numpy.polynomial.legendre.legder(c, m=1, scl=1, axis=0)
[source]
Differentiate a Legendre series.
Returns the Legendre 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]] represents 1*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 is x
and axis=1 is y
.
Parameters: |
c : array_like Array of Legendre 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 axis : int, optional Axis over which the derivative is taken. (Default: 0). New in version 1.7.0. |
---|---|
Returns: |
der : ndarray Legendre series of the derivative. |
See also
In general, the result of differentiating a Legendre 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 import legendre as L >>> c = (1,2,3,4) >>> L.legder(c) array([ 6., 9., 20.]) >>> L.legder(c, 3) array([ 60.]) >>> L.legder(c, scl=-1) array([ -6., -9., -20.]) >>> L.legder(c, 2,-1) array([ 9., 60.])
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https://docs.scipy.org/doc/numpy-1.12.0/reference/generated/numpy.polynomial.legendre.legder.html