pyscfad.pbc.gto.cell.Cell.pbc_eval_gto#

Cell.pbc_eval_gto(eval_name, coords, comp=None, kpts=None, kpt=None, shls_slice=None, non0tab=None, ao_loc=None, out=None)[source]#

Evaluate PBC-AO function value on the given grids,

Parameters:

eval_name –

str:

==========================  =======================
Function                    Expression
==========================  =======================
"GTOval_sph"                \sum_T exp(ik*T) |AO>
"GTOval_ip_sph"             nabla \sum_T exp(ik*T) |AO>
"GTOval_cart"               \sum_T exp(ik*T) |AO>
"GTOval_ip_cart"            nabla \sum_T exp(ik*T) |AO>
==========================  =======================

atm – int32 ndarray libcint integral function argument
bas – int32 ndarray libcint integral function argument
env – float64 ndarray libcint integral function argument
coords – 2D array, shape (N,3) The coordinates of the grids.

Kwargs:

shls_slice2-element list: (shl_start, shl_end). If given, only part of AOs (shl_start <= shell_id < shl_end) are evaluated. By default, all shells defined in cell will be evaluated.
non0tab2D bool array: mask array to indicate whether the AO values are zero. The mask array can be obtained by calling dft.gen_grid.make_mask()
cutofffloat: AO values smaller than cutoff will be set to zero. The default cutoff threshold is ~1e-22 (defined in gto/grid_ao_drv.h)
outndarray: If provided, results are written into this array.

Returns:: A list of 2D (or 3D) arrays to hold the AO values on grids. Each element of the list corresponds to a k-point and it has the shape (N,nao) Or shape (*,N,nao).

Examples:

>>> cell = pbc.gto.M(a=numpy.eye(3)*4, atom='He 1 1 1', basis='6-31g')
>>> coords = cell.get_uniform_grids([10,10,10])
>>> kpts = cell.make_kpts([3,3,3])
>>> ao_value = cell.pbc_eval_gto("GTOval_sph", coords, kpts)
>>> len(ao_value)
27
>>> ao_value[0].shape
(1000, 2)
>>> ao_value = cell.pbc_eval_gto("GTOval_ig_sph", coords, kpts, comp=3)
>>> print(ao_value.shape)
>>> len(ao_value)
27
>>> ao_value[0].shape
(3, 1000, 2)