basic-data-calculators-test-suite.cc

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/* -*- 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;
 
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");
}
 
 
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");
}
 
 
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;