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qmckl/org/qmckl_examples.org

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#+TITLE: Code examples
#+SETUPFILE: ../tools/theme.setup
#+INCLUDE: ../tools/lib.org
In this section, we present examples of usage of QMCkl.
For simplicity, we assume that the wave function parameters are stored
in a [[https://github.com/TREX-CoE/trexio][TREXIO]] file.
* Python
** Check numerically that MOs are orthonormal
In this example, we will compute numerically the overlap
between the molecular orbitals:
\[
S_{ij} = \int \phi_i(\mathbf{r}) \phi_j(\mathbf{r})
\text{d}\mathbf{r} \sim \sum_{k=1}^{N} \phi_i(\mathbf{r}_k)
\phi_j(\mathbf{r}_k) \delta \mathbf{r}
\]
\[
S_{ij} = \langle \phi_i | \phi_j \rangle
\sim \sum_{k=1}^{N} \langle \phi_i | \mathbf{r}_k \rangle
\langle \mathbf{r}_k | \phi_j \rangle
\]
#+begin_src python :exports code
import numpy as np
import qmckl
#+end_src
#+RESULTS:
First, we create a context for the QMCkl calculation, and load the
wave function stored in =h2o_5z.h5= inside it. It is a Hartree-Fock
determinant for the water molecule in the cc-pV5Z basis set.
#+begin_src python :exports code
trexio_filename = "..//share/qmckl/test_data/h2o_5z.h5"
context = qmckl.context_create()
qmckl.trexio_read(context, trexio_filename)
#+end_src
#+RESULTS:
: None
We now define the grid points $\mathbf{r}_k$ as a regular grid around the
molecule.
We fetch the nuclear coordinates from the context,
#+begin_src python :exports code
nucl_num = qmckl.get_nucleus_num(context)
nucl_charge = qmckl.get_nucleus_charge(context, nucl_num)
nucl_coord = qmckl.get_nucleus_coord(context, 'N', nucl_num*3)
nucl_coord = np.reshape(nucl_coord, (3, nucl_num))
for i in range(nucl_num):
print("%d %+f %+f %+f"%(int(nucl_charge[i]),
nucl_coord[i,0],
nucl_coord[i,1],
nucl_coord[i,2]) )
#+end_src
#+begin_example
8 +0.000000 +0.000000 +0.000000
1 -1.430429 +0.000000 -1.107157
1 +1.430429 +0.000000 -1.107157
#+end_example
and compute the coordinates of the grid points:
#+begin_src python :exports code
nx = ( 120, 120, 120 )
shift = np.array([5.,5.,5.])
point_num = nx[0] * nx[1] * nx[2]
rmin = np.array( list([ np.min(nucl_coord[:,a]) for a in range(3) ]) )
rmax = np.array( list([ np.max(nucl_coord[:,a]) for a in range(3) ]) )
linspace = [ None for i in range(3) ]
step = [ None for i in range(3) ]
for a in range(3):
linspace[a], step[a] = np.linspace(rmin[a]-shift[a],
rmax[a]+shift[a],
num=nx[a],
retstep=True)
dr = step[0] * step[1] * step[2]
#+end_src
#+RESULTS:
Now the grid is ready, we can create the list of grid points
$\mathbf{r}_k$ on which the MOs $\phi_i$ will be evaluated, and
transfer them to the QMCkl context:
#+begin_src python :exports code
point = []
for x in linspace[0]:
for y in linspace[1]:
for z in linspace[2]:
point += [ [x, y, z] ]
point = np.array(point)
point_num = len(point)
qmckl.set_point(context, 'N', point_num, np.reshape(point, (point_num*3)))
#+end_src
#+RESULTS:
: None
Then, we evaluate all the MOs at the grid points (and time the execution),
and thus obtain the matrix $M_{ki} = \langle \mathbf{r}_k | \phi_i \rangle =
\phi_i(\mathbf{r}_k)$.
#+begin_src python :exports code
import time
mo_num = qmckl.get_mo_basis_mo_num(context)
before = time.time()
mo_value = qmckl.get_mo_basis_mo_value(context, point_num*mo_num)
after = time.time()
mo_value = np.reshape( mo_value, (point_num, mo_num) )
print("Number of MOs: ", mo_num)
print("Number of grid points: ", point_num)
print("Execution time : ", (after - before), "seconds")
#+end_src
#+begin_example
Number of MOs: 201
Number of grid points: 1728000
Execution time : 3.511528968811035 seconds
#+end_example
and finally we compute the overlap between all the MOs as
$M^\dagger M$.
#+begin_src python :exports code
overlap = mo_value.T @ mo_value * dr
print (overlap)
#+end_src
#+begin_example
[[ 9.88693941e-01 2.34719693e-03 -1.50518232e-08 ... 3.12084178e-09
-5.81064929e-10 3.70130091e-02]
[ 2.34719693e-03 9.99509628e-01 3.18930040e-09 ... -2.46888958e-10
-1.06064273e-09 -7.65567973e-03]
[-1.50518232e-08 3.18930040e-09 9.99995073e-01 ... -5.84882580e-06
-1.21598117e-06 4.59036468e-08]
...
[ 3.12084178e-09 -2.46888958e-10 -5.84882580e-06 ... 1.00019107e+00
-2.03342837e-04 -1.36954855e-08]
[-5.81064929e-10 -1.06064273e-09 -1.21598117e-06 ... -2.03342837e-04
9.99262427e-01 1.18264754e-09]
[ 3.70130091e-02 -7.65567973e-03 4.59036468e-08 ... -1.36954855e-08
1.18264754e-09 8.97215950e-01]]
#+end_example
* Fortran
** Checking errors
All QMCkl functions return an error code. A convenient way to handle
errors is to write an error-checking function that displays the
error in text format and exits the program.
#+NAME: qmckl_check_error
#+begin_src f90
subroutine qmckl_check_error(rc, message)
use qmckl
implicit none
integer(qmckl_exit_code), intent(in) :: rc
character(len=*) , intent(in) :: message
character(len=128) :: str_buffer
if (rc /= QMCKL_SUCCESS) then
print *, message
call qmckl_string_of_error(rc, str_buffer)
print *, str_buffer
call exit(rc)
end if
end subroutine qmckl_check_error
#+end_src
** Computing an atomic orbital on a grid
:PROPERTIES:
:header-args: :tangle ao_grid.f90
:END:
The following program, in Fortran, computes the values of an atomic
orbital on a regular 3-dimensional grid. The 100^3 grid points are
automatically defined, such that the molecule fits in a box with 5
atomic units in the borders.
This program uses the ~qmckl_check_error~ function defined above.
To use this program, run
#+begin_src bash :tangle no :exports code
$ ao_grid <trexio_file> <AO_id> <point_num>
#+end_src
#+begin_src f90 :noweb yes
<<qmckl_check_error>>
program ao_grid
use qmckl
implicit none
integer(qmckl_context) :: qmckl_ctx ! QMCkl context
integer(qmckl_exit_code) :: rc ! Exit code of QMCkl functions
character(len=128) :: trexio_filename
character(len=128) :: str_buffer
integer :: ao_id
integer :: point_num_x
integer(c_int64_t) :: nucl_num
double precision, allocatable :: nucl_coord(:,:)
integer(c_int64_t) :: point_num
integer(c_int64_t) :: ao_num
integer(c_int64_t) :: ipoint, i, j, k
double precision :: x, y, z, dr(3)
double precision :: rmin(3), rmax(3)
double precision, allocatable :: points(:,:)
double precision, allocatable :: ao_vgl(:,:,:)
#+end_src
Start by fetching the command-line arguments:
#+begin_src f90
if (iargc() /= 3) then
print *, 'Syntax: ao_grid <trexio_file> <AO_id> <point_num>'
call exit(-1)
end if
call getarg(1, trexio_filename)
call getarg(2, str_buffer)
read(str_buffer, *) ao_id
call getarg(3, str_buffer)
read(str_buffer, *) point_num_x
if (point_num_x < 0 .or. point_num_x > 300) then
print *, 'Error: 0 < point_num < 300'
call exit(-1)
end if
#+end_src
Create the QMCkl context and initialize it with the wave function
present in the TREXIO file:
#+begin_src f90
qmckl_ctx = qmckl_context_create()
rc = qmckl_trexio_read(qmckl_ctx, trexio_filename, 1_8*len(trim(trexio_filename)))
call qmckl_check_error(rc, 'Read TREXIO')
#+end_src
We need to check that ~ao_id~ is in the range, so we get the total
number of AOs from QMCkl:
#+begin_src f90
rc = qmckl_get_ao_basis_ao_num(qmckl_ctx, ao_num)
call qmckl_check_error(rc, 'Getting ao_num')
if (ao_id < 0 .or. ao_id > ao_num) then
print *, 'Error: 0 < ao_id < ', ao_num
call exit(-1)
end if
#+end_src
Now we will compute the limits of the box in which the molecule fits.
For that, we first need to ask QMCkl the coordinates of nuclei.
#+begin_src f90
rc = qmckl_get_nucleus_num(qmckl_ctx, nucl_num)
call qmckl_check_error(rc, 'Get nucleus num')
allocate( nucl_coord(3, nucl_num) )
rc = qmckl_get_nucleus_coord(qmckl_ctx, 'N', nucl_coord, 3_8*nucl_num)
call qmckl_check_error(rc, 'Get nucleus coord')
#+end_src
We now compute the coordinates of opposite points of the box, and
the distance between points along the 3 directions:
#+begin_src f90
rmin(1) = minval( nucl_coord(1,:) ) - 5.d0
rmin(2) = minval( nucl_coord(2,:) ) - 5.d0
rmin(3) = minval( nucl_coord(3,:) ) - 5.d0
rmax(1) = maxval( nucl_coord(1,:) ) + 5.d0
rmax(2) = maxval( nucl_coord(2,:) ) + 5.d0
rmax(3) = maxval( nucl_coord(3,:) ) + 5.d0
dr(1:3) = (rmax(1:3) - rmin(1:3)) / dble(point_num_x-1)
#+end_src
We now produce the list of point coordinates where the AO will be
evaluated:
#+begin_src f90
point_num = point_num_x**3
allocate( points(point_num, 3) )
ipoint=0
z = rmin(3)
do k=1,point_num_x
y = rmin(2)
do j=1,point_num_x
x = rmin(1)
do i=1,point_num_x
ipoint = ipoint+1
points(ipoint,1) = x
points(ipoint,2) = y
points(ipoint,3) = z
x = x + dr(1)
end do
y = y + dr(2)
end do
z = z + dr(3)
end do
#+end_src
We give the points to QMCkl:
#+begin_src f90
rc = qmckl_set_point(qmckl_ctx, 'T', point_num, points, size(points)*1_8 )
call qmckl_check_error(rc, 'Setting points')
#+end_src
We allocate the space required to retrieve the values, gradients and
Laplacian of all AOs, and ask to retrieve the values of the
AOs computed at the point positions.
#+begin_src f90
allocate( ao_vgl(ao_num, 5, point_num) )
rc = qmckl_get_ao_basis_ao_vgl(qmckl_ctx, ao_vgl, ao_num*5_8*point_num)
call qmckl_check_error(rc, 'Setting points')
#+end_src
We finally print the value and Laplacian of the AO:
#+begin_src f90
do ipoint=1, point_num
print '(3(F10.6,X),2(E20.10,X))', points(ipoint, 1:3), ao_vgl(ao_id,1,ipoint), ao_vgl(ao_id,5,ipoint)
end do
#+end_src
#+begin_src f90
deallocate( nucl_coord, points, ao_vgl )
end program ao_grid
#+end_src