$[40\%]$ The file RandomizedChaoticBS.txt contains the chaotic randomized BS spectrum $($Z$)$ captured using high fidelity sensors for a BS system perturbed with non$-$stationary $F,U,K$ excitations. Write a python code that loads the data file, linearize the data and then implement multiple linear regression $($using the pseudo$-$inverse matrix$)$ to fit a traditional FUK model to the data in the file:

$Z=a{F}^b{U}^c{K}^d$

The code should generate figures showing the original data, the linearized data and the proposed fit. In your report explain the rationale of the approach you implemented and show any math performed previous to the code

implementation.