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mirror of https://github.com/QuantumPackage/qp2.git synced 2024-11-09 06:53:38 +01:00

opt-cg fixed bug

This commit is contained in:
AbdAmmar 2022-12-05 01:30:37 +01:00
parent 07c82cc7be
commit f6f1ca5fa4
2 changed files with 167 additions and 28 deletions

View File

@ -43,26 +43,51 @@ END_PROVIDER
coef_gauss_j_mu_x = (/ -0.47947881d0 /)
expo_gauss_j_mu_x = (/ 3.4987848d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x(i) = tmp * expo_gauss_j_mu_x(i)
enddo
elseif(ng_fit_jast .eq. 2) then
coef_gauss_j_mu_x = (/ -0.18390742d0, -0.35512656d0 /)
expo_gauss_j_mu_x = (/ 31.9279947d0 , 2.11428789d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x(i) = tmp * expo_gauss_j_mu_x(i)
enddo
elseif(ng_fit_jast .eq. 3) then
coef_gauss_j_mu_x = (/ -0.07501725d0, -0.28499012d0, -0.1953932d0 /)
expo_gauss_j_mu_x = (/ 206.74058566d0, 1.72974157d0, 11.18735164d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x(i) = tmp * expo_gauss_j_mu_x(i)
enddo
elseif(ng_fit_jast .eq. 5) then
coef_gauss_j_mu_x = (/ -0.01832955d0 , -0.10188952d0 , -0.20710858d0 , -0.18975032d0 , -0.04641657d0 /)
expo_gauss_j_mu_x = (/ 4.33116687d+03, 2.61292842d+01, 1.43447161d+00, 4.92767426d+00, 2.10654699d+02 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x(i) = tmp * expo_gauss_j_mu_x(i)
enddo
elseif(ng_fit_jast .eq. 6) then
coef_gauss_j_mu_x = (/ -0.08783664d0 , -0.16088711d0 , -0.18464486d0 , -0.0368509d0 , -0.08130028d0 , -0.0126972d0 /)
expo_gauss_j_mu_x = (/ 4.09729729d+01, 7.11620618d+00, 2.03692338d+00, 4.10831731d+02, 1.12480198d+00, 1.00000000d+04 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x(i) = tmp * expo_gauss_j_mu_x(i)
enddo
elseif(ng_fit_jast .eq. 20) then
ASSERT(n_max_fit_slat == 20)
@ -118,26 +143,51 @@ END_PROVIDER
coef_gauss_j_mu_x_2 = (/ 0.26699573d0 /)
expo_gauss_j_mu_x_2 = (/ 11.71029824d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x_2(i) = tmp * expo_gauss_j_mu_x_2(i)
enddo
elseif(ng_fit_jast .eq. 2) then
coef_gauss_j_mu_x_2 = (/ 0.11627934d0 , 0.18708824d0 /)
expo_gauss_j_mu_x_2 = (/ 102.41386863d0, 6.36239771d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x_2(i) = tmp * expo_gauss_j_mu_x_2(i)
enddo
elseif(ng_fit_jast .eq. 3) then
coef_gauss_j_mu_x_2 = (/ 0.04947216d0 , 0.14116238d0, 0.12276501d0 /)
expo_gauss_j_mu_x_2 = (/ 635.29701766d0, 4.87696954d0, 33.36745891d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x_2(i) = tmp * expo_gauss_j_mu_x_2(i)
enddo
elseif(ng_fit_jast .eq. 5) then
coef_gauss_j_mu_x_2 = (/ 0.01461527d0 , 0.03257147d0 , 0.08831354d0 , 0.11411794d0 , 0.06858783d0 /)
expo_gauss_j_mu_x_2 = (/ 8.76554470d+03, 4.90224577d+02, 3.68267125d+00, 1.29663940d+01, 6.58240931d+01 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x_2(i) = tmp * expo_gauss_j_mu_x_2(i)
enddo
elseif(ng_fit_jast .eq. 6) then
coef_gauss_j_mu_x_2 = (/ 0.01347632d0 , 0.03929124d0 , 0.06289468d0 , 0.10702493d0 , 0.06999865d0 , 0.02558191d0 /)
expo_gauss_j_mu_x_2 = (/ 1.00000000d+04, 1.20900717d+02, 3.20346191d+00, 8.92157196d+00, 3.28119120d+01, 6.49045808d+02 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_x_2(i) = tmp * expo_gauss_j_mu_x_2(i)
enddo
elseif(ng_fit_jast .eq. 20) then
@ -176,8 +226,8 @@ END_PROVIDER
! ---
BEGIN_PROVIDER [double precision, expo_gauss_j_mu_1_erf, (n_max_fit_slat)]
&BEGIN_PROVIDER [double precision, coef_gauss_j_mu_1_erf, (n_max_fit_slat)]
BEGIN_PROVIDER [double precision, expo_gauss_j_mu_1_erf, (ng_fit_jast)]
&BEGIN_PROVIDER [double precision, coef_gauss_j_mu_1_erf, (ng_fit_jast)]
BEGIN_DOC
!
@ -190,25 +240,90 @@ END_PROVIDER
implicit none
integer :: i
double precision :: tmp
double precision :: expos(n_max_fit_slat), alpha, beta
double precision :: expos(ng_fit_jast), alpha, beta
double precision :: alpha_opt, beta_opt
!alpha_opt = expo_j_xmu(1) + expo_gauss_1_erf_x(1)
!beta_opt = expo_j_xmu(2) + expo_gauss_1_erf_x(2)
! direct opt
alpha_opt = 2.87875632d0
beta_opt = 1.34801003d0
if(ng_fit_jast .eq. 1) then
tmp = -0.25d0 / (mu_erf * dsqrt(dacos(-1.d0)))
coef_gauss_j_mu_1_erf = (/ -0.47742461d0 /)
expo_gauss_j_mu_1_erf = (/ 8.72255696d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_1_erf(i) = tmp * expo_gauss_j_mu_1_erf(i)
enddo
alpha = alpha_opt * mu_erf
call expo_fit_slater_gam(alpha, expos)
beta = beta_opt * mu_erf * mu_erf
elseif(ng_fit_jast .eq. 2) then
coef_gauss_j_mu_1_erf = (/ -0.19342649d0, -0.34563835d0 /)
expo_gauss_j_mu_1_erf = (/ 78.66099999d0, 5.04324363d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_1_erf(i) = tmp * expo_gauss_j_mu_1_erf(i)
enddo
elseif(ng_fit_jast .eq. 3) then
coef_gauss_j_mu_1_erf = (/ -0.0802541d0 , -0.27019258d0, -0.20546681d0 /)
expo_gauss_j_mu_1_erf = (/ 504.53350764d0, 4.01408169d0, 26.5758329d0 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_1_erf(i) = tmp * expo_gauss_j_mu_1_erf(i)
enddo
elseif(ng_fit_jast .eq. 5) then
coef_gauss_j_mu_1_erf = (/ -0.02330531d0 , -0.11888176d0 , -0.16476192d0 , -0.19874713d0 , -0.05889174d0 /)
expo_gauss_j_mu_1_erf = (/ 1.00000000d+04, 4.66067922d+01, 3.04359857d+00, 9.54726649d+00, 3.59796835d+02 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_1_erf(i) = tmp * expo_gauss_j_mu_1_erf(i)
enddo
elseif(ng_fit_jast .eq. 6) then
coef_gauss_j_mu_1_erf = (/ -0.01865654d0 , -0.18319251d0 , -0.06543196d0 , -0.11522778d0 , -0.14825793d0 , -0.03327101d0 /)
expo_gauss_j_mu_1_erf = (/ 1.00000000d+04, 8.05593848d+00, 1.27986190d+02, 2.92674319d+01, 2.93583623d+00, 7.65609148d+02 /)
tmp = mu_erf * mu_erf
do i = 1, ng_fit_jast
expo_gauss_j_mu_1_erf(i) = tmp * expo_gauss_j_mu_1_erf(i)
enddo
elseif(ng_fit_jast .eq. 20) then
ASSERT(n_max_fit_slat == 20)
!alpha_opt = expo_j_xmu(1) + expo_gauss_1_erf_x(1)
!beta_opt = expo_j_xmu(2) + expo_gauss_1_erf_x(2)
! direct opt
alpha_opt = 2.87875632d0
beta_opt = 1.34801003d0
alpha = alpha_opt * mu_erf
call expo_fit_slater_gam(alpha, expos)
beta = beta_opt * mu_erf * mu_erf
tmp = -1.d0 / dsqrt(dacos(-1.d0))
do i = 1, ng_fit_jast
expo_gauss_j_mu_1_erf(i) = expos(i) + beta
coef_gauss_j_mu_1_erf(i) = tmp * coef_fit_slat_gauss(i)
enddo
else
print *, ' not implemented yet'
stop
do i = 1, n_max_fit_slat
expo_gauss_j_mu_1_erf(i) = expos(i) + beta
coef_gauss_j_mu_1_erf(i) = tmp * coef_fit_slat_gauss(i)
endif
tmp = 0.25d0 / mu_erf
do i = 1, ng_fit_jast
coef_gauss_j_mu_1_erf(i) = tmp * coef_gauss_j_mu_1_erf(i)
enddo
END_PROVIDER

View File

@ -157,32 +157,57 @@ end
implicit none
integer :: i
double precision :: expos(ng_fit_jast), alpha, beta
double precision :: expos(ng_fit_jast), alpha, beta, tmp
if(ng_fit_jast .eq. 1) then
coef_gauss_j_mu_x = (/ 0.85345277d0 /)
expo_gauss_j_mu_x = (/ 6.23519457d0 /)
coef_gauss_1_erf_x_2 = (/ 0.85345277d0 /)
expo_gauss_1_erf_x_2 = (/ 6.23519457d0 /)
tmp = mu_erf * mu_erf
do i = 1, n_max_fit_slat
expo_gauss_1_erf_x_2(i) = tmp * expo_gauss_1_erf_x_2(i)
enddo
elseif(ng_fit_jast .eq. 2) then
coef_gauss_j_mu_x = (/ 0.31030624d0 , 0.64364964d0 /)
expo_gauss_j_mu_x = (/ 55.39184787d0, 3.92151407d0 /)
coef_gauss_1_erf_x_2 = (/ 0.31030624d0 , 0.64364964d0 /)
expo_gauss_1_erf_x_2 = (/ 55.39184787d0, 3.92151407d0 /)
tmp = mu_erf * mu_erf
do i = 1, n_max_fit_slat
expo_gauss_1_erf_x_2(i) = tmp * expo_gauss_1_erf_x_2(i)
enddo
elseif(ng_fit_jast .eq. 3) then
coef_gauss_j_mu_x = (/ 0.33206082d0 , 0.52347449d0, 0.12605012d0 /)
expo_gauss_j_mu_x = (/ 19.90272209d0, 3.2671671d0 , 336.47320445d0 /)
coef_gauss_1_erf_x_2 = (/ 0.33206082d0 , 0.52347449d0, 0.12605012d0 /)
expo_gauss_1_erf_x_2 = (/ 19.90272209d0, 3.2671671d0 , 336.47320445d0 /)
tmp = mu_erf * mu_erf
do i = 1, n_max_fit_slat
expo_gauss_1_erf_x_2(i) = tmp * expo_gauss_1_erf_x_2(i)
enddo
elseif(ng_fit_jast .eq. 5) then
coef_gauss_j_mu_x = (/ 0.02956716d0, 0.17025555d0, 0.32774114d0, 0.39034764d0, 0.07822781d0 /)
expo_gauss_j_mu_x = (/ 6467.28126d0, 46.9071990d0, 9.09617721d0, 2.76883328d0, 360.367093d0 /)
coef_gauss_1_erf_x_2 = (/ 0.02956716d0, 0.17025555d0, 0.32774114d0, 0.39034764d0, 0.07822781d0 /)
expo_gauss_1_erf_x_2 = (/ 6467.28126d0, 46.9071990d0, 9.09617721d0, 2.76883328d0, 360.367093d0 /)
tmp = mu_erf * mu_erf
do i = 1, n_max_fit_slat
expo_gauss_1_erf_x_2(i) = tmp * expo_gauss_1_erf_x_2(i)
enddo
elseif(ng_fit_jast .eq. 6) then
coef_gauss_j_mu_x = (/ 0.18331042d0 , 0.10971118d0 , 0.29949169d0 , 0.34853132d0 , 0.0394275d0 , 0.01874444d0 /)
expo_gauss_j_mu_x = (/ 2.54293498d+01, 1.40317872d+02, 7.14630801d+00, 2.65517675d+00, 1.45142619d+03, 1.00000000d+04 /)
coef_gauss_1_erf_x_2 = (/ 0.18331042d0 , 0.10971118d0 , 0.29949169d0 , 0.34853132d0 , 0.0394275d0 , 0.01874444d0 /)
expo_gauss_1_erf_x_2 = (/ 2.54293498d+01, 1.40317872d+02, 7.14630801d+00, 2.65517675d+00, 1.45142619d+03, 1.00000000d+04 /)
tmp = mu_erf * mu_erf
do i = 1, n_max_fit_slat
expo_gauss_1_erf_x_2(i) = tmp * expo_gauss_1_erf_x_2(i)
enddo
elseif(ng_fit_jast .eq. 20) then
@ -203,7 +228,6 @@ end
endif
END_PROVIDER
! ---