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