Metadata-Version: 2.1
Name: tsaug
Version: 0.1.1
Summary: A package for time series augmentation
Home-page: https://github.com/arundo/tsaug
Author: Arundo Analytics, Inc.
Maintainer: Tailai Wen
Maintainer-email: tailai.wen@arundo.com
License: Apache License 2.0
Keywords: time series,data augmentation
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Requires-Python: >=3.5
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.14)
Requires-Dist: scipy (>=1.3)
Provides-Extra: testing
Requires-Dist: pytest ; extra == 'testing'

# tsaug

[![Build Status](https://travis-ci.com/arundo/tsaug.svg?branch=master)](https://travis-ci.com/arundo/tsaug)
[![Docs](https://readthedocs.com/projects/arundo-tsaug/badge/?version=latest)](https://arundo-tsaug.readthedocs-hosted.com/en/latest/)
[![PyPI](https://img.shields.io/pypi/v/tsaug)](https://pypi.org/project/tsaug/)

`tsaug` is a Python package for time series augmentation. It offers a set of 
augmentation methods for time series with unified APIs, as well as operators to
connect multiple augmentors into a pipeline.

See https://arundo-tsaug.readthedocs-hosted.com complete documentation.

## Installation

Prerequisites: Python 3.5 or later.

It is recommended to use **pip** for installation.

```shell
pip install tsaug
```

Alternatively, you could install from source code:

```shell
git clone https://github.com/arundo/tsaug.git
cd tsaug/
pip install ./
```

## Examples
Please see [Quick Start](https://arundo-tsaug.readthedocs-hosted.com/en/latest/quickstart.html) for some examples.

For full references of implemented augmentation methods, please refer to [References](https://arundo-tsaug.readthedocs-hosted.com/en/latest/references.html).

## Contributing

Pull requests are welcome. For major changes, please open an issue first to
discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

`tsaug` is licensed under the Apache License 2.0. See the [LICENSE](LICENSE) file for details.

