From 13fa8d19b61ddaf2a10f992d3c4dfcf3fe795065 Mon Sep 17 00:00:00 2001
From: Anthony Scemama <scemama@irsamc.ups-tlse.fr>
Date: Sat, 13 Feb 2021 16:19:36 +0100
Subject: [PATCH] Improved weights in selection

---
 src/cipsi/selection_weight.irp.f | 36 +-------------------------------
 1 file changed, 1 insertion(+), 35 deletions(-)

diff --git a/src/cipsi/selection_weight.irp.f b/src/cipsi/selection_weight.irp.f
index fb317f9b..fb05263a 100644
--- a/src/cipsi/selection_weight.irp.f
+++ b/src/cipsi/selection_weight.irp.f
@@ -33,53 +33,21 @@ subroutine update_pt2_and_variance_weights(pt2_data, N_st)
 
   double precision :: avg, element, dt, x
   integer          :: k
-!  integer, save    :: i_iter=0
-!  integer, parameter :: i_itermax = 1
-!  double precision, allocatable, save :: memo_variance(:,:), memo_pt2(:,:)
-
   pt2(:)      = pt2_data % pt2(:)
   variance(:) = pt2_data % variance(:)
 
-!  if (i_iter == 0) then
-!    allocate(memo_variance(N_st,i_itermax), memo_pt2(N_st,i_itermax))
-!    memo_pt2(:,:) = 1.d0
-!    memo_variance(:,:) = 1.d0
-!  endif
-!
-!  i_iter = i_iter+1
-!  if (i_iter > i_itermax) then
-!    i_iter = 1
-!  endif
-!
-!  dt = 2.0d0
-
   avg = sum(pt2(1:N_st)) / dble(N_st) + 1.d-32 ! Avoid future division by zero
-!  do k=1,N_st
-!    element = exp(dt*(pt2(k)/avg -1.d0))
-!    element = min(2.0d0 , element)
-!    element = max(0.5d0 , element)
-!    memo_pt2(k,i_iter) = element
-!    pt2_match_weight(k) *= product(memo_pt2(k,:))
-  !enddo
 
-  dt = 1.0d0 * selection_factor
+  dt = 2.d0 !* selection_factor
   do k=1,N_st
     element = exp(dt*(pt2(k)/avg - 1.d0))
     element = min(2.0d0 , element)
     element = max(0.5d0 , element)
-  print *, k, element
     pt2_match_weight(k) *= element
   enddo
 
 
   avg = sum(variance(1:N_st)) / dble(N_st) + 1.d-32 ! Avoid future division by zero
-!  do k=1,N_st
-!    element = exp(dt*(variance(k)/avg -1.d0))
-!    element = min(2.0d0 , element)
-!    element = max(0.5d0 , element)
-!    memo_variance(k,i_iter) = element
-!    variance_match_weight(k) *= product(memo_variance(k,:))
-!  enddo
 
   do k=1,N_st
     element = exp(dt*(variance(k)/avg -1.d0))
@@ -94,8 +62,6 @@ subroutine update_pt2_and_variance_weights(pt2_data, N_st)
     variance_match_weight(:) = 1.d0
   endif
 
-print *, 'XXX', n_det, pt2_match_weight(1), pt2_match_weight(2)
-
   threshold_davidson_pt2 = min(1.d-6, &
      max(threshold_davidson, 1.e-1 * PT2_relative_error * minval(abs(pt2(1:N_states)))) )