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/camera_approx_detail.py
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)
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-, https://github.com/PyWavelets/pywt [Online; accessed 2018-MM-DD].
.. toctree:: :maxdepth: 1 install ref/index regression/index contributing dev/index releasenotes