Metadata-Version: 2.4
Name: eegcanon-ml
Version: 0.1.2
Summary: Canonical EEG representation framework
Author: AdhiAlpha27
License: MIT
Project-URL: Homepage, https://github.com/AlphaAdhi27/eegcanon
Project-URL: Repository, https://github.com/AlphaAdhi27/eegcanon
Project-URL: Issues, https://github.com/AlphaAdhi27/eegcanon/issues
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: mne
Requires-Dist: pydantic

# EEGCanon-ML 🧠⚡

EEGCanon-ML is a Python framework that converts heterogeneous EEG data
(EDF, CSV) into a **canonical, standardized representation** for
reproducible machine learning and signal analysis.

It provides a **common EEG data language** so that models, features,
and experiments can be compared fairly across datasets.

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## Why EEGCanon-ML?

EEG workflows today suffer from:
- dataset-specific preprocessing scripts
- inconsistent channel naming
- incompatible sampling rates
- poor reproducibility across studies

**EEGCanon-ML enforces a standard EEG contract.**

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## Key Features

- Unified EEG loading (EDF, CSV)
- Canonical 10-20 channel mapping
- Sampling-rate normalization
- Structured warnings & provenance tracking
- Epoching support
- Feature extraction (PSD, Bandpower, Hjorth)
- PyTorch-ready datasets

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## Installation

```bash
pip install eegcanon-ml


