Wandas: Waveform Analysis Data Structures¶

Wandas is an open-source library for efficient signal analysis in Python. Wandas provides comprehensive functionality for signal processing and seamless integration with Matplotlib.

Features¶

Comprehensive Signal Processing Functions: Easily perform basic signal processing operations including filtering, Fourier transforms, and STFT
Integration with Visualization Libraries: Seamlessly integrate with Matplotlib for easy data visualization
Lazy Evaluation: Efficiently process large data using dask
Various Analysis Tools: Frequency analysis, octave band analysis, time-frequency analysis, and more

Usage Examples¶

Loading and Visualizing Audio Files¶

import wandas as wd

cf = wd.read_wav("data/sample.wav")
cf.describe()

Waveform and spectrogram display

Filtering¶

signal = wd.generate_sin(freqs=[5000, 1000], duration=1)
# Apply low pass filter
signal.low_pass_filter(cutoff=1000).fft().plot()

Low-pass filter results

For detailed documentation and usage examples, see the Tutorial.

Documentation Structure¶

Tutorial - 5-minute getting started guide and recipe collection for common tasks
API Reference - Detailed API specifications
Theory & Architecture - Design philosophy and algorithm explanations
Contributing Guide - Rules and methods for contribution

Next Steps¶

Explore detailed features in the API Reference
Understand the library's design philosophy in the Explanation
See Contributing Guidelines if you want to contribute.

For More Information¶

Visit the Wandas GitHub Repository for source code and issues
Check the Wandas Documentation for hosted documentation
Join the Wandas Discussion Forum for community support and discussions