fftw.jl-7a1cc6ca-52ef-59f5-83cd-3a7055c09341
Last mirrored from https://github.com/JuliaMath/FFTW.jl.git on 2019-11-18T21:22:49.968-05:00 by @UnofficialJuliaMirrorBot via Travis job 481.12 , triggered by Travis cron job on branch "master"
https://github.com/unofficialjuliamirror/fftw.jl-7a1cc6ca-52ef-59f5-83cd-3a7055c09341
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
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○.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary
Repository
Last mirrored from https://github.com/JuliaMath/FFTW.jl.git on 2019-11-18T21:22:49.968-05:00 by @UnofficialJuliaMirrorBot via Travis job 481.12 , triggered by Travis cron job on branch "master"
Basic Info
- Host: GitHub
- Owner: UnofficialJuliaMirror
- License: mit
- Language: Julia
- Default Branch: master
- Size: 348 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
FFTW.jl
This package provides Julia bindings to the FFTW library for fast Fourier transforms (FFTs), as well as functionality useful for signal processing. These functions were formerly a part of Base Julia.
Usage and documentation
julia
]add FFTW
using FFTW
fft([0; 1; 2; 1])
returns
4-element Array{Complex{Float64},1}:
4.0 + 0.0im
-2.0 + 0.0im
0.0 + 0.0im
-2.0 + 0.0im
The documentation of generic FFT functionality can be found in the AbstractFFTs.jl package. Additional functionalities supported by the FFTW library are documented in the present package.
MKL
Alternatively, the FFTs in Intel's Math Kernel Library (MKL) can be used
by setting an environment variable JULIA_FFTW_PROVIDER to MKL and running
Pkg.build("FFTW"). If Julia was built with MKL, then Julia's MKL will be
used for FFTs; otherwise the Conda.jl package
will be used to download MKL via the mkl_fft Anaconda package.
Setting this environment variable only needs to be done for the first build of the package;
after that, the package will remember to use MKL when building and updating.
Note however that MKL provides only a subset of the functionality provided by FFTW. See
Intel's documentation
for more information about potential differences or gaps in functionality.
License
The FFTW library will be downloaded on versions of Julia where it is no longer distributed as part of Julia. Note that FFTW is licensed under GPLv2 or higher (see its license file), but the bindings to the library in this package, FFTW.jl, are licensed under MIT. This means that code using the FFTW library via the FFTW.jl bindings is subject to FFTW's licensing terms. Code using alternative implementations of the FFTW API, such as MKL's FFTW3 interface are instead subject to the alternative's license. If you distribute a derived or combined work, i.e. a program that links to and is distributed with the FFTW library, then that distribution falls under the terms of the GPL. If you just distribute source code that links to FFTW.jl, and users have to download FFTW or MKL to provide the backend, then the GPL probably doesn't have much effect on you.
Owner
- Name: Unofficial Julia Mirror
- Login: UnofficialJuliaMirror
- Kind: organization
- Website: https://github.com/UnofficialJuliaMirror/MirrorUpdater.jl
- Repositories: 3
- Profile: https://github.com/UnofficialJuliaMirror
Mirror of all registered Julia packages. Updated weekly by @UnofficialJuliaMirrorBot. See also: @UnofficialJuliaMirrorSnapshots.
Citation (CITATION.bib)
% If you wish to cite FFTW in a general publication, we recommend this paper:
@Article{FFTW.jl-2005,
author = {Frigo, Matteo and Johnson, Steven~G.},
title = {The Design and Implementation of {FFTW3}},
journal = {Proceedings of the IEEE},
year = 2005,
volume = 93,
number = 2,
pages = {216--231},
note = {Special issue on ``Program Generation, Optimization, and Platform Adaptation''},
doi = {10.1109/JPROC.2004.840301}
}