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# nipype.interfaces.mrtrix3.utils module

## BrainMask

Link to code

> Bases: CommandLine

> Wrapped executable: `dwi2mask`.

> Convert a mesh surface to a partial volume estimation image

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> bmsk = mrt.BrainMask()
>     >>> bmsk.inputs.in_file = 'dwi.mif'
>     >>> bmsk.cmdline
>     'dwi2mask dwi.mif brainmask.mif'
>     >>> bmsk.run()

> in_filea pathlike object or string representing an existing file

>   Input diffusion weighted images. Maps to a command-line argument: `%s` (position: -2).

> out_filea pathlike object or string representing a file

>   Output brain mask. Maps to a command-line argument: `%s` (position: -1). (Nipype default value: `brainmask.mif`)

> argsa unicode string

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

> bval_scale‘yes’ or ‘no’

>   Specifies whether the b - values should be scaled by the square of the corresponding DW gradient norm, as often required for multishell or DSI DW acquisition schemes. The default action can also be set in the MRtrix config file, under the BValueScaling entry. Valid choices are yes / no, true / false, 0 / 1 (default: true). Maps to a command-line argument: `-bvalue_scaling %s`.

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

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

> grad_filea pathlike object or string representing an existing file

>   Dw gradient scheme (MRTrix format). Maps to a command-line argument: `-grad %s`. Mutually exclusive with inputs: `grad_fsl`.

> grad_fsla tuple of the form: (a pathlike object or string representing an existing file, a pathlike object or string representing an existing file)

>   (bvecs, bvals) dw gradient scheme (FSL format). Maps to a command-line argument: `-fslgrad %s %s`. Mutually exclusive with inputs: `grad_file`.

> in_bvala pathlike object or string representing an existing file

>   Bvals file in FSL format.

> in_bveca pathlike object or string representing an existing file

>   Bvecs file in FSL format. Maps to a command-line argument: `-fslgrad %s %s`.

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> out_filea pathlike object or string representing an existing file

>   The output response file.

## ComputeTDI

Link to code

> Bases: MRTrix3Base

> Wrapped executable: `tckmap`.

> Use track data as a form of contrast for producing a high-resolution image.

> References

> - For TDI or DEC TDI: Calamante, F.; Tournier, J.-D.; Jackson, G. D. & Connelly, A. Track-density imaging (TDI): Super-resolution white matter imaging using whole-brain track-density mapping. NeuroImage, 2010, 53, 1233-1243

> - If using -contrast length and -stat_vox mean: Pannek, K.; Mathias, J. L.; Bigler, E. D.; Brown, G.; Taylor, J. D. & Rose, S. E. The average pathlength map: A diffusion MRI tractography-derived index for studying brain pathology. NeuroImage, 2011, 55, 133-141

> - If using -dixel option with TDI contrast only: Smith, R.E., Tournier, J-D., Calamante, F., Connelly, A. A novel paradigm for automated segmentation of very large whole-brain probabilistic tractography data sets. In proc. ISMRM, 2011, 19, 673

> - If using -dixel option with any other contrast: Pannek, K., Raffelt, D., Salvado, O., Rose, S. Incorporating directional information in diffusion tractography derived maps: angular track imaging (ATI). In Proc. ISMRM, 2012, 20, 1912

> - If using -tod option: Dhollander, T., Emsell, L., Van Hecke, W., Maes, F., Sunaert, S., Suetens, P. Track Orientation Density Imaging (TODI) and Track Orientation Distribution (TOD) based tractography. NeuroImage, 2014, 94, 312-336

> - If using other contrasts / statistics: Calamante, F.; Tournier, J.-D.; Smith, R. E. & Connelly, A. A generalised framework for super-resolution track-weighted imaging. NeuroImage, 2012, 59, 2494-2503

> - If using -precise mapping option: Smith, R. E.; Tournier, J.-D.; Calamante, F. & Connelly, A. SIFT: Spherical-deconvolution informed filtering of tractograms. NeuroImage, 2013, 67, 298-312 (Appendix 3)

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> tdi = mrt.ComputeTDI()
>     >>> tdi.inputs.in_file = 'dti.mif'
>     >>> tdi.cmdline
>     'tckmap dti.mif tdi.mif'
>     >>> tdi.run()

> in_filea pathlike object or string representing an existing file

>   Input tractography. Maps to a command-line argument: `%s` (position: -2).

> argsa unicode string

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

> contrast‘tdi’ or ‘length’ or ‘invlength’ or ‘scalar_map’ or ‘scalar_map_conut’ or ‘fod_amp’ or ‘curvature’

>   Define the desired form of contrast for the output image. Maps to a command-line argument: `-constrast %s`.

> data_type‘float’ or ‘unsigned int’

>   Specify output image data type. Maps to a command-line argument: `-datatype %s`.

> dixela pathlike object or string representing a file

>   Map streamlines todixels within each voxel. Directions are stored asazimuth elevation pairs. Maps to a command-line argument: `-dixel %s`.

> ends_onlya boolean

>   Only map the streamline endpoints to the image. Maps to a command-line argument: `-ends_only`.

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

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

> fwhm_tcka float

>   Define the statistic for choosing the contribution to be made by each streamline as a function of the samples taken along their lengths. Maps to a command-line argument: `-fwhm_tck %f`.

> in_mapa pathlike object or string representing an existing file

>   Provide thescalar image map for generating images with ‘scalar_map’ contrasts, or the SHs image for fod_amp. Maps to a command-line argument: `-image %s`.

> map_zeroa boolean

>   If a streamline has zero contribution based on the contrast & statistic, typically it is not mapped; use this option to still contribute to the map even if this is the case (these non-contributing voxels can then influence the mean value in each voxel of the map). Maps to a command-line argument: `-map_zero`.

> max_todan integer (int or long)

>   Generate a Track Orientation Distribution (TOD) in each voxel. Maps to a command-line argument: `-tod %d`.

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> out_filea pathlike object or string representing a file

>   Output TDI file. Maps to a command-line argument: `%s` (position: -1). (Nipype default value: `tdi.mif`)

> precisea boolean

>   Use a more precise streamline mapping strategy, that accurately quantifies the length through each voxel (these lengths are then taken into account during TWI calculation). Maps to a command-line argument: `-precise`.

> referencea pathlike object or string representing an existing file

>   A referenceimage to be used as template. Maps to a command-line argument: `-template %s`.

> stat_tck‘mean’ or ‘sum’ or ‘min’ or ‘max’ or ‘median’ or ‘mean_nonzero’ or ‘gaussian’ or ‘ends_min’ or ‘ends_mean’ or ‘ends_max’ or ‘ends_prod’

>   Define the statistic for choosing the contribution to be made by each streamline as a function of the samples taken along their lengths. Maps to a command-line argument: `-stat_tck %s`.

> stat_vox‘sum’ or ‘min’ or ‘mean’ or ‘max’

>   Define the statistic for choosing the finalvoxel intesities for a given contrast. Maps to a command-line argument: `-stat_vox %s`.

> tck_weightsa pathlike object or string representing an existing file

>   Specify a text scalar file containing the streamline weights. Maps to a command-line argument: `-tck_weights_in %s`.

> upsamplean integer (int or long)

>   Upsample the tracks by some ratio using Hermite interpolation before mappping. Maps to a command-line argument: `-upsample %d`.

> use_deca boolean

>   Perform mapping in DEC space. Maps to a command-line argument: `-dec`.

> vox_sizea list of items which are an integer (int or long)

>   Voxel dimensions. Maps to a command-line argument: `-vox %s`.

> out_filea pathlike object or string representing a file

>   Output TDI file.

## DWIExtract

Link to code

> Bases: MRTrix3Base

> Wrapped executable: `dwiextract`.

> Extract diffusion-weighted volumes, b=0 volumes, or certain shells from a DWI dataset

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> dwiextract = mrt.DWIExtract()
>     >>> dwiextract.inputs.in_file = 'dwi.mif'
>     >>> dwiextract.inputs.bzero = True
>     >>> dwiextract.inputs.out_file = 'b0vols.mif'
>     >>> dwiextract.inputs.grad_fsl = ('bvecs', 'bvals')
>     >>> dwiextract.cmdline
>     'dwiextract -bzero -fslgrad bvecs bvals dwi.mif b0vols.mif'
>     >>> dwiextract.run()

> in_filea pathlike object or string representing an existing file

>   Input image. Maps to a command-line argument: `%s` (position: -2).

> out_filea pathlike object or string representing a file

>   Output image. Maps to a command-line argument: `%s` (position: -1).

> argsa unicode string

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

> bval_scale‘yes’ or ‘no’

>   Specifies whether the b - values should be scaled by the square of the corresponding DW gradient norm, as often required for multishell or DSI DW acquisition schemes. The default action can also be set in the MRtrix config file, under the BValueScaling entry. Valid choices are yes / no, true / false, 0 / 1 (default: true). Maps to a command-line argument: `-bvalue_scaling %s`.

> bzeroa boolean

>   Extract b=0 volumes. Maps to a command-line argument: `-bzero`.

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

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

> grad_filea pathlike object or string representing an existing file

>   Dw gradient scheme (MRTrix format). Maps to a command-line argument: `-grad %s`. Mutually exclusive with inputs: `grad_fsl`.

> grad_fsla tuple of the form: (a pathlike object or string representing an existing file, a pathlike object or string representing an existing file)

>   (bvecs, bvals) dw gradient scheme (FSL format). Maps to a command-line argument: `-fslgrad %s %s`. Mutually exclusive with inputs: `grad_file`.

> in_bvala pathlike object or string representing an existing file

>   Bvals file in FSL format.

> in_bveca pathlike object or string representing an existing file

>   Bvecs file in FSL format. Maps to a command-line argument: `-fslgrad %s %s`.

> nobzeroa boolean

>   Extract non b=0 volumes. Maps to a command-line argument: `-no_bzero`.

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> shella list of items which are a float

>   Specify one or more gradient shells. Maps to a command-line argument: `-shell %s`.

> singleshella boolean

>   Extract volumes with a specific shell. Maps to a command-line argument: `-singleshell`.

> out_filea pathlike object or string representing an existing file

>   Output image.

## Generate5tt

Link to code

> Bases: MRTrix3Base

> Wrapped executable: `5ttgen`.

> Generate a 5TT image suitable for ACT using the selected algorithm

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> gen5tt = mrt.Generate5tt()
>     >>> gen5tt.inputs.in_file = 'T1.nii.gz'
>     >>> gen5tt.inputs.algorithm = 'fsl'
>     >>> gen5tt.inputs.out_file = '5tt.mif'
>     >>> gen5tt.cmdline
>     '5ttgen fsl T1.nii.gz 5tt.mif'
>     >>> gen5tt.run()

> algorithm‘fsl’ or ‘gif’ or ‘freesurfer’

>   Tissue segmentation algorithm. Maps to a command-line argument: `%s` (position: -3).

> in_filea pathlike object or string representing an existing file

>   Input image. Maps to a command-line argument: `%s` (position: -2).

> out_filea pathlike object or string representing a file

>   Output image. Maps to a command-line argument: `%s` (position: -1).

> argsa unicode string

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

> bval_scale‘yes’ or ‘no’

>   Specifies whether the b - values should be scaled by the square of the corresponding DW gradient norm, as often required for multishell or DSI DW acquisition schemes. The default action can also be set in the MRtrix config file, under the BValueScaling entry. Valid choices are yes / no, true / false, 0 / 1 (default: true). Maps to a command-line argument: `-bvalue_scaling %s`.

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

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

> grad_filea pathlike object or string representing an existing file

>   Dw gradient scheme (MRTrix format). Maps to a command-line argument: `-grad %s`. Mutually exclusive with inputs: `grad_fsl`.

> grad_fsla tuple of the form: (a pathlike object or string representing an existing file, a pathlike object or string representing an existing file)

>   (bvecs, bvals) dw gradient scheme (FSL format). Maps to a command-line argument: `-fslgrad %s %s`. Mutually exclusive with inputs: `grad_file`.

> in_bvala pathlike object or string representing an existing file

>   Bvals file in FSL format.

> in_bveca pathlike object or string representing an existing file

>   Bvecs file in FSL format. Maps to a command-line argument: `-fslgrad %s %s`.

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> out_filea pathlike object or string representing an existing file

>   Output image.

## MRConvert

Link to code

> Bases: MRTrix3Base

> Wrapped executable: `mrconvert`.

> Perform conversion between different file types and optionally extract a subset of the input image

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> mrconvert = mrt.MRConvert()
>     >>> mrconvert.inputs.in_file = 'dwi.nii.gz'
>     >>> mrconvert.inputs.grad_fsl = ('bvecs', 'bvals')
>     >>> mrconvert.cmdline
>     'mrconvert -fslgrad bvecs bvals dwi.nii.gz dwi.mif'
>     >>> mrconvert.run()

> in_filea pathlike object or string representing an existing file

>   Input image. Maps to a command-line argument: `%s` (position: -2).

> out_filea pathlike object or string representing a file

>   Output image. Maps to a command-line argument: `%s` (position: -1). (Nipype default value: `dwi.mif`)

> argsa unicode string

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

> axesa list of items which are an integer (int or long)

>   Specify the axes that will be used. Maps to a command-line argument: `-axes %s`.

> bval_scale‘yes’ or ‘no’

>   Specifies whether the b - values should be scaled by the square of the corresponding DW gradient norm, as often required for multishell or DSI DW acquisition schemes. The default action can also be set in the MRtrix config file, under the BValueScaling entry. Valid choices are yes / no, true / false, 0 / 1 (default: true). Maps to a command-line argument: `-bvalue_scaling %s`.

> coorda list of items which are an integer (int or long)

>   Extract data at the specified coordinates. Maps to a command-line argument: `-coord %s`.

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

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

> grad_filea pathlike object or string representing an existing file

>   Dw gradient scheme (MRTrix format). Maps to a command-line argument: `-grad %s`. Mutually exclusive with inputs: `grad_fsl`.

> grad_fsla tuple of the form: (a pathlike object or string representing an existing file, a pathlike object or string representing an existing file)

>   (bvecs, bvals) dw gradient scheme (FSL format). Maps to a command-line argument: `-fslgrad %s %s`. Mutually exclusive with inputs: `grad_file`.

> in_bvala pathlike object or string representing an existing file

>   Bvals file in FSL format.

> in_bveca pathlike object or string representing an existing file

>   Bvecs file in FSL format. Maps to a command-line argument: `-fslgrad %s %s`.

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> scalinga list of items which are a float

>   Specify the data scaling parameter. Maps to a command-line argument: `-scaling %s`.

> voxa list of items which are a float

>   Change the voxel dimensions. Maps to a command-line argument: `-vox %s`.

> out_filea pathlike object or string representing an existing file

>   Output image.

## MRMath

Link to code

> Bases: MRTrix3Base

> Wrapped executable: `mrmath`.

> Compute summary statistic on image intensities along a specified axis of a single image

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> mrmath = mrt.MRMath()
>     >>> mrmath.inputs.in_file = 'dwi.mif'
>     >>> mrmath.inputs.operation = 'mean'
>     >>> mrmath.inputs.axis = 3
>     >>> mrmath.inputs.out_file = 'dwi_mean.mif'
>     >>> mrmath.inputs.grad_fsl = ('bvecs', 'bvals')
>     >>> mrmath.cmdline
>     'mrmath -axis 3 -fslgrad bvecs bvals dwi.mif mean dwi_mean.mif'
>     >>> mrmath.run()

> in_filea pathlike object or string representing an existing file

>   Input image. Maps to a command-line argument: `%s` (position: -3).

> operation‘mean’ or ‘median’ or ‘sum’ or ‘product’ or ‘rms’ or ‘norm’ or ‘var’ or ‘std’ or ‘min’ or ‘max’ or ‘absmax’ or ‘magmax’

>   Operation to computer along a specified axis. Maps to a command-line argument: `%s` (position: -2).

> out_filea pathlike object or string representing a file

>   Output image. Maps to a command-line argument: `%s` (position: -1).

> argsa unicode string

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

> axisan integer (int or long)

>   Specfied axis to perform the operation along. Maps to a command-line argument: `-axis %d`.

> bval_scale‘yes’ or ‘no’

>   Specifies whether the b - values should be scaled by the square of the corresponding DW gradient norm, as often required for multishell or DSI DW acquisition schemes. The default action can also be set in the MRtrix config file, under the BValueScaling entry. Valid choices are yes / no, true / false, 0 / 1 (default: true). Maps to a command-line argument: `-bvalue_scaling %s`.

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

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

> grad_filea pathlike object or string representing an existing file

>   Dw gradient scheme (MRTrix format). Maps to a command-line argument: `-grad %s`. Mutually exclusive with inputs: `grad_fsl`.

> grad_fsla tuple of the form: (a pathlike object or string representing an existing file, a pathlike object or string representing an existing file)

>   (bvecs, bvals) dw gradient scheme (FSL format). Maps to a command-line argument: `-fslgrad %s %s`. Mutually exclusive with inputs: `grad_file`.

> in_bvala pathlike object or string representing an existing file

>   Bvals file in FSL format.

> in_bveca pathlike object or string representing an existing file

>   Bvecs file in FSL format. Maps to a command-line argument: `-fslgrad %s %s`.

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> out_filea pathlike object or string representing an existing file

>   Output image.

## MRResize

Link to code

> Bases: MRTrix3Base

> Wrapped executable: `mrresize`.

> Resize an image by defining the new image resolution, voxel size or a scale factor. If the image is 4D, then only the first 3 dimensions can be resized. Also, if the image is down-sampled, the appropriate smoothing is automatically applied using Gaussian smoothing. For more information, see <https://mrtrix.readthedocs.io/en/latest/reference/commands/mrresize.html>

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt

> Defining the new image resolution: >>> image_resize = mrt.MRResize() >>> image_resize.inputs.in_file = ‘dwi.mif’ >>> image_resize.inputs.image_size = (256, 256, 144) >>> image_resize.cmdline # doctest: +ELLIPSIS ‘mrresize -size 256,256,144 -interp cubic dwi.mif dwi_resized.mif’ >>> image_resize.run() # doctest: +SKIP

> Defining the new image’s voxel size: >>> voxel_resize = mrt.MRResize() >>> voxel_resize.inputs.in_file = ‘dwi.mif’ >>> voxel_resize.inputs.voxel_size = (1, 1, 1) >>> voxel_resize.cmdline # doctest: +ELLIPSIS ‘mrresize -interp cubic -voxel 1,1,1 dwi.mif dwi_resized.mif’ >>> voxel_resize.run() # doctest: +SKIP

> Defining the scale factor of each image dimension: >>> scale_resize = mrt.MRResize() >>> scale_resize.inputs.in_file = ‘dwi.mif’ >>> scale_resize.inputs.scale_factor = (0.5,0.5,0.5) >>> scale_resize.cmdline # doctest: +ELLIPSIS ‘mrresize -interp cubic -scale 0.5,0.5,0.5 dwi.mif dwi_resized.mif’ >>> scale_resize.run() # doctest: +SKIP

> image_sizea tuple of the form: (an integer (int or long), an integer (int or long), an integer (int or long))

>   Number of voxels in each dimension of output image. Maps to a command-line argument: `-size %d,%d,%d`. Mutually exclusive with inputs: `voxel_size`, `scale_factor`.

> in_filea pathlike object or string representing an existing file

>   Input DWI image. Maps to a command-line argument: `%s` (position: -2).

> scale_factora tuple of the form: (a float, a float, a float)

>   Scale factors to rescale the image by in each dimension. Maps to a command-line argument: `-scale %g,%g,%g`. Mutually exclusive with inputs: `image_size`, `voxel_size`.

> voxel_sizea tuple of the form: (a float, a float, a float)

>   Desired voxel size in mm for the output image. Maps to a command-line argument: `-voxel %g,%g,%g`. Mutually exclusive with inputs: `image_size`, `scale_factor`.

> argsa unicode string

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

> bval_scale‘yes’ or ‘no’

>   Specifies whether the b - values should be scaled by the square of the corresponding DW gradient norm, as often required for multishell or DSI DW acquisition schemes. The default action can also be set in the MRtrix config file, under the BValueScaling entry. Valid choices are yes / no, true / false, 0 / 1 (default: true). Maps to a command-line argument: `-bvalue_scaling %s`.

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

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

> grad_filea pathlike object or string representing an existing file

>   Dw gradient scheme (MRTrix format). Maps to a command-line argument: `-grad %s`. Mutually exclusive with inputs: `grad_fsl`.

> grad_fsla tuple of the form: (a pathlike object or string representing an existing file, a pathlike object or string representing an existing file)

>   (bvecs, bvals) dw gradient scheme (FSL format). Maps to a command-line argument: `-fslgrad %s %s`. Mutually exclusive with inputs: `grad_file`.

> in_bvala pathlike object or string representing an existing file

>   Bvals file in FSL format.

> in_bveca pathlike object or string representing an existing file

>   Bvecs file in FSL format. Maps to a command-line argument: `-fslgrad %s %s`.

> interpolation‘cubic’ or ‘nearest’ or ‘linear’ or ‘sinc’

>   Set the interpolation method to use when resizing (choices: nearest, linear, cubic, sinc. Default: cubic). Maps to a command-line argument: `-interp %s`. (Nipype default value: `cubic`)

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> out_filea pathlike object or string representing a file

>   The output resized DWI image. Maps to a command-line argument: `%s` (position: -1).

> out_filea pathlike object or string representing an existing file

>   The output resized DWI image.

## Mesh2PVE

Link to code

> Bases: CommandLine

> Wrapped executable: `mesh2pve`.

> Convert a mesh surface to a partial volume estimation image

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> m2p = mrt.Mesh2PVE()
>     >>> m2p.inputs.in_file = 'surf1.vtk'
>     >>> m2p.inputs.reference = 'dwi.mif'
>     >>> m2p.inputs.in_first = 'T1.nii.gz'
>     >>> m2p.cmdline
>     'mesh2pve -first T1.nii.gz surf1.vtk dwi.mif mesh2volume.nii.gz'
>     >>> m2p.run()

> in_filea pathlike object or string representing an existing file

>   Input mesh. Maps to a command-line argument: `%s` (position: -3).

> out_filea pathlike object or string representing a file

>   Output file containing SH coefficients. Maps to a command-line argument: `%s` (position: -1). (Nipype default value: `mesh2volume.nii.gz`)

> referencea pathlike object or string representing an existing file

>   Input reference image. Maps to a command-line argument: `%s` (position: -2).

> argsa unicode string

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

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

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

> in_firsta pathlike object or string representing an existing file

>   Indicates that the mesh file is provided by FSL FIRST. Maps to a command-line argument: `-first %s`.

> out_filea pathlike object or string representing an existing file

>   The output response file.

## SH2Amp

Link to code

> Bases: CommandLine

> Wrapped executable: `sh2amp`.

> Sample spherical harmonics on a set of gradient orientations. Useful for checking residuals of ODF estimates.

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> sh = mrt.SH2Amp()
>     >>> sh.inputs.in_file = 'sh.mif'
>     >>> sh.inputs.directions = 'grads.txt'
>     >>> sh.cmdline
>     'sh2amp sh.mif grads.txt sh_amp.mif'
>     >>> sh.run()

> directionsa pathlike object or string representing an existing file

>   The gradient directions along which to sample the spherical harmonics MRtrix format. Maps to a command-line argument: `%s` (position: -2).

> in_filea pathlike object or string representing an existing file

>   Input ODF image. Maps to a command-line argument: `%s` (position: -3).

> argsa unicode string

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

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

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

> nonnegativea boolean

>   Cap all negative amplitudes to zero. Maps to a command-line argument: `-nonnegative`.

> out_filea pathlike object or string representing a file

>   The output spherical harmonics. Maps to a command-line argument: `%s` (position: -1). (Nipype default value: `<undefined>`)

> out_filea pathlike object or string representing an existing file

>   The output convoluted spherical harmonics file.

## SHConv

Link to code

> Bases: CommandLine

> Wrapped executable: `shconv`.

> Convolve spherical harmonics with a tissue response function. Useful for checking residuals of ODF estimates.

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> sh = mrt.SHConv()
>     >>> sh.inputs.in_file = 'csd.mif'
>     >>> sh.inputs.response = 'response.txt'
>     >>> sh.cmdline
>     'shconv csd.mif response.txt csd_shconv.mif'
>     >>> sh.run()

> in_filea pathlike object or string representing an existing file

>   Input ODF image. Maps to a command-line argument: `%s` (position: -3).

> responsea pathlike object or string representing an existing file

>   The response function. Maps to a command-line argument: `%s` (position: -2).

> argsa unicode string

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

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

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

> out_filea pathlike object or string representing a file

>   The output spherical harmonics. Maps to a command-line argument: `%s` (position: -1). (Nipype default value: `<undefined>`)

> out_filea pathlike object or string representing an existing file

>   The output convoluted spherical harmonics file.

## TCK2VTK

Link to code

> Bases: MRTrix3Base

> Wrapped executable: `tck2vtk`.

> Convert a track file to a vtk format, cave: coordinates are in XYZ coordinates not reference

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> vtk = mrt.TCK2VTK()
>     >>> vtk.inputs.in_file = 'tracks.tck'
>     >>> vtk.inputs.reference = 'b0.nii'
>     >>> vtk.cmdline
>     'tck2vtk -image b0.nii tracks.tck tracks.vtk'
>     >>> vtk.run()

> in_filea pathlike object or string representing an existing file

>   Input tractography. Maps to a command-line argument: `%s` (position: -2).

> argsa unicode string

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

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

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

> nthreadsan integer (int or long)

>   Number of threads. if zero, the number of available cpus will be used. Maps to a command-line argument: `-nthreads %d`.

> out_filea pathlike object or string representing a file

>   Output VTK file. Maps to a command-line argument: `%s` (position: -1). (Nipype default value: `tracks.vtk`)

> referencea pathlike object or string representing an existing file

>   If specified, the properties of this image will be used to convert track point positions from real (scanner) coordinates into image coordinates (in mm). Maps to a command-line argument: `-image %s`.

> voxela pathlike object or string representing an existing file

>   If specified, the properties of this image will be used to convert track point positions from real (scanner) coordinates into image coordinates. Maps to a command-line argument: `-image %s`.

> out_filea pathlike object or string representing a file

>   Output VTK file.

## TensorMetrics

Link to code

> Bases: CommandLine

> Wrapped executable: `tensor2metric`.

> Compute metrics from tensors

> Example

>     >>> import nipype.interfaces.mrtrix3 as mrt
>     >>> comp = mrt.TensorMetrics()
>     >>> comp.inputs.in_file = 'dti.mif'
>     >>> comp.inputs.out_fa = 'fa.mif'
>     >>> comp.cmdline
>     'tensor2metric -num 1 -fa fa.mif dti.mif'
>     >>> comp.run()

> in_filea pathlike object or string representing an existing file

>   Input DTI image. Maps to a command-line argument: `%s` (position: -1).

> argsa unicode string

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

> componenta list of items which are any value

>   Specify the desired eigenvalue/eigenvector(s). Note that several eigenvalues can be specified as a number sequence. Maps to a command-line argument: `-num %s`. (Nipype default value: `[1]`)

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

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

> in_maska pathlike object or string representing an existing file

>   Only perform computation within the specified binary brain mask image. Maps to a command-line argument: `-mask %s`.

> modulate‘FA’ or ‘none’ or ‘eval’

>   How to modulate the magnitude of the eigenvectors. Maps to a command-line argument: `-modulate %s`.

> out_adca pathlike object or string representing a file

>   Output ADC file. Maps to a command-line argument: `-adc %s`.

> out_evala pathlike object or string representing a file

>   Output selected eigenvalue(s) file. Maps to a command-line argument: `-value %s`.

> out_eveca pathlike object or string representing a file

>   Output selected eigenvector(s) file. Maps to a command-line argument: `-vector %s`.

> out_faa pathlike object or string representing a file

>   Output FA file. Maps to a command-line argument: `-fa %s`.

> out_adca pathlike object or string representing a file

>   Output ADC file.

> out_evala pathlike object or string representing a file

>   Output selected eigenvalue(s) file.

> out_eveca pathlike object or string representing a file

>   Output selected eigenvector(s) file.

> out_faa pathlike object or string representing a file

>   Output FA file.