trx.streamlines_ops
===================

.. py:module:: trx.streamlines_ops


Attributes
----------

.. autoapisummary::

   trx.streamlines_ops.MIN_NB_POINTS
   trx.streamlines_ops.KEY_INDEX


Functions
---------

.. autoapisummary::

   trx.streamlines_ops.intersection
   trx.streamlines_ops.difference
   trx.streamlines_ops.union
   trx.streamlines_ops.get_streamline_key
   trx.streamlines_ops.hash_streamlines
   trx.streamlines_ops.perform_streamlines_operation


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

.. py:data:: MIN_NB_POINTS
   :value: 5


.. py:data:: KEY_INDEX

.. py:function:: intersection(left, right)

   
   Intersection of two streamlines dict (see hash_streamlines)
















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.. py:function:: difference(left, right)

   
   Difference of two streamlines dict (see hash_streamlines)
















   ..
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.. py:function:: union(left, right)

   
   Union of two streamlines dict (see hash_streamlines)
















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.. py:function:: get_streamline_key(streamline, precision=None)

   
   Produces a key using a hash from a streamline using a few points only and
   the desired precision


   :Parameters:

       **streamlines: ndarray**
           A single streamline (N,3)

       **precision: int, optional**
           The number of decimals to keep when hashing the points of the
           streamlines. Allows a soft comparison of streamlines. If None, no
           rounding is performed.

   :Returns:

       Value of the hash of the first/last MIN_NB_POINTS points of the streamline.
           ..













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       !! processed by numpydoc !!

.. py:function:: hash_streamlines(streamlines, start_index=0, precision=None)

   
   Produces a dict from streamlines

   Produces a dict from streamlines by using the points as keys and the
   indices of the streamlines as values.

   :Parameters:

       **streamlines: list of ndarray**
           The list of streamlines used to produce the dict.

       **start_index: int, optional**
           The index of the first streamline. 0 by default.

       **precision: int, optional**
           The number of decimals to keep when hashing the points of the
           streamlines. Allows a soft comparison of streamlines. If None, no
           rounding is performed.

   :Returns:

       A dict where the keys are streamline points and the values are indices
           ..

       starting at start_index.
           ..













   ..
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.. py:function:: perform_streamlines_operation(operation, streamlines, precision=0)

   
   Peforms an operation on a list of list of streamlines

   Given a list of list of streamlines, this function applies the operation
   to the first two lists of streamlines. The result in then used recursively
   with the third, fourth, etc. lists of streamlines.

   A valid operation is any function that takes two streamlines dict as input
   and produces a new streamlines dict (see hash_streamlines). Union,
   difference, and intersection are valid examples of operations.

   :Parameters:

       **operation: callable**
           A callable that takes two streamlines dicts as inputs and preduces a
           new streamline dict.

       **streamlines: list of list of streamlines**
           The streamlines used in the operation.

       **precision: int, optional**
           The number of decimals to keep when hashing the points of the
           streamlines. Allows a soft comparison of streamlines. If None, no
           rounding is performed.

   :Returns:

       streamlines: list of `nib.streamline.ArraySequence`
           The streamlines obtained after performing the operation on all the
           input streamlines.

       indices: np.ndarray
           The indices of the streamlines that are used in the output.













   ..
       !! processed by numpydoc !!