def scc(G):
"""Strongly Connected Components"""
G_reversed = DiGraph()
for u in G.adj:
for v in G.adj[u]:
G_reversed.add_edge(v, u, attr=G.adj[u][v])
# topologically high to low
sorted_vertices = topological_sort(G)[::-1]
groups = _scc(G_reversed, sorted_vertices)
return groups
def get_dfs_tree(self, property, node):
if property not in self.properties:
raise Exception(property + ' is not a SKOS property')
di_graph = DiGraph()
for s, p, o in self.vocab.triples(None, SKS[property], None):
di_graph.add_edge(s, o)
tree_edges = di_graph.dfs_tree(node)
di_graph.clear()
di_graph.add_edges_from(list(tree_edges))
# label nodes with literals
for n1, n2 in di_graph.edges():
di_graph.nodes()[n1]['label'] = self.get_term_from_uri(n1)
di_graph.nodes()[n2]['label'] = self.get_term_from_uri(n2)
return di_graph
def adjust_route(topology, remove_file, routes, link_order):
# get remove_links
f = open(remove_file)
links = []
line = f.readline()
while line:
s = line.rstrip().split(' ')
s = [int(i) for i in s]
ls = s[0]
ld = s[1]
if ld < ls:
tmp = ls
ls = ld
ld = tmp
links.append((ls,ld))
line = f.readline()
f.close()
# get final topology
g = DiGraph()
f = open(topology)
line = f.readline()
line = f.readline()
while line:
s = line.rstrip().split(' ')
lls = int(s[0])
lld = int(s[1])
#g.add_nodes([int(s[0]), int(s[1])])
g.add_edge(lls, lld, link_order[lls,lld][1] / link_order[lls,lld][0])
g.add_edge(lld, lls, link_order[lls,lld][1] / link_order[lls,lld][0])
line = f.readline()
f.close()
def sort_path(paths):
for i in range(len(paths)):
for j in range(i, len(paths)):
if paths[i][1] < paths[j][1]:
tmp = paths[i]
paths[i] = paths[j]
paths[j] = tmp
def calculate_cf(paths, link_order):
for p in paths:
cf = 100000
for i in range(len(p[0]) - 1):
tmp_cf = 0
s = p[0][i]
d = p[0][i+1]
if s < d:
tmp_cf = link_order[s,d][0] / link_order[s,d][1]
else:
tmp_cf = link_order[d,s][0] / link_order[d,s][1]
if tmp_cf < cf:
cf = tmp_cf
p[1] = cf
sort_path(paths)
for ls,ld in links:
#print(ls,ld)
for s,d in routes:
route_paths = routes[s,d]
remove_route = []
remove_weight = 0
for path, weight in route_paths:
for i in range(len(path) - 1):
if (path[i] == ls and path[i+1] == ld) or (path[i] == ld and path[i+1] == ls):
remove_route.append([path, weight])
remove_weight += weight
# remove weight from all the link
for pi in range(len(path) - 1):
ps = path[pi]
pd = path[pi+1]
if pd < ps:
tmp = pd
pd = ps
ps = tmp
link_order[ps,pd][1] -= weight
break
if remove_weight != 0:
# Find k-shortest-paths between s,d
tmp_paths = algorithms.ksp_yen(g, s, d, 20)
yen_paths = [[yen_path['path'], 0, 0] for yen_path in tmp_paths]
# make sure the proportion of every yen_path
steps = 10.0
gap = remove_weight / steps
calculate_cf(yen_paths, link_order)
for step in range(int(steps)):
for yi in range(len(yen_paths[0][0]) - 1):
ys = yen_paths[0][0][yi]
yd = yen_paths[0][0][yi + 1]
if yd < ys:
tmp = ys
ys = yd
yd = tmp
link_order[ys,yd][1] += gap
yen_paths[0][2] += 1 / steps
calculate_cf(yen_paths, link_order)
# remain routes
for rr in remove_route:
route_paths.remove(rr)
# merge k-s-p into routes
for yen_path, flows, proportion in yen_paths:
if proportion == 0:
continue
exist = False
for rp in route_paths:
if rp[0] == yen_path:
rp[1] += remove_weight * proportion
exist = True
if not exist:
route_paths.append([yen_path, remove_weight * proportion])
routes[s,d] = route_paths
return routes
def main():
# Load the graph
G = DiGraph("net5")
# Get the painting object and set its properties.
paint = G.painter()
#paint.set_source_sink('ada', 'bob')
paint.set_source_sink('s5', 's7')
# load the graph dictionary
das_ergebnis = joblib.load(
"/Users/aditimiglani/Downloads/das_ergebnis.pkl")
list_of_edges = das_ergebnis['edges']
list_of_nodes = das_ergebnis['nodes']
for edge in list_of_edges:
source = str(edge['source'])
target = str(edge['target'])
load = float(edge['load'])
G.add_edge(source, target, load)
G.add_edge(target, source, load)
#G.add_edge('ada', 'sue', 3)
#G.add_edge('ada', 'john', 2)
#G.add_edge('sue', 'bob', 1)
#G.add_edge('a', 'b', 1)
#G.add_edge('sue', 'john', 1)
#G.add_edge('john', 'bob', 1)
# Generate the graph using the painter we configured.
G.export(False, paint)
# Get 5 shortest paths from the graph.
items = algorithms.ksp_yen(G, 's5', 's7', 5)
all_paths = []
#items = algorithms.ksp_yen(G, 'ada', 'bob', 5)
for path in items:
print "Cost:%s\t%s" % (path['cost'], "->".join(path['path']))
all_paths.append(path['path'])
print all_paths
sub_das_ergebnis = {}
sub_das_ergebnis['nodes'] = []
sub_das_ergebnis['edges'] = []
for sub_dict in list_of_nodes:
for path in all_paths:
for i in range(len(path)):
if path[i] == sub_dict['id']:
if sub_dict not in sub_das_ergebnis['nodes']:
if i == 0 or i == len(path) - 1:
sub_dict['root'] = True
sub_das_ergebnis['nodes'].append(sub_dict)
else:
sub_dict['root'] = False
sub_das_ergebnis['nodes'].append(sub_dict)
for sub_dict in list_of_edges:
for path in all_paths:
for i in range(len(path)):
if i < len(path) - 1:
if (path[i] == sub_dict['source']
or path[i] == sub_dict['target']) and (
path[i + 1] == sub_dict['source']
or path[i + 1] == sub_dict['target']):
if sub_dict not in sub_das_ergebnis['edges']:
sub_das_ergebnis['edges'].append(sub_dict)
joblib.dump(sub_das_ergebnis, 'sub_das_ergebnis.pkl')
print sub_das_ergebnis
print 'loading'
loaded = joblib.load('sub_das_ergebnis.pkl')
print loaded
return 0
def main():
G = DiGraph()
undershorts = Node("undershorts")
pants = Node("pants")
belt = Node("belt")
shirt = Node("shirt")
tie = Node("tie")
jacket = Node("jacket")
socks = Node("socks")
shoes = Node("shoes")
watch = Node("watch")
G.add_edge(shirt, belt)
G.add_edge(shirt, tie)
G.add_edge(tie, jacket)
G.add_edge(belt, jacket)
G.add_edge(pants, belt)
G.add_edge(undershorts, shoes)
G.add_edge(undershorts, pants)
G.add_edge(pants, shoes)
G.add_edge(socks, shoes)
G.add_edge(watch, watch)
vertices_sorted = topological_sort(G)
# Can have more than 1 answers
print(vertices_sorted)
# interstation cost (mins)
isc = 5
interrows = []
for stopA in fullStops:
for stopB in fullStops:
a, b = spsl(stopA)
c, d = spsl(stopB)
if (a == c and not (b == d)):
interrows.append((stopA, stopB, isc))
GMaster = DiGraph('awesome')
for stop in fullStops:
GMaster.add_node(stop)
for row in rows:
GMaster.add_edge(row[0], row[1], row[2])
for irow in interrows:
GMaster.add_edge(irow[0], irow[1], irow[2])
print "Calculate Routes..."
# Holds all routes in memory to aid filtering
fromToDict = {}
for stopFrom in fullStops:
print "Currently working on:", stopFrom
stA, t = spsl(stopFrom)
G = copy.deepcopy(GMaster)
distances, previous = algorithms.dijkstra(G, stopFrom)
path_len = 0
for path, weight in route_paths:
path_len += (len(path) - 1) * weight
path_len_routes_base[(alpha, s, d)] = path_len
g = DiGraph()
f = open(final_topology)
line = f.readline()
length_graph = int(line.rstrip().split(' ')[0])
line = f.readline()
while line:
s = line.rstrip().split(' ')
lls = int(s[0])
lld = int(s[1])
g.add_edge(lls, lld, 1)
g.add_edge(lld, lls, 1)
line = f.readline()
f.close()
for n in range(length_graph):
distances = dijkstra(g, length_graph, n)
for key in distances:
if key == n:
continue
path_len_shortest[(alpha, n, key)] = distances[key]
g = DiGraph()
f = open(final_topology_base)
def GenerateGraph(person1,person2):
person1_found = 'N'
person2_found = 'N'
#u'phillip.k': u's2625'
print person1
print person2
try:
node1 =person_node_mapping[person1.lower()]
person1_found = 'Y'
except:
print "Person 1 Not found"
node1 =u's78' #Janel Guerrero
try:
node2 =person_node_mapping[person2.lower()]
person2_found = 'Y'
except:
print "Person 2 Not found"
node2 = u's30018'
G = DiGraph("net5")
# Get the painting object and set its properties.
paint = G.painter()
#paint.set_source_sink('ada', 'bob')
paint.set_source_sink(node1, node2)
# load the graph dictionary
list_of_edges = das_ergebnis['edges']
list_of_nodes = das_ergebnis['nodes']
for edge in list_of_edges:
source = str(edge['source'])
target = str(edge['target'])
load = float(edge['load'])
G.add_edge(source, target, load)
G.add_edge(target, source, load)
#G.add_edge('ada', 'sue', 3)
#G.add_edge('ada', 'john', 2)
#G.add_edge('sue', 'bob', 1)
#G.add_edge('a', 'b', 1)
#G.add_edge('sue', 'john', 1)
#G.add_edge('john', 'bob', 1)
# Generate the graph using the painter we configured.
#G.export(False, paint)
# Get 5 shortest paths from the graph.
items = algorithms.ksp_yen(G, node1, node2, 5)
all_paths = []
#items = algorithms.ksp_yen(G, 'ada', 'bob', 5)
for path in items:
print "Cost:%s\t%s" % (path['cost'], "->".join(path['path']))
all_paths.append(path['path'])
print all_paths
sub_das_ergebnis = {}
sub_das_ergebnis['nodes'] = []
sub_das_ergebnis['edges'] = []
for sub_dict in list_of_nodes:
for path in all_paths:
for i in range(len(path)):
if path[i] == sub_dict['id']:
if sub_dict not in sub_das_ergebnis['nodes']:
if i == 0 or i == len(path) - 1:
sub_dict['root'] = True
sub_das_ergebnis['nodes'].append(sub_dict)
else:
sub_dict['root'] = False
sub_das_ergebnis['nodes'].append(sub_dict)
for sub_dict in list_of_edges:
for path in all_paths:
for i in range(len(path)):
if i < len(path)-1:
if (path[i] == sub_dict['source'] or path[i] == sub_dict['target']) and (path[i+1] == sub_dict['source'] or path[i+1] == sub_dict['target']):
if sub_dict not in sub_das_ergebnis['edges']:
sub_das_ergebnis['edges'].append(sub_dict)
#joblib.dump(sub_das_ergebnis, 'sub_das_ergebnis.pkl')
nodes =sub_das_ergebnis['nodes']
edges =sub_das_ergebnis['edges']
node_list = []
count =0
for node in nodes:
if node['caption'] in enron_table:
word = enron_table[node['caption']][1]
org = enron_table[node['caption']][0]
node_list.append([word,org,node['id']])
count+=1
elif node['caption'] in other_org_table:
word = other_org_table[node['caption']][1]
org = other_org_table[node['caption']][0]
node_list.append([word,org,node['id']])
count+=1
else:
continue
edge_list = []
connection_exist =[]
for edge in edges:
source = edge['source']
target = edge['target']
value = edge['load']
value = value/4
value1 = int(value*10)
value2 = int(value*200)
connection_exist.append(edge['source'])
connection_exist.append(edge['target'])
edge_list.append([edge['source'],edge['target'],value1,value2])
F = open("WorldCup2014.js","w")
F.write("var nodes = [")
nodes =[]
for node in node_list:
num = 1
if node[0] ==person1:
num = 2
if node[0] ==person2:
num = 3
string = "{id: " + str(node[2][1:]) + ", label: '" + str(node[0].title()) + "', value: " + str(20) +", group: " + str(num)+"},"
nodes.append(string)
#print string
F.write(string)
F.write("];")
F.write("var edges = [")
edges =[]
for edge in edge_list:
string = "{from: %s, to: %s, value: %s, title: 'Relationship score: %s'}," %(edge[0][1:],edge[1][1:],edge[2],edge[3])
edges.append(string)
F.write(string)
F.write("];")
F.close()
return nodes,edges
def adjust_route(topology, remove_file, routes, link_order):
# get remove_links
f = open(remove_file)
links = []
line = f.readline()
while line:
s = line.rstrip().split(' ')
s = [int(i) for i in s]
ls = s[0]
ld = s[1]
if ld < ls:
tmp = ls
ls = ld
ld = tmp
links.append((ls, ld))
line = f.readline()
f.close()
# get final topology
g = DiGraph()
f = open(topology)
line = f.readline()
line = f.readline()
while line:
s = line.rstrip().split(' ')
lls = int(s[0])
lld = int(s[1])
#g.add_nodes([int(s[0]), int(s[1])])
g.add_edge(lls, lld, link_order[lls, lld][1] / link_order[lls, lld][0])
g.add_edge(lld, lls, link_order[lls, lld][1] / link_order[lls, lld][0])
line = f.readline()
f.close()
def sort_path(paths):
for i in range(len(paths)):
for j in range(i, len(paths)):
if paths[i][1] < paths[j][1]:
tmp = paths[i]
paths[i] = paths[j]
paths[j] = tmp
def calculate_cf(paths, link_order):
for p in paths:
cf = 100000
for i in range(len(p[0]) - 1):
tmp_cf = 0
s = p[0][i]
d = p[0][i + 1]
if s < d:
tmp_cf = link_order[s, d][0] / link_order[s, d][1]
else:
tmp_cf = link_order[d, s][0] / link_order[d, s][1]
if tmp_cf < cf:
cf = tmp_cf
p[1] = cf
sort_path(paths)
for ls, ld in links:
#print(ls,ld)
for s, d in routes:
route_paths = routes[s, d]
remove_route = []
remove_weight = 0
for path, weight in route_paths:
for i in range(len(path) - 1):
if (path[i] == ls
and path[i + 1] == ld) or (path[i] == ld
and path[i + 1] == ls):
remove_route.append([path, weight])
remove_weight += weight
# remove weight from all the link
for pi in range(len(path) - 1):
ps = path[pi]
pd = path[pi + 1]
if pd < ps:
tmp = pd
pd = ps
ps = tmp
link_order[ps, pd][1] -= weight
break
if remove_weight != 0:
# Find k-shortest-paths between s,d
tmp_paths = algorithms.ksp_yen(g, s, d, 20)
yen_paths = [[yen_path['path'], 0, 0]
for yen_path in tmp_paths]
# make sure the proportion of every yen_path
steps = 10.0
gap = remove_weight / steps
calculate_cf(yen_paths, link_order)
for step in range(int(steps)):
for yi in range(len(yen_paths[0][0]) - 1):
ys = yen_paths[0][0][yi]
yd = yen_paths[0][0][yi + 1]
if yd < ys:
tmp = ys
ys = yd
yd = tmp
link_order[ys, yd][1] += gap
yen_paths[0][2] += 1 / steps
calculate_cf(yen_paths, link_order)
# remain routes
for rr in remove_route:
route_paths.remove(rr)
# merge k-s-p into routes
for yen_path, flows, proportion in yen_paths:
if proportion == 0:
continue
exist = False
for rp in route_paths:
if rp[0] == yen_path:
rp[1] += remove_weight * proportion
exist = True
if not exist:
route_paths.append(
[yen_path, remove_weight * proportion])
routes[s, d] = route_paths
return routes
def test_dag_shortest_path():
G = DiGraph()
r = Node("r")
s = Node("s")
t = Node("t")
x = Node("x")
y = Node("y")
z = Node("z")
G.add_edge(r, s, w=5)
G.add_edge(r, t, w=3)
G.add_edge(s, x, w=6)
G.add_edge(s, t, w=2)
G.add_edge(t, x, w=7)
G.add_edge(t, y, w=4)
G.add_edge(t, z, w=2)
G.add_edge(x, y, w=-1)
G.add_edge(x, z, w=1)
G.add_edge(y, z, w=-2)
dag_shortest_path(G, s)
assert [u.d for u in G.node] == [float('inf'), 0, 2, 6, 5, 3]
def test_bellman_ford():
G = DiGraph()
s = Node("s")
t = Node("t")
y = Node("y")
x = Node("x")
z = Node("z")
G.add_edge(s, t, w=6)
G.add_edge(s, y, w=7)
G.add_edge(t, y, w=8)
G.add_edge(t, x, w=5)
G.add_edge(t, z, w=-4)
G.add_edge(x, t, w=-2)
G.add_edge(y, x, w=-3)
G.add_edge(y, z, w=9)
G.add_edge(z, x, w=7)
G.add_edge(z, s, w=2)
assert bellman_ford(G, s)
def test_dijkstra():
G = DiGraph()
s = Node("s")
t = Node("t")
y = Node("y")
x = Node("x")
z = Node("z")
G.add_edge(s, t, w=10)
G.add_edge(s, y, w=5)
G.add_edge(t, y, w=2)
G.add_edge(y, t, w=3)
G.add_edge(t, x, w=1)
G.add_edge(y, x, w=9)
G.add_edge(y, z, w=2)
G.add_edge(z, s, w=7)
G.add_edge(z, x, w=6)
G.add_edge(x, z, w=4)
dijkstra(G, s)
assert [u.d for u in G.node] == [0, 8, 5, 9, 7]
path_len = 0
for path, weight in route_paths:
path_len += (len(path) - 1) * weight
path_len_routes_base[(alpha, s, d)] = path_len
g = DiGraph()
f = open(final_topology)
line = f.readline()
length_graph = int(line.rstrip().split(' ')[0])
line = f.readline()
while line:
s = line.rstrip().split(' ')
lls = int(s[0])
lld = int(s[1])
g.add_edge(lls, lld, 1);
g.add_edge(lld, lls, 1);
line = f.readline()
f.close()
for n in range(length_graph):
distances = dijkstra(g, length_graph, n)
for key in distances:
if key == n:
continue
path_len_shortest[(alpha, n, key)] = distances[key]
g = DiGraph()
f = open(final_topology_base)
def main():
G = DiGraph()
a = Node("a")
b = Node("b")
c = Node("c")
d = Node("d")
e = Node("e")
f = Node("f")
g = Node("g")
h = Node("h")
G.add_edge(a, b)
G.add_edge(e, a)
G.add_edge(b, e)
G.add_edge(b, f)
G.add_edge(b, c)
G.add_edge(e, f)
G.add_edge(f, g)
G.add_edge(g, f)
G.add_edge(c, g)
G.add_edge(c, d)
G.add_edge(d, c)
G.add_edge(d, h)
G.add_edge(g, h)
G.add_edge(h, h)
groups = scc(G)
print(groups)