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seperate file1 and file2
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2 files changed

+19
-9
lines changed

2 files changed

+19
-9
lines changed

nipype/interfaces/afni/tests/test_auto_LocalBistat.py

Lines changed: 7 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -19,7 +19,12 @@ def test_LocalBistat_inputs():
1919
nohash=True,
2020
usedefault=True,
2121
),
22-
in_files=dict(
22+
in_file1=dict(
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argstr='%s',
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mandatory=True,
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position=-2,
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),
27+
in_file2=dict(
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argstr='%s',
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mandatory=True,
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position=-1,
@@ -36,7 +41,7 @@ def test_LocalBistat_inputs():
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out_file=dict(
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argstr='-prefix %s',
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keep_extension=True,
39-
name_source='in_files',
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name_source='in_file1',
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name_template='%s_bistat',
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position=0,
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),

nipype/interfaces/afni/utils.py

Lines changed: 12 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -1339,14 +1339,18 @@ def _list_outputs(self):
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class LocalBistatInputSpec(AFNICommandInputSpec):
1342-
in_files = InputMultiPath(
1343-
File(exists=True),
1344-
minlen=2,
1345-
maxlen=2,
1342+
in_file1 = File(
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exists=True,
1344+
mandatory=True,
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argstr='%s',
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position=-2,
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desc='Filename of the first image')
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in_file2 = File(
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exists=True,
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mandatory=True,
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argstr='%s',
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position=-1,
1349-
desc='Filenames of the 2 images to compute statistics between')
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desc='Filename of the second image')
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neighborhood = traits.Either(
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traits.Tuple(traits.Enum('SPHERE', 'RHDD', 'TOHD'), traits.Float()),
13521356
traits.Tuple(traits.Enum('RECT'), traits.Tuple(traits.Float(),
@@ -1409,7 +1413,7 @@ class LocalBistatInputSpec(AFNICommandInputSpec):
14091413
out_file = traits.File(
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desc='Output dataset.',
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argstr='-prefix %s',
1412-
name_source='in_files',
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name_source='in_file1',
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name_template='%s_bistat',
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keep_extension=True,
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position=0)
@@ -1427,7 +1431,8 @@ class LocalBistat(AFNICommand):
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>>> from nipype.interfaces import afni
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>>> bistat = afni.LocalBistat()
1430-
>>> bistat.inputs.in_files = ['functional.nii', 'structural.nii']
1434+
>>> bistat.inputs.in_file1 = 'functional.nii'
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>>> bistat.inputs.in_file2 = 'structural.nii'
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>>> bistat.inputs.neighborhood = ('SPHERE', 1.2)
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>>> bistat.inputs.stat = 'pearson'
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>>> bistat.inputs.outputtype = 'NIFTI'

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