Estimation C++ DLL: Adding the new Proposal class with common, adjustable seed for both normal and uniform rng and the associated changes including the removal of now obsolete RandSampler class.
George Perendia
parent
34454ffa8d
commit
887209208f
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@ -0,0 +1,91 @@
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/*
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* Copyright (C) 2009-2010 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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///////////////////////////////////////////////////////////
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// Proposal.cpp
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// Implementation of the Class Proposal
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// Created on: 15-Dec-2010 12:43:49
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///////////////////////////////////////////////////////////
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#include "Proposal.hh"
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Proposal::Proposal(const VectorConstView &vJscale, const MatrixConstView &covariance) :
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len(covariance.getCols()),
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covarianceCholeskyDecomposition(len),
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newDraw(len),
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uniform_rng_type(0, 1), // uniform random number generator distribution type
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uniformVrng(base_rng, uniform_rng_type), // uniform random variate_generator
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normal_rng_type(0, 1), // normal random number generator distribution type (mean, standard)
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normalVrng(base_rng, normal_rng_type) // normal random variate_generator
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{
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Matrix Jscale(len);
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Matrix DD(len);
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DD = covariance;
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lapack::choleskyDecomp(DD, "U");
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Jscale.setAll(0.0);
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for (size_t i = 0; i < len; i++)
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Jscale(i, i) = vJscale(i);
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blas::gemm("N", "N", 1.0, DD, Jscale, 0.0, covarianceCholeskyDecomposition);
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}
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void
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Proposal::draw(Vector &mean, Vector &draw)
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{
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assert(len == draw.getSize());
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assert(len == mean.getSize());
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draw = mean;
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for (size_t i = 0; i < len; ++i)
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newDraw(i) = normalVrng();
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blas::gemv("T", 1.0, covarianceCholeskyDecomposition, newDraw, 1.0, draw);
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}
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Matrix &
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Proposal::getVar()
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{
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return covarianceCholeskyDecomposition;
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}
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/**
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* set or get if null arguments
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*/
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int
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Proposal::seed()
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{
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return curSeed;
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}
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void
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Proposal::seed(int newSeed)
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{
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curSeed = newSeed;
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base_rng.seed(curSeed);
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}
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/**
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* currently returns uniform for MH sampler,
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*/
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double
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Proposal::selectionTestDraw()
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{
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return uniformVrng();
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}
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@ -0,0 +1,92 @@
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/*
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* Copyright (C) 2009-2010 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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///////////////////////////////////////////////////////////
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// Proposal.hh
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// Implementation of the Class Proposal
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// Created on: 15-Dec-2010 12:43:49
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///////////////////////////////////////////////////////////
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#if !defined(CABFAB46_2FA5_4178_8D1C_05DFEAFB4570__INCLUDED_)
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#define CABFAB46_2FA5_4178_8D1C_05DFEAFB4570__INCLUDED_
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/**
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* Proposal class will then have the common, seed initialised base generator
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* (currently congruental rand48) and member functions such as seed, reset (to
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* initial,default value) and have all rand generators we need that generate from
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* that common base: single uniform and normal (either single or multivariate
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* determined by the size of the variance matrix) for now.
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*
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* The rng interfaces will be - a single, selectionTest() currently uniform for MH
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* sampler, draw(mean, newDraw) - single or multivariate parameters (currently
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* from Normal(mean,Sigma)) and poss. also the seed state (set and get), the
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* normal Chol_variance_decomp (constructed using Chol Decomp of init Variance
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* matrix) , as core members .This class will handle the main boost random rng
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* intricacies. See enclosed updated diagram (if ok I will upload it)
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*
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*/
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#include "Matrix.hh"
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#include "BlasBindings.hh"
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#include "LapackBindings.hh"
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#include <boost/random/linear_congruential.hpp>
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#include <boost/random/normal_distribution.hpp>
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#include <boost/random/uniform_real.hpp>
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#include <boost/random/variate_generator.hpp>
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// typedef for base_uniform_generator_type
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// rend48 seems better than the basic minstd_rand but
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// one my later try ecuyer1988 or taus88 which are better but not yet supported in the Boost versionwe use
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typedef boost::rand48 base_uniform_generator_type;
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class Proposal
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{
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public:
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Proposal();
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public:
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Proposal(const VectorConstView &vJscale, const MatrixConstView &covariance);
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virtual ~Proposal(){};
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virtual void draw(Vector &mean, Vector &draw);
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virtual Matrix&getVar();
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virtual int seed();
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virtual void seed(int seedInit);
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virtual double selectionTestDraw();
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private:
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size_t len;
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Matrix covarianceCholeskyDecomposition;
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/**
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* Vector of new draws
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*
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*/
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Vector newDraw;
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base_uniform_generator_type base_rng;
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boost::uniform_real<> uniform_rng_type;
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boost::variate_generator<base_uniform_generator_type &, boost::uniform_real<> > uniformVrng;
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boost::normal_distribution<double> normal_rng_type;
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boost::variate_generator<base_uniform_generator_type &, boost::normal_distribution<double> > normalVrng;
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int curSeed;
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};
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#endif // !defined(CABFAB46_2FA5_4178_8D1C_05DFEAFB4570__INCLUDED_)
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@ -1,46 +0,0 @@
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/*
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* Copyright (C) 2010 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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///////////////////////////////////////////////////////////
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// RandSampler.cpp
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// Implementation of the Class RandSampler
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// Created on: 09-Sep-2010 23:25:30
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///////////////////////////////////////////////////////////
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#include "RandSampler.hh"
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#include "BlasBindings.hh"
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/**
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* draw = Mean + randn(1,n) * Sigma_upper_chol;
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*/
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void
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RandSampler::randMultiVar(Prior &distribution, Vector &draw, const Vector &mean, const Matrix &Scale, const size_t n)
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{
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assert(n == draw.getSize());
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assert(n == mean.getSize() );
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assert(n == Scale.getRows());
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assert(n == Scale.getCols());
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draw=mean;
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Vector drawTmp(n);
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for (size_t i = 0; i < n; ++i)
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drawTmp(i) = distribution.drand();
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blas::gemv("T", 1.0, Scale, drawTmp, 1.0, draw);
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}
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@ -1,48 +0,0 @@
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/*
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* Copyright (C) 2010 Dynare Team
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*
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* This file is part of Dynare.
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*
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* Dynare is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* Dynare is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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*/
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///////////////////////////////////////////////////////////
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// RandSampler.hh
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// Implementation of the Class RandSampler
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// Created on: 09-Sep-2010 23:25:29
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///////////////////////////////////////////////////////////
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#if !defined(RS5D7E5E52_2A4F_4f98_9A5C_A7FD8C278E0A__INCLUDED_)
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#define RS5D7E5E52_2A4F_4f98_9A5C_A7FD8C278E0A__INCLUDED_
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#include "LogPosteriorDensity.hh"
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class RandSampler {
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public:
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virtual ~RandSampler(){};
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virtual double compute(VectorView &mhLogPostDens, MatrixView &mhParams, Matrix &steadyState,
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Vector &estParams, Vector &deepParams, const MatrixConstView &data, Matrix &Q, Matrix &H,
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const size_t presampleStart, int &info, const size_t startDraw, size_t nMHruns, const Matrix &Jscale,
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LogPosteriorDensity &logPosteriorDensity, Prior &drawDistribution,
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EstimatedParametersDescription &epd) = 0;
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/**
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* draw = Mean + randn(1,n) * Sigma_upper_chol;
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*
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*/
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virtual void randMultiVar(Prior &distribution, Vector &draw, const Vector &mean, const Matrix &Scale, const size_t n);
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};
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#endif // !defined(5D7E5E52_2A4F_4f98_9A5C_A7FD8C278E0A__INCLUDED_)
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@ -25,8 +25,8 @@
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double
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RandomWalkMetropolisHastings::compute(VectorView &mhLogPostDens, MatrixView &mhParams, Matrix &steadyState,
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Vector &estParams, Vector &deepParams, const MatrixConstView &data, Matrix &Q, Matrix &H,
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const size_t presampleStart, int &info, const size_t startDraw, size_t nMHruns, const Matrix &Dscale,
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LogPosteriorDensity &lpd, Prior &drawDistribution, EstimatedParametersDescription &epd)
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const size_t presampleStart, int &info, const size_t startDraw, size_t nMHruns,
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LogPosteriorDensity &lpd, Proposal &pDD, EstimatedParametersDescription &epd)
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{
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//streambuf *likbuf, *drawbuf *backup;
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std::ofstream urandfilestr, drawfilestr;
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@ -43,7 +43,7 @@ RandomWalkMetropolisHastings::compute(VectorView &mhLogPostDens, MatrixView &mhP
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for (size_t run = startDraw - 1; run < nMHruns; ++run)
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{
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overbound=false;
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randMultiVar(drawDistribution, newParDraw, parDraw, Dscale, parDraw.getSize());
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pDD.draw(parDraw, newParDraw);
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for (count=0;count<parDraw.getSize();++count)
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{
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overbound=(newParDraw(count) < epd.estParams[count].lower_bound || newParDraw(count) > epd.estParams[count].upper_bound );
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@ -68,7 +68,7 @@ RandomWalkMetropolisHastings::compute(VectorView &mhLogPostDens, MatrixView &mhP
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newLogpost = -INFINITY;
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}
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}
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urand=uniform.drand();
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urand=pDD.selectionTestDraw();
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if ((newLogpost > -INFINITY) && log(urand) < newLogpost-logpost)
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{
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parDraw = newParDraw;
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@ -26,26 +26,25 @@
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#if !defined(A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_)
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#define A6BBC5E0_598E_4863_B7FF_E87320056B80__INCLUDED_
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#include "RandSampler.hh"
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#include "LogPosteriorDensity.hh"
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#include "Proposal.hh"
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class RandomWalkMetropolisHastings : public RandSampler
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class RandomWalkMetropolisHastings
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{
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private:
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UniformPrior uniform;
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Vector parDraw, newParDraw;
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public:
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RandomWalkMetropolisHastings(size_t size) :
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uniform(0.0, 0.0, 0.0, 1.0, 0.0, 1.0),
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parDraw(size), newParDraw(size)
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{
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};
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virtual ~RandomWalkMetropolisHastings(){};
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virtual double compute(VectorView &mhLogPostDens, MatrixView &mhParams, Matrix &steadyState,
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Vector &estParams, Vector &deepParams, const MatrixConstView &data, Matrix &Q, Matrix &H,
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const size_t presampleStart, int &info, const size_t startDraw, size_t nMHruns, const Matrix &Jscale,
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LogPosteriorDensity &logPosteriorDensity, Prior &drawDistribution,
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const size_t presampleStart, int &info, const size_t startDraw, size_t nMHruns,
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LogPosteriorDensity &logPosteriorDensity, Proposal &proposalDrawDistribution,
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EstimatedParametersDescription &epd);
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};
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@ -104,9 +104,9 @@ fillEstParamsInfo(const mxArray *estim_params_info, EstimatedParameter::pType ty
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int
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sampleMHMC(LogPosteriorDensity &lpd, RandomWalkMetropolisHastings &rwmh,
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Matrix &steadyState, Vector &estParams, Vector &deepParams, const MatrixConstView &data, Matrix &Q, Matrix &H,
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size_t presampleStart, int &info, const VectorConstView &nruns, size_t fblock, size_t nBlocks,
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const Matrix &Jscale, Prior &drawDistribution, EstimatedParametersDescription &epd,
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Matrix &steadyState, Vector &estParams, Vector &deepParams, const MatrixConstView &data,
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Matrix &Q, Matrix &H, size_t presampleStart, int &info, const VectorConstView &nruns,
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size_t fblock, size_t nBlocks, Proposal pdd, EstimatedParametersDescription &epd,
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const std::string &resultsFileStem, size_t console_mode, size_t load_mh_file)
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{
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enum {iMin, iMax};
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@ -382,7 +382,7 @@ sampleMHMC(LogPosteriorDensity &lpd, RandomWalkMetropolisHastings &rwmh,
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try
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{
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jsux = rwmh.compute(mhLogPostDens, mhParamDraws, steadyState, startParams, deepParams, data, Q, H,
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presampleStart, info, irun, currInitSizeArray, Jscale, lpd, drawDistribution, epd);
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presampleStart, info, irun, currInitSizeArray, lpd, pdd, epd);
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irun = currInitSizeArray;
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sux += jsux*currInitSizeArray;
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j += currInitSizeArray; //j=j+1;
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@ -715,18 +715,13 @@ logMCMCposterior(const VectorConstView &estParams, const MatrixConstView &data,
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GaussianPrior drawGaussDist01(0.0, 1.0, -INFINITY, INFINITY, 0.0, 1.0);
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// get Jscale = diag(bayestopt_.jscale);
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const mxArray *bayestopt_ = mexGetVariablePtr("global", "bayestopt_");
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Matrix Jscale(n_estParams);
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Matrix Dscale(n_estParams);
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//Vector vJscale(n_estParams);
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Jscale.setAll(0.0);
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VectorConstView vJscale(mxGetPr(mxGetField(bayestopt_, 0, "jscale")), n_estParams, 1);
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for (size_t i = 0; i < n_estParams; i++)
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Jscale(i, i) = vJscale(i);
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blas::gemm("N", "N", 1.0, D, Jscale, 0.0, Dscale);
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const Matrix Jscale(n_estParams);
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const VectorConstView vJscale(mxGetPr(mxGetField(bayestopt_, 0, "jscale")), n_estParams, 1);
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Proposal pdd(vJscale,D);
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//sample MHMCMC draws and get get last line run in the last MH block sub-array
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int lastMHblockArrayLine = sampleMHMC(lpd, rwmh, steadyState, estParams2, deepParams, data, Q, H, presample, info,
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nMHruns, fblock, nBlocks, Dscale, drawGaussDist01, epd, resultsFileStem, console_mode, load_mh_file);
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nMHruns, fblock, nBlocks, pdd, epd, resultsFileStem, console_mode, load_mh_file);
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// Cleanups
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for (std::vector<EstimatedParameter>::iterator it = estParamsInfo.begin();
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@ -136,7 +136,7 @@ oldoptions_console_mode=options_.console_mode;
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record.Seeds(b).Unifor = rand('state');
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end
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% calculate draws and get last line run in the last MH block sub-array
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irun = logMHMCMCposterior( xparam1, varargin{2}, mexext, fblck, nblck, nruns, d)
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irun = logMHMCMCposterior( xparam1, varargin{2}, mexext, fblck, nblck, nruns, vv)
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if irun<0
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error('Error in logMHMCMCposterior');
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end
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