numpy.polynomial.hermite.hermval(x, c, tensor=True)
Evaluate an Hermite series at points x.
c is of length
n + 1, this function returns the value:
x is converted to an array only if it is a tuple or a list, otherwise it is treated as a scalar. In either case, either
x or its elements must support multiplication and addition both with themselves and with the elements of
c is a 1-D array, then
p(x) will have the same shape as
c is multidimensional, then the shape of the result depends on the value of
tensor is true the shape will be c.shape[1:] + x.shape. If
tensor is false the shape will be c.shape[1:]. Note that scalars have shape (,).
Trailing zeros in the coefficients will be used in the evaluation, so they should be avoided if efficiency is a concern.
The evaluation uses Clenshaw recursion, aka synthetic division.
>>> from numpy.polynomial.hermite import hermval >>> coef = [1,2,3] >>> hermval(1, coef) 11.0 >>> hermval([[1,2],[3,4]], coef) array([[ 11., 51.], [115., 203.]])
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