PyWavelets 1.0.3 is functionally equivalent to the 1.0.2 release. It was made
to add the add an archive of the JOSS paper to the 1.0.x branch and serve as a
reference corresponding to the version of the software reviewed that was peer
reviewed.
PyWavelets 1.0.2 is a bug-fix and maintenance release with no new features
compared to 1.0.1.
PyWavelets 1.0.1 is a bug-fix release with no new features compared to 1.0.0.
We are very pleased to announce the release of PyWavelets 1.0. We view this
version number as a milestone in the project's now more than a decade long
history. It reflects that PyWavelets has stabilized over the past few years,
and is now a mature package which a lot of other important packages depend on.
A listing of those package won't be complete, but some we are aware of are:
- scikit-image <https://scikit-image.org>_ - image processing in Python
- imagehash <https://github.com/JohannesBuchner/imagehash>_ - perceptual image hashing
- pyradiomics <https://github.com/Radiomics/pyradiomics>_ - extraction of Radiomics features from 2D and 3D images and binary masks
- tomopy <https://github.com/tomopy/tomopy>_ - Tomographic Reconstruction in Python
- SpikeSort <https://github.com/btel/SpikeSort>_ - Spike sorting library implemented in Python/NumPy/PyTables
- ODL <https://github.com/odlgroup/odl>_ - operator discretization library
This release requires Python 2.7 or >=3.5 and NumPy 1.9.1 or greater.
The 1.0 release will be the last release supporting Python 2.7. It will be a
Long Term Support (LTS) release, meaning that we will backport critical bug
fixes to 1.0.x for as long as Python itself does so (i.e. until 1 Jan 2020).
PyWavelets is a Python wavelet transforms module that includes:
* nD Forward and Inverse Discrete Wavelet Transform (DWT and IDWT)
* 1D and 2D Forward and Inverse Stationary Wavelet Transform
(Undecimated Wavelet Transform)
* 1D and 2D Wavelet Packet decomposition and reconstruction
* 1D Continuous Wavelet Tranfsorm
* Computing Approximations of wavelet and scaling functions
* Over 100 built-in wavelet filters and support for custom wavelets
* Single and double precision calculations
* Results compatibility with Matlab Wavelet Toolbox (tm)
