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
Library for processing Time Series.
Add the following dependency to the build.sbt
libraryDependencies += "io.github.carldata" %% "timeseries" % "0.7.0"Running benchmarks
sbt -mem 4000 run- 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)
We are happy to receive bug reports, fixes, documentation enhancements, and other improvements.
Please report bugs via the github issue tracker.
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.