Post-kriging apportionment refactoring

[brandynlucca]

This includes the post-processing performed on the kriged mesh population estimates, which achieves the following steps:

• Convert mesh biomass to NASC
• Distribute the kriged estimates over a grid (e.g. age-vs-length for each sex)
• Standardize the unaged distributions to be distributed across age as well with optional imputation
• Combine the aged and unaged tables into one single table
• Redistribute values in the distribution based on some defined criteria, such as excluding age-1 fish

This PR also includes a function for removing specimen-specific haul numbers from the catch data. This avoids incidentally double-counting haul weights where an entire haul's catch was represented in the specimen station dataset and not binned length station data.

All functions are accompanied by corresponding pytest functions and fixtures. coverage clocks in with 92%, with all misses pointing to interspersed validation lines that raise Errors (e.g. missing columns) that were retained from earlier debugging.

[leewujung]

@brandynlucca : Thanks for the PR. I added a few comments. I read through the code for some of the functions, but not all.

Two of my comments are about the function names - IMHO these two functions have limited use case and can be renamed to reflect the operations they are designed to do:

• standardize_kriged_estimates distributes unaged estimates to aged estimates according to previously calculated aged proportions
• combine_population_tables: combined aged and distributed unaged and already aged estimates.

I've also made notes in #369 re changing these to use xarray dataset/data variables operations.

Other than these and my other small questions, I think this PR is ready to be merged.