memgraph/tests/qa/plot_latency
2017-06-20 15:01:11 +02:00

79 lines
2.5 KiB
Python
Executable File

#!/usr/bin/env python3
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import json
from argparse import ArgumentParser
"""
Plots graph of latencies of memgraph and neo4j. Takes paths to
json of latencies as arguments.
"""
def main():
argp = ArgumentParser(description=__doc__)
argp.add_argument('--memgraph-latency',
help='Path to the json of memgraph latency')
argp.add_argument('--neo4j-latency',
help='Path to the json of neo4j latency')
args = argp.parse_args()
fig = plt.gcf()
fig.set_size_inches(10, 16)
with open(args.neo4j_latency) as json_file:
json_neo = json.load(json_file)
with open(args.memgraph_latency) as json_file:
json_mem = json.load(json_file)
tests_num = 0
time_list_neo = []
time_list_mem = []
max_time = 0
for key in json_mem['data']:
if json_neo['data'][key]['status'] == "passed" and \
json_mem['data'][key]['status'] == 'passed':
time_neo = json_neo['data'][key]['execution_time']
time_mem = json_mem['data'][key]['execution_time']
max_time = max(max_time, time_neo, time_mem)
offset = 0.01 * max_time
for key in json_mem['data']:
if json_neo['data'][key]['status'] == "passed" and \
json_mem['data'][key]['status'] == 'passed':
time_neo = json_neo['data'][key]['execution_time']
time_mem = json_mem['data'][key]['execution_time']
time_list_neo.append(time_neo)
time_list_mem.append(time_mem)
tests_num += 1
if time_neo < time_mem:
plt.plot((time_mem, time_neo), (tests_num, tests_num), color='red',
label=key, lw=0.3)
else:
plt.plot((time_mem, time_neo), (tests_num, tests_num), color='green',
label=key, lw=0.3)
ratio = '%.2f' % (max(time_neo, time_mem) / min(time_neo, time_mem))
plt.text(max(time_mem, time_neo) + offset, tests_num, key + " ---> " + \
ratio + "x", size=1)
x = range(1, tests_num + 1)
plt.plot(time_list_mem, x, marker='o', markerfacecolor='orange', color='orange',
linestyle='', markersize=0.5)
plt.plot(time_list_neo, x, marker='o', markerfacecolor='blue', color='blue',
linestyle='', markersize=0.5)
plt.margins(0.1, 0.01)
plt.savefig("latency_graph.png", dpi=2000)
if __name__ == '__main__':
main()