BSB/plot3.py at main · inet-tub/BSB · GitHub

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import matplotlib.pyplot as plt
import numpy as np


def percentage(base, cost):
    return [a/b for a, b in zip(cost, base)]


fig = plt.figure()
ax = fig.add_subplot()

datasets_list = ['Facebook', 'Microsoft', 'pFabric', 'ProjecToR']

global_view_shortest_path_routing = [172, 571, 1848, 2536]
global_view_local_routing = [201, 663, 2030, 3220]
local_view_shortest_path_routing = [189, 580, 2142, 2691]
local_view_local_routing = [219, 677, 2233, 3245]

total_width, n_algos = 0.6, 4
width = total_width / n_algos

x_1 = list(range(len(datasets_list)))
x_2 = [pos + width for pos in x_1]
x_3 = [pos + 2 * width for pos in x_1]
x_4 = [pos + 3 * width for pos in x_1]

ax.bar(x_1, percentage(local_view_local_routing, global_view_shortest_path_routing), width=width, label='1 : global view & shortest path routing', color='#FFCC9D')
ax.bar(x_2, percentage(local_view_local_routing, global_view_local_routing), width=width, label='2 : global view & local routing', color='#F0A389')
ax.bar(x_3, percentage(local_view_local_routing, local_view_shortest_path_routing), width=width, label='3 : local view & shortest path routing', color='#B3BA99')
ax.bar(x_4, percentage(local_view_local_routing, local_view_local_routing), width=width, label='4 : local view & local routing', color='#8994BD')

ax.set_xticks([pos+total_width/2-width/2 for pos in x_1], datasets_list)
ax.set_ylim([0.6, 1.1])
ax.set_yticks([0.2 * i for i in range(3, 6)])
ax.set_xlabel('datasets')
ax.set_ylabel('Cost ratio to "local view & local routing"')
ax.set_title('Communication costs on optimal network structure')

plt.legend(fontsize=6)
plt.savefig('/Users/qingyun/Desktop/master thesis drawing/ILP.pdf')
plt.show()