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#!/usr/bin/python
"""
Copyright (C) 2000, 2001, 2002 RiskMap srl
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it and/or modify it under the
terms of the QuantLib license. You should have received a copy of the
license along with this program; if not, please email ferdinando@ametrano.net
The license is also available online at http://quantlib.org/html/license.html
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the license for more details.
"""
__version__ = "$Revision: 1.12 $"
# $Source: /cvsroot/quantlib/QuantLib-Python/QuantLib/test/statistics.py,v $
import QuantLib
import unittest
class StatisticsTest(unittest.TestCase):
def runTest(self):
"Testing statistics"
tol = 1e-9
data = [ 3, 4, 5, 2, 3, 4, 5, 6, 4, 7]
weights = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
s = QuantLib.Statistics()
s.addWeightedSequence(data, weights)
samples = s.samples()
N = len(data)
if not (samples == N):
self.fail("""
wrong number of samples
calculated: %(samples)d
expected : %(N)d
""" % locals())
weightSum = s.weightSum()
rightWeightSum = reduce(lambda x,y:x+y, weights)
if not (weightSum == rightWeightSum):
self.fail("""
wrong sum of weights\n' + \
calculated: %(weightSum)f
expected : %(rightWeightSum)f
""" % locals())
minDatum = s.min()
maxDatum = s.max()
rightMin = min(data)
rightMax = max(data)
if not (minDatum == rightMin):
self.fail("""
wrong minimum value
calculated: %(minDatum)f
expected : %(rightMin)f
""" % locals())
if not (maxDatum == rightMax):
self.fail("""
wrong maximum value
calculated: %(maxDatum)f
expected : %(rightMax)f
""" % locals())
mean = s.mean()
rightMean = reduce(lambda x,y:x+y, map(lambda x,y:x*y, data, weights)) \
/ reduce(lambda x,y:x+y, weights)
if not (abs(mean-rightMean) <= tol):
self.fail("""
wrong mean value\n' + \
calculated: %(mean)f
expected : %(rightMean)f
""" % locals())
variance = s.variance()
if not (abs(variance-2.23333333333) <= tol):
self.fail("""
wrong variance
calculated: %(variance)f
expected : 2.23333333333
""" % locals())
stdDev = s.standardDeviation()
if not (abs(stdDev-1.4944341181) <= tol):
self.fail("""
wrong standard deviation
calculated: %(stdDev)f
expected : 1.4944341181
""" % locals())
skewness = s.skewness()
if not (abs(skewness-0.359543071407) <= tol):
self.fail("""
wrong skewness
calculated: %(skewness)f
expected : 0.359543071407
""" % locals())
kurtosis = s.kurtosis()
if not (abs(kurtosis+0.151799637209) <= tol):
self.fail("""
wrong kurtosis
calculated: %(kurtosis)f
expected : -0.151799637209
""" % locals())
s.reset()
data = map(lambda x: x-3,data)
s.addWeightedSequence(data, weights)
downDev = s.downsideDeviation()
if not (abs(downDev-0.333333333) <= tol):
self.fail("""
wrong down side deviation
calculated: %(downDev)f
expected : 0.333333333
""" % locals())
if __name__ == '__main__':
print 'testing QuantLib', QuantLib.__version__, QuantLib.QuantLibc.__file__, QuantLib.__file__
import sys
suite = unittest.TestSuite()
suite.addTest(StatisticsTest())
if sys.hexversion >= 0x020100f0:
unittest.TextTestRunner(verbosity=2).run(suite)
else:
unittest.TextTestRunner().run(suite)
raw_input('press any key to continue')
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