Update Chebyshev approaches

[smastelini]

This PR updates the Chebyshev regression samplers to match the original Java code and some extra details described in the original paper.

I missed these details when only using the formulae to implement the sampling methods. These changes, although functional, do not change the current changelog and could be seen as bug fixes.

[MaxHalford]

@smastelini I think you have to upgrade black, the latest convention is self._var.get()**0.5

[smastelini]

Good catch, thanks! Let me check that right now

[smastelini]

That's strange @MaxHalford, I even tried to reinstall my conda environment (and installed the latest black version) and the hooks don't catch that. Note that all tests passed in the main repo

[raphaelsty]

@smastelini If you use Vscode, you have to check the version of Python linked to it on the bottom right when viewing a Python script. Maybe it's not the environment where you installed the last version of Black.

Maybe it will solve the issue 🤔

[smastelini]

Hmm, black seems to do some choices here.

If I get the result from var in an auxiliary variable I get:

var = self._var.get(y)
sd = var**0.5

Adding spaces around ** will make the hook fail. But, if I get the the result directly, then the formatting becomes sd = self._var.get() ** 0.5. Removing the space will make the hook also fail.

Interesting choices. Look at the PR title in black's repo: Hug power operators if its operands are "simple".

[smastelini]

Thanks for the reply @raphaelsty! Actually, I ran everything on my terminal hahah

I got used to doing everything this way, git, pre-commit hooks and so on :)