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This commit is contained in:
Anthony Scemama 2019-06-04 11:42:55 +02:00
parent a1c9ec2503
commit 6455b281ff
3 changed files with 20 additions and 20 deletions
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2
src/cipsi/pt2_stoch_routines.irp.f
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@ -333,7 +333,7 @@ subroutine ZMQ_pt2(E, pt2,relative_error, error, variance, norm, N_in)
pt2(k) = 0.d0 pt2(k) = 0.d0
enddo enddo
call update_pt2_and_variance_weights(pt2, variance, norm) call update_pt2_and_variance_weights(pt2, variance, norm, N_states)
end subroutine end subroutine

24
src/cipsi/selection.irp.f
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@ -6,7 +6,7 @@ BEGIN_PROVIDER [ double precision, pt2_match_weight, (N_states) ]
! Weights adjusted along the selection to make the PT2 contributions ! Weights adjusted along the selection to make the PT2 contributions
! of each state coincide. ! of each state coincide.
END_DOC END_DOC
pt2_match_weight = 1.d0 pt2_match_weight(:) = 1.d0
END_PROVIDER END_PROVIDER
BEGIN_PROVIDER [ double precision, variance_match_weight, (N_states) ] BEGIN_PROVIDER [ double precision, variance_match_weight, (N_states) ]
@ -15,10 +15,10 @@ BEGIN_PROVIDER [ double precision, variance_match_weight, (N_states) ]
! Weights adjusted along the selection to make the variances ! Weights adjusted along the selection to make the variances
! of each state coincide. ! of each state coincide.
END_DOC END_DOC
variance_match_weight = 1.d0 variance_match_weight(:) = 1.d0
END_PROVIDER END_PROVIDER
subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_states) subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_st)
implicit none implicit none
BEGIN_DOC BEGIN_DOC
! Updates the rPT2- and Variance- matching weights. ! Updates the rPT2- and Variance- matching weights.
@ -36,12 +36,12 @@ subroutine update_pt2_and_variance_weights(pt2, variance, norm, N_states)
enddo enddo
avg = sum(rpt2(1:N_st)) / dble(N_st) avg = sum(rpt2(1:N_st)) / dble(N_st)
do k=1,N_states do k=1,N_st
pt2_match_weight(k) *= (rpt2(k)/avg)**2 pt2_match_weight(k) *= (rpt2(k)/avg)**2
enddo enddo
avg = sum(variance(1:N_st)) / dble(N_st) avg = sum(variance(1:N_st)) / dble(N_st)
do k=1,N_states do k=1,N_st
variance_match_weight(k) *= (variance(k)/avg)**2 variance_match_weight(k) *= (variance(k)/avg)**2
enddo enddo
@ -54,10 +54,10 @@ BEGIN_PROVIDER [ double precision, selection_weight, (N_states) ]
BEGIN_DOC BEGIN_DOC
! Weights used in the selection criterion ! Weights used in the selection criterion
END_DOC END_DOC
select (weight_selection) select case (weight_selection)
case (0) case (0)
selection_weight(1:N_states) = weight_one_e_dm(1:N_states) selection_weight(1:N_states) = state_average_weight(1:N_states)
case (1) case (1)
selection_weight(1:N_states) = c0_weight(1:N_states) selection_weight(1:N_states) = c0_weight(1:N_states)
@ -682,11 +682,13 @@ subroutine fill_buffer_double(i_generator, sp, h1, h2, bannedOrb, banned, fock_d
variance(istate) = variance(istate) + alpha_h_psi * alpha_h_psi variance(istate) = variance(istate) + alpha_h_psi * alpha_h_psi
norm(istate) = norm(istate) + coef * coef norm(istate) = norm(istate) + coef * coef
! if (h0_type == "Variance") then if (weight_selection /= 5) then
! sum_e_pert = sum_e_pert - alpha_h_psi * alpha_h_psi * selection_weight(istate) ! Energy selection
! else
sum_e_pert = sum_e_pert + e_pert * selection_weight(istate) sum_e_pert = sum_e_pert + e_pert * selection_weight(istate)
! endif else
! Variance selection
sum_e_pert = sum_e_pert - alpha_h_psi * alpha_h_psi * selection_weight(istate)
endif
end do end do
if(pseudo_sym)then if(pseudo_sym)then
if(dabs(mat(1, p1, p2)).lt.thresh_sym)then if(dabs(mat(1, p1, p2)).lt.thresh_sym)then

14
src/cipsi/zmq_selection.irp.f
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@ -85,7 +85,11 @@ subroutine ZMQ_selection(N_in, pt2, variance, norm)
endif endif
integer :: nproc_target integer :: nproc_target
nproc_target = nproc if (N_det < 3*nproc) then
nproc_target = N_det/3
else
nproc_target = nproc
endif
double precision :: mem double precision :: mem
mem = 8.d0 * N_det * (N_int * 2.d0 * 3.d0 + 3.d0 + 5.d0) / (1024.d0**3) mem = 8.d0 * N_det * (N_int * 2.d0 * 3.d0 + 3.d0 + 5.d0) / (1024.d0**3)
call write_double(6,mem,'Estimated memory/thread (Gb)') call write_double(6,mem,'Estimated memory/thread (Gb)')
@ -131,13 +135,7 @@ subroutine ZMQ_selection(N_in, pt2, variance, norm)
norm(k) = norm(k) * f(k) norm(k) = norm(k) * f(k)
enddo enddo
! Adjust PT2 weights for next selection call update_pt2_and_variance_weights(pt2, variance, norm, N_states)
double precision :: pt2_avg
pt2_avg = sum(pt2) / dble(N_states)
do k=1,N_states
pt2_match_weight(k) *= (pt2(k)/pt2_avg)**2
enddo
SOFT_TOUCH pt2_match_weight
end subroutine end subroutine