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dtcwt 0.8.0

A port of the Dual-Tree Complex Wavelet Transform MATLAB toolbox.

Latest Version: 0.9.1

This library provides support for computing 1D, 2D and 3D dual-tree complex wavelet transforms and their inverse in Python. Full documentation is available online.

https://travis-ci.org/rjw57/dtcwt.png?branch=master Coverage License Latest Version Downloads

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:

$ python setup.py nosetests

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

Further documentation

There is more 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/.

Provenance

Based on the Dual-Tree Complex Wavelet Transform Pack for MATLAB by Nick Kingsbury, Cambridge University. The original README can be found in ORIGINAL_README.txt. This file outlines the conditions of use of the original MATLAB toolbox.

Changes

0.8.0

  • Verified the highpass re-sampling routines in dtcwt.sampling against the existing MATLAB implementation.
  • Added experimental image registration routines.
  • Re-organised documentation.

0.7.2

  • Fixed regression from 0.7 where backend_opencl.dtwavexfm2 would return None, None, None.

0.7.1

  • Fix a memory leak in OpenCL implementation where transform results were never de-allocated.
 
File Type Py Version Uploaded on Size
dtcwt-0.8.0.tar.gz (md5) Source 2014-01-30 2MB
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