np.vstack(
-          [v3uvm, v3pev, np.flipud(v2uvm), v2lvm, v3ped, np.flipud(v3lvm)]),
-      color='black',
-      alpha=0.5,
-      closed=True)
-  axes.add_patch(v3pol)
+  v3pol = np.vstack(
+      [v3uvm, v3pev, np.flipud(v2uvm), v2lvm, np.flipud(v3ped), np.flipud(v3lvm)])
+  # Turn these into traces:
+  fmap = target['flatmap']
+  v1_trace = ny.path_trace(fmap, v1pol.T, closed=True)
+  v2_trace = ny.path_trace(fmap, v2pol.T, closed=True)
+  v3_trace = ny.path_trace(fmap, v3pol.T, closed=True)
+  # Convert the path traces into paths then into labels:
+  cortex = target['cortex']
+  v1_path = v1_trace.to_path(cortex)
+  v2_path = v2_trace.to_path(cortex)
+  v3_path = v3_trace.to_path(cortex)
+  v1 = v1_path.label > 0.5
+  v2 = v2_path.label > 0.5
+  v3 = v3_path.label > 0.5
+  if np.sum(v1) > np.sum(~v1):
+    v1 = ~v1
+  if np.sum(v2) > np.sum(~v2):
+    v2 = ~v2
+  if np.sum(v3) > np.sum(~v3):
+    v3 = ~v3
+  labels = np.zeros(cortex.vertex_count, dtype=int)
+  labels[v1] = 1
+  labels[v2] = 2
+  labels[v3] = 3
+  fmap_labels = labels[fmap.labels]
+  # If the user saves the contours, we want to save these labels.
+  save_hooks['v123-labels.mgz'] = lambda filename: ny.save(filename, labels)
+  # Plot the results:
+  ny.cortex_plot(
+      fmap,
+      color=fmap_labels,
+      cmap='rainbow',
+      mask=(fmap_labels > 0),
+      axes=axes,
+      alpha=0.5)
   axes.axis('equal')
   axes.axis('off')
+