cobaya
Code for Bayesian Analysis (by CobayaSampler)
PyMC
Bayesian Modeling and Probabilistic Programming in Python (by pymc-devs)
| cobaya | PyMC | |
|---|---|---|
| 1 | 3 | |
| 120 | 8,202 | |
| 6.7% | 1.2% | |
| 8.6 | 9.5 | |
| 26 days ago | 5 days ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
cobaya
Posts with mentions or reviews of cobaya.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-24.
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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.
PyMC
Posts with mentions or reviews of PyMC.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-09-06.
- PYMC Release: v5.0.0
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An Astronomer's Introduction to NumPyro
I believe the pymc versions were resolved into developing version 4 of pymc. Development at https://github.com/pymc-devs/pymc
It still depends on theano now evolved and renamed
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What is Probabilistic Programming?
This tutorial explains what is probabilistic programming & provides a review of 5 frameworks (PPLs) using an example taken from Chapter 4 of Statistical Rethinking by Dr. Richard McElreath. Frameworks (PPLs) reviewed are - Stan (https://mc-stan.org/) PyMC3 (https://docs.pymc.io/) Tensorflow Probability (https://www.tensorflow.org/probability) Pyro/NumPyro (https://pyro.ai/) Turing.jl (https://turing.ml/stable/) I also provide the basic review of a great library called arviz (https://arviz-devs.github.io/arviz/), which can be used for all the above-mentioned PPLs to do Exploratory Data Analysis of Bayesian Models. Here is the link to the notebook in which I have implemented the example model using the above Frameworks/PPLs https://colab.research.google.com/drive/1zgR2b0j2waGi1ppnIe1rw7emkbBXtMqF?usp=sharing