265 lines
10 KiB
Matlab
265 lines
10 KiB
Matlab
function myoutput = independent_metropolis_hastings_core(myinputs,fblck,nblck,whoiam, ThisMatlab)
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% PARALLEL CONTEXT
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% The most computationally intensive portion of code in
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% independent_metropolis_hastings (the 'for xxx = fblck:nblck' cycle).
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% See the comment in random_walk_metropolis_hastings_core.m funtion.
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%
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% INPUTS
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% See See the comment in random_walk_metropolis_hastings_core.m funtion.
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% OUTPUTS
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% See See the comment in random_walk_metropolis_hastings_core.m funtion.
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%
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% ALGORITHM
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% Portion of Independing Metropolis-Hastings.
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%
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% SPECIAL REQUIREMENTS.
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% None.
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%
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% Copyright (C) 2006-2013 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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if nargin<4,
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whoiam=0;
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end
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global bayestopt_ estim_params_ options_ M_ oo_ objective_function_penalty_base
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% Reshape 'myinputs' for local computation.
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% In order to avoid confusion in the name space, the instruction struct2local(myinputs) is replaced by:
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TargetFun=myinputs.TargetFun;
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ProposalFun=myinputs.ProposalFun;
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xparam1=myinputs.xparam1;
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vv=myinputs.vv;
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mh_bounds=myinputs.mh_bounds;
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ix2=myinputs.ix2;
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ilogpo2=myinputs.ilogpo2;
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ModelName=myinputs.ModelName;
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fline=myinputs.fline;
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npar=myinputs.npar;
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nruns=myinputs.nruns;
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NewFile=myinputs.NewFile;
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MAX_nruns=myinputs.MAX_nruns;
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d=myinputs.d;
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InitSizeArray=myinputs.InitSizeArray;
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record=myinputs.record;
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varargin=myinputs.varargin;
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if whoiam
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Parallel=myinputs.Parallel;
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% initialize persistent variables in priordens()
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priordens(xparam1',bayestopt_.pshape,bayestopt_.p6,bayestopt_.p7, ...
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bayestopt_.p3,bayestopt_.p4,1);
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end
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% (re)Set the penalty.
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objective_function_penalty_base = Inf;
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MhDirectoryName = CheckPath('metropolis',M_.dname);
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OpenOldFile = ones(nblck,1);
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if strcmpi(ProposalFun,'rand_multivariate_normal')
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n = npar;
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ProposalDensity = 'multivariate_normal_pdf';
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elseif strcmpi(ProposalFun,'rand_multivariate_student')
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n = options_.student_degrees_of_freedom;
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ProposalDensity = 'multivariate_student_pdf';
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end
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% load([MhDirectoryName '/' ModelName '_mh_history.mat'],'record');
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%%%%
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%%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
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%%%%
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if any(isnan(bayestopt_.jscale))
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if exist([ModelName '_optimal_mh_scale_parameter.mat'])% This file is created by mode_compute=6.
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load([ModelName '_optimal_mh_scale_parameter'])
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proposal_covariance = d*Scale;
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else
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error('mh:: Something is wrong. I can''t figure out the value of the scale parameter.')
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end
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else
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proposal_covariance = d*diag(bayestopt_.jscale);
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end
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jloop=0;
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for b = fblck:nblck,
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jloop=jloop+1;
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try
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% this will not work if the master uses a random generator not
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% available in the slave (different Matlab version or
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% Matlab/Octave cluster). Therefor the trap.
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% this set the random generator type (the seed is useless but
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% needed by the function)
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set_dynare_seed(options_.DynareRandomStreams.algo,...
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options_.DynareRandomStreams.seed);
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% this set the state
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set_dynare_random_generator_state(record.Seeds(b).Unifor, ...
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record.Seeds(b).Normal);
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catch
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% if the state set by master is incompatible with the slave, we
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% only reseed
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set_dynare_seed(options_.DynareRandomStreams.seed+b);
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end
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if (options_.load_mh_file~=0) && (fline(b)>1) && OpenOldFile(b)
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load([pwd filesep MhDirectoryName filesep ModelName '_mh' int2str(NewFile(b)) ...
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'_blck' int2str(b) '.mat'])
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x2 = [x2;zeros(InitSizeArray(b)-fline(b)+1,npar)];
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logpo2 = [logpo2;zeros(InitSizeArray(b)-fline(b)+1,1)];
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OpenOldFile(b) = 0;
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else
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x2 = zeros(InitSizeArray(b),npar);
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logpo2 = zeros(InitSizeArray(b),1);
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end
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if exist('OCTAVE_VERSION') || options_.console_mode
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diary off
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disp(' ')
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elseif whoiam
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% keyboard;
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waitbarString = ['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...'];
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% waitbarTitle=['Metropolis-Hastings ',options_.parallel(ThisMatlab).ComputerName];
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if options_.parallel(ThisMatlab).Local,
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waitbarTitle=['Local '];
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else
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waitbarTitle=[options_.parallel(ThisMatlab).ComputerName];
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end
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fMessageStatus(0,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab));
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else,
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hh = waitbar(0,['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...']);
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set(hh,'Name','Metropolis-Hastings');
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end
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isux = 0;
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jsux = 0;
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irun = fline(b);
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j = 1;
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while j <= nruns(b)
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par = feval(ProposalFun, xparam1, proposal_covariance, n);
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if all( par(:) > mh_bounds(:,1) ) && all( par(:) < mh_bounds(:,2) )
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try
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logpost = - feval(TargetFun, par(:),varargin{:});
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catch,
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logpost = -inf;
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end
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else
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logpost = -inf;
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end
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r = logpost - ilogpo2(b) + ...
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log(feval(ProposalDensity, ix2(b,:), xparam1, proposal_covariance, n)) - ...
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log(feval(ProposalDensity, par, xparam1, proposal_covariance, n));
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if (logpost > -inf) && (log(rand) < r)
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x2(irun,:) = par;
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ix2(b,:) = par;
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logpo2(irun) = logpost;
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ilogpo2(b) = logpost;
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isux = isux + 1;
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jsux = jsux + 1;
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else
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x2(irun,:) = ix2(b,:);
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logpo2(irun) = ilogpo2(b);
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end
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prtfrc = j/nruns(b);
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if exist('OCTAVE_VERSION') || options_.console_mode
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if mod(j, 10) == 0
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if exist('OCTAVE_VERSION')
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if (whoiam==0),
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printf('MH: Computing Metropolis-Hastings (chain %d/%d): %3.f%% done, acception rate: %3.f%%\r', b, nblck, 100 * prtfrc, 100 * isux / j);
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end
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else
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fprintf(' MH: Computing Metropolis-Hastings (chain %d/%d): %3.f \b%% done, acception rate: %3.f \b%%\r', b, nblck, 100 * prtfrc, 100 * isux / j);
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end
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end
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if mod(j,50)==0 && whoiam,
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% keyboard;
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waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) '), ' sprintf('accept. %3.f%%%%', 100 * isux/j)];
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fMessageStatus(prtfrc,whoiam,waitbarString, '', options_.parallel(ThisMatlab))
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end
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else
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if mod(j, 3)==0 && ~whoiam
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waitbar(prtfrc,hh,[ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)]);
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elseif mod(j,50)==0 && whoiam,
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% keyboard;
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waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)];
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fMessageStatus(prtfrc,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab))
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end
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end
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if (irun == InitSizeArray(b)) || (j == nruns(b)) % Now I save the simulations
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save([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'],'x2','logpo2');
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fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
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fprintf(fidlog,['\n']);
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fprintf(fidlog,['%% Mh' int2str(NewFile(b)) 'Blck' int2str(b) ' (' datestr(now,0) ')\n']);
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fprintf(fidlog,' \n');
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fprintf(fidlog,[' Number of simulations.: ' int2str(length(logpo2)) '\n']);
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fprintf(fidlog,[' Acceptation rate......: ' num2str(jsux/length(logpo2)) '\n']);
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fprintf(fidlog,[' Posterior mean........:\n']);
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for i=1:length(x2(1,:))
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fprintf(fidlog,[' params:' int2str(i) ': ' num2str(mean(x2(:,i))) '\n']);
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end
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fprintf(fidlog,[' log2po:' num2str(mean(logpo2)) '\n']);
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fprintf(fidlog,[' Minimum value.........:\n']);;
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for i=1:length(x2(1,:))
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fprintf(fidlog,[' params:' int2str(i) ': ' num2str(min(x2(:,i))) '\n']);
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end
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fprintf(fidlog,[' log2po:' num2str(min(logpo2)) '\n']);
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fprintf(fidlog,[' Maximum value.........:\n']);
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for i=1:length(x2(1,:))
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fprintf(fidlog,[' params:' int2str(i) ': ' num2str(max(x2(:,i))) '\n']);
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end
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fprintf(fidlog,[' log2po:' num2str(max(logpo2)) '\n']);
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fprintf(fidlog,' \n');
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fclose(fidlog);
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jsux = 0;
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if j == nruns(b) % I record the last draw...
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record.LastParameters(b,:) = x2(end,:);
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record.LastLogPost(b) = logpo2(end);
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end
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% size of next file in chain b
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InitSizeArray(b) = min(nruns(b)-j,MAX_nruns);
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% initialization of next file if necessary
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if InitSizeArray(b)
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x2 = zeros(InitSizeArray(b),npar);
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logpo2 = zeros(InitSizeArray(b),1);
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NewFile(b) = NewFile(b) + 1;
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irun = 0;
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end
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end
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j=j+1;
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irun = irun + 1;
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end% End of the simulations for one mh-block.
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record.AcceptationRates(b) = isux/j;
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if exist('OCTAVE_VERSION') || options_.console_mode
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printf('\n');
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diary on
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elseif ~whoiam
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close(hh);
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end
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[record.Seeds(b).Unifor, record.Seeds(b).Normal] = get_dynare_random_generator_state();
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OutputFileName(jloop,:) = {[MhDirectoryName,filesep], [ModelName '_mh*_blck' int2str(b) '.mat']};
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end% End of the loop over the mh-blocks.
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myoutput.record = record;
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myoutput.irun = irun;
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myoutput.NewFile = NewFile;
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myoutput.OutputFileName = OutputFileName;
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