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# interfaces.niftyfit.dwi

## DwiTool

Link to code

Wraps command 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'

Inputs:

    [Mandatory]
    bval_file: (a file name)
            The file containing the bvalues of the source DWI.
            flag: -bval %s, position: 2
    source_file: (a file name)
            The source image containing the fitted model.
            flag: -source %s, position: 1

    [Optional]
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    b0_file: (a file name)
            The B0 image corresponding to the source DWI
            flag: -b0 %s, position: 4
    ball_flag: (a boolean)
            Input is a ball and stick model.
            flag: -ball, position: 6
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, dti_flag2,
             ballv_flag, nod_flag, nodv_flag
    ballv_flag: (a boolean)
            Input is a ball and stick model with optimised PDD.
            flag: -ballv, position: 6
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, dti_flag2,
             ball_flag, nod_flag, nodv_flag
    bvec_file: (a file name)
            The file containing the bvectors of the source DWI.
            flag: -bvec %s, position: 3
    diso_val: (a float)
            Isotropic diffusivity for -nod [3e-3]
            flag: -diso %f
    dpr_val: (a float)
            Parallel diffusivity for -nod [1.7e-3].
            flag: -dpr %f
    dti_flag: (a boolean)
            Input is a tensor model diag/off-diag.
            flag: -dti, position: 6
            mutually_exclusive: mono_flag, ivim_flag, dti_flag2, ball_flag,
             ballv_flag, nod_flag, nodv_flag
    dti_flag2: (a boolean)
            Input is a tensor model lower triangular
            flag: -dti2, position: 6
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, ball_flag,
             ballv_flag, nod_flag, nodv_flag
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    famap_file: (a file name)
            Filename of FA map
            flag: -famap %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
    ivim_flag: (a boolean)
            Inputs is an IVIM model to non-directional data.
            flag: -ivim, position: 6
            mutually_exclusive: mono_flag, dti_flag, dti_flag2, ball_flag,
             ballv_flag, nod_flag, nodv_flag
    logdti_file: (a file name)
            Filename of output logdti map.
            flag: -logdti2 %s
    mask_file: (a file name)
            The image mask
            flag: -mask %s, position: 5
    mcmap_file: (a file name)
            Filename of multi-compartment model parameter map (-ivim,-ball,-nod)
            flag: -mcmap %s
    mdmap_file: (a file name)
            Filename of MD map/ADC
            flag: -mdmap %s
    mono_flag: (a boolean)
            Input is a single exponential to non-directional data [default with
            no b-vectors]
            flag: -mono, position: 6
            mutually_exclusive: ivim_flag, dti_flag, dti_flag2, ball_flag,
             ballv_flag, nod_flag, nodv_flag
    nod_flag: (a boolean)
            Input is a NODDI model
            flag: -nod, position: 6
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, dti_flag2,
             ball_flag, ballv_flag, nodv_flag
    nodv_flag: (a boolean)
            Input is a NODDI model with optimised PDD
            flag: -nodv, position: 6
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, dti_flag2,
             ball_flag, ballv_flag, nod_flag
    rgbmap_file: (a file name)
            Filename of colour FA map.
            flag: -rgbmap %s
    syn_file: (a file name)
            Filename of synthetic image. Requires: bvec_file/b0_file.
            flag: -syn %s
            requires: bvec_file, b0_file
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'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
    v1map_file: (a file name)
            Filename of PDD map [x,y,z]
            flag: -v1map %s

Outputs:

    famap_file: (a file name)
            Filename of FA map
    logdti_file: (a file name)
            Filename of output logdti map
    mcmap_file: (a file name)
            Filename of multi-compartment model parameter map (-ivim,-ball,-nod)
    mdmap_file: (a file name)
            Filename of MD map/ADC
    rgbmap_file: (a file name)
            Filename of colour FA map
    syn_file: (a file name)
            Filename of synthetic image
    v1map_file: (a file name)
            Filename of PDD map [x,y,z]

## FitDwi

Link to code

Wraps command 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 -mcmap dwi_mcmap.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'

Inputs:

    [Mandatory]
    bval_file: (a file name)
            The file containing the bvalues of the source DWI.
            flag: -bval %s, position: 2
    bvec_file: (a file name)
            The file containing the bvectors of the source DWI.
            flag: -bvec %s, position: 3
    source_file: (a file name)
            The source image containing the dwi data.
            flag: -source %s, position: 1

    [Optional]
    acceptance: (a float)
            Fraction of iterations to accept [0.23].
            flag: -accpetance %f
    args: (a unicode string)
            Additional parameters to the command
            flag: %s
    ball_flag: (a boolean)
            Fit the ball and stick model.
            flag: -ball, position: 4
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, ballv_flag,
             nod_flag, nodv_flag
    ballv_flag: (a boolean)
            Fit the ball and stick model with optimised PDD.
            flag: -ballv, position: 4
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, ball_flag,
             nod_flag, nodv_flag
    cov_file: (a file name)
            Filename of ithe nc*nc covariance matrix [I]
            flag: -cov %s
    csf_t2_val: (a float)
            CSF T2 value [400ms].
            flag: -csfT2 %f
    diso_val: (a float)
            Isotropic diffusivity for -nod [3e-3]
            flag: -diso %f
    dpr_val: (a float)
            Parallel diffusivity for -nod [1.7e-3].
            flag: -dpr %f
    dti_flag: (a boolean)
            Fit the tensor model [default with b-vectors].
            flag: -dti, position: 4
            mutually_exclusive: mono_flag, ivim_flag, ball_flag, ballv_flag,
             nod_flag, nodv_flag
    environ: (a dictionary with keys which are a newbytes or None or a
             newstr or None and with values which are a newbytes or None or a
             newstr or None, nipype default value: {})
            Environment variables
    error_file: (a file name)
            Filename of parameter error maps.
            flag: -error %s
    famap_file: (a file name)
            Filename of FA map
            flag: -famap %s
    gn_flag: (a boolean)
            Use Gauss-Newton algorithm [Levenberg-Marquardt].
            flag: -gn
            mutually_exclusive: wls_flag
    ignore_exception: (a boolean, nipype default value: False)
            Print an error message instead of throwing an exception in case the
            interface fails to run
    ivim_flag: (a boolean)
            Fit IVIM model to non-directional data.
            flag: -ivim, position: 4
            mutually_exclusive: mono_flag, dti_flag, ball_flag, ballv_flag,
             nod_flag, nodv_flag
    lm_vals: (a tuple of the form: (a float, a float))
            LM parameters (initial value, decrease rate) [100,1.2].
            flag: -lm %f %f
            requires: gn_flag
    mask_file: (a file name)
            The image mask
            flag: -mask %s
    maxit_val: (an integer (int or long))
            Maximum number of non-linear LSQR iterations [100x2 passes])
            flag: -maxit %d
            requires: gn_flag
    mcmap_file: (a file name)
            Filename of multi-compartment model parameter map (-ivim,-ball,-nod)
            flag: -mcmap %s
            requires: nodv_flag
    mcmaxit: (an integer (int or long))
            Number of iterations to run [10,000].
            flag: -mcmaxit %d
    mcout: (a file name)
            Filename of mc samples (ascii text file)
            flag: -mcout %s
    mcsamples: (an integer (int or long))
            Number of samples to keep [100].
            flag: -mcsamples %d
    mdmap_file: (a file name)
            Filename of MD map/ADC
            flag: -mdmap %s
    mono_flag: (a boolean)
            Fit single exponential to non-directional data [default with no
            b-vectors]
            flag: -mono, position: 4
            mutually_exclusive: ivim_flag, dti_flag, ball_flag, ballv_flag,
             nod_flag, nodv_flag
    nod_flag: (a boolean)
            Fit the NODDI model
            flag: -nod, position: 4
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, ball_flag,
             ballv_flag, nodv_flag
    nodiff_file: (a file name)
            Filename of average no diffusion image.
            flag: -nodiff %s
    nodv_flag: (a boolean)
            Fit the NODDI model with optimised PDD
            flag: -nodv, position: 4
            mutually_exclusive: mono_flag, ivim_flag, dti_flag, ball_flag,
             ballv_flag, nod_flag
    perf_thr: (a float)
            Threshold for perfusion/diffsuion effects [100].
            flag: -perfthreshold %f
    prior_file: (a file name)
            Filename of parameter priors for -ball and -nod.
            flag: -prior %s
    res_file: (a file name)
            Filename of model residual map.
            flag: -res %s
    rgbmap_file: (a file name)
            Filename of colour-coded FA map
            flag: -rgbmap %s
            requires: dti_flag
    rot_sform_flag: (an 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).
            flag: -rotsform %d
    slice_no: (an integer (int or long))
            Fit to single slice number.
            flag: -slice %d
    swls_val: (a float)
            Use location-weighted least squares for DTI fitting [3x3 Gaussian]
            flag: -swls %f
    syn_file: (a file name)
            Filename of synthetic image.
            flag: -syn %s
    te_file: (a file name)
            Filename of TEs (ms).
            flag: -TE %s
            mutually_exclusive: te_file
    te_value: (a file name)
            Value of TEs (ms).
            flag: -TE %s
            mutually_exclusive: te_file
    ten_type: ('lower-tri' or 'diag-off-diag', nipype default value:
             lower-tri)
            Use lower triangular (tenmap2) or diagonal, off-diagonal tensor
            format
    tenmap2_file: (a file name)
            Filename of tensor map [lower tri]
            flag: -tenmap2 %s
            requires: dti_flag
    tenmap_file: (a file name)
            Filename of tensor map [diag,offdiag].
            flag: -tenmap %s
            requires: dti_flag
    terminal_output: (u'stream' or u'allatonce' or u'file' or u'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
    v1map_file: (a file name)
            Filename of PDD map [x,y,z]
            flag: -v1map %s
    vb_flag: (a boolean)
            Use Variational Bayes fitting with known prior (currently identity
            covariance...).
            flag: -vb
    voxel: (a tuple of the form: (an integer (int or long), an integer
             (int or long), an integer (int or long)))
            Fit to single voxel only.
            flag: -voxel %d %d %d
    wls_flag: (a boolean)
            Use Variational Bayes fitting with known prior (currently identity
            covariance...).
            flag: -wls
            mutually_exclusive: gn_flag
    wm_t2_val: (a float)
            White matter T2 value [80ms].
            flag: -wmT2 %f

Outputs:

    error_file: (a file name)
            Filename of parameter error maps
    famap_file: (a file name)
            Filename of FA map
    mcmap_file: (a file name)
            Filename of multi-compartment model parameter map
            (-ivim,-ball,-nod).
    mcout: (a file name)
            Filename of mc samples (ascii text file)
    mdmap_file: (a file name)
            Filename of MD map/ADC
    nodiff_file: (a file name)
            Filename of average no diffusion image.
    res_file: (a file name)
            Filename of model residual map
    rgbmap_file: (a file name)
            Filename of colour FA map
    syn_file: (a file name)
            Filename of synthetic image
    tenmap2_file: (a file name)
            Filename of tensor map [lower tri]
    tenmap_file: (a file name)
            Filename of tensor map
    v1map_file: (a file name)
            Filename of PDD map [x,y,z]