weibull_distribution.hpp

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//============================================================================
// vSMC/include/vsmc/rng/weibull_distribution.hpp
//----------------------------------------------------------------------------
//                         vSMC: Scalable Monte Carlo
//----------------------------------------------------------------------------
// Copyright (c) 2013-2015, Yan Zhou
// All rights reserved.
//
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// modification, are permitted provided that the following conditions are met:
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//   this list of conditions and the following disclaimer.
//
//   Redistributions in binary form must reproduce the above copyright notice,
//   this list of conditions and the following disclaimer in the documentation
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//============================================================================

#ifndef VSMC_RNG_WEIBULL_DISTRIBUTION_HPP
#define VSMC_RNG_WEIBULL_DISTRIBUTION_HPP

#include <vsmc/rng/internal/common.hpp>
#include <vsmc/rng/u01_distribution.hpp>
#include <vsmc/rng/normal_distribution.hpp>

namespace vsmc
{

namespace internal
{

template <typename RealType>
inline bool weibull_distribution_check_param(RealType a, RealType b)
{
    return a > 0 && b > 0;
}

} // namespace vsmc::internal

template <typename RealType>
class WeibullDistribution
{
    VSMC_DEFINE_RNG_DISTRIBUTION_2(
        Weibull, weibull, RealType, result_type, a, 1, result_type, b, 1)
    VSMC_DEFINE_RNG_DISTRIBUTION_OPERATORS

    public:
    result_type min VSMC_MNE() const { return 0; }

    result_type max VSMC_MNE() const
    {
        return std::numeric_limits<result_type>::max VSMC_MNE();
    }

    void reset() {}

    private:
    template <typename RNGType>
    result_type generate(RNGType &rng, const param_type &param)
    {
        U01OODistribution<RealType> runif;

        return param.b() *
            std::exp((1 / param.a()) * std::log(-std::log(runif(rng))));
    }
}; // class WeibullDistribution

namespace internal
{

template <typename RealType, typename RNGType>
inline void weibull_distribution_impl(
    RNGType &rng, std::size_t n, RealType *r, RealType a, RealType b)
{
    u01_oo_distribution(rng, n, r);
    log(n, r, r);
    if (is_equal<RealType>(a, 1)) {
        mul(n, -b, r, r);
    } else {
        mul(n, static_cast<RealType>(-1), r, r);
        log(n, r, r);
        mul(n, 1 / a, r, r);
        exp(n, r, r);
        mul(n, b, r, r);
    }
}

} // namespace vsmc::internal

template <typename RealType, typename RNGType>
inline void weibull_distribution(
    RNGType &rng, std::size_t n, RealType *r, RealType a, RealType b)
{
    const std::size_t k = 1000;
    const std::size_t m = n / k;
    const std::size_t l = n % k;
    for (std::size_t i = 0; i != m; ++i)
        internal::weibull_distribution_impl(rng, k, r + i * k, a, b);
    internal::weibull_distribution_impl(rng, l, r + m * k, a, b);
}

template <typename RealType, typename RNGType>
inline void rng_rand(RNGType &rng, WeibullDistribution<RealType> &dist,
    std::size_t n, RealType *r)
{
    dist(rng, n, r);
}

} // namespace vsmc

#endif // VSMC_RNG_WEIBULL_DISTRIBUTION_HPP