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org/qmckl_ao.org
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org/qmckl_blas.org Normal file
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@ -0,0 +1,322 @@
#+TITLE: BLAS functions
#+SETUPFILE: ../tools/theme.setup
#+INCLUDE: ../tools/lib.org
* Headers :noexport:
#+begin_src elisp :noexport :results none
(org-babel-lob-ingest "../tools/lib.org")
#+end_src
#+begin_src c :comments link :tangle (eval c_test) :noweb yes
#include "qmckl.h"
#include "assert.h"
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
int main() {
qmckl_context context;
context = qmckl_context_create();
#+end_src
* Matrix operations
** ~qmckl_dgemm~
Matrix multiply l$C_{ij} = \beta C_{ij} + \alpha \sum_{k} A_{ik} \cdot B_{kj}$ using Fortran ~matmul~ function.
TODO: Add description about the external library dependence.
#+NAME: qmckl_dgemm_args
| qmckl_context | context | in | Global state |
| bool | TransA | in | Number of rows of the input matrix |
| bool | TransB | in | Number of rows of the input matrix |
| int64_t | m | in | Number of rows of the input matrix |
| int64_t | n | in | Number of columns of the input matrix |
| int64_t | k | in | Number of columns of the input matrix |
| double | alpha | in | Number of columns of the input matrix |
| double | A[][lda] | in | Array containing the $m \times n$ matrix $A$ |
| int64_t | lda | in | Leading dimension of array ~A~ |
| double | B[][ldb] | in | Array containing the $n \times m$ matrix $B$ |
| int64_t | ldb | in | Leading dimension of array ~B~ |
| double | beta | in | Array containing the $n \times m$ matrix $B$ |
| double | C[][ldc] | out | Array containing the $n \times m$ matrix $B$ |
| int64_t | ldc | in | Leading dimension of array ~B~ |
*** Requirements
- ~context~ is not ~QMCKL_NULL_CONTEXT~
- ~m > 0~
- ~n > 0~
- ~k > 0~
- ~lda >= m~
- ~ldb >= n~
- ~ldc >= n~
- ~A~ is allocated with at least $m \times k \times 8$ bytes
- ~B~ is allocated with at least $k \times n \times 8$ bytes
- ~C~ is allocated with at least $m \times n \times 8$ bytes
*** C header
#+CALL: generate_c_header(table=qmckl_dgemm_args,rettyp="qmckl_exit_code",fname="qmckl_dgemm")
#+RESULTS:
#+BEGIN_src c :tangle (eval h_func) :comments org
qmckl_exit_code qmckl_dgemm (
const qmckl_context context,
const bool TransA,
const bool TransB,
const int64_t m,
const int64_t n,
const int64_t k,
const double alpha,
const double* A,
const int64_t lda,
const double* B,
const int64_t ldb,
const double beta,
double* const C,
const int64_t ldc );
#+END_src
*** Source
#+begin_src f90 :tangle (eval f)
integer function qmckl_dgemm_f(context, TransA, TransB, m, n, k, alpha, A, LDA, B, LDB, beta, C, LDC) &
result(info)
use qmckl
implicit none
integer(qmckl_context) , intent(in) :: context
logical*8 , intent(in) :: TransA, TransB
integer*8 , intent(in) :: m, n, k
real*8 , intent(in) :: alpha, beta
integer*8 , intent(in) :: lda
real*8 , intent(in) :: A(m,k)
integer*8 , intent(in) :: ldb
real*8 , intent(in) :: B(k,n)
integer*8 , intent(in) :: ldc
real*8 , intent(out) :: C(m,n)
real*8, allocatable :: AT(:,:), BT(:,:), CT(:,:)
integer*8 :: i,j,l, LDA_2, LDB_2
info = QMCKL_SUCCESS
if (TransA) then
allocate(AT(k,m))
do i = 1, m
do j = 1, k
AT(j,i) = A(i,j)
end do
end do
LDA_2 = M
else
LDA_2 = LDA
endif
if (TransB) then
allocate(BT(n,k))
do i = 1, k
do j = 1, n
BT(j,i) = B(i,j)
end do
end do
LDB_2 = K
else
LDB_2 = LDB
endif
if (context == QMCKL_NULL_CONTEXT) then
info = QMCKL_INVALID_CONTEXT
return
endif
if (m <= 0_8) then
info = QMCKL_INVALID_ARG_4
return
endif
if (n <= 0_8) then
info = QMCKL_INVALID_ARG_5
return
endif
if (k <= 0_8) then
info = QMCKL_INVALID_ARG_6
return
endif
if (LDA_2 .ne. m) then
info = QMCKL_INVALID_ARG_9
return
endif
if (LDB_2 .ne. k) then
info = QMCKL_INVALID_ARG_10
return
endif
if (LDC .ne. m) then
info = QMCKL_INVALID_ARG_13
return
endif
if (TransA) then
C = matmul(AT,B)
else if (TransB) then
C = matmul(A,BT)
else
C = matmul(A,B)
endif
end function qmckl_dgemm_f
#+end_src
*** C interface :noexport:
#+CALL: generate_c_interface(table=qmckl_dgemm_args,rettyp="qmckl_exit_code",fname="qmckl_dgemm")
#+RESULTS:
#+BEGIN_src f90 :tangle (eval f) :comments org :exports none
integer(c_int32_t) function qmckl_dgemm &
(context, TransA, TransB, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc) &
bind(C) result(info)
use, intrinsic :: iso_c_binding
implicit none
integer (c_int64_t) , intent(in) , value :: context
logical*8 , intent(in) , value :: TransA
logical*8 , intent(in) , value :: TransB
integer (c_int64_t) , intent(in) , value :: m
integer (c_int64_t) , intent(in) , value :: n
integer (c_int64_t) , intent(in) , value :: k
real (c_double ) , intent(in) , value :: alpha
integer (c_int64_t) , intent(in) , value :: lda
real (c_double ) , intent(in) :: A(lda,*)
integer (c_int64_t) , intent(in) , value :: ldb
real (c_double ) , intent(in) :: B(ldb,*)
real (c_double ) , intent(in) , value :: beta
integer (c_int64_t) , intent(in) , value :: ldc
real (c_double ) , intent(out) :: C(ldc,*)
integer(c_int32_t), external :: qmckl_dgemm_f
info = qmckl_dgemm_f &
(context, TransA, TransB, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc)
end function qmckl_dgemm
#+END_src
#+CALL: generate_f_interface(table=qmckl_dgemm_args,rettyp="qmckl_exit_code",fname="qmckl_dgemm")
#+RESULTS:
#+begin_src f90 :tangle (eval fh_func) :comments org :exports none
interface
integer(c_int32_t) function qmckl_dgemm &
(context, TransA, TransB, m, n, k, alpha, A, lda, B, ldb, beta, C, ldc) &
bind(C)
use, intrinsic :: iso_c_binding
import
implicit none
integer (c_int64_t) , intent(in) , value :: context
logical*8 , intent(in) , value :: TransA
logical*8 , intent(in) , value :: TransB
integer (c_int64_t) , intent(in) , value :: m
integer (c_int64_t) , intent(in) , value :: n
integer (c_int64_t) , intent(in) , value :: k
real (c_double ) , intent(in) , value :: alpha
integer (c_int64_t) , intent(in) , value :: lda
real (c_double ) , intent(in) :: A(lda,*)
integer (c_int64_t) , intent(in) , value :: ldb
real (c_double ) , intent(in) :: B(ldb,*)
real (c_double ) , intent(in) , value :: beta
integer (c_int64_t) , intent(in) , value :: ldc
real (c_double ) , intent(out) :: C(ldc,*)
end function qmckl_dgemm
end interface
#+end_src
*** Test :noexport:
#+begin_src f90 :tangle (eval f_test)
integer(qmckl_exit_code) function test_qmckl_dgemm(context) bind(C)
use qmckl
implicit none
integer(qmckl_context), intent(in), value :: context
double precision, allocatable :: A(:,:), B(:,:), C(:,:), D(:,:)
integer*8 :: m, n, k, LDA, LDB, LDC
integer*8 :: i,j,l
logical*8 :: TransA, TransB
double precision :: x, alpha, beta
TransA = .False.
TransB = .False.
m = 1_8
k = 4_8
n = 6_8
LDA = m
LDB = k
LDC = m
allocate( A(LDA,k), B(LDB,n) , C(LDC,n), D(LDC,n))
A = 0.d0
B = 0.d0
C = 0.d0
D = 0.d0
alpha = 1.0d0
beta = 0.0d0
do j=1,k
do i=1,m
A(i,j) = -10.d0 + dble(i+j)
end do
end do
do j=1,n
do i=1,k
B(i,j) = -10.d0 + dble(i+j)
end do
end do
test_qmckl_dgemm = qmckl_dgemm(context, TransA, TransB, m, n, k, alpha, A, LDA, B, LDB, beta, C, LDC)
if (test_qmckl_dgemm /= QMCKL_SUCCESS) return
test_qmckl_dgemm = QMCKL_FAILURE
x = 0.d0
do j=1,n
do i=1,m
do l=1,k
D(i,j) = D(i,j) + A(i,l)*B(l,j)
end do
x = x + (D(i,j) - C(i,j))**2
end do
end do
if (dabs(x) <= 1.d-15) then
test_qmckl_dgemm = QMCKL_SUCCESS
endif
deallocate(A,B,C,D)
end function test_qmckl_dgemm
#+end_src
#+begin_src c :comments link :tangle (eval c_test)
qmckl_exit_code test_qmckl_dgemm(qmckl_context context);
assert(QMCKL_SUCCESS == test_qmckl_dgemm(context));
#+end_src
* End of files :noexport:
#+begin_src c :comments link :tangle (eval c_test)
assert (qmckl_context_destroy(context) == QMCKL_SUCCESS);
return 0;
}
#+end_src
# -*- mode: org -*-
# vim: syntax=c

3
org/qmckl_context.org
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@ -31,10 +31,12 @@ int main() {
#include "qmckl_nucleus_private_type.h"
#include "qmckl_electron_private_type.h"
#include "qmckl_ao_private_type.h"
#include "qmckl_mo_private_type.h"
#include "qmckl_jastrow_private_type.h"
#include "qmckl_nucleus_private_func.h"
#include "qmckl_electron_private_func.h"
#include "qmckl_ao_private_func.h"
#include "qmckl_mo_private_func.h"
#+end_src
#+begin_src c :tangle (eval c)
@ -119,6 +121,7 @@ typedef struct qmckl_context_struct {
qmckl_nucleus_struct nucleus;
qmckl_electron_struct electron;
qmckl_ao_basis_struct ao_basis;
qmckl_mo_basis_struct mo_basis;
qmckl_jastrow_struct jastrow;
/* To be implemented:

4
org/qmckl_electron.org
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@ -532,11 +532,11 @@ qmckl_set_electron_num(qmckl_context context,
"up_num <= 0");
}
if (down_num <= 0) {
if (down_num < 0) {
return qmckl_failwith( context,
QMCKL_INVALID_ARG_3,
"qmckl_set_electron_num",
"down_num <= 0");
"down_num < 0");
}
int32_t mask = 1 << 0;

618
org/qmckl_jastrow.org
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@ -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,
@ -4424,28 +4491,26 @@ end function qmckl_compute_dim_cord_vect_f
:END:
#+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_vect_full[dim_cord_vect][nucl_num] | out | Full list of coefficients |
| qmckl_context | context | in | Global state |
| int64_t | nucl_num | in | Number of atoms |
| 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[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:

880
org/qmckl_mo.org Normal file
View File

@ -0,0 +1,880 @@
#+TITLE: Molecular Orbitals
#+SETUPFILE: ../tools/theme.setup
#+INCLUDE: ../tools/lib.org
The molecular orbitals (MOs) are defined in the basis of AOs along with a AO to MO
coefficient matrix \[C\]. Using these coefficients (e.g. from Hartree Fock SCF method)
the MOs are defined as follows:
\[
\phi_i(\mathbf{r}) = C_i * \chi_i (\mathbf{r})
\]
In this section we demonstrate how to use the QMCkl specific DGEMM
function to calculate the MOs.
* Headers :noexport:
#+begin_src elisp :noexport :results none
(org-babel-lob-ingest "../tools/lib.org")
#+end_src
#+begin_src c :tangle (eval h_private_type)
#ifndef QMCKL_MO_HPT
#define QMCKL_MO_HPT
#include <stdbool.h>
#+end_src
#+begin_src c :tangle (eval c_test) :noweb yes
#include "qmckl.h"
#include "assert.h"
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include <stdio.h>
#include <math.h>
#include "chbrclf.h"
#include "qmckl_ao_private_func.h"
#include "qmckl_mo_private_func.h"
int main() {
qmckl_context context;
context = qmckl_context_create();
qmckl_exit_code rc;
#+end_src
#+begin_src c :tangle (eval c)
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#ifdef HAVE_STDINT_H
#include <stdint.h>
#elif HAVE_INTTYPES_H
#include <inttypes.h>
#endif
#include <stdlib.h>
#include <string.h>
#include <stdbool.h>
#include <assert.h>
#include "qmckl.h"
#include "qmckl_context_private_type.h"
#include "qmckl_memory_private_type.h"
#include "qmckl_memory_private_func.h"
#include "qmckl_ao_private_type.h"
#include "qmckl_ao_private_func.h"
#include "qmckl_mo_private_type.h"
#include "qmckl_mo_private_func.h"
#+end_src
* Context
The following arrays are stored in the context:
|---------------------+--------------------+--------------------------------------------------------------|
| ~type~ | | Gaussian (~'G'~) or Slater (~'S'~) |
| ~mo_num~ | | Number of MOs |
| ~coefficient~ | ~[mo_num, ao_num]~ | Orbital coefficients |
Computed data:
|---------------+-----------------------------------+----------------------------------------------------------------------------------------|
|---------------+-----------------------------------+----------------------------------------------------------------------------------------|
| ~mo_vgl~ | ~[5][walk_num][elec_num][mo_num]~ | Value, gradients, Laplacian of the MOs at electron positions |
| ~mo_vgl_date~ | ~uint64_t~ | Late modification date of Value, gradients, Laplacian of the MOs at electron positions |
|---------------+-----------------------------------+----------------------------------------------------------------------------------------|
** Data structure
#+begin_src c :comments org :tangle (eval h_private_type)
typedef struct qmckl_mo_basis_struct {
int64_t mo_num;
double * coefficient;
double * mo_vgl;
int64_t mo_vgl_date;
int32_t uninitialized;
bool provided;
char type;
} qmckl_mo_basis_struct;
#+end_src
The ~uninitialized~ integer contains one bit set to one for each
initialization function which has not been called. It becomes equal
to zero after all initialization functions have been called. The
struct is then initialized and ~provided == true~.
Some values are initialized by default, and are not concerned by
this mechanism.
** Access functions
#+begin_src c :comments org :tangle (eval h_private_func) :exports none
char qmckl_get_mo_basis_type (const qmckl_context context);
int64_t qmckl_get_mo_basis_mo_num (const qmckl_context context);
double* qmckl_get_mo_basis_coefficient (const qmckl_context context);
#+end_src
When all the data for the AOs have been provided, the following
function returns ~true~.
#+begin_src c :comments org :tangle (eval h_func)
bool qmckl_mo_basis_provided (const qmckl_context context);
#+end_src
#+NAME:post
#+begin_src c :exports none
if ( (ctx->mo_basis.uninitialized & mask) != 0) {
return NULL;
}
#+end_src
#+begin_src c :comments org :tangle (eval c) :noweb yes :exports none
char qmckl_get_mo_basis_type (const qmckl_context context) {
if (qmckl_context_check(context) == QMCKL_NULL_CONTEXT) {
return (char) 0;
}
qmckl_context_struct* const ctx = (qmckl_context_struct* const) context;
assert (ctx != NULL);
int32_t mask = 1;
if ( (ctx->mo_basis.uninitialized & mask) != 0) {
return (char) 0;
}
assert (ctx->mo_basis.type != (char) 0);
return ctx->mo_basis.type;
}
int64_t qmckl_get_mo_basis_mo_num (const qmckl_context context) {
if (qmckl_context_check(context) == QMCKL_NULL_CONTEXT) {
return (int64_t) 0;
}
qmckl_context_struct* const ctx = (qmckl_context_struct* const) context;
assert (ctx != NULL);
int32_t mask = 1 << 1;
if ( (ctx->mo_basis.uninitialized & mask) != 0) {
return (int64_t) 0;
}
assert (ctx->mo_basis.mo_num > (int64_t) 0);
return ctx->mo_basis.mo_num;
}
bool qmckl_mo_basis_provided(const qmckl_context context) {
if (qmckl_context_check(context) == QMCKL_NULL_CONTEXT) {
return false;
}
qmckl_context_struct* const ctx = (qmckl_context_struct* const) context;
assert (ctx != NULL);
return ctx->mo_basis.provided;
}
#+end_src
** Initialization functions
To set the basis set, all the following functions need to be
called.
#+begin_src c :comments org :tangle (eval h_func)
qmckl_exit_code qmckl_set_mo_basis_type (qmckl_context context, const char t);
qmckl_exit_code qmckl_set_mo_basis_mo_num (qmckl_context context, const int64_t mo_num);
qmckl_exit_code qmckl_set_mo_basis_coefficient (qmckl_context context, const double * coefficient);
#+end_src
#+NAME:pre2
#+begin_src c :exports none
if (qmckl_context_check(context) == QMCKL_NULL_CONTEXT) {
return QMCKL_NULL_CONTEXT;
}
qmckl_context_struct* const ctx = (qmckl_context_struct* const) context;
#+end_src
#+NAME:post2
#+begin_src c :exports none
ctx->mo_basis.uninitialized &= ~mask;
ctx->mo_basis.provided = (ctx->mo_basis.uninitialized == 0);
if (ctx->mo_basis.provided) {
qmckl_exit_code rc_ = qmckl_finalize_basis(context);
if (rc_ != QMCKL_SUCCESS) return rc_;
}
return QMCKL_SUCCESS;
#+end_src
#+begin_src c :comments org :tangle (eval c) :noweb yes :exports none
qmckl_exit_code qmckl_set_mo_basis_type(qmckl_context context, const char t) {
<<pre2>>
if (t != 'G' && t != 'S') {
return qmckl_failwith( context,
QMCKL_INVALID_ARG_2,
"qmckl_set_mo_basis_type",
NULL);
}
int32_t mask = 1;
ctx->mo_basis.type = t;
<<post2>>
}
qmckl_exit_code qmckl_set_mo_basis_mo_num(qmckl_context context, const int64_t mo_num) {
<<pre2>>
if (mo_num <= 0) {
return qmckl_failwith( context,
QMCKL_INVALID_ARG_2,
"qmckl_set_mo_basis_mo_num",
"mo_num <= 0");
}
int32_t mask = 1 << 1;
ctx->mo_basis.mo_num = mo_num;
<<post2>>
}
qmckl_exit_code qmckl_set_mo_basis_coefficient(qmckl_context context, const double* coefficient) {
<<pre2>>
int32_t mask = 1 << 2;
if (ctx->mo_basis.coefficient != NULL) {
qmckl_exit_code rc = qmckl_free(context, ctx->mo_basis.coefficient);
if (rc != QMCKL_SUCCESS) {
return qmckl_failwith( context, rc,
"qmckl_set_mo_basis_coefficient",
NULL);
}
}
qmckl_memory_info_struct mem_info = qmckl_memory_info_struct_zero;
mem_info.size = ctx->ao_basis.ao_num * ctx->mo_basis.mo_num * sizeof(double);
double* new_array = (double*) qmckl_malloc(context, mem_info);
if (new_array == NULL) {
return qmckl_failwith( context,
QMCKL_ALLOCATION_FAILED,
"qmckl_set_mo_basis_coefficient",
NULL);
}
memcpy(new_array, coefficient, mem_info.size);
ctx->mo_basis.coefficient = new_array;
<<post2>>
}
#+end_src
When the basis set is completely entered, other data structures are
computed to accelerate the calculations.
* Computation
** Computation of MOs
*** Get
#+begin_src c :comments org :tangle (eval h_func) :noweb yes
qmckl_exit_code qmckl_get_mo_basis_vgl(qmckl_context context, double* const mo_vgl);
#+end_src
#+begin_src c :comments org :tangle (eval c) :noweb yes :exports none
qmckl_exit_code qmckl_get_mo_basis_vgl(qmckl_context context, double* const mo_vgl) {
if (qmckl_context_check(context) == QMCKL_NULL_CONTEXT) {
return QMCKL_NULL_CONTEXT;
}
qmckl_exit_code rc;
rc = qmckl_provide_ao_vgl(context);
if (rc != QMCKL_SUCCESS) return rc;
rc = qmckl_provide_mo_vgl(context);
if (rc != QMCKL_SUCCESS) return rc;
qmckl_context_struct* const ctx = (qmckl_context_struct* const) context;
assert (ctx != NULL);
size_t sze = 5 * ctx->electron.num * ctx->mo_basis.mo_num * ctx->electron.walk_num;
memcpy(mo_vgl, ctx->mo_basis.mo_vgl, sze * sizeof(double));
return QMCKL_SUCCESS;
}
#+end_src
#+begin_src f90 :tangle (eval fh_func) :comments org :exports none
interface
integer(c_int32_t) function qmckl_get_mo_basis_vgl (context, mo_vgl) &
bind(C)
use, intrinsic :: iso_c_binding
import
implicit none
integer (c_int64_t) , intent(in) , value :: context
double precision, intent(out) :: mo_vgl(*)
end function
end interface
#+end_src
*** Provide
#+begin_src c :comments org :tangle (eval h_private_func) :noweb yes :exports none
qmckl_exit_code qmckl_provide_mo_vgl(qmckl_context context);
#+end_src
#+begin_src c :comments org :tangle (eval c) :noweb yes :exports none
qmckl_exit_code qmckl_provide_mo_vgl(qmckl_context context)
{
if (qmckl_context_check(context) == QMCKL_NULL_CONTEXT) {
return QMCKL_NULL_CONTEXT;
}
qmckl_context_struct* const ctx = (qmckl_context_struct* const) context;
assert (ctx != NULL);
if (!ctx->ao_basis.provided) {
return qmckl_failwith( context,
QMCKL_NOT_PROVIDED,
"qmckl_ao_basis",
NULL);
}
if(!(ctx->electron.provided)) {
return qmckl_failwith( context,
QMCKL_NOT_PROVIDED,
"qmckl_electron",
NULL);
}
if (!ctx->mo_basis.provided) {
return qmckl_failwith( context,
QMCKL_NOT_PROVIDED,
"qmckl_mo_basis",
NULL);
}
/* Compute if necessary */
if (ctx->electron.coord_new_date > ctx->mo_basis.mo_vgl_date) {
/* Allocate array */
if (ctx->mo_basis.mo_vgl == NULL) {
qmckl_memory_info_struct mem_info = qmckl_memory_info_struct_zero;
mem_info.size = 5 * ctx->electron.num * ctx->mo_basis.mo_num *
ctx->electron.walk_num * sizeof(double);
double* mo_vgl = (double*) qmckl_malloc(context, mem_info);
if (mo_vgl == NULL) {
return qmckl_failwith( context,
QMCKL_ALLOCATION_FAILED,
"qmckl_mo_basis_vgl",
NULL);
}
ctx->mo_basis.mo_vgl = mo_vgl;
}
qmckl_exit_code rc;
if (ctx->mo_basis.type == 'G') {
rc = qmckl_compute_mo_basis_gaussian_vgl(context,
ctx->ao_basis.ao_num,
ctx->mo_basis.mo_num,
ctx->electron.num,
ctx->electron.walk_num,
ctx->mo_basis.coefficient,
ctx->ao_basis.ao_vgl,
ctx->mo_basis.mo_vgl);
} else {
return qmckl_failwith( context,
QMCKL_FAILURE,
"compute_mo_basis_vgl",
"Not yet implemented");
}
if (rc != QMCKL_SUCCESS) {
return rc;
}
ctx->mo_basis.mo_vgl_date = ctx->date;
}
return QMCKL_SUCCESS;
}
#+end_src
*** Compute
:PROPERTIES:
:Name: qmckl_compute_mo_basis_gaussian_vgl
:CRetType: qmckl_exit_code
:FRetType: qmckl_exit_code
:END:
#+NAME: qmckl_mo_basis_gaussian_vgl_args
| ~qmckl_context~ | ~context~ | in | Global state |
| ~int64_t~ | ~ao_num~ | in | Number of AOs |
| ~int64_t~ | ~mo_num~ | in | Number of MOs |
| ~int64_t~ | ~elec_num~ | in | Number of electrons |
| ~int64_t~ | ~walk_num~ | in | Number of walkers |
| ~double~ | ~coef_normalized[mo_num][ao_num]~ | in | AO to MO transformation matrix |
| ~double~ | ~ao_vgl[5][walk_num][elec_num][ao_num]~ | in | Value, gradients and Laplacian of the AOs |
| ~double~ | ~mo_vgl[5][walk_num][elec_num][mo_num]~ | out | Value, gradients and Laplacian of the MOs |
#+begin_src f90 :comments org :tangle (eval f) :noweb yes
integer function qmckl_compute_mo_basis_gaussian_vgl_f(context, &
ao_num, mo_num, elec_num, walk_num, &
coef_normalized, ao_vgl, mo_vgl) &
result(info)
use qmckl
implicit none
integer(qmckl_context), intent(in) :: context
integer*8 , intent(in) :: ao_num, mo_num
integer*8 , intent(in) :: elec_num
integer*8 , intent(in) :: walk_num
double precision , intent(in) :: ao_vgl(ao_num,elec_num,walk_num,5)
double precision , intent(in) :: coef_normalized(ao_num,mo_num)
double precision , intent(out) :: mo_vgl(mo_num,elec_num,walk_num,5)
logical*8 :: TransA, TransB
double precision :: alpha, beta
integer :: info_qmckl_dgemm_value
integer :: info_qmckl_dgemm_Gx
integer :: info_qmckl_dgemm_Gy
integer :: info_qmckl_dgemm_Gz
integer :: info_qmckl_dgemm_lap
integer*8 :: M, N, K, LDA, LDB, LDC, i,j
integer*8 :: inucl, iprim, iwalk, ielec, ishell
double precision :: x, y, z, two_a, ar2, r2, v, cutoff
TransA = .False.
TransB = .False.
alpha = 1.0d0
beta = 0.0d0
info = QMCKL_SUCCESS
info_qmckl_dgemm_value = QMCKL_SUCCESS
info_qmckl_dgemm_Gx = QMCKL_SUCCESS
info_qmckl_dgemm_Gy = QMCKL_SUCCESS
info_qmckl_dgemm_Gz = QMCKL_SUCCESS
info_qmckl_dgemm_lap = QMCKL_SUCCESS
! Don't compute exponentials when the result will be almost zero.
! TODO : Use numerical precision here
cutoff = -dlog(1.d-15)
M = 1_8
N = mo_num * 1_8
K = ao_num * 1_8
LDA = M
LDB = K
LDC = M
do iwalk = 1, walk_num
do ielec = 1, elec_num
! Value
info_qmckl_dgemm_value = qmckl_dgemm(context,TransA, TransB, M, N, K, alpha, &
ao_vgl(:, ielec, iwalk, 1), LDA, &
coef_normalized(1:ao_num,1:mo_num),size(coef_normalized,1) * 1_8, &
beta, &
mo_vgl(:,ielec,iwalk,1),LDC)
! Grad_x
info_qmckl_dgemm_Gx = qmckl_dgemm(context,TransA, TransB, M, N, K, alpha, &
ao_vgl(:, ielec, iwalk, 2), LDA, &
coef_normalized(1:ao_num,1:mo_num),size(coef_normalized,1) * 1_8, &
beta, &
mo_vgl(:,ielec,iwalk,2),LDC)
! Grad_y
info_qmckl_dgemm_Gy = qmckl_dgemm(context,TransA, TransB, M, N, K, alpha, &
ao_vgl(:, ielec, iwalk, 3), LDA, &
coef_normalized(1:ao_num,1:mo_num),size(coef_normalized,1) * 1_8, &
beta, &
mo_vgl(:,ielec,iwalk,3),LDC)
! Grad_z
info_qmckl_dgemm_Gz = qmckl_dgemm(context,TransA, TransB, M, N, K, alpha, &
ao_vgl(:, ielec, iwalk, 4), LDA, &
coef_normalized(1:ao_num,1:mo_num),size(coef_normalized,1) * 1_8, &
beta, &
mo_vgl(:,ielec,iwalk,4),LDC)
! Lapl_z
info_qmckl_dgemm_lap = qmckl_dgemm(context, TransA, TransB, M, N, K, alpha, &
ao_vgl(:, ielec, iwalk, 5), LDA, &
coef_normalized(1:ao_num,1:mo_num),size(coef_normalized,1) * 1_8, &
beta, &
mo_vgl(:,ielec,iwalk,5),LDC)
end do
end do
if(info_qmckl_dgemm_value .eq. QMCKL_SUCCESS .and. &
info_qmckl_dgemm_Gx .eq. QMCKL_SUCCESS .and. &
info_qmckl_dgemm_Gy .eq. QMCKL_SUCCESS .and. &
info_qmckl_dgemm_Gz .eq. QMCKL_SUCCESS .and. &
info_qmckl_dgemm_lap .eq. QMCKL_SUCCESS ) then
info = QMCKL_SUCCESS
else
info = QMCKL_FAILURE
end if
end function qmckl_compute_mo_basis_gaussian_vgl_f
#+end_src
#+CALL: generate_c_header(table=qmckl_mo_basis_gaussian_vgl_args,rettyp=get_value("CRetType"),fname="qmckl_compute_mo_basis_gaussian_vgl"))
#+RESULTS:
#+begin_src c :tangle (eval h_func) :comments org
qmckl_exit_code qmckl_compute_mo_basis_gaussian_vgl (
const qmckl_context context,
const int64_t ao_num,
const int64_t mo_num,
const int64_t elec_num,
const int64_t walk_num,
const double* coef_normalized,
const double* ao_vgl,
double* const mo_vgl );
#+end_src
#+CALL: generate_c_interface(table=qmckl_mo_basis_gaussian_vgl_args,rettyp=get_value("CRetType"),fname="qmckl_compute_mo_basis_gaussian_vgl"))
#+RESULTS:
#+begin_src f90 :tangle (eval f) :comments org :exports none
integer(c_int32_t) function qmckl_compute_mo_basis_gaussian_vgl &
(context, ao_num, mo_num, elec_num, walk_num, coef_normalized, ao_vgl, mo_vgl) &
bind(C) result(info)
use, intrinsic :: iso_c_binding
implicit none
integer (c_int64_t) , intent(in) , value :: context
integer (c_int64_t) , intent(in) , value :: ao_num
integer (c_int64_t) , intent(in) , value :: mo_num
integer (c_int64_t) , intent(in) , value :: elec_num
integer (c_int64_t) , intent(in) , value :: walk_num
real (c_double ) , intent(in) :: coef_normalized(ao_num,mo_num)
real (c_double ) , intent(in) :: ao_vgl(ao_num,elec_num,walk_num,5)
real (c_double ) , intent(out) :: mo_vgl(mo_num,elec_num,walk_num,5)
integer(c_int32_t), external :: qmckl_compute_mo_basis_gaussian_vgl_f
info = qmckl_compute_mo_basis_gaussian_vgl_f &
(context, ao_num, mo_num, elec_num, walk_num, coef_normalized, ao_vgl, mo_vgl)
end function qmckl_compute_mo_basis_gaussian_vgl
#+end_src
*** Test
#+begin_src python :results output :exports none
import numpy as np
def f(a,x,y):
return np.sum( [c * np.exp( -b*(np.linalg.norm(x-y))**2) for b,c in a] )
def df(a,x,y,n):
h0 = 1.e-6
if n == 1: h = np.array([h0,0.,0.])
elif n == 2: h = np.array([0.,h0,0.])
elif n == 3: h = np.array([0.,0.,h0])
return ( f(a,x+h,y) - f(a,x-h,y) ) / (2.*h0)
def d2f(a,x,y,n):
h0 = 1.e-6
if n == 1: h = np.array([h0,0.,0.])
elif n == 2: h = np.array([0.,h0,0.])
elif n == 3: h = np.array([0.,0.,h0])
return ( f(a,x+h,y) - 2.*f(a,x,y) + f(a,x-h,y) ) / h0**2
def lf(a,x,y):
return d2f(a,x,y,1) + d2f(a,x,y,2) + d2f(a,x,y,3)
elec_26_w1 = np.array( [ 1.49050402641, 2.90106987953, -1.05920815468 ] )
elec_15_w2 = np.array( [ -2.20180344582,-1.9113150239, 2.2193744778600002 ] )
nucl_1 = np.array( [ 1.096243353458458e+00, 8.907054016973815e-01, 7.777092280258892e-01 ] )
nucl_2 = np.array( [ 1.168459237342663e+00, 1.125660720053393e+00, 2.833370314829343e+00 ] )
#double prim_vgl[prim_num][5][walk_num][elec_num];
x = elec_26_w1 ; y = nucl_1
a = [( 8.236000E+03, -1.130000E-04 * 6.1616545431994848e+02 ),
( 1.235000E+03, -8.780000E-04 * 1.4847738511079908e+02 ),
( 2.808000E+02, -4.540000E-03 * 4.8888635917437597e+01 ),
( 7.927000E+01, -1.813300E-02 * 1.8933972232608955e+01 ),
( 2.559000E+01, -5.576000E-02 * 8.1089160941724145e+00 ),
( 8.997000E+00, -1.268950E-01 * 3.7024003863155635e+00 ),
( 3.319000E+00, -1.703520E-01 * 1.7525302846177560e+00 ),
( 9.059000E-01, 1.403820E-01 * 6.6179013183966806e-01 ),
( 3.643000E-01, 5.986840E-01 * 3.3419848027174592e-01 ),
( 1.285000E-01, 3.953890E-01 * 1.5296336817449557e-01 )]
print ( "[1][0][0][26] : %25.15e"% f(a,x,y))
print ( "[1][1][0][26] : %25.15e"% df(a,x,y,1))
print ( "[1][2][0][26] : %25.15e"% df(a,x,y,2))
print ( "[1][3][0][26] : %25.15e"% df(a,x,y,3))
print ( "[1][4][0][26] : %25.15e"% lf(a,x,y))
x = elec_15_w2 ; y = nucl_2
a = [(3.387000E+01, 6.068000E-03 *1.0006253235944540e+01),
(5.095000E+00, 4.530800E-02 *2.4169531573445120e+00),
(1.159000E+00, 2.028220E-01 *7.9610924849766440e-01),
(3.258000E-01, 5.039030E-01 *3.0734305383061117e-01),
(1.027000E-01, 3.834210E-01 *1.2929684417481876e-01)]
print ( "[0][1][15][14] : %25.15e"% f(a,x,y))
print ( "[1][1][15][14] : %25.15e"% df(a,x,y,1))
print ( "[2][1][15][14] : %25.15e"% df(a,x,y,2))
print ( "[3][1][15][14] : %25.15e"% df(a,x,y,3))
print ( "[4][1][15][14] : %25.15e"% lf(a,x,y))
#+end_src
#+begin_src c :tangle (eval c_test) :exports none
{
#define walk_num chbrclf_walk_num
#define elec_num chbrclf_elec_num
#define shell_num chbrclf_shell_num
#define ao_num chbrclf_ao_num
int64_t elec_up_num = chbrclf_elec_up_num;
int64_t elec_dn_num = chbrclf_elec_dn_num;
double* elec_coord = &(chbrclf_elec_coord[0][0][0]);
const int64_t nucl_num = chbrclf_nucl_num;
const double* nucl_charge = chbrclf_charge;
const double* nucl_coord = &(chbrclf_nucl_coord[0][0]);
rc = qmckl_set_electron_num (context, elec_up_num, elec_dn_num);
assert (rc == QMCKL_SUCCESS);
rc = qmckl_set_electron_walk_num (context, walk_num);
assert (rc == QMCKL_SUCCESS);
assert(qmckl_electron_provided(context));
rc = qmckl_set_electron_coord (context, 'N', elec_coord);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_nucleus_num (context, nucl_num);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_nucleus_coord (context, 'T', &(nucl_coord[0]));
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_nucleus_charge(context, nucl_charge);
assert(rc == QMCKL_SUCCESS);
assert(qmckl_nucleus_provided(context));
const int64_t * nucleus_index = &(chbrclf_basis_nucleus_index[0]);
const int64_t * nucleus_shell_num = &(chbrclf_basis_nucleus_shell_num[0]);
const int32_t * shell_ang_mom = &(chbrclf_basis_shell_ang_mom[0]);
const int64_t * shell_prim_num = &(chbrclf_basis_shell_prim_num[0]);
const int64_t * shell_prim_index = &(chbrclf_basis_shell_prim_index[0]);
const double * shell_factor = &(chbrclf_basis_shell_factor[0]);
const double * exponent = &(chbrclf_basis_exponent[0]);
const double * coefficient = &(chbrclf_basis_coefficient[0]);
const double * prim_factor = &(chbrclf_basis_prim_factor[0]);
const double * ao_factor = &(chbrclf_basis_ao_factor[0]);
const char typ = 'G';
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_type (context, typ);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_shell_num (context, chbrclf_shell_num);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_prim_num (context, chbrclf_prim_num);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_nucleus_index (context, nucleus_index);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_nucleus_shell_num (context, nucleus_shell_num);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_shell_ang_mom (context, shell_ang_mom);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_shell_factor (context, shell_factor);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_shell_prim_num (context, shell_prim_num);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_shell_prim_index (context, shell_prim_index);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_exponent (context, exponent);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_coefficient (context, coefficient);
assert(rc == QMCKL_SUCCESS);
assert(!qmckl_ao_basis_provided(context));
rc = qmckl_set_ao_basis_prim_factor (context, prim_factor);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_ao_basis_ao_num(context, chbrclf_ao_num);
assert(rc == QMCKL_SUCCESS);
rc = qmckl_set_ao_basis_ao_factor (context, ao_factor);
assert(rc == QMCKL_SUCCESS);
assert(qmckl_ao_basis_provided(context));
double ao_vgl[5][walk_num][elec_num][chbrclf_ao_num];
rc = qmckl_get_ao_vgl(context, &(ao_vgl[0][0][0][0]));
assert (rc == QMCKL_SUCCESS);
/* Set up MO data */
rc = qmckl_set_mo_basis_type(context, typ);
assert (rc == QMCKL_SUCCESS);
const int64_t mo_num = chbrclf_mo_num;
rc = qmckl_set_mo_basis_mo_num(context, mo_num);
assert (rc == QMCKL_SUCCESS);
const double * mo_coefficient = &(chbrclf_mo_coef[0]);
rc = qmckl_set_mo_basis_coefficient(context, mo_coefficient);
assert (rc == QMCKL_SUCCESS);
assert(qmckl_mo_basis_provided(context));
double mo_vgl[5][walk_num][elec_num][chbrclf_mo_num];
rc = qmckl_get_mo_basis_vgl(context, &(mo_vgl[0][0][0][0]));
assert (rc == QMCKL_SUCCESS);
// Test overlap of MO
//double point_x[100];
//double point_y[100];
//double point_z[100];
//int32_t npoints=100;
//// obtain points
//double dr = 20./(npoints-1);
//double dr3 = dr*dr*dr;
//
//for (int i=0;i<npoints;++i) {
// point_x[i] = -10. + dr*i;
// point_y[i] = -10. + dr*i;
// point_z[i] = -10. + dr*i;
//}
//
//double ovlmo1 = 0.0;
//// Calculate overlap
//for (int i=0;i<npoints;++i) {
// printf(".");
// fflush(stdout);
// for (int j=0;j<npoints;++j) {
// for (int k=0;k<npoints;++k) {
// // Set point
// elec_coord[0] = point_x[i];
// elec_coord[1] = point_y[j];
// elec_coord[2] = point_z[k];
// rc = qmckl_set_electron_coord (context, 'N', elec_coord);
// assert(rc == QMCKL_SUCCESS);
//
// // Calculate value of MO (1st electron)
// double mo_vgl[5][walk_num][elec_num][chbrclf_mo_num];
// rc = qmckl_get_mo_basis_vgl(context, &(mo_vgl[0][0][0][0]));
// assert (rc == QMCKL_SUCCESS);
// ovlmo1 += mo_vgl[0][0][0][0]*mo_vgl[0][0][0][0]*dr3;
// }
// }
//}
//printf("OVL MO1 = %10.15f\n",ovlmo1);
printf("\n");
printf(" mo_vgl mo_vgl[0][0][26][219] %25.15e\n", mo_vgl[0][0][2][3]);
printf(" mo_vgl mo_vgl[1][0][26][219] %25.15e\n", mo_vgl[1][0][2][3]);
printf(" mo_vgl mo_vgl[0][0][26][220] %25.15e\n", mo_vgl[0][0][2][3]);
printf(" mo_vgl mo_vgl[1][0][26][220] %25.15e\n", mo_vgl[1][0][2][3]);
printf(" mo_vgl mo_vgl[0][0][26][221] %25.15e\n", mo_vgl[0][0][2][3]);
printf(" mo_vgl mo_vgl[1][0][26][221] %25.15e\n", mo_vgl[1][0][2][3]);
printf(" mo_vgl mo_vgl[0][0][26][222] %25.15e\n", mo_vgl[0][0][2][3]);
printf(" mo_vgl mo_vgl[1][0][26][222] %25.15e\n", mo_vgl[1][0][2][3]);
printf(" mo_vgl mo_vgl[0][0][26][223] %25.15e\n", mo_vgl[0][0][2][3]);
printf(" mo_vgl mo_vgl[1][0][26][223] %25.15e\n", mo_vgl[1][0][2][3]);
printf(" mo_vgl mo_vgl[0][0][26][224] %25.15e\n", mo_vgl[0][0][2][3]);
printf(" mo_vgl mo_vgl[1][0][26][224] %25.15e\n", mo_vgl[1][0][2][3]);
printf("\n");
}
#+end_src
* End of files :noexport:
#+begin_src c :tangle (eval h_private_type)
#endif
#+end_src
*** Test
#+begin_src c :tangle (eval c_test)
rc = qmckl_context_destroy(context);
assert (rc == QMCKL_SUCCESS);
return 0;
}
#+end_src
*** Compute file names
#+begin_src emacs-lisp
; The following is required to compute the file names
(setq pwd (file-name-directory buffer-file-name))
(setq name (file-name-nondirectory (substring buffer-file-name 0 -4)))
(setq f (concat pwd name "_f.f90"))
(setq fh (concat pwd name "_fh.f90"))
(setq c (concat pwd name ".c"))
(setq h (concat name ".h"))
(setq h_private (concat name "_private.h"))
(setq c_test (concat pwd "test_" name ".c"))
(setq f_test (concat pwd "test_" name "_f.f90"))
; Minted
(require 'ox-latex)
(setq org-latex-listings 'minted)
(add-to-list 'org-latex-packages-alist '("" "listings"))
(add-to-list 'org-latex-packages-alist '("" "color"))
#+end_src
# -*- mode: org -*-
# vim: syntax=c

458
org/qmckl_sherman_morrison_woodbury.org
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59032
org/qmckl_tests.org
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2
org/table_of_contents
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@ -6,8 +6,10 @@ qmckl_numprec.org
qmckl_nucleus.org
qmckl_electron.org
qmckl_ao.org
qmckl_mo.org
qmckl_jastrow.org
qmckl_sherman_morrison_woodbury.org
qmckl_distance.org
qmckl_utils.org
qmckl_blas.org
qmckl_tests.org

27
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
@ -40,6 +39,7 @@
f_of_c_d = { '' : ''
, 'qmckl_context' : 'integer (c_int64_t)'
, 'qmckl_exit_code' : 'integer (c_int32_t)'
, 'bool' : 'logical*8'
, 'int32_t' : 'integer (c_int32_t)'
, 'int64_t' : 'integer (c_int64_t)'
, 'uint32_t' : 'integer (c_int32_t)'
@ -62,6 +62,7 @@ ctypeid_d = { '' : ''
, 'real' : 'real(c_float)'
, 'real*8' : 'real(c_double)'
, 'character' : 'character(c_char)'
, 'character' : 'character(c_char)'
}
#+END_SRC
@ -188,23 +189,6 @@ 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
@ -256,8 +240,5 @@ 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