caribou_hi

caribou_hi is a Bayesian model of the diffuse neutral interstellar medium. Written in the bayes_spec framework, caribou implements models to predict 21-cm observations of neutral hydrogen in emission, absorption, or both. The bayes_spec framework provides methods to fit these models to data using Monte Carlo Markov Chain techniques.

Useful information can be found in the caribou_hi Github repository, the bayes_spec Github repository, and in the tutorials below.

Installation

conda create --name caribou_hi -c conda-forge pytensor pymc pip
conda activate caribou_hi
# Due to a bug in arviz, this fork is temporarily necessary
# See: https://github.com/arviz-devs/arviz/issues/2437
pip install git+https://github.com/tvwenger/arviz.git@plot_pair_reference_labels
pip install caribou_hi

Tutorials:

• AbsorptionModel Tutorial
  • Simulating Data
  • Model Definition
  • Variational Inference
  • Posterior Sampling: MCMC
• EmissionModel Tutorial
  • Simulating Data
  • Model Definition
  • Variational Inference
  • Posterior Sampling: MCMC
• EmissionAbsorptionModel Tutorial
  • Simulating Data
  • Model Definition
  • Variational Inference
  • Posterior Sampling: MCMC
• EmissionAbsorptionModel Constant Column Density Bias
  • Simulating Data
  • Model Definition
  • Variational Inference
  • Posterior Sampling: MCMC
• AbsorptionPhysicalModel Tutorial
  • Simulating Data
  • Model Definition
  • Variational Inference
  • Posterior Sampling: MCMC
• EmissionPhysicalModel Tutorial
  • Simulating Data
  • Model Definition
  • Variational Inference
  • Posterior Sampling: MCMC
• EmissionAbsorptionPhysicalModel Tutorial
  • Simulating Data
  • Model Definition
  • Variational Inference
  • Posterior Sampling: MCMC
• Optimization Tutorial
  • Model Definition and Simulated Data
  • Optimize

API:

• caribou_hi
  • caribou_hi