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Merge pull request #2164 from TheChymera/whitespace
STY: Removed trailing whitespace
2 parents 9abafec + ca11c52 commit 7ead69d

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nipype/interfaces/afni/preprocess.py

Lines changed: 12 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -119,7 +119,7 @@ class AlignEpiAnatPyOutputSpec(TraitedSpec):
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desc="matrix to volume register and align epi"
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"to anatomy and put into standard space")
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epi_vr_motion = File(
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desc="motion parameters from EPI time-series"
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desc="motion parameters from EPI time-series"
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"registration (tsh included in name if slice"
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"timing correction is also included).")
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skullstrip = File(
@@ -131,20 +131,20 @@ class AlignEpiAnatPy(AFNIPythonCommand):
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an EPI and an anatomical structural dataset, and applies the resulting
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transformation to one or the other to bring them into alignment.
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This script computes the transforms needed to align EPI and
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anatomical datasets using a cost function designed for this purpose. The
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script combines multiple transformations, thereby minimizing the amount of
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This script computes the transforms needed to align EPI and
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anatomical datasets using a cost function designed for this purpose. The
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script combines multiple transformations, thereby minimizing the amount of
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interpolation applied to the data.
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Basic Usage:
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align_epi_anat.py -anat anat+orig -epi epi+orig -epi_base 5
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The user must provide EPI and anatomical datasets and specify the EPI
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sub-brick to use as a base in the alignment.
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sub-brick to use as a base in the alignment.
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Internally, the script always aligns the anatomical to the EPI dataset,
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and the resulting transformation is saved to a 1D file.
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As a user option, the inverse of this transformation may be applied to the
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and the resulting transformation is saved to a 1D file.
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As a user option, the inverse of this transformation may be applied to the
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EPI dataset in order to align it to the anatomical data instead.
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This program generates several kinds of output in the form of datasets
@@ -182,7 +182,7 @@ def _list_outputs(self):
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epi_prefix = ''.join(self._gen_fname(self.inputs.in_file).split('+')[:-1])
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outputtype = self.inputs.outputtype
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if outputtype == 'AFNI':
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ext = '.HEAD'
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ext = '.HEAD'
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else:
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Info.output_type_to_ext(outputtype)
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matext = '.1D'
@@ -620,7 +620,7 @@ class AutoTLRCInputSpec(CommandLineInputSpec):
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mandatory=True,
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exists=True,
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copyfile=False)
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base = traits.Str(
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base = traits.Str(
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desc = ' Reference anatomical volume'
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' Usually this volume is in some standard space like'
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' TLRC or MNI space and with afni dataset view of'
@@ -706,7 +706,7 @@ def _list_outputs(self):
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ext = '.HEAD'
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outputs['out_file'] = os.path.abspath(self._gen_fname(self.inputs.in_file, suffix='+tlrc')+ext)
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return outputs
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class BandpassInputSpec(AFNICommandInputSpec):
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in_file = File(
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desc='input file to 3dBandpass',

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