# numpy.polynomial.hermite.hermval3d#

polynomial.hermite.hermval3d(x, y, z, c)[source]#

Evaluate a 3-D Hermite series at points (x, y, z).

This function returns the values:

$p(x,y,z) = \sum_{i,j,k} c_{i,j,k} * H_i(x) * H_j(y) * H_k(z)$

The parameters x, y, and z are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars and they must have the same shape after conversion. In either case, either x, y, and z or their elements must support multiplication and addition both with themselves and with the elements of c.

If c has fewer than 3 dimensions, ones are implicitly appended to its shape to make it 3-D. The shape of the result will be c.shape[3:] + x.shape.

Parameters:
x, y, zarray_like, compatible object

The three dimensional series is evaluated at the points (x, y, z), where x, y, and z must have the same shape. If any of x, y, or z is a list or tuple, it is first converted to an ndarray, otherwise it is left unchanged and if it isn’t an ndarray it is treated as a scalar.

carray_like

Array of coefficients ordered so that the coefficient of the term of multi-degree i,j,k is contained in c[i,j,k]. If c has dimension greater than 3 the remaining indices enumerate multiple sets of coefficients.

Returns:
valuesndarray, compatible object

The values of the multidimensional polynomial on points formed with triples of corresponding values from x, y, and z.

Notes

New in version 1.7.0.

Examples

>>> from numpy.polynomial.hermite import hermval3d
>>> x = [1, 2]
>>> y = [4, 5]
>>> z = [6, 7]
>>> c = [[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]]
>>> hermval3d(x, y, z, c)
array([ 40077., 120131.])