adding python wrapper for ICA AROMA

Author: jdkent

nipype/interfaces/fsl/ICA_AROMA.py

@@ -0,0 +1,115 @@
+#ICA_AROMA pulled from: https://github.com/rhr-pruim/ICA-AROMA
+#This assumes ICA_AROMA.py is already installed and callable via $PATH
+from nipype.interfaces.base import (
+    TraitedSpec,
+    CommandLineInputSpec,
+    CommandLine,
+    File,
+    Directory,
+    traits,
+    OutputMultiPath
+)
+import os
+
+class ICA_AROMAInputSpec(CommandLineInputSpec):
+    featDir = Directory(exists=True,
+                        desc='If a feat directory exists and temporal filtering '
+                        'has not been run yet, ICA_AROMA can use the files in '
+                        'this directory.',mandatory=False,xor=['infile','mask','affmat','warp','mc'])
+    infile = File(exists=True, 
+                  desc='volume to be denoised', 
+                  argstr='-i %s',mandatory=False,xor=['featDir'])
+    outdir = Directory(desc='path to output directory', 
+                  argstr='-o %s',mandatory=True)
+    mask = File(exists=True, 
+                desc='path/name volume mask', 
+                argstr='-m %s',mandatory=False,xor=['featDir'])
+    dim = traits.Int(desc='Dimensionality reduction when running '
+                     'MELODIC (defualt is automatic estimation)', 
+                     argstr='-dim %d')
+    TR = traits.Float(desc='TR in seconds. If this is not specified '
+                      'the TR will be extracted from the header of the fMRI nifti file.',
+                      argstr='%.2f')
+    melodic_dir = Directory(exists=True,
+                            desc='path to MELODIC directory if MELODIC has already been ran',
+                            argstr='-meldir %s')
+    affmat = File(exists=True,
+                  desc='path/name of the mat-file describing the '
+                  'affine registration (e.g. FSL FLIRT) of the '
+                  'functional data to structural space (.mat file)',
+                  argstr='-affmat %s',mandatory=False,xor=['featDir'])
+    warp = File(exists=True,
+                desc='File name of the warp-file describing '
+                'the non-linear registration (e.g. FSL FNIRT) '
+                'of the structural data to MNI152 space (.nii.gz)',
+                argstr='-warp %s',mandatory=False,xor=['featDir'])
+    mc = File(exists=True,
+              desc='motion parameters file',
+              argstr='-mc %s',mandatory=False,xor=['featDir'])
+    denoise_type = traits.Str(argstr='-den %s',
+                              desc='Type of denoising strategy: '
+                              '-none: only classification, no denoising '
+                              '-nonaggr (default): non-aggresssive denoising, i.e. partial component regression '
+                              '-aggr: aggressive denoising, i.e. full component regression '
+                              '-both: both aggressive and non-aggressive denoising (two outputs)',
+                              mandatory=True)
+
+class ICA_AROMAOutputSpec(TraitedSpec):
+    out_file = OutputMultiPath(File(exists=True), 
+                               desc='if generated: 1-(non aggressive denoised volume),'
+                               '2-(aggressive denoised volume)')
+   
+class ICA_AROMA(CommandLine):
+    """
+
+    Example
+    -------
+
+    >>> from nipype.interfaces.fsl import ICA_AROMA 
+    >>> AROMA_obj=ICA_AROMA.ICA_AROMA()
+    >>> outDir=os.path.join(os.getcwd(),'ICA_AROMA_testout')
+    >>> func='/path/to/mcImg_brain.nii.gz'
+    >>> affmat='/path/to/functoT1.mat'
+    >>> warp='/path/to/T1toMNI_warp.nii.gz'
+    >>> mc='/path/to/mcImg.par'
+    >>> mask='/path/to/mcImg_mask.nii.gz'
+    >>> denoise_type='both'
+    >>> AROMA_obj.inputs.infile=func
+    >>> AROMA_obj.inputs.affmat=affmat
+    >>> AROMA_obj.inputs.warp=warp
+    >>> AROMA_obj.inputs.mc=mc
+    >>> AROMA_obj.inputs.mask=mask
+    >>> AROMA_obj.inputs.denoise_type=denoise_type
+    >>> AROMA_obj.inputs.outdir=outDir
+    >>> AROMA_obj.cmdline
+    'ICA_AROMA.py -affmat /path/to/functoT1.mat -den both 
+    -i /path/to/mcImg_brain.nii.gz 
+    -m /path/to/mcImg_mask.nii.gz 
+    -mc /path/to/mcImg.par 
+    -o /path/to/ICA_AROMA_testout 
+    -warp /path/to/T1toMNI_warp.nii.gz'
+    >>> AROMA_obj.run()
+
+    """
+    _cmd = 'ICA_AROMA.py'
+    input_spec = ICA_AROMAInputSpec
+    output_spec = ICA_AROMAOutputSpec
+
+    def _list_outputs(self):
+        outputs = self.output_spec.get()
+        outdir = self.input_spec.outdir
+        denoising_strategy = input_spec.denoise_type
+
+        if denoising_strategy is "noaggr":
+          outputs['out_file'] = os.path.join(outdir,'denoised_func_data_nonaggr.nii.gz')
+        elif denoising_strategy is "aggr":
+          outputs['out_file'] = os.path.join(outdir,'denoised_func_data_aggr.nii.gz')
+        elif denoising_strategy is "both":
+          outputs['out_file'] = (os.path.join(outdir,'denoised_func_data_nonaggr.nii.gz'), os.path.join(outdir,'denoised_func_data_aggr.nii.gz'))
+        elif denoising_strategy is "none":
+          print "No denoising selected"
+        else:
+          raise RuntimeError('denoise_type must be specified as one of'
+                             ' noaggr,aggr,both, or none')
+
+        return outputs