NumPy Np.Interp()

The NumPy interp() function allows you to get the one-dimensional linear interpolation to a function with the provided discrete data points (xp, fp), evaluated at x.

Function Syntax

The function syntax is as shown below:

1	numpy.interp(x, xp, fp, left=None, right=None, period=None)

Parameters

The function parameters are discussed below:

x – defines the x-coordinates at which the interpolated values are evaluated.
xp – represents the x-coordinates of the data points.
fp – represents the y-coordinates of the data points. They must be of the same length as xp.
left – defines the value to return for x < xp[0].
right – defines the value to return for x > xp[-1].
period – specifies the period for the x-coordinates.

Resource: https://en.wikipedia.org/wiki/Linear_interpolation

Return Value

The function returns the interpolated values with the same shape as the input (x).

Example

The following example illustrates how to use the interp() function in NumPy.

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# import numpy
import numpy as np
x = 1.4
xp = [6,4,2]
fp = [1,2,3]
print(np.interp(x, xp, fp))

The code above should return:

1.0

Example #2

Consider the code below with periodic coordinates.

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x = [0, 1.8, 2.4, 1., 2]
xp = [100, 90, 45, 33]
fp = [4,3,2,1]
print(np.interp(x, xp, fp, period=240))

The above code should return:

1	[1.57225434 1.54104046 1.53063584 1.55491329 1.53757225]

Conclusion

This article covers the basics of the interp function in NumPy. Feel free to explore the docs for more.

Happy coding!!