Metadata-Version: 2.4
Name: atarihns
Version: 0.0.18
Summary: A helper to calculate human normalized score for different atari environments efficiently and easily.
Author-email: Taha Shieenavaz <tahashieenavaz@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Taha Shieenavaz
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
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        The above copyright notice and this permission notice shall be included in all
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Project-URL: Homepage, https://github.com/tahashieenavaz/atarihns
Project-URL: Repository, https://github.com/tahashieenavaz/atarihns
Project-URL: Documentation, https://github.com/tahashieenavaz/atarihns#readme
Keywords: reinforcement learning,atari,human normalized score,hns score
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

# Atari HNS (Human Normalized Score)

Lightweight helper for computing Atari human-normalized scores (HNS) using published human and random baselines.

## Installation

- From PyPI (once published): `pip install atarihns`
- From source: clone the repo and run `pip install .`

## Usage

```python
from atarihns import get_human_score, get_random_score
from atarihns import calculate_hns, get_hns # alias

environment = "Pong-v5"
agent_score = 15.0

human = get_human_score(environment)
random = get_random_score(environment)
hns = calculate_hns(environment, agent_score)

print(f"{environment} human: {human}, random: {random}, hns: {hns:.3f}")
```

## Notes

- Baseline scores for ALE environments are defined in `atarihns.constants.ATARI_SCORES` as `(random, human)`.
- Helper functions raise `KeyError` if an environment name is missing from the table.
