/usr/include/visp/vpNoise.h is in libvisp-dev 2.9.0-3+b2.
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*
* $Id: vpNoise.h 4649 2014-02-07 14:57:11Z fspindle $
*
* This file is part of the ViSP software.
* Copyright (C) 2005 - 2014 by INRIA. All rights reserved.
*
* This software is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* ("GPL") version 2 as published by the Free Software Foundation.
* See the file LICENSE.txt at the root directory of this source
* distribution for additional information about the GNU GPL.
*
* For using ViSP with software that can not be combined with the GNU
* GPL, please contact INRIA about acquiring a ViSP Professional
* Edition License.
*
* See http://www.irisa.fr/lagadic/visp/visp.html for more information.
*
* This software was developed at:
* INRIA Rennes - Bretagne Atlantique
* Campus Universitaire de Beaulieu
* 35042 Rennes Cedex
* France
* http://www.irisa.fr/lagadic
*
* If you have questions regarding the use of this file, please contact
* INRIA at visp@inria.fr
*
* This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
* WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
*
*
* Description:
* Generation of random number with uniform and normal probability density.
*
* Authors:
* Eric Marchand
*
*****************************************************************************/
#ifndef vpNoise_hh
#define vpNoise_hh
/*!
\file vpNoise.h
\brief Class for generating random number
with uniform and normal probability density
The algorithms and notations used are described in
James E. Gentle, Random Number Generation and Monte Carlo Methods,
Springer 1998
*/
#include <visp/vpConfig.h>
/*!
\class vpUniRand
\ingroup Random
\brief Class for generating random numbers with uniform probability density.
The algorithms and notations used are described in
Random Number Generation and Monte Carlo Methods
James E. Gentle, Springer 1998
*/
class VISP_EXPORT vpUniRand
{
/*unsigned*/ long a ;
/*unsigned*/ long m ; //2^31-1
/*unsigned*/ long q ; //integer part of m/a
/*unsigned*/ long r ;//r=m mod a
double normalizer ; //we use a normalizer > m to ensure ans will never be 1 (it is the case if x = 739806647)
private:
void draw0();
protected:
long x;
double draw1();
public:
vpUniRand(const long seed = 0)
: a(16807), m(2147483647), q(127773), r(2836), normalizer(2147484721.0), x((seed)? seed : 739806647)
{
}
virtual ~vpUniRand() {};
double operator()() {return draw1();}
};
/*!
\class vpGaussRand
\ingroup Random
\brief Class for generating random number with normal probability density.
The algorithms and notations used are described in "Random Number Generation and Monte Carlo Methods",
James E. Gentle, Springer 1998
The code below shows how to use the random generator.
\code
#include <iostream>
#include <visp/vpNoise.h>
int main()
{
vpGaussRand noise(0.5, 10);
for(int i=0; i< 10; i++) {
std::cout << "noise " << i << ": " << noise() << std::endl;
}
return 0;
}
\endcode
*/
class vpGaussRand : public vpUniRand
{
private :
double mean;
double sigma;
double gaussianDraw();
public:
/*!
Default noise generator constructor.
*/
vpGaussRand() : vpUniRand(), mean(0), sigma(0) {}
/*!
Gaussian noise random generator constructor.
\param sigma_val : Standard deviation.
\param mean_val : Mean value.
\param noise_seed : Seed of the noise
*/
vpGaussRand(const double sigma_val, const double mean_val, const long noise_seed = 0)
: vpUniRand(noise_seed), mean(mean_val), sigma(sigma_val) {}
/*!
Set the standard deviation and mean for gaussian noise.
\param sigma_val : New standard deviation sigma.
\param mean_val : New mean value.
*/
void setSigmaMean(const double sigma_val, const double mean_val) {
this->mean = mean_val;
this->sigma = sigma_val;
}
/*!
Set the seed of the noise.
\param seed_val : New seed.
*/
void seed(const long seed_val) {
x=seed_val;
}
/*!
Return a random value from the Gaussian noise generator.
*/
double operator()() {
return sigma*gaussianDraw()+mean;
}
};
#endif
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