def get_suitability_graph_from_session(request):
graph = request.session['graph']
suitability_graph = SuitabilityGraph()
for node_id, (node_weight, adj_dict, data) in graph.iteritems():
new_adj_dict = {int(neighbour): edge_cost for neighbour, edge_cost in adj_dict.iteritems()}
suitability_graph[int(node_id)] = (node_weight, new_adj_dict, data)
dist = {}
for k, v in request.session['dist'].iteritems():
k_ = k.split(",")
dist[(long(k_[0]), long(k_[1]))] = v
suitability_graph.dist = dist
pairs = set()
for k in request.session['pairs_dist_paths']:
k_ = k.split(",")
pairs.add((long(k_[0]), long(k_[1])))
suitability_graph.pairs_dist_paths = pairs
return suitability_graph
suitability_graph.compute_dist_paths(origins=hotspots,
destinations=hotspots,
compute_paths=False)
print "compute", time.clock() - start_time, "# hotspots:", len(
hotspots)
for num_seats in capacity:
# suitability_graph.extend_suitable_regions(seed, generator)
# hotspots = suitability_graph.get_suitable_nodes(generator)
# print i, "# hotspots:", len(hotspots)
for num_terminals in nums_terminals:
new_terminals = set()
for sample in range(num_samples):
graph_temp = SuitabilityGraph()
graph_temp.append_graph(suitability_graph)
graph_temp.dist = dict(suitability_graph.dist)
graph_temp.pairs_dist_paths = set(
suitability_graph.pairs_dist_paths)
graph_temp.method_dist_paths = suitability_graph.method_dist_paths
print("sample:", sample)
terminals = np.random.choice(a=ms[msns] * ns[msns],
size=num_terminals +
max(nums_pois),
replace=False)
# while len(set(hotspots).intersection(terminals)) != 0:
# terminals = np.random.choice(a=size * size, size=num_terminals + max(nums_pois), replace=False)
temp = set(hotspots)
temp.update(terminals)
start_time = time.clock()
graph_temp.update_dist_paths(temp, compute_paths=False)
print "update", time.clock() - start_time