priority_flow.data_loader

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

load_dem()	Load the Digital Elevation Model (DEM) test data.
load_watershed_mask()	Load the watershed mask test data.
load_river_mask()	Load the river mask test data.
load_all_test_data()	Load all test data files at once.
get_data_info()	Get information about the available test data files.

Module Contents

priority_flow.data_loader.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).

Return type:

numpy.ndarray

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}")

priority_flow.data_loader.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).

Return type:

numpy.ndarray

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)}")

priority_flow.data_loader.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).

Return type:

numpy.ndarray

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)}")

priority_flow.data_loader.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

Return type:

dict

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}")

priority_flow.data_loader.get_data_info()

Get information about the available test data files.

Returns:

A dictionary containing metadata about each data file.

Return type:

dict