interfaces.afni.utils¶

AFNItoNIFTI¶

Wraps command 3dAFNItoNIFTI

Converts AFNI format files to NIFTI format. This can also convert 2D or 1D data, which you can numpy.squeeze() to remove extra dimensions.

For complete details, see the 3dAFNItoNIFTI Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> a2n = afni.AFNItoNIFTI()
>>> a2n.inputs.in_file = 'afni_output.3D'
>>> a2n.inputs.out_file =  'afni_output.nii'
>>> a2n.cmdline  
'3dAFNItoNIFTI -prefix afni_output.nii afni_output.3D'
>>> res = a2n.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dAFNItoNIFTI
        flag: %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
denote: (a boolean)
        When writing the AFNI extension field, remove text notes that might
        contain subject identifying information.
        flag: -denote
environ: (a 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', 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
newid: (a boolean)
        Give the new dataset a new AFNI ID code, to distinguish it from the
        input dataset.
        flag: -newid
        mutually_exclusive: oldid
oldid: (a boolean)
        Give the new dataset the input datasets AFNI ID code.
        flag: -oldid
        mutually_exclusive: newid
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
pure: (a boolean)
        Do NOT write an AFNI extension field into the output file. Only use
        this option if needed. You can also use the 'nifti_tool' program to
        strip extensions from a file.
        flag: -pure
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

Autobox¶

Link to code

Wraps command 3dAutobox

Computes size of a box that fits around the volume. Also can be used to crop the volume to that box.

For complete details, see the 3dAutobox Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> abox = afni.Autobox()
>>> abox.inputs.in_file = 'structural.nii'
>>> abox.inputs.padding = 5
>>> abox.cmdline  
'3dAutobox -input structural.nii -prefix structural_autobox -npad 5'
>>> res = abox.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file
        flag: -input %s

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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
no_clustering: (a boolean)
        Don't do any clustering to find box. Any non-zero voxel will be
        preserved in the cropped volume. The default method uses some
        clustering to find the cropping box, and will clip off small
        isolated blobs.
        flag: -noclust
out_file: (a file name)
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
padding: (an integer (int or long))
        Number of extra voxels to pad on each side of box
        flag: -npad %d
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (a file name)
        output file
x_max: (an integer (int or long))
x_min: (an integer (int or long))
y_max: (an integer (int or long))
y_min: (an integer (int or long))
z_max: (an integer (int or long))
z_min: (an integer (int or long))

References:: None None

BrickStat¶

Link to code

Wraps command 3dBrickStat

Computes maximum and/or minimum voxel values of an input dataset. TODO Add optional arguments.

For complete details, see the 3dBrickStat Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> brickstat = afni.BrickStat()
>>> brickstat.inputs.in_file = 'functional.nii'
>>> brickstat.inputs.mask = 'skeleton_mask.nii.gz'
>>> brickstat.inputs.min = True
>>> brickstat.cmdline  
'3dBrickStat -min -mask skeleton_mask.nii.gz functional.nii'
>>> res = brickstat.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dmaskave
        flag: %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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
        flag: -mask %s, position: 2
min: (a boolean)
        print the minimum value in dataset
        flag: -min, position: 1
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

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
>>> 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'
>>> res = calc.run()  

Inputs:

[Mandatory]
expr: (a unicode string)
        expr
        flag: -expr "%s", position: 3
in_file_a: (an existing file name)
        input file to 3dcalc
        flag: -a %s, position: 0

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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
        flag: -b %s, position: 1
in_file_c: (an existing file name)
        operand file to 3dcalc
        flag: -c %s, position: 2
other: (a file name)
        other options
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
single_idx: (an integer (int or long))
        volume index for in_file_a
start_idx: (an integer (int or long))
        start index for in_file_a
        requires: stop_idx
stop_idx: (an integer (int or long))
        stop index for in_file_a
        requires: start_idx
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

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
>>> copy3d = afni.Copy()
>>> copy3d.inputs.in_file = 'functional.nii'
>>> copy3d.cmdline  
'3dcopy functional.nii functional_copy'
>>> res = copy3d.run()  

>>> from copy import deepcopy
>>> copy3d_2 = deepcopy(copy3d)
>>> copy3d_2.inputs.outputtype = 'NIFTI'
>>> copy3d_2.cmdline  
'3dcopy functional.nii functional_copy.nii'
>>> res = copy3d_2.run()  

>>> copy3d_3 = deepcopy(copy3d)
>>> copy3d_3.inputs.outputtype = 'NIFTI_GZ'
>>> copy3d_3.cmdline  
'3dcopy functional.nii functional_copy.nii.gz'
>>> res = copy3d_3.run()  

>>> copy3d_4 = deepcopy(copy3d)
>>> copy3d_4.inputs.out_file = 'new_func.nii'
>>> copy3d_4.cmdline  
'3dcopy functional.nii new_func.nii'
>>> res = copy3d_4.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dcopy
        flag: %s, position: -2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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 image file name
        flag: %s, position: -1
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

Eval¶

Link to code

Wraps command 1deval

Evaluates an expression that may include columns of data from one or more text files.

For complete details, see the 1deval Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> eval = afni.Eval()
>>> eval.inputs.in_file_a = 'seed.1D'
>>> eval.inputs.in_file_b = 'resp.1D'
>>> eval.inputs.expr = 'a*b'
>>> eval.inputs.out1D = True
>>> eval.inputs.out_file =  'data_calc.1D'
>>> eval.cmdline  
'1deval -a seed.1D -b resp.1D -expr "a*b" -1D -prefix data_calc.1D'
>>> res = eval.run()  

Inputs:

[Mandatory]
expr: (a unicode string)
        expr
        flag: -expr "%s", position: 3
in_file_a: (an existing file name)
        input file to 1deval
        flag: -a %s, position: 0

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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 1deval
        flag: -b %s, position: 1
in_file_c: (an existing file name)
        operand file to 1deval
        flag: -c %s, position: 2
other: (a file name)
        other options
out1D: (a boolean)
        output in 1D
        flag: -1D
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
single_idx: (an integer (int or long))
        volume index for in_file_a
start_idx: (an integer (int or long))
        start index for in_file_a
        requires: stop_idx
stop_idx: (an integer (int or long))
        stop index for in_file_a
        requires: start_idx
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

FWHMx¶

Link to code

Wraps command 3dFWHMx

Unlike the older 3dFWHM, this program computes FWHMs for all sub-bricks in the input dataset, each one separately. The output for each one is written to the file specified by ‘-out’. The mean (arithmetic or geometric) of all the FWHMs along each axis is written to stdout. (A non-positive output value indicates something bad happened; e.g., FWHM in z is meaningless for a 2D dataset; the estimation method computed incoherent intermediate results.)

For complete details, see the 3dFWHMx Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> fwhm = afni.FWHMx()
>>> fwhm.inputs.in_file = 'functional.nii'
>>> fwhm.cmdline  
'3dFWHMx -input functional.nii -out functional_subbricks.out > functional_fwhmx.out'
>>> res = fwhm.run()  

(Classic) METHOD:

Calculate ratio of variance of first differences to data variance.

Should be the same as 3dFWHM for a 1-brick dataset. (But the output format is simpler to use in a script.)

Note

IMPORTANT NOTE [AFNI > 16]

A completely new method for estimating and using noise smoothness values is now available in 3dFWHMx and 3dClustSim. This method is implemented in the ‘-acf’ options to both programs. ‘ACF’ stands for (spatial) AutoCorrelation Function, and it is estimated by calculating moments of differences out to a larger radius than before.

Notably, real FMRI data does not actually have a Gaussian-shaped ACF, so the estimated ACF is then fit (in 3dFWHMx) to a mixed model (Gaussian plus mono-exponential) of the form

$ACF(r) = a * exp(-r*r/(2*b*b)) + (1-a)*exp(-r/c)$

where $r$ is the radius, and $a, b, c$ are the fitted parameters. The apparent FWHM from this model is usually somewhat larger in real data than the FWHM estimated from just the nearest-neighbor differences used in the ‘classic’ analysis.

The longer tails provided by the mono-exponential are also significant. 3dClustSim has also been modified to use the ACF model given above to generate noise random fields.

Note

TL;DR or summary

The take-awaymessage is that the ‘classic’ 3dFWHMx and 3dClustSim analysis, using a pure Gaussian ACF, is not very correct for FMRI data – I cannot speak for PET or MEG data.

Warning

Do NOT use 3dFWHMx on the statistical results (e.g., ‘-bucket’) from 3dDeconvolve or 3dREMLfit!!! The function of 3dFWHMx is to estimate the smoothness of the time series NOISE, not of the statistics. This proscription is especially true if you plan to use 3dClustSim next!!

Note

Recommendations

For FMRI statistical purposes, you DO NOT want the FWHM to reflect the spatial structure of the underlying anatomy. Rather, you want the FWHM to reflect the spatial structure of the noise. This means that the input dataset should not have anatomical (spatial) structure.
One good form of input is the output of ‘3dDeconvolve -errts’, which is the dataset of residuals left over after the GLM fitted signal model is subtracted out from each voxel’s time series.
If you don’t want to go to that much trouble, use ‘-detrend’ to approximately subtract out the anatomical spatial structure, OR use the output of 3dDetrend for the same purpose.
If you do not use ‘-detrend’, the program attempts to find non-zero spatial structure in the input, and will print a warning message if it is detected.

Note

Notes on -demend

I recommend this option, and it is not the default only for historical compatibility reasons. It may become the default someday.
It is already the default in program 3dBlurToFWHM. This is the same detrending as done in 3dDespike; using 2*q+3 basis functions for q > 0.
If you don’t use ‘-detrend’, the program now [Aug 2010] checks if a large number of voxels are have significant nonzero means. If so, the program will print a warning message suggesting the use of ‘-detrend’, since inherent spatial structure in the image will bias the estimation of the FWHM of the image time series NOISE (which is usually the point of using 3dFWHMx).

Inputs:

[Mandatory]
in_file: (an existing file name)
        input dataset
        flag: -input %s

[Optional]
acf: (a boolean or a file name or a tuple of the form: (an existing
         file name, a float), nipype default value: False)
        computes the spatial autocorrelation
        flag: -acf
args: (a unicode string)
        Additional parameters to the command
        flag: %s
arith: (a boolean)
        if in_file has more than one sub-brick, compute the final estimate
        as the arithmetic mean of the individual sub-brick FWHM estimates
        flag: -arith
        mutually_exclusive: geom
automask: (a boolean, nipype default value: False)
        compute a mask from THIS dataset, a la 3dAutomask
        flag: -automask
combine: (a boolean)
        combine the final measurements along each axis
        flag: -combine
compat: (a boolean)
        be compatible with the older 3dFWHM
        flag: -compat
demed: (a boolean)
        If the input dataset has more than one sub-brick (e.g., has a time
        axis), then subtract the median of each voxel's time series before
        processing FWHM. This will tend to remove intrinsic spatial
        structure and leave behind the noise.
        flag: -demed
        mutually_exclusive: detrend
detrend: (a boolean or an integer (int or long), nipype default
         value: False)
        instead of demed (0th order detrending), detrend to the specified
        order. If order is not given, the program picks q=NT/30. -detrend
        disables -demed, and includes -unif.
        flag: -detrend
        mutually_exclusive: demed
environ: (a 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', nipype default value: {})
        Environment variables
geom: (a boolean)
        if in_file has more than one sub-brick, compute the final estimate
        as the geometric mean of the individual sub-brick FWHM estimates
        flag: -geom
        mutually_exclusive: arith
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)
        use only voxels that are nonzero in mask
        flag: -mask %s
out_detrend: (a file name)
        Save the detrended file into a dataset
        flag: -detprefix %s
out_file: (a file name)
        output file
        flag: > %s, position: -1
out_subbricks: (a file name)
        output file listing the subbricks FWHM
        flag: -out %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored
unif: (a boolean)
        If the input dataset has more than one sub-brick, then normalize
        each voxel's time series to have the same MAD before processing
        FWHM.
        flag: -unif

Outputs:

acf_param: (a tuple of the form: (a float, a float, a float) or a
         tuple of the form: (a float, a float, a float, a float))
        fitted ACF model parameters
fwhm: (a tuple of the form: (a float, a float, a float) or a tuple of
         the form: (a float, a float, a float, a float))
        FWHM along each axis
out_acf: (an existing file name)
        output acf file
out_detrend: (a file name)
        output file, detrended
out_file: (an existing file name)
        output file
out_subbricks: (an existing file name)
        output file (subbricks)

References:: None

MaskTool¶

Link to code

Wraps command 3dmask_tool

3dmask_tool - for combining/dilating/eroding/filling masks

For complete details, see the 3dmask_tool Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> masktool = afni.MaskTool()
>>> masktool.inputs.in_file = 'functional.nii'
>>> masktool.inputs.outputtype = 'NIFTI'
>>> masktool.cmdline  
'3dmask_tool -prefix functional_mask.nii -input functional.nii'
>>> res = automask.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file or files to 3dmask_tool
        flag: -input %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
count: (a boolean)
        Instead of created a binary 0/1 mask dataset, create one with counts
        of voxel overlap, i.e., each voxel will contain the number of masks
        that it is set in.
        flag: -count, position: 2
datum: ('byte' or 'short' or 'float')
        specify data type for output. Valid types are 'byte', 'short' and
        'float'.
        flag: -datum %s
dilate_inputs: (a unicode string)
        Use this option to dilate and/or erode datasets as they are read.
        ex. '5 -5' to dilate and erode 5 times
        flag: -dilate_inputs %s
dilate_results: (a unicode string)
        dilate and/or erode combined mask at the given levels.
        flag: -dilate_results %s
environ: (a 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', nipype default value: {})
        Environment variables
fill_dirs: (a unicode string)
        fill holes only in the given directions. This option is for use with
        -fill holes. should be a single string that specifies 1-3 of the
        axes using {x,y,z} labels (i.e. dataset axis order), or using the
        labels in {R,L,A,P,I,S}.
        flag: -fill_dirs %s
        requires: fill_holes
fill_holes: (a boolean)
        This option can be used to fill holes in the resulting mask, i.e.
        after all other processing has been done.
        flag: -fill_holes
frac: (a float)
        When combining masks (across datasets and sub-bricks), use this
        option to restrict the result to a certain fraction of the set of
        volumes
        flag: -frac %s
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
inter: (a boolean)
        intersection, this means -frac 1.0
        flag: -inter
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored
union: (a boolean)
        union, this means -frac 0
        flag: -union

Outputs:

out_file: (an existing file name)
        mask file

References:: None None

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
>>> 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'
>>> merge.cmdline  
'3dmerge -1blur_fwhm 4 -doall -prefix e7.nii functional.nii functional2.nii'
>>> res = merge.run()  

Inputs:

[Mandatory]
in_files: (a list of items which are an existing file name)
        flag: %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
blurfwhm: (an integer (int or long))
        FWHM blur value (mm)
        flag: -1blur_fwhm %d
doall: (a boolean)
        apply options to all sub-bricks in dataset
        flag: -doall
environ: (a 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', 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 image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

Notes¶

Link to code

Wraps command 3dNotes

A program to add, delete, and show notes for AFNI datasets.

For complete details, see the 3dNotes Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> notes = afni.Notes()
>>> notes.inputs.in_file = 'functional.HEAD'
>>> notes.inputs.add = 'This note is added.'
>>> notes.inputs.add_history = 'This note is added to history.'
>>> notes.cmdline  
'3dNotes -a "This note is added." -h "This note is added to history." functional.HEAD'
>>> res = notes.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dNotes
        flag: %s, position: -1

[Optional]
add: (a unicode string)
        note to add
        flag: -a "%s"
add_history: (a unicode string)
        note to add to history
        flag: -h "%s"
        mutually_exclusive: rep_history
args: (a unicode string)
        Additional parameters to the command
        flag: %s
delete: (an integer (int or long))
        delete note number num
        flag: -d %d
environ: (a 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', 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 image file name
        flag: %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
rep_history: (a unicode string)
        note with which to replace history
        flag: -HH "%s"
        mutually_exclusive: add_history
ses: (a boolean)
        print to stdout the expanded notes
        flag: -ses
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

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.

Examples¶

>>> from nipype.interfaces import afni
>>> refit = afni.Refit()
>>> refit.inputs.in_file = 'structural.nii'
>>> refit.inputs.deoblique = True
>>> refit.cmdline  
'3drefit -deoblique structural.nii'
>>> res = refit.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3drefit
        flag: %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
deoblique: (a boolean)
        replace current transformation matrix with cardinal matrix
        flag: -deoblique
environ: (a 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', 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
space: ('TLRC' or 'MNI' or 'ORIG')
        Associates the dataset with a specific template type, e.g. TLRC,
        MNI, ORIG
        flag: -space %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored
xdel: (a float)
        new x voxel dimension in mm
        flag: -xdel %f
xorigin: (a unicode string)
        x distance for edge voxel offset
        flag: -xorigin %s
ydel: (a float)
        new y voxel dimension in mm
        flag: -ydel %f
yorigin: (a unicode string)
        y distance for edge voxel offset
        flag: -yorigin %s
zdel: (a float)
        new z voxel dimension in mm
        flag: -zdel %f
zorigin: (a unicode string)
        z distance for edge voxel offset
        flag: -zorigin %s

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
>>> resample = afni.Resample()
>>> resample.inputs.in_file = 'functional.nii'
>>> resample.inputs.orientation= 'RPI'
>>> resample.inputs.outputtype = 'NIFTI'
>>> resample.cmdline  
'3dresample -orient RPI -prefix functional_resample.nii -inset functional.nii'
>>> res = resample.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dresample
        flag: -inset %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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
master: (a file name)
        align dataset grid to a reference file
        flag: -master %s
orientation: (a unicode string)
        new orientation code
        flag: -orient %s
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
resample_mode: ('NN' or 'Li' or 'Cu' or 'Bk')
        resampling method from set {"NN", "Li", "Cu", "Bk"}. These are for
        "Nearest Neighbor", "Linear", "Cubic" and "Blocky"interpolation,
        respectively. Default is NN.
        flag: -rmode %s
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored
voxel_size: (a tuple of the form: (a float, a float, a float))
        resample to new dx, dy and dz
        flag: -dxyz %f %f %f

Outputs:

out_file: (an existing file name)
        output file

References:: None None

TCat¶

Link to code

Wraps command 3dTcat

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

TODO Replace InputMultiPath in_files with Traits.List, if possible. Current version adds extra whitespace.

For complete details, see the 3dTcat Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> tcat = afni.TCat()
>>> tcat.inputs.in_files = ['functional.nii', 'functional2.nii']
>>> tcat.inputs.out_file= 'functional_tcat.nii'
>>> tcat.inputs.rlt = '+'
>>> tcat.cmdline  
'3dTcat -rlt+ -prefix functional_tcat.nii functional.nii functional2.nii'
>>> res = tcat.run()  

Inputs:

[Mandatory]
in_files: (a list of items which are an existing file name)
        input file to 3dTcat
        flag:  %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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 image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
rlt: ('' or '+' or '++')
        Remove linear trends in each voxel time series loaded from each
        input dataset, SEPARATELY. Option -rlt removes the least squares fit
        of 'a+b*t' to each voxel time series. Option -rlt+ adds dataset mean
        back in. Option -rlt++ adds overall mean of all dataset timeseries
        back in.
        flag: -rlt%s, position: 1
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

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
>>> tstat = afni.TStat()
>>> tstat.inputs.in_file = 'functional.nii'
>>> tstat.inputs.args = '-mean'
>>> tstat.inputs.out_file = 'stats'
>>> tstat.cmdline  
'3dTstat -mean -prefix stats functional.nii'
>>> res = tstat.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dTstat
        flag: %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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 file
        flag: -mask %s
options: (a unicode string)
        selected statistical output
        flag: %s
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

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.in_folder = '.'
>>> to3d.inputs.out_file = 'dicomdir.nii'
>>> to3d.inputs.filetype = 'anat'
>>> to3d.cmdline  
'to3d -datum float -anat -prefix dicomdir.nii ./*.dcm'
>>> res = to3d.run()  

Inputs:

[Mandatory]
in_folder: (an existing directory name)
        folder with DICOM images to convert
        flag: %s/*.dcm, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
assumemosaic: (a boolean)
        assume that Siemens image is mosaic
        flag: -assume_dicom_mosaic
datatype: ('short' or 'float' or 'byte' or 'complex')
        set output file datatype
        flag: -datum %s
environ: (a 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', 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
        flag: -%s
funcparams: (a unicode string)
        parameters for functional data
        flag: -time:zt %s alt+z2
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 image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
skipoutliers: (a boolean)
        skip the outliers check
        flag: -skip_outliers
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

Unifize¶

Link to code

Wraps command 3dUnifize

3dUnifize - for uniformizing image intensity

The input dataset is supposed to be a T1-weighted volume, possibly already skull-stripped (e.g., via 3dSkullStrip). However, this program can be a useful step to take BEFORE 3dSkullStrip, since the latter program can fail if the input volume is strongly shaded – 3dUnifize will (mostly) remove such shading artifacts.
The output dataset has the white matter (WM) intensity approximately uniformized across space, and scaled to peak at about 1000.
The output dataset is always stored in float format!
If the input dataset has more than 1 sub-brick, only sub-brick #0 will be processed!
Want to correct EPI datasets for nonuniformity? You can try the new and experimental [Mar 2017] ‘-EPI’ option.
The principal motive for this program is for use in an image registration script, and it may or may not be useful otherwise.
This program replaces the older (and very different) 3dUniformize, which is no longer maintained and may sublimate at any moment. (In other words, we do not recommend the use of 3dUniformize.)

For complete details, see the 3dUnifize Documentation.

Examples¶

>>> from nipype.interfaces import afni
>>> unifize = afni.Unifize()
>>> unifize.inputs.in_file = 'structural.nii'
>>> unifize.inputs.out_file = 'structural_unifized.nii'
>>> unifize.cmdline  
'3dUnifize -prefix structural_unifized.nii -input structural.nii'
>>> res = unifize.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dUnifize
        flag: -input %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', nipype default value: {})
        Environment variables
epi: (a boolean)
        Assume the input dataset is a T2 (or T2*) weighted EPI time series.
        After computing the scaling, apply it to ALL volumes (TRs) in the
        input dataset. That is, a given voxel will be scaled by the same
        factor at each TR. This option also implies '-noduplo' and
        '-T2'.This option turns off '-GM' if you turned it on.
        flag: -EPI
        mutually_exclusive: gm
        requires: no_duplo, t2
gm: (a boolean)
        Also scale to unifize 'gray matter' = lower intensity voxels (to aid
        in registering images from different scanners).
        flag: -GM
ignore_exception: (a boolean, nipype default value: False)
        Print an error message instead of throwing an exception in case the
        interface fails to run
no_duplo: (a boolean)
        Do NOT use the 'duplo down' step; this can be useful for lower
        resolution datasets.
        flag: -noduplo
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
scale_file: (a file name)
        output file name to save the scale factor used at each voxel
        flag: -ssave %s
t2: (a boolean)
        Treat the input as if it were T2-weighted, rather than T1-weighted.
        This processing is done simply by inverting the image contrast,
        processing it as if that result were T1-weighted, and then re-
        inverting the results counts of voxel overlap, i.e., each voxel will
        contain the number of masks that it is set in.
        flag: -T2
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored
urad: (a float)
        Sets the radius (in voxels) of the ball used for the sneaky trick.
        Default value is 18.3, and should be changed proportionally if the
        dataset voxel size differs significantly from 1 mm.
        flag: -Urad %s

Outputs:

out_file: (an existing file name)
        unifized file
scale_file: (a file name)
        scale factor file

References:: None None

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
>>> zcutup = afni.ZCutUp()
>>> zcutup.inputs.in_file = 'functional.nii'
>>> zcutup.inputs.out_file = 'functional_zcutup.nii'
>>> zcutup.inputs.keep= '0 10'
>>> zcutup.cmdline  
'3dZcutup -keep 0 10 -prefix functional_zcutup.nii functional.nii'
>>> res = zcutup.run()  

Inputs:

[Mandatory]
in_file: (an existing file name)
        input file to 3dZcutup
        flag: %s, position: -1

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
environ: (a 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', 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 unicode string)
        slice range to keep in output
        flag: -keep %s
out_file: (a file name)
        output image file name
        flag: -prefix %s
outputtype: ('AFNI' or 'NIFTI_GZ' or 'NIFTI')
        AFNI output filetype
terminal_output: ('stream' or 'allatonce' or 'file' or 'none')
        Control terminal output: `stream` - displays to terminal immediately
        (default), `allatonce` - waits till command is finished to display
        output, `file` - writes output to file, `none` - output is ignored

Outputs:

out_file: (an existing file name)
        output file

References:: None None

Release	Devel
0.13.0	0.13.0
Download	Github

Table Of Contents

Versions

Links

interfaces.afni.utils¶

AFNItoNIFTI¶

Examples¶

Autobox¶

Examples¶

BrickStat¶

Examples¶

Calc¶

Examples¶

Copy¶

Examples¶

Eval¶

Examples¶

FWHMx¶

Examples¶

MaskTool¶

Examples¶

Merge¶

Examples¶

Notes¶

Examples¶

Refit¶

Examples¶

Resample¶

Examples¶

TCat¶

Examples¶

TStat¶

Examples¶

To3D¶

Examples¶

Unifize¶

Examples¶

ZCutUp¶

Examples¶