https://github.com/TimeSynth/TimeSynth

A Multipurpose Library for Synthetic Time Series Generation in Python
https://github.com/TimeSynth/TimeSynth

generator python python3 series time-series timeseries

Last synced: 2 months ago
JSON representation

A Multipurpose Library for Synthetic Time Series Generation in Python

• Host: GitHub
• URL: https://github.com/TimeSynth/TimeSynth
• Owner: TimeSynth
• License: mit
• Created: 2016-07-06T15:40:50.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2023-10-26T22:59:57.000Z (about 1 year ago)
• Last Synced: 2024-04-24T16:04:20.768Z (9 months ago)
• Topics: generator, python, python3, series, time-series, timeseries
• Language: Jupyter Notebook
• Homepage:
• Size: 2.87 MB
• Stars: 326
• Watchers: 19
• Forks: 62
• Open Issues: 12
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-time-series - TimeSynth

README

        
[![Build Status](https://travis-ci.org/TimeSynth/TimeSynth.svg?branch=master)](https://travis-ci.org/TimeSynth/TimeSynth) [![codecov](https://codecov.io/gh/TimeSynth/TimeSynth/branch/master/graph/badge.svg)](https://codecov.io/gh/TimeSynth/TimeSynth)

# TimeSynth

_Multipurpose Library for Synthetic Time Series_

**Please cite as:**   

J. R. Maat, A. Malali, and P. Protopapas, “TimeSynth: A Multipurpose Library for Synthetic Time Series in Python,” 2017. [Online]. Available: http://github.com/TimeSynth/TimeSynth

**TimeSynth** is an open source library for generating synthetic time series for

model testing. The library can generate regular and irregular time series. The architecture

allows the user to match different signals with different architectures allowing

a vast array of signals to be generated. The available signals and noise types are

listed below.

N.B. We only support Python 3.6+ at this time.

#### Signal Types

* Harmonic functions(sin, cos or custom functions)

* Gaussian processes with different kernels

    * Constant

    * Squared exponential

    * Exponential

    * Rational quadratic

    * Linear

    * Matern

    * Periodic

* Pseudoperiodic signals

* Autoregressive(p) process

* Continuous autoregressive process (CAR)

* Nonlinear Autoregressive Moving Average model (NARMA)

#### Noise Types

* White noise

* Red noise

### Installation

To install the package via github,

```{bash}

git clone https://github.com/TimeSynth/TimeSynth.git

cd TimeSynth

python setup.py install

```

### Using TimeSynth

```shell

$ python

```

The code snippet demonstrates creating a irregular sinusoidal signal with white noise.

```python

>>> import timesynth as ts

>>> # Initializing TimeSampler

>>> time_sampler = ts.TimeSampler(stop_time=20)

>>> # Sampling irregular time samples

>>> irregular_time_samples = time_sampler.sample_irregular_time(num_points=500, keep_percentage=50)

>>> # Initializing Sinusoidal signal

>>> sinusoid = ts.signals.Sinusoidal(frequency=0.25)

>>> # Initializing Gaussian noise

>>> white_noise = ts.noise.GaussianNoise(std=0.3)

>>> # Initializing TimeSeries class with the signal and noise objects

>>> timeseries = ts.TimeSeries(sinusoid, noise_generator=white_noise)

>>> # Sampling using the irregular time samples

>>> samples, signals, errors = timeseries.sample(irregular_time_samples)

```