interfaces.fsl.maths

AR1Image

Link to code

Wraps command fslmaths

Use fslmaths to generate an AR1 coefficient image across a given dimension. (Should use -odt float and probably demean first)

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to find AR(1) coefficientacross
        flag: -%sar1, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

ApplyMask

Link to code

Wraps command fslmaths

Use fslmaths to apply a binary mask to another image.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
mask_file: (an existing file name)
        binary image defining mask space
        flag: -mas %s, position: 4

[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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

BinaryMaths

Link to code

Wraps command fslmaths

Use fslmaths to perform mathematical operations using a second image or a numeric value.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
operand_file: (an existing file name)
        second image to perform operation with
        flag: %s, position: 5
        mutually_exclusive: operand_value
operand_value: (a float)
        value to perform operation with
        flag: %.8f, position: 5
        mutually_exclusive: operand_file
operation: ('add' or 'sub' or 'mul' or 'div' or 'rem' or 'max' or
         'min')
        operation to perform
        flag: -%s, position: 4

[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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

ChangeDataType

Link to code

Wraps command fslmaths

Use fslmaths to change the datatype of an image.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        output data type
        flag: -odt %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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

DilateImage

Link to code

Wraps command fslmaths

Use fslmaths to perform a spatial dilation of an image.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
operation: ('mean' or 'modal' or 'max')
        filtering operation to perfoem in dilation
        flag: -dil%s, position: 6

[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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
kernel_file: (an existing file name)
        use external file for kernel
        flag: %s, position: 5
        mutually_exclusive: kernel_size
kernel_shape: ('3D' or '2D' or 'box' or 'boxv' or 'gauss' or 'sphere'
         or 'file')
        kernel shape to use
        flag: -kernel %s, position: 4
kernel_size: (a float)
        kernel size - voxels for box/boxv, mm for sphere, mm sigma for gauss
        flag: %.4f, position: 5
        mutually_exclusive: kernel_file
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

ErodeImage

Link to code

Wraps command fslmaths

Use fslmaths to perform a spatial erosion of an image.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
kernel_file: (an existing file name)
        use external file for kernel
        flag: %s, position: 5
        mutually_exclusive: kernel_size
kernel_shape: ('3D' or '2D' or 'box' or 'boxv' or 'gauss' or 'sphere'
         or 'file')
        kernel shape to use
        flag: -kernel %s, position: 4
kernel_size: (a float)
        kernel size - voxels for box/boxv, mm for sphere, mm sigma for gauss
        flag: %.4f, position: 5
        mutually_exclusive: kernel_file
minimum_filter: (a boolean, nipype default value: False)
        if true, minimum filter rather than erosion by zeroing-out
        flag: %s, position: 6
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

IsotropicSmooth

Link to code

Wraps command fslmaths

Use fslmaths to spatially smooth an image with a gaussian kernel.

Inputs:

[Mandatory]
fwhm: (a float)
        fwhm of smoothing kernel [mm]
        flag: -s %.5f, position: 4
        mutually_exclusive: sigma
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
sigma: (a float)
        sigma of smoothing kernel [mm]
        flag: -s %.5f, position: 4
        mutually_exclusive: fwhm

[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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

MathsCommand

Link to code

Wraps command fslmaths

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

MaxImage

Link to code

Wraps command fslmaths

Use fslmaths to generate a max image across a given dimension.

Examples

>>> from nipype.interfaces.fsl.maths import MaxImage
>>> maxer = MaxImage()
>>> maxer.inputs.in_file = "functional.nii"  # doctest: +SKIP
>>> maxer.dimension = "T"
>>> maxer.cmdline  # doctest: +SKIP
'fslmaths functional.nii -Tmax functional_max.nii'

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to max across
        flag: -%smax, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

MaxnImage

Link to code

Wraps command fslmaths

Use fslmaths to generate an image of index of max across a given dimension.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to index max across
        flag: -%smaxn, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

MeanImage

Link to code

Wraps command fslmaths

Use fslmaths to generate a mean image across a given dimension.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to mean across
        flag: -%smean, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

MedianImage

Link to code

Wraps command fslmaths

Use fslmaths to generate a median image across a given dimension.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to median across
        flag: -%smedian, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

MinImage

Link to code

Wraps command fslmaths

Use fslmaths to generate a minimum image across a given dimension.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to min across
        flag: -%smin, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

MultiImageMaths

Link to code

Wraps command fslmaths

Use fslmaths to perform a sequence of mathematical operations.

Examples

>>> from nipype.interfaces.fsl import MultiImageMaths
>>> maths = MultiImageMaths()
>>> maths.inputs.in_file = "functional.nii"
>>> maths.inputs.op_string = "-add %s -mul -1 -div %s"
>>> maths.inputs.operand_files = ["functional2.nii", "functional3.nii"]
>>> maths.inputs.out_file = "functional4.nii"
>>> maths.cmdline
'fslmaths functional.nii -add functional2.nii -mul -1 -div functional3.nii functional4.nii'

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
op_string: (a string)
        python formatted string of operations to perform
        flag: %s, position: 4
operand_files: (a list of items which are an existing file name)
        list of file names to plug into op string

[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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

PercentileImage

Link to code

Wraps command fslmaths

Use fslmaths to generate a percentile image across a given dimension.

Examples

>>> from nipype.interfaces.fsl.maths import MaxImage
>>> percer = PercentileImage()
>>> percer.inputs.in_file = "functional.nii"  # doctest: +SKIP
>>> percer.dimension = "T"
>>> percer.perc = 90
>>> percer.cmdline  # doctest: +SKIP
'fslmaths functional.nii -Tperc 90 functional_perc.nii'

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to percentile across
        flag: -%sperc, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type
perc: (0 <= a long integer <= 100)
        nth percentile (0-100) of FULL RANGE across dimension
        flag: %f, position: 5

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

SpatialFilter

Link to code

Wraps command fslmaths

Use fslmaths to spatially filter an image.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
operation: ('mean' or 'median' or 'meanu')
        operation to filter with
        flag: -f%s, position: 6

[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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
kernel_file: (an existing file name)
        use external file for kernel
        flag: %s, position: 5
        mutually_exclusive: kernel_size
kernel_shape: ('3D' or '2D' or 'box' or 'boxv' or 'gauss' or 'sphere'
         or 'file')
        kernel shape to use
        flag: -kernel %s, position: 4
kernel_size: (a float)
        kernel size - voxels for box/boxv, mm for sphere, mm sigma for gauss
        flag: %.4f, position: 5
        mutually_exclusive: kernel_file
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

StdImage

Link to code

Wraps command fslmaths

Use fslmaths to generate a standard deviation in an image across a given dimension.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
dimension: ('T' or 'X' or 'Y' or 'Z', nipype default value: T)
        dimension to standard deviate across
        flag: -%sstd, position: 4
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

TemporalFilter

Link to code

Wraps command fslmaths

Use fslmaths to apply a low, high, or bandpass temporal filter to a timeseries.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        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
highpass_sigma: (a float, nipype default value: -1)
        highpass filter sigma (in volumes)
        flag: -bptf %.6f, position: 4
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
lowpass_sigma: (a float, nipype default value: -1)
        lowpass filter sigma (in volumes)
        flag: %.6f, position: 5
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

Threshold

Link to code

Wraps command fslmaths

Use fslmaths to apply a threshold to an image in a variety of ways.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
thresh: (a float)
        threshold value
        flag: %s, position: 4

[Optional]
args: (a unicode string)
        Additional parameters to the command
        flag: %s
direction: ('below' or 'above', nipype default value: below)
        zero-out either below or above thresh value
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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type
use_nonzero_voxels: (a boolean)
        use nonzero voxels to calculate robust range
        requires: use_robust_range
use_robust_range: (a boolean)
        interpret thresh as percentage (0-100) of robust range

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)

UnaryMaths

Link to code

Wraps command fslmaths

Use fslmaths to perorm a variety of mathematical operations on an image.

Inputs:

[Mandatory]
in_file: (an existing file name)
        image to operate on
        flag: %s, position: 2
operation: ('exp' or 'log' or 'sin' or 'cos' or 'tan' or 'asin' or
         'acos' or 'atan' or 'sqr' or 'sqrt' or 'recip' or 'abs' or 'bin' or
         'binv' or 'fillh' or 'fillh26' or 'index' or 'edge' or 'nan' or
         'nanm' or 'rand' or 'randn' or 'range')
        operation to perform
        flag: -%s, position: 4

[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
internal_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for calculations (default is float)
        flag: -dt %s, position: 1
nan2zeros: (a boolean)
        change NaNs to zeros before doing anything
        flag: -nan, position: 3
out_file: (a file name)
        image to write
        flag: %s, position: -2
output_datatype: ('float' or 'char' or 'int' or 'short' or 'double'
         or 'input')
        datatype to use for output (default uses input type)
        flag: -odt %s, position: -1
output_type: ('NIFTI' or 'NIFTI_PAIR' or 'NIFTI_GZ' or
         'NIFTI_PAIR_GZ')
        FSL output type

Outputs:

out_file: (an existing file name)
        image written after calculations

References:: BibTeX(‘@article{JenkinsonBeckmannBehrensWoolrichSmith2012,author={M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, and S.M. Smith},title={FSL},journal={NeuroImage},volume={62},pages={782-790},year={2012},}’, key=’JenkinsonBeckmannBehrensWoolrichSmith2012’)