numpy.polynomial.hermite.hermder(c, m=1, scl=1, axis=0)
[source]
Differentiate a Hermite series.
Returns the Hermite series coefficients c
differentiated m
times along axis
. At each iteration the result is multiplied by scl
(the scaling factor is for use in a linear change of variable). The argument c
is an array of coefficients from low to high degree along each axis, e.g., [1,2,3] represents the series 1*H_0 + 2*H_1 + 3*H_2
while [[1,2],[1,2]] represents 1*H_0(x)*H_0(y) + 1*H_1(x)*H_0(y) + 2*H_0(x)*H_1(y) + 2*H_1(x)*H_1(y)
if axis=0 is x
and axis=1 is y
.
Parameters: |
c : array_like Array of Hermite series coefficients. If m : int, optional Number of derivatives taken, must be non-negative. (Default: 1) scl : scalar, optional Each differentiation is multiplied by axis : int, optional Axis over which the derivative is taken. (Default: 0). New in version 1.7.0. |
---|---|
Returns: |
der : ndarray Hermite series of the derivative. |
See also
In general, the result of differentiating a Hermite series does not resemble the same operation on a power series. Thus the result of this function may be “unintuitive,” albeit correct; see Examples section below.
>>> from numpy.polynomial.hermite import hermder >>> hermder([ 1. , 0.5, 0.5, 0.5]) array([ 1., 2., 3.]) >>> hermder([-0.5, 1./2., 1./8., 1./12., 1./16.], m=2) array([ 1., 2., 3.])
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https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.polynomial.hermite.hermder.html