basic-data-calculators-test-suite.cc

Go to the documentation of this file.

/*
 * 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 "ns3/basic-data-calculators.h"
#include "ns3/test.h"
 
#include <cmath>
 
using namespace ns3;
 
// See issue #698 for discussion of this tolerance
const double TOLERANCE = 1e-13;
 
class OneIntegerTestCase : public TestCase
{
  public:
    OneIntegerTestCase();
    ~OneIntegerTestCase() override;
 
  private:
    void DoRun() override;
};
 
OneIntegerTestCase::OneIntegerTestCase()
    : TestCase("Basic Statistical Functions using One Integer")
 
{
}
 
OneIntegerTestCase::~OneIntegerTestCase()
{
}
 
void
OneIntegerTestCase::DoRun()
{
    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");
}
 
class FiveIntegersTestCase : public TestCase
{
  public:
    FiveIntegersTestCase();
    ~FiveIntegersTestCase() override;
 
  private:
    void DoRun() override;
};
 
FiveIntegersTestCase::FiveIntegersTestCase()
    : TestCase("Basic Statistical Functions using Five Integers")
 
{
}
 
FiveIntegersTestCase::~FiveIntegersTestCase()
{
}
 
void
FiveIntegersTestCase::DoRun()
{
    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");
}
 
class FiveDoublesTestCase : public TestCase
{
  public:
    FiveDoublesTestCase();
    ~FiveDoublesTestCase() override;
 
  private:
    void DoRun() override;
};
 
FiveDoublesTestCase::FiveDoublesTestCase()
    : TestCase("Basic Statistical Functions using Five Double Values")
 
{
}
 
FiveDoublesTestCase::~FiveDoublesTestCase()
{
}
 
void
FiveDoublesTestCase::DoRun()
{
    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;