Interpolation
Explore interpolation techniques with SciPy's interp1d function to fill missing data in scientific signals. Learn to implement various interpolation types like linear and quadratic to smooth noisy data and enhance plotting accuracy for real-world applications.
We'll cover the following...
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 ...