-
numpy.polynomial.chebyshev.chebder(c, m=1, scl=1, axis=0)
[source] -
Differentiate a Chebyshev series.
Returns the Chebyshev 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*T_0 + 2*T_1 + 3*T_2
while [[1,2],[1,2]] represents1*T_0(x)*T_0(y) + 1*T_1(x)*T_0(y) + 2*T_0(x)*T_1(y) + 2*T_1(x)*T_1(y)
if axis=0 isx
and axis=1 isy
.Parameters: c : array_like
Array of Chebyshev 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
Chebyshev series of the derivative.
See also
Notes
In general, the result of differentiating a C-series needs to be ?reprojected? onto the C-series basis set. Thus, typically, the result of this function is ?unintuitive,? albeit correct; see Examples section below.
Examples
12345678910>>>
from
numpy.polynomial
import
chebyshev as C
>>> c
=
(
1
,
2
,
3
,
4
)
>>> C.chebder(c)
array([
14.
,
12.
,
24.
])
>>> C.chebder(c,
3
)
array([
96.
])
>>> C.chebder(c,scl
=
-
1
)
array([
-
14.
,
-
12.
,
-
24.
])
>>> C.chebder(c,
2
,
-
1
)
array([
12.
,
96.
])
numpy.polynomial.chebyshev.chebder()

2025-01-10 15:47:30
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