def filter(self, csv_in, csv_out, max_dist):
print('filtering graph for maximum distance: %s' % max_dist)
g = graph.read_graph(csv_in)
for edge in g:
loc1 = self.locmap.coords[edge[0]]
loc2 = self.locmap.coords[edge[1]]
dist = geo.distance(loc1, loc2)
if dist > max_dist:
g[edge] = 0.
graph.write_graph(g, csv_out)
def crop(self, csv_in, csv_out, min_lat, min_lng, max_lat, max_lng):
print('cropping graph for rectangle: %s %s %s %s' %
(min_lat, min_lng, max_lat, max_lng))
g = graph.read_graph(csv_in)
new_g = {}
for edge in g:
loc1 = self.locmap.coords[edge[0]]
loc2 = self.locmap.coords[edge[1]]
if geo.in_area(loc1, min_lat, min_lng, max_lat, max_lng)\
and geo.in_area(loc2, min_lat, min_lng, max_lat, max_lng):
new_g[edge] = g[edge]
graph.write_graph(new_g, csv_out)
def graphinfo(csv_in):
g = graph.read_graph(csv_in)
print('edges: %s' % (len(g),))
degs = graph.degrees(g)
print('nodes: %s' % (len(degs),))
total = 0.
max_deg = -1.
min_deg = float("inf")
for node in degs:
deg = degs[node]
total += deg
if deg > max_deg:
max_deg = deg
if deg < min_deg:
min_deg = deg
print('degress: min: %s; max: %s, mean: %s' % (min_deg, max_deg, total / len(degs)))
def graphinfo(csv_in):
g = graph.read_graph(csv_in)
print('edges: %s' % (len(g), ))
degs = graph.degrees(g)
print('nodes: %s' % (len(degs), ))
total = 0.
max_deg = -1.
min_deg = float("inf")
for node in degs:
deg = degs[node]
total += deg
if deg > max_deg:
max_deg = deg
if deg < min_deg:
min_deg = deg
print('degress: min: %s; max: %s, mean: %s' %
(min_deg, max_deg, total / len(degs)))
def compute(self, infile, outfile):
g = graph.read_graph(infile)
f = open(outfile, 'w')
total_distance = 0.
count = 0.
for edge in g:
loc1 = self.locmap.coords[edge[0]]
loc2 = self.locmap.coords[edge[1]]
weight = g[edge]
dist = geo.distance(loc1, loc2)
for i in range(weight):
f.write('%s\n' % dist)
total_distance += dist
count += 1.
f.close()
mean_distance = total_distance / count
print('mean distance: %s' % mean_distance)
def compute(self, infile, outfile):
g = graph.read_graph(infile)
f = open(outfile, "w")
total_distance = 0.0
count = 0.0
for edge in g:
loc1 = self.locmap.coords[edge[0]]
loc2 = self.locmap.coords[edge[1]]
weight = g[edge]
dist = geo.distance(loc1, loc2)
for i in range(weight):
f.write("%s\n" % dist)
total_distance += dist
count += 1.0
f.close()
mean_distance = total_distance / count
print("mean distance: %s" % mean_distance)
