topostats.tracing.skeletonize
=============================

.. py:module:: topostats.tracing.skeletonize

.. autoapi-nested-parse::

   Skeletonize molecules.

   ..
       !! processed by numpydoc !!


Attributes
----------

.. autoapisummary::

   topostats.tracing.skeletonize.LOGGER


Functions
---------

.. autoapisummary::

   topostats.tracing.skeletonize.get_skeleton
   topostats.tracing.skeletonize._get_skeletonize
   topostats.tracing.skeletonize._skeletonize_zhang
   topostats.tracing.skeletonize._skeletonize_lee
   topostats.tracing.skeletonize._skeletonize_thin


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

.. py:data:: LOGGER

.. py:function:: get_skeleton(image: numpy.ndarray, method: str) -> numpy.ndarray

   
   Skeletonizing masked molecules.

   :param image: Image of molecule to be skeletonized.
   :type image: np.ndarray
   :param method: Method to use, default is 'zhang' other options are 'lee', and 'thin'.
   :type method: str

   :returns: Skeletonised version of the image.all($0)
   :rtype: np.ndarray

   .. rubric:: Notes

   This is a thin wrapper to the methods provided
   by the `skimage.morphology
   <https://scikit-image.org/docs/stable/api/skimage.morphology.html?highlight=skeletonize>`_
   module. See also the `examples
   <https://scikit-image.org/docs/stable/auto_examples/edges/plot_skeleton.html>_















   ..
       !! processed by numpydoc !!

.. py:function:: _get_skeletonize(method: str = 'zhang') -> collections.abc.Callable

   
   Creator component which determines which skeletonize method to use.

   :param method: Method to use for skeletonizing, methods are 'zhang' (default), 'lee', and 'thin'.
   :type method: str

   :returns: Returns the function appropriate for the required skeletonizing method.
   :rtype: Callable















   ..
       !! processed by numpydoc !!

.. py:function:: _skeletonize_zhang(image: numpy.ndarray) -> numpy.ndarray

.. py:function:: _skeletonize_lee(image: numpy.ndarray) -> numpy.ndarray

.. py:function:: _skeletonize_thin(image: numpy.ndarray) -> numpy.ndarray