Home · Quickstart · Documentation · Citation · NiPy

# interfaces.fsl.utils

## AvScale

Link to code

Wraps command avscale

Use FSL avscale command to extract info from mat file output of FLIRT

### Examples

avscale = AvScale() avscale.inputs.mat_file = ‘flirt.mat’ res = avscale.run() # doctest: +SKIP

Inputs:

    [Mandatory]

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    mat_file: (an existing file name)
            mat file to read
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type

Outputs:

    average_scaling
            Average Scaling
    backward_half_transform
            Backwards Half Transform
    determinant
            Determinant
    forward_half_transform
            Forward Half Transform
    left_right_orientation_preserved: (a boolean)
            True if LR orientation preserved
    rotation_translation_matrix
            Rotation and Translation Matrix
    scales
            Scales (x,y,z)
    skews
            Skews

## ConvertXFM

Link to code

Wraps command convert_xfm

Use the FSL utility convert_xfm to modify FLIRT transformation matrices.

### Examples

    >>> import nipype.interfaces.fsl as fsl
    >>> invt = fsl.ConvertXFM()
    >>> invt.inputs.in_file = "flirt.mat"
    >>> invt.inputs.invert_xfm = True
    >>> invt.inputs.out_file = 'flirt_inv.mat'
    >>> invt.cmdline
    'convert_xfm -omat flirt_inv.mat -inverse flirt.mat'

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input transformation matrix

    [Optional]
    args: (a string)
            Additional parameters to the command
    concat_xfm: (a boolean)
            write joint transformation of two input matrices
            mutually_exclusive: invert_xfm, concat_xfm, fix_scale_skew
            requires: in_file2
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    fix_scale_skew: (a boolean)
            use secondary matrix to fix scale and skew
            mutually_exclusive: invert_xfm, concat_xfm, fix_scale_skew
            requires: in_file2
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    in_file2: (an existing file name)
            second input matrix (for use with fix_scale_skew or concat_xfm
    invert_xfm: (a boolean)
            invert input transformation
            mutually_exclusive: invert_xfm, concat_xfm, fix_scale_skew
    out_file: (a file name)
            final transformation matrix
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type

Outputs:

    out_file: (an existing file name)
            output transformation matrix

## EPIDeWarp

Link to code

Wraps command epidewarp.fsl

Wraps fieldmap unwarping script from Freesurfer’s epidewarp.fsl_

### Examples

    >>> dewarp = EPIDeWarp()
    >>> dewarp.inputs.epi_file = "functional.nii"
    >>> dewarp.inputs.mag_file = "magnitude.nii"
    >>> dewarp.inputs.dph_file = "phase.nii"
    >>> res = dewarp.run()

### References

_epidewarp.fsl: http://surfer.nmr.mgh.harvard.edu/fswiki/epidewarp.fsl

Inputs:

    [Mandatory]
    dph_file: (an existing file name)
            Phase file assumed to be scaled from 0 to 4095
    mag_file: (an existing file name)
            Magnitude file

    [Optional]
    args: (a string)
            Additional parameters to the command
    cleanup: (a boolean)
            cleanup
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    epidw: (a string)
            dewarped epi volume
    esp: (a float, nipype default value: 0.58)
            EPI echo spacing
    exfdw: (a string)
            dewarped example func volume
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    nocleanup: (a boolean, nipype default value: True)
            no cleanup
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    sigma: (an integer, nipype default value: 2)
            2D spatial gaussing smoothing                        stdev (default = 2mm)
    tediff: (a float, nipype default value: 2.46)
            difference in B0 field map TEs
    tmpdir: (a string)
            tmpdir
    vsm: (a string)
            voxel shift map

Outputs:

    exf_mask: (a file name)
            Mask from example functional volume
    exfdw: (a file name)
            dewarped functional volume example
    unwarped_file: (a file name)
            unwarped epi file
    vsm_file: (a file name)
            voxel shift map

## ExtractROI

Link to code

Wraps command fslroi

Uses FSL Fslroi command to extract region of interest (ROI) from an image.

You can a) take a 3D ROI from a 3D data set (or if it is 4D, the same ROI is taken from each time point and a new 4D data set is created), b) extract just some time points from a 4D data set, or c) control time and space limits to the ROI. Note that the arguments are minimum index and size (not maximum index). So to extract voxels 10 to 12 inclusive you would specify 10 and 3 (not 10 and 12).

### Examples

    >>> from nipype.interfaces.fsl import ExtractROI
    >>> from nipype.testing import anatfile
    >>> fslroi = ExtractROI(in_file=anatfile, roi_file='bar.nii', t_min=0, t_size=1)
    >>> fslroi.cmdline == 'fslroi %s bar.nii 0 1'%anatfile
    True

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file

    [Optional]
    args: (a string)
            Additional parameters to the command
    crop_list: (a list of items which are a tuple of the form: (an integer, an integer))
            mutually_exclusive: x_min, x_size, y_min, y_size, z_min, z_size, t_min, t_size
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    roi_file: (a file name)
            output file
    t_min: (an integer)
    t_size: (an integer)
    x_min: (an integer)
    x_size: (an integer)
    y_min: (an integer)
    y_size: (an integer)
    z_min: (an integer)
    z_size: (an integer)

Outputs:

    roi_file: (an existing file name)

## FilterRegressor

Link to code

Wraps command fsl_regfilt

Data de-noising by regressing out part of a design matrix

Uses simple OLS regression on 4D images

Inputs:

    [Mandatory]
    design_file: (an existing file name)
            name of the matrix with time courses (e.g. GLM design or MELODIC mixing matrix)
    filter_all: (a boolean)
            use all columns in the design file in denoising
            mutually_exclusive: filter_columns
    filter_columns: (a list of items which are an integer)
            (1-based) column indices to filter out of the data
            mutually_exclusive: filter_all
    in_file: (an existing file name)
            input file name (4D image)

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    mask: (an existing file name)
            mask image file name
    out_file: (a file name)
            output file name for the filtered data
    out_vnscales: (a boolean)
            output scaling factors for variance normalization
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    var_norm: (a boolean)
            perform variance-normalization on data

Outputs:

    out_file: (an existing file name)
            output file name for the filtered data

## ImageMaths

Link to code

Wraps command fslmaths

Use FSL fslmaths command to allow mathematical manipulation of images

FSL info

### Examples

    >>> from nipype.interfaces import fsl
    >>> from nipype.testing import anatfile
    >>> maths = fsl.ImageMaths(in_file=anatfile, op_string= '-add 5',                                out_file='foo_maths.nii')
    >>> maths.cmdline == 'fslmaths %s -add 5 foo_maths.nii'%anatfile
    True

Inputs:

    [Mandatory]
    in_file: (an existing file name)

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    in_file2: (an existing file name)
    op_string: (a string)
            string defining the operation, i. e. -add
    out_data_type: ('char' or 'short' or 'int' or 'float' or 'double' or 'input')
            output datatype, one of (char, short, int, float, double, input)
    out_file: (a file name)
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    suffix: (a string)
            out_file suffix

Outputs:

    out_file: (an existing file name)

## ImageMeants

Link to code

Wraps command fslmeants

Use fslmeants for printing the average timeseries (intensities) to the screen (or saves to a file). The average is taken over all voxels in the mask (or all voxels in the image if no mask is specified)

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file for computing the average timeseries

    [Optional]
    args: (a string)
            Additional parameters to the command
    eig: (a boolean)
            calculate Eigenvariate(s) instead of mean (output will have 0 mean)
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    mask: (an existing file name)
            input 3D mask
    nobin: (a boolean)
            do not binarise the mask for calculation of Eigenvariates
    order: (an integer, nipype default value: 1)
            select number of Eigenvariates
    out_file: (a file name)
            name of output text matrix
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    show_all: (a boolean)
            show all voxel time series (within mask) instead of averaging
    spatial_coord: (a list of items which are an integer)
            <x y z> requested spatial coordinate (instead of mask)
    transpose: (a boolean)
            output results in transpose format (one row per voxel/mean)
    use_mm: (a boolean)
            use mm instead of voxel coordinates (for -c option)

Outputs:

    out_file: (an existing file name)
            path/name of output text matrix

## ImageStats

Link to code

Wraps command fslstats

Use FSL fslstats command to calculate stats from images

FSL info

### Examples

    >>> from nipype.interfaces.fsl import ImageStats
    >>> from nipype.testing import funcfile
    >>> stats = ImageStats(in_file=funcfile, op_string= '-M')
    >>> stats.cmdline == 'fslstats %s -M'%funcfile
    True

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to generate stats of
    op_string: (a string)
            string defining the operation, options are applied in order, e.g. -M -l 10 -M will
            report the non-zero mean, apply athreshold and then report the new nonzero mean

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    mask_file: (an existing file name)
            mask file used for option -k %s
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    split_4d: (a boolean)
            give a separate output line for each 3D volume of a 4D timeseries

Outputs:

    out_stat
            stats output

## Merge

Link to code

Wraps command fslmerge

Use fslmerge to concatenate images

Inputs:

    [Mandatory]
    dimension: ('t' or 'x' or 'y' or 'z')
            dimension along which the file will be merged
    in_files: (a list of items which are an existing file name)

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    merged_file: (a file name)
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type

Outputs:

    merged_file: (an existing file name)

## Overlay

Link to code

Wraps command overlay

Use FSL’s overlay command to combine background and statistical images into one volume

### Examples

    >>> from nipype.interfaces import fsl
    >>> combine = fsl.Overlay()
    >>> combine.inputs.background_image = 'mean_func.nii.gz'
    >>> combine.inputs.auto_thresh_bg = True
    >>> combine.inputs.stat_image = 'zstat1.nii.gz'
    >>> combine.inputs.stat_thresh = (3.5, 10)
    >>> combine.inputs.show_negative_stats = True
    >>> res = combine.run()

Inputs:

    [Mandatory]
    auto_thresh_bg: (a boolean)
            automatically threhsold the background image
            mutually_exclusive: auto_thresh_bg, full_bg_range, bg_thresh
    background_image: (an existing file name)
            image to use as background
    bg_thresh: (a tuple of the form: (a float, a float))
            min and max values for background intensity
            mutually_exclusive: auto_thresh_bg, full_bg_range, bg_thresh
    full_bg_range: (a boolean)
            use full range of background image
            mutually_exclusive: auto_thresh_bg, full_bg_range, bg_thresh
    stat_image: (an existing file name)
            statistical image to overlay in color
    stat_thresh: (a tuple of the form: (a float, a float))
            min and max values for the statistical overlay

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    out_file: (a file name)
            combined image volume
    out_type: ('float' or 'int', nipype default value: float)
            write output with float or int
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    show_negative_stats: (a boolean)
            display negative statistics in overlay
            mutually_exclusive: stat_image2
    stat_image2: (an existing file name)
            second statistical image to overlay in color
            mutually_exclusive: show_negative_stats
    stat_thresh2: (a tuple of the form: (a float, a float))
            min and max values for second statistical overlay
    transparency: (a boolean, nipype default value: True)
            make overlay colors semi-transparent
    use_checkerboard: (a boolean)
            use checkerboard mask for overlay

Outputs:

    out_file: (an existing file name)
            combined image volume

## PlotMotionParams

Link to code

Wraps command fsl_tsplot

Use fsl_tsplot to plot the estimated motion parameters from a realignment program.

### Examples

    >>> import nipype.interfaces.fsl as fsl
    >>> plotter = fsl.PlotMotionParams()
    >>> plotter.inputs.in_file = 'functional.par'
    >>> plotter.inputs.in_source = 'fsl'
    >>> plotter.inputs.plot_type = 'rotations'
    >>> res = plotter.run()

### Notes

The ‘in_source’ attribute determines the order of columns that are expected in the source file. FSL prints motion parameters in the order rotations, translations, while SPM prints them in the opposite order. This interface should be able to plot timecourses of motion parameters generated from other sources as long as they fall under one of these two patterns. For more flexibilty, see the `fsl.PlotTimeSeries` interface.

Inputs:

    [Mandatory]
    in_file: (an existing file name or a list of items which are an existing file name)
            file with motion parameters
    in_source: ('spm' or 'fsl')
            which program generated the motion parameter file - fsl, spm
    plot_type: ('rotations' or 'translations' or 'displacement')
            which motion type to plot - rotations, translations, displacement

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    out_file: (a file name)
            image to write
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    plot_size: (a tuple of the form: (an integer, an integer))
            plot image height and width

Outputs:

    out_file: (an existing file name)
            image to write

## PlotTimeSeries

Link to code

Wraps command fsl_tsplot

Use fsl_tsplot to create images of time course plots.

### Examples

    >>> import nipype.interfaces.fsl as fsl
    >>> plotter = fsl.PlotTimeSeries()
    >>> plotter.inputs.in_file = 'functional.par'
    >>> plotter.inputs.title = 'Functional timeseries'
    >>> plotter.inputs.labels = ['run1', 'run2']
    >>> plotter.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name or a list of items which are an existing file name)
            file or list of files with columns of timecourse information

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    labels: (a string or a list of items which are a string)
            label or list of labels
    legend_file: (an existing file name)
            legend file
    out_file: (a file name)
            image to write
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    plot_finish: (an integer)
            final column from in-file to plot
            mutually_exclusive: plot_range
    plot_range: (a tuple of the form: (an integer, an integer))
            first and last columns from the in-file to plot
            mutually_exclusive: plot_start, plot_finish
    plot_size: (a tuple of the form: (an integer, an integer))
            plot image height and width
    plot_start: (an integer)
            first column from in-file to plot
            mutually_exclusive: plot_range
    sci_notation: (a boolean)
            switch on scientific notation
    title: (a string)
            plot title
    x_precision: (an integer)
            precision of x-axis labels
    x_units: (an integer, nipype default value: 1)
            scaling units for x-axis (between 1 and length of in file)
    y_max: (a float)
            maximum y value
            mutually_exclusive: y_range
    y_min: (a float)
            minumum y value
            mutually_exclusive: y_range
    y_range: (a tuple of the form: (a float, a float))
            min and max y axis values
            mutually_exclusive: y_min, y_max

Outputs:

    out_file: (an existing file name)
            image to write

## PowerSpectrum

Link to code

Wraps command fslpspec

Use FSL PowerSpectrum command for power spectrum estimation.

### Examples

    >>> from nipype.interfaces import fsl
    >>> pspec = fsl.PowerSpectrum()
    >>> pspec.inputs.in_file = 'functional.nii'
    >>> res = pspec.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input 4D file to estimate the power spectrum

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    out_file: (a file name)
            name of output 4D file for power spectrum
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type

Outputs:

    out_file: (an existing file name)
            path/name of the output 4D power spectrum file

## Reorient2Std

Link to code

Wraps command fslreorient2std

fslreorient2std is a tool for reorienting the image to match the approximate orientation of the standard template images (MNI152).

### Examples

    >>> reorient = Reorient2Std()
    >>> reorient.inputs.in_file = "functional.nii"
    >>> res = reorient.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    out_file: (a file name)
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type

Outputs:

    out_file: (an existing file name)

## Slicer

Link to code

Wraps command slicer

Use FSL’s slicer command to output a png image from a volume.

### Examples

    >>> from nipype.interfaces import fsl
    >>> from nipype.testing import example_data
    >>> slice = fsl.Slicer()
    >>> slice.inputs.in_file = example_data('functional.nii')
    >>> slice.inputs.all_axial = True
    >>> slice.inputs.image_width = 750
    >>> res = slice.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input volume

    [Optional]
    all_axial: (a boolean)
            output all axial slices into one picture
            mutually_exclusive: single_slice, middle_slices, all_axial, sample_axial
            requires: image_width
    args: (a string)
            Additional parameters to the command
    colour_map: (an existing file name)
            use different colour map from that stored in nifti header
    dither_edges: (a boolean)
            produce semi-transparaent (dithered) edges
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    image_edges: (an existing file name)
            volume to display edge overlay for (useful for checking registration
    image_width: (an integer)
            max picture width
    intensity_range: (a tuple of the form: (a float, a float))
            min and max intensities to display
    label_slices: (a boolean, nipype default value: True)
            display slice number
    middle_slices: (a boolean)
            output picture of mid-sagital, axial, and coronal slices
            mutually_exclusive: single_slice, middle_slices, all_axial, sample_axial
    nearest_neighbour: (a boolean)
            use nearest neighbour interpolation for output
    out_file: (a file name)
            picture to write
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    sample_axial: (an integer)
            output every n axial slices into one picture
            mutually_exclusive: single_slice, middle_slices, all_axial, sample_axial
            requires: image_width
    scaling: (a float)
            image scale
    show_orientation: (a boolean, nipype default value: True)
            label left-right orientation
    single_slice: ('x' or 'y' or 'z')
            output picture of single slice in the x, y, or z plane
            mutually_exclusive: single_slice, middle_slices, all_axial, sample_axial
            requires: slice_number
    slice_number: (an integer)
            slice number to save in picture
    threshold_edges: (a float)
            use threshold for edges

Outputs:

    out_file: (an existing file name)
            picture to write

## Smooth

Link to code

Wraps command fslmaths

Use fslmaths to smooth the image

Inputs:

    [Mandatory]
    fwhm: (a float)
    in_file: (an existing file name)

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type
    smoothed_file: (a file name)

Outputs:

    smoothed_file: (an existing file name)

## Split

Link to code

Wraps command fslsplit

Uses FSL Fslsplit command to separate a volume into images in time, x, y or z dimension.

Inputs:

    [Mandatory]
    dimension: ('t' or 'x' or 'y' or 'z')
            dimension along which the file will be split
    in_file: (an existing file name)
            input filename

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    out_base_name: (a string)
            outputs prefix
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type

Outputs:

    out_files: (an existing file name)

## SwapDimensions

Link to code

Wraps command fslswapdim

Use fslswapdim to alter the orientation of an image.

This interface accepts a three-tuple corresponding to the new orientation. You may either provide dimension ids in the form of (-)x, (-)y, or (-z), or nifti-syle dimension codes (RL, LR, AP, PA, IS, SI).

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input image
    new_dims: (a tuple of the form: ('x' or '-x' or 'y' or '-y' or 'z' or '-z' or 'RL' or
             'LR' or 'AP' or 'PA' or 'IS' or 'SI', 'x' or '-x' or 'y' or '-y' or 'z' or '-z' or 'RL'
             or 'LR' or 'AP' or 'PA' or 'IS' or 'SI', 'x' or '-x' or 'y' or '-y' or 'z' or '-z' or
             'RL' or 'LR' or 'AP' or 'PA' or 'IS' or 'SI'))
            3-tuple of new dimension order

    [Optional]
    args: (a string)
            Additional parameters to the command
    environ: (a dictionary with keys which are a value of type 'str' and with values which
             are a value of type 'str', nipype default value: {})
            Environment variables
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    out_file: (a file name)
            image to write
    output_type: ('NIFTI_PAIR' or 'NIFTI_PAIR_GZ' or 'NIFTI_GZ' or 'NIFTI')
            FSL output type

Outputs:

    out_file: (an existing file name)
            image with new dimensions