Commit 489ee9e4 authored by Francois Hamonic's avatar Francois Hamonic
Browse files

whiskers plot

parent cae52ce0
import matplotlib.pyplot as plt
import csv
import pylab
def readCSV(file_name, delimiter=' '):
file = csv.DictReader(open(file_name), delimiter=delimiter)
return list([row for row in file])
rows = readCSV('output/contraction_benefits.csv', ",")
x_datas = range(0,105,5)
x_datas = range(0, 105, 5)
def get_datas(t, percent):
return [100*(1-float(row["nb_{}_contract".format(t)])/float(row["nb_{}".format(t)])) for row in rows if int(row["percent_arcs"]) == percent]
datas = [
# get_datas("constraints", p)
get_datas("vars", p)
# get_datas("elems", p)
for p in x_datas
]
fig_size = plt.rcParams["figure.figsize"]
fig_size[0] = 10
fig_size[1] = 5
plt.rcParams["figure.figsize"] = fig_size
plt.subplots_adjust(left=0.125, right=0.95, top=0.92, bottom=0.13)
plt.rcParams.update({'font.size': 16})
ymin = 0
ymax = 100
yrange = ymax - ymin
y_border_percent = 7.5
y_bottom = ymin - y_border_percent * yrange / 100
y_top = ymax + y_border_percent * yrange / 100
plt.ylim(y_bottom, y_top)
vars_datas = [
get_datas("vars", p) for p in x_datas
]
constr_datas = [
get_datas("constraints", p) for p in x_datas
]
elems_datas = [
get_datas("elems", p) for p in x_datas
]
# plt.title("quebec-{}-{}-ECA value vs available budget.pdf".format(orig, median))
plt.ylabel('percentage of elements\nremoved by the preprocessing', rotation=90, fontweight ='bold')
plt.xlabel("percentage of restored arcs", fontweight ='bold')
plt.rcParams["figure.figsize"] = (10, 8)
plt.rcParams["font.size"] = 13.75
fig, axs = plt.subplots(3)
for i in [0, 1, 2]:
# axs[i].axhline(y=75, color='lightblue', linestyle='--')
# axs[i].axhline(y=50, color='dodgerblue', linestyle='--')
# axs[i].axhline(y=25, color='lightblue', linestyle='--')
axs[i].axhline(y=20, color='lightblue', linestyle='--')
axs[i].axhline(y=40, color='lightblue', linestyle='--')
axs[i].axhline(y=60, color='lightblue', linestyle='--')
axs[i].axhline(y=80, color='lightblue', linestyle='--')
bplot1 = axs[0].boxplot(vars_datas, showfliers=False, patch_artist=True)
axs[0].set(xlabel=None, ylabel='removed variables')
axs[0].set_xticklabels([])
bplot2 = axs[1].boxplot(constr_datas, showfliers=False, patch_artist=True)
axs[1].set(xlabel=None, ylabel='removed constraints')
axs[1].set_xticklabels([])
bplot3 = axs[2].boxplot(elems_datas, showfliers=False, patch_artist=True)
axs[2].set(xlabel="percentage of improvable arcs", ylabel='removed entries')
axs[2].set_xticklabels([x if x % 10 == 0 else "" for x in x_datas])
for bplot in (bplot1, bplot2, bplot3):
for patch in bplot['boxes']:
patch.set_facecolor('white')
plt.boxplot(datas, showfliers=False)
pylab.xticks(range(1, 1+len(datas)), x_datas)
# legend = plt.legend(loc='lower right', shadow=True, fontsize='medium')
plt.tight_layout()
fig.subplots_adjust(hspace=0.08)
plt.savefig("output/contraction_benefits_whiskers.pdf", dpi=500)
plt.show()
plt.savefig("output/contraction_benefits_whiskers.pdf", dpi=500)
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