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# interfaces.afni.preprocess

## Allineate

Link to code

Wraps command 3dAllineate

Program to align one dataset (the ‘source’) to a base dataset

For complete details, see the 3dAllineate Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> allineate = afni.Allineate()
    >>> allineate.inputs.in_file = 'functional.nii'
    >>> allineate.inputs.out_file= 'functional_allineate.nii'
    >>> allineate.inputs.matrix= 'cmatrix.mat'
    >>> res = allineate.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dAllineate

    [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
    matrix: (an existing file name)
            matrix to align input file
    out_file: (a file name, nipype default value: %s_allineate)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## AutoTcorrelate

Link to code

Wraps command 3dAutoTcorrelate

Computes the correlation coefficient between the time series of each pair of voxels in the input dataset, and stores the output into a new anatomical bucket dataset [scaled to shorts to save memory space].

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> corr = afni.AutoTcorrelate()
    >>> corr.inputs.in_file = 'functional.nii'
    >>> corr.inputs.out_file = 'my_similarity_matrix.1D'
    >>> corr.inputs.polort = -1
    >>> corr.inputs.eta2 = True
    >>> corr.inputs.mask = 'mask.nii'
    >>> corr.inputs.mask_only_targets = True
    >>> corr.cmdline
    '3dAutoTcorrelate -eta2 -mask mask.nii -mask_only_targets -prefix ...my_similarity_matrix.1D -polort -1 functional.nii'
    >>> res = corr.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            timeseries x space (volume or surface) file

    [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
    eta2: (a boolean)
            eta^2 similarity
    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 of voxels
    mask_only_targets: (a boolean)
            use mask only on targets voxels
    out_file: (a file name, nipype default value: %s_similarity_matrix.1D)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    polort: (an integer)
            Remove polynomical trend of order m or -1 for no detrending
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Automask

Link to code

Wraps command 3dAutomask

Create a brain-only mask of the image using AFNI 3dAutomask command

For complete details, see the 3dAutomask Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> automask = afni.Automask()
    >>> automask.inputs.in_file = 'functional.nii'
    >>> automask.inputs.dilate = 1
    >>> automask.inputs.outputtype = "NIFTI"
    >>> automask.cmdline
    '3dAutomask -apply_prefix functional_masked.nii -dilate 1 -prefix functional_mask.nii functional.nii'
    >>> res = automask.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dAutomask

    [Optional]
    apply_mask: (a file name)
            output file from 3dAutomask
    apply_suffix: (a string)
            out_file suffix
    args: (a string)
            Additional parameters to the command
    brain_file: (a file name, nipype default value: %s_masked)
            output file from 3dAutomask
    clfrac: (a float)
            sets the clip level fraction (must be 0.1-0.9). A small value will tend to make the mask
            larger [default = 0.5].
    dilate: (an integer)
            dilate the mask outwards
    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
    erode: (an integer)
            erode the mask inwards
    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_suffix: (a string)
            out_file suffix
    out_file: (a file name, nipype default value: %s_mask)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    brain_file: (an existing file name)
            brain file (skull stripped)
    out_file: (an existing file name)
            mask file

## BrickStat

Link to code

Wraps command 3dBrickStat

Compute maximum and/or minimum voxel values of an input dataset

For complete details, see the 3dBrickStat Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> brickstat = afni.BrickStat()
    >>> brickstat.inputs.in_file = 'functional.nii'
    >>> brickstat.inputs.mask = 'skeleton_mask.nii.gz'
    >>> brickstat.inputs.min = True
    >>> res = brickstat.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dmaskave

    [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 dset = use dset as mask to include/exclude voxels
    min: (a boolean)
            print the minimum value in dataset
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype

Outputs:

    min_val: (a float)
            output

## Calc

Link to code

Wraps command 3dcalc

This program does voxel-by-voxel arithmetic on 3D datasets

For complete details, see the 3dcalc Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> calc = afni.Calc()
    >>> calc.inputs.in_file_a = 'functional.nii'
    >>> calc.inputs.in_file_b = 'functional2.nii'
    >>> calc.inputs.expr='a*b'
    >>> calc.inputs.out_file =  'functional_calc.nii.gz'
    >>> calc.inputs.outputtype = "NIFTI"
    >>> calc.cmdline
    '3dcalc -a functional.nii  -b functional2.nii -expr "a*b" -prefix functional_calc.nii.gz'

Inputs:

    [Mandatory]
    expr: (a string)
            expr
    in_file_a: (an existing file name)
            input file to 3dcalc

    [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_file_b: (an existing file name)
            operand file to 3dcalc
    out_file: (a file name, nipype default value: %s_calc)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    single_idx: (an integer)
            volume index for in_file_a
    start_idx: (an integer)
            start index for in_file_a
            requires: stop_idx
    stop_idx: (an integer)
            stop index for in_file_a
            requires: start_idx
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Copy

Link to code

Wraps command 3dcopy

Copies an image of one type to an image of the same or different type using 3dcopy command

For complete details, see the 3dcopy Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> copy = afni.Copy()
    >>> copy.inputs.in_file = 'functional.nii'
    >>> copy.inputs.out_file = 'new_func.nii'
    >>> res = copy.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dcopy

    [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, nipype default value: %s_copy)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Despike

Link to code

Wraps command 3dDespike

Removes ‘spikes’ from the 3D+time input dataset

For complete details, see the 3dDespike Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> despike = afni.Despike()
    >>> despike.inputs.in_file = 'functional.nii'
    >>> res = despike.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dDespike

    [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, nipype default value: %s_despike)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Detrend

Link to code

Wraps command 3dDetrend

This program removes components from voxel time series using linear least squares

For complete details, see the 3dDetrend Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> detrend = afni.Detrend()
    >>> detrend.inputs.in_file = 'functional.nii'
    >>> detrend.inputs.args = '-polort 2'
    >>> res = detrend.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dDetrend

    [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, nipype default value: %s_detrend)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Fim

Link to code

Wraps command 3dfim+

Program to calculate the cross-correlation of an ideal reference waveform with the measured FMRI time series for each voxel

For complete details, see the 3dfim+ Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> fim = afni.Fim()
    >>> fim.inputs.in_file = 'functional.nii'
    >>> fim.inputs.ideal_file= 'seed.1D'
    >>> fim.inputs.out_file = 'functional_corr.nii'
    >>> fim.inputs.out = 'Correlation'
    >>> fim.inputs.fim_thr = 0.0009
    >>> res = fim.run()

Inputs:

    [Mandatory]
    ideal_file: (an existing file name)
            ideal time series file name
    in_file: (an existing file name)
            input file to 3dfim+

    [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
    fim_thr: (a float)
            fim internal mask threshold value
    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: (a string)
            Flag to output the specified parameter
    out_file: (a file name, nipype default value: %s_fim)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Fourier

Link to code

Wraps command 3dFourier

Program to lowpass and/or highpass each voxel time series in a dataset, via the FFT

For complete details, see the 3dFourier Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> fourier = afni.Fourier()
    >>> fourier.inputs.in_file = 'functional.nii'
    >>> fourier.inputs.args = '-retrend'
    >>> fourier.inputs.highpass = 0.005
    >>> fourier.inputs.lowpass = 0.1
    >>> res = fourier.run()

Inputs:

    [Mandatory]
    highpass: (a float)
            highpass
    in_file: (an existing file name)
            input file to 3dFourier
    lowpass: (a float)
            lowpass

    [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, nipype default value: %s_fourier)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Maskave

Link to code

Wraps command 3dmaskave

Computes average of all voxels in the input dataset which satisfy the criterion in the options list

For complete details, see the 3dmaskave Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> maskave = afni.Maskave()
    >>> maskave.inputs.in_file = 'functional.nii'
    >>> maskave.inputs.mask= 'seed_mask.nii'
    >>> maskave.inputs.quiet= True
    >>> maskave.cmdline
    '3dmaskave -mask seed_mask.nii -quiet functional.nii > functional_maskave.1D'
    >>> res = maskave.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dmaskave

    [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)
            matrix to align input file
    out_file: (a file name, nipype default value: %s_maskave.1D)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    quiet: (a boolean)
            matrix to align input file
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Merge

Link to code

Wraps command 3dmerge

Merge or edit volumes using AFNI 3dmerge command

For complete details, see the 3dmerge Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> merge = afni.Merge()
    >>> merge.inputs.in_files = ['functional.nii', 'functional2.nii']
    >>> merge.inputs.blurfwhm = 4
    >>> merge.inputs.doall = True
    >>> merge.inputs.out_file = 'e7.nii'
    >>> res = merge.run()

Inputs:

    [Mandatory]
    in_files: (an existing file name)

    [Optional]
    args: (a string)
            Additional parameters to the command
    blurfwhm: (an integer)
            FWHM blur value (mm)
    doall: (a boolean)
            apply options to all sub-bricks in dataset
    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, nipype default value: %s_merge)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## ROIStats

Link to code

Wraps command 3dROIstats

Display statistics over masked regions

For complete details, see the 3dROIstats Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> roistats = afni.ROIStats()
    >>> roistats.inputs.in_file = 'functional.nii'
    >>> roistats.inputs.mask = 'skeleton_mask.nii.gz'
    >>> roistats.inputs.quiet=True
    >>> res = roistats.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dROIstats

    [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)
            input mask
    mask_f2short: (a boolean)
            Tells the program to convert a float mask to short integers, by simple rounding.
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    quiet: (a boolean)
            execute quietly

Outputs:

    stats: (an existing file name)
            output

## Refit

Link to code

Wraps command 3drefit

Changes some of the information inside a 3D dataset’s header

For complete details, see the `3drefit Documentation. <http://afni.nimh.nih.gov/pub/dist/doc/program_help/3drefit.html>

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> refit = afni.Refit()
    >>> refit.inputs.in_file = 'structural.nii'
    >>> refit.inputs.deoblique=True
    >>> res = refit.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3drefit

    [Optional]
    args: (a string)
            Additional parameters to the command
    deoblique: (a boolean)
            replace current transformation matrix with cardinal matrix
    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, nipype default value: %s_refit)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix
    xorigin: (a string)
            x distance for edge voxel offset
    yorigin: (a string)
            y distance for edge voxel offset
    zorigin: (a string)
            z distance for edge voxel offset

Outputs:

    out_file: (an existing file name)
            output file

## Resample

Link to code

Wraps command 3dresample

Resample or reorient an image using AFNI 3dresample command

For complete details, see the 3dresample Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> resample = afni.Resample()
    >>> resample.inputs.in_file = 'functional.nii'
    >>> resample.inputs.orientation= 'RPI'
    >>> res = resample.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dresample

    [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
    orientation: (a string)
            new orientation code
    out_file: (a file name, nipype default value: %s_resample)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## SkullStrip

Link to code

Wraps command 3dSkullStrip

A program to extract the brain from surrounding tissue from MRI T1-weighted images

For complete details, see the 3dSkullStrip Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> skullstrip = afni.SkullStrip()
    >>> skullstrip.inputs.in_file = 'functional.nii'
    >>> skullstrip.inputs.args = '-o_ply'
    >>> res = skullstrip.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dSkullStrip

    [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, nipype default value: %s_skullstrip)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## TCat

Link to code

Wraps command 3dTcat

Concatenate sub-bricks from input datasets into one big 3D+time dataset

For complete details, see the 3dTcat Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> tcat = afni.TCat()
    >>> tcat.inputs.in_files = ['functional.nii', 'functional2.nii']
    >>> tcat.inputs.out_file= 'functional_tcat.nii'
    >>> tcat.inputs.rlt = '+'
    >>> res = tcat.run()

Inputs:

    [Mandatory]
    in_files: (an existing file name)
            input file to 3dTcat

    [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, nipype default value: %s_tcat)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    rlt: (a string)
            options
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## TCorrelate

Link to code

Wraps command 3dTcorrelate

Computes the correlation coefficient between corresponding voxel time series in two input 3D+time datasets ‘xset’ and ‘yset’

For complete details, see the 3dTcorrelate Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> tcorrelate = afni.TCorrelate()
    >>> tcorrelate.inputs.xset= 'u_rc1s1_Template.nii'
    >>> tcorrelate.inputs.yset = 'u_rc1s2_Template.nii'
    >>> tcorrelate.inputs.out_file = 'functional_tcorrelate.nii.gz'
    >>> tcorrelate.inputs.polort = -1
    >>> tcorrelate.inputs.pearson = True
    >>> res = tcarrelate.run()

Inputs:

    [Mandatory]
    xset: (an existing file name)
            input xset
    yset: (an existing file name)
            input yset

    [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, nipype default value: %s_tcorr)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    pearson: (a boolean)
            Correlation is the normal Pearson correlation coefficient
    polort: (an integer)
            Remove polynomical trend of order m

Outputs:

    out_file: (an existing file name)
            output file

## TShift

Link to code

Wraps command 3dTshift

Shifts voxel time series from input so that seperate slices are aligned to the same temporal origin

For complete details, see the `3dTshift Documentation. <http://afni.nimh.nih.gov/pub/dist/doc/program_help/3dTshift.html>

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> tshift = afni.TShift()
    >>> tshift.inputs.in_file = 'functional.nii'
    >>> tshift.inputs.tpattern = 'alt+z'
    >>> tshift.inputs.tzero = 0.0
    >>> tshift.cmdline
    '3dTshift -prefix functional_tshift+orig.BRIK -tpattern alt+z -tzero 0.0 functional.nii'
    >>> res = tshift.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dTShift

    [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: (an integer)
            ignore the first set of points specified
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    interp: ('Fourier' or 'linear' or 'cubic' or 'quintic' or 'heptic')
            different interpolation methods (see 3dTShift for details) default = Fourier
    out_file: (a file name, nipype default value: %s_tshift)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    rlt: (a boolean)
            Before shifting, remove the mean and linear trend
    rltplus: (a boolean)
            Before shifting, remove the mean and linear trend and later put back the mean
    suffix: (a string)
            output image suffix
    tpattern: ('alt+z' or 'alt+z2' or 'alt-z' or 'alt-z2' or 'seq+z' or 'seq-z')
            use specified slice time pattern rather than one in header
    tr: (a string)
            manually set the TRYou can attach suffix "s" for seconds or "ms" for milliseconds.
    tslice: (an integer)
            align each slice to time offset of given slice
            mutually_exclusive: tzero
    tzero: (a float)
            align each slice to given time offset
            mutually_exclusive: tslice

Outputs:

    out_file: (an existing file name)
            output file

## TStat

Link to code

Wraps command 3dTstat

Compute voxel-wise statistics using AFNI 3dTstat command

For complete details, see the 3dTstat Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> tstat = afni.TStat()
    >>> tstat.inputs.in_file = 'functional.nii'
    >>> tstat.inputs.args= '-mean'
    >>> res = tstat.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dTstat

    [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, nipype default value: %s_tstat)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## To3D

Link to code

Wraps command to3d

Create a 3D dataset from 2D image files using AFNI to3d command

For complete details, see the to3d Documentation

### Examples

    >>> from nipype.interfaces import afni
    >>> To3D = afni.To3D()
    >>> To3D.inputs.datatype = 'float'
    >>> To3D.inputs.infolder = 'dicomdir'
    >>> To3D.inputs.filetype = "anat"
    >>> To3D.inputs.outputtype = "NIFTI"
    >>> To3D.cmdline
    'to3d -datum float -anat -prefix dicomdir.nii dicomdir/*.dcm'
    >>> res = To3D.run()

Inputs:

    [Mandatory]
    in_folder: (an existing directory name)
            folder with DICOM images to convert
            mutually_exclusive: infolder, in_folder
    infolder: (an existing directory name)
            folder with DICOM images to convert
            mutually_exclusive: infolder, in_folder

    [Optional]
    args: (a string)
            Additional parameters to the command
    assumemosaic: (a boolean)
            assume that Siemens image is mosaic
    datatype: ('short' or 'float' or 'byte' or 'complex')
            set output file datatype
    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
    filetype: ('spgr' or 'fse' or 'epan' or 'anat' or 'ct' or 'spct' or 'pet' or 'mra' or
             'bmap' or 'diff' or 'omri' or 'abuc' or 'fim' or 'fith' or 'fico' or 'fitt' or 'fift'
             or 'fizt' or 'fict' or 'fibt' or 'fibn' or 'figt' or 'fipt' or 'fbuc')
            type of datafile being converted
    funcparams: (a string)
            parameters for functional data
    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, nipype default value: %s)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    skipoutliers: (a boolean)
            skip the outliers check
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file

## Volreg

Link to code

Wraps command 3dvolreg

Register input volumes to a base volume using AFNI 3dvolreg command

For complete details, see the 3dvolreg Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> volreg = afni.Volreg()
    >>> volreg.inputs.in_file = 'functional.nii'
    >>> volreg.inputs.args = '-Fourier -twopass'
    >>> volreg.inputs.zpad = 4
    >>> volreg.inputs.outputtype = "NIFTI"
    >>> volreg.cmdline
    '3dvolreg -Fourier -twopass -1Dfile functional.1D -prefix functional_volreg.nii -zpad 4 functional.nii'
    >>> res = volreg.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dvolreg

    [Optional]
    args: (a string)
            Additional parameters to the command
    basefile: (an existing file name)
            base file for registration
    copyorigin: (a boolean)
            copy base file origin coords to output
    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
    md1dfile: (a file name)
            max displacement output file
    oned_file: (a file name, nipype default value: %s.1D)
            1D movement parameters output file
    out_file: (a file name, nipype default value: %s_volreg)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix
    timeshift: (a boolean)
            time shift to mean slice time offset
    verbose: (a boolean)
            more detailed description of the process
    zpad: (an integer)
            Zeropad around the edges by 'n' voxels during rotations

Outputs:

    md1d_file: (an existing file name)
            max displacement info file
    oned_file: (an existing file name)
            movement parameters info file
    out_file: (an existing file name)
            registered file

## Warp

Link to code

Wraps command 3dWarp

Use 3dWarp for spatially transforming a dataset

For complete details, see the 3dWarp Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> warp = afni.Warp()
    >>> warp.inputs.in_file = 'structural.nii'
    >>> warp.inputs.deoblique = True
    >>> res = warp.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dWarp

    [Optional]
    args: (a string)
            Additional parameters to the command
    deoblique: (a boolean)
            transform dataset from oblique to cardinal
    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
    gridset: (an existing file name)
            copy grid of specified dataset
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the interface fails to
            run
    interp: ('linear' or 'cubic' or 'NN' or 'quintic')
            spatial interpolation methods [default = linear]
    matparent: (an existing file name)
            apply transformation from 3dWarpDrive
    mni2tta: (a boolean)
            transform dataset from MNI152 to Talaraich
    out_file: (a file name, nipype default value: %s_warp)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string, nipype default value: _warp)
            out_file suffix
    tta2mni: (a boolean)
            transform dataset from Talairach to MNI152
    zpad: (an integer)
            pad input dataset with N planes of zero on all sides.

Outputs:

    out_file: (an existing file name)
            output file

## ZCutUp

Link to code

Wraps command 3dZcutup

Cut z-slices from a volume using AFNI 3dZcutup command

For complete details, see the 3dZcutup Documentation.

### Examples

    >>> from nipype.interfaces import afni as afni
    >>> zcutup = afni.ZCutUp()
    >>> zcutup.inputs.in_file = 'functional.nii'
    >>> zcutup.inputs.out_file = 'functional_zcutup.nii'
    >>> zcutup.inputs.keep= '0 10'
    >>> res = zcutup.run()

Inputs:

    [Mandatory]
    in_file: (an existing file name)
            input file to 3dZcutup

    [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
    keep: (a string)
            slice range to keep in output
    out_file: (a file name, nipype default value: %s_zcupup)
            output image file name
    outputtype: ('NIFTI_GZ' or 'AFNI' or 'NIFTI')
            AFNI output filetype
    prefix: (a string)
            output image prefix
    suffix: (a string)
            output image suffix

Outputs:

    out_file: (an existing file name)
            output file