jgraving / pypwt

A CUDA implementation of the Wavelet Transform

pypwt

pypwt is a python module for parallel Discrete Wavelet Transform. This is a wrapper of PDWT.

Features

• Pythonic interface providing the full potential of PDWT
• Compatible with Python >=2.7 and Python >=3.4
• Test suite
• Documentation and examples

Installation

Requirements

You need cython and nvcc (the Nvidia CUDA compiler, available in the NVIDIA CUDA Toolkit).

For the tests, you need pywavelets. python-pywt is packaged for Debian-like distributions, more recent changes are available on the new repository.

Compiling

Running

python setup.py install --user

should build and install the module. For python3, just replace python with python3.

Testing

If pywt is available, you can check if pypwt gives consistent results :

cd test
python test_all.py

the results are stored in results.log.

Getting started

Computing a Wavelet Transform wity pypwt is simple. In ipython:

from pypwt import Wavelets
from scipy.misc import lena
l = lena()
W = Wavelets(l, "db2", 3)
W
------------- Wavelet transform infos ------------
Wavelet name : db2
Number of levels : 3
Stationary WT : no
Cycle spinning : no
Separable transform : yes
Estimated memory footprint : 5.2 MB
Running on device : GeForce GTX TITAN X
--------------------------------------------------
W.forward()
W.soft_threshold(10)
W.inverse()
imshow(W.image)