def build_graph(num_nodes, edge_path):
filelist = []
if os.path.isfile(edge_path):
filelist = [edge_path]
elif os.path.isdir(edge_path):
filelist = [
os.path.join(dp, f)
for dp, dn, filenames in os.walk(edge_path) for f in filenames
]
else:
raise ValueError(edge_path + " not supported")
edges, edge_weight = [], []
for name in filelist:
with open(name) as inf:
for line in inf:
slots = line.strip("\n").split()
edges.append([slots[0], slots[1]])
edges.append([slots[1], slots[0]])
if len(slots) > 2:
edge_weight.extend([float(slots[2]), float(slots[2])])
edges = np.array(edges, dtype="int64")
assert num_nodes > edges.max(
), "Node id in any edges should be smaller then num_nodes!"
edge_feat = dict()
if len(edge_weight) == len(edges):
edge_feat["weight"] = np.array(edge_weight)
graph = Graph(num_nodes, edges, edge_feat=edge_feat)
log.info("Build graph done")
graph.outdegree()
del edges, edge_feat
log.info("Build graph index done")
if "weight" in graph.edge_feat:
graph.node_feat["alias"], graph.node_feat[
"events"] = graph_alias_sample_table(graph, "weight")
log.info("Build graph alias sample table done")
return graph
def build_graph(num_nodes, edge_path, output_path, undigraph=True):
""" build_graph
"""
edge_file = os.path.join(output_path, "edge.npy")
edge_weight_file = os.path.join(output_path, "edge_weight.npy")
alias_file = os.path.join(output_path, "alias.npy")
events_file = os.path.join(output_path, "events.npy")
if os.path.isfile(edge_file):
edges = np.load(edge_file)
edge_feat = dict()
if os.path.isfile(edge_weight_file):
log.info("Loading weight from cache")
edge_feat["weight"] = np.load(edge_weight_file, allow_pickle=True)
node_feat = dict()
if os.path.isfile(alias_file):
log.info("Loading alias from cache")
node_feat["alias"] = np.load(alias_file, allow_pickle=True)
if os.path.isfile(events_file):
log.info("Loading events from cache")
node_feat["events"] = np.load(events_file, allow_pickle=True)
else:
filelist = get_file_list(edge_path)
edges, edge_weight = [], []
log.info("Reading edge files")
for name in filelist:
with open(name) as inf:
for line in inf:
slots = line.strip("\n").split()
edges.append([slots[0], slots[1]])
if len(slots) > 2:
edge_weight.append(slots[2])
edges = np.array(edges, dtype="int64")
assert num_nodes > edges.max(
), "Node id in any edges should be smaller then num_nodes!"
log.info("Read edge files done.")
edge_feat = dict()
node_feat = dict()
if len(edge_weight) == len(edges):
edge_feat["weight"] = np.array(edge_weight, dtype="float32")
if undigraph is True:
edges = np.concatenate([edges, edges[:, [1, 0]]], 0)
if "weight" in edge_feat:
edge_feat["weight"] = np.concatenate(
[edge_feat["weight"], edge_feat["weight"]],
0).astype("float64")
graph = Graph(num_nodes, edges, node_feat, edge_feat=edge_feat)
log.info("Build graph done")
graph.outdegree()
log.info("Build graph index done")
if "weight" in graph.edge_feat and "alias" not in graph.node_feat and "events" not in graph.node_feat:
graph.node_feat["alias"], graph.node_feat[
"events"] = graph_alias_sample_table(graph, "weight")
log.info(
"Build graph alias sample table done, and saving alias & evnets cache"
)
np.save(alias_file, graph.node_feat["alias"])
np.save(events_file, graph.node_feat["events"])
return graph
