numpy.polynomial.laguerre.lagder¶
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numpy.polynomial.laguerre.
lagder
(c, m=1, scl=1, axis=0)[source]¶ Differentiate a Laguerre series.
Returns the Laguerre 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*L_0 + 2*L_1 + 3*L_2
while [[1,2],[1,2]] represents1*L_0(x)*L_0(y) + 1*L_1(x)*L_0(y) + 2*L_0(x)*L_1(y) + 2*L_1(x)*L_1(y)
if axis=0 isx
and axis=1 isy
.Parameters: c : array_like
Array of Laguerre 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
Laguerre series of the derivative.
See also
Notes
In general, the result of differentiating a Laguerre 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.laguerre import lagder >>> lagder([ 1., 1., 1., -3.]) array([ 1., 2., 3.]) >>> lagder([ 1., 0., 0., -4., 3.], m=2) array([ 1., 2., 3.])