# 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/`.