def returnsingle():
source = request.GET.get('source')
sink = request.GET.get('sink')
rank = request.GET.get('rank')
# Load the graph
G = DiGraph("net5")
# Get the painting object and set its properties.
paint = G.painter()
paint.set_source_sink(source, sink)
# Generate the graph using the painter we configured.
G.export(False, paint)
i=int(rank)
iRank = i
# Get shortest paths from the graph.
items = algorithms.ksp_yen(G, source, sink, i)
for path in items:
sCost = path['cost']
sPath = ", ".join(path['path'])
response.content_type='application/json'
response.headers['Access-Control-Allow-Origin']='*'
bus_Stop, bus_No, stop_Name, route_Id = result.busChanger(source,sink,iRank)
if i==1:
return { "BusStop": bus_Stop, "BusNo": bus_No, "StopName": stop_Name, "RouteNo ": route_Id}
else:
i=i-1
continue
def main():
# Load the graph
G = DiGraph("net5")
# Get the painting object and set its properties.
paint = G.painter()
paint.set_source_sink("C", "H")
paint.set_rank_same(['C', 'D', 'F'])
paint.set_rank_same(['E', 'G', 'H'])
# Generate the graph using the painter we configured.
G.export(False, paint)
# Get 30 shortest paths from the graph.
items = algorithms.ksp_yen(G, "C", "H", 30)
for path in items:
print "Cost:%s\t%s" % (path['cost'], "->".join(path['path']))
return 0
def main():
# Load the graph
G = DiGraph("net5")
# Get the painting object and set its properties.
paint = G.painter()
paint.set_source_sink("C", "H")
paint.set_rank_same(['C', 'D', 'F'])
paint.set_rank_same(['E', 'G', 'H'])
# Generate the graph using the painter we configured.
G.export(False, paint)
# Get 30 shortest paths from the graph.
items = algorithms.ksp_yen(G, "C", "H", 30)
for path in items:
print "Cost:%s\t%s" % (path['cost'], "->".join(path['path']))
return 0
from graph import DiGraph
import algorithms
source = "s175"
sink = "s555"
rank = "13"
# Load the graph
G = DiGraph("net5")
# Get the painting object and set its properties.
paint = G.painter()
paint.set_source_sink(source, sink)
# Generate the graph using the painter we configured.
G.export(False, paint)
i=int(rank)
iRank = i
# Get shortest paths from the graph.
items = algorithms.ksp_yen(G, source, sink, i)
print(items)
#for path in items:
# sCost = path['cost']
# sPath = ", ".join(path['path'])
# response.content_type='application/json'
# if i==1:
# return { "Cost": sCost, "Path": sPath, "BusChange": result.busChanger(source,sink,iRank) }
# else:
# i=i-1
# continue
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
