A Causal Inference Framework for Environmental Data Analysis
Project description
EnvCausal
A Causal Inference Framework for Environmental Data Analysis
This repository contains all the necessary data and custom Python scripts to reproduce the results in the paper "Machine Learning–Aided Causal Inference Framework for Environmental Data Analysis: A COVID-19 Case Study".
Jupyter Notebook examples will be uploaded in future releases.
Install
pip install EnvCausal
Script descriptions
clustering.py -- A PCA-then-k-means clustering pipeline.
causal_estimate.py -- A dowhy package wrapper, results will be written in a txt file1.
recover_network.py -- A SAM model for Bayesian network recovery, adjacent matrix will be returned.
result_plot.py -- A couple of functions for result visualization.
1Inspired by Dowhy example: Iterating over multiple refutation tests
Acknowledgements
This software is based in part on the following packages:
DoWhy
EconML
CausalML
CausalDiscoveryToolbox
Thanks for the developers' effort on those fascinating causal inference tools!
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file EnvCausal-0.3.4.tar.gz
.
File metadata
- Download URL: EnvCausal-0.3.4.tar.gz
- Upload date:
- Size: 2.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.1 importlib_metadata/2.0.0 pkginfo/1.6.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.55.1 CPython/3.7.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 23c1b933cf4c188d03f25dcb34fd3e3d6ae07cde5c9974688d7d94011ef76e2e |
|
MD5 | 8954d883da7ad03ade216f7478e07bcd |
|
BLAKE2b-256 | 94ddbc84930cfbec5f58c374e2e064361e31726b3fcaf377524f8a078fe97630 |