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# nipype.interfaces.fsl.aroma module

This commandline module provides classes for interfacing with the ICA-AROMA.py command line tool.

## ICA_AROMA

Link to code

> Bases: CommandLine

> Wrapped executable: `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
>     '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'

> denoise_type‘nonaggr’ or ‘aggr’ or ‘both’ or ‘no’

>   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). Maps to a command-line argument: `-den %s`. (Nipype default value: `nonaggr`)

> feat_dira pathlike object or string representing an existing directory

>   If a feat directory exists and temporal filtering has not been run yet, ICA_AROMA can use the files in this directory. Maps to a command-line argument: `-feat %s`. Mutually exclusive with inputs: `in_file`, `mat_file`, `fnirt_warp_file`, `motion_parameters`.

> in_filea pathlike object or string representing an existing file

>   Volume to be denoised. Maps to a command-line argument: `-i %s`. Mutually exclusive with inputs: `feat_dir`.

> motion_parametersa pathlike object or string representing an existing file

>   Motion parameters file. Maps to a command-line argument: `-mc %s`. Mutually exclusive with inputs: `feat_dir`.

> out_dira pathlike object or string representing a directory

>   Output directory. Maps to a command-line argument: `-o %s`. (Nipype default value: `out`)

> TRa float

>   TR in seconds. If this is not specified the TR will be extracted from the header of the fMRI nifti file. Maps to a command-line argument: `-tr %.3f`.

> argsa unicode string

>   Additional parameters to the command. Maps to a command-line argument: `%s`.

> diman integer (int or long)

>   Dimensionality reduction when running MELODIC (defualt is automatic estimation). Maps to a command-line argument: `-dim %d`.

> environa dictionary with keys which are a bytes or None or a value of class ‘str’ and with values which are a bytes or None or a value of class ‘str’

>   Environment variables. (Nipype default value: `{}`)

> fnirt_warp_filea pathlike object or string representing an existing file

>   File name of the warp-file describing the non-linear registration (e.g. FSL FNIRT) of the structural data to MNI152 space (.nii.gz). Maps to a command-line argument: `-warp %s`. Mutually exclusive with inputs: `feat_dir`.

> maska pathlike object or string representing an existing file

>   Path/name volume mask. Maps to a command-line argument: `-m %s`. Mutually exclusive with inputs: `feat_dir`.

> mat_filea pathlike object or string representing an existing file

>   Path/name of the mat-file describing the affine registration (e.g. FSL FLIRT) of the functional data to structural space (.mat file). Maps to a command-line argument: `-affmat %s`. Mutually exclusive with inputs: `feat_dir`.

> melodic_dira pathlike object or string representing an existing directory

>   Path to MELODIC directory if MELODIC has already been run. Maps to a command-line argument: `-meldir %s`.

> aggr_denoised_filea pathlike object or string representing an existing file

>   If generated: aggressively denoised volume.

> nonaggr_denoised_filea pathlike object or string representing an existing file

>   If generated: non aggressively denoised volume.

> out_dira pathlike object or string representing an existing directory

>   Directory contains (in addition to the denoised files): melodic.ica + classified_motion_components + classification_overview + feature_scores + melodic_ic_mni).