scipy.interpolate.Akima1DInterpolator¶

class
scipy.interpolate.
Akima1DInterpolator
(x, y, axis=0)[source]¶ Akima interpolator
Fit piecewise cubic polynomials, given vectors x and y. The interpolation method by Akima uses a continuously differentiable subspline built from piecewise cubic polynomials. The resultant curve passes through the given data points and will appear smooth and natural.
 Parameters
 xndarray, shape (m, )
1D array of monotonically increasing real values.
 yndarray, shape (m, …)
ND array of real values. The length of
y
along the first axis must be equal to the length ofx
. axisint, optional
Specifies the axis of
y
along which to interpolate. Interpolation defaults to the first axis ofy
.
See also
Notes
New in version 0.14.
Use only for precise data, as the fitted curve passes through the given points exactly. This routine is useful for plotting a pleasingly smooth curve through a few given points for purposes of plotting.
References
 [1] A new method of interpolation and smooth curve fitting based
on local procedures. Hiroshi Akima, J. ACM, October 1970, 17(4), 589602.
 Attributes
 axis
 c
 extrapolate
 x
Methods
__call__
(self, x[, nu, extrapolate])Evaluate the piecewise polynomial or its derivative.
derivative
(self[, nu])Construct a new piecewise polynomial representing the derivative.
antiderivative
(self[, nu])Construct a new piecewise polynomial representing the antiderivative.
roots
(self[, discontinuity, extrapolate])Find real roots of the the piecewise polynomial.