Skip to main content

Interactive visualizations to assess fairness, explain models, generate counterfactual examples, analyze causal effects and analyze errors in Machine Learning models.

Project description

AffectLog Widgets

This repository contains the affectlog_widgets library, which is used for creating interactive, visual Trustworthy AI tools. This project provides a set of widgets for model assessment, fairness analysis, error detection, and more, built on top of machine learning frameworks.

Requirements for Development

To contribute to affectlog_widgets, make sure to install the following dependencies.

Testing Dependencies

For running tests with code coverage and mocking, use the following:

pytest==7.0.1
pytest-cov
pytest-mock==3.6.1

Parser Dependencies

For parsing requirements, use:

requirements-parser==0.2.0

Package Building

Ensure you have the necessary tools for building the package:

wheel

Machine Learning & Fairness Libraries

Install the following libraries to enable machine learning and fairness evaluation tools:

fairlearn==0.7.0
ml-wrappers>=0.4.0
sktime
pmdarima

Note: For Windows users running Python 3.7, add the following fix for joblib compatibility:

joblib<1.3.0; python_version <= '3.7' and sys_platform == 'win32'

Notebook Testing

To test notebooks and perform notebook validation, install:

nbformat
papermill
scrapbook
jupyter
nbval

Documentation Dependencies

For generating documentation, install the following:

docutils<=0.19
sphinx==5.0.2
sphinx-gallery==0.10.0
pydata-sphinx-theme==0.7.2

Setting up the Development Environment

Follow these steps to set up your local development environment:

  1. Clone the repository:

    git clone <repository_url>
    cd affectlog_widgets
    
  2. Install Dependencies: You can install all dependencies via pip:

    pip install -r requirements.txt
    
  3. Run Tests: To ensure everything is working, run the tests:

    pytest
    

Local Installation

For local development, ensure that trustworthyai is available in your project. You can use the relative path for local development:

../trustworthyai/.

Add this path when running your local environment so the necessary modules can be accessed.

Contributing

If you're interested in contributing, please create a feature branch from main, make your changes, and open a pull request. Ensure that all tests pass and documentation is updated where necessary.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

affectlog_widgets-0.0.4.tar.gz (30.6 kB view details)

Uploaded Source

Built Distribution

affectlog_widgets-0.0.4-py3-none-any.whl (35.7 kB view details)

Uploaded Python 3

File details

Details for the file affectlog_widgets-0.0.4.tar.gz.

File metadata

  • Download URL: affectlog_widgets-0.0.4.tar.gz
  • Upload date:
  • Size: 30.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for affectlog_widgets-0.0.4.tar.gz
Algorithm Hash digest
SHA256 cf0391457cbee4dd04a890a9bc3945ac5541aca36e18bd4d1931bd49dd52774e
MD5 f8339c40495a23ee1449c92d7a01bb49
BLAKE2b-256 7f5766f6a6a6ed5ef20d6268956cc97f9c26de4aa31a3cbf9ae4d126d3b4709a

See more details on using hashes here.

File details

Details for the file affectlog_widgets-0.0.4-py3-none-any.whl.

File metadata

File hashes

Hashes for affectlog_widgets-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 e9d80b9cecc179efd7e6a2ac25edb96098ea0e1d94c4ddc51684271f4baa482e
MD5 7a66241d764802daf4a8e627a5ab2823
BLAKE2b-256 14e40d29a768046046b74704543c7cdbb8ad26eec0fc9bdd908e2b98154a62a0

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page