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#!/usr/bin/env python3 | |
import argparse | |
import matplotlib as mpl | |
mpl.use('Agg') | |
import matplotlib.pyplot as plt | |
plt.style.use('bmh') | |
import numpy as np | |
import pandas as pd | |
import math | |
from matplotlib import rcParams | |
rcParams.update({'figure.autolayout': True}) | |
import os | |
import sys | |
import json | |
import glob | |
def main(): | |
parser = argparse.ArgumentParser() | |
parser.add_argument('--out', type=str, default='images/qpth-timing') | |
args = parser.parse_args() | |
# msesF = os.path.join(args.workDir, 'mses.csv') | |
# msesDf = pd.read_csv(msesF, sep=',', names=['lam', 'mse']) | |
# fig, ax = plt.subplots(1, 1, figsize=(5,3)) | |
# # fig.tight_layout() | |
# plt.plot(msesDf['lam'].values, msesDf['mse'].values) | |
# plt.xlabel("$\lambda$") | |
# plt.ylabel("MSE") | |
# ax.set_yscale('log') | |
# for ext in ['pdf', 'png']: | |
# f = args.out + '.' + ext | |
# fig.savefig(f) | |
# if ext == 'pdf': | |
# os.system('pdfcrop "{}" "{}"'.format(f, f)) | |
# print("Created {}".format(f)) | |
batchSzs = [1, 64, 128] | |
gurobiMeans = [3.60602e-02, 2.33186e+00, 4.66950e+00] | |
gurobiStds = [3.86304e-03, 2.29599e-02, 2.93522e-02] | |
singleMeans = [7.75610e-02, 3.30584e+00, 6.64419e+00] | |
singleStds = [2.73885e-02, 7.14157e-02, 6.35851e-02] | |
batchedMeans = [6.98230e-02, 1.45570e-01, 1.83456e-01] | |
batchedStds = [6.51156e-03, 2.80604e-03, 2.77888e-03] | |
nSamples = len(gurobiMeans) | |
indices = np.array(list(range(nSamples))) | |
barWidth = 0.2 | |
cmap = plt.get_cmap("Set1") | |
colors = cmap(np.linspace(0, 1, 9)) | |
alpha = 0.7 | |
# fig = plt.figure(figsize=(10, 4)) | |
# ax = fig.add_subplot(111) | |
fig, ax = plt.subplots(1, 1, figsize=(5,3)) | |
plt.bar(indices, gurobiMeans, barWidth, | |
yerr=gurobiStds, label='Gurobi', | |
color=colors[0], ecolor='0.3', alpha=alpha) | |
plt.bar(indices + barWidth, singleMeans, barWidth, | |
yerr=singleStds, label='qpth (Single)', | |
color=colors[1], ecolor='0.3', alpha=alpha) | |
plt.bar(indices + 2 * barWidth, batchedMeans, barWidth, | |
yerr=batchedStds, label='qpth (Batched)', | |
color=colors[2], ecolor='0.3', alpha=alpha) | |
# box = ax.get_position() | |
# ax.set_position([box.x0, box.y0 + 0.05, box.width, box.height * 0.85]) | |
# plt.legend(loc='upper center', bbox_to_anchor=(0.5, 1.25), ncol=4, | |
# fancybox=True, shadow=True) | |
plt.ylabel("Runtime (s)") | |
plt.xlabel("Batch Size") | |
ax.set_xticks(indices + 1.5 * barWidth) | |
xticks = [] | |
for batchSz in batchSzs: | |
xticks.append(batchSz) | |
ax.set_xticklabels(xticks) | |
ax.set_yscale('log') | |
# locs, labels = plt.xticks() | |
# plt.ylim(0, 1) | |
for ext in ['pdf', 'png']: | |
f = args.out + '.' + ext | |
fig.savefig(f) | |
if ext == 'pdf': | |
os.system('pdfcrop "{}" "{}"'.format(f, f)) | |
print("Created {}".format(f)) | |
if __name__ == '__main__': | |
main() |
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