Universal constraint sampler

[Osburg]

This PR adds a new sampler that supports nonlinear/linear equality/inequality constraints and NChooseKConstraints as discussed in #314. This only works for continuous inputs. In principle also batch constraints (and all other constraints you can compute a jacobian for) are supported, but since the returned sample is sampled from a larger set of candidates, the batch structure is no longer respected. By adapting the sampling logic in this last step this method can be made available for batch constraints. Closes #314.

[jduerholt]

Hi @Osburg,

Thanks for the PR, I will have a look over the Christmas days. Sorry for the delay.

Best,

Johannes

[jduerholt]

Looks overall good to me, just one question: is it on purpose that you inherit from the SamplerStrategy, because then you also inherit from their the handling of NChooseKs, which is totally fine for me, but I just wanted to ask ;)

[Osburg]

is it on purpose that you inherit from the SamplerStrategy, because then you also inherit from their the handling of NChooseKs, which is totally fine for me, but I just wanted to ask ;)

Thanks for pointing this out :) This was not my intention, I did not pay attention apparently. So I guess I should let UniversalConstraintSampler inherit from Strategy instead?

[jduerholt]

Yep, I would then recommend to inherit from Strategy.

[jduerholt]

Hi @Osburg,

thanks for the update, only some minor issues remain. We could also implement the pending_candidates at a later point in time. But this should not be too complicated. We can do it as you want.

Best,

Johannes

[jduerholt]

Looks good to me! Thank you very much!