SciPy

scipy.interpolate.PchipInterpolator

class scipy.interpolate.PchipInterpolator(x, y, axis=0)[source]

PCHIP 1-d monotonic cubic interpolation

x and y are arrays of values used to approximate some function f, with y = f(x). The interpolant uses monotonic cubic splines to find the value of new points.

Parameters :

x : ndarray

A 1-D array of monotonically increasing real values. x cannot include duplicate values (otherwise f is overspecified)

y : ndarray

A 1-D array of real values. y‘s length along the interpolation axis must be equal to the length of x.

axis : int, optional

Axis in the yi array corresponding to the x-coordinate values.

Notes

Assumes x is sorted in monotonic order (e.g. x[1] > x[0]).

Methods

__call__(x) Evaluate the interpolant
append(xi, yi[, order]) Append a single point with derivatives to the PiecewisePolynomial
derivative(x[, der]) Evaluate one derivative of the polynomial at the point x
derivatives(x[, der]) Evaluate many derivatives of the polynomial at the point x
extend(xi, yi[, orders]) Extend the PiecewisePolynomial by a list of points