def compare_capacities(paras, rep="", save_to_csv=True):
"""
Compare new and old definition of capacities.
"""
G = paras["G"]
paras_real = G.paras_real
capacities_new = extract_capacity_from_traffic(G, paras_real)
capacities_old = extract_old_capacity_from_traffic(G, paras_real)
with open("/home/earendil/Documents/ELSA/Modules/All_areas_volumes_" + str(paras_real["airac"]) + ".pic", "r") as f:
real_areas, volumes = pickle.load(f)
sectors = sorted(capacities_new.keys())
capacities_new, capacities_old, areas, volumes = (
[capacities_new[v] for v in sectors],
[capacities_old[v] for v in sectors],
[real_areas[G.node[v]["name"]] for v in sectors],
[volumes[G.node[v]["name"]] for v in sectors],
)
if save_to_csv:
for met, met_name in [
(capacities_new, "cap_new"),
(capacities_old, "cap_old"),
(areas, "areas"),
(volumes, "vol"),
]:
with open(rep + "/" + met_name + "_dist.csv", "wb") as csvfile:
writer = csv.writer(csvfile, delimiter=";")
writer.writerow([met_name])
for d in met:
writer.writerow([d])
os.system("mkdir -p " + rep)
plot_scatter(
capacities_old, capacities_new, rep=rep, suffix="capacities", xlabel="Old capacities", ylabel="New capacities"
)
plot_scatter(areas, capacities_new, rep=rep, suffix="area_new_capacities", xlabel="area", ylabel="New capacities")
plot_quantiles(
capacities_old, capacities_new, rep=rep, suffix="capacities", xlabel="Old capacities", ylabel="New capacities"
)
plot_quantiles(areas, capacities_new, rep=rep, suffix="area_new_capacities", xlabel="area", ylabel="New capacities")
plot_hist(capacities_new, rep=rep, suffix="capacities_new", xlabel="capacities_new")
def compute_basic_stats(paras, rep="", save_to_csv=False):
"""
Simple statistics.
Beware! Here the weights are not given by the traffic. They are the time of crossing!
"""
G = paras["G"].G_nav
os.system("mkdir -p " + rep)
print "Number of nodes, number of edges:", len(G.nodes()), len(G.edges())
# ----- Distribution of degree ----- #
deg = [G.degree(n) for n in G.nodes()]
bins = max(deg) - min(deg)
if save_to_csv:
with open(rep + "/deg_dist.csv", "wb") as csvfile:
writer = csv.writer(csvfile, delimiter=";")
writer.writerow(["Degree"])
for d in deg:
writer.writerow([d])
print ""
print "Min/Mean/Std/Max degree:", min(deg), np.mean(deg), np.std(deg), max(deg)
plot_hist(deg, xlabel="Degree", title="Distribution of degree", bins=bins, rep=rep, suffix="deg")
# ----- Distribution of strength ----- #
strr = [G.degree(n, weight="weight") for n in G.nodes()]
bins = max(strr) - min(strr)
if save_to_csv:
with open(rep + "/str_dist.csv", "wb") as csvfile:
writer = csv.writer(csvfile, delimiter=";")
writer.writerow(["Strength"])
for s in strr:
writer.writerow([s])
print ""
print "Min/Mean/Std/Max stregth:", min(strr), np.mean(strr), np.std(strr), max(strr)
plot_hist(strr, xlabel="Strength", title="Distribution of strength", bins=bins, rep=rep, suffix="str")
# ----- Distribution of weights ----- #
wei = [G[e[0]][e[1]]["weight"] for e in G.edges()]
bins = 30
if save_to_csv:
with open(rep + "/wei_dist.csv", "wb") as csvfile:
writer = csv.writer(csvfile, delimiter=";")
writer.writerow(["Weights"])
for w in wei:
writer.writerow([w])
print ""
print "Min/Mean/Std/Max weight:", min(wei), np.mean(wei), np.std(wei), max(wei)
print "Total weight:", sum(wei)
plot_hist(wei, xlabel="Time of travel between navpoints", title="", bins=bins, rep=rep, suffix="wei")