Metadata-Version: 2.1
Name: emlangkit
Version: 0.0.1
Summary:  Emergent Language Analysis Toolkit
Author-email: Olaf Lipinski <o.lipinski@soton.ac.uk>
Project-URL: Homepage, https://github.com/olipinski/emlangkit
Project-URL: Bug Tracker, https://github.com/olipinski/emlangkit/issues
Keywords: emergent communication,emergent language
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: editdistance

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://pre-commit.com/)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

# Emergent Language Analysis Toolkit

This toolkit aims to collect all metrics currently used in emergent
communication research into one place. The usage should be convenient and the
inputs should be standardised, to ease adoption and spread of these metrics.

## Installation

To install emlangkit, run `pip install emlangkit`.

Automatic tests are run for Python 3.9, 3.10, 3.11.

## Usage

All metrics are available through the `Language` class in `emlangkit.Language`.
This class accepts two numpy arrays as inputs - messages and observations. These
are then used, with some possible speedups, to calculate any requested metric,
as per example below

```python
import numpy as np
from emlangkit import Language

messages = np.array(
    [[1, 2, 0, 3, 4], [1, 2, 2, 3, 4], [1, 2, 2, 3, 0], [1, 0, 0, 1, 2]]
)
observations = np.array([[4, 4], [4, 3], [3, 2], [1, 4]])

lang = Language(messages=messages, observations=observations)

score, p_value = lang.topsim()

# Mutual information already requires both language and observation entropy
mi = lang.mutual_information()

# So this call uses less computation
lang_entropy = lang.language_entropy()
```

## Metrics

Currently available metrics, with their implementations as per below.

- Entropy (`emlangkit.metrics.entropy`)
- Mutual Information (`emlangkit.metrics.mutual_information`)
- Topographic Similarity (`emlangkit.metrics.topsim`)
- Positional Disentanglement (`emlangkit.metrics.posdis`)
- Bag-of-Words Disentanglement (`emlangkit.metrics.bosdis`)

## Contributing

All pull requests are welcome! Just please make sure to install pre-commit and
run the pytests before submitting a PR. Additionally, if a lot of new code is
added, please also add the relevant tests.

## Related Libraries

This is a non-exhaustive list of libraries related to EC research. Please feel
free to open a PR to add to it!

- EGG - https://github.com/facebookresearch/EGG
- Harris' Articulation Scheme - https://github.com/wedddy0707/HarrisSegmentation
- CGI -
  https://github.com/wedddy0707/categorial_grammar_induction_of_emergent_language

## Sources

Most of the base metrics are inspired or taken from either
[EGG](https://github.com/facebookresearch/EGG), or code from the paper
"Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of
Compositional Communication"
[here](https://proceedings.neurips.cc/paper/2021/hash/c2839bed26321da8b466c80a032e4714-Abstract.html).

## Citation

If you find emlangkit useful in your work, please cite it as below:

```
@software{lipinski_emlangkit_2023,
        title = {emlangkit: Emergent Language Analysis Toolkit},
        url = {https://github.com/olipinski/emlangkit},
        author = {Lipinski, Olaf},
        year = {2023}
}
```
