Python interface to the FFTW library
Project description
Compute fast Fourier transforms in Python.
Example
The following code snippet shows how to compute the forward Fourier transform of an arbitrary array of 64 samples:
>>> from fftw.fftw import Plan >>> import numpy >>> input_array = numpy.arange(64, dtype=numpy.complex) >>> plan = Plan(input_array, output_array=numpy.empty_like(input_array)) >>> result_array = plan() >>> print(input_array) [ 0.+0.j 1.+0.j 2.+0.j 3.+0.j 4.+0.j 5.+0.j 6.+0.j 7.+0.j 8.+0.j 9.+0.j 10.+0.j 11.+0.j 12.+0.j 13.+0.j 14.+0.j 15.+0.j 16.+0.j 17.+0.j 18.+0.j 19.+0.j 20.+0.j 21.+0.j 22.+0.j 23.+0.j 24.+0.j 25.+0.j 26.+0.j 27.+0.j 28.+0.j 29.+0.j 30.+0.j 31.+0.j 32.+0.j 33.+0.j 34.+0.j 35.+0.j 36.+0.j 37.+0.j 38.+0.j 39.+0.j 40.+0.j 41.+0.j 42.+0.j 43.+0.j 44.+0.j 45.+0.j 46.+0.j 47.+0.j 48.+0.j 49.+0.j 50.+0.j 51.+0.j 52.+0.j 53.+0.j 54.+0.j 55.+0.j 56.+0.j 57.+0.j 58.+0.j 59.+0.j 60.+0.j 61.+0.j 62.+0.j 63.+0.j] >>> print(result_array) [ 2016. +0.j -32.+651.374964j -32.+324.9014524j -32.+215.72647697j -32.+160.87486375j -32.+127.75116108j -32.+105.48986269j -32. +89.43400872j -32. +77.254834j -32. +67.65831544j -32. +59.86778918j -32. +53.38877458j -32. +47.89138441j -32. +43.14700523j -32. +38.99211282j -32. +35.30655922j -32. +32.j -32. +29.00310941j -32. +26.26172131j -32. +23.73281748j -32. +21.38171641j -32. +19.18006188j -32. +17.10435635j -32. +15.13487283j -32. +13.254834j -32. +11.44978308j -32. +9.70709388j -32. +8.01558273j -32. +6.36519576j -32. +4.7467516j -32. +3.15172491j -32. +1.57205919j -32. +0.j -32. -1.57205919j -32. -3.15172491j -32. -4.7467516j -32. -6.36519576j -32. -8.01558273j -32. -9.70709388j -32. -11.44978308j -32. -13.254834j -32. -15.13487283j -32. -17.10435635j -32. -19.18006188j -32. -21.38171641j -32. -23.73281748j -32. -26.26172131j -32. -29.00310941j -32. -32.j -32. -35.30655922j -32. -38.99211282j -32. -43.14700523j -32. -47.89138441j -32. -53.38877458j -32. -59.86778918j -32. -67.65831544j -32. -77.254834j -32. -89.43400872j -32.-105.48986269j -32.-127.75116108j -32.-160.87486375j -32.-215.72647697j -32.-324.9014524j -32.-651.374964j ]
Installation
Requirements
The following dependencies are required to build, run and test the package:
setuptools
pkgconfig
numpy
cffi
nose
An installation of the FFTW library is required. It should be discoverable with a call to pkg-config:
$ pkg-config --libs fftw3
Local or non-system installation locations are supported using PKG_CONFIG_PATH:
$ export PKG_CONFIG_PATH=$HOME/local/lib/pkgconfig $ pkg-config --libs fftw3
Using pip
The recommended way to install the package is via pip:
$ pip install fftw-cffi
Using setup.py
This method is suitable for environments where pip is not available, or for testing modifications to the package:
$ python setup.py install
Contributing
Guidelines
The development team welcomes feedback, code and enhancement proposals to the package from the community. Please consider opening an issue or submitting patches for inclusion to the code base via pull-request. For code contributions, please provide appropriate test cases for each new features and verify that the complete test suite runs successfully.
Running the tests
If the bindings were modified, then one should first rebuild the CFFI module with:
$ python setup.py build_ext --inplace
Before running the test suite with a call to:
$ python setup.py nosetests
License
The fftw-cffi source code is released under the terms of the new BSD license. The copyright information can be checked out in the accompanying LICENSE file.
A separate installation of the FFTW library is required. The source code can be downloaded from the official homepage and installed following the instructions available in the corresponding README file. The FFTW library is licensed under the GPL version 2 or later.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
