Run check. Edit possum to pass test.

FSLOUTTYPE defaults to “nit”, not “nii.gz”.

Author: tsalo

nipype/algorithms/tests/test_auto_CompCor.py

@@ -80,7 +80,7 @@ class B0Calc(FSLCommand):
     >>> b0calc.inputs.in_file = 'tissue+air_map.nii'
     >>> b0calc.inputs.z_b0 = 3.0
     >>> b0calc.cmdline  # doctest: +IGNORE_UNICODE
-    'b0calc -i tissue+air_map.nii -o tissue+air_map_b0field.nii.gz --b0=3.00'
+    'b0calc -i tissue+air_map.nii -o tissue+air_map_b0field.nii --b0=3.00'
 
     """
 

nipype/algorithms/tests/test_auto_ErrorMap.py

@@ -1,42 +1,42 @@
 # AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
 from ...testing import assert_equal
-from ..confounds import TSNR
+from ..nilearn import SignalExtraction
 
 
-def test_TSNR_inputs():
-    input_map = dict(detrended_file=dict(hash_files=False,
+def test_SignalExtraction_inputs():
+    input_map = dict(class_labels=dict(mandatory=True,
+    ),
+    detrend=dict(mandatory=False,
     usedefault=True,
     ),
     ignore_exception=dict(nohash=True,
     usedefault=True,
     ),
     in_file=dict(mandatory=True,
     ),
-    mean_file=dict(hash_files=False,
+    incl_shared_variance=dict(mandatory=False,
     usedefault=True,
     ),
-    regress_poly=dict(),
-    stddev_file=dict(hash_files=False,
+    include_global=dict(mandatory=False,
     usedefault=True,
     ),
-    tsnr_file=dict(hash_files=False,
+    label_files=dict(mandatory=True,
+    ),
+    out_file=dict(mandatory=False,
     usedefault=True,
     ),
     )
-    inputs = TSNR.input_spec()
+    inputs = SignalExtraction.input_spec()
 
     for key, metadata in list(input_map.items()):
         for metakey, value in list(metadata.items()):
             yield assert_equal, getattr(inputs.traits()[key], metakey), value
 
 
-def test_TSNR_outputs():
-    output_map = dict(detrended_file=dict(),
-    mean_file=dict(),
-    stddev_file=dict(),
-    tsnr_file=dict(),
+def test_SignalExtraction_outputs():
+    output_map = dict(out_file=dict(),
     )
-    outputs = TSNR.output_spec()
+    outputs = SignalExtraction.output_spec()
 
     for key, metadata in list(output_map.items()):
         for metakey, value in list(metadata.items()):

nipype/algorithms/tests/test_auto_Overlap.py

@@ -0,0 +1,2 @@
+0.000000 10.000000 1.000000
+10.000000 10.000000 1.000000