/usr/include/shark/Rng/Bernoulli.h is in libshark-dev 3.1.4+ds1-1ubuntu1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 | /*!
*
*
* \brief Implements a Bernoulli distribution.
*
*
*
* \author O. Krause
* \date 2010-01-01
*
*
* \par Copyright 1995-2015 Shark Development Team
*
* <BR><HR>
* This file is part of Shark.
* <http://image.diku.dk/shark/>
*
* Shark is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as published
* by the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* Shark 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 Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with Shark. If not, see <http://www.gnu.org/licenses/>.
*
*/
#ifndef SHARK_RNG_BERNOULLI_H
#define SHARK_RNG_BERNOULLI_H
#include <shark/Rng/Rng.h>
#include <boost/random.hpp>
#include <cmath>
namespace shark{
/*!
* \brief This class simulates a "Bernoulli trial", which
* is like a coin toss.
*
* This class is a thin wrapper for the boost::bernoulli_distribution class.
* A bernoulli distribution simulates a generalized coin toss.
* A probability for the occurrence of the event (coin side)
* is defined. When using the equal probability of "0.5" for the
* occurrence and non-occurrence of the event (coin side), then the
* event (coin) is named "normal", otherwise it is named "abnormal".
*
* \author O.Krause
* \date 2010-01-01
*
* \par Changes:
* none
*
* \par Status:
* testing
*
*/
template<typename RngType = shark::DefaultRngType>
class Bernoulli : public boost::variate_generator< RngType*,boost::bernoulli_distribution<> >
{
private:
typedef boost::variate_generator<RngType*,boost::bernoulli_distribution<> > Base;
public:
//! Creates a new Bernoulli random generator using the global generator from instance and
//! sets the probability for the occurrence of the event
//! to "prob".
/*
Bernoulli(double prob=0.5)
:Base(&Rng::globalRng,boost::bernoulli_distribution<>(prob))
{}*/
//! Creates a new Bernoulli random generator instance by
//! using the pseudo random number generator "rng" for the determination
//! of random values and sets the probability for the occurrence
//! of the event to "prob".
Bernoulli( RngType & rng, double prob = 0.5 )
:Base(&rng,boost::bernoulli_distribution<>(prob))
{}
/*!
* \brief Returns a Bernoulli random number, i.e. a "true" or "false"
* marking the occurrence and non-occurrence of an event respectively,
* using the preset propability
*
* \return a bernoulli distributed number
*/
using Base::operator();
/*!
* \brief Returns a Bernoulli random number, i.e. a "true" or "false"
* marking the occurrence and non-occurrence of an event respectively,
* when the probability for the occurrence is "p".
*
* \return a bernoulli distributed number
*/
bool operator()(double p)
{
boost::bernoulli_distribution<> dist(p);
return dist(Base::engine());
}
/*!
* \brief Returns the probability for the occurrence of an event.
*
* \return the probability for the occurrence of an event
*/
double prob()const
{
return Base::distribution().p();
}
/*!
* \brief Sets the probability for the occurrence of an event to "newP".
*
* \param newP the new probability for the occurrence of an event
* \return none
*/
void prob(double newP)
{
Base::distribution()=boost::bernoulli_distribution<>(newP);
}
//! Returns the probability \f$p\f$ for the occurrence of an
//! event ("x = true") or \f$1 - p\f$ for the non-occurrence
//! ("x = false").
double p(bool x) const
{
return x ? prob() : 1 - prob();
}
};
///\brief Flips a coin with probability of heads being pHeads by drawing random numbers from rng.
template<class RngType>
bool coinToss(RngType& rng, double pHeads){
Bernoulli<RngType> dist(rng, pHeads);
return dist();
}
}
#endif
|