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# nipype.interfaces.niftyfit.dwi module

The dwi module of niftyfit, which wraps the fitting methods in NiftyFit.

## DwiTool

Link to code

> Bases: NiftyFitCommand

> Wrapped executable: `dwi_tool`.

> Interface for executable dwi_tool from Niftyfit platform.

> Use DwiTool.

> Diffusion-Weighted MR Prediction. Predicts DWI from previously fitted models and calculates model derived maps.

> Source code

> Examples

>     >>> from nipype.interfaces import niftyfit
>     >>> dwi_tool = niftyfit.DwiTool(dti_flag=True)
>     >>> dwi_tool.inputs.source_file = 'dwi.nii.gz'
>     >>> dwi_tool.inputs.bvec_file = 'bvecs'
>     >>> dwi_tool.inputs.bval_file = 'bvals'
>     >>> dwi_tool.inputs.mask_file = 'mask.nii.gz'
>     >>> dwi_tool.inputs.b0_file = 'b0.nii.gz'
>     >>> dwi_tool.inputs.rgbmap_file = 'rgb_map.nii.gz'
>     >>> dwi_tool.cmdline
>     'dwi_tool -source dwi.nii.gz -bval bvals -bvec bvecs -b0 b0.nii.gz -mask mask.nii.gz -dti -famap dwi_famap.nii.gz -logdti2 dwi_logdti2.nii.gz -mcmap dwi_mcmap.nii.gz -mdmap dwi_mdmap.nii.gz -rgbmap rgb_map.nii.gz -syn dwi_syn.nii.gz -v1map dwi_v1map.nii.gz'

> bval_filea pathlike object or string representing an existing file

>   The file containing the bvalues of the source DWI. Maps to a command-line argument: `-bval %s` (position: 2).

> source_filea pathlike object or string representing an existing file

>   The source image containing the fitted model. Maps to a command-line argument: `-source %s` (position: 1).

> argsa unicode string

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

> b0_filea pathlike object or string representing an existing file

>   The B0 image corresponding to the source DWI. Maps to a command-line argument: `-b0 %s` (position: 4).

> ball_flaga boolean

>   Input is a ball and stick model. Maps to a command-line argument: `-ball` (position: 6). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `dti_flag2`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> ballv_flaga boolean

>   Input is a ball and stick model with optimised PDD. Maps to a command-line argument: `-ballv` (position: 6). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `dti_flag2`, `ball_flag`, `nod_flag`, `nodv_flag`.

> bvec_filea pathlike object or string representing an existing file

>   The file containing the bvectors of the source DWI. Maps to a command-line argument: `-bvec %s` (position: 3).

> diso_vala float

>   Isotropic diffusivity for -nod [3e-3]. Maps to a command-line argument: `-diso %f`.

> dpr_vala float

>   Parallel diffusivity for -nod [1.7e-3]. Maps to a command-line argument: `-dpr %f`.

> dti_flaga boolean

>   Input is a tensor model diag/off-diag. Maps to a command-line argument: `-dti` (position: 6). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag2`, `ball_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> dti_flag2a boolean

>   Input is a tensor model lower triangular. Maps to a command-line argument: `-dti2` (position: 6). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `ball_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> 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: `{}`)

> famap_filea pathlike object or string representing a file

>   Filename of FA map. Maps to a command-line argument: `-famap %s`.

> ivim_flaga boolean

>   Inputs is an IVIM model to non-directional data. Maps to a command-line argument: `-ivim` (position: 6). Mutually exclusive with inputs: `mono_flag`, `dti_flag`, `dti_flag2`, `ball_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> logdti_filea pathlike object or string representing a file

>   Filename of output logdti map. Maps to a command-line argument: `-logdti2 %s`.

> mask_filea pathlike object or string representing an existing file

>   The image mask. Maps to a command-line argument: `-mask %s` (position: 5).

> mcmap_filea pathlike object or string representing a file

>   Filename of multi-compartment model parameter map (-ivim,-ball,-nod). Maps to a command-line argument: `-mcmap %s`.

> mdmap_filea pathlike object or string representing a file

>   Filename of MD map/ADC. Maps to a command-line argument: `-mdmap %s`.

> mono_flaga boolean

>   Input is a single exponential to non-directional data [default with no b-vectors]. Maps to a command-line argument: `-mono` (position: 6). Mutually exclusive with inputs: `ivim_flag`, `dti_flag`, `dti_flag2`, `ball_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> nod_flaga boolean

>   Input is a NODDI model. Maps to a command-line argument: `-nod` (position: 6). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `dti_flag2`, `ball_flag`, `ballv_flag`, `nodv_flag`.

> nodv_flaga boolean

>   Input is a NODDI model with optimised PDD. Maps to a command-line argument: `-nodv` (position: 6). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `dti_flag2`, `ball_flag`, `ballv_flag`, `nod_flag`.

> rgbmap_filea pathlike object or string representing a file

>   Filename of colour FA map. Maps to a command-line argument: `-rgbmap %s`.

> syn_filea pathlike object or string representing a file

>   Filename of synthetic image. Requires: bvec_file/b0_file. Maps to a command-line argument: `-syn %s`. Requires inputs: `bvec_file`, `b0_file`.

> v1map_filea pathlike object or string representing a file

>   Filename of PDD map [x,y,z]. Maps to a command-line argument: `-v1map %s`.

> famap_filea pathlike object or string representing a file

>   Filename of FA map.

> logdti_filea pathlike object or string representing a file

>   Filename of output logdti map.

> mcmap_filea pathlike object or string representing a file

>   Filename of multi-compartment model parameter map (-ivim,-ball,-nod).

> mdmap_filea pathlike object or string representing a file

>   Filename of MD map/ADC.

> rgbmap_filea pathlike object or string representing a file

>   Filename of colour FA map.

> syn_filea pathlike object or string representing a file

>   Filename of synthetic image.

> v1map_filea pathlike object or string representing a file

>   Filename of PDD map [x,y,z].

## FitDwi

Link to code

> Bases: NiftyFitCommand

> Wrapped executable: `fit_dwi`.

> Interface for executable fit_dwi from Niftyfit platform.

> Use NiftyFit to perform diffusion model fitting.

> Diffusion-weighted MR Fitting. Fits DWI parameter maps to multi-shell, multi-directional data.

> Source code

> Examples

>     >>> from nipype.interfaces import niftyfit
>     >>> fit_dwi = niftyfit.FitDwi(dti_flag=True)
>     >>> fit_dwi.inputs.source_file = 'dwi.nii.gz'
>     >>> fit_dwi.inputs.bvec_file = 'bvecs'
>     >>> fit_dwi.inputs.bval_file = 'bvals'
>     >>> fit_dwi.inputs.rgbmap_file = 'rgb.nii.gz'
>     >>> fit_dwi.cmdline
>     'fit_dwi -source dwi.nii.gz -bval bvals -bvec bvecs -dti -error dwi_error.nii.gz -famap dwi_famap.nii.gz -mcout dwi_mcout.txt -mdmap dwi_mdmap.nii.gz -nodiff dwi_no_diff.nii.gz -res dwi_resmap.nii.gz -rgbmap rgb.nii.gz -syn dwi_syn.nii.gz -tenmap2 dwi_tenmap2.nii.gz -v1map dwi_v1map.nii.gz'

> bval_filea pathlike object or string representing an existing file

>   The file containing the bvalues of the source DWI. Maps to a command-line argument: `-bval %s` (position: 2).

> bvec_filea pathlike object or string representing an existing file

>   The file containing the bvectors of the source DWI. Maps to a command-line argument: `-bvec %s` (position: 3).

> source_filea pathlike object or string representing an existing file

>   The source image containing the dwi data. Maps to a command-line argument: `-source %s` (position: 1).

> acceptancea float

>   Fraction of iterations to accept [0.23]. Maps to a command-line argument: `-accpetance %f`.

> argsa unicode string

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

> ball_flaga boolean

>   Fit the ball and stick model. Maps to a command-line argument: `-ball` (position: 4). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> ballv_flaga boolean

>   Fit the ball and stick model with optimised PDD. Maps to a command-line argument: `-ballv` (position: 4). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `ball_flag`, `nod_flag`, `nodv_flag`.

> cov_filea pathlike object or string representing an existing file

>   Filename of ithe nc*nc covariance matrix [I]. Maps to a command-line argument: `-cov %s`.

> csf_t2_vala float

>   CSF T2 value [400ms]. Maps to a command-line argument: `-csfT2 %f`.

> diso_vala float

>   Isotropic diffusivity for -nod [3e-3]. Maps to a command-line argument: `-diso %f`.

> dpr_vala float

>   Parallel diffusivity for -nod [1.7e-3]. Maps to a command-line argument: `-dpr %f`.

> dti_flaga boolean

>   Fit the tensor model [default with b-vectors]. Maps to a command-line argument: `-dti` (position: 4). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `ball_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> 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: `{}`)

> error_filea pathlike object or string representing a file

>   Filename of parameter error maps. Maps to a command-line argument: `-error %s`.

> famap_filea pathlike object or string representing a file

>   Filename of FA map. Maps to a command-line argument: `-famap %s`.

> gn_flaga boolean

>   Use Gauss-Newton algorithm [Levenberg-Marquardt]. Maps to a command-line argument: `-gn`. Mutually exclusive with inputs: `wls_flag`.

> ivim_flaga boolean

>   Fit IVIM model to non-directional data. Maps to a command-line argument: `-ivim` (position: 4). Mutually exclusive with inputs: `mono_flag`, `dti_flag`, `ball_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

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

>   LM parameters (initial value, decrease rate) [100,1.2]. Maps to a command-line argument: `-lm %f %f`. Requires inputs: `gn_flag`.

> mask_filea pathlike object or string representing an existing file

>   The image mask. Maps to a command-line argument: `-mask %s`.

> maxit_valan integer (int or long)

>   Maximum number of non-linear LSQR iterations [100x2 passes]). Maps to a command-line argument: `-maxit %d`. Requires inputs: `gn_flag`.

> mcmap_filea pathlike object or string representing a file

>   Filename of multi-compartment model parameter map (-ivim,-ball,-nod). Maps to a command-line argument: `-mcmap %s`. Requires inputs: `nodv_flag`.

> mcmaxitan integer (int or long)

>   Number of iterations to run [10,000]. Maps to a command-line argument: `-mcmaxit %d`.

> mcouta pathlike object or string representing a file

>   Filename of mc samples (ascii text file). Maps to a command-line argument: `-mcout %s`.

> mcsamplesan integer (int or long)

>   Number of samples to keep [100]. Maps to a command-line argument: `-mcsamples %d`.

> mdmap_filea pathlike object or string representing a file

>   Filename of MD map/ADC. Maps to a command-line argument: `-mdmap %s`.

> mono_flaga boolean

>   Fit single exponential to non-directional data [default with no b-vectors]. Maps to a command-line argument: `-mono` (position: 4). Mutually exclusive with inputs: `ivim_flag`, `dti_flag`, `ball_flag`, `ballv_flag`, `nod_flag`, `nodv_flag`.

> nod_flaga boolean

>   Fit the NODDI model. Maps to a command-line argument: `-nod` (position: 4). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `ball_flag`, `ballv_flag`, `nodv_flag`.

> nodiff_filea pathlike object or string representing a file

>   Filename of average no diffusion image. Maps to a command-line argument: `-nodiff %s`.

> nodv_flaga boolean

>   Fit the NODDI model with optimised PDD. Maps to a command-line argument: `-nodv` (position: 4). Mutually exclusive with inputs: `mono_flag`, `ivim_flag`, `dti_flag`, `ball_flag`, `ballv_flag`, `nod_flag`.

> perf_thra float

>   Threshold for perfusion/diffsuion effects [100]. Maps to a command-line argument: `-perfthreshold %f`.

> prior_filea pathlike object or string representing an existing file

>   Filename of parameter priors for -ball and -nod. Maps to a command-line argument: `-prior %s`.

> res_filea pathlike object or string representing a file

>   Filename of model residual map. Maps to a command-line argument: `-res %s`.

> rgbmap_filea pathlike object or string representing a file

>   Filename of colour-coded FA map. Maps to a command-line argument: `-rgbmap %s`. Requires inputs: `dti_flag`.

> rot_sform_flagan integer (int or long)

>   Rotate the output tensors according to the q/s form of the image (resulting tensors will be in mm coordinates, default: 0). Maps to a command-line argument: `-rotsform %d`.

> slice_noan integer (int or long)

>   Fit to single slice number. Maps to a command-line argument: `-slice %d`.

> swls_vala float

>   Use location-weighted least squares for DTI fitting [3x3 Gaussian]. Maps to a command-line argument: `-swls %f`.

> syn_filea pathlike object or string representing a file

>   Filename of synthetic image. Maps to a command-line argument: `-syn %s`.

> te_filea pathlike object or string representing an existing file

>   Filename of TEs (ms). Maps to a command-line argument: `-TE %s`. Mutually exclusive with inputs: `te_file`.

> te_valuea pathlike object or string representing an existing file

>   Value of TEs (ms). Maps to a command-line argument: `-TE %s`. Mutually exclusive with inputs: `te_file`.

> ten_type‘lower-tri’ or ‘diag-off-diag’

>   Use lower triangular (tenmap2) or diagonal, off-diagonal tensor format. (Nipype default value: `lower-tri`)

> tenmap2_filea pathlike object or string representing a file

>   Filename of tensor map [lower tri]. Maps to a command-line argument: `-tenmap2 %s`. Requires inputs: `dti_flag`.

> tenmap_filea pathlike object or string representing a file

>   Filename of tensor map [diag,offdiag]. Maps to a command-line argument: `-tenmap %s`. Requires inputs: `dti_flag`.

> v1map_filea pathlike object or string representing a file

>   Filename of PDD map [x,y,z]. Maps to a command-line argument: `-v1map %s`.

> vb_flaga boolean

>   Use Variational Bayes fitting with known prior (currently identity covariance…). Maps to a command-line argument: `-vb`.

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

>   Fit to single voxel only. Maps to a command-line argument: `-voxel %d %d %d`.

> wls_flaga boolean

>   Use Variational Bayes fitting with known prior (currently identity covariance…). Maps to a command-line argument: `-wls`. Mutually exclusive with inputs: `gn_flag`.

> wm_t2_vala float

>   White matter T2 value [80ms]. Maps to a command-line argument: `-wmT2 %f`.

> error_filea pathlike object or string representing a file

>   Filename of parameter error maps.

> famap_filea pathlike object or string representing a file

>   Filename of FA map.

> mcmap_filea pathlike object or string representing a file

>   Filename of multi-compartment model parameter map (-ivim,-ball,-nod).

> mcouta pathlike object or string representing a file

>   Filename of mc samples (ascii text file).

> mdmap_filea pathlike object or string representing a file

>   Filename of MD map/ADC.

> nodiff_filea pathlike object or string representing a file

>   Filename of average no diffusion image.

> res_filea pathlike object or string representing a file

>   Filename of model residual map.

> rgbmap_filea pathlike object or string representing a file

>   Filename of colour FA map.

> syn_filea pathlike object or string representing a file

>   Filename of synthetic image.

> tenmap2_filea pathlike object or string representing a file

>   Filename of tensor map [lower tri].

> tenmap_filea pathlike object or string representing a file

>   Filename of tensor map.

> v1map_filea pathlike object or string representing a file

>   Filename of PDD map [x,y,z].