Metadata-Version: 2.4
Name: effdim
Version: 0.1.0
Summary: A unified library for estimating effective dimensionality.
Author-email: amanasci <kumaramanasci@gmail.com>
License-Expression: MIT
License-File: LICENSE
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Requires-Dist: numpy
Requires-Dist: scipy
Provides-Extra: dev
Requires-Dist: black; extra == 'dev'
Requires-Dist: mypy; extra == 'dev'
Requires-Dist: pytest; extra == 'dev'
Requires-Dist: pytest-cov; extra == 'dev'
Description-Content-Type: text/markdown

# EffDim

**EffDim** is a unified, research-oriented Python library designed to compute "effective dimensionality" (ED) across diverse data modalities.

## Installation

```bash
pip install effdim
```

## Usage

```python
import numpy as np
import effdim

data = np.random.randn(100, 50)
ed = effdim.compute(data, method='pca', threshold=0.95)
print(f"Effective Dimension: {ed}")
```

## Features

- **Modality Agnostic**: Works with raw data, covariance matrices, and pre-computed spectra.
- **Unified Interface**: Simple `compute` and `analyze` functions.
- **Extensive Estimators**: PCA, Participation Ratio, Shannon Entropy, and more.
