def generate_graph(nc, seed):
out_dir = FULLY + 'small-world-n1000-k10-p5-nc' + str(nc) + '-seed' + str(
seed)
graph = create_graph(n=1000, nc=nc, feature_dim=16, k=10, p=0.5, seed=seed)
features = get_features_from_graph(graph)
FullySynthetic.save_graph(out_dir, graph, features)
return out_dir
def gen_fully(full, n_nodes, n_edges, p):
name_p = str(int(p))
outdir = full + "/erdos-renyi-n{}-p{}".format(n_nodes, name_p)
FullySynthetic.generate_erdos_renyi_graph(outdir,
n_nodes=n_nodes,
n_edges=n_edges)
return outdir
def create_graph(n, nc, feature_dim, k, p, seed=100):
"""
:param n: number of nodes
:param nc: number of connected components
:return: graph of networkx format
"""
# np.random.seed(123)
n_nodes = random_number_of_nodes(n, nc, k)
graphs = []
idx_node_large_graph = 0
for n_node in n_nodes:
graph, feature = FullySynthetic.generate_small_world_graph(
None, n_node, k, p, feature_dim=feature_dim, seed=seed)
add_feature_to_graph(graph, feature)
print("====Subgraph===")
print(nx.info(graph))
to_one_connected_components(graph)
graph, idx_node_large_graph = relabel_graph(graph,
idx_node_large_graph)
graphs.append(graph)
check_graphs_labels_distinguish(graphs)
while len(graphs) > 1:
graph = nx.compose(graphs[0], graphs[1])
graphs = [graph, *graphs[2:]]
print("====Large graph====")
print(nx.info(graphs[0]))
print("Number of connected components:",
len(list(nx.connected_components(graphs[0]))))
return graphs[0]
from input.semi_synthetic import SemiSynthetic
from input.fully_synthetic import FullySynthetic
import numpy as np
n_nodes = [1000, 2000, 5000, 10000, 20000]
ks = [20,60,100,200,350]
for n in n_nodes:
for k in ks:
#np.random.seed(123)
outdir="../dataspace/graph/fully-synthetic/small-world-n{}-k{}-p5-seed123/".format(n, k)
FullySynthetic.generate_small_world_graph(outdir,n_nodes=n,k_neighbors=k, p_edge_modify=0.5, feature_dim=16)
semiSynthetic = SemiSynthetic(outdir+'/graphsage',outdir+'/random-d01')
semiSynthetic.generate_random_clone_synthetic(0, 0.01)
def gen_fully_smallworld(full, n_nodes, p):
name_p = str(int(p))
outdir = full+"/small_world-n{}-p{}".format(n_nodes,name_p)
FullySynthetic.generate_small_world_graph(outdir, n_nodes, int(p), 0.35)
return outdir
check_graphs_labels_distinguish(graphs)
while len(graphs) > 1:
graph = nx.compose(graphs[0], graphs[1])
graphs = [graph, *graphs[2:]]
print("====Large graph====")
print(nx.info(graphs[0]))
print("Number of connected components:",
len(list(nx.connected_components(graphs[0]))))
return graphs[0]
def get_features_from_graph(graph):
features = None
if 'feature' in graph.node[graph.nodes()[0]]:
features = []
for idx, node in enumerate(graph.nodes()):
features.append(graph.node[node]['feature'])
features = np.array(features)
return features
if __name__ == '__main__':
args = parse_args()
print(args)
graph = create_graph(args.n, args.nc, args.feature_dim, args.k, args.p,
args.seed)
features = get_features_from_graph(graph)
FullySynthetic.save_graph(args.output_dir, graph, features)
def gen_fully(n_nodes,p):
name_p = str(p).replace("0.","")
outdir = full+"/erdos-renyi-n{}-p{}".format(n_nodes,name_p)
FullySynthetic.generate_erdos_renyi_graph(outdir,n_nodes=n_nodes,p_edge_creation=p)
return outdir