- ProbPy is a Python library that aims at simplifying calculations with
discrete multi variable probabilistic distributions by offering an abstraction over how data is stored and how the operations between distributions are performed.
The library can be used in the implementation of many algorithms such as Bayes Theorem, Bayesian Inference algorithms like Variable Elimination, Gibbs Ask (MCMC), HMMs implementations, Information Theory, etc.
Hosted at GitHub: https://github.com/petermlm/ProbPy.
Metadata
Release files for ProbPy 1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| ProbPy-1.2.tar.gz | 26.2 kB | Without provenance | Details for ProbPy-1.2.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| ProbPy-1.2-py3-none-any.whl | Python 3 | none | any | Details for ProbPy-1.2-py3-none-any.whl |
Total release size: 51.8 kB
Release files / ProbPy-1.2.tar.gz
| Download URL | ProbPy-1.2.tar.gz |
|---|---|
| Size | 26.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.8.10
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Release files / ProbPy-1.2-py3-none-any.whl
| Download URL | ProbPy-1.2-py3-none-any.whl |
|---|---|
| Size | 25.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.0 CPython/3.8.10
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Security for ProbPy 1.2
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