Notes from UT Austin visit on November 5, 2018

[gully]

We eventually want to scale up the spectral inference to more sources with supercomputing resources. For now, let's focus on a few good demo sources, with good priors, good initial guesses, good noise models, and reproducible workflows.

Tasks:

• Make sure all order have the same user-defined priors
• Spot check the residuals for all initial guesses, iteratively refine
• git commit all config.yaml and s0_phi.json files
• Run token MCMC of ~3 samples to make sure everything compiles
• pull all changes to NAS HECC resources
• git commit the conda environment.yml file and .envrc file for reproducibility
• Pick system for deployment-- pleiades or other
• Deploy to Pleiades