Apply thinning

[mattj89]

Description

Please include a summary of the changes and the related issue. Please also include relevant motivation and context. List any dependencies that are required for this change.

Updated to account for small change in functionality in openMCMC- now the user can specify a thinning frequency for the MCMC chain, and the sampler will store only every n_thin iterations of the chain. This option is now exposed to the user in pyelq.model, defaulting to 1. Also, the gitignore was updated to prevent pushing of local .vscode settings.

Fixes # (issue)

Type of change

Please delete options that are not relevant.

• New feature (non-breaking change which adds functionality)
• This change requires a documentation update

Jupyter Notebooks

No changes to Jupyter notebooks.

How Has This Been Tested?

Please describe the tests that you ran to verify your changes. Provide instructions so we can reproduce. Please also list any relevant details for your test configuration

• Test A: All existing model tests pass using with the modified code (using the default n_thin = 1).
• Test B: Data analysis run using the modified code is successful.

Checklist:

• My code follows the style guidelines of this project
• I have performed a self-review of my code
• 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