added tests

Author: chrisgorgo

nipype/interfaces/fsl/tests/test_auto_MotionOutliers.py

@@ -0,0 +1,65 @@
+# AUTO-GENERATED by tools/checkspecs.py - DO NOT EDIT
+from nipype.testing import assert_equal
+from nipype.interfaces.fsl.utils import MotionOutliers
+
+def test_MotionOutliers_inputs():
+    input_map = dict(args=dict(argstr='%s',
+    ),
+    dummy=dict(argstr='--dummy=%d',
+    ),
+    environ=dict(nohash=True,
+    usedefault=True,
+    ),
+    ignore_exception=dict(nohash=True,
+    usedefault=True,
+    ),
+    in_file=dict(argstr='-i %s',
+    mandatory=True,
+    ),
+    mask=dict(argstr='-m %s',
+    ),
+    metric=dict(argstr='--%s',
+    ),
+    no_motion_correction=dict(argstr='--nomoco',
+    ),
+    out_file=dict(argstr='-o %s',
+    hash_files=False,
+    keep_extension=True,
+    name_source='in_file',
+    name_template='%s_outliers.txt',
+    ),
+    out_metric_plot=dict(argstr='-p %s',
+    hash_files=False,
+    keep_extension=True,
+    name_source='in_file',
+    name_template='%s_metrics.png',
+    ),
+    out_metric_values=dict(argstr='-s %s',
+    hash_files=False,
+    keep_extension=True,
+    name_source='in_file',
+    name_template='%s_metrics.txt',
+    ),
+    output_type=dict(),
+    terminal_output=dict(nohash=True,
+    ),
+    threshold=dict(argstr='--thresh=%g',
+    ),
+    )
+    inputs = MotionOutliers.input_spec()
+
+    for key, metadata in input_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(inputs.traits()[key], metakey), value
+
+def test_MotionOutliers_outputs():
+    output_map = dict(out_file=dict(),
+    out_metric_plot=dict(),
+    out_metric_values=dict(),
+    )
+    outputs = MotionOutliers.output_spec()
+
+    for key, metadata in output_map.items():
+        for metakey, value in metadata.items():
+            yield assert_equal, getattr(outputs.traits()[key], metakey), value
+

nipype/interfaces/fsl/utils.py

@@ -2005,6 +2005,7 @@ class MotionOutliersOutputSpec(TraitedSpec):
     out_metric_values = File(exists=True)
     out_metric_plot = File(exists=True)
 
+
 class MotionOutliers(FSLCommand):
     """
     Use FSL fsl_motion_outliers`http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLMotionOutliers`_ to find outliers in timeseries (4d) data.