pyscfad.pbc.dft.numint.NumInt.eval_ao

NumInt.eval_ao(cell, coords, kpt=array([0., 0., 0.]), deriv=0, relativity=0, shls_slice=None, non0tab=None, out=None, verbose=None)

Evaluate AO function value on the given grids.

Args:

mol : an instance of Mole

coords2D array, shape (N,3)

The coordinates of the grids.

Kwargs:

derivint

AO derivative order. It affects the shape of the return array. If deriv=0, the returned AO values are stored in a (N,nao) array. Otherwise the AO values are stored in an array of shape (M,N,nao). Here N is the number of grids, nao is the number of AO functions, M is the size associated to the derivative deriv.

relativitybool

No effects.

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 mol will be evaluated.

non0tab2D bool array

mask array to indicate whether the AO values are zero. The mask array can be obtained by calling 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.

verboseint or object of Logger

No effects.

Returns:

2D array of shape (N,nao) for AO values if deriv = 0. Or 3D array of shape (:,N,nao) for AO values and AO derivatives if deriv > 0. In the 3D array, the first (N,nao) elements are the AO values, followed by (3,N,nao) for x,y,z components; Then 2nd derivatives (6,N,nao) for xx, xy, xz, yy, yz, zz; Then 3rd derivatives (10,N,nao) for xxx, xxy, xxz, xyy, xyz, xzz, yyy, yyz, yzz, zzz; …

Examples:

>>> mol = gto.M(atom='O 0 0 0; H 0 0 1; H 0 1 0', basis='ccpvdz')
>>> coords = numpy.random.random((100,3))  # 100 random points
>>> ao_value = eval_ao(mol, coords)
>>> print(ao_value.shape)
(100, 24)
>>> ao_value = eval_ao(mol, coords, deriv=1, shls_slice=(1,4))
>>> print(ao_value.shape)
(4, 100, 7)
>>> ao_value = eval_ao(mol, coords, deriv=2, shls_slice=(1,4))
>>> print(ao_value.shape)
(10, 100, 7)