Error Estimation in RLS adaptation code seems to be incorrect

[Walleclipse]

Hello,
I'm a little confused about the error-estimation in RLS adaptation code.
I think Error Estimates in RLS adaptation is incorrect, but it may be that I misunderstood it.

39~52 lines of rls.py estimated the error after updating the parameter theta. Which is Posteriori Error Estimation:
pos_Error(t) = y(t) - phi(t)*theta(t+1)
But in the many real scenario, we need to report Priori Error Estimation:
pri_Error(t) = y(t) - phi(t)*theta(t)
So we need to move the line 69 before than parameter-updating (line 66). Is that right? or just I misunderstand it?

And I have another question. You may miss the updating of the F matrix. You may need to add the following code to line 44
self.F = (self.F - k @ hidden_vec @ self.F)/self.lbd ;

Thanks,

[changliuliu]

@LlamasI

[HighlyAuditory]

Thanks for the catch. In fact, if you look into other parts you can see we haven't used these error results to evaluate our algorithm. We evaluate our algorithm by comparing the generated results with the ground truth.
Those lines are just some lines we wrote at first and forgot to remove. I should have clean up the code more carefully.