def Gen_Filtering_Graph(relation_count=100, ori_tw_count=30):
"""
this function aim to generate a graph that was filtered by certain criterion
"""
import FSDao
import igraph
g = FSDao.read_pickle_graph(properties["base_dir"] + properties["expr_dir"] + "relation.pickle.old")
f = open(properties["base_dir"] + "users_unfilter.csv")
uid_list = []
for line in f:
t = line.strip().split(",")
if int(t[1]) <= relation_count:
continue
if int(t[2]) <= ori_tw_count:
continue
uid_list.append(int(t[0]))
f.close()
sub_vlsit = [v.index for v in g.vs if v["user_id"] in uid_list]
g_sub = g.subgraph(sub_vlsit)
# FSDao.write_pickle(properties['base_dir']+properties['expr_dir'],'relation.pickle',g_sub)
return g_sub
pass
def Gen_Filtering_Graph(relation_count=100, ori_tw_count=30):
'''
this function aim to generate a graph that was filtered by certain criterion
'''
import FSDao
import igraph
g = FSDao.read_pickle_graph(properties['base_dir'] +
properties['expr_dir'] + 'relation.pickle.old')
f = open(properties['base_dir'] + 'users_unfilter.csv')
uid_list = []
for line in f:
t = line.strip().split(',')
if int(t[1]) <= relation_count:
continue
if int(t[2]) <= ori_tw_count:
continue
uid_list.append(int(t[0]))
f.close()
sub_vlsit = [v.index for v in g.vs if v['user_id'] in uid_list]
g_sub = g.subgraph(sub_vlsit)
#FSDao.write_pickle(properties['base_dir']+properties['expr_dir'],'relation.pickle',g_sub)
return g_sub
pass
def __init__(self, base_dir,expr_dir):
self.base_dir=base_dir
self.expr_dir=expr_dir
self.g=FSDao.read_pickle_graph(self.base_dir+self.expr_dir+SQLDao.ce.properties['relation_graph_file_name'])
pass
