def voronoi2(G,movie,isDirected):
global color_map
if isDirected==0:
G2 = nx.Graph()
else:
G2 = nx.DiGraph()
#Converting frequencies to distances
for u, v, d in G.edges(data=True):
G2.add_edge(u, v, weight=(1 / d['weight']))
# Choosing 2 Ankers and as a result -> Dividing the Graph to 2 partitions
if movie == 'Captain America - Civil War':
anker1 = 'STEVE ROGERS'
anker2 = ['TONY STARK', 'NATASHA ROMANOFF']
else:
anker1 = 'WAYNE'
anker2 = ['BANE', 'SELINA']
color_map = []
for v in G2:
# print('v=' +str(v)," to anker:",anker1,'|',spw(G2, v, anker1)," to anker:",anker2,'|',spw(G2, v, anker2))
if (v == anker1):
color_map.append('blue')
elif (v in anker2):
color_map.append('red')
elif (spw(G2, v, anker1) < spw(G2, v, anker2[0]) and spw(G2, v, anker1) < spw(G2, v, anker2[1])):
color_map.append('blue')
else:
color_map.append('red')
return G2
def narrowDiGraphTo10MainCharacters(G, speakers):
mainCharacters = []
speakersDictionary = {}
#Putting all the speakers in a dictionary
for speaker in speakers:
if speaker in speakersDictionary:
speakersDictionary[speaker] = speakersDictionary[speaker] + 1
else:
speakersDictionary[speaker] = 1
#sorting in order to get the main characters
sortedSpeakers = sorted(speakersDictionary.items(), key=lambda kv: kv[1],reverse=True)
mainCharactersNumber=10
for i in range(mainCharactersNumber):
mainCharacters.append(sortedSpeakers[i][0])
print()
G3 = nx.DiGraph()
for u, v, d in G.edges(data=True):
if (u in mainCharacters and v in mainCharacters):
G3.add_edge(u, v, weight=d['weight'])
return G3
def buildGraphFromListDirectedUnweighted(speakers):
edges = []
G = nx.DiGraph()
for i in range(0, len(speakers) - 2):
if(speakers[i]!=speakers[i+1]):
G.add_edge(speakers[i], speakers[i + 1], weight=1)
return G
def level2Nodes(filename): DG = nx.DiGraph() with open(filename, "r") as f2: for line in f2: di = eval(line) TG = json_graph.tree_graph(di) DG.add_edges_from(TG.edges()) return DG
def best(self):
d = nx.DiGraph()
d.add_nodes_from([expert.name for expert in self.expert_list])
for exp in self.expert_list:
for expert in self.expert_list:
if exp.reinforce_dominate(expert):
d.add_edge(exp.name, expert.name)
return [
self.find_by_name(elem[0]) for elem in d.out_degree
if max(d.out_degree, key=lambda x: x[1])[1] == elem[1]
]
def buildGraphFromListDirectedWeighted(speakers):
edges = []
G = nx.DiGraph()
for i in range(0, len(speakers) - 2):
if(speakers[i]!=speakers[i+1]):
if (G.has_edge(speakers[i], speakers[i + 1])):
G[speakers[i]][speakers[i + 1]]['weight'] += 1
else:
G.add_edge(speakers[i], speakers[i + 1], weight=1)
return G
def combineEverything(fname, allNodes, toOutput = 2):
DG = level2Nodes(fname)
DGN_s1Nodes = DG.nodes()
tmpDict = level1Nodes()
for n in DGN_s1Nodes: #ex: Root1: {science:{[psychology, linguistics]}}
if n in tmpDict:
#print n, type(tmpDict[n]) == list
for v in tmpDict[n]:
DG.add_edge(n, v)
del tmpDict[n]
###print nodes have hierachy but not grouped
"""
for k, vd in tmpDict.iteritems():
if len(vd) > 1:
for v in vd:
DG.add_edge(k , v)
DG.add_edge("ROOT0", k)
"""
###
DGN_s2Nodes = DG.nodes()
isolatedNodes = allNodes - set(DGN_s2Nodes)
for d in DGN_s2Nodes:
if d.startswith("Root") or d.startswith("L"):
#print d, DG.neighbors(d)
DG.add_edge("ROOT0", d)
#print DG.neighbors("ROOT0")
DG2 = nx.DiGraph()
for sn in isolatedNodes:
DG2.add_edge("ROOT0", sn)
#if sn in DG.nodes():
# DG.remove_node(sn)
if toOutput == 2:
try:
tmpout1 = str(json_graph.tree_data(DG, "ROOT0")).replace("'id'", "'name'")
out1 = "var data1 ="+tmpout1+";"
tmpout2 = str(json_graph.tree_data(DG2, "ROOT0")).replace("'id'", "'name'")
out2 = "var data2 ="+tmpout2+";"
fout = open("file"+str(file_id)+"_final.js", "w")
fout.write(out1+"\n"+out2)
fout.close()
except:
nx.write(DG, "out.gml")
else:
try:
print json_graph.tree_data(DG, "ROOT0")
print json_graph.tree_data(DG2, "ROOT0")
except:
nx.write_gml(DG,"out.gml")
def graph_problem():
g = nx.DiGraph()
g.add_edge(0, 1, weight=-7)
g.add_edge(1, 2, weight=-7)
g.add_edge(2, 3, weight=-7)
g.add_edge(3, 0, weight=-9)
g.add_edge(1, 0, weight=-3)
g.add_edge(2, 1, weight=-3)
g.add_edge(3, 2, weight=-3)
g.add_edge(0, 3, weight=-1)
g.add_edge(0, 2, weight=-4)
g.add_edge(1, 3, weight=-4)
g.add_edge(2, 0, weight=-6)
g.add_edge(3, 1, weight=-6)
return g
def graph_problem():
g = nx.DiGraph()
g.add_edge(0, 1, weight=7)
g.add_edge(1, 2, weight=7)
g.add_edge(2, 3, weight=7)
g.add_edge(3, 0, weight=9)
g.add_edge(1, 0, weight=3)
g.add_edge(2, 1, weight=3)
g.add_edge(3, 2, weight=3)
g.add_edge(0, 3, weight=1)
g.add_edge(0, 2, weight=4)
g.add_edge(1, 3, weight=4)
g.add_edge(2, 0, weight=6)
g.add_edge(3, 1, weight=6)
return g
def displayGraph(self):
G = nx.DiGraph()
for key, value in self.time_exchange_data_job_dict.items():
if value.time != 0:
if not G.has_node(value.from_storage_id):
G.add_node(value.from_storage_id)
if not G.has_node(value.to_storage_id):
G.add_node(value.to_storage_id)
G.add_edge(value.from_storage_id, value.to_storage_id, weight=value.time)
pos = nx.spring_layout(G, scale=2)
nx.draw(G, pos, with_labels=True)
labels = nx.get_edge_attributes(G, 'weight')
nx.draw_networkx_edge_labels(G, pos , edge_labels= labels)
plt.savefig('Graph'+key+'.png', format="PNG")
plt.show()
def checkHypernymWNBeta(itemArr, rootid, fp = None, debug = False):
global synonym
itemArr = map(checkSynonym, itemArr)
tmpItemArr = itemArr
allHypoHyper = set()
hypo = {}
iid = 0
for i in itemArr[0:-1]:
iid += 1
for j in itemArr[iid:]:
#print i, j
h = isRelated(i, j)
if h != None and (h in itemArr):
allHypoHyper.add(h)
hypo.setdefault(h, [])
if h != i:
hypo[h].append(i)
if h != j:
hypo[h].append(j)
DG = nx.DiGraph()
in_edge = set()
#kk = hypo.keys()
for k, v in hypo.iteritems():
#print k, set(v)
for vs in list(set(v)):
if vs not in in_edge:
DG.add_edge(k, vs)
in_edge.add(vs)
if vs in tmpItemArr:
tmpItemArr.remove(vs)
### from here, the code merge some nodes by their common hypernym
hiddenNodes = hiddenHypo(tmpItemArr)
dup = set()
hid = 1
middleNodes = set()
for k, v in sorted(hiddenNodes.iteritems(), key=lambda k:len(k[1]), reverse=True):
if debug:
print "K", k, v, tmpItemArr
#continue
if v == set(tmpItemArr):
break
vt = v - dup
#dup.update(v)
if len(vt) <= 1:
#dup.update(vt)
continue
if k in itemArr:
#print "k = ", k, vt
#dup.discard(k)
vt.discard(k)
for vs in vt:
DG.add_edge(k, vs)
else:
for vs in vt:
##DG.add_edge(str(rootid)+"_Hidden"+str(hid), vs)
DG.add_edge(str(rootid)+"_M_"+k, vs)
##hid += 1
middleNodes.add(str(rootid)+"_M_"+k)
dup.update(vt)
###ends here;
if len(tmpItemArr) == 1:
RootName = tmpItemArr[0]
else:
"""
@quickHyper(tmpItemArr) => find a common hypernym of input['head', 'optic', 'lobe', 'valve', 'tissue', 'nose', 'vessel', 'tongue']
output might be the same as middleNodes
quickHyper(tmpItemArr - dup | middleNodes) = > input becomes "nose" and body_part
"""
RootName = quickHyper(tmpItemArr)
#RootName = quickHyper(list(set(tmpItemArr)- dup | middleNodes))
if RootName == "Root":
RootName = "Root"+str(rootid)
else:
RootName = "L"+str(rootid)+"_"+RootName
for t in tmpItemArr:
if t not in dup:
DG.add_edge(RootName, t)
##for l in range(1, hid):
## DG.add_edge("Root"+str(rootid), str(rootid)+"_Hidden"+str(l))
for l in list(middleNodes):
DG.add_edge(RootName, l)
if fp != None:
try:
fp.write(json_graph.tree_data(DG, RootName).__str__()+"\n")
except:
fp.write(nx.to_dict_of_lists(DG).__str__()+"\n")
nx.write_gml(DG,"out.gml")
else:
try:
#print json_graph.tree_data(DG, "Root"+str(rootid))
print json_graph.tree_data(DG, RootName)
except:
print nx.to_dict_of_lists(DG)
nx.write_gml(DG,"out.gml")