Skip to content

Latest commit

 

History

History
61 lines (42 loc) · 2.71 KB

README.md

File metadata and controls

61 lines (42 loc) · 2.71 KB
Raw

Vortex: State Space Modeling for Streaming Data

Vortex is a scalable Scala library tailored for high-performance and fault-tolerant state space modeling over streaming data. With real-time analytics capabilities, it enables efficient processing of continuous data streams, providing insightful, actionable information.

Features

•	Real-time state space modeling for streaming data.
•	High-performance, fault-tolerant processing.
•	Scalable architecture for large-scale data analysis.
•	Seamless integration with Scala-based streaming platforms, including a specialized ZIO module.

Project Structure

•	/modules: The core of Vortex, organized as a multi-project SBT build.
•	core: Core algorithms and functionalities for state space modeling.
•	stream: Integration with streaming data sources and stream processing utilities.
•	zio: ZIO-specific module for leveraging ZIO’s functional programming capabilities.
•	protobuf: Utilization and configurations of Protocol Buffers for efficient serialization.
•	/docs: Comprehensive documentation, including setup guides, usage examples, and API references.
•	/tests: Unit and integration tests to ensure reliability and precision.
•	/examples: Sample applications and scripts demonstrating Vortex in various scenarios.

Key Functionalities

State Space Modeling:

  • Implement state-of-the-art state space models.
  • Provide tools for model fitting, diagnostics, and predictions.

Time Series Processing:

  • Support for various windowing operations for streaming data.
  • Facilitate the handling of both regular and irregular time series.

Signal Processing:

  • Implement Fast Fourier Transforms (FFT) and Wavelet Transforms for frequency domain analysis.
  • Provide utilities for noise reduction, trend extraction, and signal decomposition.

Real-Time Data Analysis:

  • Enable real-time processing and analysis of streaming data.
  • Ensure low latency and high throughput for live data feeds.
  • Functional Programming in ZIO Streams:
  • Leverage the power of functional programming for building robust and type-safe data pipelines.
  • Integrate seamlessly with the ZIO ecosystem for asynchronous and concurrent tasks.

Project Goals

Achieve parity with key functionalities of the StatsModels Python project. Provide a Scala-native, type-safe, and functional approach to time series analysis. Make state space modeling and signal processing accessible and efficient in a streaming context.

Getting Started

Contributing

Contributions to Vortex are highly appreciated! Please review our CONTRIBUTING.md for code of conduct and contribution guidelines.

License

Vortex is licensed under the Apache 2.0 License - detailed in the LICENSE.md file.

Acknowledgments