Pytrad: Causal Discovery for Python
Pytrad is an open-source causal discovery library for Python, which is a Python translation and extension of Tetrad.
The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us?
Package Overview
Our Pytrad implements methods for causal discovery:
- Constrained-based causal discovery methods.
- Score-based causal discovery methods.
- Causal discovery methods based on constrained functional causal models.
- Hidden causal representation learning.
- Granger causality.
- Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations.
Install
Pytrad needs the following packages to be installed beforehand:
- python 3
- numpy
- networkx
- pandas
- scipy
- scikit-learn
- statsmodels
- pydot
(For visualization)
- matplotlib
- graphviz
To use Pytrad, we could install it using pip:
pip install pytrad
Documentation
Please kindly refer to Pytrad Doc for detailed tutorials and usages.
Metadata
Release files for Pytrad 0.1.1.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| Pytrad-0.1.1.5.tar.gz | 114.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| Pytrad-0.1.1.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 262.1 kB
Release files / Pytrad-0.1.1.5.tar.gz
| Download URL | Pytrad-0.1.1.5.tar.gz |
|---|---|
| Size | 114.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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Release files / Pytrad-0.1.1.5-py3-none-any.whl
| Download URL | Pytrad-0.1.1.5-py3-none-any.whl |
|---|---|
| Size | 147.4 kB |
| Tags | Python 3 |
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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/3.10.0 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.3
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