def test_get_indices_leading_to_endpoints():
endpoints = np.array([7, 7, 7, 5, 5, 5, 7, 7, 7, 22, 5, 5, 13, 13, 13, 22,
22, 23, 13, 13, 13, 22, 22, 23, 13, 13, 13, 28, 28, 29])
# unique_endpoints = np.array([5, 7, 13, 22, 23, 28, 29])
result_indices_to_endpoints = {5: np.array([3, 4, 5, 10, 11]),
7: np.array([0, 1, 2, 6, 7, 8]),
13: np.array([12, 13, 14, 18, 19, 20, 24, 25, 26]),
22: np.array([9, 15, 16, 21, 22]),
23: np.array([17, 23]),
28: np.array([27, 28]),
29: np.array([29])}
indices_to_endpoints = trap_analysis.get_indices_leading_to_endpoints(endpoints)
for minimum in indices_to_endpoints:
indices_to_endpoints[minimum] = np.sort(indices_to_endpoints[minimum])
are_equal = compare_methods.compare_two_dictionaries_where_values_are_arrays(indices_to_endpoints,
result_indices_to_endpoints)
assert are_equal
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'))
