subroutine da_minimise_cg(grid, config_flags, & it, cv_size, xbx, be, iv, & j_grad_norm_target, xhat, cv, & re, y, j_cost) !------------------------------------------------------------------------- ! Purpose: Main Conjugate Gradient minimisation routine ! ! Here ! cv is updated in outer-loop. ! xhat is the control variable in inner-loop. ! ! Called from da_solve ! ! History: 12/12/08 - Split J and GradJ calculations (Tom Auligne) ! 12/12/08 - Re-orthonormalization option (Tom Auligne) ! ! History: Sep. 2010 - Add Cloud control variables (hongli Wang) !------------------------------------------------------------------------- implicit none integer, intent(in) :: it ! external iteration. integer, intent(in) :: cv_size ! Total cv size type (xbx_type),intent(inout) :: xbx ! Header & non-gridded vars. type (be_type), intent(in) :: be ! background error structure. type (iv_type), intent(inout) :: iv ! ob. increment vector. real, intent(inout) :: j_grad_norm_target ! Target norm. real, intent(inout) :: xhat(1:cv_size) ! control variable (local). real, intent(inout) :: cv(1:cv_size) ! control variable (local). type (y_type), intent(inout) :: re ! residual (o-a) structure. type (y_type), intent(inout) :: y ! y = H(x_inc) structure. type (j_type), intent(out) :: j_cost ! cost function type(domain), intent(inout) :: grid type(grid_config_rec_type), intent(inout) :: config_flags integer :: iter integer :: jp_start, jp_end ! Start/end indices of Jp. #ifdef CLOUD_CV integer :: mz(11) #else integer :: mz(7) #endif real :: fhat(1:cv_size) ! cv copy. real :: ghat(1:cv_size) ! cv copy. real :: ghat0(1:cv_size) ! cv copy. real :: phat(1:cv_size) ! cv copy. type(qhat_type), allocatable :: qhat(:) ! cv copy. real :: apdotp,step,rrmold,rrmnew,ratio real :: ob_grad, rrmnew_norm, gdot real :: j_total, j0_total ! Variables for Conjugate Gradient preconditioning real :: precon(1:cv_size) ! cv copy. real :: g_total, g_partial, jo_partial integer :: i, ii, nv, nn, istart, iend #ifdef CLOUD_CV integer :: sz(9) #else integer :: sz(5) #endif if (trace_use) call da_trace_entry("da_minimise_cg") write(unit=stdout,fmt='(A)') 'Minimize cost function using CG method' write(unit=stdout,fmt=*) ' ' !------------------------------------------------------------------------- ! [1.0] Initialization: !------------------------------------------------------------------------- #ifdef CLOUD_CV mz = (/ be%v1%mz, be%v2%mz, be%v3%mz, be%v4%mz, be%v5%mz, be%v6%mz, be%v7%mz,be%v8%mz,be%v9%mz, be%alpha%mz, be % ne /) sz = (/ be%cv%size1, be%cv%size2, be%cv%size3, be%cv%size4, be%cv%size5, be%cv%size6, be%cv%size7,be%cv%size8, be%cv%size9 /) #else mz = (/ be%v1%mz, be%v2%mz, be%v3%mz, be%v4%mz, be%v5%mz, be%alpha%mz, be % ne /) sz = (/ be%cv%size1, be%cv%size2, be%cv%size3, be%cv%size4, be%cv%size5 /) #endif jp_start = be % cv % size_jb + be % cv % size_je + 1 jp_end = be % cv % size_jb + be % cv % size_je + be % cv % size_jp call da_calculate_j(it, 0, cv_size, be%cv%size_jb, be%cv%size_je, be%cv%size_jp, & be%cv%size_jl, xbx, be, iv, xhat, cv, re, y, j_cost, ghat, grid, config_flags) j0_total = j_cost%total if (j0_total == 0.0) return ghat0 = ghat ! [1.1] Preconditioning: !----------------------- precon = 1.0 if (precondition_cg) then g_total = da_dot(cv_size,ghat,ghat) iend = 0 #ifdef CLOUD_CV do nv = 1, 9 #else do nv = 1, 5 #endif nn = sz(nv) / mz(nv) do ii = 1, mz(nv) istart = iend + 1 iend = istart + nn - 1 g_partial = da_dot(nn, ghat(istart:iend), ghat(istart:iend)) #ifdef CLOUD_CV jo_partial = j0_total / SUM(mz(1:8)) #else jo_partial = j0_total / SUM(mz(1:5)) #endif precon(istart:iend)= 1 / & (1 + precondition_factor*(g_partial/g_total)/(jo_partial/j0_total)) end do end do end if phat = - precon * ghat rrmold = da_dot_cv(cv_size, -phat, ghat, grid, mz, jp_start, jp_end) j_grad_norm_target = sqrt (rrmold) if (orthonorm_gradient) then allocate(qhat(0:ntmax)) allocate(qhat(0)%values(1:cv_size)) qhat(0)%values = ghat / sqrt(rrmold) end if write(unit=stdout,fmt='("Starting outer iteration : ",i3)') it write(unit=stdout,fmt=11) j0_total, sqrt(rrmold), eps(it)*j_grad_norm_target 11 format('Starting cost function: ' ,1PD22.15,', Gradient= ',1PD22.15,/,& 'For this outer iteration gradient target is: ',1PD22.15) write(unit=stdout,fmt='(A)') & '----------------------------------------------------------' write(unit=stdout,fmt='(A)') & 'Iter Cost Function Gradient Step' !------------------------------------------------------------------------- ! [2.0] iteratively solve for minimum of cost function: !------------------------------------------------------------------------- do iter=1, ntmax if (rrmold == 0.0) exit call da_calculate_gradj(it,iter,cv_size,be%cv%size_jb,be%cv%size_je,be%cv%size_jp, & be%cv%size_jl,xbx,be,iv,phat,y,fhat,grid,config_flags) apdotp = da_dot_cv(cv_size, fhat, phat, grid, mz, jp_start, jp_end) step = 0.0 if (apdotp .gt. 0.0) step = rrmold/apdotp ghat = ghat + step * fhat xhat = xhat + step * phat ! Orthonormalize new gradient (using modified Gramm-Schmidt algorithm) if (orthonorm_gradient) then do i = iter-1, 0, -1 gdot = da_dot_cv(cv_size, ghat, qhat(i)%values, grid, mz, jp_start, jp_end) ghat = ghat - gdot * qhat(i)%values end do end if rrmnew = da_dot_cv (cv_size, precon*ghat, ghat, grid, mz, jp_start, jp_end) rrmnew_norm = sqrt(rrmnew) ratio = 0.0 if (rrmold .gt. 0.0) ratio = rrmnew/rrmold if (orthonorm_gradient) then allocate(qhat(iter)%values(1:cv_size)) qhat(iter)%values = ghat / rrmnew_norm end if phat = - precon * ghat + ratio * phat rrmold=rrmnew ! Print Gradient (and Cost Function) !----------------------------------- if (calculate_cg_cost_fn) then call da_calculate_j(it, iter, cv_size, be%cv%size_jb, be%cv%size_je, be%cv%size_jp, & be%cv%size_jl, xbx, be, iv, xhat, cv, re, y, j_cost, fhat, grid, config_flags) j_total = j_cost%total else j_total = j0_total + 0.5 * da_dot_cv(cv_size,ghat0,xhat,grid,mz,jp_start,jp_end) endif write(unit=stdout,fmt=12)iter, j_total, rrmnew_norm, step if (rrmnew_norm < eps(it) * j_grad_norm_target) exit 12 format(i3,5x,1PD22.15,5x,1PD22.15,5x,1PD22.15) end do !------------------------------------------------------------------------- ! End of the minimization of cost function !------------------------------------------------------------------------- iter = MIN(iter, ntmax) ! Free memory used for reorthonormalization !------------------------------------------ if (orthonorm_gradient) then do i = iter-1, 0, -1 if (allocated(qhat(i)%values)) deallocate(qhat(i)%values) end do deallocate(qhat) end if write(unit=stdout,fmt='(A)') & '----------------------------------------------------------' write(unit=stdout,fmt='(A)') " " write(unit=stdout, & fmt='("Inner iteration stopped after ",i4," iterations")') iter write(unit=stdout,fmt='(A)') " " call da_calculate_j(it, iter, cv_size, be%cv%size_jb, be%cv%size_je, be%cv%size_jp, & be%cv%size_jl, xbx, be, iv, xhat, cv, re, y, j_cost, ghat, grid, config_flags) rrmnew_norm = SQRT(da_dot_cv(cv_size,ghat,ghat,grid,mz,jp_start,jp_end)) write(unit=stdout,fmt=15) iter, j_cost%total , rrmnew_norm 15 format('Final: ',I3,' iter, J=',1PD22.15,', g=',1PD22.15) write(unit=stdout,fmt='(A)') & '----------------------------------------------------------' if (trace_use) call da_trace_exit("da_minimise_cg") end subroutine da_minimise_cg