Skip to content

HTTPS clone URL

Subversion checkout URL

You can clone with HTTPS or Subversion.

Download ZIP
Ruby wrapper around the FFTW library for performing Fast Fourier Transforms
branch: master

This branch is even with mgomes:master

Fetching latest commit…

Cannot retrieve the latest commit at this time

Failed to load latest commit information.
doc
test
.gitignore
History.md
Makefile
README.rdoc
ToDo
extconf.rb
na_fftw3.c
na_fftw3.o

README.rdoc

module NumRu::FFTW3

Fast Fourier Transforms by using ((<FFTW|URL:www.fftw.org>)) Ver.3.

Takeshi Horinouchi

(C) Takeshi Horinouchi / GFD Dennou Club, 2003

NO WARRANTY

Features

Features yet to be introduced

  • Sine / cosine transforms

  • User choice of optimization levels (i.e., FFTW_MEASURE etc in addition to FFTW_ESTIMATE).

  • Multi-threaded FFT3 support – don't know whether it's really feasible.

Installation

  • Install ((<FFTW|URL:www.fftw.org>)) Ver.3.

    • NOTE: To activate the single-float transform, you have to install FFTW3 with the single-float compilation, in addition to the default double-float version. This can be done by configuring FFTW3 with the –enable-float option, and install it again. The single-float version will coexist with the double-float version. If you do not install the single-float version, FFT is always done with the double precision, which is not bad if you are not time- and memory-conscious.

  • Install ((<NArray|URL:www.ruby-lang.org/en/raa-list.rhtml?name=NArray>)).

  • Then, install this library as follows (replace “version” with the actual version number):

    % tar xvzf fftw3-version.tar.gz
    % cd fftw3-version
    % ruby extconf.rb
    % make
    % make site-install

    Or

    % make install

    (If you are using Ruby 1.8, make install is the same make site-install.)

How to use

See the following peice of code. (Install this library and copy and paste the following to the interactive shell irb).

require "narray"
require "numru/fftw3"
include NumRu

na = NArray.float(8,6)   # float -> will be corced to complex
na[1,1]=1

# <example 1>
fc = FFTW3.fft(na, -1)/na.length  # forward 2D FFT and normalization
nc = FFTW3.fft(fc, 1)       # backward 2D FFT (complex) --> 
nb = nc.real                # should be equal to na except round errors  

# <example 2>
fc = FFTW3.fft(na, -1, 0) / na.shape[0]  # forward FFT with the first dim

# <example 3>
fc = FFTW3.fft(na, -1, 1) / na.shape[1]  # forward FFT with the second dim

API Reference

Module methods

—fft(narray, dir [,dim,dim,…])

Complex FFT.

The 3rd, 4th,... arguments are optional.

ARGUMENTS
* narray (NArray or NArray-compatible Array) : array to be
  transformed. If real, coerced to complex before transformation.
  If narray is single-precision and the single-precision
  version of FFTW3 is installed (before installing this module),
  this method does a single-precision transform. 
  Otherwise, a double-precision transform is used.
* dir (-1 or 1) : forward transform if -1; backward transform if 1.
* optional 3rd, 4th,... arguments (Integer) : Specifies dimensions 
  to apply FFT. For example, if 0, the first dimension is
  transformed (1D FFT); If -1, the last dimension is used (1D FFT);
  If 0,2,4, the first, third, and fifth dimensions
  are transformed (3D FFT); If entirely omitted, ALL DIMENSIONS
  ARE SUBJECT TO FFT, so 3D FFT is done with a 3D array.

RETURN VALUE
* a complex NArray

NOTE
* As in FFTW, return value is NOT normalized. Thus, a consecutive
  forward and backward transform would multiply the size of
  data used for transform. You can normalize, for example,
  the forward transform FFTW.fft(narray, -1, 0, 1)
  (FFT regarding the first (dim 0) & second (dim 1) dimensions) by
  dividing with (narray.shape[0]*narray.shape[1]). Likewise,
  the result of FFTW.fft(narray, -1) (FFT for all dimensions)
  can be normalized by narray.length.
Something went wrong with that request. Please try again.