.. AUTO-GENERATED FILE -- DO NOT EDIT!

interfaces.mrtrix3.reconst
==========================


.. _nipype.interfaces.mrtrix3.reconst.EstimateFOD:


.. index:: EstimateFOD

EstimateFOD
-----------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/mrtrix3/reconst.py#L137>`__

Wraps the executable command ``dwi2fod``.

Estimate fibre orientation distributions from diffusion data using spherical deconvolution

Example
~~~~~~~

>>> import nipype.interfaces.mrtrix3 as mrt
>>> fod = mrt.EstimateFOD()
>>> fod.inputs.algorithm = 'csd'
>>> fod.inputs.in_file = 'dwi.mif'
>>> fod.inputs.wm_txt = 'wm.txt'
>>> fod.inputs.grad_fsl = ('bvecs', 'bvals')
>>> fod.cmdline                               # doctest: +ELLIPSIS
'dwi2fod -fslgrad bvecs bvals -lmax 8 csd dwi.mif wm.txt wm.mif gm.mif csf.mif'
>>> fod.run()                                 # doctest: +SKIP

Inputs::

        [Mandatory]
        wm_txt: (a file name)
                WM response text file
                argument: ``%s``, position: -6
        in_file: (an existing file name)
                input DWI image
                argument: ``%s``, position: -7
        algorithm: (u'csd' or u'msmt_csd')
                FOD algorithm
                argument: ``%s``, position: -8
        wm_odf: (a file name, nipype default value: wm.mif)
                output WM ODF
                argument: ``%s``, position: -5

        [Optional]
        csf_txt: (a file name)
                CSF response text file
                argument: ``%s``, position: -2
        shell: (a list of items which are a float)
                specify one or more dw gradient shells
                argument: ``-shell %s``
        nthreads: (an integer (int or long))
                number of threads. if zero, the number of available cpus will be
                used
                argument: ``-nthreads %d``
        grad_file: (an existing file name)
                dw gradient scheme (MRTrix format
                argument: ``-grad %s``
        grad_fsl: (a tuple of the form: (an existing file name, an existing
                  file name))
                (bvecs, bvals) dw gradient scheme (FSL format
                argument: ``-fslgrad %s %s``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        gm_odf: (a file name, nipype default value: gm.mif)
                output GM ODF
                argument: ``%s``, position: -3
        in_bval: (an existing file name)
                bvals file in FSL format
        in_dirs: (an existing file name)
                specify the directions over which to apply the non-negativity
                constraint (by default, the built-in 300 direction set is used).
                These should be supplied as a text file containing the [ az el ]
                pairs for the directions.
                argument: ``-directions %s``
        bval_scale: (u'yes' or u'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).
                argument: ``-bvalue_scaling %s``
        gm_txt: (a file name)
                GM response text file
                argument: ``%s``, position: -4
        mask_file: (an existing file name)
                mask image
                argument: ``-mask %s``
        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
        in_bvec: (an existing file name)
                bvecs file in FSL format
                argument: ``-fslgrad %s %s``
        max_sh: (an integer (int or long), nipype default value: 8)
                maximum harmonic degree of response function
                argument: ``-lmax %d``
        csf_odf: (a file name, nipype default value: csf.mif)
                output CSF ODF
                argument: ``%s``, position: -1

Outputs::

        wm_odf: (a file name)
                output WM ODF
                argument: ``%s``
        gm_odf: (a file name)
                output GM ODF
                argument: ``%s``
        csf_odf: (a file name)
                output CSF ODF
                argument: ``%s``

.. _nipype.interfaces.mrtrix3.reconst.FitTensor:


.. index:: FitTensor

FitTensor
---------

`Link to code <file:///build/nipype-1.1.8/nipype/interfaces/mrtrix3/reconst.py#L53>`__

Wraps the executable command ``dwi2tensor``.

Convert diffusion-weighted images to tensor images


Example
~~~~~~~

>>> import nipype.interfaces.mrtrix3 as mrt
>>> tsr = mrt.FitTensor()
>>> tsr.inputs.in_file = 'dwi.mif'
>>> tsr.inputs.in_mask = 'mask.nii.gz'
>>> tsr.inputs.grad_fsl = ('bvecs', 'bvals')
>>> tsr.cmdline                               # doctest: +ELLIPSIS
'dwi2tensor -fslgrad bvecs bvals -mask mask.nii.gz dwi.mif dti.mif'
>>> tsr.run()                                 # doctest: +SKIP

Inputs::

        [Mandatory]
        out_file: (a file name, nipype default value: dti.mif)
                the output diffusion tensor image
                argument: ``%s``, position: -1
        in_file: (an existing file name)
                input diffusion weighted images
                argument: ``%s``, position: -2

        [Optional]
        nthreads: (an integer (int or long))
                number of threads. if zero, the number of available cpus will be
                used
                argument: ``-nthreads %d``
        grad_file: (an existing file name)
                dw gradient scheme (MRTrix format
                argument: ``-grad %s``
        grad_fsl: (a tuple of the form: (an existing file name, an existing
                  file name))
                (bvecs, bvals) dw gradient scheme (FSL format
                argument: ``-fslgrad %s %s``
        args: (a unicode string)
                Additional parameters to the command
                argument: ``%s``
        in_mask: (an existing file name)
                only perform computation within the specified binary brain mask
                image
                argument: ``-mask %s``
        reg_term: (a float)
                specify the strength of the regularisation term on the magnitude of
                the tensor elements (default = 5000). This only applies to the non-
                linear methods
                argument: ``-regularisation %f``
        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
        bval_scale: (u'yes' or u'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).
                argument: ``-bvalue_scaling %s``
        in_bval: (an existing file name)
                bvals file in FSL format
        in_bvec: (an existing file name)
                bvecs file in FSL format
                argument: ``-fslgrad %s %s``
        method: (u'nonlinear' or u'loglinear' or u'sech' or u'rician')
                select method used to perform the fitting
                argument: ``-method %s``

Outputs::

        out_file: (an existing file name)
                the output DTI file
