few more changes to correct calculation of number of voxels in mask

make_image_from_bin.py

@@ -84,8 +84,9 @@ def make_image_from_bin( image, binfile, mask ):
     print "sum",sum(imdat)
 
     # map the binary data to mask
-    print "shape2",shape(a[0:sum(imdat)])
-    imdat[imdat>0]=short(a[0:sum(imdat)].flatten())
+    mask_voxels=(imdat.flatten()>0).sum()
+    print "shape2",shape(a[0:mask_voxels])
+    imdat[imdat>0]=short(a[0:mask_voxels].flatten())
 
     # write out the image as nifti
     thdr=nim.get_header()

pyClusterROI_test.py

@@ -159,8 +159,8 @@
 # random clustering
 
 # for both group-mean and 2-level clustering we need to know the number of
-# voxels in in the mask, which for us is 32254 
-mask_voxels=18377#31146
+# nonzero voxels in in the mask 
+mask_voxels=(nb.load(maskname).get_data().flatten()>0).sum()
 
 # group_mean clustering is pretty simple, input the connectivity files and run.
 # we can perform multiple clusterings with this function, so once again the
@@ -171,7 +171,6 @@
 group_mean_binfile_parcellate( tcorr_conn_files,\
     'rm_group_mean_tcorr_cluster', NUM_CLUSTERS,mask_voxels);
 
-
 # now group mean cluster scorr files
 scorr_conn_files=['rm_scorr_conn_0.npy','rm_scorr_conn_1.npy',\
     'rm_scorr_conn_2.npy']