More interpolation types in Tabular.

[GuySten]

Description

This pull request implement more interpolation types in Tabular by using inverse transform sampling algorithm.

Fixes #2409.

Checklist

• I have performed a self-review of my own code
• I have run clang-format (version 15) on any C++ source files (if applicable)
• I have followed the style guidelines for Python source files (if applicable)
• I have made corresponding changes to the documentation (if applicable)
• I have added tests that prove my fix is effective or that my feature works (if applicable)

[shimwell]

While working through the open PRs I just noticed that a conflict has crept into this one

[GuySten]

I fixed the conflicts.

[paulromano]

Thanks for putting this together @GuySten and sorry it has taken me a long time to look this one over. In general, I feel like the addition of the Lambert W function on the C++ side is a lot of code for something that would almost never be used. I would be comfortable adding the sampling routines on the Python side (where we already have access to lambertw from scipy) but would prefer not to include the C++ portion. If someone really needs to sample a lin-log distribution on the C++ side, I think a better option is to just linearize it first and we already have the openmc.data.grid.linearize function that can handle that.

[GuySten]

I removed lin log interpolation from cpp side.