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numpy.polynomial.hermite_e.hermeder(c, m=1, scl=1, axis=0)
[source] -
Differentiate a Hermite_e series.
Returns the series coefficients
c
differentiatedm
times alongaxis
. At each iteration the result is multiplied byscl
(the scaling factor is for use in a linear change of variable). The argumentc
is an array of coefficients from low to high degree along each axis, e.g., [1,2,3] represents the series1*He_0 + 2*He_1 + 3*He_2
while [[1,2],[1,2]] represents1*He_0(x)*He_0(y) + 1*He_1(x)*He_0(y) + 2*He_0(x)*He_1(y) + 2*He_1(x)*He_1(y)
if axis=0 isx
and axis=1 isy
.Parameters: c : array_like
Array of Hermite_e series coefficients. If
c
is multidimensional the different axis correspond to different variables with the degree in each axis given by the corresponding index.m : int, optional
Number of derivatives taken, must be non-negative. (Default: 1)
scl : scalar, optional
Each differentiation is multiplied by
scl
. The end result is multiplication byscl**m
. This is for use in a linear change of variable. (Default: 1)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
Notes
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.
Examples
>>> from numpy.polynomial.hermite_e import hermeder >>> hermeder([ 1., 1., 1., 1.]) array([ 1., 2., 3.]) >>> hermeder([-0.25, 1., 1./2., 1./3., 1./4 ], m=2) array([ 1., 2., 3.])
numpy.polynomial.hermite_e.hermeder()
2017-01-10 18:17:01
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