4 releases
| 0.1.2 | Feb 20, 2024 |
|---|---|
| 0.1.1 | Feb 16, 2024 |
| 0.1.0 | Sep 25, 2023 |
| 0.1.0-alpha.0 | Sep 8, 2023 |
#172 in Testing
Used in 3 crates
44KB
1.5K
SLoC
augurs - a time series framework for Rust
This repository contains augurs, a time series framework built in Rust.
It aims to provide some useful primitives for working with time series,
as well as the main functionality: heavily optimized forecasting models
based on existing R or Python implementations.
As well as the core Rust library, augurs will provide bindings to other languages such as Python and Javascript (via WASM).
Status: please note that this repository is very much in progress. APIs are subject to change, and functionality may not be fully implemented.
Crate descriptions
| Name | Purpose | Status |
|---|---|---|
augurs-core |
Common structs and traits | alpha - API is flexible right now |
augurs-ets |
Automatic exponential smoothing models | alpha - non-seasonal models working and tested against statsforecast |
augurs-mstl |
Multiple Seasonal Trend Decomposition using LOESS (MSTL) | beta - working and tested against R |
augurs-seasons |
Seasonality detection using periodograms | alpha - working and tested against Python in limited scenarios |
augurs-testing |
Testing data and, eventually, evaluation harness for implementations | alpha - just data right now |
augurs-js |
WASM bindings to augurs | alpha - untested, should work though |
pyaugurs |
Python bindings to augurs | alpha - untested, should work though |
Releasing
Releases are made using release-plz: a PR should be automatically created for each release, and merging will perform the release and publish automatically.
License
Dual-licensed to be compatible with the Rust project.
Licensed under the Apache License, Version 2.0 <http://www.apache.org/licenses/LICENSE-2.0> or the MIT license <http://opensource.org/licenses/MIT>, at your option.
lib.rs:
Testing utilities and data for the augurs time series framework.
Eventually I'd like this to be a fully fledged testing harness to automatically compare results between the augurs, Python and R implementations, but for now it's just a place to put some data.