Time series signal processing — filtering, smoothing, peak detection, frequency analysis
SignalAI is a lightweight Python library for time series signal processing. It provides smoothing, peak/valley detection, FFT analysis, and bandpass filtering using NumPy — no heavy DSP libraries required.
pip install signalaifrom signalai import SignalAI
import numpy as np
signal = SignalAI()
data = np.sin(np.linspace(0, 4 * np.pi, 200)) + np.random.normal(0, 0.1, 200)
signal.load(data)
smoothed = signal.smooth(window_size=10)
peaks = signal.detect_peaks(threshold=0.5)
stats = signal.get_stats()
print(f"Found {len(peaks)} peaks, mean={stats['mean']:.3f}")graph TD
A[Raw Signal] --> B[SignalAI]
B --> C[Smoothing]
B --> D[Peak Detection]
B --> E[FFT Analysis]
B --> F[Bandpass Filter]
C & D & E & F --> G[Processed Output]
Inspired by signal processing and time series analysis trends but built as a lightweight NumPy-only toolkit.
Built by Officethree Technologies | Made with love and AI