Metadata-Version: 2.4
Name: npyci
Version: 0.1.0
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Programming Language :: Rust
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Requires-Dist: numpy>=1.20
Summary: High-performance signal processing for BCI research
Keywords: signal-processing,bci,neuroscience,eeg,filtering
Author: Fredrik Whaug
License: AGPL-3.0
Requires-Python: >=3.8
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Repository, https://github.com/fredrikWHaug/zerostone

# npyci - NumPy for BCI

High-performance signal processing for BCI research, powered by Rust.

## Installation

```bash
pip install npyci
```

## Quick Start

```python
import numpy as np
import npyci as npy

# Create a lowpass filter
lpf = npy.IirFilter.butterworth_lowpass(sample_rate=1000.0, cutoff=30.0)

# Generate and filter a signal
signal = np.random.randn(1000).astype(np.float32)
filtered = lpf.process(signal)
```

## Features

- Zero-allocation signal processing
- Real-time performance
- Butterworth IIR filters (lowpass, highpass, bandpass)
- More primitives coming soon!

## License

AGPL-3.0

