def store_transf_matrix(path_hdf5: str,
atoms: List,
dictCGFs: Dict,
basis_name: str,
project_name: str,
package_name: str = 'cp2k') -> str:
"""
calculate the transformation of the overlap matrix from both spherical
to cartesian and from cartesian to spherical.
:param path_hdf5: Path to the HDF5 file.
:param atoms: Atoms that made up the molecule.
:param project_name: Name of the project.
:param package_name: Name of the ab initio simulation package.
:returns: Numpy matrix containing the transformation matrix.
"""
# Norms of the spherical CGFs for each element
dict_global_norms = compute_normalization_sphericals(dictCGFs)
# Compute the transformation matrix between cartesian and spherical
path = os.path.join(project_name, 'trans_mtx')
with h5py.File(path_hdf5) as f5:
if path not in f5:
mtx = calc_transf_matrix(f5, atoms, basis_name, dict_global_norms,
package_name)
store = StoreasHDF5(f5, package_name)
store.funHDF5(path, mtx)
return path
def test_compare_with_cp2k():
"""
Test overlap matrix transformation from cartesian to spherical
"""
# Overlap matrix in cartesian coordinates
basisname = "DZVP-MOLOPT-SR-GTH"
# Molecular geometry in a.u.
atoms = change_mol_units(readXYZ('test/test_files/ethylene.xyz'))
dictCGFs = create_dict_CGFs(path_hdf5, basisname, atoms)
# Compute the overlap matrix using the general multipole expression
rs = calcMtxOverlapP(atoms, dictCGFs)
number_of_contracted = sum(len(dictCGFs[at.symbol]) for at in atoms)
mtx_overlap = triang2mtx(rs, number_of_contracted)
dict_global_norms = compute_normalization_sphericals(dictCGFs)
with h5py.File(path_hdf5, 'r') as f5:
transf_mtx = calc_transf_matrix(f5, atoms, basisname,
dict_global_norms, 'cp2k')
# Use a sparse representation of the transformation matrix
transf_mtx = sparse.csr_matrix(transf_mtx)
transpose = transf_mtx.transpose()
# Compare the results with CP2K overlap matrix
test = transf_mtx.dot(sparse.csr_matrix.dot(mtx_overlap, transpose))
sum_diag = np.sum(np.diag(test))
number_of_sphericals = transf_mtx.shape[0]
assert abs(sum_diag - number_of_sphericals) < 1e-16
def test_compare_with_cp2k():
"""
Test overlap matrix transformation from cartesian to spherical
"""
# Overlap matrix in cartesian coordinates
basisname = "DZVP-MOLOPT-SR-GTH"
# Molecular geometry in a.u.
atoms = change_mol_units(
readXYZ('test/test_files/Cd33Se33_fivePoints.xyz'))
dictCGFs = create_dict_CGFs(path_hdf5, basisname, atoms)
# Compute the overlap matrix using the general multipole expression
rs = calcMtxOverlapP(atoms, dictCGFs)
mtx_overlap = triang2mtx(rs, 1452) # there are 1452 Cartesian basis CGFs
dict_global_norms = compute_normalization_sphericals(dictCGFs)
with h5py.File(path_hdf5, 'r') as f5:
transf_mtx = calc_transf_matrix(f5, atoms, basisname,
dict_global_norms, 'cp2k')
# Use a sparse representation of the transformation matrix
transf_mtx = sparse.csr_matrix(transf_mtx)
transpose = transf_mtx.transpose()
# Compare the results with CP2K overlap matrix
test = transf_mtx.dot(sparse.csr_matrix.dot(mtx_overlap, transpose))
expected = np.load('test/test_files/overlap_Cd33Se33_cp2k.npy')
assert np.allclose(test, expected, atol=1e-5)
def test_cube():
"""
Test the density compute to create a cube file.
"""
if not os.path.exists(scratch_path):
os.makedirs(scratch_path)
# Overlap matrix in cartesian coordinates
basisname = "DZVP-MOLOPT-SR-GTH"
# Read coordinates
molecule = change_mol_units(readXYZ(path_xyz))
# String representation of the molecule
geometries = split_file_geometries(path_xyz)
try:
shutil.copy(path_original_hdf5, path_test_hdf5)
# Contracted Gauss functions
dictCGFs = create_dict_CGFs(path_test_hdf5, basisname, molecule)
dict_global_norms = compute_normalization_sphericals(dictCGFs)
# Compute the transformation matrix and store it in the HDF5
with h5py.File(path_test_hdf5, 'r') as f5:
transf_mtx = calc_transf_matrix(
f5, molecule, basisname, dict_global_norms, 'cp2k')
path_transf_mtx = join(project_name, 'trans_mtx')
store_arrays_in_hdf5(
path_test_hdf5, path_transf_mtx, transf_mtx)
# voxel size and Number of steps
grid_data = GridCube(0.300939, 80)
rs = workflow_compute_cubes(
'cp2k', project_name, package_args, path_time_coeffs=None,
grid_data=grid_data, guess_args=None, geometries=geometries,
dictCGFs=dictCGFs, calc_new_wf_guess_on_points=[],
path_hdf5=path_test_hdf5, enumerate_from=0, package_config=None,
traj_folders=None, work_dir=scratch_path, basisname=basisname,
hdf5_trans_mtx=path_transf_mtx, nHOMO=6, orbitals_range=(6, 6),
ignore_warnings=False)
xs = retrieve_hdf5_data(path_test_hdf5, rs)[0]
np.save("grid_density", xs)
finally:
# Remove intermediate results
shutil.rmtree(scratch_path)