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numpy.polynomial.polynomial.polyder
numpy.polynomial.polynomial.polyder(c, m=1, scl=1, axis=0)[source]-
Differentiate a polynomial.
Returns the polynomial coefficients
cdifferentiatedmtimes alongaxis. At each iteration the result is multiplied byscl(the scaling factor is for use in a linear change of variable). The argumentcis an array of coefficients from low to high degree along each axis, e.g., [1,2,3] represents the polynomial1 + 2*x + 3*x**2while [[1,2],[1,2]] represents1 + 1*x + 2*y + 2*x*yif axis=0 isxand axis=1 isy.Parameters: -
c : array_like -
Array of polynomial 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 -
Polynomial coefficients of the derivative.
See also
Examples
>>> from numpy.polynomial import polynomial as P >>> c = (1,2,3,4) # 1 + 2x + 3x**2 + 4x**3 >>> P.polyder(c) # (d/dx)(c) = 2 + 6x + 12x**2 array([ 2., 6., 12.]) >>> P.polyder(c,3) # (d**3/dx**3)(c) = 24 array([24.]) >>> P.polyder(c,scl=-1) # (d/d(-x))(c) = -2 - 6x - 12x**2 array([ -2., -6., -12.]) >>> P.polyder(c,2,-1) # (d**2/d(-x)**2)(c) = 6 + 24x array([ 6., 24.]) -
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https://docs.scipy.org/doc/numpy-1.17.0/reference/generated/numpy.polynomial.polynomial.polyder.html