# -*- coding: utf-8 -*-
#
# Copyright 2018-2020 Data61, CSIRO
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import warnings
import pandas as pd
import networkx as nx
from stellargraph.data.epgm import EPGM
from stellargraph.core.graph import *
from stellargraph import globalvar
[docs]def from_epgm(epgm_location, dataset_name=None, directed=False):
"""
Imports a graph stored in EPGM format to a NetworkX object
Args:
epgm_location (str): The directory containing the EPGM data
dataset_name (str), optional: The name of the dataset to import
directed (bool): If True, load as a directed graph, otherwise
load as an undirected graph
Returns:
A NetworkX graph containing the data for the EPGM-stored graph.
"""
G_epgm = EPGM(epgm_location)
graphs = G_epgm.G["graphs"]
# if dataset_name is not given, use the name of the 1st graph head
if not dataset_name:
dataset_name = graphs[0]["meta"]["label"]
warnings.warn(
"dataset name not specified, using dataset '{}' in the 1st graph head".format(
dataset_name
),
RuntimeWarning,
stacklevel=2,
)
# Select graph using dataset_name
for g in graphs:
if g["meta"]["label"] == dataset_name:
graph_id = g["id"]
# Convert to StellarGraph (via nx)
Gnx = G_epgm.to_nx(graph_id, directed=directed)
print(
"Graph statistics: {} nodes, {} edges".format(
Gnx.number_of_nodes(), Gnx.number_of_edges()
)
)
return Gnx