signaldepends

signaldepends is a Python library designed to simplify signal processing and analysis. It provides a framework for defining, manipulating, and visualizing signals, making it easier for developers and researchers to work with time-series data. The library's core functionality revolves around representing signals as objects that can be operated upon using intuitive methods.

Key features of signaldepends include the ability to perform common signal processing operations such as filtering, spectral analysis, and feature extraction. It aims to offer a high-level abstraction over lower-level signal processing libraries, allowing users to focus on the analytical aspects rather than the implementation details. The library supports various signal types and can handle both real-valued and complex-valued signals.

signaldepends also includes tools for visualizing signals and their transformations, aiding in the understanding and interpretation of data. This visual feedback is crucial for debugging and exploring signal characteristics. The library's design emphasizes modularity and extensibility, enabling users to integrate their custom signal processing algorithms. The goal is to provide a unified and efficient environment for signal processing tasks in Python, catering to a wide range of applications from audio processing to sensor data analysis.