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PyWavelets - Wavelet Transforms in Python

PyWavelets is open source wavelet transform software for Python_. It combines a simple high level interface with low level C and Cython performance.

PyWavelets is very easy to use and get started with. Just install the package, open the Python interactive shell and type:

>>> import pywt
>>> cA, cD = pywt.dwt([1, 2, 3, 4], 'db1')

Voilà! Computing wavelet transforms has never been so simple :)

Here is a slightly more involved example of applying a digital wavelet transform to an image:

.. plot:: pyplots/

Main features

The main features of PyWavelets are:

  • 1D, 2D and nD Forward and Inverse Discrete Wavelet Transform (DWT and IDWT)
  • 1D, 2D and nD Multilevel DWT and IDWT
  • 1D, 2D and nD Stationary Wavelet Transform (Undecimated Wavelet Transform)
  • 1D and 2D Wavelet Packet decomposition and reconstruction
  • 1D Continuous Wavelet Transform
  • Computing Approximations of wavelet and scaling functions
  • Over 100 `built-in wavelet filters`_ and support for custom wavelets
  • Single and double precision calculations
  • Real and complex calculations
  • Results compatible with Matlab Wavelet Toolbox (TM)

Getting help

Use `GitHub Issues`_, `StackOverflow`_, or the `PyWavelets discussions group`_ to post your comments or questions.


PyWavelets is a free Open Source software released under the MIT license.


If you use PyWavelets in a scientific publication, we would appreciate citations of the project:

Lee G, Gommers R, Wasilewski F, Wohlfahrt K, O'Leary A, Nahrstaedt H, and Contributors, "PyWavelets - Wavelet Transforms in Python", 2006-, [Online; accessed 2018-MM-DD].


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