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/*=========================================================================
Program: Insight Segmentation & Registration Toolkit
Module: $RCSfile: itkMersenneTwisterRandomVariateGeneratorTest.cxx,v $
Language: C++
Date: $Date: 2005-10-06 19:35:15 $
Version: $Revision: 1.9 $
Copyright (c) Insight Software Consortium. All rights reserved.
See ITKCopyright.txt or http://www.itk.org/HTML/Copyright.htm for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#if defined(_MSC_VER)
#pragma warning ( disable : 4786 )
#endif
#include "itkMersenneTwisterRandomVariateGenerator.h"
#include "vnl/vnl_sample.h"
#include "vnl/vnl_math.h"
#include "itkTimeProbe.h"
bool ComputeMeanAndVariance( const unsigned long numberOfSamples );
bool SequenceCheck();
int itkMersenneTwisterRandomVariateGeneratorTest(int, char* [] )
{
#if __CYGWIN__
vnl_sample_reseed(0x1234abcd);
#endif
std::cout << "MersenneTwisterRandomVariateGenerator Test" << std::endl;
bool pass = true;
pass &= SequenceCheck ( );
pass &= ComputeMeanAndVariance( 1000000UL );
pass &= ComputeMeanAndVariance( 100000UL );
if( pass )
{
return EXIT_SUCCESS;
}
else
{
return EXIT_FAILURE;
}
}
bool SequenceCheck ()
{
bool status = true;
typedef itk::Statistics::MersenneTwisterRandomVariateGenerator GeneratorType;
GeneratorType::Pointer generator = GeneratorType::New();
GeneratorType::IntegerType randomSeed = 14543 ; // any number to initialize the seed.
generator->SetSeed ( randomSeed );
double Expected[] = { 0.252523,
0.223867,
0.691444,
0.997124,
0.122781,
0.36465,
0.363542,
0.0424811,
0.540263,
0.553432 };
for ( int i = 0; i < 10; i++ )
{
double Value = generator->GetUniformVariate(0.0, 1.0);
double diff = Value - Expected[i];
std::cout << "[" << i << "] " << Value << " Expected: " << Expected[i] << std::endl;
if ( ( diff * diff ) > 0.0001 )
{
status &= false;
std::cout << "\tFailed!" << std::endl;
}
}
return status;
}
bool ComputeMeanAndVariance(const unsigned long numberOfSamples)
{
std::cout << "Test mean and variance of a uniform distribution [0, 10): " << std::endl;
bool pass = true;
const double tolerance = 0.05;
typedef itk::Statistics::MersenneTwisterRandomVariateGenerator GeneratorType;
GeneratorType::Pointer generator = GeneratorType::New();
GeneratorType::IntegerType randomSeed = 14543 ; // any number to initialize the seed.
generator->Initialize( randomSeed );
double MTsum = 0.0f;
double MTsum2 = 0.0f;
std::cout << "Compute Mean and variance with " <<
numberOfSamples << " samples... " << std::endl;
itk::TimeProbe clockMT1;
clockMT1.Start();
for(unsigned int i=0; i < numberOfSamples; i++)
{
generator->GetUniformVariate(0,10);
}
clockMT1.Stop();
for(unsigned int i=0; i < numberOfSamples; i++)
{
double variate = generator->GetUniformVariate(0,10);
MTsum += variate;
MTsum2 += variate * variate;
}
{
const double mean = MTsum / numberOfSamples;
const double variance = MTsum2 / numberOfSamples - mean * mean;
std::cout << "Mean [MersenneTwisterRandomVariateGenerator] = "
<< mean << std::endl;
std::cout << "Variance [MersenneTwisterRandomVariateGenerator] = "
<< variance << std::endl;
const double uniformVariance = 100.0/12.0;
std::cout << "Testing Mean " << std::endl;
if( vcl_abs(mean - 5) > tolerance )
{
pass = false;
std::cout << "[FAILED]" << std::endl;
}
else
{
std::cout << "[PASSED]" << std::endl;
}
std::cout << "Testing Variance " << std::endl;
if( vcl_abs(variance - uniformVariance) > tolerance )
{
pass = false;
std::cout << "[FAILED]" << std::endl;
}
else
{
std::cout << "[PASSED]" << std::endl;
}
}
double vnlSum = 0.0f;
double vnlSum2 = 0.0f;
std::cout << "USING VNL " << std::endl;
itk::TimeProbe clockVnl1;
clockVnl1.Start();
for(unsigned int i=0; i < numberOfSamples; i++)
{
vnl_sample_uniform(0,10);
}
clockVnl1.Stop();
for(unsigned int i=0; i < numberOfSamples; i++)
{
double variate = vnl_sample_uniform(0,10);
vnlSum += variate;
vnlSum2 += variate * variate;
}
{
const double mean = vnlSum / numberOfSamples;
const double variance = vnlSum2 / numberOfSamples - mean * mean;
std::cout << "Mean [VNL] = "
<< mean << std::endl;
std::cout << "Variance [VNL] = "
<< variance << std::endl;
const double uniformVariance = 100.0/12.0;
std::cout << "Testing Mean " << std::endl;
if( vcl_abs(mean - 5) > tolerance )
{
pass = false;
std::cout << "[FAILED]" << std::endl;
}
else
{
std::cout << "[PASSED]" << std::endl;
}
std::cout << "Testing Variance " << std::endl;
if( vcl_abs(variance - uniformVariance) > (tolerance*3) )
{
pass = false;
std::cout << "[FAILED]" << std::endl;
}
else
{
std::cout << "[PASSED]" << std::endl;
}
}
std::cout <<
"MersenneTwisterRandomVariateGenerator: Computing "
<< numberOfSamples << " random numbers took " <<
clockMT1.GetMeanTime() << " s" << std::endl;
std::cout <<
"vnl_sample : Computing "
<< numberOfSamples << " random numbers took " <<
clockVnl1.GetMeanTime() << " s" << std::endl;
return pass;
}
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