Avoid random and computation in preprocessing init class

[samuelgarcia]

Some classes for preprocessing like WhitenRecording, NormalizeByQuantileRecording,ZScoreRecordingare using internallyget_random_data_chunks()`.

This make the end user experience easier but this is rather bad for:

• reproducibility
• parralel processing

For parralel processing particularly it is really really bad because:

• every worker make a differents random and so the noise or covariance matrix is not the same across workers. And so the n_jobs>1 make different results for every run.
• the startup of every worker can be super long when n_jobs is very high because each worker is fighting for CPU ressource for all inversing a covaraince matrix for instance.

We have a way to store _kwargs but we should have another way (other dict) that would enable to restore the class very quickly in the same state without any random in between.

[zm711]

How close are we to this? The issue is two years old and I doubt we really look at it. It is an ongoing effort, but I think we've made huge progress no?

[zm711]

@alejoe91 I'll bring you into this :) What do you think? Close this as super stale for now? I don't know if keep this as a reminder is serving a purpose at this point.

[alejoe91]

This is fixed :) the random stuff is computed in the main process and added as kwargs