Merge branch 'logarithmic_reduction_fortran' into 'master'
Implements a logarithmic reduction Fortran routine and the associated test See merge request Dynare/dynare!2089bgp-dev
Sébastien Villemot
commit
39c561db96
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@ -108,7 +108,7 @@ if (nargin == 5 && ~isempty(ch) )
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if (res > cvg_tol)
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info(1) = 403
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info(2) = log(res)
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error(['The norm of the residual is ' num2str(res) ' whereas the tolerance criterion is ' num2str(cvg_tol)]);
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dprintf('The norm of the residual is %s whereas the tolerance criterion is %s', num2str(res), num2str(cvg_tol));
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end
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end
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@ -77,20 +77,27 @@ while cc>tol && kk<=maxit
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tmp1 = (eye(n)-tmp0*[tmp0(:,n+i);tmp0(:,i)])\[tmp0(:,i)*tmp0(:,i),tmp0(:,n+i)*tmp0(:,n+i)];
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X1 = X0 + U0*tmp1(:,n+i);
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U1 = U0*tmp1(:,i);
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cc = max(max(abs(X1-X0)));
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cc = norm(X1-X0,1);
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if isnan(cc)
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info(1) = 412;
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info(2) = -1.;
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return
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end
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X0 = X1; U0 = U1;
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tmp0 = tmp1;
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kk = kk+1;
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end
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if kk==maxit
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disp(['logarithmic_reduction:: Convergence not achieved after ' int2str(maxit) ' iterations!']);
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info = 1;
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info(1) = 411;
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info(2) = log(cc);
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end
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if nargin>5 && check
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if max(max(abs(A*X1*X1 + B*X1 + C)))>tol
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disp(['logarithmic_reduction:: Algotithm did not converge to the solution of the matrix quadratic equation!']);
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info = 1;
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res = norm(A*X1*X1 + B*X1 + C, 1);
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if res>tol
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info(1) = 413;
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info(2) = log(res);
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dprintf('The norm of the residual is %s whereas the tolerance criterion is %s', num2str(res), num2str(tol));
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end
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end
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@ -1,17 +1,18 @@
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mex_PROGRAMS = cycle_reduction
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nodist_cycle_reduction_SOURCES = \
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mexFunction.f08 \
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matlab_mex.F08 \
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blas_lapack.F08
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blas_lapack.F08 \
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mexFunction.f08
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BUILT_SOURCES = $(nodist_cycle_reduction_SOURCES)
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CLEANFILES = $(nodist_cycle_reduction_SOURCES)
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mexFunction.o: matlab_mex.mod blas.mod lapack.mod
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mexFunction.mod: mexFunction.o
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%.f08: $(top_srcdir)/../../sources/cycle_reduction/%.f08
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$(LN_S) -f $< $@
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%.F08: $(top_srcdir)/../../sources/cycle_reduction/%.F08
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$(LN_S) -f $< $@
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@ -0,0 +1,19 @@
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mex_PROGRAMS = logarithmic_reduction
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nodist_logarithmic_reduction_SOURCES = \
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matlab_mex.F08 \
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blas_lapack.F08 \
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mexFunction.f08
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BUILT_SOURCES = $(nodist_logarithmic_reduction_SOURCES)
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CLEANFILES = $(nodist_logarithmic_reduction_SOURCES)
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mexFunction.o: matlab_mex.mod blas.mod lapack.mod
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mexFunction.mod: mexFunction.o
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%.f08: $(top_srcdir)/../../sources/logarithmic_reduction/%.f08
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$(LN_S) -f $< $@
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%.F08: $(top_srcdir)/../../sources/logarithmic_reduction/%.F08
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$(LN_S) -f $< $@
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@ -1,6 +1,6 @@
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ACLOCAL_AMFLAGS = -I ../../../m4
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast libkordersim local_state_space_iterations folded_to_unfolded_dr k_order_simul k_order_mean cycle_reduction
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast libkordersim local_state_space_iterations folded_to_unfolded_dr k_order_simul k_order_mean cycle_reduction logarithmic_reduction
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# libdynare++ must come before gensylv and k_order_perturbation
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if ENABLE_MEX_DYNAREPLUSPLUS
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@ -170,6 +170,8 @@ AC_CONFIG_FILES([Makefile
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num_procs/Makefile
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block_trust_region/Makefile
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disclyap_fast/Makefile
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cycle_reduction/Makefile])
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cycle_reduction/Makefile
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logarithmic_reduction/Makefile])
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AC_OUTPUT
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@ -0,0 +1,2 @@
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include ../mex.am
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include ../../logarithmic_reduction.am
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@ -1,6 +1,6 @@
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ACLOCAL_AMFLAGS = -I ../../../m4
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast libkordersim local_state_space_iterations folded_to_unfolded_dr k_order_simul k_order_mean cycle_reduction
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SUBDIRS = mjdgges kronecker bytecode block_kalman_filter sobol perfect_foresight_problem num_procs block_trust_region disclyap_fast libkordersim local_state_space_iterations folded_to_unfolded_dr k_order_simul k_order_mean cycle_reduction logarithmic_reduction
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# libdynare++ must come before gensylv and k_order_perturbation
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if ENABLE_MEX_DYNAREPLUSPLUS
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@ -173,6 +173,7 @@ AC_CONFIG_FILES([Makefile
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num_procs/Makefile
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block_trust_region/Makefile
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disclyap_fast/Makefile
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cycle_reduction/Makefile])
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cycle_reduction/Makefile
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logarithmic_reduction/Makefile])
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AC_OUTPUT
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@ -0,0 +1,3 @@
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EXEEXT = .mex
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include ../mex.am
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include ../../logarithmic_reduction.am
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@ -26,7 +26,8 @@ EXTRA_DIST = \
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num_procs \
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block_trust_region \
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disclyap_fast \
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cycle_reduction
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cycle_reduction \
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logarithmic_reduction
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clean-local:
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rm -rf `find mex/sources -name *.o`
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@ -48,6 +48,57 @@ module blas
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real(real64), dimension(*), intent(inout) :: y
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end subroutine dgemv
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end interface
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contains
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! Updating a matrix using blas DGEMM
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! C <- alpha*op(A)*op(B) + beta*C
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subroutine matmul_add(opA, opB, alpha, A, B, beta, C)
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character, intent(in) :: opA, opB
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real(real64), dimension(:,:), intent(in) :: A, B
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real(real64), dimension(:,:), intent(inout) :: C
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real(real64), intent(in) :: alpha, beta
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integer(blint) :: m, n, k, lda, ldb
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if (opA == "N") then
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m = int(size(A,1), blint)
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k = int(size(A,2), blint)
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lda = m
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else
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m = int(size(A,2), blint)
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k = int(size(A,1), blint)
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lda = k
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end if
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if (opB == "N") then
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n = int(size(B,2), blint)
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ldb = k
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else
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n = int(size(B,1), blint)
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ldb = n
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end if
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#ifdef DEBUG
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if ( (opA /= "N") .and. (opA /= "T") .and. (opA /= "C") ) then
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print *, "opA must be either N, T or C"
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end if
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if ( (opB /= "N") .and. (opB /= "T") .and. (opB /= "C") ) then
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print *, "opB must be either N, T or C"
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end if
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if (((opA == "N") .and. (opB == "N") .and. (size(A,2) /= size(B,1))) .or.&
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&((opA == "N") .and. (opB /= "N") .and. (size(A,2) /= size(B,2))) .or.&
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&((opA /= "N") .and. (opB == "N") .and. (size(A,1) /= size(B,1))) .or.&
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&((opA /= "N") .and. (opB /= "N") .and. (size(A,1) /= size(B,2)))) &
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then
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print *, "Inconsistent number of columns of op(A) and number of rows &
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&of op(B)"
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end if
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if (m /= size(C,1)) then
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print *, "Inconsistent number of rows of op(A) and number of rows &
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&of C"
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end if
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#endif
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call dgemm(opA, opB, m, n, k, alpha, A, lda, B, &
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ldb, beta, C, m)
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end subroutine
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end module blas
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module lapack
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@ -104,5 +155,39 @@ module lapack
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real(real64) :: dlange
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end function dlange
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end interface
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contains
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! Computing inv(A)*B using lapack DGESV
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! B <- inv(A)*B
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subroutine left_divide(A, B, ipiv, info)
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real(real64), dimension(:,:), intent(inout) :: A
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real(real64), dimension(:,:), intent(inout) :: B
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integer(blint), dimension(:), intent(inout) :: ipiv
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integer(blint), intent(inout) :: info
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integer(blint) :: m, n
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#ifdef DEBUG
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if (size(ipiv) /= size(A,1)) then
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print *, "Inconsistent number of rows of A and size of ipiv"
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end if
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if (size(A,2) /= size(B,1)) then
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print *, "Inconsistent number of columns of A and number of rows of B"
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end if
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#endif
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m = int(size(A,1), blint)
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n = int(size(B,2), blint)
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call dgesv(m, n, A, m, ipiv, B, m, info)
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end subroutine left_divide
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! Matlab-like norm function calling lapack DLANGE routine
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real(real64) function norm(A, c)
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real(real64), dimension(:,:), intent(in) :: A
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character, intent(in) :: c
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real(real64), dimension(:), allocatable :: work
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integer(blint) :: nrow
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nrow = int(size(A,1),blint)
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norm = dlange(c, nrow, int(size(A,2), blint), &
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&A, nrow, work)
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end function norm
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end module lapack
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@ -18,51 +18,13 @@
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! Implements the cyclic reduction algorithm described in
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! D.A. Bini, G. Latouche, B. Meini (2002), "Solving matrix polynomial equations arising in queueing problems", Linear Algebra and its Applications 340, pp. 222-244
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! D.A. Bini, B. Meini (1996), "On the solution of a nonlinear matrix equation arising in queueing problems", SIAM J. Matrix Anal. Appl. 17, pp. 906-926.
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module reduction
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use matlab_mex
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module c_reduction
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use lapack
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use blas
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use matlab_mex
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implicit none
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contains
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! Matlab-like norm function calling lapack DLANGE routine
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real(real64) function norm(A, c)
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real(real64), dimension(:,:), intent(in) :: A
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character, intent(in) :: c
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real(real64), dimension(:), allocatable :: work
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integer(blint) :: nrow
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nrow = int(size(A,1),blint)
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norm = dlange(c, nrow, int(size(A,2), blint), &
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&A, nrow, work)
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end function norm
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! Updating a matrix using blas DGEMM
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! C <- alpha*A*B + beta*C
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subroutine updatemat(alpha, A, B, beta, C)
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real(real64), dimension(:,:), intent(in) :: A, B
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real(real64), dimension(:,:), intent(inout) :: C
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real(real64), intent(in) :: alpha, beta
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integer(blint) :: m, n, k
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m = int(size(A,1), blint)
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n = int(size(B,2), blint)
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k = int(size(A,2), blint)
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call dgemm("N", "N", m, n, k, alpha, A, m, B, &
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k, beta, C, m)
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end subroutine
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! Computing inv(A)*B using lapack DGESV
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! B <- inv(A)*B
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subroutine invA_B(A, B, ipiv, info)
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real(real64), dimension(:,:), intent(inout) :: A
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real(real64), dimension(:,:), intent(inout) :: B
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integer(blint), dimension(:), intent(inout) :: ipiv
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integer(blint), intent(inout) :: info
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integer(blint) :: m, n
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m = int(size(A,1), blint)
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n = int(size(B,2), blint)
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call dgesv(m, n, A, m, ipiv, B, m, info)
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end subroutine invA_B
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! Cycle reduction algorithm
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subroutine cycle_reduction(A0, A1, A2, X, cvg_tol, check, info)
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@ -93,9 +55,9 @@ loop: do
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! Computing [A0;A2]*(A1\[A0 A2])
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A1_tmp = A1i
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invA1_A02 = A02
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call invA_B(A1_tmp, invA1_A02, ipiv, info_inv)
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call updatemat(1._real64, A02(:,1:n), invA1_A02, 0._real64, Q0)
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call updatemat(1._real64, A02(:,n+1:dn), invA1_A02, 0._real64, Q2)
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call left_divide(A1_tmp, invA1_A02, ipiv, info_inv)
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call matmul_add("N", "N", 1._real64, A02(:,1:n), invA1_A02, 0._real64, Q0)
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call matmul_add("N", "N", 1._real64, A02(:,n+1:dn), invA1_A02, 0._real64, Q2)
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! Updating A02, A1 and Ahat
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A1i = A1i - Q0(:,n+1:dn) - Q2(:,1:n)
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A02(:,1:n) = -Q0(:,1:n)
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@ -121,23 +83,23 @@ loop: do
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! Computing X = -Ahat\A0
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X = -A0
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call invA_B(Ahat, X, ipiv, info_inv)
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call left_divide(Ahat, X, ipiv, info_inv)
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! Checking residuals if necessary
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if (check) then
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! A1_tmp <- A2*X + A1
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A1_tmp = A1
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call updatemat(1._real64, A2, X, 1._real64, A1_tmp)
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call matmul_add("N", "N", 1._real64, A2, X, 1._real64, A1_tmp)
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! A0_tmp <- A1_tmp*X + A0
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A0_tmp = A0
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call updatemat(1._real64, A1_tmp, X, 1._real64, A0_tmp)
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call matmul_add("N", "N", 1._real64, A1_tmp, X, 1._real64, A0_tmp)
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residual = norm(A0_tmp, "1")
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if (residual>cvg_tol) then
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info(1) = 403._c_double
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info(2) = log(residual)
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write (cvg_tol_str,"(es8.2)") cvg_tol
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write (residual_str,"(es8.2)") residual
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call mexErrMsgTxt("The norm of the residual is "&
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call mexPrintf("The norm of the residual is "&
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&// trim(residual_str) // &
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&", whereas the tolerance criterion is " &
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// trim(cvg_tol_str) // "." )
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|
@ -145,11 +107,10 @@ loop: do
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end if
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end subroutine cycle_reduction
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end module reduction
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end module c_reduction
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subroutine mexFunction(nlhs, plhs, nrhs, prhs) bind(c, name='mexFunction')
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use reduction
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use matlab_mex
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use c_reduction
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implicit none
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type(c_ptr), dimension(*), intent(in), target :: prhs
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|
|
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|
|
@ -0,0 +1,213 @@
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|||
! Copyright © 2022 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 <https://www.gnu.org/licenses/>.
|
||||
|
||||
! Implements the logarithmic reduction algorithm described in
|
||||
! D.A. Bini, G. Latouche, B. Meini (2002), "Solving matrix polynomial equations arising in queueing problems", Linear Algebra and its Applications 340, pp. 222-244
|
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module l_reduction
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use lapack
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use blas
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use matlab_mex
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implicit none
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contains
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! Logarithmic reduction algorithm
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subroutine logarithmic_reduction(A0, A1, A2, G, cvg_tol, check, max_it, info)
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real(real64), dimension(:,:), intent(in) :: A0, A1, A2
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real(real64), dimension(:,:), intent(inout) :: G
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real(real64), intent(in) :: cvg_tol
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logical, intent(in) :: check
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integer, intent(in) :: max_it
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real(c_double), dimension(2), intent(inout) :: info
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||||
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||||
real(real64), dimension(:,:), allocatable :: tmp_inv, tmp, D02, Id, P, &
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&A1_tmp, A0_tmp, G_new, P_new
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||||
integer :: it, n, dn, i, j
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||||
integer(blint) :: info_inv
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||||
integer(blint), dimension(:), allocatable :: ipiv
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||||
real(real64) :: crit
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||||
character(kind=c_char, len=10) :: cvg_tol_str, residual_str
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||||
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||||
n = size(A0,1)
|
||||
dn = 2*n
|
||||
allocate(D02(n,dn), ipiv(n), Id(n,n), tmp(n,dn), G_new(n,n), P_new(n,n))
|
||||
info = [0._c_double,0._c_double]
|
||||
! Set the identity matrix
|
||||
do j=1,n
|
||||
do i=1,n
|
||||
if (i == j) then
|
||||
Id(i,j) = 1.
|
||||
else
|
||||
Id(i,j) = 0.
|
||||
end if
|
||||
end do
|
||||
end do
|
||||
|
||||
! Initialization: D02_0
|
||||
D02(:,1:n) = A0
|
||||
D02(:,n+1:dn) = A2
|
||||
tmp_inv = -A1
|
||||
call left_divide(tmp_inv, D02, ipiv, info_inv)
|
||||
G = D02(:,1:n)
|
||||
P = D02(:,n+1:dn)
|
||||
it = 0
|
||||
loop: do
|
||||
! Computing E1_(i+1)
|
||||
tmp_inv = Id
|
||||
call matmul_add("N", "N", -1._real64, D02(:,1:n), D02(:,n+1:dn), 1._real64, tmp_inv)
|
||||
call matmul_add("N", "N", -1._real64, D02(:,n+1:dn), D02(:,1:n), 1._real64, tmp_inv)
|
||||
! Computing matrices [D0^2 D2^2], id est -E0_(i+1) and -E2_(i+1)
|
||||
call matmul_add("N", "N", 1._real64, D02(:,1:n), D02(:,1:n), 0._real64, tmp(:,1:n))
|
||||
call matmul_add("N", "N", 1._real64, D02(:,n+1:dn), D02(:,n+1:dn), 0._real64, tmp(:,n+1:dn))
|
||||
! Computing D0_(i+1) and D2_(i+1)
|
||||
call left_divide(tmp_inv, tmp, ipiv, info_inv)
|
||||
! Computing G_(i+1) = G_i + P_i*D0_(i+1)
|
||||
G_new = G
|
||||
call matmul_add("N", "N", 1._real64, P, tmp(:,1:n), 1._real64, G_new)
|
||||
! Computing P_(i+1)
|
||||
call matmul_add("N", "N", 1._real64, P, tmp(:,n+1:dn), 0._real64, P_new)
|
||||
crit = norm(G_new - G,"1")
|
||||
! Checking for stopping conditions
|
||||
if (crit < cvg_tol) then
|
||||
exit loop
|
||||
elseif (it == max_it) then
|
||||
info(1) = 411._c_double
|
||||
info(2) = real(log(crit), c_double)
|
||||
exit loop
|
||||
elseif (isnan(crit) .or. (info_inv /= 0_blint)) then
|
||||
info(1) = 412._c_double
|
||||
info(2) = -1._c_double
|
||||
exit loop
|
||||
end if
|
||||
it = it + 1
|
||||
G = G_new
|
||||
P = P_new
|
||||
D02 = tmp
|
||||
end do loop
|
||||
|
||||
! Checking residuals if necessary
|
||||
if (check) then
|
||||
! A1_tmp <- A2*X + A1
|
||||
A1_tmp = A1
|
||||
call matmul_add("N", "N", 1._real64, A2, G, 1._real64, A1_tmp)
|
||||
! A0_tmp <- A1_tmp*X + A0
|
||||
A0_tmp = A0
|
||||
call matmul_add("N", "N", 1._real64, A1_tmp, G, 1._real64, A0_tmp)
|
||||
crit = norm(A0_tmp, "1")
|
||||
if (crit>cvg_tol) then
|
||||
info(1) = 413._c_double
|
||||
info(2) = real(log(crit), c_double)
|
||||
write (cvg_tol_str,"(es8.2)") cvg_tol
|
||||
write (residual_str,"(es8.2)") crit
|
||||
call mexPrintf("The norm of the residual is "&
|
||||
&// trim(residual_str) // &
|
||||
&", whereas the tolerance criterion is " &
|
||||
// trim(cvg_tol_str) // "." )
|
||||
end if
|
||||
end if
|
||||
end subroutine logarithmic_reduction
|
||||
|
||||
end module l_reduction
|
||||
|
||||
subroutine mexFunction(nlhs, plhs, nrhs, prhs) bind(c, name='mexFunction')
|
||||
use l_reduction
|
||||
implicit none
|
||||
|
||||
type(c_ptr), dimension(*), intent(in), target :: prhs
|
||||
type(c_ptr), dimension(*), intent(out) :: plhs
|
||||
integer(c_int), intent(in), value :: nlhs, nrhs
|
||||
|
||||
integer :: i, n, max_it
|
||||
character(kind=c_char, len=2) :: num2str
|
||||
real(real64) :: cvg_tol
|
||||
real(real64), dimension(2) :: info
|
||||
real(real64), dimension(:,:), pointer, contiguous :: A0, A1, A2, X
|
||||
logical :: check
|
||||
|
||||
! 0. Checking the consistency and validity of input arguments
|
||||
if (nrhs < 5) then
|
||||
call mexErrMsgTxt("Must have at least 5 inputs")
|
||||
end if
|
||||
if (nrhs > 6) then
|
||||
call mexErrMsgTxt("Too many input arguments")
|
||||
end if
|
||||
if (nlhs > 2) then
|
||||
call mexErrMsgTxt("Too many output arguments")
|
||||
end if
|
||||
|
||||
do i=1,3
|
||||
if (.not. (c_associated(prhs(i)) .and. mxIsDouble(prhs(i)) .and. &
|
||||
(.not. mxIsComplex(prhs(i))) .and. (.not. mxIsSparse(prhs(i))))) then
|
||||
write (num2str,"(i2)") i
|
||||
call mexErrMsgTxt("Argument " // trim(num2str) // " should be a real dense matrix")
|
||||
end if
|
||||
end do
|
||||
do i=4,5
|
||||
if (.not. (c_associated(prhs(i)) .and. mxIsScalar(prhs(i)) .and. &
|
||||
mxIsNumeric(prhs(i)))) then
|
||||
write (num2str,"(i2)") i
|
||||
call mexErrMsgTxt("Argument " // trim(num2str) // " should be a numeric scalar")
|
||||
end if
|
||||
end do
|
||||
|
||||
check = .false.
|
||||
if (nrhs == 6) then
|
||||
if (.not. (c_associated(prhs(6)))) then
|
||||
call mexErrMsgTxt("Argument 6 should be a Matlab object")
|
||||
else
|
||||
if (.not. (mxIsEmpty(prhs(6)))) then
|
||||
check = .true.
|
||||
end if
|
||||
end if
|
||||
end if
|
||||
|
||||
n = int(mxGetM(prhs(1))) ! Order of the considered matrices
|
||||
if ((n /= mxGetN(prhs(1))) & ! Number of columns of A0
|
||||
&.or. (n /= mxGetM(prhs(2))) & ! Number of lines of A1
|
||||
&.or. (n /= mxGetN(prhs(2))) & ! Number of columns of A1
|
||||
&.or. (n /= mxGetM(prhs(3))) & ! Number of lines of A2
|
||||
&.or. (n /= mxGetN(prhs(3))) & ! Number of columns of A2
|
||||
) then
|
||||
call mexErrMsgTxt("Input dimension mismatch")
|
||||
end if
|
||||
|
||||
! 1. Storing the relevant information in Fortran format
|
||||
A2(1:n,1:n) => mxGetPr(prhs(1))
|
||||
A1(1:n,1:n) => mxGetPr(prhs(2))
|
||||
A0(1:n,1:n) => mxGetPr(prhs(3))
|
||||
cvg_tol = mxGetScalar(prhs(4))
|
||||
max_it = int(mxGetScalar(prhs(5)))
|
||||
info = [0._c_double,0._c_double]
|
||||
|
||||
plhs(1) = mxCreateDoubleMatrix(int(n, mwSize), int(n, mwSize), mxREAL)
|
||||
X(1:n,1:n) => mxGetPr(plhs(1))
|
||||
|
||||
! 2. Calling the Logarithmic Reduction algorithm
|
||||
call logarithmic_reduction(A0, A1, A2, X, cvg_tol, check, max_it, info)
|
||||
|
||||
! 3. Editing the information output if necessary
|
||||
if (nlhs == 2) then
|
||||
if (info(1) == 0._c_double) then
|
||||
plhs(2) = mxCreateDoubleScalar(0._c_double)
|
||||
else
|
||||
plhs(2) = mxCreateDoubleMatrix(1_mwSize, 2_mwSize, mxREAL)
|
||||
mxGetPr(plhs(2)) = info
|
||||
end if
|
||||
end if
|
||||
|
||||
end subroutine mexFunction
|
||||
|
|
@ -1224,7 +1224,9 @@ M_TRS_FILES += run_block_byte_tests_matlab.m.trs \
|
|||
test_aggregate_routine_1_2_3.m.trs \
|
||||
run_kronecker_tests.m.trs \
|
||||
nonlinearsolvers.m.trs \
|
||||
cyclereduction.m.trs
|
||||
cyclereduction.m.trs \
|
||||
logarithmicreduction.m.trs
|
||||
|
||||
|
||||
M_XFAIL_TRS_FILES = $(patsubst %.mod, %.m.trs, $(XFAIL_MODFILES))
|
||||
|
||||
|
|
@ -1237,7 +1239,9 @@ O_TRS_FILES += run_block_byte_tests_octave.o.trs \
|
|||
histval_initval_file_unit_tests.o.trs \
|
||||
run_kronecker_tests.o.trs \
|
||||
nonlinearsolvers.o.trs \
|
||||
cyclereduction.o.trs
|
||||
cyclereduction.o.trs \
|
||||
logarithmicreduction.o.trs
|
||||
|
||||
|
||||
O_XFAIL_TRS_FILES = $(patsubst %.mod, %.o.trs, $(XFAIL_MODFILES))
|
||||
|
||||
|
|
|
|||
|
|
@ -54,8 +54,8 @@ tElapsed1 = 0.;
|
|||
try
|
||||
tic; [X1,info] = cycle_reduction_matlab(C,B,A,cvg_tol,[0.]); tElapsed1 = toc;
|
||||
disp(['Elapsed time for the Matlab cycle reduction algorithm is: ' num2str(tElapsed1) ' (n=' int2str(n) ').'])
|
||||
R = C+B*X1+A*X1*X1;
|
||||
if (max(abs(R(:))) > cvg_tol)
|
||||
R = norm(C+B*X1+A*X1*X1,1);
|
||||
if (R > cvg_tol)
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Matlab cycle_reduction solution is wrong')
|
||||
|
|
@ -74,8 +74,8 @@ tElapsed2 = 0.;
|
|||
try
|
||||
tic; [X2,info] = cycle_reduction(C,B,A,cvg_tol,[0.]); tElapsed2 = toc;
|
||||
disp(['Elapsed time for the Fortran cycle reduction algorithm is: ' num2str(tElapsed2) ' (n=' int2str(n) ').'])
|
||||
R = C+B*X2+A*X2*X2;
|
||||
if (max(abs(R(:))) > cvg_tol)
|
||||
R = norm(C+B*X2+A*X2*X2,1);
|
||||
if (R > cvg_tol)
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Fortran cycle_reduction solution is wrong')
|
||||
|
|
@ -90,7 +90,7 @@ end
|
|||
|
||||
% 3. Compare solutions of the Fortran and Matlab routines
|
||||
NumberOfTests = NumberOfTests+1;
|
||||
if (max(abs(X1(:) - X2(:))) > cvg_tol)
|
||||
if (norm(X1 - X2, 1) > cvg_tol)
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Fortran and Matlab cycle reduction solutions differ');
|
||||
|
|
|
|||
|
|
@ -0,0 +1,140 @@
|
|||
debug = false;
|
||||
|
||||
if debug
|
||||
[top_test_dir, ~, ~] = fileparts(mfilename('fullpath'));
|
||||
else
|
||||
top_test_dir = getenv('TOP_TEST_DIR');
|
||||
end
|
||||
|
||||
addpath([top_test_dir filesep '..' filesep 'matlab']);
|
||||
|
||||
if ~debug
|
||||
% Test Dynare Version
|
||||
if ~strcmp(dynare_version(), getenv('DYNARE_VERSION'))
|
||||
error('Incorrect version of Dynare is being tested')
|
||||
end
|
||||
end
|
||||
|
||||
dynare_config;
|
||||
|
||||
NumberOfTests = 0;
|
||||
testFailed = 0;
|
||||
|
||||
if ~debug
|
||||
skipline()
|
||||
disp('*** TESTING: logarithmicreduction.m ***');
|
||||
end
|
||||
|
||||
matlab_cr_path = [top_test_dir filesep '..' filesep 'matlab' filesep 'missing' filesep 'mex' filesep 'logarithmic_reduction'];
|
||||
addpath(matlab_cr_path);
|
||||
logarithmic_reduction_matlab = @logarithmic_reduction;
|
||||
rmpath(matlab_cr_path);
|
||||
|
||||
if isoctave
|
||||
addpath([top_test_dir filesep '..' filesep 'mex' filesep 'octave']);
|
||||
else
|
||||
addpath([top_test_dir filesep '..' filesep 'mex' filesep 'matlab']);
|
||||
end
|
||||
|
||||
t0 = clock;
|
||||
|
||||
% Set the dimension of the problem to be solved.
|
||||
n = 500;
|
||||
% Set the equation to be solved
|
||||
A = eye(n);
|
||||
B = diag(30*ones(n,1)); B(1,1) = 20; B(end,end) = 20; B = B - diag(10*ones(n-1,1),-1); B = B - diag(10*ones(n-1,1),1);
|
||||
C = diag(15*ones(n,1)); C = C - diag(5*ones(n-1,1),-1); C = C - diag(5*ones(n-1,1),1);
|
||||
cvg_tol = 1e-12;
|
||||
X1 = zeros(n,n);
|
||||
X2 = zeros(n,n);
|
||||
|
||||
% 1. Solve the equation with the Matlab logarithmic reduction algorithm
|
||||
NumberOfTests = NumberOfTests+1;
|
||||
tElapsed1 = 0.;
|
||||
try
|
||||
tic; [X1,info] = logarithmic_reduction_matlab(A,B,C,cvg_tol,300,[0.]); tElapsed1 = toc;
|
||||
disp(['Elapsed time for the Matlab logarithmic reduction algorithm is: ' num2str(tElapsed1) ' (n=' int2str(n) ').'])
|
||||
R = norm(C+B*X1+A*X1*X1,1);
|
||||
if (R > cvg_tol)
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Matlab logarithmic_reduction solution is wrong')
|
||||
end
|
||||
end
|
||||
catch
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Matlab logarithmic_reduction failed')
|
||||
end
|
||||
end
|
||||
|
||||
% 2. Solve the equation with the Fortran logarithmic reduction algorithm
|
||||
NumberOfTests = NumberOfTests+1;
|
||||
tElapsed2 = 0.;
|
||||
try
|
||||
tic; [X2,info] = logarithmic_reduction(A,B,C,cvg_tol,300,[0.]); tElapsed2 = toc;
|
||||
disp(['Elapsed time for the Fortran logarithmic reduction algorithm is: ' num2str(tElapsed2) ' (n=' int2str(n) ').'])
|
||||
R = norm(C+B*X2+A*X2*X2,1);
|
||||
if (R > cvg_tol)
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Fortran logarithmic_reduction solution is wrong')
|
||||
end
|
||||
end
|
||||
catch
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Fortran logarithmic_reduction failed')
|
||||
end
|
||||
end
|
||||
|
||||
% 3. Compare solutions of the Fortran and Matlab routines
|
||||
NumberOfTests = NumberOfTests+1;
|
||||
if (norm(X1 - X2, 1) > cvg_tol)
|
||||
testFailed = testFailed+1;
|
||||
if debug
|
||||
dprintf('Fortran and Matlab logarithmic reduction solutions differ');
|
||||
end
|
||||
end
|
||||
|
||||
% Compare the Fortran and Matlab execution time
|
||||
if debug
|
||||
if tElapsed1<tElapsed2
|
||||
skipline()
|
||||
dprintf('Matlab logarithmic reduction is %5.2f times faster than its Fortran counterpart.', tElapsed2/tElapsed1)
|
||||
skipline()
|
||||
else
|
||||
skipline()
|
||||
dprintf('Fortran logarithmic reduction is %5.2f times faster than its Matlab counterpart.', tElapsed1/tElapsed2)
|
||||
skipline()
|
||||
end
|
||||
end
|
||||
|
||||
t1 = clock;
|
||||
|
||||
if ~debug
|
||||
cd(getenv('TOP_TEST_DIR'));
|
||||
else
|
||||
dprintf('FAILED tests: %i', testFailed)
|
||||
end
|
||||
|
||||
if isoctave
|
||||
fid = fopen('logarithmicreduction.o.trs', 'w+');
|
||||
else
|
||||
fid = fopen('logarithmicreduction.m.trs', 'w+');
|
||||
end
|
||||
if testFailed
|
||||
fprintf(fid,':test-result: FAIL\n');
|
||||
else
|
||||
fprintf(fid,':test-result: PASS\n');
|
||||
end
|
||||
fprintf(fid,':number-tests: %i\n', NumberOfTests);
|
||||
fprintf(fid,':number-failed-tests: %i\n', testFailed);
|
||||
fprintf(fid,':list-of-passed-tests: logarithmicreduction.m\n');
|
||||
fprintf(fid,':elapsed-time: %f\n', etime(t1, t0));
|
||||
fclose(fid);
|
||||
|
||||
if ~debug
|
||||
exit;
|
||||
end
|
||||
|
||||
Loading…
Reference in New Issue