Metadata-Version: 2.1
Name: StructuralCausalModels
Version: 3.2.0
Summary: A Python package for Structural Causal Models.
Home-page: https://github.com/Black-Swan-ICL/PySCMs
Author: K. M-H
Author-email: kmh.pro@protonmail.com
License: MIT
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Intended Audience :: Science/Research
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: pytest
Requires-Dist: pytest-cov

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# StructuralCausalModels
## Description
A Python package implementing Structural Causal Models (SCMs). 

The package makes it possible to go from Structural Causal Models to 
Graphs. It is also possible to generate a Linear Structural Causal 
Model directly from a coefficient matrix (i.e. the weighted adjacency
matrix of the graph).

'Graph' objects are defined by giving an adjacency matrix (and a name,
optionally). They contain and maintain different representations of a
graph which can be useful depending on the circumstances, and tools to
go from any one representation to any other. 

The representations implemented at present are:

- via an adjacency matrix,
- via adjacency lists,
- via edges ("typed" edges : no edge, forward, backward or undirected 
  edge).

## Documentation
The documentation for the package is available 
[here](https://pyscms.readthedocs.io/en/latest/modules.html).


