mirror of https://gitlab.com/scemama/qmcchem.git
388 lines
11 KiB
Fortran
388 lines
11 KiB
Fortran
! Providers of *_srmc_block_walk
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!==============================
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BEGIN_SHELL [ /usr/bin/python ]
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from properties import *
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t = """
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BEGIN_PROVIDER [ $T, $X_srmc_block_walk $D1 ]
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&BEGIN_PROVIDER [ $T, $X_srmc_block_walk_kahan $D2 ]
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&BEGIN_PROVIDER [ $T, $X_2_srmc_block_walk $D1 ]
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&BEGIN_PROVIDER [ $T, $X_2_srmc_block_walk_kahan $D2 ]
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implicit none
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BEGIN_DOC
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! SRMC averages of $X. Computed in E_loc_srmc_block_walk
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END_DOC
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$X_srmc_block_walk = 0.d0
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$X_srmc_block_walk_kahan = 0.d0
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$X_2_srmc_block_walk = 0.d0
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$X_2_srmc_block_walk_kahan = 0.d0
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END_PROVIDER
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"""
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for p in properties:
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if p[1] != 'e_loc':
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if p[2] == "":
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D1 = ""
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D2 = ", (3)"
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else:
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D1 = ", ("+p[2][1:-1]+")"
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D2 = ", ("+p[2][1:-1]+",3)"
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print t.replace("$X",p[1]).replace("$T",p[0]).replace("$D1",D1).replace("$D2",D2)
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END_SHELL
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BEGIN_PROVIDER [ double precision, E_loc_srmc_block_walk ]
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&BEGIN_PROVIDER [ double precision, E_loc_2_srmc_block_walk ]
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&BEGIN_PROVIDER [ double precision, E_loc_srmc_block_walk_kahan, (3) ]
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&BEGIN_PROVIDER [ double precision, E_loc_2_srmc_block_walk_kahan, (3) ]
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implicit none
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include '../types.F'
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BEGIN_DOC
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! Properties averaged over the block using the SRMC method
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END_DOC
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real, allocatable :: elec_coord_tmp(:,:,:)
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integer :: mod_align
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double precision :: E_loc_save(4,walk_num_dmc_max)
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double precision :: E_loc_save_tmp(4,walk_num_dmc_max)
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double precision :: psi_value_save(walk_num)
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double precision :: psi_value_save_tmp(walk_num)
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double precision :: srmc_weight(walk_num)
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double precision, allocatable :: psi_grad_psi_inv_save(:,:,:)
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double precision, allocatable :: psi_grad_psi_inv_save_tmp(:,:,:)
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!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_grad_psi_inv_save
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!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_grad_psi_inv_save_tmp
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!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: E_loc_save
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!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: E_loc_save_tmp
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!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_value_save
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!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: psi_value_save_tmp
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!DIR$ ATTRIBUTES ALIGN : $IRP_ALIGN :: srmc_weight
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allocate ( psi_grad_psi_inv_save(elec_num_8,3,walk_num) , &
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psi_grad_psi_inv_save_tmp(elec_num_8,3,walk_num) , &
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elec_coord_tmp(mod_align(elec_num+1),3,walk_num) )
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psi_value_save = 0.d0
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psi_value_save_tmp = 0.d0
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srmc_weight = 1.d0
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! Initialization
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if (vmc_algo /= t_Brownian) then
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call abrt(irp_here,'SRMC should run with Brownian algorithm')
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endif
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integer :: k, i_walk, i_step
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BEGIN_SHELL [ /usr/bin/python ]
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from properties import *
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t = """
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if (calc_$X) then
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!DIR$ VECTOR ALIGNED
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$X_srmc_block_walk = 0.d0
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!DIR$ VECTOR ALIGNED
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$X_srmc_block_walk_kahan = 0.d0
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!DIR$ VECTOR ALIGNED
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$X_2_srmc_block_walk = 0.d0
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!DIR$ VECTOR ALIGNED
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$X_2_srmc_block_walk_kahan = 0.d0
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endif
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"""
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for p in properties:
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print t.replace("$X",p[1])
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END_SHELL
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logical :: loop
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integer*8 :: cpu0, cpu1, cpu2, count_rate, count_max
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loop = .True.
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call system_clock(cpu0, count_rate, count_max)
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cpu2 = cpu0
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block_weight = 0.d0
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real, external :: accep_rate
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double precision :: delta, thr
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thr = 2.d0/time_step_sq
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logical :: first_loop
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first_loop = .True.
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do while (loop)
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! Every walker makes a step
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do i_walk=1,walk_num
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if (.not.first_loop) then
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integer :: i,j,l
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do l=1,3
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do i=1,elec_num+1
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elec_coord(i,l) = elec_coord_full(i,l,i_walk)
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enddo
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do i=1,elec_num
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psi_grad_psi_inv_x(i) = psi_grad_psi_inv_save(i,1,i_walk)
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psi_grad_psi_inv_y(i) = psi_grad_psi_inv_save(i,2,i_walk)
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psi_grad_psi_inv_z(i) = psi_grad_psi_inv_save(i,3,i_walk)
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enddo
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psi_value = psi_value_save(i_walk)
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E_loc = E_loc_save(1,i_walk)
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enddo
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SOFT_TOUCH elec_coord psi_grad_psi_inv_x psi_grad_psi_inv_y psi_grad_psi_inv_z psi_value E_loc
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else
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do l=1,3
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do i=1,elec_num+1
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elec_coord(i,l) = elec_coord_full(i,l,i_walk)
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enddo
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enddo
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TOUCH elec_coord
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psi_value_save(i_walk) = psi_value
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E_loc_save(:,i_walk) = E_loc
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endif
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double precision :: p,q
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real :: delta_x
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logical :: accepted
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call brownian_step(p,q,accepted,delta_x)
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if ( psi_value * psi_value_save(i_walk) >= 0.d0 ) then
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! delta = (E_loc+E_loc_save(1,i_walk))*0.5d0
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! delta = (5.d0 * E_loc + 8.d0 * E_loc_save(1,i_walk) - E_loc_save(2,i_walk))/12.d0
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delta = (9.d0*E_loc+19.d0*E_loc_save(1,i_walk)- &
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5.d0*E_loc_save(2,i_walk)+E_loc_save(3,i_walk))/24.d0
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! delta = -((-251.d0*E_loc)-646.d0*E_loc_save(1,i_walk)+264.d0*E_loc_save(2,i_walk)-&
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! 106.d0*E_loc_save(3,i_walk)+19.d0*E_loc_save(4,i_walk))/720.d0
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delta = (delta - E_ref)*p
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if (delta >= 0.d0) then
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srmc_weight(i_walk) = dexp(-dtime_step*delta)
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else
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srmc_weight(i_walk) = 2.d0-dexp(dtime_step*delta)
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endif
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! if (accepted) then
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! ! Compute correction to past weights
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! double precision :: delta_old, delta_new
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! delta_old = (9.d0*E_loc_save(1,i_walk)+19.d0*E_loc_save(2,i_walk)-&
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! 5.d0*E_loc_save(3,i_walk)+E_loc_save(4,i_walk))/24.d0 - E_ref
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!
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!
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! if (delta_old >= 0.d0) then
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! srmc_weight(i_walk) = srmc_weight(i_walk) * dexp(dtime_step*delta_old)
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! else
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! srmc_weight(i_walk) = srmc_weight(i_walk) * (2.d0-dexp(-dtime_step*delta_old))
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! endif
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!
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! delta_new = (-(E_loc_save_tmp(3,i_walk)-13.d0*E_loc_save_tmp(2,i_walk)&
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! -13.d0*E_loc_save_tmp(1,i_walk)+E_loc))/24.d0 - E_ref
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!
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! if (delta_new >= 0.d0) then
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! srmc_weight(i_walk) = srmc_weight(i_walk) * dexp(-dtime_step*delta_new)
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! else
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! srmc_weight(i_walk) = srmc_weight(i_walk) * (2.d0-dexp(dtime_step*delta_new) )
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! endif
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!
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! endif
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elec_coord(elec_num+1,1) += p*time_step
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elec_coord(elec_num+1,2) = E_loc
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elec_coord(elec_num+1,3) = srmc_weight(i_walk) * srmc_pop_weight_mult
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do l=1,3
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do i=1,elec_num+1
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elec_coord_full(i,l,i_walk) = elec_coord(i,l)
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enddo
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enddo
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do i=1,elec_num
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psi_grad_psi_inv_save(i,1,i_walk) = psi_grad_psi_inv_x(i)
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psi_grad_psi_inv_save(i,2,i_walk) = psi_grad_psi_inv_y(i)
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psi_grad_psi_inv_save(i,3,i_walk) = psi_grad_psi_inv_z(i)
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enddo
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psi_value_save(i_walk) = psi_value
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if (accepted) then
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E_loc_save(4,i_walk) = E_loc_save(3,i_walk)
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E_loc_save(3,i_walk) = E_loc_save(2,i_walk)
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E_loc_save(2,i_walk) = E_loc_save(1,i_walk)
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E_loc_save(1,i_walk) = E_loc
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endif
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BEGIN_SHELL [ /usr/bin/python ]
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from properties import *
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t = """
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if (calc_$X) then
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! Kahan's summation algorithm to compute these sums reducing the rounding error:
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! $X_srmc_block_walk += $X * srmc_pop_weight_mult * srmc_weight(i_walk)
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! $X_2_srmc_block_walk += $X_2 * srmc_pop_weight_mult * srmc_weight(i_walk)
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! see http://en.wikipedia.org/wiki/Kahan_summation_algorithm
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$X_srmc_block_walk_kahan($D2 3) = $X * srmc_pop_weight_mult * srmc_weight(i_walk) - $X_srmc_block_walk_kahan($D2 1)
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$X_srmc_block_walk_kahan($D2 2) = $X_srmc_block_walk $D1 + $X_srmc_block_walk_kahan($D2 3)
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$X_srmc_block_walk_kahan($D2 1) = ($X_srmc_block_walk_kahan($D2 2) - $X_srmc_block_walk $D1 ) &
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- $X_srmc_block_walk_kahan($D2 3)
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$X_srmc_block_walk $D1 = $X_srmc_block_walk_kahan($D2 2)
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$X_2_srmc_block_walk_kahan($D2 3) = $X_2 * srmc_pop_weight_mult * srmc_weight(i_walk) - $X_2_srmc_block_walk_kahan($D2 1)
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$X_2_srmc_block_walk_kahan($D2 2) = $X_2_srmc_block_walk $D1 + $X_2_srmc_block_walk_kahan($D2 3)
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$X_2_srmc_block_walk_kahan($D2 1) = ($X_2_srmc_block_walk_kahan($D2 2) - $X_2_srmc_block_walk $D1 ) &
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- $X_2_srmc_block_walk_kahan($D2 3)
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$X_2_srmc_block_walk $D1 = $X_2_srmc_block_walk_kahan($D2 2)
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endif
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"""
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for p in properties:
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if p[2] == "":
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D1 = ""
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D2 = ""
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else:
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D1 = "("+":"*(p[2].count(',')+1)+")"
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D2 = ":"*(p[2].count(',')+1)+","
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print t.replace("$X",p[1]).replace("$D1",D1).replace("$D2",D2)
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END_SHELL
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block_weight += srmc_pop_weight_mult * srmc_weight(i_walk)
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else
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srmc_weight(i_walk) = 0.d0
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endif
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enddo
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! Move to the next projection step
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if (srmc_projection > 0) then
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srmc_projection_step = mod(srmc_projection_step,srmc_projection)+1
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else
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srmc_projection_step = 1
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endif
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! Eventually, recompute the weight of the population
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if (srmc_projection_step == 1) then
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srmc_pop_weight_mult = 1.d0
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do k=1,srmc_projection
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srmc_pop_weight_mult *= srmc_pop_weight(k)
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enddo
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endif
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! Remove contribution of the old value of the weight at the new
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! projection step
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srmc_pop_weight_mult *= 1.d0/srmc_pop_weight(srmc_projection_step)
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! Compute the new weight of the population
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double precision :: sum_weight
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sum_weight = 0.d0
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do k=1,walk_num
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sum_weight += srmc_weight(k)
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enddo
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srmc_pop_weight(srmc_projection_step) = sum_weight/dble(walk_num)
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! Update the running population weight
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srmc_pop_weight_mult *= srmc_pop_weight(srmc_projection_step)
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! Reconfiguration
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integer :: ipos(walk_num)
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call reconfigure(ipos,srmc_weight)
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do k=1,walk_num
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do l=1,3
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do i=1,elec_num+1
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elec_coord_tmp(i,l,k) = elec_coord_full(i,l,k)
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enddo
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do i=1,elec_num
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psi_grad_psi_inv_save_tmp(i,l,k) = psi_grad_psi_inv_save(i,l,k)
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enddo
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enddo
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psi_value_save_tmp(k) = psi_value_save(k)
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E_loc_save_tmp(:,k) = E_loc_save(:,k)
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enddo
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integer :: ipm
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do k=1,walk_num
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ipm = ipos(k)
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do l=1,3
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do i=1,elec_num+1
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elec_coord_full(i,l,k) = elec_coord_tmp(i,l,ipm)
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enddo
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do i=1,elec_num
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psi_grad_psi_inv_save(i,l,k) = psi_grad_psi_inv_save_tmp(i,l,ipm)
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enddo
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enddo
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psi_value_save(k) = psi_value_save_tmp(ipm)
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E_loc_save(:,k) = E_loc_save_tmp(:,ipm)
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enddo
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call system_clock(cpu1, count_rate, count_max)
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if (cpu1 < cpu0) then
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cpu1 = cpu1+cpu0
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endif
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loop = dble(cpu1-cpu0)*dble(walk_num)/dble(count_rate) < block_time
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if (cpu1-cpu2 > count_rate) then
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integer :: do_run
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call get_running(do_run)
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loop = loop.and.(do_run == t_Running)
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cpu2 = cpu1
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endif
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SOFT_TOUCH elec_coord_full srmc_pop_weight_mult
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first_loop = .False.
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enddo
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double precision :: factor
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factor = 1.d0/block_weight
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SOFT_TOUCH block_weight
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BEGIN_SHELL [ /usr/bin/python ]
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from properties import *
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t = """
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if (calc_$X) then
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$X_srmc_block_walk *= factor
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$X_2_srmc_block_walk *= factor
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endif
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"""
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for p in properties:
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print t.replace("$X",p[1])
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END_SHELL
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deallocate ( elec_coord_tmp, psi_grad_psi_inv_save, psi_grad_psi_inv_save_tmp )
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END_PROVIDER
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BEGIN_PROVIDER [ double precision, srmc_pop_weight_mult ]
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implicit none
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BEGIN_DOC
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! Population weight of SRMC
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END_DOC
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srmc_pop_weight_mult = srmc_pop_weight(srmc_projection)
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END_PROVIDER
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BEGIN_PROVIDER [ integer, srmc_projection ]
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&BEGIN_PROVIDER [ integer, srmc_projection_step ]
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implicit none
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BEGIN_DOC
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! Number of projection steps for SRMC
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END_DOC
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real :: srmc_projection_time
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srmc_projection_time = 1.
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call get_simulation_srmc_projection_time(srmc_projection_time)
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srmc_projection = int( srmc_projection_time/time_step)
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srmc_projection_step = 0
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END_PROVIDER
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BEGIN_PROVIDER [ double precision, srmc_pop_weight, (0:srmc_projection+1) ]
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implicit none
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BEGIN_DOC
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! Population weight of SRMC
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END_DOC
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srmc_pop_weight = 1.d0
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END_PROVIDER
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