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.
The easiest way to install
dtcwt is via
$ 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