def betweenness_test(name):
if os.path.isfile(DATA_PATH + name + ".between"):
print "Skipping", name
return
start = time.time()
G, coords = osmParser.simpleLoadFromFile(name)
print "Calculating betweenness", name
nodeToBetweenness = snap.TIntFltH()
edgeToBetweenness = snap.TIntPrFltH()
snap.GetBetweennessCentr(G, nodeToBetweenness, edgeToBetweenness, 0.25)
betweenness = {}
for node in nodeToBetweenness:
betweenness[node] = nodeToBetweenness[node]
betweenOut = open(DATA_PATH + name + ".between", 'w')
pickle.dump(betweenness, betweenOut, 1)
plotTopK(name, betweenness, coords, "GnBu")
end = time.time()
print "took", end - start, "seconds"
def approx_closeness_test(name):
if os.path.isfile(DATA_PATH + name + ".acloseness"):
print "Skipping", name
return
start = time.time()
G, coords = osmParser.simpleLoadFromFile(name)
print "Calculating approx closeness", name
closeness = weightedBetween.approxCloseness(G, coords)
closeOut = open(DATA_PATH + name + ".acloseness", 'w')
pickle.dump(closeness, closeOut, 1)
plotTopK(name, closeness, coords, "PuBu")
end = time.time()
print "took", end - start, "seconds"
def urbanness_test(name):
if os.path.isfile(DATA_PATH + name + ".urban"):
print "Skipping", name
return
start = time.time()
G, coords = osmParser.simpleLoadFromFile(name)
print "Calculating urbanness", name
urbanness = weightedBetween.urbanness(G, coords)
urbanOut = open(DATA_PATH + name + ".urban", 'w')
pickle.dump(urbanness, urbanOut, 1)
plotTopK(name, urbanness, coords, "BuPu")
end = time.time()
print "took", end - start, "seconds"
def weighted_closeness_test(name):
if os.path.isfile(DATA_PATH + name + ".wcloseness"):
print "Skipping", name
return
start = time.time()
G, coords = osmParser.simpleLoadFromFile(name)
print "Calculating weighted closeness", name
nodeToCloseness = weightedBetween.closenessCentrality(G, coords)
closeOut = open(DATA_PATH + name + ".wcloseness", 'w')
pickle.dump(nodeToCloseness, closeOut, 1)
plotTopK(name, nodeToCloseness, coords, "GnBu")
end = time.time()
print "took", end - start, "seconds"
def __init__(self, name):
graph, self.nid_to_coords = osmParser.simpleLoadFromFile(name)
# For getting a new node id to set an edge to.
self.NID_GENERATOR = 0
# An integer representing the baseline # of time steps it takes to cross this street. Each indiv. car's time
# may vary by a factor of 0.75 to 1.25.
self.street_weights = {}
# The average coordinates for each street (node). Average the lon lat of this street's endpoints.
# Used for heuristics in A* search.
self.street_coordinates = {}
# Keep track of which edges in the snap_graph are which nodes in the dual graph. Discarded after initialization.
self._names = {}
# An instance of PUNGraph from snap.
self.graph = self._create_dual_representation(graph)
def plotStat(name, stat):
if not os.path.isfile(DATA_PATH + name + "." + stat):
print "Skipping", name
return
if stat == "tsd":
print "Plotting TSD for", name
plotTSD(name)
return
G, coords = osmParser.simpleLoadFromFile(name)
infoIn = open(DATA_PATH + name + "." + stat, 'r')
data = pickle.load(infoIn)
color = ""
if stat == "between":
color = "RdPu"
elif stat == "wbetween":
color = "OrRd"
elif stat == "closeness":
color = "YlGnBu"
elif stat == "wcloseness":
color = "GnBu"
elif stat == "acloseness":
color = "PuBu"
elif stat == "urbanness":
color = "BuPu"
else:
print "Invalid stat name, exiting"
return
if stat == "wbetween":
plotTopK(name, data, coords, color, useNodeBetween=False)
else:
plotTopK(name, data, coords, color)
def plotCity(name):
G, coordsMap = osmParser.simpleLoadFromFile(name)
x = []
y = []
for edge in G.Edges():
start = edge.GetSrcNId()
end = edge.GetDstNId()
coords1 = coordsMap[start]
coords2 = coordsMap[end]
x.append(coords1[0])
x.append(coords2[0])
x.append(None)
y.append(coords1[1])
y.append(coords2[1])
y.append(None)
plt.plot(y, x, 'k', linewidth=0.5)
plt.xlabel("longitude")
plt.ylabel("latitude")
plt.axis('image')
def closeness_test(name):
if os.path.isfile(DATA_PATH + name + ".closeness"):
print "Skipping", name
return
start = time.time()
G, coords = osmParser.simpleLoadFromFile(name)
print "Calculating closeness", name
##
nodeToCloseness = {}
for node in G.Nodes():
nodeToCloseness[node.GetId()] = snap.GetClosenessCentr(G, node.GetId())
##
closeOut = open(DATA_PATH + name + ".closeness", 'w')
pickle.dump(nodeToCloseness, closeOut, 1)
plotTopK(name, nodeToCloseness, coords, "YlGnBu")
end = time.time()
print "took", end - start, "seconds"
def analyzeCity(city):
graph, nodesMap = osmParser.simpleLoadFromFile(city)
return algorithm2(graph, nodesMap), nodesMap