mirror of
https://github.com/TREX-CoE/qmckl.git
synced 2024-08-17 10:51:44 +02:00
Fixed sub in een_rescaled_e.
This commit is contained in:
parent
e4beaff674
commit
b0a4d08ad8
@ -61,7 +61,7 @@ int main() {
|
||||
#include "qmckl_jastrow_private_func.h"
|
||||
#include "qmckl_jastrow_private_type.h"
|
||||
#+end_src
|
||||
|
||||
|
||||
* Context
|
||||
:PROPERTIES:
|
||||
:Name: qmckl_jastrow
|
||||
@ -609,7 +609,7 @@ qmckl_exit_code qmckl_get_jastrow_cord_vector (const qmckl_context context, doub
|
||||
}
|
||||
|
||||
assert (ctx->jastrow.cord_vector != NULL);
|
||||
memcpy(cord_vector, ctx->jastrow.cord_vector, ctx->jastrow.cord_num*sizeof(double));
|
||||
memcpy(cord_vector, ctx->jastrow.cord_vector, ctx->jastrow.dim_cord_vect*sizeof(double));
|
||||
return QMCKL_SUCCESS;
|
||||
}
|
||||
|
||||
@ -3022,8 +3022,16 @@ integer function qmckl_compute_een_rescaled_e_f(context, walk_num, elec_num, cor
|
||||
end do
|
||||
end do
|
||||
end do
|
||||
|
||||
do l = 0, cord_num
|
||||
do j = 1, elec_num
|
||||
een_rescaled_e(l, j, j, nw) = 0.0d0
|
||||
end do
|
||||
end do
|
||||
|
||||
end do
|
||||
|
||||
|
||||
end function qmckl_compute_een_rescaled_e_f
|
||||
#+end_src
|
||||
|
||||
@ -3107,6 +3115,10 @@ for l in range(1,cord_num+1):
|
||||
een_rescaled_e[j, i, l] = x
|
||||
k = k + 1
|
||||
|
||||
for l in range(0,cord_num+1):
|
||||
for j in range(0, elec_num):
|
||||
een_rescaled_e[j,j,l] = 0.0
|
||||
|
||||
print(" een_rescaled_e[0, 2, 1] = ",een_rescaled_e[0, 2, 1])
|
||||
print(" een_rescaled_e[0, 3, 1] = ",een_rescaled_e[0, 3, 1])
|
||||
print(" een_rescaled_e[0, 4, 1] = ",een_rescaled_e[0, 4, 1])
|
||||
@ -3141,7 +3153,7 @@ assert(fabs(een_rescaled_e[0][1][5][2]-0.3424402276009091) < 1.e-12);
|
||||
#+end_src
|
||||
|
||||
** Electron-electron rescaled distances for each order and derivatives
|
||||
|
||||
|
||||
~een_rescaled_e_deriv_e~ stores the table of the derivatives of the
|
||||
rescaled distances between all pairs of electrons and raised to the
|
||||
power \(p\) defined by ~cord_num~. Here we take its derivatives
|
||||
@ -4699,6 +4711,7 @@ end function qmckl_compute_lkpm_combined_index_f
|
||||
|
||||
*** Test
|
||||
|
||||
#+name: helper_funcs
|
||||
#+begin_src python :results output :exports none :noweb yes
|
||||
import numpy as np
|
||||
|
||||
@ -4725,21 +4738,46 @@ for l in range(2,cord_num+1):
|
||||
for i in range(elec_num):
|
||||
een_rescaled_n[a, i, l] = een_rescaled_n[a, i, l - 1] * een_rescaled_n[a, i, 1]
|
||||
|
||||
print(" een_rescaled_n[0, 2, 1] = ",een_rescaled_n[0, 2, 1])
|
||||
print(" een_rescaled_n[0, 3, 1] = ",een_rescaled_n[0, 3, 1])
|
||||
print(" een_rescaled_n[0, 4, 1] = ",een_rescaled_n[0, 4, 1])
|
||||
print(" een_rescaled_n[1, 3, 2] = ",een_rescaled_n[1, 3, 2])
|
||||
print(" een_rescaled_n[1, 4, 2] = ",een_rescaled_n[1, 4, 2])
|
||||
print(" een_rescaled_n[1, 5, 2] = ",een_rescaled_n[1, 5, 2])
|
||||
elec_dist = np.zeros(shape=(elec_num, elec_num),dtype=float)
|
||||
for i in range(elec_num):
|
||||
for j in range(elec_num):
|
||||
elec_dist[i, j] = np.linalg.norm(elec_coord[i] - elec_coord[j])
|
||||
|
||||
kappa = 1.0
|
||||
|
||||
een_rescaled_e_ij = np.zeros(shape=(elec_num * (elec_num - 1)//2, cord_num+1), dtype=float)
|
||||
een_rescaled_e_ij[:,0] = 1.0
|
||||
|
||||
k = 0
|
||||
for j in range(elec_num):
|
||||
for i in range(j):
|
||||
een_rescaled_e_ij[k, 1] = np.exp(-kappa * elec_dist[i, j])
|
||||
k = k + 1
|
||||
|
||||
for l in range(2, cord_num + 1):
|
||||
for k in range(elec_num * (elec_num - 1)//2):
|
||||
een_rescaled_e_ij[k, l] = een_rescaled_e_ij[k, l - 1] * een_rescaled_e_ij[k, 1]
|
||||
|
||||
een_rescaled_e = np.zeros(shape=(elec_num, elec_num, cord_num + 1), dtype=float)
|
||||
een_rescaled_e[:,:,0] = 1.0
|
||||
|
||||
for l in range(1,cord_num+1):
|
||||
k = 0
|
||||
for j in range(elec_num):
|
||||
for i in range(j):
|
||||
x = een_rescaled_e_ij[k, l]
|
||||
een_rescaled_e[i, j, l] = x
|
||||
een_rescaled_e[j, i, l] = x
|
||||
k = k + 1
|
||||
|
||||
for l in range(0,cord_num+1):
|
||||
for j in range(0, elec_num):
|
||||
een_rescaled_e[j,j,l] = 0.0
|
||||
|
||||
lkpm_of_cindex = np.array(lkpm_combined_index).T
|
||||
#+end_src
|
||||
|
||||
#+RESULTS:
|
||||
: een_rescaled_n[0, 2, 1] = 0.10612983920006765
|
||||
: een_rescaled_n[0, 3, 1] = 0.135652809635553
|
||||
: een_rescaled_n[0, 4, 1] = 0.023391817607642338
|
||||
: een_rescaled_n[1, 3, 2] = 0.880957224822116
|
||||
: een_rescaled_n[1, 4, 2] = 0.027185942659395074
|
||||
: een_rescaled_n[1, 5, 2] = 0.01343938025140174
|
||||
#+RESULTS: helper_funcs
|
||||
|
||||
#+begin_src c :tangle (eval c_test)
|
||||
//assert(qmckl_electron_provided(context));
|
||||
@ -5025,102 +5063,42 @@ import numpy as np
|
||||
|
||||
<<jastrow_data>>
|
||||
|
||||
<<helper_funcs>>
|
||||
|
||||
kappa = 1.0
|
||||
|
||||
elec_coord = np.array(elec_coord)[0]
|
||||
nucl_coord = np.array(nucl_coord)
|
||||
elnuc_dist = np.zeros(shape=(elec_num, nucl_num),dtype=float)
|
||||
for i in range(elec_num):
|
||||
for j in range(nucl_num):
|
||||
elnuc_dist[i, j] = np.linalg.norm(elec_coord[i] - nucl_coord[:,j])
|
||||
factor_een = 0.0
|
||||
|
||||
elnuc_dist_deriv_e = np.zeros(shape=(4, elec_num, nucl_num),dtype=float)
|
||||
for a in range(nucl_num):
|
||||
for i in range(elec_num):
|
||||
rij_inv = 1.0 / elnuc_dist[i, a]
|
||||
for ii in range(3):
|
||||
elnuc_dist_deriv_e[ii, i, a] = (elec_coord[i][ii] - nucl_coord[ii][a]) * rij_inv
|
||||
elnuc_dist_deriv_e[3, i, a] = 2.0 * rij_inv
|
||||
|
||||
en_distance_rescaled_deriv_e = np.zeros(shape=(4,elec_num,nucl_num),dtype=float)
|
||||
for a in range(nucl_num):
|
||||
for i in range(elec_num):
|
||||
f = 1.0 - kappa * en_distance_rescaled[i][a]
|
||||
for ii in range(4):
|
||||
en_distance_rescaled_deriv_e[ii][i][a] = elnuc_dist_deriv_e[ii][i][a]
|
||||
en_distance_rescaled_deriv_e[3][i][a] = en_distance_rescaled_deriv_e[3][i][a] + \
|
||||
(-kappa * en_distance_rescaled_deriv_e[0][i][a] * en_distance_rescaled_deriv_e[0][i][a]) + \
|
||||
(-kappa * en_distance_rescaled_deriv_e[1][i][a] * en_distance_rescaled_deriv_e[1][i][a]) + \
|
||||
(-kappa * en_distance_rescaled_deriv_e[2][i][a] * en_distance_rescaled_deriv_e[2][i][a])
|
||||
for ii in range(4):
|
||||
en_distance_rescaled_deriv_e[ii][i][a] = en_distance_rescaled_deriv_e[ii][i][a] * f
|
||||
|
||||
third = 1.0 / 3.0
|
||||
factor_en_deriv_e = np.zeros(shape=(4,elec_num),dtype=float)
|
||||
dx = np.zeros(shape=(4),dtype=float)
|
||||
pow_ser_g = np.zeros(shape=(3),dtype=float)
|
||||
for a in range(nucl_num):
|
||||
for i in range(elec_num):
|
||||
x = en_distance_rescaled[i][a]
|
||||
if abs(x) < 1e-18:
|
||||
continue
|
||||
pow_ser_g = np.zeros(shape=(3),dtype=float)
|
||||
den = 1.0 + aord_vector[1][type_nucl_vector[a]-1] * x
|
||||
invden = 1.0 / den
|
||||
invden2 = invden * invden
|
||||
invden3 = invden2 * invden
|
||||
xinv = 1.0 / (x + 1.0E-18)
|
||||
|
||||
for ii in range(4):
|
||||
dx[ii] = en_distance_rescaled_deriv_e[ii][i][a]
|
||||
|
||||
lap1 = 0.0
|
||||
lap2 = 0.0
|
||||
lap3 = 0.0
|
||||
for ii in range(3):
|
||||
x = en_distance_rescaled[i][a]
|
||||
if x < 1e-18:
|
||||
continue
|
||||
for p in range(2,aord_num+1):
|
||||
y = p * aord_vector[(p-1) + 1][type_nucl_vector[a]-1] * x
|
||||
pow_ser_g[ii] = pow_ser_g[ii] + y * dx[ii]
|
||||
lap1 = lap1 + (p - 1) * y * xinv * dx[ii] * dx[ii]
|
||||
lap2 = lap2 + y
|
||||
x = x * en_distance_rescaled[i][a]
|
||||
|
||||
lap3 = lap3 - 2.0 * aord_vector[1][type_nucl_vector[a]-1] * dx[ii] * dx[ii]
|
||||
|
||||
factor_en_deriv_e[ii][i] = factor_en_deriv_e[ii][i] + aord_vector[0][type_nucl_vector[a]-1] * \
|
||||
dx[ii] * invden2 + pow_ser_g[ii]
|
||||
|
||||
ii = 3
|
||||
lap2 = lap2 * dx[ii] * third
|
||||
lap3 = lap3 + den * dx[ii]
|
||||
lap3 = lap3 * (aord_vector[0][type_nucl_vector[a]-1] * invden3)
|
||||
factor_en_deriv_e[ii][i] = factor_en_deriv_e[ii][i] + lap1 + lap2 + lap3
|
||||
|
||||
print("factor_en_deriv_e[0][0]:",factor_en_deriv_e[0][0])
|
||||
print("factor_en_deriv_e[1][0]:",factor_en_deriv_e[1][0])
|
||||
print("factor_en_deriv_e[2][0]:",factor_en_deriv_e[2][0])
|
||||
print("factor_en_deriv_e[3][0]:",factor_en_deriv_e[3][0])
|
||||
for n in range(0, dim_cord_vect):
|
||||
l = lkpm_of_cindex[0,n]
|
||||
k = lkpm_of_cindex[1,n]
|
||||
p = lkpm_of_cindex[2,n]
|
||||
m = lkpm_of_cindex[3,n]
|
||||
|
||||
for a in range(0, nucl_num):
|
||||
accu2 = 0.0
|
||||
cn = cord_vector_full[a][n]
|
||||
for j in range(0, elec_num):
|
||||
accu = 0.0
|
||||
for i in range(0, elec_num):
|
||||
accu = accu + een_rescaled_e[i,j,k] * \
|
||||
een_rescaled_n[a,i,m]
|
||||
accu2 = accu2 + accu * een_rescaled_n[a,j,m+l]
|
||||
factor_een = factor_een + accu2 * cn
|
||||
|
||||
print("factor_een:",factor_een)
|
||||
#+end_src
|
||||
|
||||
#+RESULTS:
|
||||
: factor_en_deriv_e[0][0]: 0.11609919541763383
|
||||
: factor_en_deriv_e[1][0]: -0.23301394780804574
|
||||
: factor_en_deriv_e[2][0]: 0.17548337641865783
|
||||
: factor_en_deriv_e[3][0]: -0.9667363412285741
|
||||
: factor_een: -0.37407972141304213
|
||||
|
||||
|
||||
#+begin_src c :tangle (eval c_test)
|
||||
/* Check if Jastrow is properly initialized */
|
||||
assert(qmckl_jastrow_provided(context));
|
||||
|
||||
//double factor_een[walk_num];
|
||||
//rc = qmckl_get_jastrow_factor_een(context, &(factor_een[0]));
|
||||
|
||||
double factor_een[walk_num];
|
||||
rc = qmckl_get_jastrow_factor_een(context, &(factor_een[0]));
|
||||
|
||||
#+end_src
|
||||
|
||||
|
@ -1117,7 +1117,7 @@ double n2_elec_coord[n2_walk_num][n2_elec_num][3] = { {
|
||||
#define n2_type_nucl_num ((int64_t) 1)
|
||||
#define n2_aord_num ((int64_t) 5)
|
||||
#define n2_bord_num ((int64_t) 5)
|
||||
#define n2_cord_num ((int64_t) 23)
|
||||
#define n2_cord_num ((int64_t) 5)
|
||||
#define n2_dim_cord_vec ((int64_t) 23)
|
||||
|
||||
int64_t n2_type_nucl_vector[n2_nucl_num] = {
|
||||
@ -1140,7 +1140,7 @@ double n2_bord_vector[n2_bord_num + 1] = {
|
||||
0.0073096 ,
|
||||
0.002866 };
|
||||
|
||||
double n2_cord_vector[n2_cord_num][n2_type_nucl_num] = {
|
||||
double n2_cord_vector[n2_dim_cord_vec][n2_type_nucl_num] = {
|
||||
{ 5.717020e-01},
|
||||
{-5.142530e-01},
|
||||
{-5.130430e-01},
|
||||
|
Loading…
Reference in New Issue
Block a user