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Merge branch 'master' of github.com:TREX-CoE/qmckl

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Anthony Scemama 2021-09-28 22:36:44 +02:00
commit 92b425fe85
6 changed files with 1629 additions and 360 deletions
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17
org/qmckl_ao.org
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@ -14,10 +14,10 @@ Gaussian ($p=2$):
\exp \left( - \gamma_{ks} | \mathbf{r}-\mathbf{R}_A | ^p \right).
\]
In the case of Gaussian functions, $n_s$ is always zero.
The normalization factor $\mathcal{N}_s$ ensures that all the functions
of the shell are normalized to unity. Usually, basis sets are given
a combination of normalized primitives, so the normalization
In the case of Gaussian functions, $n_s$ is always zero. The
normalization factor $\mathcal{N}_s$ ensures that all the functions of
the shell are normalized (integrate) to unity. Usually, basis sets are
given a combination of normalized primitives, so the normalization
coefficients of the primitives, $f_{ks}$, need also to be provided.
Atomic orbitals (AOs) are defined as
@ -26,10 +26,11 @@ Atomic orbitals (AOs) are defined as
\chi_i (\mathbf{r}) = \mathcal{M}_i\, P_{\eta(i)}(\mathbf{r})\, R_{\theta(i)} (\mathbf{r})
\]
where $\theta(i)$ returns the shell on which the AO is expanded,
and $\eta(i)$ denotes which angular function is chosen.
Here, the parameter $\mathcal{M}_i$ is an extra parameter which allows
the normalization of the different functions of the same shell to be
where $\theta(i)$ returns the shell on which the AO is expanded, and
$\eta(i)$ denotes which angular function is chosen and $P$ are the
generating functions of the given angular momentum $\eta(i)$. Here,
the parameter $\mathcal{M}_i$ is an extra parameter which allows the
normalization of the different functions of the same shell to be
different, as in GAMESS for example.
In this section we describe first how the basis set is stored in the

606
org/qmckl_jastrow.org
View File

@ -202,7 +202,7 @@ for i in range(elec_num):
type_nucl_num = 1
aord_num = 5
bord_num = 5
cord_num = 23
cord_num = 5
dim_cord_vect= 23
type_nucl_vector = [ 1, 1]
aord_vector = [
@ -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;
}
@ -860,19 +860,22 @@ qmckl_exit_code qmckl_set_jastrow_cord_vector(qmckl_context context, double cons
int32_t mask = 1 << 5;
int64_t cord_num;
qmckl_exit_code rc = qmckl_get_jastrow_cord_num(context, &cord_num);
qmckl_exit_code rc = qmckl_provide_dim_cord_vect(context);
if (rc != QMCKL_SUCCESS) return rc;
int64_t dim_cord_vect;
rc = qmckl_get_jastrow_dim_cord_vect(context, &dim_cord_vect);
if (rc != QMCKL_SUCCESS) return rc;
int64_t type_nucl_num;
rc = qmckl_get_jastrow_type_nucl_num(context, &type_nucl_num);
if (rc != QMCKL_SUCCESS) return rc;
if (cord_num == 0) {
if (dim_cord_vect == 0) {
return qmckl_failwith( context,
QMCKL_FAILURE,
"qmckl_set_jastrow_coefficient",
"cord_num is not set");
"dim_cord_vect is not set");
}
if (cord_vector == NULL) {
@ -892,7 +895,7 @@ qmckl_exit_code qmckl_set_jastrow_cord_vector(qmckl_context context, double cons
}
qmckl_memory_info_struct mem_info = qmckl_memory_info_struct_zero;
mem_info.size = cord_num * type_nucl_num * sizeof(double);
mem_info.size = dim_cord_vect * type_nucl_num * sizeof(double);
double* new_array = (double*) qmckl_malloc(context, mem_info);
if(new_array == NULL) {
@ -1324,20 +1327,20 @@ end function qmckl_compute_asymp_jasb_f
#+CALL: generate_c_header(table=qmckl_asymp_jasb_args,rettyp=get_value("CRetType"),fname=get_value("Name"))
#+RESULTS:
#+begin_src c :tangle (eval h_private_func) :comments org
#+BEGIN_src c :tangle (eval h_func) :comments org
qmckl_exit_code qmckl_compute_asymp_jasb (
const qmckl_context context,
const int64_t bord_num,
const double* bord_vector,
const double rescale_factor_kappa_ee,
double* const asymp_jasb );
#+end_src
#+END_src
#+CALL: generate_c_interface(table=qmckl_asymp_jasb_args,rettyp=get_value("CRetType"),fname=get_value("Name"))
#+RESULTS:
#+begin_src f90 :tangle (eval f) :comments org :exports none
#+BEGIN_src f90 :tangle (eval f) :comments org :exports none
integer(c_int32_t) function qmckl_compute_asymp_jasb &
(context, bord_num, bord_vector, rescale_factor_kappa_ee, asymp_jasb) &
bind(C) result(info)
@ -1356,7 +1359,7 @@ end function qmckl_compute_asymp_jasb_f
(context, bord_num, bord_vector, rescale_factor_kappa_ee, asymp_jasb)
end function qmckl_compute_asymp_jasb
#+end_src
#+END_src
*** Test
#+name: asymp_jasb
@ -1380,11 +1383,6 @@ print("asymp_jasb[1] : ", asymp_jasb[1])
#+end_src
#+RESULTS: asymp_jasb
: asym_one : 0.6634291325000664
: asymp_jasb[0] : 1.043287918508297
: asymp_jasb[1] : 0.7115733522582638
#+RESULTS:
: asym_one : 0.43340325572525706
: asymp_jasb[0] : 0.5323750557252571
: asymp_jasb[1] : 0.31567342786262853
@ -1416,6 +1414,8 @@ rc = qmckl_set_jastrow_aord_vector(context, aord_vector);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_jastrow_bord_vector(context, bord_vector);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_jastrow_bord_vector(context, bord_vector);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_jastrow_cord_vector(context, cord_vector);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_jastrow_dependencies(context);
@ -2114,28 +2114,16 @@ print("factor_ee_deriv_e[0][0]:",factor_ee_deriv_e[0][0])
print("factor_ee_deriv_e[1][0]:",factor_ee_deriv_e[1][0])
print("factor_ee_deriv_e[2][0]:",factor_ee_deriv_e[2][0])
print("factor_ee_deriv_e[3][0]:",factor_ee_deriv_e[3][0])
print(factor_ee_deriv_e)
#+end_src
#+RESULTS:
#+begin_example
asym_one : 0.43340325572525706
asymp_jasb[0] : 0.5323750557252571
asymp_jasb[1] : 0.31567342786262853
factor_ee_deriv_e[0][0]: 0.16364894652107934
factor_ee_deriv_e[1][0]: -0.6927548119830084
factor_ee_deriv_e[2][0]: 0.073267755223968
factor_ee_deriv_e[3][0]: 1.5111672803213185
[[ 0.16364895 0.60354957 -0.19825547 0.02359797 -0.13123153 -0.18789233
0.07762515 -0.42459184 0.27920265 -0.2056531 ]
[-0.69275481 0.15690393 0.09831069 0.18490587 0.04361723 0.3250686
0.12657961 -0.01736522 -0.40149005 0.17622416]
[ 0.07326776 -0.27532276 0.22396943 0.18771633 -0.34506246 0.07298062
0.63302352 -0.00910198 -0.30238713 -0.25908332]
[ 1.51116728 1.5033247 0.00325003 2.89377255 0.1338393 2.15893795
1.74732003 0.23561147 2.67455607 0.82810434]]
#+end_example
: asym_one : 0.43340325572525706
: asymp_jasb[0] : 0.5323750557252571
: asymp_jasb[1] : 0.31567342786262853
: factor_ee_deriv_e[0][0]: 0.16364894652107934
: factor_ee_deriv_e[1][0]: -0.6927548119830084
: factor_ee_deriv_e[2][0]: 0.073267755223968
: factor_ee_deriv_e[3][0]: 1.5111672803213185
#+begin_src c :tangle (eval c_test)
@ -3039,6 +3027,13 @@ 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
@ -3124,6 +3119,10 @@ 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])
@ -3135,7 +3134,7 @@ print(" een_rescaled_e[1, 5, 2] = ",een_rescaled_e[1, 5, 2])
#+RESULTS:
: een_rescaled_e[0, 2, 1] = 0.08084493981483197
: een_rescaled_e[0, 3, 1] = 0.1066745707571846
: een_rescaled_e[0, 4, 1] = 0.01754273169464735
: een_rescaled_e[0, 4, 1] = 0.017542731694647366
: een_rescaled_e[1, 3, 2] = 0.02214680362033448
: een_rescaled_e[1, 4, 2] = 0.0005700154999202759
: een_rescaled_e[1, 5, 2] = 0.3424402276009091
@ -3159,9 +3158,10 @@ assert(fabs(een_rescaled_e[0][1][5][2]-0.3424402276009091) < 1.e-12);
** Electron-electron rescaled distances for each order and derivatives
~een_rescaled_e~ stores the table of the rescaled distances between all
pairs of electrons and raised to the power \(p\) defined by ~cord_num~.
Here we take its derivatives required for the een jastrow.
~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
required for the een jastrow.
TODO: write formulae
@ -3419,7 +3419,7 @@ end function qmckl_compute_factor_een_rescaled_e_deriv_e_f
#+end_src
*** Test
#+name: een_e_deriv_e
#+begin_src python :results output :exports none :noweb yes
import numpy as np
@ -3431,6 +3431,16 @@ 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])
elec_dist_deriv_e = np.zeros(shape=(4,elec_num, elec_num),dtype=float)
for j in range(elec_num):
for i in range(elec_num):
rij_inv = 1.0 / elec_dist[i, j]
for ii in range(3):
elec_dist_deriv_e[ii, i, j] = -(elec_coord[j][ii] - elec_coord[i][ii]) * rij_inv
elec_dist_deriv_e[3, i, j] = 2.0 * rij_inv
elec_dist_deriv_e[:, j, j] = 0.0
kappa = 1.0
een_rescaled_e_ij = np.zeros(shape=(elec_num * (elec_num - 1)//2, cord_num+1), dtype=float)
@ -3458,25 +3468,49 @@ for l in range(1,cord_num+1):
een_rescaled_e[j, i, l] = x
k = k + 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, 4, 1] = ",een_rescaled_e[0, 4, 1])
print(" een_rescaled_e[1, 3, 2] = ",een_rescaled_e[1, 3, 2])
print(" een_rescaled_e[1, 4, 2] = ",een_rescaled_e[1, 4, 2])
print(" een_rescaled_e[1, 5, 2] = ",een_rescaled_e[1, 5, 2])
een_rescaled_e_deriv_e = np.zeros(shape=(elec_num,4,elec_num,cord_num+1),dtype=float)
for l in range(0,cord_num+1):
kappa_l = -1.0 * kappa * l
for j in range(0,elec_num):
for i in range(0,elec_num):
for ii in range(0,4):
een_rescaled_e_deriv_e[i,ii,j,l] = kappa_l * elec_dist_deriv_e[ii,i,j]
een_rescaled_e_deriv_e[i,3,j,l] = een_rescaled_e_deriv_e[i,3,j,l] + \
een_rescaled_e_deriv_e[i,0,j,l] * een_rescaled_e_deriv_e[i,0,j,l] + \
een_rescaled_e_deriv_e[i,1,j,l] * een_rescaled_e_deriv_e[i,1,j,l] + \
een_rescaled_e_deriv_e[i,2,j,l] * een_rescaled_e_deriv_e[i,2,j,l]
for ii in range(0,4):
een_rescaled_e_deriv_e[i,ii,j,l] = een_rescaled_e_deriv_e[i,ii,j,l] * een_rescaled_e[i,j,l]
#print(" een_rescaled_e_deriv_e[1, 1, 3, 1] = ",een_rescaled_e_deriv_e[0, 0, 2, 1])
#print(" een_rescaled_e_deriv_e[1, 1, 4, 1] = ",een_rescaled_e_deriv_e[0, 0, 3, 1])
#print(" een_rescaled_e_deriv_e[1, 1, 5, 1] = ",een_rescaled_e_deriv_e[0, 0, 4, 1])
#print(" een_rescaled_e_deriv_e[2, 1, 4, 2] = ",een_rescaled_e_deriv_e[1, 0, 3, 2])
#print(" een_rescaled_e_deriv_e[2, 1, 5, 2] = ",een_rescaled_e_deriv_e[1, 0, 4, 2])
#print(" een_rescaled_e_deriv_e[2, 1, 6, 2] = ",een_rescaled_e_deriv_e[1, 0, 5, 2])
#+end_src
#+RESULTS:
: een_rescaled_e[0, 2, 1] = 0.08084493981483197
: een_rescaled_e[0, 3, 1] = 0.1066745707571846
: een_rescaled_e[0, 4, 1] = 0.01754273169464735
: een_rescaled_e[1, 3, 2] = 0.02214680362033448
: een_rescaled_e[1, 4, 2] = 0.0005700154999202759
: een_rescaled_e[1, 5, 2] = 0.3424402276009091
#+RESULTS: een_e_deriv_e
: een_rescaled_e_deriv_e[1, 1, 3, 1] = 0.05991352796887283
: een_rescaled_e_deriv_e[1, 1, 4, 1] = 0.011714035071545248
: een_rescaled_e_deriv_e[1, 1, 5, 1] = 0.00441398875758468
: een_rescaled_e_deriv_e[2, 1, 4, 2] = 0.013553180060167595
: een_rescaled_e_deriv_e[2, 1, 5, 2] = 0.00041342909359870457
: een_rescaled_e_deriv_e[2, 1, 6, 2] = 0.5880599146214673
#+begin_src c :tangle (eval c_test)
//assert(qmckl_electron_provided(context));
double een_rescaled_e_deriv_e[walk_num][elec_num][4][elec_num][(cord_num + 1)];
rc = qmckl_get_jastrow_een_rescaled_e_deriv_e(context, &(een_rescaled_e_deriv_e[0][0][0][0][0]));
// value of (0,0,0,2,1)
assert(fabs(een_rescaled_e_deriv_e[0][0][0][2][1] + 0.05991352796887283 ) < 1.e-12);
assert(fabs(een_rescaled_e_deriv_e[0][0][0][3][1] + 0.011714035071545248 ) < 1.e-12);
assert(fabs(een_rescaled_e_deriv_e[0][0][0][4][1] + 0.00441398875758468 ) < 1.e-12);
assert(fabs(een_rescaled_e_deriv_e[0][1][0][3][2] + 0.013553180060167595 ) < 1.e-12);
assert(fabs(een_rescaled_e_deriv_e[0][1][0][4][2] + 0.00041342909359870457) < 1.e-12);
assert(fabs(een_rescaled_e_deriv_e[0][1][0][5][2] + 0.5880599146214673 ) < 1.e-12);
#+end_src
** Electron-nucleus rescaled distances for each order
@ -4076,6 +4110,14 @@ for i in range(elec_num):
for a in range(nucl_num):
elnuc_dist[i, a] = np.linalg.norm(elec_coord[i] - nucl_coord[:,a])
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
kappa = 1.0
een_rescaled_n = np.zeros(shape=(nucl_num, elec_num, cord_num + 1), dtype=float)
@ -4090,24 +4132,50 @@ 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])
een_rescaled_n_deriv_e = np.zeros(shape=(elec_num,4,nucl_num,cord_num+1),dtype=float)
for l in range(0,cord_num+1):
kappa_l = -1.0 * kappa * l
for j in range(0,elec_num):
for a in range(0,nucl_num):
for ii in range(0,4):
een_rescaled_n_deriv_e[j,ii,a,l] = kappa_l * elnuc_dist_deriv_e[ii,j,a]
een_rescaled_n_deriv_e[j,3,a,l] = een_rescaled_n_deriv_e[j,3,a,l] + \
een_rescaled_n_deriv_e[j,0,a,l] * een_rescaled_n_deriv_e[j,0,a,l] + \
een_rescaled_n_deriv_e[j,1,a,l] * een_rescaled_n_deriv_e[j,1,a,l] + \
een_rescaled_n_deriv_e[j,2,a,l] * een_rescaled_n_deriv_e[j,2,a,l]
for ii in range(0,4):
een_rescaled_n_deriv_e[j,ii,a,l] = een_rescaled_n_deriv_e[j,ii,a,l] * een_rescaled_n[a,j,l]
print(" een_rescaled_n_deriv_e[1, 1, 3, 1] = ",een_rescaled_n_deriv_e[2, 0, 0, 1])
print(" een_rescaled_n_deriv_e[1, 1, 4, 1] = ",een_rescaled_n_deriv_e[3, 0, 0, 1])
print(" een_rescaled_n_deriv_e[1, 1, 5, 1] = ",een_rescaled_n_deriv_e[4, 0, 0, 1])
print(" een_rescaled_n_deriv_e[2, 1, 4, 2] = ",een_rescaled_n_deriv_e[3, 0, 1, 2])
print(" een_rescaled_n_deriv_e[2, 1, 5, 2] = ",een_rescaled_n_deriv_e[4, 0, 1, 2])
print(" een_rescaled_n_deriv_e[2, 1, 6, 2] = ",een_rescaled_n_deriv_e[5, 0, 1, 2])
#+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
: een_rescaled_n_deriv_e[1, 1, 3, 1] = -0.07633444246999128
: een_rescaled_n_deriv_e[1, 1, 4, 1] = 0.00033282346259738276
: een_rescaled_n_deriv_e[1, 1, 5, 1] = -0.004775370547333061
: een_rescaled_n_deriv_e[2, 1, 4, 2] = 0.1362654644223866
: een_rescaled_n_deriv_e[2, 1, 5, 2] = -0.0231253431662794
: een_rescaled_n_deriv_e[2, 1, 6, 2] = 0.001593334817691633
#+begin_src c :tangle (eval c_test)
//assert(qmckl_electron_provided(context));
assert(qmckl_electron_provided(context));
double een_rescaled_n_deriv_e[walk_num][elec_num][4][nucl_num][(cord_num + 1)];
rc = qmckl_get_jastrow_een_rescaled_n_deriv_e(context, &(een_rescaled_n_deriv_e[0][0][0][0][0]));
// value of (0,2,1)
assert(fabs(een_rescaled_n_deriv_e[0][2][0][0][1]+0.07633444246999128 ) < 1.e-12);
assert(fabs(een_rescaled_n_deriv_e[0][3][0][0][1]-0.00033282346259738276) < 1.e-12);
assert(fabs(een_rescaled_n_deriv_e[0][4][0][0][1]+0.004775370547333061 ) < 1.e-12);
assert(fabs(een_rescaled_n_deriv_e[0][3][0][1][2]-0.1362654644223866 ) < 1.e-12);
assert(fabs(een_rescaled_n_deriv_e[0][4][0][1][2]+0.0231253431662794 ) < 1.e-12);
assert(fabs(een_rescaled_n_deriv_e[0][5][0][1][2]-0.001593334817691633 ) < 1.e-12);
#+end_src
@ -4264,7 +4332,6 @@ qmckl_exit_code qmckl_provide_cord_vect_full(qmckl_context context)
qmckl_exit_code rc =
qmckl_compute_cord_vect_full(context,
ctx->nucleus.num,
ctx->jastrow.cord_num,
ctx->jastrow.dim_cord_vect,
ctx->jastrow.type_nucl_num,
ctx->jastrow.type_nucl_vector,
@ -4426,26 +4493,24 @@ end function qmckl_compute_dim_cord_vect_f
#+NAME: qmckl_factor_cord_vect_full_args
| qmckl_context | context | in | Global state |
| int64_t | nucl_num | in | Number of atoms |
| int64_t | cord_num | in | Order of polynomials |
| int64_t | dim_cord_vect | in | dimension of cord full table |
| int64_t | type_nucl_num | in | dimension of cord full table |
| int64_t | type_nucl_vector[nucl_num] | in | dimension of cord full table |
| double | cord_vector[cord_num][type_nucl_num] | in | dimension of cord full table |
| double | cord_vector[dim_cord_vect][type_nucl_num] | in | dimension of cord full table |
| double | cord_vect_full[dim_cord_vect][nucl_num] | out | Full list of coefficients |
#+begin_src f90 :comments org :tangle (eval f) :noweb yes
integer function qmckl_compute_cord_vect_full_f(context, nucl_num, cord_num, dim_cord_vect, type_nucl_num, &
integer function qmckl_compute_cord_vect_full_f(context, nucl_num, dim_cord_vect, type_nucl_num, &
type_nucl_vector, cord_vector, cord_vect_full) &
result(info)
use qmckl
implicit none
integer(qmckl_context), intent(in) :: context
integer*8 , intent(in) :: nucl_num
integer*8 , intent(in) :: cord_num
integer*8 , intent(in) :: dim_cord_vect
integer*8 , intent(in) :: type_nucl_num
integer*8 , intent(in) :: type_nucl_vector(nucl_num)
double precision , intent(in) :: cord_vector(cord_num, type_nucl_num)
double precision , intent(in) :: cord_vector(type_nucl_num, dim_cord_vect)
double precision , intent(out) :: cord_vect_full(nucl_num,dim_cord_vect)
double precision :: x
integer*8 :: i, a, k, l, nw
@ -4462,11 +4527,6 @@ integer function qmckl_compute_cord_vect_full_f(context, nucl_num, cord_num, dim
return
endif
if (cord_num <= 0) then
info = QMCKL_INVALID_ARG_3
return
endif
if (type_nucl_num <= 0) then
info = QMCKL_INVALID_ARG_4
return
@ -4479,7 +4539,7 @@ integer function qmckl_compute_cord_vect_full_f(context, nucl_num, cord_num, dim
do a = 1, nucl_num
cord_vect_full(1:dim_cord_vect,a) = cord_vector(1:dim_cord_vect,type_nucl_vector(a))
cord_vect_full(a,1:dim_cord_vect) = cord_vector(type_nucl_vector(a),1:dim_cord_vect)
end do
end function qmckl_compute_cord_vect_full_f
@ -4492,7 +4552,6 @@ end function qmckl_compute_cord_vect_full_f
qmckl_exit_code qmckl_compute_cord_vect_full (
const qmckl_context context,
const int64_t nucl_num,
const int64_t cord_num,
const int64_t dim_cord_vect,
const int64_t type_nucl_num,
const int64_t* type_nucl_vector,
@ -4506,14 +4565,7 @@ end function qmckl_compute_cord_vect_full_f
#+RESULTS:
#+begin_src f90 :tangle (eval f) :comments org :exports none
integer(c_int32_t) function qmckl_compute_cord_vect_full &
(context, &
nucl_num, &
cord_num, &
dim_cord_vect, &
type_nucl_num, &
type_nucl_vector, &
cord_vector, &
cord_vect_full) &
(context, nucl_num, dim_cord_vect, type_nucl_num, type_nucl_vector, cord_vector, cord_vect_full) &
bind(C) result(info)
use, intrinsic :: iso_c_binding
@ -4521,23 +4573,15 @@ end function qmckl_compute_cord_vect_full_f
integer (c_int64_t) , intent(in) , value :: context
integer (c_int64_t) , intent(in) , value :: nucl_num
integer (c_int64_t) , intent(in) , value :: cord_num
integer (c_int64_t) , intent(in) , value :: dim_cord_vect
integer (c_int64_t) , intent(in) , value :: type_nucl_num
integer (c_int64_t) , intent(in) :: type_nucl_vector(nucl_num)
real (c_double ) , intent(in) :: cord_vector(type_nucl_num,cord_num)
real (c_double ) , intent(in) :: cord_vector(type_nucl_num,dim_cord_vect)
real (c_double ) , intent(out) :: cord_vect_full(nucl_num,dim_cord_vect)
integer(c_int32_t), external :: qmckl_compute_cord_vect_full_f
info = qmckl_compute_cord_vect_full_f &
(context, &
nucl_num, &
cord_num, &
dim_cord_vect, &
type_nucl_num, &
type_nucl_vector, &
cord_vector, &
cord_vect_full)
(context, nucl_num, dim_cord_vect, type_nucl_num, type_nucl_vector, cord_vector, cord_vect_full)
end function qmckl_compute_cord_vect_full
#+end_src
@ -4644,9 +4688,9 @@ end function qmckl_compute_lkpm_combined_index_f
end function qmckl_compute_lkpm_combined_index
#+end_src
*** Test
#+name: helper_funcs
#+begin_src python :results output :exports none :noweb yes
import numpy as np
@ -4673,21 +4717,46 @@ 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));
@ -4834,10 +4903,10 @@ integer function qmckl_compute_factor_een_f(context, walk_num, elec_num, nucl_nu
implicit none
integer(qmckl_context), intent(in) :: context
integer*8 , intent(in) :: walk_num, elec_num, cord_num, nucl_num, dim_cord_vect
integer*8 , intent(in) :: lkpm_combined_index(4,dim_cord_vect)
double precision , intent(in) :: cord_vect_full(dim_cord_vect, nucl_num)
double precision , intent(in) :: een_rescaled_e(walk_num, elec_num, elec_num, 0:cord_num)
double precision , intent(in) :: een_rescaled_n(walk_num, elec_num, nucl_num, 0:cord_num)
integer*8 , intent(in) :: lkpm_combined_index(dim_cord_vect,4)
double precision , intent(in) :: cord_vect_full(nucl_num, dim_cord_vect)
double precision , intent(in) :: een_rescaled_e(0:cord_num, elec_num, elec_num, walk_num)
double precision , intent(in) :: een_rescaled_n(0:cord_num, nucl_num, elec_num, walk_num)
double precision , intent(out) :: factor_een(walk_num)
integer*8 :: i, a, j, l, k, p, m, n, nw
@ -4874,23 +4943,27 @@ integer function qmckl_compute_factor_een_f(context, walk_num, elec_num, nucl_nu
do nw =1, walk_num
do n = 1, dim_cord_vect
l = lkpm_combined_index(1, n)
k = lkpm_combined_index(2, n)
p = lkpm_combined_index(3, n)
m = lkpm_combined_index(4, n)
l = lkpm_combined_index(n, 1)
k = lkpm_combined_index(n, 2)
p = lkpm_combined_index(n, 3)
m = lkpm_combined_index(n, 4)
do a = 1, nucl_num
accu2 = 0.0d0
cn = cord_vect_full(n, a)
cn = cord_vect_full(a, n)
do j = 1, elec_num
accu = 0.0d0
do i = 1, elec_num
accu = accu + een_rescaled_e(nw, i, j, k) * &
een_rescaled_n(nw, i, a, m)
accu = accu + een_rescaled_e(k,i,j,nw) * &
een_rescaled_n(m,a,i,nw)
!if(nw .eq. 1) then
! print *,l,k,p,m,j,i,een_rescaled_e(k,i,j,nw), een_rescaled_n(m,a,i,nw), accu
!endif
end do
accu2 = accu2 + accu * een_rescaled_n(nw, j, a, m + l)
accu2 = accu2 + accu * een_rescaled_n(m + l,a,j,nw)
!print *, l,m,nw,accu, accu2, een_rescaled_n(m + l, a, j, nw), cn, factor_een(nw)
end do
factor_een(nw) = factor_een(nw) + accu2 + cn
factor_een(nw) = factor_een(nw) + accu2 * cn
end do
end do
end do
@ -4916,7 +4989,6 @@ end function qmckl_compute_factor_een_f
double* const factor_een );
#+end_src
#+CALL: generate_c_interface(table=qmckl_factor_een_args,rettyp=get_value("CRetType"),fname=get_value("Name"))
#+RESULTS:
@ -4973,100 +5045,44 @@ 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));
//
assert(qmckl_jastrow_provided(context));
double factor_een[walk_num];
rc = qmckl_get_jastrow_factor_een(context, &(factor_een[0]));
assert(fabs(factor_een[0] + 0.37407972141304213) < 1e-12);
#+end_src
** Electron-electron-nucleus Jastrow \(f_{een}\) derivative
@ -5221,12 +5237,12 @@ integer function qmckl_compute_factor_een_deriv_e_f(context, walk_num, elec_num,
implicit none
integer(qmckl_context), intent(in) :: context
integer*8 , intent(in) :: walk_num, elec_num, cord_num, nucl_num, dim_cord_vect
integer*8 , intent(in) :: lkpm_combined_index(4,dim_cord_vect)
double precision , intent(in) :: cord_vect_full(dim_cord_vect, nucl_num)
double precision , intent(in) :: een_rescaled_e(walk_num, elec_num, elec_num, 0:cord_num)
double precision , intent(in) :: een_rescaled_n(walk_num, elec_num, nucl_num, 0:cord_num)
double precision , intent(in) :: een_rescaled_e_deriv_e(walk_num, elec_num, 4, elec_num, 0:cord_num)
double precision , intent(in) :: een_rescaled_n_deriv_e(walk_num, elec_num, 4, nucl_num, 0:cord_num)
integer*8 , intent(in) :: lkpm_combined_index(dim_cord_vect, 4)
double precision , intent(in) :: cord_vect_full(nucl_num, dim_cord_vect)
double precision , intent(in) :: een_rescaled_e(0:cord_num, elec_num, elec_num, walk_num)
double precision , intent(in) :: een_rescaled_n(0:cord_num, nucl_num, elec_num, walk_num)
double precision , intent(in) :: een_rescaled_e_deriv_e(0:cord_num, elec_num, 4, elec_num, walk_num)
double precision , intent(in) :: een_rescaled_n_deriv_e(0:cord_num, nucl_num, 4, elec_num, walk_num)
double precision , intent(out) :: factor_een_deriv_e(elec_num, 4, walk_num)
integer*8 :: i, a, j, l, k, p, m, n, nw
@ -5264,41 +5280,41 @@ integer function qmckl_compute_factor_een_deriv_e_f(context, walk_num, elec_num,
do nw =1, walk_num
do n = 1, dim_cord_vect
l = lkpm_combined_index(1, n)
k = lkpm_combined_index(2, n)
p = lkpm_combined_index(3, n)
m = lkpm_combined_index(4, n)
l = lkpm_combined_index(n, 1)
k = lkpm_combined_index(n, 2)
p = lkpm_combined_index(n, 3)
m = lkpm_combined_index(n, 4)
do a = 1, nucl_num
cn = cord_vect_full(n, a)
cn = cord_vect_full(a, n)
do j = 1, elec_num
accu = 0.0d0
accu2 = 0.0d0
daccu = 0.0d0
daccu2 = 0.0d0
do i = 1, elec_num
accu = accu + een_rescaled_e(nw, i, j, k) * &
een_rescaled_n(nw, i, a, m)
accu2 = accu2 + een_rescaled_e(nw, i, j, k) * &
een_rescaled_n(nw, i, a, m + l)
daccu(1:4) = daccu(1:4) + een_rescaled_e_deriv_e(nw, j, 1:4, i, k) * &
een_rescaled_n(nw, i, a, m)
daccu2(1:4) = daccu2(1:4) + een_rescaled_e_deriv_e(nw, j, 1:4, i, k) * &
een_rescaled_n(nw, i, a, m + l)
accu = accu + een_rescaled_e(k, i, j, nw) * &
een_rescaled_n(m, a, i, nw)
accu2 = accu2 + een_rescaled_e(k, i, j, nw) * &
een_rescaled_n(m + l, a, i, nw)
daccu(1:4) = daccu(1:4) + een_rescaled_e_deriv_e(k, j, 1:4, i, nw) * &
een_rescaled_n(m, a, i, nw)
daccu2(1:4) = daccu2(1:4) + een_rescaled_e_deriv_e(k, j, 1:4, i, nw) * &
een_rescaled_n(m + l, a, i, nw)
end do
factor_een_deriv_e(j, 1:4, nw) = factor_een_deriv_e(j, 1:4, nw) + &
(accu * een_rescaled_n_deriv_e(nw, j, 1:4, a, m + l) &
+ daccu(1:4) * een_rescaled_n(nw, j, a, m + l) &
+ daccu2(1:4) * een_rescaled_n(nw, j, a, m) &
+ accu2 * een_rescaled_n_deriv_e(nw, j, 1:4, a, m)) * cn
(accu * een_rescaled_n_deriv_e(m + l, a, 1:4, j, nw) &
+ daccu(1:4) * een_rescaled_n(m + l, a, j, nw) &
+ daccu2(1:4) * een_rescaled_n(m, a, j, nw) &
+ accu2 * een_rescaled_n_deriv_e(m, a, 1:4, j, nw)) * cn
factor_een_deriv_e(j, 4, nw) = factor_een_deriv_e(j, 4, nw) + 2.0d0 * ( &
daccu (1) * een_rescaled_n_deriv_e(nw, j, 1, a, m + l) + &
daccu (2) * een_rescaled_n_deriv_e(nw, j, 2, a, m + l) + &
daccu (3) * een_rescaled_n_deriv_e(nw, j, 3, a, m + l) + &
daccu2(1) * een_rescaled_n_deriv_e(nw, j, 1, a, m ) + &
daccu2(2) * een_rescaled_n_deriv_e(nw, j, 2, a, m ) + &
daccu2(3) * een_rescaled_n_deriv_e(nw, j, 3, a, m ) ) * cn
daccu (1) * een_rescaled_n_deriv_e(m + l, a, 1, j, nw) + &
daccu (2) * een_rescaled_n_deriv_e(m + l, a, 2, j, nw) + &
daccu (3) * een_rescaled_n_deriv_e(m + l, a, 3, j, nw) + &
daccu2(1) * een_rescaled_n_deriv_e(m, a, 1, j, nw ) + &
daccu2(2) * een_rescaled_n_deriv_e(m, a, 2, j, nw ) + &
daccu2(3) * een_rescaled_n_deriv_e(m, a, 3, j, nw ) ) * cn
end do
end do
@ -5391,98 +5407,60 @@ import numpy as np
<<jastrow_data>>
<<een_e_deriv_e>>
<<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
daccu = np.zeros(4, dtype=float)
daccu2 = np.zeros(4, dtype=float)
een_rescaled_e_deriv_e_t = een_rescaled_e_deriv_e.T
print(een_rescaled_e_deriv_e_t.shape)
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]
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):
cn = cord_vector_full[a][n]
for j in range(0, elec_num):
accu = 0.0
accu2 = 0.0
daccu = 0.0
daccu2 = 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 + een_rescaled_e[i,j,k] * \
een_rescaled_n[a,i,m+l]
# daccu[0:4] = daccu[0:4] + een_rescaled_e_deriv_e_t[k,j,0:4,i,k] * \
# een_rescaled_n[a,i,m]
# daccu[0:4] = daccu[0:4] + een_rescaled_e_deriv_e_t[k,j,0:4,i,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
: (6, 10, 4, 10)
: factor_een: 0.0
#+begin_src c :tangle (eval c_test)
///* Check if Jastrow is properly initialized */
/* Check if Jastrow is properly initialized */
assert(qmckl_jastrow_provided(context));
double factor_een_deriv_e[walk_num][elec_num];
rc = qmckl_get_jastrow_factor_een_deriv_e(context, &(factor_een_deriv_e[0][0]));
assert(fabs(factor_een_deriv_e[0][0] + 0.0005481671107226865) < 1e-12);
#+end_src
* End of files :noexport:

1306
org/qmckl_sherman_morrison_woodbury.org Normal file
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File diff suppressed because one or more lines are too long

4
org/qmckl_tests.org
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@ -1191,7 +1191,7 @@ 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] = {
@ -1214,7 +1214,7 @@ 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},

1
org/table_of_contents
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@ -7,6 +7,7 @@ qmckl_nucleus.org
qmckl_electron.org
qmckl_ao.org
qmckl_jastrow.org
qmckl_sherman_morrison_woodbury.org
qmckl_distance.org
qmckl_utils.org
qmckl_tests.org

29
tools/lib.org
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@ -11,11 +11,10 @@
** Function to get the value of a property.
#+NAME: get_value
#+begin_src elisp :var key="Type"
(setq x (org-property-values key))
(pop x)
(org-with-point-at org-babel-current-src-block-location
(org-entry-get nil key t))
#+end_src
#+RESULTS: get_value
** Table of function arguments
@ -42,6 +41,8 @@ f_of_c_d = { '' : ''
, 'qmckl_exit_code' : 'integer (c_int32_t)'
, 'int32_t' : 'integer (c_int32_t)'
, 'int64_t' : 'integer (c_int64_t)'
, 'uint32_t' : 'integer (c_int32_t)'
, 'uint64_t' : 'integer (c_int64_t)'
, 'float' : 'real (c_float )'
, 'double' : 'real (c_double )'
, 'char' : 'character'
@ -55,6 +56,8 @@ ctypeid_d = { '' : ''
, 'qmckl_exit_code' : 'integer(c_int32_t)'
, 'integer' : 'integer(c_int32_t)'
, 'integer*8' : 'integer(c_int64_t)'
, 'integer' : 'integer(c_uint32_t)'
, 'integer*8' : 'integer(c_uint64_t)'
, 'real' : 'real(c_float)'
, 'real*8' : 'real(c_double)'
, 'character' : 'character(c_char)'
@ -184,23 +187,6 @@ results='\n'.join(results)
return results
#+END_SRC
#+RESULTS: generate_c_interface
#+begin_src f90 :tangle (eval f) :comments org :exports none
integer(c_int32_t) function [] &
() &
bind(C) result(info)
use, intrinsic :: iso_c_binding
implicit none
integer(c_int32_t), external :: []_f
info = []_f &
()
end function []
#+end_src
*** Generates a Fortran interface to the C function
#+NAME: generate_f_interface
@ -252,8 +238,5 @@ results='\n'.join(results)
return results
#+END_SRC
#+RESULTS: generate_f_interface
#+begin_src f90 :tangle (eval fh_func) :comments org :exports none
#+end_src