High-performance signal processing for BCI research

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  • License: GNU Affero General Public License v3 (AGPL-3.0)
  • Author: Fredrik Whaug
  • Tags signal-processing , bci , neuroscience , eeg , filtering
  • Requires: Python >=3.8
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Reason this release was yanked:

Package renamed to zpybci. Install with: pip install zpybci

Project description

npyci - NumPy for BCI

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

Installation

pip install npyci

Quick Start

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

Project details

Verified details

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Meta
  • License: GNU Affero General Public License v3 (AGPL-3.0)
  • Author: Fredrik Whaug
  • Tags signal-processing , bci , neuroscience , eeg , filtering
  • Requires: Python >=3.8
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0.1.0 yanked

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