def generate_timely_graph(visited: List[str], string2candidate: Dict[str, CandidateFeature]):
#generate id
id2candidate: Dict[str, int] = {}
for counter in range(len(visited)):
id2candidate[visited[counter]] = counter
import gexf
gexf = gexf.Gexf('Felix Neutatz', '28-11-2012')
# make an undirected dynamical graph
graph = gexf.addGraph('directed', 'dynamic', '28-11-2012')
edge_counter = 0
current_time = 0
id2candidate['__root__'] = -1
graph.addNode(-1, '__root__', start=str(0.0))
for v_i in range(len(visited)):
id2candidate[visited[v_i]] = v_i
graph.addNode(v_i, visited[v_i], start=str(current_time))
current_candidate = string2candidate[visited[v_i]]
current_time += string2candidate[str(current_candidate)].runtime_properties['execution_time']
if not isinstance(current_candidate, RawFeature):
for p in current_candidate.parents:
graph.addEdge(edge_counter, id2candidate[str(p)], id2candidate[str(current_candidate)], start=str(current_time))
edge_counter += 1
else:
graph.addEdge(edge_counter, id2candidate['__root__'], id2candidate[str(current_candidate)], start=str(current_time))
gexf.write(open('/tmp/dynamic_graph.gexf', "wb+"))
open("C:\Users\CRAZY\PycharmProjects\Small_Projects\NMProject\MonthData.csv", "rb"))
rowno = 0
for row in monthreader:
if rowno == 0:
rowno += 1
continue
if rowno == 1:
rowno += 1
month = monthreader[2]
G = networkx.DiGraph()
G.add_node(monthreader[0])
G.add_node(monthreader[1])
G.add_edge(monthreader[0],monthreader[1],weight=monthreader[3])
else:
if monthreader[2] == month:
if not G.has_node(monthreader[0])
G.add_node(monthreader[0])
G.add_node(monthreader[1])
G.add_edge(monthreader[0], monthreader[1], weight=monthreader[3])
gexf = gexf.Gexf('Your Name','28-11-2012')
#make an undirected dynamical graph
graph = gexf.addGraph('undirected','dynamic','28-11-2012',timeformat='date')
#you add nodes with a unique id
graph.addNode(Source,"source_id")
#make edge with unique id, the edge has time duration from start to end
graph.addEdge(edge_id,Source,Target,start = Date , end = Date)
#write the gexf format to fileout
gexf.write(fileOut)
cols.remove('Article URL.1')
gexf = Gexf("emCOMP", "Article Similarity")
graph = gexf.addGraph("undirected", "static", "Article Similarity")
#add nodes
for r in rows:
graph.addNode(r, dates.loc[r, "updated_domain"])
#add edges
count = 0
count_r = 0
for r in rows:
print("r" + str(count_r))
for c in cols:
#can be adapted for directed graph
if (df.loc[r, c] > .85):
r_date = datetime.datetime.strptime(str(dates.loc[r, "first_ts"]),
'%Y-%m-%d %H:%M:%S')
c_date = datetime.datetime.strptime(str(dates.loc[c, "first_ts"]),
'%Y-%m-%d %H:%M:%S')
if (r < c):
graph.addEdge(count, r, c, df.loc[r, c])
else:
graph.addEdge(count, c, r, df.loc[r, c])
count = count + 1
count_r = count_r + 1
output_file = open("edge_matrix.gexf", "w")
gexf.write(output_file)