.. AUTO-GENERATED FILE -- DO NOT EDIT!

interfaces.fsl.aroma
====================


.. _nipype.interfaces.fsl.aroma.ICA_AROMA:


.. index:: ICA_AROMA

ICA_AROMA
---------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/fsl/aroma.py#L98>`__

Wraps the executable command ``ICA_AROMA.py``.

Interface for the ICA_AROMA.py script.

ICA-AROMA (i.e. 'ICA-based Automatic Removal Of Motion Artifacts') concerns
a data-driven method to identify and remove motion-related independent
components from fMRI data. To that end it exploits a small, but robust
set of theoretically motivated features, preventing the need for classifier
re-training and therefore providing direct and easy applicability.

See link for further documentation: https://github.com/rhr-pruim/ICA-AROMA

Example
~~~~~~~

>>> from nipype.interfaces.fsl import ICA_AROMA
>>> from nipype.testing import example_data
>>> AROMA_obj = ICA_AROMA()
>>> AROMA_obj.inputs.in_file = 'functional.nii'
>>> AROMA_obj.inputs.mat_file = 'func_to_struct.mat'
>>> AROMA_obj.inputs.fnirt_warp_file = 'warpfield.nii'
>>> AROMA_obj.inputs.motion_parameters = 'fsl_mcflirt_movpar.txt'
>>> AROMA_obj.inputs.mask = 'mask.nii.gz'
>>> AROMA_obj.inputs.denoise_type = 'both'
>>> AROMA_obj.inputs.out_dir = 'ICA_testout'
>>> AROMA_obj.cmdline  # doctest: +ELLIPSIS
'ICA_AROMA.py -den both -warp warpfield.nii -i functional.nii -m mask.nii.gz -affmat func_to_struct.mat -mc fsl_mcflirt_movpar.txt -o .../ICA_testout'

Inputs::

        [Mandatory]
        denoise_type: (u'nonaggr' or u'aggr' or u'both' or u'no', nipype
                  default value: nonaggr)
                Type of denoising strategy:
                -no: 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)
                argument: ``-den %s``
        motion_parameters: (an existing file name)
                motion parameters file
                argument: ``-mc %s``
                mutually_exclusive: feat_dir
        feat_dir: (an existing directory name)
                If a feat directory exists and temporal filtering has not been run
                yet, ICA_AROMA can use the files in this directory.
                argument: ``-feat %s``
                mutually_exclusive: in_file, mat_file, fnirt_warp_file,
                  motion_parameters
        in_file: (an existing file name)
                volume to be denoised
                argument: ``-i %s``
                mutually_exclusive: feat_dir
        out_dir: (a directory name, nipype default value: out)
                output directory
                argument: ``-o %s``

        [Optional]
        dim: (an integer (int or long))
                Dimensionality reduction when running MELODIC (defualt is automatic
                estimation)
                argument: ``-dim %d``
        fnirt_warp_file: (an existing file name)
                File name of the warp-file describing the non-linear registration
                (e.g. FSL FNIRT) of the structural data to MNI152 space (.nii.gz)
                argument: ``-warp %s``
                mutually_exclusive: feat_dir
        melodic_dir: (an existing directory name)
                path to MELODIC directory if MELODIC has already been run
                argument: ``-meldir %s``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        TR: (a float)
                TR in seconds. If this is not specified the TR will be extracted
                from the header of the fMRI nifti file.
                argument: ``-tr %.3f``
        mask: (an existing file name)
                path/name volume mask
                argument: ``-m %s``
                mutually_exclusive: feat_dir
        environ: (a dictionary with keys which are a newbytes or None or a
                  newstr or None and with values which are a newbytes or None or a
                  newstr or None, nipype default value: {})
                Environment variables
        mat_file: (an existing file name)
                path/name of the mat-file describing the affine registration (e.g.
                FSL FLIRT) of the functional data to structural space (.mat file)
                argument: ``-affmat %s``
                mutually_exclusive: feat_dir

Outputs::

        aggr_denoised_file: (an existing file name)
                if generated: aggressively denoised volume
        nonaggr_denoised_file: (an existing file name)
                if generated: non aggressively denoised volume
        out_dir: (an existing directory name)
                directory contains (in addition to the denoised files): melodic.ica
                + classified_motion_components + classification_overview +
                feature_scores + melodic_ic_mni)
