scaleogram 0.9.1

User friendly scaleogram plot for Continuous Wavelet Transform

# scaleogram

Scaleogram is a user friendly plot tool for data analysis with Continuous Wavelet Transform.

It has the following features:

• simple call signature for complete beginners

• readable axes and clean matplotlib integration

• support for periodicity and frequency units

• speed

• portability: tested with python2.7 and python3.7

• comprehensive error message and documentation with examples

• support for Cone Of Influence mask

## Install with pip

Installation should be straightforward with

` pip install scaleogram `

## Install from github

` git clone http://github.com/alsauve/scaleogram cd scaleogram python ./setup.py install --user `

### Prerequisites

This module depends on

• PyWavelet >= 0.9

• matplotlib >= 2.0

• numpy >= 1.0

## Running the tests

A features test matrix can be plotted with

` # launch graphical tests python -m scaleogram.test `

## Built With

• [ViM](https://www.vim.org/) - The editor

• [Spyder](https://www.spyder-ide.org/) - The Scientific Python Developement Environment

• [Jupyter](https://jupyter.org/) - The Jupyter Notebook

## Contributing

Please read [CONTRIBUTING.md](https://gist.github.com/PurpleBooth/b24679402957c63ec426) for details on our code of conduct, and the process for submitting pull requests to us.

## Versioning

We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/alsauve/scaleogram/tags).

## Authors

• Alexandre sauve - Initial work - [Scaleogram](https://github.com/alsauve/scaleogram)

## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details

## Acknowledgments

• The team behind PyWavelet for their nice job into making wavelet transform available

• The Matlab environement for inspiration and good documentation

• Mabel Calim Costa for the waipy package and inspiration