from py2neo import Graph as pGraph
from igraph import Graph as iGraph
graph = pGraph("http://localhost:7474/db/data/")
print graph
query = """
MATCH (n)-[r]->(m)
WHERE r.prob>0.8
RETURN n.person_ID,m.person_ID,r.prob
"""
data = graph.cypher.execute(query)
print data
ig=iGraph.TupleList(data,weights=True)
print ig
def build_graph(self, random=False):
neo4j = pGraph()
# actors - movies
print "getting data from neo4j"
query = """
MATCH (p1:Actor)-[:ACTS_IN]->(m:Movie)
RETURN p1.name, m.title
"""
data = neo4j.cypher.execute(query)
actors = list(set([datum[0] for datum in data]))
movies = list(set([datum[1] for datum in data]))
query = """
MATCH (p1:Director)-[:DIRECTED]->(m:Movie)
RETURN p1.name, m.title
"""
data1 = neo4j.cypher.execute(query)
directors = list(set([datum[0] for datum in data1]))
movies1 = list(set([datum[1] for datum in data1]))
print "building vertices"
self.graph = igraph.Graph()
self.graph.add_vertices(actors)
self.graph.vs['actor'] = True
self.graph.vs['movie'] = False
self.graph.vs['director'] = False
self.graph.add_vertices(list(set(movies+movies1)))
for v in self.graph.vs:
if not v['actor']:
v['movie'] = True
v['actor'] = False
v['director'] = False
for d in directors:
try:
v = self.graph.vs.find(name=d)
v['director'] = True
except:
self.graph.add_vertex(
name=d,
**{
'movie': False,
'actor': False,
'director': True
}
)
print "connecting vertices"
if random:
# todo make random network connections
pass
else:
for datum in data:
self.graph.add_edge(
datum[0], datum[1], **{'label': 'acts_in'}
)
for datum in data1:
self.graph.add_edge(
datum[0], datum[1], **{'label': 'directs'}
)
# -*- coding: utf-8 -*-
"""
@author Hamsavardhini
"""
from py2neo import Graph as pGraph
from igraph import Graph as iGraph
import re
neo4j = pGraph("http://localhost:7474/db/data/")
query = "Match(n)-[r]->(c) return n,c"
data = neo4j.cypher.execute(query)
ig = iGraph.TupleList(data)
new_dict = {}
attributes = []
clusterID = []
class clustering(object):
def walktrap(self):
wcluster = ig.community_walktrap().as_clustering()
self.modularity = wcluster.modularity
self.membership = wcluster.membership
self.num_of_clusters = max(wcluster.membership) + 1
# print self.num_of_clusters
# print len(self.membership)
# print self.modularity
# ig.write_svg("walktrap.svg",layout=ig.layout_kamada_kawai())
def match_input(self):
self.walktrap()
import scholarly
import json
import urllib
from py2neo import Graph as pGraph, authenticate
from py2neo.packages.httpstream import http
from flask import Flask, render_template, url_for
http.socket_timeout = 9999
app = Flask(__name__)
authenticate("localhost:7474","neo4j", "BigData1")
neo4j = pGraph()
@app.route("/")
def main():
return render_template("index.html")
@app.route("/clustering")
def clustering():
return render_template("cluster.html")
@app.route("/analytics")
def analytics():
return render_template("analytics.html")
@app.route("/papers/cluster/<algorithm>/<int:limit>")
@app.route("/papers/cluster/<algorithm>/<int:limit>/<keyword>")
def paper_clusters(algorithm, limit, keyword=""):
