FIX: bugfix to replace np.unique() with _unique_rows() for 2D inputs needed for sorting vector properties. proper 2D ndarray to list of lists for JSON export in parrec2nii

Author: grlee77

bin/parrec2nii

@@ -9,6 +9,7 @@ import numpy.linalg as npl
 import sys
 import os
 import json
+from copy import deepcopy
 import nibabel
 import nibabel.parrec as pr
 from nibabel.parrec import one_line
@@ -134,6 +135,24 @@ def error(msg, exit_code):
     sys.exit(exit_code)
 
 
+def sort_info_to_lists(sort_info):
+    sort_info = deepcopy(sort_info)
+    # convert from elements from numpy array to lists for easy JSON export
+    for key in sort_info:
+        ndim = sort_info[key].ndim
+        if ndim == 1:
+            sort_info[key] = list(sort_info[key])
+        elif ndim == 2:
+            k = sort_info[key]
+            k_list = []
+            for row in range(k.shape[0]):
+                k_list.append(list(k[row]))
+            sort_info[key] = k_list
+        else:
+            raise ValueError("only 1D and 2D arrays supported")
+    return sort_info
+
+
 def proc_file(infile, opts):
     # figure out the output filename, and see if it exists
     basefilename = splitext_addext(os.path.basename(infile))[0]
@@ -265,15 +284,15 @@ def proc_file(infile, opts):
 
     opts.dim_info = True  # TODO: remove hard-coded value
     if opts.dim_info and pr_img.dataobj._dim_4_labels is not None:
-        if len(list(pr_img.dataobj._dim_4_labels.keys())) > 0:
-            with open(basefilename + '.ordering.json', 'w') as fid:
-                json.dump(pr_img.dataobj._dim_4_labels, fid, sort_keys=True,
-                          indent=4)
+        labels = pr_img.dataobj._dim_4_labels
     elif opts.dim_info and pr_img.dataobj._dim_3_4_labels is not None:
-        if len(list(pr_img.dataobj._dim_3_4_labels.keys())) > 0:
-            with open(basefilename + '.ordering.json', 'w') as fid:
-                json.dump(pr_img.dataobj._dim_3_4_labels, fid, sort_keys=True,
-                          indent=4)
+        labels = pr_img.dataobj._dim_3_4_labels
+    else:
+        labels = None
+    if labels is not None and len(labels) > 0:
+        sort_info = sort_info_to_lists(labels)
+        with open(basefilename + '.ordering.json', 'w') as fid:
+            json.dump(sort_info, fid, sort_keys=True, indent=4)
 
     # write out dwell time if requested
     if opts.dwell_time:

nibabel/parrec.py

@@ -249,6 +249,18 @@ class PARRECError(Exception):
 GEN_RE = re.compile(r".\s+(.*?)\s*:\s*(.*)")
 
 
+def _unique_rows(a):
+    """
+    find unique rows of a 2D array.  based on discussion at:
+    http://stackoverflow.com/questions/16970982/find-unique-rows-in-numpy-array
+    """
+    if a.ndim != 2:
+        raise ValueError("expected 2D input")
+    b = np.ascontiguousarray(a).view(
+            np.dtype((np.void, a.dtype.itemsize * a.shape[1])))
+    return np.unique(b).view(a.dtype).reshape(-1, a.shape[1])
+
+
 def _split_header(fobj):
     """ Split header into `version`, `gen_dict`, `image_lines` """
     version = None
@@ -1171,8 +1183,17 @@ def sorted_labels(self, sorted_indices=None, collapse_slices=True):
             dynamic_keys.remove('slice number')
 
         non_unique_keys = []
+
         for key in dynamic_keys:
-            if len(np.unique(self.image_defs[key])) > 1:
+            ndim = self.image_defs[key].ndim
+            if ndim == 1:
+                num_unique = len(np.unique(self.image_defs[key]))
+            elif ndim == 2:
+                # for 2D cases, e.g. 'image angulation'
+                num_unique = len(_unique_rows(self.image_defs[key]))
+            else:
+                raise ValueError("unexpected image_defs shape > 2D")
+            if num_unique > 1:
                 non_unique_keys.append(key)
 
         if collapse_slices:
@@ -1189,13 +1210,11 @@ def sorted_labels(self, sorted_indices=None, collapse_slices=True):
 
         sort_info = {}
         for key in non_unique_keys:
+
             if collapse_slices:
-                sort_info[key] = list(
-                    self.image_defs[key][sorted_indices][sl1_indices])
+                sort_info[key] = self.image_defs[key][sorted_indices][sl1_indices]
             else:
-                sort_info[key] = list(
-                    self.image_defs[key][sorted_indices])
-
+                sort_info[key] = self.image_defs[key][sorted_indices]
         return sort_info