def test_shortest_path():
dist_matrix = generate_graph(20)
# We compare path length and not costs (-> set distances to 0 or 1)
dist_matrix[dist_matrix != 0] = 1
for directed in (True, False):
if not directed:
dist_matrix = np.minimum(dist_matrix, dist_matrix.T)
graph_py = floyd_warshall_slow(dist_matrix.copy(), directed)
for i in range(dist_matrix.shape[0]):
# Non-reachable nodes have distance 0 in graph_py
dist_dict = defaultdict(int)
dist_dict.update(single_source_shortest_path_length(dist_matrix, i))
for j in range(graph_py[i].shape[0]):
assert_array_almost_equal(dist_dict[j], graph_py[i, j])
def test_shortest_path():
dist_matrix = generate_graph(20)
# We compare path length and not costs (-> set distances to 0 or 1)
dist_matrix[dist_matrix != 0] = 1
for directed in (True, False):
if not directed:
dist_matrix = np.minimum(dist_matrix, dist_matrix.T)
graph_py = floyd_warshall_slow(dist_matrix.copy(), directed)
for i in range(dist_matrix.shape[0]):
# Non-reachable nodes have distance 0 in graph_py
dist_dict = defaultdict(int)
dist_dict.update(single_source_shortest_path_length(dist_matrix, i))
for j in range(graph_py[i].shape[0]):
assert_array_almost_equal(dist_dict[j], graph_py[i, j])
# once row_val equals the row[0] entry continue with for loop
indices.append(row[1])
data.append(row[2])
indptr.append(len(indices))
check = csr_matrix((data, indices, indptr), dtype=float).toarray()
check2 = csr_matrix((data, indices, indptr), dtype=float)
print(indices[0:5])
print(indptr[0:5])
print(data[0:5])
print(check[0:4, 0:5])
print(check.shape)
print(check[6, 264306])
#6 | 264306
t1 = time.time()
route = list(sorted(single_source_shortest_path_length(check2, 1).items()))
t2 = time.time()
total = t2 - t1
print("time", total)
t1 = time.time()
route = graph_shortest_path(check2, directed=False)
t2 = time.time()
total = t2 - t1
print("time", total)
print(route)