#+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 :PROPERTIES: :header-args: :tangle mo_ortho.py :END: 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) ).T # Transpose to get mo_num x point_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 : 5.577778577804565 seconds #+end_example and finally we compute the overlap between all the MOs as $M.M^\dagger$. #+begin_src python :exports code overlap = mo_value @ mo_value.T * 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 * C ** Check numerically that MOs are orthonormal, with cusp fitting :PROPERTIES: :header-args: :tangle mo_ortho.c :END: In this example, we will compute numerically the overlap between the molecular orbitals: \[ S_{ij} = \int \phi_i(\mathbf{r}) \phi_j(\mathbf{r}) \text{d}\mathbf{r} \sim \sum_{k=1}^{N} \phi_i(\mathbf{r}_k) \phi_j(\mathbf{r}_k) \delta \mathbf{r} \] \[ S_{ij} = \langle \phi_i | \phi_j \rangle \sim \sum_{k=1}^{N} \langle \phi_i | \mathbf{r}_k \rangle \langle \mathbf{r}_k | \phi_j \rangle \] We apply the cusp fitting procedure, so the MOs might deviate slightly from orthonormality. #+begin_src c :exports code #include #include #include #include int main(int argc, char** argv) { const char* trexio_filename = "..//share/qmckl/test_data/h2o_5z.h5"; qmckl_exit_code rc = QMCKL_SUCCESS; #+end_src 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 c :exports code qmckl_context context = qmckl_context_create(); rc = qmckl_trexio_read(context, trexio_filename, strlen(trexio_filename)); if (rc != QMCKL_SUCCESS) { fprintf(stderr, "Error reading TREXIO file:\n%s\n", qmckl_string_of_error(rc)); exit(1); } #+end_src We impose the electron-nucleus cusp fitting to occur when the electrons are close to the nuclei. The critical distance is 0.5 atomic units for hydrogens and 0.1 for the oxygen. To identify which atom is an oxygen and which are hydrogens, we fetch the nuclear charges from the context. #+begin_src c :exports code int64_t nucl_num; rc = qmckl_get_nucleus_num(context, &nucl_num); if (rc != QMCKL_SUCCESS) { fprintf(stderr, "Error getting nucl_num:\n%s\n", qmckl_string_of_error(rc)); exit(1); } double nucl_charge[nucl_num]; rc = qmckl_get_nucleus_charge(context, &(nucl_charge[0]), nucl_num); if (rc != QMCKL_SUCCESS) { fprintf(stderr, "Error getting nucl_charge:\n%s\n", qmckl_string_of_error(rc)); exit(1); } double r_cusp[nucl_num]; for (size_t i=0 ; i rmax[j] ? nucl_coord[i][j] : rmax[j]; } } rmin[0] -= shift[0]; rmin[1] -= shift[1]; rmin[2] -= shift[2]; rmax[0] += shift[0]; rmax[1] += shift[1]; rmax[2] += shift[2]; double step[3]; double* linspace[3]; for (int i=0 ; i<3 ; ++i) { linspace[i] = (double*) calloc( sizeof(double), nx[i] ); if (linspace[i] == NULL) { fprintf(stderr, "Allocation failed (linspace)\n"); exit(1); } step[i] = (rmax[i] - rmin[i]) / ((double) (nx[i]-1)); for (size_t j=0 ; j #+end_src #+begin_src f90 :noweb yes <> 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 ' 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