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WIP: ICA_AROMA.py, adding effigies edits
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‎nipype/interfaces/fsl/ICA_AROMA.py‎

Lines changed: 72 additions & 75 deletions
Original file line numberDiff line numberDiff line change
@@ -12,52 +12,59 @@
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import os
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class ICA_AROMAInputSpec(CommandLineInputSpec):
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featDir = Directory(exists=True,
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feat_dir = Directory(exists=True, mandatory=True,
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argstr='-feat %s',
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xor=['in_file','mat_file','fnirt_warp_file','motion_parameters'],
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desc='If a feat directory exists and temporal filtering '
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'has not been run yet, ICA_AROMA can use the files in '
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'this directory.',mandatory=False,xor=['infile','mask','affmat','warp','mc'])
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infile = File(exists=True,
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desc='volume to be denoised',
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argstr='-i %s',mandatory=False,xor=['featDir'])
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outdir = Directory(desc='path to output directory',
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argstr='-o %s',mandatory=True)
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mask = File(exists=True,
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desc='path/name volume mask',
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argstr='-m %s',mandatory=False,xor=['featDir'])
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dim = traits.Int(desc='Dimensionality reduction when running '
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'MELODIC (defualt is automatic estimation)',
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argstr='-dim %d')
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TR = traits.Float(desc='TR in seconds. If this is not specified '
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'the TR will be extracted from the header of the fMRI nifti file.',
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argstr='%.2f')
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melodic_dir = Directory(exists=True,
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desc='path to MELODIC directory if MELODIC has already been ran',
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argstr='-meldir %s')
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affmat = File(exists=True,
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desc='path/name of the mat-file describing the '
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'affine registration (e.g. FSL FLIRT) of the '
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'functional data to structural space (.mat file)',
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argstr='-affmat %s',mandatory=False,xor=['featDir'])
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warp = File(exists=True,
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desc='File name of the warp-file describing '
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'the non-linear registration (e.g. FSL FNIRT) '
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'of the structural data to MNI152 space (.nii.gz)',
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argstr='-warp %s',mandatory=False,xor=['featDir'])
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mc = File(exists=True,
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desc='motion parameters file',
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argstr='-mc %s',mandatory=False,xor=['featDir'])
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denoise_type = traits.Str(argstr='-den %s',
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'this directory.')
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in_file = File(exists=True, mandatory=True,
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argstr='-i %s', xor=['feat_dir'],
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desc='volume to be denoised')
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out_dir = Directory('out', mandatory=True,
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argstr='-o %s',
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desc='output directory')
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mask = File(exists=True, argstr='-m %s', xor=['feat_dir'],
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desc='path/name volume mask')
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dim = traits.Int(argstr='-dim %d',
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desc='Dimensionality reduction when running '
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'MELODIC (defualt is automatic estimation)')
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TR = traits.Float(argstr='-tr %.3f',
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desc='TR in seconds. If this is not specified '
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'the TR will be extracted from the '
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'header of the fMRI nifti file.')
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melodic_dir = Directory(exists=True, argstr='-meldir %s',
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desc='path to MELODIC directory if MELODIC has already been run')
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mat_file = File(exists=True, mandatory=True,
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argstr='-affmat %s', xor=['feat_dir'],
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desc='path/name of the mat-file describing the '
41+
'affine registration (e.g. FSL FLIRT) of the '
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'functional data to structural space (.mat file)')
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fnirt_warp_file = File(exists=True, mandatory=True,
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argstr='-warp %s', xor=['feat_dir'],
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desc='File name of the warp-file describing '
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'the non-linear registration (e.g. FSL FNIRT) '
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'of the structural data to MNI152 space (.nii.gz)')
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motion_parameters = File(exists=True, mandatory=True,
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argstr='-mc %s', xor=['feat_dir'],
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desc='motion parameters file')
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denoise_type = traits.Enum('nonaggr', 'aggr', 'both', 'no', usedefault=True,
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mandatory=True, argstr='-den %s',
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desc='Type of denoising strategy: '
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'-none: only classification, no denoising '
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'-nonaggr (default): non-aggresssive denoising, i.e. partial component regression '
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'-aggr: aggressive denoising, i.e. full component regression '
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'-both: both aggressive and non-aggressive denoising (two outputs)',
55-
mandatory=True)
57+
'-both: both aggressive and non-aggressive denoising (two outputs)')
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5759
class ICA_AROMAOutputSpec(TraitedSpec):
58-
out_file = OutputMultiPath(File(exists=True),
59-
desc='if generated: 1-(non aggressive denoised volume),'
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'2-(aggressive denoised volume)')
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aggr_denoised_file=File(exists=True,
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desc='if generated: aggressively denoised volume')
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nonaggr_denoised_file=File(exists=True,
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desc='if generated: non aggressively denoised volume' )
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out_dir = Directory(exists=True,
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desc='directory contains (in addition to the denoised files): '
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'melodic.ica + classified_motion_components + '
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'classification_overview + feature_scores + melodic_ic_mni)')
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6269
class ICA_AROMA(CommandLine):
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"""
@@ -66,50 +73,40 @@ class ICA_AROMA(CommandLine):
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-------
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>>> from nipype.interfaces.fsl import ICA_AROMA
69-
>>> AROMA_obj=ICA_AROMA.ICA_AROMA()
70-
>>> outDir=os.path.join(os.getcwd(),'ICA_AROMA_testout')
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>>> func='/path/to/mcImg_brain.nii.gz'
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>>> affmat='/path/to/functoT1.mat'
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>>> warp='/path/to/T1toMNI_warp.nii.gz'
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>>> mc='/path/to/mcImg.par'
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>>> mask='/path/to/mcImg_mask.nii.gz'
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>>> denoise_type='both'
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>>> AROMA_obj.inputs.infile=func
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>>> AROMA_obj.inputs.affmat=affmat
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>>> AROMA_obj.inputs.warp=warp
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>>> AROMA_obj.inputs.mc=mc
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>>> AROMA_obj.inputs.mask=mask
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>>> AROMA_obj.inputs.denoise_type=denoise_type
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>>> AROMA_obj.inputs.outdir=outDir
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>>> from nipype.testing import example_data
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>>> AROMA_obj = ICA_AROMA.ICA_AROMA()
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>>> AROMA_obj.inputs.in_file=example_data('functional.nii')
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>>> AROMA_obj.inputs.mat_file=example_data('func_to_struct.mat')
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>>> AROMA_obj.inputs.fnirt_warp_file=example_data('warpfield.nii')
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>>> AROMA_obj.inputs.motion_parameters=example_data('functional.par')
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>>> AROMA_obj.inputs.mask=example_data('mask.nii.gz')
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>>> AROMA_obj.inputs.denoise_type='both'
84+
>>> AROMA_obj.inputs.out_dir='ICA_testout'
8485
>>> AROMA_obj.cmdline
85-
'ICA_AROMA.py -affmat /path/to/functoT1.mat -den both
86-
-i /path/to/mcImg_brain.nii.gz
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-m /path/to/mcImg_mask.nii.gz
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-mc /path/to/mcImg.par
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-o /path/to/ICA_AROMA_testout
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-warp /path/to/T1toMNI_warp.nii.gz'
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>>> AROMA_obj.run()
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'ICA_AROMA.py -den both
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-warp /home/james/dev/nipype/nipype/testing/data/warpfield.nii
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-i /home/james/dev/nipype/nipype/testing/data/functional.nii
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-m /home/james/dev/nipype/nipype/testing/data/mask.nii.gz
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-affmat /home/james/dev/nipype/nipype/testing/data/func_to_struct.mat
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-mc /home/james/dev/nipype/nipype/testing/data/functional.par
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-o ICA_testout'
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"""
9495
_cmd = 'ICA_AROMA.py'
9596
input_spec = ICA_AROMAInputSpec
9697
output_spec = ICA_AROMAOutputSpec
9798

9899
def _list_outputs(self):
99-
outputs = self.output_spec.get()
100-
outdir = self.input_spec.outdir
101-
denoising_strategy = input_spec.denoise_type
102100

103-
if denoising_strategy is "noaggr":
104-
outputs['out_file'] = os.path.join(outdir,'denoised_func_data_nonaggr.nii.gz')
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elif denoising_strategy is "aggr":
106-
outputs['out_file'] = os.path.join(outdir,'denoised_func_data_aggr.nii.gz')
107-
elif denoising_strategy is "both":
108-
outputs['out_file'] = (os.path.join(outdir,'denoised_func_data_nonaggr.nii.gz'), os.path.join(outdir,'denoised_func_data_aggr.nii.gz'))
109-
elif denoising_strategy is "none":
110-
print "No denoising selected"
111-
else:
112-
raise RuntimeError('denoise_type must be specified as one of'
113-
' noaggr,aggr,both, or none')
101+
out_dir = os.path.abspath(self.inputs.out_dir)
102+
outputs['out_dir'] = out_dir
103+
#outputs = self.output_spec.get()
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#outdir = self.input_spec.outdir
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#denoising_strategy = input_spec.denoise_type
114106

115-
return outputs
107+
if self.inputs.denoise_type in ('aggr', 'both'):
108+
outputs['aggr_denoised_file'] = os.path.join(out_dir, 'denoised_func_data_aggr.nii.gz')
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if self.inputs.denoise_type in ('nonaggr', 'both'):
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outputs['nonaggr_denoised_file'] = os.path.join(out_dir, 'denoised_func_data_nonaggr.nii.gz')
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return outputs

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