numpy.polynomial.hermite_e.hermeder — NumPy v1.13 Manual (original) (raw)

numpy.polynomial.hermite_e. hermeder(c, m=1, scl=1, axis=0)[source]

Differentiate a Hermite_e series.

Returns the 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*He_0 + 2*He_1 + 3*He_2while [[1,2],[1,2]] represents 1*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 is x and axis=1 is y.

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 by scl**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.

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.])