wmtsa-python Icon


Discrete wavelet methods for time series analysis using python

As of 2015-04-28, this project may now be found at https://bitbucket.org/fluiddyn/fluiddata.

Add a Review
7 Downloads (This Week)
Last Update:
Download wmtsa-python.zip
Browse All Files
Windows Mac Linux


Several python libraries implement discrete wavelet transforms. However, none of them, or at least none that I know, is aimed at scientific use. This module started as translation of the wmtsa Matlab toolbox (http://www.atmos.washington.edu/~wmtsa/), so most naming conventions and most of the code structure follows their choices. The code uses a mix of python and cython for improved performance.
The code reflects my needs and preferences, but contributions from others are welcome.
The code is still evolving, so downloading the latest version from svn is always the best option.
The code has to some extent been tested, but bugs are to be expected.


The code has been moved to BitBucket, in an effort to combine it to more general fluid dynamics tools:


Any further development will take place on BitBucket. Please download the code from there, and report any issue there as well.

wmtsa-python Web Site


  • Maximum overlap discrete wavelet transform
  • Stationary wavelet transform
  • Wavelet spectrum


Write a Review

User Reviews

Be the first to post a review of wmtsa-python!

Additional Project Details

Intended Audience


User Interface


Programming Language




Thanks for helping keep SourceForge clean.

Screenshot instructions:
Red Hat Linux   Ubuntu

Click URL instructions:
Right-click on ad, choose "Copy Link", then paste here →
(This may not be possible with some types of ads)

More information about our ad policies

Briefly describe the problem (required):

Upload screenshot of ad (required):
Select a file, or drag & drop file here.

Please provide the ad click URL, if possible:

Get latest updates about Open Source Projects, Conferences and News.

Sign up for the SourceForge newsletter:

No, thanks
Screenshots can attract more users to your project.
Features can attract more users to your project.