performance.py
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	#!/usr/bin/python

	import os
	import numpy as np
	from numpy import array

	testdir = "tests"
	os.system("mkdir -p " + testdir)

	Ntr = [1, 2, 4, 8, 16]
	#sample = "Running the algorithm with 4 threads on 10000 by 10000 array for 5 iterations took 1.547 seconds"

	def loadtimes(fstream):
	t = []
	for line in fstream:
	# skip if no information is contained
	if not line.startswith("Running the algorithm"):
	continue

	values = line.split(' ') # split into string set
	values = [i for i in values if i != ''] # fliter null strings
	t.append(float(values[15])) # 16-th value should contain the elapsed time
	return t

	T = [] # times
	for filename in os.listdir(os.getcwd() + '/' + testdir):
	with open(os.path.join(os.getcwd() + '/' + testdir, filename), 'r') as f:
	t = np.array(loadtimes(f))
	T.append(t)

	Tmean = np.mean(T, axis=0).tolist()
	Tsq = np.sqrt(np.var(T, axis=0)).tolist() # compute mean and variance of arrays

	# output values
	out = open("times.txt", 'w')
	print("ntr t dt", file=out)
	for (ntr, t, dt) in zip(Ntr, Tmean, Tsq):
	print("%d %.3g %.3g" % (ntr, t, dt), file=out)
	out.close()