def generate_monthly_trans_graphs():
graphs = get_monthly_venue_graphs()
for idx in range(len(graphs)-1, 0, -1):
cur_graph = graphs[idx]
prev_graph = graphs[idx-1]
for edge in prev_graph.Edges():
src_nid = edge.GetSrcNId()
dst_nid = edge.GetDstNId()
cur_eid = cur_graph.GetEId(src_nid, dst_nid)
cur_weight = cur_graph.GetIntAttrDatE(cur_eid, 'trsn_cnt')
prev_eid = prev_graph.GetEId(src_nid, dst_nid)
prev_weight = prev_graph.GetIntAttrDatE(prev_eid, 'trsn_cnt')
diff = cur_weight - prev_weight
# cur_graph.AddIntAttrDatE(cur_eid, cur_weight - prev_weight, 'trsn_cnt')
# month_coeff = float(idx)
month_coeff = 1
cur_graph.AddIntAttrDatE(cur_eid, ORI_FACTOR*cur_weight + month_coeff*MUL_FACTOR*diff, 'trsn_cnt')
print "updated trans graph for month ", idx
for idx, G in enumerate(graphs):
idx_str = str(idx) if idx < 10 else '9'+str(idx)
GH.save_graph(G, TRANS_PATH, TRANS_FILE_PREFIX + idx_str)
"""
Currently, the graph has node attribute:
- vid
- ckn (insofar, checkin number)
- sts (start timestamp)
- ets (end timestamp)
- lat
- lng
- category
- pcategor
And edge attribute:
- trsn_cnt
- duration
"""
venue_g = GH.load_graph(graph_path, graph_name)
category_list = VH.get_category_list(venue_path, category_name)
pcategory_list = VH.get_category_list(venue_path, pcategory_name)
# GH.print_node_attr_names(venue_g)
# GH.print_edge_attr_names(venue_g)
# print category_list
GH.print_nids(venue_g)
# create snapshop of the graph - node accurate, but edge aren't
ts_list = TH.gen_ts_list("201201010000", "201301010000", 30)
ts_list.reverse()
for ts in ts_list:
GH.filter_node_sts(venue_g, ts)
GH.save_graph(venue_g, graph_path, "sf_venue_" + ts)
for nid, vid in enumerate(node_set):
node_hash[vid] = nid
trsn_g = snap.TNEANet.New()
#node_id: 0 to n-1
for vid, nid in node_hash.iteritems():
trsn_g.AddNode(nid)
trsn_g.AddStrAttrDatN(nid, vid, 'vid')
#freq: frequncy(cnt) of edge
print trsn_g.GetNodes()
for idx, trsn in enumerate(trsn_list):
src_nid = node_hash[trsn[0]]
dst_nid = node_hash[trsn[1]]
print src_nid, dst_nid
#TODO: add timestamp filter
if not trsn_g.IsEdge(src_nid, dst_nid):
GH.add_edge_attrs(trsn_g, src_nid, dst_nid, time_list[idx])
GH.add_node_attrs(trsn_g, src_nid, dst_nid, time_list[idx])
print "add a new edge, hoho~"
else:
GH.update_edge_attrs(trsn_g, src_nid, dst_nid, time_list[idx])
GH.update_node_attrs(trsn_g, src_nid, dst_nid, time_list[idx])
print "update node info, haha~"
print idx, trsn
print len(trsn_list)
GH.save_graph(trsn_g, graph_path, 'sf_trsn_graph')
print "succesfully build the graph!"
return False
data_path = "../DataSet/Transition/"
graph_path = "../DataSet/GraphData/"
venue_path = "../DataSet/VenueData/"
trsn_list = VH.load_pickle_file(data_path, "sf_trsn_small_new")
time_list = VH.load_pickle_file(data_path, "sf_time_small_new")
full_venue_dict = VH.GetFullVenueDict(venue_path, "venues-CA-new.json")
category_dict = VH.load_json(venue_path, "category_map.json")
pcategory_dict = VH.load_json(venue_path, "pcategory_map.json")
vid_map = create_vid_map(trsn_list)
ts_list = TH.gen_ts_list("201201010000", "201301010000", 30)
venue_g = snap.TNEANet.New()
for ts_idx, ts in enumerate(ts_list):
for trsn_idx, trsn in enumerate(trsn_list):
src_ts = time_list[trsn_idx][0] # only need check one ts
dst_ts = time_list[trsn_idx][1]
if within_ts_range(ts, src_ts):
src_nid = vid_map[trsn[0]]
dst_nid = vid_map[trsn[1]]
GH.add_node(venue_g, src_nid, trsn[0], src_ts)
GH.add_node(venue_g, dst_nid, trsn[1], dst_ts)
GH.add_edge(venue_g, src_nid, dst_nid, time_list[trsn_idx])
GH.add_category(venue_g, full_venue_dict, category_dict, pcategory_dict)
print venue_g.GetNodes()
GH.save_graph(venue_g, graph_path, "sf_venue_small_" + str(ts))
venue_dict[data['id']] = data
fin.close()
return venue_dict
# add attributes for graph nodes
def AddNodeAttr(graph, full_venue_dict):
''' for each node in the graph, add two attributes
1. two float values: latitude, longitute
2. category
3. parent-category
'''
for NI in graph.Nodes():
vid = graph.GetStrAttrDatN(NI.GetId(), 'vid')
if vid in full_venue_dict:
graph.AddFltAttrDatN(NI.GetId(), float(full_venue_dict[vid]['lat']), 'lat')
graph.AddFltAttrDatN(NI.GetId(), float(full_venue_dict[vid]['lng']), 'lng')
graph.AddStrAttrDatN(NI.GetId(), full_venue_dict[vid]['category'], 'category')
graph.AddStrAttrDatN(NI.GetId(), full_venue_dict[vid]['parentcategory'], 'pcategory')
#GH.save_graph(graph, result_path, result_filename)
#return None
trsn_g = GH.load_graph(graph_data_path, graph_filename)
full_venue_dict = VH.GetFullVenueDict(venue_graph_data_path, venue_filename)
category_dict = VH.load_json(venue_graph_data_path, 'category_map.json')
pcategory_dict = VH.load_json(venue_graph_data_path, 'pcategory_map.json')
GH.add_category(trsn_g, full_venue_dict, category_dict, pcategory_dict)
GH.save_graph(trsn_g, graph_data_path, 'sf_venue_graph')
print 'successfully build venue_graph!'
