the function used for calculating eigenvalues, does not return them sorted so the final results are wrong. One have to sort them manually before calculating eigengaps

Hi,
Thanks for the excellent repo.
There is a name issue at utils.py could you please update as follows?
change
calinski_harabaz_score
with
calinski_harabasz_score

Ref: https://stackoverflow.com/questions/63482327/importerror-cannot-import-name-calinski-harabaz-score-from-sklearn-metrics

Hi,

Firstly, your article and repo are excellent to explain spectral clustering with the gap heuristic.
I'd like to make a suggestion w.r.t. you eigenvalue computation, the scipy sparse eigsh code will warn (once) when you call it with a symmetric matrix (non sparse) and k=N, in the warning it falls back to the eigh call.
The confusing part is that for 100 function calls, it'll emit the warning once, so is easily missed.
May I suggest substituting this to np.linalg.eigh for full matrices?
Note that setting K < N affects the heuristic, whereas the full eigenvalues does not.
I'm referring to this notebook:
https://github.com/ciortanmadalina/high_noise_clustering/raw/master/spectral_clustering.ipynb

Thanks!