Troyer model

[aburrell]

Description

Fixes #153 by adding the Troyer model. Also adds AMERE files to the .gitignore.

Type of change

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• This change requires a documentation update

How Has This Been Tested?

Added unit tests.

Test Configuration

• Operating system: OS X Tahoe
• Version number: Python 3.10
• Any details about your local setup that are relevant: pysat RC

Checklist:

• Make sure you are merging into the develop (not main) branch
• My commits are formatted appropriately (following the SciPy/NumPy style)
• My code follows the style guidelines of this project
• I assert that I have not used AI in the development of this pull request
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes
• Any dependent changes have been merged and published in downstream modules
• Add a note to Changelog.rst, summarising the changes
• Add yourself to AUTHORS.rst and .zenodo.json

[aburrell]

@rileytroyer let me know what you think!

[coveralls]

coverage: 99.497% (+0.02%) from 99.481% — troyer_model_plus into develop

[rileytroyer]

For future builds, assuming availability, would you envision including a argument to specify the specific percentile, or would you have that as a separate function?

[aburrell]

I think I'd add a kwarg that defaults to 50 or .5 (depending on how we formulate it) for the fully probabilistic code. Maybe even allow array-like input/output for less computations and an ensemble output? I look forward to upgrading it in the future!