# This file is part of MAMMULT: Metrics And Models for Multilayer Networks
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or (at
# your option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
####
##
## This is the hypergeometric model. Each layer has the same number of
## non-isolated nodes as the initial graph, but the nodes are
## activated at random. The input is a file of number of non-isolated
## nodes in each layer, and the total number of nodes in the multiplex.
##
## The output file is a node-layer participation file, in the format
##
## node_id1 layer_id1
## node_id2 layer_id2
## .....
##
import sys
import random
if len(sys.argv) < 3:
print "Usage: %s " % sys.argv[0]
sys.exit(1)
N = int(sys.argv[2])
layer_degs = []
node_layers = {}
lines = open(sys.argv[1]).readlines()
M = 0
for l in lines:
if l[0] == "#":
continue
n = [int(x) for x in l.strip(" \n").split(" ")][0]
layer_degs.append(n)
M += 1
for i in range(M):
num = layer_degs[i]
added = []
n = 0
while n < num:
j = random.choice(range(N))
if j not in added:
n += 1
added.append(j)
if node_layers.has_key(j):
node_layers[j].append(i)
else:
node_layers[j] = [i]
for n in node_layers.keys():
for i in node_layers[n]:
print n,i