fastwht is a C++ implementation (using fxt) of the fast Walsh-Hadamard transform with bindings to MATLAB and Python. The algorithm performs the transform in place in O( N log(N) ) operations. The current version is order of magnitude faster than MATLAB's own implementation fwht. As Python's Numpy and Scipy packages do not implement this transform, no such comparison has been made for the Python implementation.
The MATLAB interface supports the two functions fastwht and had_mat_idx. The fastwht function is a faster version of MATLAB's fwht function, and for its usage, we refer to MATLAB's own documentation. The had_mat_idx function is a function generating requested entries in a 2^n x 2^n sequency ordered Hadamard matrix. This function is very convenient to use when you want to evaluate a Walsh function at a single or a few dyadic grid points. This can be done by using the relation between Walsh functions and Hadamard matrices.
Below you find a test of performance between the fastwht function found in this repository and MATLAB's fwht and fft functions. As you can see from the figure, the function performs on par with the fft function, while it is order of magnitude faster than MATLAB's own implementation.
The interface between C++ and Python is auto-generated using Swig version 3.0.8. On top of this python interface, there has been built an extra layer of wrapper code to support complex arrays and matrix objects. None of swig's auto-generated code is submitted in this repository.
You may pull the required code directly from this repository and compile it yourself, or you can download these precompiled binaries: MATLAB and Python. Remember to update your Python and MATLAB path after you have compiled the code. The current release has mostly been tested on Linux machines.
If the fastwht function receives a matrix input, it applies the fast Walsh-Hadamard transform to each column in the matrix. This operation can be performed in parallel. If you have access to a mex compiler (with openMP), this part of the code can be easily parallelised (in the MATLAB version) by uncommenting the lines 22, 282-284 and 289. To compile the code with openMP use the mex compiler with the following flags.
# From within the matlab subdirectory
mex CFLAGS='-O2 -fPIC -fopenmp' LDFLAGS='-fopenmp' fastwht.cpp ../hadamard.cpp
The project is published under GNU General Public License version 3.
For any questions concerning the code, please contact Vegard Antun at [email protected]