Interpolation
In this lesson, we will learn about the need for interpolation and how to implement it.
We'll cover the following
The need for interpolation
If a reading is missing between two consecutive readings, one approach is to replace the missing value using interpolation over the values that are present.
The signal in a weakly linked circuit is a good real-world example of a noisy signal. It is easy to identify the shape of the signal by looking at it, but difficult to quantify its mathematical form. This causes a lot of frustration amongst engineers, and that is why interpolation is a necessary tool to have.
The interp1d()
function from the scipy.interpolate
sub-package interpolates the data based on splines of varying order. interp1d
returns an object which behaves like a function. When this function is given an arbitrary value of , it returns the corresponding interpolated value.
This is a very useful technique when plotting data. Let’s see a code example of this along with the graphs below:
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