228 lines
9.3 KiB
Matlab
228 lines
9.3 KiB
Matlab
function [y, y_] = local_state_space_iteration_2(yhat, epsilon, ghx, ghu, constant, ghxx, ghuu, ghxu, a, b, c) % --*-- Unitary tests --*--
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% Given the demeaned states (yhat) and structural innovations (epsilon), this routine computes the level of selected endogenous variables when the
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% model is approximated by an order two taylor expansion around the deterministic steady state. Depending on the number of input/output
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% argument the pruning algorithm advocated by C. Sims is used or not (this version should not be used if the selected endogenous variables
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% are not the states of the model).
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%
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% INPUTS
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% - yhat [double] n×1 vector, initial condition for the state variables (centered).
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% - epsilon [double] q×1 vector, innovations.
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% - ghx [double] m×n matrix, restricted dr.ghx where we only consider the lines corresponding to a subset of endogenous variables.
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% - ghu [double] m×q matrix, restricted dr.ghu where we only consider the lines corresponding to a subset of endogenous variables.
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% - constant [double] m×1 vector, deterministic steady state plus second order correction for a subset of endogenous variables.
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% - ghxx [double] m×n² matrix, restricted dr.ghxx where we only consider the lines corresponding to a subset of endogenous variables.
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% - ghuu [double] m×q² matrix, restricted dr.ghuu where we only consider the lines corresponding to a subset of endogenous variables.
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% - ghxu [double] m×nq matrix, restricted dr.ghxu where we only consider the lines corresponding to a subset of endogenous variables.
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% - yhat_ [double] [OPTIONAL] n×1 vector, initial condition for the state variables (centered) related to pruning.
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% - ss [double] [OPTIONAL] n×1 vector, deterministic steady state for the state variables.
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% - dummy [double] scalar, number of threads used.
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%
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% OUTPUTS
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% - y [double] m×1 vector, (subset of the) endogenous variables.
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% - y_ [double] n×1 vector, update of the latent variables needed for the pruning version (first order update).
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%
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% REMARKS
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% 1. If the function has more than nine input arguments (pruning) then it must have two output arguments (otherwise only one input).
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% 2. Ninth input argument is not used, it is here only to have a common interface with the mex version.
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% Copyright © 2011-2022 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 <https://www.gnu.org/licenses/>.
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if nargin==9
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pruning = false;
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if nargout>1
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error('local_state_space_iteration_2:: Numbers of input and output argument are inconsistent.')
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end
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elseif nargin==11
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pruning = true;
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yhat_ = a;
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ss = b;
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if nargout~=2
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error('local_state_space_iteration_2:: Numbers of input and output argument are inconsistent.')
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end
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else
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error('local_state_space_iteration_2:: Wrong number of input arguments.')
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end
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if pruning
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for i =1:size(yhat,2)
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y(:,i) = constant + ghx*yhat(:,i) + ghu*epsilon(:,i) ...
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+ A_times_B_kronecker_C(.5*ghxx, yhat_(:,i)) ...
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+ A_times_B_kronecker_C(.5*ghuu, epsilon(:,i)) ...
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+ A_times_B_kronecker_C(ghxu, yhat_(:,i), epsilon(:,i));
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end
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y_ = ghx*yhat_+ghu*epsilon;
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y_ = bsxfun(@plus, y_, ss);
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else
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for i =1:size(yhat,2)
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y(:,i) = constant + ghx*yhat(:,i) + ghu*epsilon(:,i) ...
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+ A_times_B_kronecker_C(.5*ghxx, yhat(:,i)) ...
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+ A_times_B_kronecker_C(.5*ghuu, epsilon(:,i)) ...
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+ A_times_B_kronecker_C(ghxu, yhat(:,i), epsilon(:,i));
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end
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end
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return
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%@test:1
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n = 2;
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q = 3;
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yhat = zeros(n,1);
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epsilon = zeros(q,1);
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ghx = rand(n,n);
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ghu = rand(n,q);
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constant = ones(n,1);
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ghxx = rand(n,n*n);
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ghuu = rand(n,q*q);
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ghxu = rand(n,n*q);
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yhat_ = zeros(n,1);
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ss = ones(n,1);
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addpath(sprintf('%s/missing/mex/local_state_space_iterations', fileparts(which('dynare'))))
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% Call the tested routine.
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for i=1:10
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y1 = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,1);
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[y2,y2_] = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,yhat_,ss,1);
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end
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rmpath(sprintf('%s/missing/mex/local_state_space_iterations', fileparts(which('dynare'))))
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% Check the results.
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t(1) = dassert(y1,ones(n,1));
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t(2) = dassert(y2,ones(n,1));
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t(3) = dassert(y2_,ones(n,1));
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T = all(t);
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%@eof:1
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%@test:2
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old_path = pwd;
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cd([fileparts(which('dynare')) '/../tests/particle']);
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load dsgebase2data;
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cd(old_path);
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n = length(state_variables_idx);
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q = size(ReducedForm.ghu,2);
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yhatinit = randn(n,1);
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epsilon = randn(q,2);
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ghx = ReducedForm.ghx(state_variables_idx,:);
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ghu = ReducedForm.ghu(state_variables_idx,:);
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constant = ReducedForm.constant(state_variables_idx,:);
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ghxx = ReducedForm.ghxx(state_variables_idx,:);
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ghuu = ReducedForm.ghuu(state_variables_idx,:);
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ghxu = ReducedForm.ghxu(state_variables_idx,:);
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yhatinit_ = randn(n,1);
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ss = ReducedForm.state_variables_steady_state;
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t = true(6,1);
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% Call the tested routine (matlab).
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addpath(sprintf('%s/missing/mex/local_state_space_iterations', fileparts(which('dynare'))))
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try
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yhat1 = local_state_space_iteration_2(yhatinit, epsilon(:,1), ghx, ghu, constant, ghxx, ghuu, ghxu, 1);
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yhat1 = local_state_space_iteration_2(yhat1, epsilon(:,2), ghx, ghu, constant, ghxx, ghuu, ghxu, 1);
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catch
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t(1) = false;
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end
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try
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[yhat2, yhat2_] = local_state_space_iteration_2(yhatinit, epsilon(:,1), ghx, ghu, constant, ghxx, ghuu, ghxu, yhatinit_, ss, 1);
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[yhat2, yhat2_] = local_state_space_iteration_2(yhat2, epsilon(:,2), ghx, ghu, constant, ghxx, ghuu, ghxu, yhat2_, ss, 1);
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catch
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t(2) = false;
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end
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rmpath(sprintf('%s/missing/mex/local_state_space_iterations', fileparts(which('dynare'))))
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% Call the tested routine (mex).
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try
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yhat3 = local_state_space_iteration_2(yhatinit, epsilon(:,1), ghx, ghu, constant, ghxx, ghuu, ghxu, 1);
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yhat3 = local_state_space_iteration_2(yhat3, epsilon(:,2), ghx, ghu, constant, ghxx, ghuu, ghxu, 1);
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catch
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t(3) = false;
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end
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try
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[yhat4, yhat4_] = local_state_space_iteration_2(yhatinit, epsilon(:,1), ghx, ghu, constant, ghxx, ghuu, ghxu, yhatinit_, ss, 1);
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[yhat4, yhat4_] = local_state_space_iteration_2(yhat4, epsilon(:,2), ghx, ghu, constant, ghxx, ghuu, ghxu, yhat4_, ss, 1);
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catch
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t(4) = false;
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end
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t(5) = max(abs(yhat1-yhat3))<1e-10; % Compare matlab and mex routines without pruning.
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t(6) = max(abs(yhat2-yhat4))<1e-10; % Compare matlab and mex routines with pruning.
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% Check the results.
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T = all(t);
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%@eof:2
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%@test:3
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n = 2;
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q = 3;
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yhat = .01*randn(n,1);
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epsilon = .001*randn(q,1);
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ghx = rand(n,n);
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ghu = rand(n,q);
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constant = ones(n,1);
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ghxx = rand(n,n*n);
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ghuu = rand(n,q*q);
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ghxu = rand(n,n*q);
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yhat_ = zeros(n,1);
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ss = ones(n,1);
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% Call the tested routine (mex version).
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y1a = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,1);
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[y2a,y2a_] = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,yhat_,ss,1);
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% Call the tested routine (matlab version)
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addpath(sprintf('%s/missing/mex/local_state_space_iterations', fileparts(which('dynare'))))
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y1b = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,1);
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[y2b,y2b_] = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,yhat_,ss,1);
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rmpath(sprintf('%s/missing/mex/local_state_space_iterations', fileparts(which('dynare'))))
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% Check the results.
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t(1) = max(abs(y1a-y1b))<1e-6;
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t(2) = max(abs(y2a-y2b))<1e-6;
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t(3) = max(abs(y2a_-y2b_))<1e-6;
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T = all(t);
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%@eof:3
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%@test:4
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% TIMING TEST (parallelization with openmp)
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old_path = pwd;
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cd([fileparts(which('dynare')) '/../tests/particle']);
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load dsgebase2data;
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cd(old_path);
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n = length(state_variables_idx);
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q = size(ReducedForm.ghu,2);
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yhat = randn(n,10000000);
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epsilon = .01*randn(q,10000000);
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ghx = ReducedForm.ghx(state_variables_idx,:);
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ghu = ReducedForm.ghu(state_variables_idx,:);
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constant = ReducedForm.constant(state_variables_idx,:);
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ghxx = ReducedForm.ghxx(state_variables_idx,:);
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ghuu = ReducedForm.ghuu(state_variables_idx,:);
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ghxu = ReducedForm.ghxu(state_variables_idx,:);
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yhatinit_ = randn(n,1);
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ss = ReducedForm.state_variables_steady_state;
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yhat_ = randn(n,10000000);
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t = NaN(4,1);
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tic, for i=1:10, y1 = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,1); end
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t1 = toc;
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tic, for i=1:10, y2 = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,2); end
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t2 = toc;
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t(1) = dassert(y1,y2,1e-15); clear('y1');
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tic, for i=1:10, y3 = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,3); end
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t3 = toc;
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t(2) = dassert(y2,y3,1e-15); clear('y2');
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tic, for i=1:10, y4 = local_state_space_iteration_2(yhat,epsilon,ghx,ghu,constant,ghxx,ghuu,ghxu,4); end
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t4 = toc;
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t(3) = dassert(y4,y3,1e-15); clear('y3','y4');
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t(4) = (t1>t2) && (t2>t3) && (t3>t4);
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if ~t(4)
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disp('Timmings:')
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[t1, t2, t3, t4]
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end
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% Check the results.
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T = all(t);
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%@eof:4 |