Getting Started

This library provides support for computing 1D, 2D and 3D dual-tree complex wavelet transforms and their inverse in Python along with some signal processing algorithms which make use of the DTCWT.

This section will guide you through using the dtcwt library. See API Reference for full details on the library’s API.

Installation

The easiest way to install dtcwt is via easy_install or pip:

$ pip install dtcwt

If you want to check out the latest in-development version, look at the project’s GitHub page. Once checked out, installation is based on setuptools and follows the usual conventions for a Python project:

$ python setup.py install

(Although the develop command may be more useful if you intend to perform any significant modification to the library.) A test suite is provided so that you may verify the code works on your system:

$ pip install -r tests/requirements.txt
$ py.test

This will also write test-coverage information to the cover/ directory.

Building the documentation

There is a pre-built version of this documentation available online and you can build your own copy via the Sphinx documentation system:

$ python setup.py build_sphinx

Compiled documentation may be found in build/docs/html/.