https://github.com/palash1992/DynamicGEM
Tip revision: 59fe09dee81b84e706d5daf7dfcfabfad2c3396f authored by Sujit-O on 09 May 2019, 05:11:20 UTC
compiled TIMERS for python 3.6 and matlab runtime v 9.6
compiled TIMERS for python 3.6 and matlab runtime v 9.6
Tip revision: 59fe09d
testgraphgen.py
import matplotlib.pyplot as plt
import numpy as np
import random
import networkx as nx
import operator
import sys
sys.path.append('./')
# from graph_generation import SBM_graph
from utils import graph_util
import SBM_graph
from matplotlib import rc
import seaborn
import os
font = {'family': 'serif', 'serif': ['computer modern roman']}
rc('text', usetex=True)
rc('font', weight='bold')
rc('font', size=20)
rc('lines', markersize=10)
rc('xtick', labelsize=12)
rc('ytick', labelsize=12)
rc('axes', labelsize='x-large')
rc('axes', labelweight='bold')
rc('axes', titlesize='x-large')
rc('axes', linewidth=3)
plt.rc('font', **font)
seaborn.set_style("darkgrid")
def _resample_egde_for_node(sbm_graph, node_id):
if sbm_graph._graph is None:
sbm_graph.sample_graph()
else:
n = sbm_graph._node_num
for i in range(n):
if i == node_id:
continue
if sbm_graph._graph.has_edge(node_id, i):
sbm_graph._graph.remove_edge(node_id, i)
sbm_graph._graph.remove_edge(i, node_id)
prob = sbm_graph._B[sbm_graph._node_community[node_id], sbm_graph._node_community[i]]
if np.random.uniform() <= prob:
sbm_graph._graph.add_edge(node_id, i)
sbm_graph._graph.add_edge(i, node_id)
def dyn_node_chng_v2(sbm_graph, node_id):
if sbm_graph._graph is None:
sbm_graph.sample_graph()
else:
n = sbm_graph._node_num
othercommnodes =[i for i in range(n) if sbm_graph._node_community[i]!=sbm_graph._node_community[node_id] if not sbm_graph._graph.has_edge(node_id, i)]
edgesnodes = random.sample(othercommnodes,30)
for i in edgesnodes:
sbm_graph._graph.add_edge(node_id, i)
sbm_graph._graph.add_edge(i, node_id)
for i in range(n):
if i == node_id:
continue
if sbm_graph._node_community[i]==sbm_graph._node_community[node_id]:
if sbm_graph._graph.has_edge(node_id, i):
prob = 0.1
if np.random.uniform() <= prob:
sbm_graph._graph.remove_edge(node_id, i)
sbm_graph._graph.remove_edge(i, node_id)
def diminish_community_v2(sbm_graph, community_id, nodes_to_purturb, chngnodes):
n = sbm_graph._node_num
community_nodes = [i for i in range(n) if sbm_graph._node_community[i] == community_id]
nodes_to_purturb = min(len(community_nodes), nodes_to_purturb)
perturb_nodes=chngnodes
pos=nx.spring_layout(sbm_graph._graph)
color=['#FFD700','#4B0082']
plt.figure()
plt.subplot(231)
nodes_draw=nx.draw_networkx_nodes(sbm_graph._graph,pos,node_size=40,node_color=[color[sbm_graph._node_community[p]] for p in sbm_graph._graph.nodes()])
nx.draw_networkx_edges(sbm_graph._graph,pos,arrows=False,width=0.5,alpha=0.5)
nodes_draw.set_edgecolor('w')
nodes_draw=nx.draw_networkx_nodes(sbm_graph._graph,pos,
nodelist=perturb_nodes,
node_color='r',
node_size=50,
with_labels=False)
nodes_draw.set_edgecolor('k')
nx.draw_networkx_labels(sbm_graph._graph,pos,font_size=8)
left_communitis = [i for i in range(sbm_graph._community_num) if i != community_id]
for node_id in perturb_nodes:
new_community = random.sample(left_communitis, 1)[0]
print ('Node %d change from community %d to %d' % (node_id,
sbm_graph._node_community[node_id],
new_community))
sbm_graph._node_community[node_id] = new_community
for node_id in perturb_nodes:
_resample_egde_for_node(sbm_graph, node_id)
# pos=nx.spring_layout(sbm_graph._graph)
plt.subplot(232)
nodes_draw=nx.draw_networkx_nodes(sbm_graph._graph,pos,node_size=40,node_color=[color[sbm_graph._node_community[p]] for p in sbm_graph._graph.nodes()])
nx.draw_networkx_edges(sbm_graph._graph,pos,arrows=False,width=0.5,alpha=0.5)
nx.draw_networkx_labels(sbm_graph._graph,pos,font_size=8)
nodes_draw.set_edgecolor('w')
nodes_draw=nx.draw_networkx_nodes(sbm_graph._graph,pos,
nodelist=perturb_nodes,
node_color='r',
node_size=50,
with_labels=False)
nodes_draw.set_edgecolor('k')
nodes=[i for i in range(n) if sbm_graph._node_community[i] == community_id ]
chngnodes = random.sample(nodes, nodes_to_purturb)
for node_id in chngnodes:
dyn_node_chng_v2(sbm_graph, node_id)
print("Changed Nodes: ",chngnodes)
plt.subplot(233)
nodes_draw=nx.draw_networkx_nodes(sbm_graph._graph,pos,node_size=40,node_color=[color[sbm_graph._node_community[p]] for p in sbm_graph._graph.nodes()])
nx.draw_networkx_edges(sbm_graph._graph,pos,arrows=False,width=0.5,alpha=0.5)
nx.draw_networkx_labels(sbm_graph._graph,pos,font_size=8)
nodes_draw.set_edgecolor('w')
nodes_draw=nx.draw_networkx_nodes(sbm_graph._graph,pos,
nodelist=chngnodes,
node_color='r',
node_size=50,
with_labels=False)
nodes_draw.set_edgecolor('k')
if not os.path.exists('./figures'):
os.mkdir('./figures')
count=[ files for files in os.listdir('./figures') if '.pdf' in files]
plt.savefig('./figures/motivation'+str(len(count)+1)+'.pdf',bbox_inches='tight',dpi=600)
plt.show()
return perturb_nodes, chngnodes
def get_community_diminish_series_v2(node_num,
community_num,
length,
community_id,
nodes_to_purturb,
):
my_graph = SBM_graph.SBMGraph(node_num, community_num,community_id,nodes_to_purturb)
my_graph.sample_graph_v3()
chngnodes=my_graph._chngnodes
graphs = [my_graph._graph.copy()]
nodes_comunities = [my_graph._node_community[:]]
perturbations = [[]]
dyn_change_nodes = [[]]
for i in range(length - 1):
print('Step %d' % i)
print("Migrating Nodes")
print(chngnodes)
perturb_nodes, chngnodes = diminish_community_v2(my_graph,
community_id,
nodes_to_purturb,
chngnodes)
print("Dynamically changed nodes")
print(chngnodes)
perturbations.append(perturb_nodes)
dyn_change_nodes.append(chngnodes)
graphs.append(my_graph._graph.copy())
nodes_comunities.append(my_graph._node_community[:])
return zip(graphs, nodes_comunities, perturbations, dyn_change_nodes)
def drawGraph(node_num, community_num):
my_graph = SBM_graph.SBMGraph(node_num, community_num)
my_graph.sample_graph()
graphs = [my_graph._graph.copy()]
nx.draw(graphs)
if __name__ == '__main__':
node_num = 100
community_num = 2
node_change_num = 2
length = 2
get_community_diminish_series_v2(node_num,
community_num,
length,
1,
node_change_num)
plt.show()
# drawGraph(node_num, community_num)
# prefix = 'data/synthetic/dynamic_SBM/node_pertuabtion_%d_%d_%d' % (node_num, community_num, node_change_num)
# dynamic_sbm_series = get_random_perturbation_series(node_num, community_num, length, node_change_num)
# graph_util.saveDynamicSBmGraph(prefix, dynamic_sbm_series)
# prefix = 'data/synthetic/dynamic_SBM/community_diminish_%d_%d_%d' % (node_num, community_num, node_change_num)
# dynamic_sbm_series = get_community_diminish_series(node_num, community_num, length, 1, node_change_num)
# graph_util.saveDynamicSBmGraph(prefix, dynamic_sbm_series)