def test_get_minimums_in_watersheds():
num_of_cols = 6
num_of_rows = 5
minimum_indices = np.array([5, 7, 13, 22, 23, 28, 29])
neighbors = np.array([[4, 10, 11, -1, -1, -1, -1, -1],
[0, 1, 2, 6, 8, 12, 13, 14],
[6, 7, 8, 12, 14, 18, 19, 20],
[15, 16, 17, 21, 23, 27, 28, 29],
[16, 17, 22, 28, 29, -1, -1, -1],
[21, 22, 23, 27, 29, -1, -1, -1],
[22, 23, 28, -1, -1, -1, -1, -1]])
connections = [{5}, {7, 13}, {22, 23, 28, 29}]
result_connections = trap_analysis.get_minimums_in_watersheds(minimum_indices, num_of_cols, num_of_rows)
assert sorted(connections) == sorted(result_connections)
import time
saved_files = '/home/shomea/a/anderovo/Dropbox/watershedLargeFiles/'
file_name = saved_files + 'anders_hoh.tiff'
"""
Save the watershed using pickle and numpy save.
"""
landscape = load_geotiff.get_landscape_tyrifjorden(file_name)
# Get downslope neighbors
downslope_neighbors = util.get_downslope_indices(landscape.num_of_nodes_x, landscape.num_of_nodes_y,
landscape.coordinates[:, 2])
# Get endpoints
endpoints = trap_analysis.get_node_endpoints(landscape.num_of_nodes_x, landscape.num_of_nodes_y, downslope_neighbors)
# Get minimums in each watershed
minimum_indices = np.where(downslope_neighbors == -1)[0]
minimums_in_each_watershed = sorted(trap_analysis.get_minimums_in_watersheds(minimum_indices, landscape.num_of_nodes_x,
landscape.num_of_nodes_y))
# Get indices leading to endpoints
indices_leading_to_endpoints = trap_analysis.get_indices_leading_to_endpoints(endpoints)
# Get the nodes in the watersheds. Save to file.
nodes_in_watersheds = trap_analysis.get_nodes_in_watersheds(endpoints, minimums_in_each_watershed)
cPickle.dump(nodes_in_watersheds, open('nodesInWatershedsStandard.pkl', 'wb'))
