Fix loss function bugs and inconsistencies

[iancze]

A feature branch on top of WIP-v0.3 (original PR #243, since split off into incremental bits)

Scope of this branch is fixing loss function bugs and inconsistencies, aiming to close
* #237
* #153
* #100

• Expanded scope to include major documentation edits to be more concise with the objective of making the core package easier to develop and maintain. Some tutorials moved to the MPoL-dev/examples repository.
• Added the mpol.losses.neg_log_likelihood_avg method to be used in point-estimate or optimization situations where data amplitudes or weights may be adjusted as part of the optimization (such as via self-calibration). Moved all documentation around loss functions into the Losses API.
• Renamed mpol.losses.nll -> mpol.losses.r_chi_squared and mpol.losses.nll_gridded -> mpol.losses.r_chi_squared_gridded because that is what those routines were previously calculating (see the api-reference-label for more details). (#237). Tutorials have also been updated to reflect the change.
• Fixed implementation and docstring of {meth}mpol.losses.log_likelihood (#237).