refactoring & testing in preparation for 4d label files; pep8

Author: Shoshana Berleant

nipype/algorithms/stats.py

@@ -13,7 +13,6 @@
 '''
 from __future__ import (print_function, division, unicode_literals,
                         absolute_import)
-from builtins import str
 
 import numpy as np
 
@@ -71,11 +70,7 @@ def _run_interface(self, runtime):
         ins = self.inputs
 
         if ins.stat == 'mean': # always true for now
-            nlmasker = nl.NiftiLabelsMasker(ins.label_file,
-                                            detrend=ins.detrend)
-            nlmasker.fit()
-            region_signals = nlmasker.transform_single_imgs(ins.in_file)
-
+            region_signals = self._3d_label_handler(nl, ins)
             num_labels_found = region_signals.shape[1]
             if len(ins.class_labels) != num_labels_found:
                 raise ValueError('The length of class_labels {} does not '
@@ -90,6 +85,13 @@ def _run_interface(self, runtime):
             np.savetxt(ins.out_file, output, fmt=b'%s', delimiter='\t')
         return runtime
 
+    def _3d_label_handler(self, nl, ins):
+        nlmasker = nl.NiftiLabelsMasker(ins.label_file,
+                                        detrend=ins.detrend)
+        nlmasker.fit()
+        region_signals = nlmasker.transform_single_imgs(ins.in_file)
+        return region_signals
+
     def _list_outputs(self):
         outputs = self._outputs().get()
         outputs['out_file'] = self.inputs.out_file

nipype/algorithms/tests/test_stats.py

@@ -13,7 +13,7 @@
 
 no_nilearn = True
 try:
-    import nilearn
+    __import__('nilearn')
     no_nilearn = False
 except ImportError:
     pass
@@ -23,6 +23,7 @@ class TestSignalExtraction(unittest.TestCase):
     filenames = {
         'in_file': 'fmri.nii',
         'label_file': 'labels.nii',
+        '4d_label_file': '4dlabels.nii',
         'out_file': 'signals.tsv'
     }
 
@@ -70,6 +71,11 @@ def test_signal_extraction_bad_class_labels(self):
                                label_file=self.filenames['label_file'],
                                class_labels=['bad']).run()
 
+    @skipif(no_nilearn)
+    def test_signal_extraction_4d_label(self):
+        # setup
+        utils.save_toy_nii(self.fake_4d_label_data, self.filenames['4d_label_file'])
+
     def tearDown(self):
         os.chdir(self.orig_dir)
         shutil.rmtree(self.temp_dir)
@@ -92,3 +98,16 @@ def tearDown(self):
 
                                 [[2, 0],
                                  [1, 3]]])
+
+    fake_4d_label_data = np.array([[[[0.2, 0.3, 0.5],
+                                     [0.1, 0.1, 0.8]],
+
+                                    [[0.1, 0.3, 0.6],
+                                     [0.3, 0.4, 0.3]]],
+
+
+                                   [[[0.2, 0.2, 0.6],
+                                     [0., 0.3, 0.7]],
+
+                                    [[0.3, 0.3, 0.4],
+                                     [0.3, 0.4, 0.3]]]])