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/* boost random/uniform_smallint.hpp header file
*
* Copyright Jens Maurer 2000-2001
* Distributed under the Boost Software License, Version 1.0. (See
* accompanying file LICENSE_1_0.txt or copy at
* http://www.boost.org/LICENSE_1_0.txt)
*
* See http://www.boost.org for most recent version including documentation.
*
* $Id: uniform_smallint.hpp 71018 2011-04-05 21:27:52Z steven_watanabe $
*
* Revision history
* 2001-04-08 added min<max assertion (N. Becker)
* 2001-02-18 moved to individual header files
*/
#ifndef NDNBOOST_RANDOM_UNIFORM_SMALLINT_HPP
#define NDNBOOST_RANDOM_UNIFORM_SMALLINT_HPP
#include <istream>
#include <iosfwd>
#include <ndnboost/assert.hpp>
#include <ndnboost/config.hpp>
#include <ndnboost/limits.hpp>
#include <ndnboost/type_traits/is_integral.hpp>
#include <ndnboost/random/detail/config.hpp>
#include <ndnboost/random/detail/operators.hpp>
#include <ndnboost/random/detail/signed_unsigned_tools.hpp>
#include <ndnboost/random/uniform_01.hpp>
#include <ndnboost/detail/workaround.hpp>
namespace ndnboost {
namespace random {
// uniform integer distribution on a small range [min, max]
/**
* The distribution function uniform_smallint models a \random_distribution.
* On each invocation, it returns a random integer value uniformly distributed
* in the set of integer numbers {min, min+1, min+2, ..., max}. It assumes
* that the desired range (max-min+1) is small compared to the range of the
* underlying source of random numbers and thus makes no attempt to limit
* quantization errors.
*
* Let \f$r_{\mathtt{out}} = (\mbox{max}-\mbox{min}+1)\f$ the desired range of
* integer numbers, and
* let \f$r_{\mathtt{base}}\f$ be the range of the underlying source of random
* numbers. Then, for the uniform distribution, the theoretical probability
* for any number i in the range \f$r_{\mathtt{out}}\f$ will be
* \f$\displaystyle p_{\mathtt{out}}(i) = \frac{1}{r_{\mathtt{out}}}\f$.
* Likewise, assume a uniform distribution on \f$r_{\mathtt{base}}\f$ for
* the underlying source of random numbers, i.e.
* \f$\displaystyle p_{\mathtt{base}}(i) = \frac{1}{r_{\mathtt{base}}}\f$.
* Let \f$p_{\mathtt{out\_s}}(i)\f$ denote the random
* distribution generated by @c uniform_smallint. Then the sum over all
* i in \f$r_{\mathtt{out}}\f$ of
* \f$\displaystyle
* \left(\frac{p_{\mathtt{out\_s}}(i)}{p_{\mathtt{out}}(i)} - 1\right)^2\f$
* shall not exceed
* \f$\displaystyle \frac{r_{\mathtt{out}}}{r_{\mathtt{base}}^2}
* (r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})
* (r_{\mathtt{out}} - r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})\f$.
*
* The template parameter IntType shall denote an integer-like value type.
*
* @xmlnote
* The property above is the square sum of the relative differences
* in probabilities between the desired uniform distribution
* \f$p_{\mathtt{out}}(i)\f$ and the generated distribution
* \f$p_{\mathtt{out\_s}}(i)\f$.
* The property can be fulfilled with the calculation
* \f$(\mbox{base\_rng} \mbox{ mod } r_{\mathtt{out}})\f$, as follows:
* Let \f$r = r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}}\f$.
* The base distribution on \f$r_{\mathtt{base}}\f$ is folded onto the
* range \f$r_{\mathtt{out}}\f$. The numbers i < r have assigned
* \f$\displaystyle
* \left\lfloor\frac{r_{\mathtt{base}}}{r_{\mathtt{out}}}\right\rfloor+1\f$
* numbers of the base distribution, the rest has only \f$\displaystyle
* \left\lfloor\frac{r_{\mathtt{base}}}{r_{\mathtt{out}}}\right\rfloor\f$.
* Therefore,
* \f$\displaystyle p_{\mathtt{out\_s}}(i) =
* \left(\left\lfloor\frac{r_{\mathtt{base}}}
* {r_{\mathtt{out}}}\right\rfloor+1\right) /
* r_{\mathtt{base}}\f$ for i < r and \f$\displaystyle p_{\mathtt{out\_s}}(i) =
* \left\lfloor\frac{r_{\mathtt{base}}}
* {r_{\mathtt{out}}}\right\rfloor/r_{\mathtt{base}}\f$ otherwise.
* Substituting this in the
* above sum formula leads to the desired result.
* @endxmlnote
*
* Note: The upper bound for
* \f$(r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})
* (r_{\mathtt{out}} - r_{\mathtt{base}} \mbox{ mod } r_{\mathtt{out}})\f$ is
* \f$\displaystyle \frac{r_{\mathtt{out}}^2}{4}\f$. Regarding the upper bound
* for the square sum of the relative quantization error of
* \f$\displaystyle \frac{r_\mathtt{out}^3}{4r_{\mathtt{base}}^2}\f$, it
* seems wise to either choose \f$r_{\mathtt{base}}\f$ so that
* \f$r_{\mathtt{base}} > 10r_{\mathtt{out}}^2\f$ or ensure that
* \f$r_{\mathtt{base}}\f$ is
* divisible by \f$r_{\mathtt{out}}\f$.
*/
template<class IntType = int>
class uniform_smallint
{
public:
typedef IntType input_type;
typedef IntType result_type;
class param_type
{
public:
typedef uniform_smallint distribution_type;
/** constructs the parameters of a @c uniform_smallint distribution. */
param_type(IntType min_arg = 0, IntType max_arg = 9)
: _min(min_arg), _max(max_arg)
{
NDNBOOST_ASSERT(_min <= _max);
}
/** Returns the minimum value. */
IntType a() const { return _min; }
/** Returns the maximum value. */
IntType b() const { return _max; }
/** Writes the parameters to a @c std::ostream. */
NDNBOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, param_type, parm)
{
os << parm._min << " " << parm._max;
return os;
}
/** Reads the parameters from a @c std::istream. */
NDNBOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, param_type, parm)
{
is >> parm._min >> std::ws >> parm._max;
return is;
}
/** Returns true if the two sets of parameters are equal. */
NDNBOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(param_type, lhs, rhs)
{ return lhs._min == rhs._min && lhs._max == rhs._max; }
/** Returns true if the two sets of parameters are different. */
NDNBOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(param_type)
private:
IntType _min;
IntType _max;
};
/**
* Constructs a @c uniform_smallint. @c min and @c max are the
* lower and upper bounds of the output range, respectively.
*/
explicit uniform_smallint(IntType min_arg = 0, IntType max_arg = 9)
: _min(min_arg), _max(max_arg) {}
/**
* Constructs a @c uniform_smallint from its parameters.
*/
explicit uniform_smallint(const param_type& parm)
: _min(parm.a()), _max(parm.b()) {}
/** Returns the minimum value of the distribution. */
result_type a() const { return _min; }
/** Returns the maximum value of the distribution. */
result_type b() const { return _max; }
/** Returns the minimum value of the distribution. */
result_type min NDNBOOST_PREVENT_MACRO_SUBSTITUTION () const { return _min; }
/** Returns the maximum value of the distribution. */
result_type max NDNBOOST_PREVENT_MACRO_SUBSTITUTION () const { return _max; }
/** Returns the parameters of the distribution. */
param_type param() const { return param_type(_min, _max); }
/** Sets the parameters of the distribution. */
void param(const param_type& parm)
{
_min = parm.a();
_max = parm.b();
}
/**
* Effects: Subsequent uses of the distribution do not depend
* on values produced by any engine prior to invoking reset.
*/
void reset() { }
/** Returns a value uniformly distributed in the range [min(), max()]. */
template<class Engine>
result_type operator()(Engine& eng) const
{
typedef typename Engine::result_type base_result;
return generate(eng, ndnboost::is_integral<base_result>());
}
/** Returns a value uniformly distributed in the range [param.a(), param.b()]. */
template<class Engine>
result_type operator()(Engine& eng, const param_type& parm) const
{ return uniform_smallint(parm)(eng); }
/** Writes the distribution to a @c std::ostream. */
NDNBOOST_RANDOM_DETAIL_OSTREAM_OPERATOR(os, uniform_smallint, ud)
{
os << ud._min << " " << ud._max;
return os;
}
/** Reads the distribution from a @c std::istream. */
NDNBOOST_RANDOM_DETAIL_ISTREAM_OPERATOR(is, uniform_smallint, ud)
{
is >> ud._min >> std::ws >> ud._max;
return is;
}
/**
* Returns true if the two distributions will produce identical
* sequences of values given equal generators.
*/
NDNBOOST_RANDOM_DETAIL_EQUALITY_OPERATOR(uniform_smallint, lhs, rhs)
{ return lhs._min == rhs._min && lhs._max == rhs._max; }
/**
* Returns true if the two distributions may produce different
* sequences of values given equal generators.
*/
NDNBOOST_RANDOM_DETAIL_INEQUALITY_OPERATOR(uniform_smallint)
private:
// \cond show_private
template<class Engine>
result_type generate(Engine& eng, ndnboost::mpl::true_) const
{
// equivalent to (eng() - eng.min()) % (_max - _min + 1) + _min,
// but guarantees no overflow.
typedef typename Engine::result_type base_result;
typedef typename ndnboost::make_unsigned<base_result>::type base_unsigned;
typedef typename ndnboost::make_unsigned<result_type>::type range_type;
range_type range = random::detail::subtract<result_type>()(_max, _min);
base_unsigned base_range =
random::detail::subtract<result_type>()((eng.max)(), (eng.min)());
base_unsigned val =
random::detail::subtract<base_result>()(eng(), (eng.min)());
if(range >= base_range) {
return ndnboost::random::detail::add<range_type, result_type>()(
static_cast<range_type>(val), _min);
} else {
base_unsigned modulus = static_cast<base_unsigned>(range) + 1;
return ndnboost::random::detail::add<range_type, result_type>()(
static_cast<range_type>(val % modulus), _min);
}
}
template<class Engine>
result_type generate(Engine& eng, ndnboost::mpl::false_) const
{
typedef typename Engine::result_type base_result;
typedef typename ndnboost::make_unsigned<result_type>::type range_type;
range_type range = random::detail::subtract<result_type>()(_max, _min);
base_result val = ndnboost::uniform_01<base_result>()(eng);
// what is the worst that can possibly happen here?
// base_result may not be able to represent all the values in [0, range]
// exactly. If this happens, it will cause round off error and we
// won't be able to produce all the values in the range. We don't
// care about this because the user has already told us not to by
// using uniform_smallint. However, we do need to be careful
// to clamp the result, or floating point rounding can produce
// an out of range result.
range_type offset = static_cast<range_type>(val * (static_cast<base_result>(range) + 1));
if(offset > range) return _max;
return ndnboost::random::detail::add<range_type, result_type>()(offset , _min);
}
// \endcond
result_type _min;
result_type _max;
};
} // namespace random
using random::uniform_smallint;
} // namespace ndnboost
#endif // NDNBOOST_RANDOM_UNIFORM_SMALLINT_HPP