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/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2003 Ferdinando Ametrano
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it and/or modify it
under the terms of the QuantLib license. You should have received a
copy of the license along with this program; if not, please email
<quantlib-dev@lists.sf.net>. The license is also available online at
<http://quantlib.org/license.shtml>.
This program 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 license for more details.
*/
/*! \file randomsequencegenerator.hpp
\brief Random sequence generator based on a pseudo-random number generator
*/
#ifndef quantlib_random_sequence_generator_h
#define quantlib_random_sequence_generator_h
#include <ql/methods/montecarlo/sample.hpp>
#include <ql/errors.hpp>
#include <vector>
namespace QuantLib {
//! Random sequence generator based on a pseudo-random number generator
/*! Random sequence generator based on a pseudo-random number
generator RNG.
Class RNG must implement the following interface:
\code
RNG::sample_type RNG::next() const;
\endcode
If a client of this class wants to use the nextInt32Sequence method,
class RNG must also implement
\code
unsigned long RNG::nextInt32() const;
\endcode
\warning do not use with low-discrepancy sequence generator.
*/
template<class RNG>
class RandomSequenceGenerator {
public:
typedef Sample<std::vector<Real> > sample_type;
RandomSequenceGenerator(Size dimensionality,
const RNG& rng)
: dimensionality_(dimensionality), rng_(rng),
sequence_(std::vector<Real> (dimensionality), 1.0),
int32Sequence_(dimensionality) {
QL_REQUIRE(dimensionality>0,
"dimensionality must be greater than 0");
}
explicit RandomSequenceGenerator(Size dimensionality,
BigNatural seed = 0)
: dimensionality_(dimensionality), rng_(seed),
sequence_(std::vector<Real> (dimensionality), 1.0),
int32Sequence_(dimensionality) {}
const sample_type& nextSequence() const {
sequence_.weight = 1.0;
for (Size i=0; i<dimensionality_; i++) {
typename RNG::sample_type x(rng_.next());
sequence_.value[i] = x.value;
sequence_.weight *= x.weight;
}
return sequence_;
}
std::vector<BigNatural> nextInt32Sequence() const {
for (Size i=0; i<dimensionality_; i++) {
int32Sequence_[i] = rng_.nextInt32();
}
return int32Sequence_;
}
const sample_type& lastSequence() const {
return sequence_;
}
Size dimension() const {return dimensionality_;}
private:
Size dimensionality_;
RNG rng_;
mutable sample_type sequence_;
mutable std::vector<BigNatural> int32Sequence_;
};
}
#endif
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