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import matplotlib.pyplot as plt
import numpy as np
import csv
import sys
import re
def load_data(filename):
data = {}
with open(filename) as f:
line = f.readline()
while line:
line = re.sub('\s+', ' ', line.strip()).split(" ")
if "transactions:" in line:
data["transactions"] = float(line[2].replace("(", ""))
if "queries:" in line:
data["queries"] = float(line[2].replace("(", ""))
if "avg:" in line:
data["latency(ms)"] = float(line[1])
line = f.readline()
return data
BAR_WIDTH=0.25
labels=['transactions', 'queries', 'latency(ms)']
data_num = len(sys.argv)-2
factor = (data_num+1) * BAR_WIDTH
datas = []
for i in range(0, data_num):
filename = sys.argv[1+i]
data = load_data(filename)
datas.append(data)
fig = plt.figure()
ax1 = fig.add_subplot()
ax1.set_ylabel("Operations / second")
ax2 = ax1.twinx()
ax2.set_ylabel("Average latency (ms)")
for i in range(0, data_num):
filename = sys.argv[1+i]
ax1.bar([BAR_WIDTH*i, factor+BAR_WIDTH*i], [datas[i][labels[0]], datas[i][labels[1]]], align="edge", edgecolor="black", linewidth=1, width=BAR_WIDTH, label=filename)
for i in range(0, data_num):
filename = sys.argv[1+i]
ax2.bar([factor*2+BAR_WIDTH*i], datas[i][labels[2]], align="edge", edgecolor="black", linewidth=1, width=BAR_WIDTH, label=filename)
h1, l1 = ax1.get_legend_handles_labels()
ax1.legend(h1, l1, loc="upper left")
plt.xlim(0, (len(labels)-1)*factor+BAR_WIDTH*data_num)
plt.xticks([x*factor+BAR_WIDTH*data_num/2 for x in range(0, len(labels))], labels)
plt.savefig(sys.argv[1+data_num])
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