numpyro
cobaya
| numpyro | cobaya | |
|---|---|---|
| 2 | 1 | |
| 2,046 | 118 | |
| 1.1% | 5.1% | |
| 8.7 | 8.6 | |
| about 7 hours ago | 8 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
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numpyro
- Bayesian Analysis with Python
-
Saving the World with Bayesian Modeling
Perhaps an alternative to look into: Numpyro [1] has a JAX backend so can be really fast when compiled; and it can run on GPUs. So that might be helpful for your problem with loads of data.
[1] https://github.com/pyro-ppl/numpyro
cobaya
-
Problem installing Monte Python
Another suggestion would be to consider using a more modern package. Cobaya (https://github.com/CobayaSampler/cobaya) is one such package that would do what you want, but is much more modern and user friendly than MontePython.
What are some alternatives?
PyMC - Bayesian Modeling and Probabilistic Programming in Python
montepython_public - Public repository for the Monte Python Code
trax - Trax — Deep Learning with Clear Code and Speed
Poetry - Python packaging and dependency management made easy
einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
causalnex - A Python library that helps data scientists to infer causation rather than observing correlation.
pyprobml - Python code for "Probabilistic Machine learning" book by Kevin Murphy
BayesianEcosystems_IAP - Notes and code for Bayesian ecosystem modeling IAP course
pyro - Deep universal probabilistic programming with Python and PyTorch
Bayeslite - BayesDB on SQLite. A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself.
plc-2.0 - ``plc`` is the public Planck Likelihood Code. It provides C and Fortran libraries that allow users to compute the log likelihoods of the temperature, polarization, and lensing maps. Optionally, it also provides a python version of this library, as well as tools to modify the predetermined options for some likelihoods (e.g. changing the high-ell and low-ell lmin and lmax values of the temperature).