priority_flow.data_loader
=========================

.. py:module:: priority_flow.data_loader

.. autoapi-nested-parse::

   Data loading functions for PriorityFlow package.

   This module provides functions to load the test data files that were converted
   from the R package's TestDomain_Inputs directory.



Functions
---------

.. autoapisummary::

   priority_flow.data_loader.load_dem
   priority_flow.data_loader.load_watershed_mask
   priority_flow.data_loader.load_river_mask
   priority_flow.data_loader.load_all_test_data
   priority_flow.data_loader.get_data_info


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

.. py:function:: load_dem()

   Load the Digital Elevation Model (DEM) test data.

   This is a small elevation dataset (215km by 172km at 1km spatial resolution)
   converted from the R package's TestDomain_Inputs.

   :returns: A 2D array of elevation values with shape (215, 172) representing
             the domain dimensions (nrow=215, ncol=172).
   :rtype: numpy.ndarray

   .. rubric:: Examples

   >>> import priority_flow.data_loader as dl
   >>> dem = dl.load_dem()
   >>> print(f"DEM shape: {dem.shape}")
   >>> print(f"Elevation range: {dem.min():.2f} to {dem.max():.2f}")


.. py:function:: load_watershed_mask()

   Load the watershed mask test data.

   A mask showing the watershed drainage area for the test domain.

   :returns: A 2D array of 0's and 1's showing the watershed extent
             (1=inside the watershed, 0=outside the watershed) with shape (215, 172).
   :rtype: numpy.ndarray

   .. rubric:: Examples

   >>> import priority_flow.data_loader as dl
   >>> mask = dl.load_watershed_mask()
   >>> print(f"Watershed mask shape: {mask.shape}")
   >>> print(f"Watershed cells: {np.sum(mask)}")


.. py:function:: load_river_mask()

   Load the river mask test data.

   A mask showing an example river network for the test domain.

   :returns: A 2D array of 0's and 1's showing the location of river cells
             (1=river, 0=non-river) with shape (215, 172).
   :rtype: numpy.ndarray

   .. rubric:: Examples

   >>> import priority_flow.data_loader as dl
   >>> river_mask = dl.load_river_mask()
   >>> print(f"River mask shape: {river_mask.shape}")
   >>> print(f"River cells: {np.sum(river_mask)}")


.. py:function:: load_all_test_data()

   Load all test data files at once.

   :returns: A dictionary containing all test data arrays with keys:
             - 'dem': Digital Elevation Model
             - 'watershed_mask': Watershed drainage area mask
             - 'river_mask': River network mask
   :rtype: dict

   .. rubric:: Examples

   >>> import priority_flow.data_loader as dl
   >>> data = dl.load_all_test_data()
   >>> print(f"Available data: {list(data.keys())}")
   >>> print(f"DEM shape: {data['dem'].shape}")


.. py:function:: get_data_info()

   Get information about the available test data files.

   :returns: A dictionary containing metadata about each data file.
   :rtype: dict