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import networkx as nx
import argparse
import numpy as np
import pandas as pd
import random
import copy
from tqdm import tqdm
# COMMAND PARSING
parser = argparse.ArgumentParser()
parser.add_argument("output_dir")
args = parser.parse_args()
raise FileExistsError("Output directory does not exists !")
# "stochastic_block_model_graph": {
# "nb_nodes":GRAPH_SIZE,
# "nb_edges":EDGE_SIZE,
# "nb_com" :[2,5,8,16],
# "percentage_edge_betw":[0.1,0.01]
# },
# "ER_graph": {
# "nb_nodes":GRAPH_SIZE,
# "nb_edges":EDGE_SIZE
# },
# "powerlaw_graph": { # configuration_model
# "nb_nodes":GRAPH_SIZE,
# "nb_edges":EDGE_SIZE,
# "exponent":[2,3],
# "tries":[100]
# },
"coords":["random","country"],
def get_params(inp):
return (dict(zip(inp.keys(), values)) for values in itertools.product(*inp.values()))
pbar = tqdm(parameters.items(),total=len(parameters))
for method,args in pbar:
pbar.set_description("Generating graphs using : " + method)
list_of_params = get_params(parameters[method])
for ix,params in enumerate(list_of_params):
params["nb_edges"] = params["nb_edges"] * params["nb_nodes"]
print("Gen graph using the following parameters : ",params)
for sp_id in range(sample_per_params):
try:
G = func(**params)
G.graph.update(params)
nx.write_gml(G, OUTPUT_DIR+"/graph_{method}_{ix}{sp_id}.gml".format(method=method,ix=ix,sp_id=sp_id),stringizer=str)
except Exception as e:
print(e)
print("Can't generate graphs using these parameters")