Commit e6a59cd2 authored by ratto's avatar ratto
Browse files

Parallelized version of independent MH.

git-svn-id: https://www.dynare.org/svn/dynare/trunk@2951 ac1d8469-bf42-47a9-8791-bf33cf982152
parent 2ac1194d
function independent_metropolis_hastings(TargetFun,ProposalFun,xparam1,vv,mh_bounds,varargin)
% Independent Metropolis-Hastings algorithm.
% Independent Metropolis-Hastings algorithm.
%
% INPUTS
% o TargetFun [char] string specifying the name of the objective
......@@ -10,10 +11,10 @@ function independent_metropolis_hastings(TargetFun,ProposalFun,xparam1,vv,mh_bou
% o varargin list of argument following mh_bounds
%
% OUTPUTS
% None
% None
%
% ALGORITHM
% Metropolis-Hastings.
% ALGORITHM
% Metropolis-Hastings.
%
% SPECIAL REQUIREMENTS
% None.
......@@ -35,119 +36,88 @@ function independent_metropolis_hastings(TargetFun,ProposalFun,xparam1,vv,mh_bou
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
global M_ options_ bayestopt_
global M_ options_ bayestopt_ estim_params_ oo_
%%%%
%%%% Initialization of the independent metropolis-hastings chains.
%%%%
[ ix2, ilogpo2, ModelName, MhDirectoryName, fblck, fline, npar, nblck, nruns, NewFile, MAX_nruns, d ] = ...
metropolis_hastings_initialization(TargetFun,xparam1,vv,mh_bounds,varargin{:});
xparam1 = transpose(xparam1);
OpenOldFile = ones(nblck,1);
if strcmpi(ProposalFun,'rand_multivariate_normal')
n = npar;
ProposalDensity = 'multivariate_normal_pdf';
elseif strcmpi(ProposalFun,'rand_multivariate_student')
n = options_.student_degrees_of_freedom;
ProposalDensity = 'multivariate_student_pdf';
end
load([MhDirectoryName '/' ModelName '_mh_history'],'record');
%%%%
%%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
%%%%
InitSizeArray = min([MAX_nruns*ones(nblck) nruns],[],2);
jscale = diag(bayestopt_.jscale);
for b = fblck:nblck
randn('state',record.Seeds(b).Normal);
rand('state',record.Seeds(b).Unifor);
if (options_.load_mh_file~=0) & (fline(b)>1) & OpenOldFile(b)
load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) ...
'_blck' int2str(b) '.mat'])
x2 = [x2;zeros(InitSizeArray(b)-fline(b)+1,npar)];
logpo2 = [logpo2;zeros(InitSizeArray(b)-fline(b)+1,1)];
OpenOldFile(b) = 0;
else
x2 = zeros(InitSizeArray(b),npar);
logpo2 = zeros(InitSizeArray(b),1);
metropolis_hastings_initialization(TargetFun, xparam1, vv, mh_bounds, varargin{:});
xparam1 = transpose(xparam1);
InitSizeArray = min([repmat(MAX_nruns,nblck,1) fline+nruns-1],[],2);
load([MhDirectoryName '/' ModelName '_mh_history.mat'],'record');
localVars = struct('TargetFun', TargetFun, ...
'ProposalFun', ProposalFun, ...
'xparam1', xparam1, ...
'vv', vv, ...
'mh_bounds', mh_bounds, ...
'ix2', ix2, ...
'ilogpo2', ilogpo2, ...
'ModelName', ModelName, ...
'fline', fline, ...
'npar', npar, ...
'nruns', nruns, ...
'NewFile', NewFile, ...
'MAX_nruns', MAX_nruns, ...
'd', d);
localVars.InitSizeArray=InitSizeArray;
localVars.record=record;
localVars.varargin=varargin;
% tic,
if isnumeric(options_.parallel),% | isunix, % for the moment exclude unix platform from parallel implementation
fout = independent_metropolis_hastings_core(localVars, fblck, nblck, 0);
record = fout.record;
else
% global variables for parallel routines
globalVars = struct('M_',M_, ...
'options_', options_, ...
'bayestopt_', bayestopt_, ...
'estim_params_', estim_params_, ...
'oo_', oo_);
% which files have to be copied to run remotely
NamFileInput(1,:) = {'',[ModelName '_static.m']};
NamFileInput(2,:) = {'',[ModelName '_dynamic.m']};
if options_.steadystate_flag,
NamFileInput(length(NamFileInput)+1,:)={'',[ModelName '_steadystate.m']};
end
if (options_.load_mh_file~=0) & any(fline>1) ,
NamFileInput(length(NamFileInput)+1,:)={[M_.dname '/metropolis/'],[ModelName '_mh' int2str(NewFile(1)) '_blck*.mat']};
end
hh = waitbar(0,['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(nblck) ')...']);
set(hh,'Name','Metropolis-Hastings');
isux = 0;
jsux = 0;
irun = fline(b);
j = 1;
while j <= nruns(b)
par = feval(ProposalFun, xparam1, d * jscale, n);
if all(par(:)>mh_bounds(:,1)) && all(par(:)<mh_bounds(:,2))
logpost = - feval(TargetFun,par(:),varargin{:});
else
logpost = -inf;
end
r = logpost - ilogpo2(b) + ...
log(feval(ProposalDensity, ix2(b,:), xparam1, d, n)) - ...
log(feval(ProposalDensity, par, xparam1, d, n));
if (logpost > -inf) && (log(rand) < r)
x2(irun,:) = par;
ix2(b,:) = par;
logpo2(irun) = logpost;
ilogpo2(b) = logpost;
isux = isux + 1;
jsux = jsux + 1;
else
x2(irun,:) = ix2(b,:);
logpo2(irun) = ilogpo2(b);
end
prtfrc = j/nruns(b);
waitbar(prtfrc,hh,[ '(' int2str(b) '/' int2str(nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)]);
if (irun == InitSizeArray(b)) | (j == nruns(b)) % Now I save the simulations
save([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b)],'x2','logpo2');
InitSizeArray(b) = min(nruns(b)-j,MAX_nruns);
fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
fprintf(fidlog,['\n']);
fprintf(fidlog,['%% Mh' int2str(NewFile(b)) 'Blck' int2str(b) ' (' datestr(now,0) ')\n']);
fprintf(fidlog,' \n');
fprintf(fidlog,[' Number of simulations.: ' int2str(length(logpo2)) '\n']);
fprintf(fidlog,[' Acceptation rate......: ' num2str(jsux/length(logpo2)) '\n']);
fprintf(fidlog,[' Posterior mean........:\n']);
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(mean(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(mean(logpo2)) '\n']);
fprintf(fidlog,[' Minimum value.........:\n']);;
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(min(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(min(logpo2)) '\n']);
fprintf(fidlog,[' Maximum value.........:\n']);
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(max(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(max(logpo2)) '\n']);
fprintf(fidlog,' \n');
fclose(fidlog);
jsux = 0;
if j == nruns(b) % I record the last draw...
record.LastParameters(b,:) = x2(end,:);
record.LastLogLiK(b) = logpo2(end);
end
if InitSizeArray(b)
x2 = zeros(InitSizeArray(b),npar);
logpo2 = zeros(InitSizeArray(b),1);
NewFile(b) = NewFile(b) + 1;
irun = 0;
else% InitSizeArray is equal to zero because we are at the end of an mc chain.
InitSizeArray(b) = min(nruns(b),MAX_nruns);
end
end
j=j+1;
irun = irun + 1;
end% End of the simulations for one mh-block.
record.AcceptationRates(b) = isux/j;
close(hh);
record.Seeds(b).Normal = randn('state');
record.Seeds(b).Unifor = rand('state');
end% End of the loop over the mh-blocks.
save([MhDirectoryName '/' ModelName '_mh_history'],'record');
% from where to get back results
% NamFileOutput(1,:) = {[M_.dname,'/metropolis/'],'*.*'};
[fout, nBlockPerCPU, totCPU] = masterParallel(options_.parallel, fblck, nblck,NamFileInput,'independent_metropolis_hastings_core', localVars, globalVars);
for j=1:totCPU,
offset = sum(nBlockPerCPU(1:j-1))+fblck-1;
record.LastLogLiK(offset+1:sum(nBlockPerCPU(1:j)))=fout(j).record.LastLogLiK(offset+1:sum(nBlockPerCPU(1:j)));
record.LastParameters(offset+1:sum(nBlockPerCPU(1:j)),:)=fout(j).record.LastParameters(offset+1:sum(nBlockPerCPU(1:j)),:);
record.AcceptationRates(offset+1:sum(nBlockPerCPU(1:j)))=fout(j).record.AcceptationRates(offset+1:sum(nBlockPerCPU(1:j)));
record.Seeds(offset+1:sum(nBlockPerCPU(1:j)))=fout(j).record.Seeds(offset+1:sum(nBlockPerCPU(1:j)));
end
end
irun = fout(1).irun;
NewFile = fout(1).NewFile;
% ComptationalTime=toc,
% record.Seeds.Normal = randn('state');
% record.Seeds.Unifor = rand('state');
save([MhDirectoryName '/' ModelName '_mh_history.mat'],'record');
disp(['MH: Number of mh files : ' int2str(NewFile(1)) ' per block.'])
disp(['MH: Total number of generated files : ' int2str(NewFile(1)*nblck) '.'])
disp(['MH: Total number of iterations : ' int2str((NewFile(1)-1)*MAX_nruns+irun-1) '.'])
disp('MH: average acceptation rate per chain : ')
disp(record.AcceptationRates);
disp(' ')
\ No newline at end of file
function myoutput = independent_metropolis_hastings_core(myinputs,fblck,nblck,whoiam, ThisMatlab)
% Copyright (C) 2006-2008 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare 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
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if nargin<4,
whoiam=0;
end
global bayestopt_ estim_params_ options_ M_ oo_
struct2local(myinputs);
MhDirectoryName = CheckPath('metropolis');
OpenOldFile = ones(nblck,1);
if strcmpi(ProposalFun,'rand_multivariate_normal')
n = npar;
ProposalDensity = 'multivariate_normal_pdf';
elseif strcmpi(ProposalFun,'rand_multivariate_student')
n = options_.student_degrees_of_freedom;
ProposalDensity = 'multivariate_student_pdf';
end
% load([MhDirectoryName '/' ModelName '_mh_history.mat'],'record');
%%%%
%%%% NOW i run the (nblck-fblck+1) metropolis-hastings chains
%%%%
jscale = diag(bayestopt_.jscale);
jloop=0;
for b = fblck:nblck,
jloop=jloop+1;
randn('state',record.Seeds(b).Normal);
rand('state',record.Seeds(b).Unifor);
if (options_.load_mh_file~=0) & (fline(b)>1) & OpenOldFile(b)
load(['./' MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) ...
'_blck' int2str(b) '.mat'])
x2 = [x2;zeros(InitSizeArray(b)-fline(b)+1,npar)];
logpo2 = [logpo2;zeros(InitSizeArray(b)-fline(b)+1,1)];
OpenOldFile(b) = 0;
else
x2 = zeros(InitSizeArray(b),npar);
logpo2 = zeros(InitSizeArray(b),1);
end
if exist('OCTAVE_VERSION')
diary off;
elseif whoiam
% keyboard;
waitbarString = ['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...'];
% waitbarTitle=['Metropolis-Hastings ',options_.parallel(ThisMatlab).PcName];
if options_.parallel(ThisMatlab).Local,
waitbarTitle=['Local '];
else
waitbarTitle=[options_.parallel(ThisMatlab).PcName];
end
fMessageStatus(0,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab), MasterName, DyMo);
else,
hh = waitbar(0,['Please wait... Metropolis-Hastings (' int2str(b) '/' int2str(options_.mh_nblck) ')...']);
set(hh,'Name','Metropolis-Hastings');
end
isux = 0;
jsux = 0;
irun = fline(b);
j = 1;
while j <= nruns(b)
par = feval(ProposalFun, xparam1, d * jscale, n);
if all( par(:) > mh_bounds(:,1) ) & all( par(:) < mh_bounds(:,2) )
logpost = - feval(TargetFun, par(:),varargin{:});
else
logpost = -inf;
end
r = logpost - ilogpo2(b) + ...
log(feval(ProposalDensity, ix2(b,:), xparam1, d, n)) - ...
log(feval(ProposalDensity, par, xparam1, d, n));
if (logpost > -inf) && (log(rand) < r)
x2(irun,:) = par;
ix2(b,:) = par;
logpo2(irun) = logpost;
ilogpo2(b) = logpost;
isux = isux + 1;
jsux = jsux + 1;
else
x2(irun,:) = ix2(b,:);
logpo2(irun) = ilogpo2(b);
end
prtfrc = j/nruns(b);
if exist('OCTAVE_VERSION')
if mod(j, 10) == 0,
printf('MH: Computing Metropolis-Hastings (chain %d/%d): %3.f%% done, acception rate: %3.f%%\r', b, nblck, 100 * prtfrc, 100 * isux / j);
end
if mod(j,50)==0 & whoiam,
% keyboard;
waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) '), ' sprintf('accept. %3.f%%%%', 100 * isux/j)];
fMessageStatus(prtfrc,whoiam,waitbarString, '', options_.parallel(ThisMatlab), MasterName, DyMo)
end
else
if mod(j, 3)==0 & ~whoiam
waitbar(prtfrc,hh,[ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)]);
elseif mod(j,50)==0 & whoiam,
% keyboard;
waitbarString = [ '(' int2str(b) '/' int2str(options_.mh_nblck) ') ' sprintf('%f done, acceptation rate %f',prtfrc,isux/j)];
fMessageStatus(prtfrc,whoiam,waitbarString, waitbarTitle, options_.parallel(ThisMatlab), MasterName, DyMo)
end
end
if (irun == InitSizeArray(b)) | (j == nruns(b)) % Now I save the simulations
save([MhDirectoryName '/' ModelName '_mh' int2str(NewFile(b)) '_blck' int2str(b) '.mat'],'x2','logpo2');
fidlog = fopen([MhDirectoryName '/metropolis.log'],'a');
fprintf(fidlog,['\n']);
fprintf(fidlog,['%% Mh' int2str(NewFile(b)) 'Blck' int2str(b) ' (' datestr(now,0) ')\n']);
fprintf(fidlog,' \n');
fprintf(fidlog,[' Number of simulations.: ' int2str(length(logpo2)) '\n']);
fprintf(fidlog,[' Acceptation rate......: ' num2str(jsux/length(logpo2)) '\n']);
fprintf(fidlog,[' Posterior mean........:\n']);
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(mean(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(mean(logpo2)) '\n']);
fprintf(fidlog,[' Minimum value.........:\n']);;
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(min(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(min(logpo2)) '\n']);
fprintf(fidlog,[' Maximum value.........:\n']);
for i=1:length(x2(1,:))
fprintf(fidlog,[' params:' int2str(i) ': ' num2str(max(x2(:,i))) '\n']);
end
fprintf(fidlog,[' log2po:' num2str(max(logpo2)) '\n']);
fprintf(fidlog,' \n');
fclose(fidlog);
jsux = 0;
if j == nruns(b) % I record the last draw...
record.LastParameters(b,:) = x2(end,:);
record.LastLogLiK(b) = logpo2(end);
end
% size of next file in chain b
InitSizeArray(b) = min(nruns(b)-j,MAX_nruns);
% initialization of next file if necessary
if InitSizeArray(b)
x2 = zeros(InitSizeArray(b),npar);
logpo2 = zeros(InitSizeArray(b),1);
NewFile(b) = NewFile(b) + 1;
irun = 0;
end
end
j=j+1;
irun = irun + 1;
end% End of the simulations for one mh-block.
record.AcceptationRates(b) = isux/j;
if exist('OCTAVE_VERSION')
printf('\n');
diary on;
elseif ~whoiam
close(hh);
end
record.Seeds(b).Normal = randn('state');
record.Seeds(b).Unifor = rand('state');
OutputFileName(jloop,:) = {[MhDirectoryName,filesep], [ModelName '_mh*_blck' int2str(b) '.mat']};
end% End of the loop over the mh-blocks.
myoutput.record = record;
myoutput.irun = irun;
myoutput.NewFile = NewFile;
myoutput.OutputFileName = OutputFileName;
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