Biblioteka Timeseries powstała w ramach prac badawczo rozwojowych w RAMACH PROGRAMU OPERACYJNEGO INTELIGENTNY ROZWÓJ w projekcie:

Predykacja wydajności sieci kanalizacyjno-burzowej w czasie rzeczywistym jako usługa Saas oparta na danych pozyskanych metodami uczenia maszynowego

Welcome to the Time Series library

Library for processing Time Series.

Quick start

Add the following dependency to the build.sbt

libraryDependencies += "io.github.carldata" %% "timeseries" % "0.7.0"

Running benchmarks

sbt -mem 4000 run

Features

Basic functionality
- Slicing series
- Map, fold and filter
- Integration
- Differentiation
- groupBy
- Rolling window
- Resampling
- join and merge
Calculate statistics
- min, max
- mean, variance and standard deviation
- covariance and correlation
- normalization
IO
- Read data to/from CSV string
Generators
- Constant series
- Random noise
- Random Walk
- periodic pattern
Metrics
- MSE and RMSE between 2 series
- MAE between 2 series
- MAPE between 2 series
- MAD between 2 series
ARIMA
- Check is series is stationary
- AR(p) - Autoregressive
- I(d) - Integrate
- MA(q) - Moving average
Advanced functionality
- Finding sessions (periods of activity)

Join in!

We are happy to receive bug reports, fixes, documentation enhancements, and other improvements.

Please report bugs via the github issue tracker.

Redistributing

timeseries source code is distributed under the Apache-2.0 license.

Contributions

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be licensed as above, without any additional terms or conditions.