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# workflows.dmri.fsl.dti

## `create_bedpostx_pipeline()`

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Creates a pipeline that does the same as bedpostx script from FSL - calculates diffusion model parameters (distributions not MLE) voxelwise for the whole volume (by splitting it slicewise).

### Example

    >>> nipype_bedpostx = create_bedpostx_pipeline("nipype_bedpostx")
    >>> nipype_bedpostx.inputs.inputnode.dwi = 'diffusion.nii'
    >>> nipype_bedpostx.inputs.inputnode.mask = 'mask.nii'
    >>> nipype_bedpostx.inputs.inputnode.bvecs = 'bvecs'
    >>> nipype_bedpostx.inputs.inputnode.bvals = 'bvals'
    >>> nipype_bedpostx.inputs.xfibres.n_fibres = 2
    >>> nipype_bedpostx.inputs.xfibres.fudge = 1
    >>> nipype_bedpostx.inputs.xfibres.burn_in = 1000
    >>> nipype_bedpostx.inputs.xfibres.n_jumps = 1250
    >>> nipype_bedpostx.inputs.xfibres.sample_every = 25
    >>> nipype_bedpostx.run()

Inputs:

    inputnode.dwi
    inputnode.mask

Outputs:

    outputnode.thsamples
    outputnode.phsamples
    outputnode.fsamples
    outputnode.mean_thsamples
    outputnode.mean_phsamples
    outputnode.mean_fsamples
    outputnode.dyads
    outputnode.dyads_dispersion

### Graph

## `transpose()`

Link to code