""" Run it like:
$ python benchmark.py < inputs/BR.txt
"""
from timeit import timeit
from graph import Graph
from dijkstra import dijkstra
from dijkstra_h import dijkstra_h
G = Graph()
G.build_graph()
s = 2646
print timeit(lambda: dijkstra(G, s), number=1)
print timeit(lambda: dijkstra_h(G, s), number=1)
# output for BR.txt
#2.55977678299
#0.0487070083618
# output for map.txt
#0.00156283378601
#0.000765800476074
from graph import Graph
from kruskal import kruskal
from dijkstra_h import path, dijkstra_h
G = Graph()
G.build_graph()
# minimmum spanning tree
mst = kruskal(G)
length = sum([edge.weight for edge in mst])
print length
# shortest path from city s to f
s = 93
f = 112
d, p = dijkstra_h(G, s)
print d[f]
# shortest path tree from city s
s = 104
d, p = dijkstra_h(G, s)
edges = []
for v in G.vertices():
edges += path(p, s, v)
edges = set(edges)
cost = 0
for a, b in edges:
cost += G.weight(a, b)
print cost
""" Run it like:
$ python benchmark.py < inputs/BR.txt
"""
from timeit import timeit
from graph import Graph
from dijkstra import dijkstra
from dijkstra_h import dijkstra_h
G = Graph()
G.build_graph()
s = 2646
print timeit(lambda : dijkstra(G, s), number=1)
print timeit(lambda : dijkstra_h(G, s), number=1)
# output for BR.txt
#2.55977678299
#0.0487070083618
# output for map.txt
#0.00156283378601
#0.000765800476074
from dijkstra_h import path, dijkstra_h
G = Graph()
G.build_graph()
# minimmum spanning tree
mst = kruskal(G)
length = sum([edge.weight for edge in mst])
print length
# shortest path from city s to f
s = 93; f = 112
d, p = dijkstra_h(G, s)
print d[f]
# shortest path tree from city s
s = 104
d, p = dijkstra_h(G, s)
edges = []
for v in G.vertices():
edges += path(p, s, v)
edges = set(edges)
cost = 0
for a, b in edges:
cost += G.weight(a, b)
print cost
