Numpy interpolate cubic

1. How to do cubic interpolation in Python?
2. What does cubic interpolation do?
3. What is interpolation in Numpy?

How to do cubic interpolation in Python?

S′i(xi+1)=S′i+1(xi+1),i=1,…,n−2,S″i(xi+1)=S″i+1(xi+1),i=1,…,n−2, which gives us 2(n−2) equations. Two more equations are required to compute the coefficients of Si(x). These last two constraints are arbitrary, and they can be chosen to fit the circumstances of the interpolation being performed.

What does cubic interpolation do?

Cubic spline interpolation is a mathematical method commonly used to construct new points within the boundaries of a set of known points. These new points are function values of an interpolation function (referred to as spline), which itself consists of multiple cubic piecewise polynomials.

What is interpolation in Numpy?

interp() function returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x. Syntax : numpy.interp(x, xp, fp, left = None, right = None, period = None)