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unison/src/stats/test/basic-data-calculators-test-suite.cc
2013-05-15 17:18:23 -04:00

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C++

/* -*- Mode:C++; c-file-style:"gnu"; indent-tabs-mode:nil; -*- */
/*
* Copyright (c) 2011 University of Washington
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License version 2 as
* published by the Free Software Foundation;
*
* 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
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*
* Author: Mitch Watrous (watrous@u.washington.edu)
*/
#include <cmath>
#include "ns3/test.h"
#include "ns3/basic-data-calculators.h"
using namespace ns3;
const double TOLERANCE = 1e-14;
// ===========================================================================
// Test case for a single integer.
// ===========================================================================
class OneIntegerTestCase : public TestCase
{
public:
OneIntegerTestCase ();
virtual ~OneIntegerTestCase ();
private:
virtual void DoRun (void);
};
OneIntegerTestCase::OneIntegerTestCase ()
: TestCase ("Basic Statistical Functions using One Integer")
{
}
OneIntegerTestCase::~OneIntegerTestCase ()
{
}
void
OneIntegerTestCase::DoRun (void)
{
MinMaxAvgTotalCalculator<int> calculator;
long count = 1;
double sum = 0;
double sqrSum = 0;
double min;
double max;
double mean;
double stddev;
double variance;
// Put all of the values into the calculator.
int multiple = 5;
int value;
for (long i = 0; i < count; i++)
{
value = multiple * (i + 1);
calculator.Update (value);
sum += value;
sqrSum += value * value;
}
// Calculate the expected values for the statistical functions.
min = multiple;
max = multiple * count;
mean = sum / count;
variance = 0;
stddev = std::sqrt (variance);
// Test the calculator.
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getCount(), count, TOLERANCE, "Count value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getSum(), sum, TOLERANCE, "Sum value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMin(), min, TOLERANCE, "Min value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMax(), max, TOLERANCE, "Max value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMean(), mean, TOLERANCE, "Mean value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getStddev(), stddev, TOLERANCE, "Stddev value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getVariance(), variance, TOLERANCE, "Variance value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getSqrSum(), sqrSum, TOLERANCE, "SqrSum value wrong");
}
// ===========================================================================
// Test case for five integers.
// ===========================================================================
class FiveIntegersTestCase : public TestCase
{
public:
FiveIntegersTestCase ();
virtual ~FiveIntegersTestCase ();
private:
virtual void DoRun (void);
};
FiveIntegersTestCase::FiveIntegersTestCase ()
: TestCase ("Basic Statistical Functions using Five Integers")
{
}
FiveIntegersTestCase::~FiveIntegersTestCase ()
{
}
void
FiveIntegersTestCase::DoRun (void)
{
MinMaxAvgTotalCalculator<int> calculator;
long count = 5;
double sum = 0;
double sqrSum = 0;
double min;
double max;
double mean;
double stddev;
double variance;
// Put all of the values into the calculator.
int multiple = 5;
int value;
for (long i = 0; i < count; i++)
{
value = multiple * (i + 1);
calculator.Update (value);
sum += value;
sqrSum += value * value;
}
// Calculate the expected values for the statistical functions.
min = multiple;
max = multiple * count;
mean = sum / count;
variance = (count * sqrSum - sum * sum) / (count * (count - 1));
stddev = std::sqrt (variance);
// Test the calculator.
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getCount(), count, TOLERANCE, "Count value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getSum(), sum, TOLERANCE, "Sum value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMin(), min, TOLERANCE, "Min value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMax(), max, TOLERANCE, "Max value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMean(), mean, TOLERANCE, "Mean value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getStddev(), stddev, TOLERANCE, "Stddev value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getVariance(), variance, TOLERANCE, "Variance value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getSqrSum(), sqrSum, TOLERANCE, "SqrSum value wrong");
}
// ===========================================================================
// Test case for five double values.
// ===========================================================================
class FiveDoublesTestCase : public TestCase
{
public:
FiveDoublesTestCase ();
virtual ~FiveDoublesTestCase ();
private:
virtual void DoRun (void);
};
FiveDoublesTestCase::FiveDoublesTestCase ()
: TestCase ("Basic Statistical Functions using Five Double Values")
{
}
FiveDoublesTestCase::~FiveDoublesTestCase ()
{
}
void
FiveDoublesTestCase::DoRun (void)
{
MinMaxAvgTotalCalculator<double> calculator;
long count = 5;
double sum = 0;
double sqrSum = 0;
double min;
double max;
double mean;
double stddev;
double variance;
// Put all of the values into the calculator.
double multiple = 3.14;
double value;
for (long i = 0; i < count; i++)
{
value = multiple * (i + 1);
calculator.Update (value);
sum += value;
sqrSum += value * value;
}
// Calculate the expected values for the statistical functions.
min = multiple;
max = multiple * count;
mean = sum / count;
variance = (count * sqrSum - sum * sum) / (count * (count - 1));
stddev = std::sqrt (variance);
// Test the calculator.
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getCount(), count, TOLERANCE, "Count value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getSum(), sum, TOLERANCE, "Sum value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMin(), min, TOLERANCE, "Min value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMax(), max, TOLERANCE, "Max value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getMean(), mean, TOLERANCE, "Mean value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getStddev(), stddev, TOLERANCE, "Stddev value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getVariance(), variance, TOLERANCE, "Variance value wrong");
NS_TEST_ASSERT_MSG_EQ_TOL (calculator.getSqrSum(), sqrSum, TOLERANCE, "SqrSum value wrong");
}
class BasicDataCalculatorsTestSuite : public TestSuite
{
public:
BasicDataCalculatorsTestSuite ();
};
BasicDataCalculatorsTestSuite::BasicDataCalculatorsTestSuite ()
: TestSuite ("basic-data-calculators", UNIT)
{
AddTestCase (new OneIntegerTestCase, TestCase::QUICK);
AddTestCase (new FiveIntegersTestCase, TestCase::QUICK);
AddTestCase (new FiveDoublesTestCase, TestCase::QUICK);
}
static BasicDataCalculatorsTestSuite basicDataCalculatorsTestSuite;