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

interfaces.dipy.tensors
=======================


.. _nipype.interfaces.dipy.tensors.DTI:


.. index:: DTI

DTI
---

`Link to code <file:///build/nipype-4ReYCB/nipype-0.11.0/nipype/interfaces/dipy/tensors.py#L84>`__

Calculates the diffusion tensor model parameters

Example
~~~~~~~

>>> import nipype.interfaces.dipy as dipy
>>> dti = dipy.DTI()
>>> dti.inputs.in_file = 'diffusion.nii'
>>> dti.inputs.bvecs = 'bvecs'
>>> dti.inputs.bvals = 'bvals'
>>> dti.run()                                   # doctest: +SKIP

Inputs::

        [Mandatory]
        bvals: (an existing file name)
                The input b-value text file
        bvecs: (an existing file name)
                The input b-vector text file
        in_file: (an existing file name)
                The input 4D diffusion-weighted image file

        [Optional]
        mask_file: (an existing file name)
                An optional white matter mask
        out_filename: (a file name)
                The output filename for the DTI parameters image

Outputs::

        out_file: (an existing file name)

.. _nipype.interfaces.dipy.tensors.TensorMode:


.. index:: TensorMode

TensorMode
----------

`Link to code <file:///build/nipype-4ReYCB/nipype-0.11.0/nipype/interfaces/dipy/tensors.py#L146>`__

Creates a map of the mode of the diffusion tensors given a set of
diffusion-weighted images, as well as their associated b-values and
b-vectors. Fits the diffusion tensors and calculates tensor mode
with Dipy.

.. [1] Daniel B. Ennis and G. Kindlmann, "Orthogonal Tensor
    Invariants and the Analysis of Diffusion Tensor Magnetic Resonance
    Images", Magnetic Resonance in Medicine, vol. 55, no. 1, pp. 136-146,
    2006.

Example
~~~~~~~

>>> import nipype.interfaces.dipy as dipy
>>> mode = dipy.TensorMode()
>>> mode.inputs.in_file = 'diffusion.nii'
>>> mode.inputs.bvecs = 'bvecs'
>>> mode.inputs.bvals = 'bvals'
>>> mode.run()                                   # doctest: +SKIP

Inputs::

        [Mandatory]
        bvals: (an existing file name)
                The input b-value text file
        bvecs: (an existing file name)
                The input b-vector text file
        in_file: (an existing file name)
                The input 4D diffusion-weighted image file

        [Optional]
        mask_file: (an existing file name)
                An optional white matter mask
        out_filename: (a file name)
                The output filename for the Tensor mode image

Outputs::

        out_file: (an existing file name)

.. module:: nipype.interfaces.dipy.tensors


.. _nipype.interfaces.dipy.tensors.tensor_fitting:

:func:`tensor_fitting`
----------------------

`Link to code <file:///build/nipype-4ReYCB/nipype-0.11.0/nipype/interfaces/dipy/tensors.py#L32>`__



Use dipy to fit DTI

Parameters
~~~~~~~~~~
in_file : str
    Full path to a DWI data file.
bvals : str
    Full path to a file containing gradient magnitude information (b-values).
bvecs : str
    Full path to a file containing gradient direction information (b-vectors).
mask_file : str, optional
    Full path to a file containing a binary mask. Defaults to use the entire volume.

Returns
~~~~~~~
TensorFit object, affine

