fix outputs

Author: Shoshana Berleant

nipype/interfaces/fsl/preprocess.py

@@ -323,17 +323,20 @@ def _list_outputs(self):
             nclasses = self.inputs.number_classes
         # when using multichannel, results basename is based on last
         # input filename
+        _gen_fname_opts = {}
         if isdefined(self.inputs.out_basename):
-            basefile = self.inputs.out_basename
+            _gen_fname_opts['basename'] = self.inputs.out_basename
+            _gen_fname_opts['cwd'] = os.getcwd()
         else:
-            basefile = self.inputs.in_files[-1]
+            _gen_fname_opts['basename'] = self.inputs.in_files[-1]
+            _gen_fname_opts['cwd'], _, _ = split_filename(_gen_fname_opts['basename'])
 
-        outputs['tissue_class_map'] = self._gen_fname(basefile, suffix='_seg')
+        outputs['tissue_class_map'] = self._gen_fname(suffix='_seg', **_gen_fname_opts)
         if self.inputs.segments:
             outputs['tissue_class_files'] = []
             for i in range(nclasses):
                 outputs['tissue_class_files'].append(
-                    self._gen_fname(basefile, suffix='_seg_%d' % i))
+                    self._gen_fname(suffix='_seg_%d' % i, **_gen_fname_opts))
         if isdefined(self.inputs.output_biascorrected):
             outputs['restored_image'] = []
             if len(self.inputs.in_files) > 1:
@@ -342,22 +345,21 @@ def _list_outputs(self):
                 for val, f in enumerate(self.inputs.in_files):
                     # image numbering is 1-based
                     outputs['restored_image'].append(
-                        self._gen_fname(basefile,
-                                        suffix='_restore_%d' % (val + 1)))
+                        self._gen_fname(suffix='_restore_%d' % (val + 1), **_gen_fname_opts))
             else:
                 # single image segmentation has unnumbered output image
                 outputs['restored_image'].append(
-                    self._gen_fname(basefile, suffix='_restore'))
+                    self._gen_fname(suffix='_restore', **_gen_fname_opts))
 
-        outputs['mixeltype'] = self._gen_fname(basefile, suffix='_mixeltype')
+        outputs['mixeltype'] = self._gen_fname(suffix='_mixeltype', **_gen_fname_opts)
         if not self.inputs.no_pve:
             outputs['partial_volume_map'] = self._gen_fname(
-                basefile, suffix='_pveseg')
+                suffix='_pveseg', **_gen_fname_opts)
             outputs['partial_volume_files'] = []
             for i in range(nclasses):
                 outputs[
                     'partial_volume_files'].append(
-                        self._gen_fname(basefile, suffix='_pve_%d' % i))
+                        self._gen_fname(suffix='_pve_%d' % i, **_gen_fname_opts))
         if self.inputs.output_biasfield:
             outputs['bias_field'] = []
             if len(self.inputs.in_files) > 1:
@@ -366,18 +368,17 @@ def _list_outputs(self):
                 for val, f in enumerate(self.inputs.in_files):
                     # image numbering is 1-based
                     outputs['bias_field'].append(
-                        self._gen_fname(basefile,
-                                        suffix='_bias_%d' % (val + 1)))
+                        self._gen_fname(suffix='_bias_%d' % (val + 1), **_gen_fname_opts))
             else:
                 # single image segmentation has unnumbered output image
                 outputs['bias_field'].append(
-                    self._gen_fname(basefile, suffix='_bias'))
+                    self._gen_fname(suffix='_bias', **_gen_fname_opts))
 
         if self.inputs.probability_maps:
             outputs['probability_maps'] = []
             for i in range(nclasses):
                 outputs['probability_maps'].append(
-                    self._gen_fname(basefile, suffix='_prob_%d' % i))
+                    self._gen_fname(suffix='_prob_%d' % i, **_gen_fname_opts))
         return outputs
 
 

nipype/interfaces/fsl/tests/test_preprocess.py

@@ -12,7 +12,7 @@
 from nipype.testing import (assert_equal, assert_not_equal, assert_raises,
                             skipif)
 
-from nipype.utils.filemanip import split_filename
+from nipype.utils.filemanip import split_filename, filename_to_list
 from .. import preprocess as fsl
 from nipype.interfaces.fsl import Info
 from nipype.interfaces.base import File, TraitError, Undefined, isdefined
@@ -174,15 +174,18 @@ def test_fast_list_outputs():
     the cwd '''
     def _run_and_test(opts, output_base):
         outputs = fsl.FAST(**opts)._list_outputs()
-        assert_equal(output_base, outputs['tissue_class_map'][:len(output_base)])
-        assert_true(False)
+        for output in outputs.values():
+            filenames = filename_to_list(output)
+            if filenames is not None:
+                for filename in filenames:
+                    assert_equal(filename[:len(output_base)], output_base)
 
     # set up
     infile, indir = setup_infile()
     cwd = tempfile.mkdtemp()
     os.chdir(cwd)
     yield assert_not_equal, indir, cwd
-    out_basename = 'a_basename.nii.gz'
+    out_basename = 'a_basename'
 
     # run and test
     opts = {'in_files': tmp_infile}