:py:mod:`AFQ.tractography.tractography`
=======================================

.. py:module:: AFQ.tractography.tractography


Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   AFQ.tractography.tractography.track
   AFQ.tractography.tractography._tracking



.. py:function:: track(params_file, directions='prob', max_angle=30.0, sphere=None, seed_mask=None, seed_threshold=0, thresholds_as_percentages=False, n_seeds=1, random_seeds=False, rng_seed=None, stop_mask=None, stop_threshold=0, step_size=0.5, minlen=50, maxlen=250, odf_model='CSD', tracker='local', trx=False)

   
   Tractography


   :Parameters:

       **params_file** : str, nibabel img.
           Full path to a nifti file containing CSD spherical harmonic
           coefficients, or nibabel img with model params.

       **directions** : str
           How tracking directions are determined.
           One of: {"det" | "prob"}
           Default: "prob"

       **max_angle** : float, optional.
           The maximum turning angle in each step. Default: 30

       **sphere** : Sphere object, optional.
           The discretization of direction getting. default:
           dipy.data.default_sphere.

       **seed_mask** : array, optional.
           Float or binary mask describing the ROI within which we seed for
           tracking.
           Default to the entire volume (all ones).

       **seed_threshold** : float, optional.
           A value of the seed_mask above which tracking is seeded.
           Default to 0.

       **n_seeds** : int or 2D array, optional.
           The seeding density: if this is an int, it is is how many seeds in each
           voxel on each dimension (for example, 2 => [2, 2, 2]). If this is a 2D
           array, these are the coordinates of the seeds. Unless random_seeds is
           set to True, in which case this is the total number of random seeds
           to generate within the mask. Default: 1

       **random_seeds** : bool
           Whether to generate a total of n_seeds random seeds in the mask.
           Default: False.

       **rng_seed** : int
           random seed used to generate random seeds if random_seeds is
           set to True. Default: None

       **stop_mask** : array or str, optional.
           If array: A float or binary mask that determines a stopping criterion
           (e.g. FA).
           If tuple: it contains a sequence that is interpreted as:
           (pve_wm, pve_gm, pve_csf), each item of which is either a string
           (full path) or a nibabel img to be used in particle filtering
           tractography.
           A tuple is required if tracker is set to "pft".
           Defaults to no stopping (all ones).

       **stop_threshold** : float or tuple, optional.
           If float, this a value of the stop_mask below which tracking is
           terminated (and stop_mask has to be an array).
           If str, "CMC" for Continuous Map Criterion [R2bb8bf7259c4-Girard2014]_.
                   "ACT" for Anatomically-constrained tractography [Smith2012]_.
           A string is required if the tracker is set to "pft".
           Defaults to 0 (this means that if no stop_mask is passed,
           we will stop only at the edge of the image).

       **thresholds_as_percentages** : bool, optional
           Interpret seed_threshold and stop_threshold as percentages of the
           total non-nan voxels in the seed and stop mask to include
           (between 0 and 100), instead of as a threshold on the
           values themselves.
           Default: False

       **step_size** : float, optional.
           The size of a step (in mm) of tractography. Default: 0.5

       **minlen: int, optional**
           The miminal length (mm) in a streamline. Default: 20

       **maxlen: int, optional**
           The miminal length (mm) in a streamline. Default: 250

       **odf_model** : str, optional
           One of {"DTI", "CSD", "DKI"}. Defaults to use "DTI"

       **tracker** : str, optional
           Which strategy to use in tracking. This can be the standard local
           tracking ("local") or Particle Filtering Tracking ([R2bb8bf7259c4-Girard2014]_).
           One of {"local", "pft"}. Default: "local"

       **trx** : bool, optional
           Whether to return the streamlines compatible with input to TRX file
           (i.e., as a LazyTractogram class instance).
           Default: False

   :Returns:

       list of streamlines ()
           ..









   .. rubric:: References

   .. [R2bb8bf7259c4-Girard2014] Girard, G., Whittingstall, K., Deriche, R., &
       Descoteaux, M. Towards quantitative connectivity analysis: reducing
       tractography biases. NeuroImage, 98, 266-278, 2014.

   .. only:: latex

      [R2bb8bf7259c4-Girard2014]_




   ..
       !! processed by numpydoc !!

.. py:function:: _tracking(tracker, seeds, dg, stopping_criterion, params_img, step_size=0.5, minlen=40, maxlen=200, random_seed=None, trx=False)

   
   Helper function
















   ..
       !! processed by numpydoc !!