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qmcchem/src/SAMPLING/pdmc_step.irp.f

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2016-12-28 16:57:53 +01:00
! Providers of *_pdmc_block_walk
!==============================
BEGIN_SHELL [ /usr/bin/python ]
from properties import *
t = """
BEGIN_PROVIDER [ $T, $X_pdmc_block_walk $D1 ]
&BEGIN_PROVIDER [ $T, $X_pdmc_block_walk_kahan $D2 ]
&BEGIN_PROVIDER [ $T, $X_2_pdmc_block_walk $D1 ]
&BEGIN_PROVIDER [ $T, $X_2_pdmc_block_walk_kahan $D2 ]
implicit none
BEGIN_DOC
! pdMC averages of $X. Computed in E_loc_pdmc_block_walk
END_DOC
$X_pdmc_block_walk = 0.d0
$X_pdmc_block_walk_kahan = 0.d0
$X_2_pdmc_block_walk = 0.d0
$X_2_pdmc_block_walk_kahan = 0.d0
END_PROVIDER
"""
for p in properties:
if p[1] != 'e_loc':
if p[2] == "":
D1 = ""
D2 = ", (3)"
else:
D1 = ", ("+p[2][1:-1]+")"
D2 = ", ("+p[2][1:-1]+",3)"
print t.replace("$X",p[1]).replace("$T",p[0]).replace("$D1",D1).replace("$D2",D2)
END_SHELL
BEGIN_PROVIDER [ double precision, E_loc_pdmc_block_walk ]
&BEGIN_PROVIDER [ double precision, E_loc_2_pdmc_block_walk ]
&BEGIN_PROVIDER [ double precision, E_loc_pdmc_block_walk_kahan, (3) ]
&BEGIN_PROVIDER [ double precision, E_loc_2_pdmc_block_walk_kahan, (3) ]
implicit none
include '../types.F'
BEGIN_DOC
! Properties averaged over the block using the PDMC method
END_DOC
real, allocatable :: elec_coord_tmp(:,:,:)
integer :: mod_align
double precision :: E_loc_save(4,walk_num_dmc_max)
double precision :: psi_value_save(walk_num)
double precision :: psi_value_save_tmp(walk_num)
double precision :: pdmc_weight(walk_num)
double precision, allocatable :: psi_grad_psi_inv_save(:,:,:)
double precision, allocatable :: psi_grad_psi_inv_save_tmp(:,:,:)
!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_grad_psi_inv_save
!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_grad_psi_inv_save_tmp
!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: E_loc_save
!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_value_save
!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_value_save_tmp
!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: pdmc_weight
allocate ( psi_grad_psi_inv_save(elec_num_8,3,walk_num) , &
psi_grad_psi_inv_save_tmp(elec_num_8,3,walk_num) , &
elec_coord_tmp(mod_align(elec_num+1),3,walk_num) )
psi_value_save = 0.d0
psi_value_save_tmp = 0.d0
pdmc_weight = 1.d0
! Initialization
if (vmc_algo /= t_Brownian) then
call abrt(irp_here,'PDMC should run with Brownian algorithm')
endif
integer :: k, i_walk, i_step
BEGIN_SHELL [ /usr/bin/python ]
from properties import *
t = """
if (calc_$X) then
!DIR$ VECTOR ALIGNED
$X_pdmc_block_walk = 0.d0
!DIR$ VECTOR ALIGNED
$X_pdmc_block_walk_kahan = 0.d0
!DIR$ VECTOR ALIGNED
$X_2_pdmc_block_walk = 0.d0
!DIR$ VECTOR ALIGNED
$X_2_pdmc_block_walk_kahan = 0.d0
endif
"""
for p in properties:
print t.replace("$X",p[1])
END_SHELL
logical :: loop
integer*8 :: cpu0, cpu1, cpu2, count_rate, count_max
loop = .True.
call system_clock(cpu0, count_rate, count_max)
cpu2 = cpu0
block_weight = 0.d0
real, external :: accep_rate
double precision :: delta, thr
thr = 2.d0/time_step_sq
logical :: first_loop
first_loop = .True.
if (walk_num > 1) then
call abrt(irp_here,'walk_num > 1')
endif
integer :: info
! double precision :: H(0:pdmc_n_diag/2,0:pdmc_n_diag/2), S(0:pdmc_n_diag/2,0:pdmc_n_diag/2), w(0:pdmc_n_diag/2), work(3*pdmc_n_diag+1)
! H = 0.d0
! S = 0.d0
do while (loop)
i_walk = 1
if (.not.first_loop) then
integer :: i,j,l
do l=1,3
do i=1,elec_num+1
elec_coord(i,l) = elec_coord_full(i,l,i_walk)
enddo
do i=1,elec_num
psi_grad_psi_inv_x(i) = psi_grad_psi_inv_save(i,1,i_walk)
psi_grad_psi_inv_y(i) = psi_grad_psi_inv_save(i,2,i_walk)
psi_grad_psi_inv_z(i) = psi_grad_psi_inv_save(i,3,i_walk)
enddo
psi_value = psi_value_save(i_walk)
E_loc = E_loc_save(1,i_walk)
enddo
SOFT_TOUCH elec_coord psi_grad_psi_inv_x psi_grad_psi_inv_y psi_grad_psi_inv_z psi_value E_loc
else
do l=1,3
do i=1,elec_num+1
elec_coord(i,l) = elec_coord_full(i,l,i_walk)
enddo
enddo
TOUCH elec_coord
psi_value_save(i_walk) = psi_value
E_loc_save(:,i_walk) = E_loc
endif
double precision :: p,q
real :: delta_x
logical :: accepted
call brownian_step(p,q,accepted,delta_x)
! if ( psi_value * psi_value_save(i_walk) >= 0.d0 ) then
!2 delta = (E_loc+E_loc_save(1,i_walk))*0.5d0
!3 delta = (5.d0 * E_loc + 8.d0 * E_loc_save(1,i_walk) - E_loc_save(2,i_walk))/12.d0
delta = (9.d0*E_loc+19.d0*E_loc_save(1,i_walk)-5.d0*E_loc_save(2,i_walk)+E_loc_save(3,i_walk))/24.d0
! delta = -((-251.d0*E_loc)-646.d0*E_loc_save(1,i_walk)+264.d0*E_loc_save(2,i_walk)-&
! 106.d0*E_loc_save(3,i_walk)+19.d0*E_loc_save(4,i_walk))/720.d0
delta = (delta - E_ref)*p
if (delta >= 0.d0) then
pdmc_weight(i_walk) = dexp(-dtime_step*delta)
else
pdmc_weight(i_walk) = 2.d0-dexp(dtime_step*delta)
endif
elec_coord(elec_num+1,1) += p*time_step
elec_coord(elec_num+1,2) = E_loc
elec_coord(elec_num+1,3) = pdmc_weight(i_walk) * pdmc_pop_weight_mult(pdmc_n_diag)
do l=1,3
do i=1,elec_num+1
elec_coord_full(i,l,i_walk) = elec_coord(i,l)
enddo
enddo
do i=1,elec_num
psi_grad_psi_inv_save(i,1,i_walk) = psi_grad_psi_inv_x(i)
psi_grad_psi_inv_save(i,2,i_walk) = psi_grad_psi_inv_y(i)
psi_grad_psi_inv_save(i,3,i_walk) = psi_grad_psi_inv_z(i)
enddo
psi_value_save(i_walk) = psi_value
E_loc_save(4,i_walk) = E_loc_save(3,i_walk)
E_loc_save(3,i_walk) = E_loc_save(2,i_walk)
E_loc_save(2,i_walk) = E_loc_save(1,i_walk)
E_loc_save(1,i_walk) = E_loc
if (dabs(pdmc_weight(i_walk)*pdmc_pop_weight_mult(pdmc_n_diag)) > 1.d-15) then
dmc_zv_weight = 1.d0/(pdmc_weight(i_walk)*pdmc_pop_weight_mult(pdmc_n_diag))
dmc_zv_weight_half = 1.d0/(pdmc_weight(i_walk)*pdmc_pop_weight_mult(pdmc_n_diag/2))
else
dmc_zv_weight = 0.d0
dmc_zv_weight_half = 0.d0
endif
TOUCH dmc_zv_weight dmc_zv_weight_half
! do i=1,pdmc_n_diag+1
! E_loc_zv(i) = E_loc * pdmc_pop_weight_mult(i-1) * pdmc_weight(i_walk) * dmc_zv_weight + (E_trial-E_loc) * dmc_zv_weight
! E_loc_zv(i+pdmc_n_diag+1) = pdmc_pop_weight_mult(i-1) * pdmc_weight(i_walk) * dmc_zv_weight
! enddo
BEGIN_SHELL [ /usr/bin/python ]
from properties import *
t = """
if (calc_$X) then
! Kahan's summation algorithm to compute these sums reducing the rounding error:
! $X_pdmc_block_walk += $X * pdmc_pop_weight_mult(pdmc_n_diag) * pdmc_weight(i_walk)
! $X_2_pdmc_block_walk += $X_2 * pdmc_pop_weight_mult(pdmc_n_diag) * pdmc_weight(i_walk)
! see http://en.wikipedia.org/wiki/Kahan_summation_algorithm
$X_pdmc_block_walk_kahan($D2 3) = $X * pdmc_pop_weight_mult(pdmc_n_diag) * pdmc_weight(i_walk) - $X_pdmc_block_walk_kahan($D2 1)
$X_pdmc_block_walk_kahan($D2 2) = $X_pdmc_block_walk $D1 + $X_pdmc_block_walk_kahan($D2 3)
$X_pdmc_block_walk_kahan($D2 1) = ($X_pdmc_block_walk_kahan($D2 2) - $X_pdmc_block_walk $D1 ) &
- $X_pdmc_block_walk_kahan($D2 3)
$X_pdmc_block_walk $D1 = $X_pdmc_block_walk_kahan($D2 2)
$X_2_pdmc_block_walk_kahan($D2 3) = $X_2 * pdmc_pop_weight_mult(pdmc_n_diag) * pdmc_weight(i_walk) - $X_2_pdmc_block_walk_kahan($D2 1)
$X_2_pdmc_block_walk_kahan($D2 2) = $X_2_pdmc_block_walk $D1 + $X_2_pdmc_block_walk_kahan($D2 3)
$X_2_pdmc_block_walk_kahan($D2 1) = ($X_2_pdmc_block_walk_kahan($D2 2) - $X_2_pdmc_block_walk $D1 ) &
- $X_2_pdmc_block_walk_kahan($D2 3)
$X_2_pdmc_block_walk $D1 = $X_2_pdmc_block_walk_kahan($D2 2)
endif
"""
for p in properties:
if p[2] == "":
D1 = ""
D2 = ""
else:
D1 = "("+":"*(p[2].count(',')+1)+")"
D2 = ":"*(p[2].count(',')+1)+","
print t.replace("$X",p[1]).replace("$D1",D1).replace("$D2",D2)
END_SHELL
block_weight += pdmc_pop_weight_mult(pdmc_n_diag) * pdmc_weight(i_walk)
pdmc_pop_weight_mult(0) = 1.d0/pdmc_weight(i_walk)
! do k=0,pdmc_n_diag/2
! do l=0,pdmc_n_diag/2
! H(k,l) += E_loc*pdmc_pop_weight_mult(k+l) * pdmc_weight(i_walk)
! S(k,l) += pdmc_pop_weight_mult(k+l) * pdmc_weight(i_walk)
! enddo
! enddo
! H = H + (E_trial - E_loc)
! else
! pdmc_weight(i_walk) = 1.d0
! pdmc_pop_weight(:,:) = 1.d0
! pdmc_pop_weight_mult(:) = 1.d0
! endif
do k=1,pdmc_n_diag
! Move to the next projection step
if (pdmc_projection(pdmc_n_diag) > 0) then
pdmc_projection_step(k) = mod(pdmc_projection_step(k),pdmc_projection(k))+1
else
pdmc_projection_step(k) = 1
endif
! Eventually, recompute the weight of the population
if (pdmc_projection_step(k) == k) then
pdmc_pop_weight_mult(k) = 1.d0
do l=1,pdmc_projection(k)
pdmc_pop_weight_mult(k) *= pdmc_pop_weight(l,k)
enddo
endif
! Remove contribution of the old value of the weight at the new
! projection step
pdmc_pop_weight_mult(k) *= 1.d0/pdmc_pop_weight(pdmc_projection_step(k),k)
pdmc_pop_weight(pdmc_projection_step(k),k) = pdmc_weight(i_walk)/dble(walk_num)
! Update the running population weight
pdmc_pop_weight_mult(k) *= pdmc_pop_weight(pdmc_projection_step(k),k)
enddo
call system_clock(cpu1, count_rate, count_max)
if (cpu1 < cpu0) then
cpu1 = cpu1+cpu0
endif
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loop = dble(cpu1-cpu0)/dble(count_rate) < block_time
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if (cpu1-cpu2 > count_rate) then
integer :: do_run
call get_running(do_run)
loop = loop.and.(do_run == t_Running)
cpu2 = cpu1
endif
SOFT_TOUCH elec_coord_full pdmc_pop_weight_mult
first_loop = .False.
enddo
double precision :: factor
factor = 1.d0/block_weight
SOFT_TOUCH block_weight
BEGIN_SHELL [ /usr/bin/python ]
from properties import *
t = """
if (calc_$X) then
$X_pdmc_block_walk *= factor
$X_2_pdmc_block_walk *= factor
endif
"""
for p in properties:
print t.replace("$X",p[1])
END_SHELL
! H(0,0) = H(3,3)
! H(1,0) = H(4,3)
! H(0,1) = H(3,4)
! H(1,1) = H(4,4)
! S(0,0) = S(3,3)
! S(1,0) = S(4,3)
! S(0,1) = S(3,4)
! S(1,1) = S(4,4)
!
! print *, H(0,0)/S(0,0)
! print *, H(1,1)/S(1,1)
! print *, ''
!
! call dsygv(1, 'N', 'U', pdmc_n_diag/2+1, H, pdmc_n_diag/2+1, S, pdmc_n_diag/2+1, w, work, 3*(pdmc_n_diag+1), info)
! call dsygv(1, 'N', 'U', 2, H, pdmc_n_diag/2+1, S, pdmc_n_diag/2+1, w, work, 3*(pdmc_n_diag+1), info)
! E_loc_zv_diag_pdmc_block_walk = w(0)
! print *, w
deallocate ( elec_coord_tmp, psi_grad_psi_inv_save, psi_grad_psi_inv_save_tmp )
END_PROVIDER
BEGIN_PROVIDER [ integer, pdmc_projection, (pdmc_n_diag) ]
&BEGIN_PROVIDER [ integer, pdmc_projection_step, (pdmc_n_diag) ]
implicit none
BEGIN_DOC
! Number of projection steps for PDMC
END_DOC
real :: pdmc_projection_time
pdmc_projection_time = 1.
call get_simulation_srmc_projection_time(pdmc_projection_time)
pdmc_projection(pdmc_n_diag) = int( pdmc_projection_time/time_step)
integer :: k
do k=1,pdmc_n_diag-1
pdmc_projection(k) = k*pdmc_projection(pdmc_n_diag)/pdmc_n_diag
enddo
pdmc_projection_step(:) = 0
END_PROVIDER
BEGIN_PROVIDER [ double precision, pdmc_pop_weight, (0:pdmc_projection(pdmc_n_diag)+1,pdmc_n_diag) ]
implicit none
BEGIN_DOC
! Population weight of PDMC
END_DOC
pdmc_pop_weight(:,:) = 1.d0
END_PROVIDER
BEGIN_PROVIDER [ double precision, pdmc_pop_weight_mult, (0:pdmc_n_diag) ]
implicit none
BEGIN_DOC
! Population weight of PDMC
END_DOC
pdmc_pop_weight_mult(:) = 1.d0
END_PROVIDER
BEGIN_PROVIDER [ integer, pdmc_n_diag ]
implicit none
BEGIN_DOC
! Size of the matrix to diagonalize
END_DOC
pdmc_n_diag = 8
END_PROVIDER