priority_flow.get_border
========================

.. py:module:: priority_flow.get_border

.. autoapi-nested-parse::

   Get Border functions for PriorityFlow.

   This module provides functions to identify border cells by reading in a mask
   and returning a mask of the border cells for irregular boundaries.



Functions
---------

.. autoapisummary::

   priority_flow.get_border.get_border


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

.. py:function:: get_border(mask_mat: numpy.ndarray) -> numpy.ndarray

   Identify border cells.

   Function that reads in a mask and returns a mask of the border cells for the
   irregular boundary. Border cells are identified as cells that have fewer than
   4 valid neighbors within the domain.

   :param mask_mat: Matrix mask with values of 0 for cells outside the domain and 1 for cells inside the domain
   :type mask_mat: np.ndarray

   :returns: Matrix mask where 1 indicates border cells and 0 indicates non-border cells
   :rtype: np.ndarray

   .. rubric:: Notes

   This function implements a border detection algorithm that:
   1. Identifies cells at the domain boundary
   2. Counts valid neighbors for each cell
   3. Classifies cells with fewer than 4 neighbors as border cells
   4. Handles irregular domain boundaries

   The algorithm uses D4 connectivity (4-directional) to identify border cells:
   - Cells with 4 valid neighbors are interior cells (not borders)
   - Cells with fewer than 4 valid neighbors are border cells
   - Only cells within the domain mask are considered

   Border cells are typically:
   - Domain edge cells
   - Cells adjacent to masked areas
   - Cells in irregular boundary regions
   - Cells with incomplete neighbor connectivity