pandora.cpp.interval_tools_cpp
==============================

.. py:module:: pandora.cpp.interval_tools_cpp


Functions
---------

.. autoapisummary::

   pandora.cpp.interval_tools_cpp.create_connected_graph
   pandora.cpp.interval_tools_cpp.graph_regularization


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

.. py:function:: create_connected_graph(border_left: numpy.ndarray, border_right: numpy.ndarray, depth: int) -> numpy.ndarray

   Create a boolean connection matrix from segment coordinates

   :param border_left: array containing the coordinates of segments left border
   :type border_left: (n, 2) np.ndarray where n is the number of segments
   :param border_right: array containing the coordinates of segments right border
   :type border_right: (n, 2) np.ndarray where n is the number of segments
   :param depth: the depth for regularization. It corresponds to the number of rows
       to explore below and above.
   :return: A symmetric boolean matrix of shape (n, n). 1 indicating that the segment are connected
   :rtype: np.ndarray of shape (n, n)


.. py:function:: graph_regularization(interval_inf: numpy.ndarray, interval_sup: numpy.ndarray, border_left: numpy.ndarray, border_right: numpy.ndarray, connection_graph: numpy.ndarray, quantile: float) -> Tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]

   Regularize the intervals based on quantiles and a given connection graph.

   :param interval_inf: The lower estimation of the disparity to regularize
   :type interval_inf: (row, col) np.ndarray
   :param interval_sup: The upper estimation of the disparity to regularize
   :type interval_sup: (row, col) np.ndarray
   :param border_left: array containing the coordinates of segments left border
   :type border_left: (n, 2) np.ndarray where n is the number of segments
   :param border_right: array containing the coordinates of segments right border
   :type border_right: (n, 2) np.ndarray where n is the number of segments
   :param connection graph: A matrix indicating if the segments (n in total) are connected
   :type connection graph: (n, n) boolean symmetric np.ndarray
   :param quantile: Which quantile to select for the regularized value
   :type quantile: float. 0 <= quantile <= 1
   :return: The regularized inf and sup of the disparity, and a boolean mask indicating regularization
   :rtype: Tuple[np.ndarray, np.ndarray, np.ndarray]