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Fixed sub in een_rescaled_e.

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v1j4y 2021-09-22 15:47:39 +02:00
parent e4beaff674
commit b0a4d08ad8
2 changed files with 78 additions and 100 deletions
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174
org/qmckl_jastrow.org
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@ -61,7 +61,7 @@ int main() {
#include "qmckl_jastrow_private_func.h" #include "qmckl_jastrow_private_func.h"
#include "qmckl_jastrow_private_type.h" #include "qmckl_jastrow_private_type.h"
#+end_src #+end_src
* Context * Context
:PROPERTIES: :PROPERTIES:
:Name: qmckl_jastrow :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); 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; 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 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 do
end function qmckl_compute_een_rescaled_e_f end function qmckl_compute_een_rescaled_e_f
#+end_src #+end_src
@ -3107,6 +3115,10 @@ for l in range(1,cord_num+1):
een_rescaled_e[j, i, l] = x een_rescaled_e[j, i, l] = x
k = k + 1 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, 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, 3, 1] = ",een_rescaled_e[0, 3, 1])
print(" een_rescaled_e[0, 4, 1] = ",een_rescaled_e[0, 4, 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 #+end_src
** Electron-electron rescaled distances for each order and derivatives ** Electron-electron rescaled distances for each order and derivatives
~een_rescaled_e_deriv_e~ stores the table of the derivatives of the ~een_rescaled_e_deriv_e~ stores the table of the derivatives of the
rescaled distances between all pairs of electrons and raised to the rescaled distances between all pairs of electrons and raised to the
power \(p\) defined by ~cord_num~. Here we take its derivatives power \(p\) defined by ~cord_num~. Here we take its derivatives
@ -4699,6 +4711,7 @@ end function qmckl_compute_lkpm_combined_index_f
*** Test *** Test
#+name: helper_funcs
#+begin_src python :results output :exports none :noweb yes #+begin_src python :results output :exports none :noweb yes
import numpy as np import numpy as np
@ -4725,21 +4738,46 @@ for l in range(2,cord_num+1):
for i in range(elec_num): 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] 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]) elec_dist = np.zeros(shape=(elec_num, elec_num),dtype=float)
print(" een_rescaled_n[0, 3, 1] = ",een_rescaled_n[0, 3, 1]) for i in range(elec_num):
print(" een_rescaled_n[0, 4, 1] = ",een_rescaled_n[0, 4, 1]) for j in range(elec_num):
print(" een_rescaled_n[1, 3, 2] = ",een_rescaled_n[1, 3, 2]) elec_dist[i, j] = np.linalg.norm(elec_coord[i] - elec_coord[j])
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]) 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 #+end_src
#+RESULTS: #+RESULTS: helper_funcs
: 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
#+begin_src c :tangle (eval c_test) #+begin_src c :tangle (eval c_test)
//assert(qmckl_electron_provided(context)); //assert(qmckl_electron_provided(context));
@ -5025,102 +5063,42 @@ import numpy as np
<<jastrow_data>> <<jastrow_data>>
<<helper_funcs>>
kappa = 1.0 kappa = 1.0
elec_coord = np.array(elec_coord)[0] factor_een = 0.0
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])
elnuc_dist_deriv_e = np.zeros(shape=(4, elec_num, nucl_num),dtype=float) for n in range(0, dim_cord_vect):
for a in range(nucl_num): l = lkpm_of_cindex[0,n]
for i in range(elec_num): k = lkpm_of_cindex[1,n]
rij_inv = 1.0 / elnuc_dist[i, a] p = lkpm_of_cindex[2,n]
for ii in range(3): m = lkpm_of_cindex[3,n]
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 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 #+end_src
#+RESULTS: #+RESULTS:
: factor_en_deriv_e[0][0]: 0.11609919541763383 : factor_een: -0.37407972141304213
: factor_en_deriv_e[1][0]: -0.23301394780804574
: factor_en_deriv_e[2][0]: 0.17548337641865783
: factor_en_deriv_e[3][0]: -0.9667363412285741
#+begin_src c :tangle (eval c_test) #+begin_src c :tangle (eval c_test)
/* Check if Jastrow is properly initialized */ /* Check if Jastrow is properly initialized */
assert(qmckl_jastrow_provided(context)); assert(qmckl_jastrow_provided(context));
//double factor_een[walk_num]; double factor_een[walk_num];
//rc = qmckl_get_jastrow_factor_een(context, &(factor_een[0])); rc = qmckl_get_jastrow_factor_een(context, &(factor_een[0]));
#+end_src #+end_src

4
org/qmckl_tests.org
View File

@ -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_type_nucl_num ((int64_t) 1)
#define n2_aord_num ((int64_t) 5) #define n2_aord_num ((int64_t) 5)
#define n2_bord_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) #define n2_dim_cord_vec ((int64_t) 23)
int64_t n2_type_nucl_vector[n2_nucl_num] = { int64_t n2_type_nucl_vector[n2_nucl_num] = {
@ -1140,7 +1140,7 @@ double n2_bord_vector[n2_bord_num + 1] = {
0.0073096 , 0.0073096 ,
0.002866 }; 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}, { 5.717020e-01},
{-5.142530e-01}, {-5.142530e-01},
{-5.130430e-01}, {-5.130430e-01},