def test_shuffle_adjacency():
graph_args = {
"generator_type": "uniform",
"sizes": [2, 2],
"p_in": 1.0,
"p_out": .0,
"out_path": None,
"visualize": False,
"cull_disconnected": False,
"connect_disconnected": False,
"generator_type": "uniform",
"shuffle_labels": True
}
graph = generate_appm.main(graph_args)
adjacency_matrix = nx.adjacency_matrix(
graph, np.arange(graph.number_of_nodes())).todense()
node_list = list(graph.nodes())
first_node_index = node_list[0]
second_node_index = node_list[1]
third_node_index = node_list[2]
# first and second should have an edge
assert_equal(adjacency_matrix[first_node_index, second_node_index], 1)
# first and third should not have an edge
assert_equal(adjacency_matrix[first_node_index, third_node_index], 0)
def run_graph_generate(args):
print("graph_generate")
generate_args_base = {
"sizes": args["cluster_sizes"],
"p_in": args["p"],
"p_out": args["q"],
"seed": args["seed"],
"cull_disconnected": args["cull_disconnected"],
"connect_disconnected": args["connect_disconnected"],
"generator_type": args["generator_type"],
"out_path": None,
"visualize": False,
}
graphs = {}
num_graphs = args["num_graphs"]
for i in range(num_graphs):
if i == 0 or (i+1) % 100 == 0 or i == (num_graphs - 1):
print(f"graph {i+1}/{num_graphs}")
generate_args = generate_args_base.copy()
if args.get('verbose', False):
print(f"{i}: {generate_args}")
graph = generate_appm.main(generate_args)
graph_id = str(uuid.uuid4())
graphs[graph_id] = {'args': generate_args, 'graph': graph }
out_path = (f"{args['results_base']}"
f"/{datetime.now().strftime(TIMESTAMP_FORMAT)}.pk")
dump_pickle(graphs, out_path)
def test_simple_adjacency():
graph_args = {
"generator_type": "uniform",
"sizes": [2, 2],
"p_in": 1.0,
"p_out": 1.0,
"out_path": None,
"visualize": False,
"cull_disconnected": False,
"connect_disconnected": True,
"generator_type": "uniform",
"shuffle_labels": False
}
graph = generate_appm.main(graph_args)
adjacency_matrix = nx.adjacency_matrix(graph).todense()
correct_adjacency = np.ones((4, 4))
# no self-edges
correct_adjacency[np.arange(4), np.arange(4)] = 0
assert_true(np.allclose(adjacency_matrix, correct_adjacency))
def _generate_new_graph(self):
graph = generate_appm.main(self.graph_args)
self.graph = graph
def _generate_new_graph(self):
if self.graph is not None and self._fixed_graph:
return
graph_args = generate_graph_args()
graph = generate_appm.main(graph_args)
self.graph = graph