fftwtools/0000755000176200001440000000000014017172673012311 5ustar liggesusersfftwtools/NAMESPACE0000644000176200001440000000035614014563614013530 0ustar liggesusers#exportPattern("^[^\\.]") export( fftw, fftw2d, fftw3d, fftw_c2c, fftw_c2c_2d, fftw_c2c_3d, fftw_c2c_xd, fftw_c2r, fftw_r2c, fftw_r2c_2d, fftw_r2c_3d, mvfftw, mvfftw_c2c, mvfftw_c2r, mvfftw_r2c) useDynLib(fftwtools, .registration = TRUE) fftwtools/man/0000755000176200001440000000000014014563614013060 5ustar liggesusersfftwtools/man/mvfftw.Rd0000644000176200001440000000711012121155253014650 0ustar liggesusers% The fftwtools R package % fftw2d and general mvfftw tools in R % Copyright (C) 2013 Karim Rahim % % Written by Karim Rahim. % % This file is part of the fftwtools package for R. % % The fftwtools package is free software: you can redistribute it and % or modify it under the terms of the GNU General Public License as % published by the Free Software Foundation, either version 2 of the % License, or any later version. % % The fftwtools package is distributed in the hope that it will be % useful, but WITHOUT ANY WARRANTY; without even the implied warranty % of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with fftwtools. If not, see . % % If you wish to report bugs please contact the author. % karim.rahim@gmail.com % Jeffery Hall, Queen's University, Kingston Ontario % Canada, K7L 3N6 \name{mvfftw} \alias{mvfftw} \alias{mvfftw_c2c} \alias{mvfftw_r2c} \alias{mvfftw_c2r} \title{Compute the FFT on each column of a matrix using FFTW3} \description{ This will compute the FFT of each column of a matrix using the FFTW3 libraries. Use mvfftw_r2c(x, HermConj=0) for real to complex fft. This will return the result without the redundant complex conjugate. This follows the R convention for returning the unscaled inverse of the FFT. The function mvfftw_c2r(res, HermConj=0, n=dim(x)[1]) will invert the FFT from the result not containing the "Hermitian" redundant conjugate. You must specify, n, the column dimension of the original data--the column length of the original data--if the redundant complex conjugate is not included. } \usage{ mvfftw(data, inverse=0, HermConj=1, n=NULL, fftplanopt=0) mvfftw(data, inverse=0, HermConj=1, n=NULL, fftplanopt=0) mvfftw_r2c(data, HermConj=1, fftplanopt=0) mvfftw_c2c(data, inverse=0, fftplanopt=0) mvfftw_c2r(data, HermConj=1, n=NULL, fftplanopt=0) } \arguments{ \item{data}{(complex or real) matrix of columns to be processed} \item{inverse}{(integer) 1 or 0 indicating if inverse fft is preformed. The return follows the format of the R FFT commands. The result is not scaled.} \item{HermConj}{(integer) 1 or 0 indicating if either "Hermitian" redundant conjugate should be returned, or that the complex to real data includes the "Hermitian" redundant conjugate.} \item{n}{(integer) column length of the original data set, when using the inverse coplex to real fft without providing the "Hermitian" redundant conjugate.} \item{fftplanopt}{(integer) 0 or 1 specifying the flag passed to FFTW. 0 indicates the flag FFTW_ESTIMATE is used, and 1 indicates FFTW_MEASURE is used. See FFTW documentation for use of these flags. } } \author{Karim Rahim} \examples{ x=c(1, 2, 3, 9, 8, 5, 1, 2, 9, 8, 7, 2) x= t(matrix(x, nrow=4)) mvfft(x) t(mvfft(t(mvfft(x)))) res <- mvfftw_r2c(x, HermConj=1) res mvfftw_c2c(res, inverse=1)/3 mvfftw_c2r(res)/3 res <- mvfftw_r2c(x, HermConj=0) res mvfftw_c2r(res, HermConj=0, n=3)/3 mvfftw_r2c(x, HermConj=1) mvfft(x) res <- mvfftw_r2c(x, HermConj=0) res mvfftw_c2r(res, HermConj=0, n=3)/3 res <- mvfftw_r2c(t(x), HermConj=1) res mvfftw_c2r(res, HermConj=1)/4 res <- mvfftw_r2c(t(x), HermConj=0) res mvfftw_c2r(res, HermConj=0, n=4)/4 mvfftw_r2c(t(x), HermConj=1) mvfft(t(x)) mvfftw(mvfftw(x, HermConj=0), inverse=1, HermConj=0, n=3)/3 mvfftw(mvfftw(t(x), HermConj=0), inverse=1, HermConj=0, n=4)/4 mvfftw(mvfftw(t(x), inverse=1))/4 } \keyword{fftw} fftwtools/man/fftw3d.Rd0000644000176200001440000000432214014563614014545 0ustar liggesusers% The fftwtools R package % fftw2d and general mvfftw tools in R % Copyright (C) 2013 Karim Rahim % % Written by Karim Rahim. % % This file is part of the fftwtools package for R. % % The fftwtools package is free software: you can redistribute it and % or modify it under the terms of the GNU General Public License as % published by the Free Software Foundation, either version 2 of the % License, or any later version. % % The fftwtools package is distributed in the hope that it will be % useful, but WITHOUT ANY WARRANTY; without even the implied warranty % of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with fftwtools. If not, see . % % If you wish to report bugs please contact the author. % karim.rahim@gmail.com % Jeffery Hall, Queen's University, Kingston Ontario % Canada, K7L 3N6 \name{fftw3d} \alias{fftw3d} \alias{fftw_c2c_3d} \alias{fftw_r2c_3d} \title{Compute a two-dimensional FFT on a matrix using FFTW3} \description{ Computes three-dimensional FFT on an array using the FFTW3 libraries. Use fftw_r2c_3d(x, HermConj=0) for real to complex FFT. This will return the result without the "Hermitian" redundancy. These functions follow the R convention when returning the inverse of the FFT. For the two-dimension fft, the inverse is currently requires the entire matrix, including the redundant complex conjugate. } \usage{ fftw3d(data, inverse=0, HermConj=1) fftw_r2c_3d(data, HermConj=1) fftw_c2c_3d(data, inverse=0) } \arguments{ \item{data}{(complex or real) 3-dimensional array to be processed} \item{inverse}{(integer) 1 or 0 indicating if inverse FFT is preformed. The return follows the format of the R FFT commands--the output is not scaled.} \item{HermConj}{(integer) 1 or 0 indicating if either "Hermitian" redundant conjugate should be returned.} } \author{Karim Rahim} \examples{ x=c(1, 2, 3, 9, 8, 5, 1, 2, 9, 8, 7, 2) x= array(x, dim=c(3,2,2)) fftw3d(x) fftw3d(x, HermConj=0) fftw3d(fftw3d(x), inverse=1)/12 fftw_r2c_3d(x) fftw_r2c_3d(x, HermConj=0) } \keyword{fftw} fftwtools/man/fftw2d.Rd0000644000176200001440000000477113736207504014557 0ustar liggesusers% The fftwtools R package % fftw2d and general mvfftw tools in R % Copyright (C) 2013 Karim Rahim % % Written by Karim Rahim. % % This file is part of the fftwtools package for R. % % The fftwtools package is free software: you can redistribute it and % or modify it under the terms of the GNU General Public License as % published by the Free Software Foundation, either version 2 of the % License, or any later version. % % The fftwtools package is distributed in the hope that it will be % useful, but WITHOUT ANY WARRANTY; without even the implied warranty % of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with fftwtools. If not, see . % % If you wish to report bugs please contact the author. % karim.rahim@gmail.com % Jeffery Hall, Queen's University, Kingston Ontario % Canada, K7L 3N6 \name{fftw2d} \alias{fftw2d} \alias{fftw_c2c_2d} \alias{fftw_r2c_2d} \alias{fftw_c2c_xd} \title{Compute a two-dimensional FFT on a matrix using FFTW3} \description{ Computes two-dimensional FFT on a matrix using the FFTW3 libraries. Use fftw_r2c_2d(x, HermConj=0) for real to complex FFT. This will return the result without the "Hermitian" redundancy. These functions follow the R convention when returning the inverse of the FFT. For the two-dimension fft, the inverse is currently requires the entire matrix, including the redundant complex conjugate. The function \code{fftw_c2c_xd} can calculate a higher dimensional FFT on a higher dimensional array. } \usage{ fftw2d(data, inverse=0, HermConj=1) fftw_r2c_2d(data, HermConj=1) fftw_c2c_2d(data, inverse=0) fftw_c2c_xd(data, inverse=0) } \arguments{ \item{data}{(complex or real) matrix to be processed (or array for \code{fftw_c2c_xd})} \item{inverse}{(integer) 1 or 0 indicating if inverse FFT is preformed. The return follows the format of the R FFT commands--the output is not scaled.} \item{HermConj}{(integer) 1 or 0 indicating if either "Hermitian" redundant conjugate should be returned.} } \author{Karim Rahim and Ege Rubak} \examples{ x=c(1, 2, 3, 9, 8, 5, 1, 2, 9, 8, 7, 2) x= t(matrix(x, nrow=4)) mvfft(x) t(mvfft(t(mvfft(x)))) fftw2d(x) fftw2d(x, HermConj=0) fftw2d(fftw2d(x), inverse=1)/12 fftw2d(fftw2d(t(x)), inverse=1)/12 fftw_r2c_2d(x) fftw_r2c_2d(x, HermConj=0) fftw_c2c_xd(x) } \keyword{fftw} fftwtools/man/fftw.Rd0000644000176200001440000000605312121155144014311 0ustar liggesusers% The fftwtools R package % fftw2d and general mvfftw tools in R % Copyright (C) 2013 Karim Rahim % % Written by Karim Rahim. % % This file is part of the fftwtools package for R. % % The fftwtools package is free software: you can redistribute it and % or modify it under the terms of the GNU General Public License as % published by the Free Software Foundation, either version 2 of the % License, or any later version. % % The fftwtools package is distributed in the hope that it will be % useful, but WITHOUT ANY WARRANTY; without even the implied warranty % of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with fftwtools. If not, see . % % If you wish to report bugs please contact the author. % karim.rahim@gmail.com % Jeffery Hall, Queen's University, Kingston Ontario % Canada, K7L 3N6 \name{fftw} \alias{fftw} \alias{fftw_c2c} \alias{fftw_r2c} \alias{fftw_c2r} \title{Compute fft using fftw3} \description{ These functions compute the FFT using the FFTW3 libraries. Use fftw_r2c(x, HermConj=0) for real to complex fft. This will return the result without the redundant complex conjugate. This follows the R convention for returning the unscaled inverse of the FFT. The function fftw_c2r(res, HermConj=0, n=length(x)) will invert the FFT from the result not containing the redundant complex conjugate. You must specify, n, the dimension of the original data--length--if the redundant complex conjugate is not included. } \usage{ fftw(data, inverse=0, HermConj=1, n=NULL) fftw(data, inverse=0, HermConj=1, n=NULL) fftw_r2c(data, HermConj=1) fftw_c2c(data, inverse=0) fftw_c2r(data, HermConj=1, n=NULL) } \arguments{ \item{data}{(complex or real) vector to be processed} \item{inverse}{(integer) 1 or 0 indicating if inverse FFT is preformed. The return follows the format of the R FFT commands--the output is not scaled.} \item{HermConj}{(integer) 1 or 0 indicating if either "Hermitian" redundant conjugate should be returned, or that the complex to real data includes the "Hermitian" redundant conjugate.} \item{n}{(integer) column length of the original data set. This is required when using the inverse complex to real FFT without providing the "Hermitian" redundant conjugate.} } \author{Karim Rahim} \examples{ res <- fftw_r2c(1:9) res fftw_c2r(res)/9 res fftw_c2r(res)/9 res <- fftw_r2c(1:10) res fftw_c2r(res)/10 res fftw_c2r(res)/10 res <- fftw_r2c(1:9, HermConj=0) res fftw_c2r(res, HermConj=0, n=9)/9 res <- fftw_r2c(1:10, HermConj=0) res fftw_c2r(res, HermConj=0, n=10)/10 fftw_r2c(1:3) fftw_c2r(fftw_r2c(1:3))/3 fftw_c2r(fftw_r2c(1:2))/2 fftw_c2r(fftw_r2c(1:4))/4 fftw_r2c(1:3, HermConj=1) fftw_c2r(fftw_r2c(1:3, HermConj=0), HermConj=0, n=3)/3 fftw_c2r(fftw_r2c(1:4, HermConj=0), HermConj=0, n=4)/4 fftw_c2r(fftw_r2c(1:20, HermConj=0), HermConj=0, n=20)/20 } \keyword{fftw} fftwtools/DESCRIPTION0000644000176200001440000000202614017172673014017 0ustar liggesusersPackage: fftwtools Version: 0.9-11 Title: Wrapper for 'FFTW3' Includes: One-Dimensional, Two-Dimensional, Three-Dimensional, and Multivariate Transforms Author: Karim Rahim Maintainer: Karim Rahim Depends: R (>= 3.0) SystemRequirements: fftw3 (libfftw3-dev (deb), or fftw-devel (rpm)) Suggests: fftw Description: Provides a wrapper for several 'FFTW' functions. This package provides access to the two-dimensional 'FFT', the multivariate 'FFT', and the one-dimensional real to complex 'FFT' using the 'FFTW3' library. The package includes the functions fftw() and mvfftw() which are designed to mimic the functionality of the R functions fft() and mvfft(). The 'FFT' functions have a parameter that allows them to not return the redundant complex conjugate when the input is real data. License: GPL (>= 2) ByteCompile: true URL: https://github.com/krahim/fftwtools NeedsCompilation: yes Packaged: 2021-02-27 23:01:27 UTC; karim Repository: CRAN Date/Publication: 2021-03-01 14:10:02 UTC fftwtools/build/0000755000176200001440000000000014016547507013411 5ustar liggesusersfftwtools/build/vignette.rds0000644000176200001440000000034414016547507015751 0ustar liggesusersQM @+K!譛!/] . ahyhޛ}=04=L6 CǮF ae'AkMS)">H Uk|ISF㲌/֌2jB 4_obc+b7as1aԗzj?TE o=05TըK$AZ!fftwtools/configure.ac0000644000176200001440000000246314016474006014576 0ustar liggesusers ## This file is part of fftwtools ## Note this file was copied from the file used in the R FFTW package ## As was the general build principle, and I am indebted to the authors of that ## package. ## ## Process this file with autoconf to produce a configure script. ## Rewritten 22 Feb 2021 by Dirk Eddelbuettel and released under GPL-2 or later AC_PREREQ(2.61) ## Update this version number along with DESCRIPTION AC_INIT([fftwtools], [0.9-11]) # Ensure C++ is set up as R expects : ${R_HOME=`R RHOME`} if test -z "${R_HOME}"; then AC_MSG_ERROR([Could not determine R_HOME.]) fi CC=`"${R_HOME}/bin/R" CMD config CC` CFLAGS=`"${R_HOME}/bin/R" CMD config CFLAGS` AC_REQUIRE_CPP AC_PROG_CC ## Check for pkg-config AC_DEFUN([AC_PROG_PKGCONFIG], [AC_CHECK_PROG(PKGCONFIG,pkg-config,yes)]) AC_PROG_PKGCONFIG ## Report failure if test x"${PKGCONFIG}" != x"yes"; then AC_MSG_ERROR([pkg-config not found.]) fi ## Determine values fftw3_cflags=`pkg-config --cflags fftw3` fftw3_libs=`pkg-config --libs fftw3` ## Substitute in, respected existing values AC_SUBST([PKG_CFLAGS],["${fftw3_cflags} ${PKG_CFLAGS}"]) AC_SUBST([PKG_LIBS],["${fftw3_libs} ${PKG_LIBS}"]) AC_CONFIG_FILES([src/Makevars]) AC_OUTPUT echo " ${PACKAGE_NAME} ${PACKAGE_VERSION} ================ compiler flags: ${PKG_CFLAGS} link argument: ${PKG_LIBS} " fftwtools/src/0000755000176200001440000000000014016547507013101 5ustar liggesusersfftwtools/src/fftwtools.h0000644000176200001440000000454014014563614015277 0ustar liggesusers/* ## The fftwtools R package */ /* ## fftw2d and general mvfftw tools in R */ /* ## Copyright (C) 2013 Karim Rahim */ /* ## This file is part of the fftwtools package for R. */ /* ## The fftwtools package is free software: you can redistribute it and */ /* ## /or modify */ /* ## it under the terms of the GNU General Public License as published by */ /* ## the Free Software Foundation, either version 2 of the License, or */ /* ## any later version. */ /* ## The fftwtools package is distributed in the hope that it will be */ /* ## useful, but WITHOUT ANY WARRANTY; without even the implied warranty */ /* ## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the */ /* ## GNU General Public License for more details. */ /* ## You should have received a copy of the GNU General Public License */ /* ## along with Foobar. If not, see . */ /* ## If you wish to report bugs please contact the author. */ /* ## karim.rahim@gmail.com */ /* ## Jeffery Hall, Queen's University, Kingston Ontario */ /* ## Canada, K7L 3N6 */ #ifndef __FFTWTOOLS_H__ #define __FFTWTOOLS_H__ /* real to complex forward */ void cfft_r2c(int* n, double* data, double complex* res, int* retHermConj); /* complex to real backward */ void cfft_c2r(int* n, double complex* data, double* res); /* complex to complex --eitherway */ void cfft_c2c(int* n, double complex* data, double complex* res, int* inverse); void cmvfft_r2c(int *n, int *m, double* data, double complex* res, int* fftwplanopt); void cmvfft_c2r(int *n, int *m, double complex* data, double* res, int* fftwplanopt); void cmvfft_c2c(int *n, int *m, double complex* data, double complex* res, int* inverse, int* fftwplanopt); void cfft_r2c_2d(int* nx, int* ny, double* data, double complex* res); void cfft_c2c_2d(int* nx, int* ny, double complex* data, double complex* res, int* inverse); void cfft_r2c_3d(int* nx, int* ny, int *nz, double* data, double complex* res); void cfft_c2c_3d(int* nx, int* ny, int *nz, double complex* data, double complex* res, int* inverse); void cfft_c2c_xd(int* r, int* n, double complex* data, double complex* res, int* inverse); #endif fftwtools/src/fftwtools.c0000644000176200001440000001305014014563614015266 0ustar liggesusers/* ## The fftwtools R package */ /* ## fftw2d and general mvfftw tools in R */ /* ## Copyright (C) 2013 Karim Rahim */ /* ## This file is part of the fftwtools package for R. */ /* ## The fftwtools package is free software: you can redistribute it and */ /* ## /or modify */ /* ## it under the terms of the GNU General Public License as published by */ /* ## the Free Software Foundation, either version 2 of the License, or */ /* ## any later version. */ /* ## The fftwtools package is distributed in the hope that it will be */ /* ## useful, but WITHOUT ANY WARRANTY; without even the implied warranty */ /* ## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the */ /* ## GNU General Public License for more details. */ /* ## You should have received a copy of the GNU General Public License */ /* ## along with Foobar. If not, see . */ /* ## If you wish to report bugs please contact the author. */ /* ## karim.rahim@gmail.com */ /* ## Jeffery Hall, Queen's University, Kingston Ontario */ /* ## Canada, K7L 3N6 */ #include #include #include"fftwtools.h" void cfft_r2c(int* n, double* data, double complex* res, int* retHermConj) { int i, nc = *n/2 +1; fftw_plan p; p = fftw_plan_dft_r2c_1d(*n, data, res, FFTW_ESTIMATE); fftw_execute(p); if(*retHermConj == 1) { for(i=nc; i < *n; i++) { res[i] = conj(res[*n - i]); } } fftw_destroy_plan(p); } void cfft_c2r(int* n, double complex* data, double* res) { fftw_plan p; p = fftw_plan_dft_c2r_1d(*n, data, res, FFTW_ESTIMATE); fftw_execute(p); fftw_destroy_plan(p); } void cfft_c2c(int* n, double complex* data, double complex* res, int* inverse) { int sign; fftw_plan p; if(*inverse == 1) { sign = FFTW_BACKWARD; } else { sign = FFTW_FORWARD; } p = fftw_plan_dft_1d(*n, data, res, sign, FFTW_ESTIMATE); fftw_execute(p); fftw_destroy_plan(p); } void cmvfft_r2c(int *n, int *m, double* data, double complex* res, int* fftwplanopt) { int nc = *n/2 +1; fftw_plan p; if(*fftwplanopt == 1 ) { *fftwplanopt = FFTW_MEASURE; } else { *fftwplanopt = FFTW_ESTIMATE; } p = fftw_plan_many_dft_r2c(1, n, *m, data, NULL, 1, *n, res, NULL, 1, nc, *fftwplanopt); fftw_execute(p); fftw_destroy_plan(p); } void cmvfft_c2r(int *n, int *m, double complex* data, double* res, int* fftwplanopt) { int nc = *n/2 +1; fftw_plan p; if(*fftwplanopt == 1 ) { *fftwplanopt = FFTW_MEASURE; } else { *fftwplanopt = FFTW_ESTIMATE; } p = fftw_plan_many_dft_c2r(1, n, *m, data, NULL, 1, nc, res, NULL, 1, *n, *fftwplanopt); fftw_execute(p); fftw_destroy_plan(p); } void cmvfft_c2c(int *n, int *m, double complex* data, double complex* res, int* inverse, int* fftwplanopt) { int sign; fftw_plan p; if(*fftwplanopt == 1 ) { *fftwplanopt = FFTW_MEASURE; } else { *fftwplanopt = FFTW_ESTIMATE; } if(*inverse == 1) { sign = FFTW_BACKWARD; } else { sign = FFTW_FORWARD; } p = fftw_plan_many_dft(1, n, *m, data, NULL, 1, *n, res, NULL, 1, *n, sign, *fftwplanopt); fftw_execute(p); fftw_destroy_plan(p); } void cfft_r2c_2d(int* nx, int* ny, double* data, double complex* res) { fftw_plan p; p = fftw_plan_dft_r2c_2d(*nx, *ny, data, res, FFTW_ESTIMATE); fftw_execute(p); fftw_destroy_plan(p); } void cfft_c2c_2d(int* nx, int* ny, double complex* data, double complex* res, int* inverse) { int sign; fftw_plan p; if(*inverse == 1) { sign = FFTW_BACKWARD; } else { sign = FFTW_FORWARD; } p = fftw_plan_dft_2d(*nx, *ny, data, res, sign, FFTW_ESTIMATE); fftw_execute(p); fftw_destroy_plan(p); } void cfft_r2c_3d(int* nx, int* ny, int *nz, double* data, double complex* res) { fftw_plan p; p = fftw_plan_dft_r2c_3d(*nx, *ny, *nz, data, res, FFTW_ESTIMATE); fftw_execute(p); fftw_destroy_plan(p); } void cfft_c2c_3d(int* nx, int* ny, int *nz, double complex* data, double complex* res, int* inverse) { int sign; fftw_plan p; if(*inverse == 1) { sign = FFTW_BACKWARD; } else { sign = FFTW_FORWARD; } p = fftw_plan_dft_3d(*nx, *ny, *nz, data, res, sign, FFTW_ESTIMATE); fftw_execute(p); fftw_destroy_plan(p); } void cfft_c2c_xd(int* r, int* n, double complex* data, double complex* res, int* inverse) { int sign; fftw_plan p; if(*inverse == 1) { sign = FFTW_BACKWARD; } else { sign = FFTW_FORWARD; } p = fftw_plan_dft(*r, n, data, res, sign, FFTW_ESTIMATE); fftw_execute(p); fftw_destroy_plan(p); } fftwtools/src/fftwtools_init.c0000644000176200001440000000303214014563614016310 0ustar liggesusers#include // for NULL #include /* FIXME: Check these declarations against the C/Fortran source code. */ /* .C calls */ extern void cfft_c2c(void *, void *, void *, void *); extern void cfft_c2c_2d(void *, void *, void *, void *, void *); extern void cfft_c2c_3d(void *, void *, void *, void *, void *, void *); extern void cfft_c2c_xd(void *, void *, void *, void *, void *); extern void cfft_c2r(void *, void *, void *); extern void cfft_r2c(void *, void *, void *, void *); extern void cfft_r2c_2d(void *, void *, void *, void *); extern void cfft_r2c_3d(void *, void *, void *, void *, void *); extern void cmvfft_c2c(void *, void *, void *, void *, void *, void *); extern void cmvfft_c2r(void *, void *, void *, void *, void *); extern void cmvfft_r2c(void *, void *, void *, void *, void *); static const R_CMethodDef CEntries[] = { {"cfft_c2c", (DL_FUNC) &cfft_c2c, 4}, {"cfft_c2c_2d", (DL_FUNC) &cfft_c2c_2d, 5}, {"cfft_c2c_3d", (DL_FUNC) &cfft_c2c_3d, 6}, {"cfft_c2c_xd", (DL_FUNC) &cfft_c2c_xd, 5}, {"cfft_c2r", (DL_FUNC) &cfft_c2r, 3}, {"cfft_r2c", (DL_FUNC) &cfft_r2c, 4}, {"cfft_r2c_2d", (DL_FUNC) &cfft_r2c_2d, 4}, {"cfft_r2c_3d", (DL_FUNC) &cfft_r2c_3d, 5}, {"cmvfft_c2c", (DL_FUNC) &cmvfft_c2c, 6}, {"cmvfft_c2r", (DL_FUNC) &cmvfft_c2r, 5}, {"cmvfft_r2c", (DL_FUNC) &cmvfft_r2c, 5}, {NULL, NULL, 0} }; void R_init_fftwtools(DllInfo *dll) { R_registerRoutines(dll, CEntries, NULL, NULL, NULL); R_useDynamicSymbols(dll, FALSE); } fftwtools/src/Makevars.win0000644000176200001440000000072612301424616015364 0ustar liggesusers## This file is copied from the FFTW package and the build script is based ## on the one created by the authors of that package. ## ## Note added May 4, 2013 ## I found using win-builder.R-project.org, Uwe's setup, that this file was required for ## a build on windows. ## It is not required on my Linux machine. ## May 5th. I'm confused now as it appears this file is needed for building the package on Linux. PKG_CPPFLAGS= PKG_LIBS= -lfftw3 -lm all: $(SHLIB) fftwtools/src/Makevars.in0000644000176200001440000000071614016473715015205 0ustar liggesusers## This file is copied from the FFTW package and the build script is based ## on the one created by the authors of that package. ## ## Note added May 4, 2013 ## I found using win-builder.R-project.org, Uwe's setup, that this file was required for ## a build on windows. ## It is not required on my Linux machine. ## May 5th. I'm confused now as it appears this file is needed for building the package on Linux. PKG_CPPFLAGS=@PKG_CFLAGS@ PKG_LIBS=@PKG_LIBS@ fftwtools/vignettes/0000755000176200001440000000000014016547506014321 5ustar liggesusersfftwtools/vignettes/testTimeAndSimpleUse.bib0000644000176200001440000000051412141054533021035 0ustar liggesusers@Article{FFTW05, author = {Frigo, Matteo and Johnson, Steven~G.}, title = {The Design and Implementation of {FFTW3}}, journal = {Proceedings of the IEEE}, year = 2005, volume = 93, number = 2, pages = {216--231}, note = {Special issue on ``Program Generation, Optimization, and Platform Adaptation''} } fftwtools/vignettes/auto/0000755000176200001440000000000012141250557015263 5ustar liggesusersfftwtools/vignettes/auto/testTimeAndSimpleUse.el0000644000176200001440000000033212141250557021653 0ustar liggesusers(TeX-add-style-hook "testTimeAndSimpleUse" (lambda () (LaTeX-add-bibliographies) (TeX-run-style-hooks "inputenc" "utf8" "fullpage" "hyperref" "latex2e" "art10" "article"))) fftwtools/vignettes/testTimeAndSimpleUse.Rnw0000644000176200001440000001255212301441772021057 0ustar liggesusers\documentclass{article} \usepackage{hyperref} \usepackage{fullpage} %\usepackage{natbib} %\usepackage{graphics} %\usepackage{amsmath} %\usepackage{indentfirst} \usepackage[utf8]{inputenc} % \VignetteIndexEntry{ffttools example and simple use example} \begin{document} <>= options(keep.source = TRUE, width = 60) fftwtools1 <- packageDescription("fftwtools") @ \title{FFTWTOOLS Timing and Simple Use (Version \Sexpr{fftwtools1$Version})} \author{Karim J. Rahim} \maketitle \section{Overview} The package \texttt{fftwtool} provides a wrapper for \texttt{FFTW} code discussed in \cite{FFTW05}. This vignette provides example code for comparing execution times of \texttt{fftw} from the package \texttt{fftwtools} to the standard \texttt{R} \texttt{fft} function, and it demonstrates how to replace the \texttt{R} function \texttt{fft} with \texttt{fftw}. The functions \texttt{fftw} and \texttt{mvfftw} mimic the behaviour of the \texttt{R} functions \texttt{fft} and \texttt{mvfft}. There is an \texttt{R} package called \texttt{FFTW} which offers different functionality than fftwtools, specifically it allows the user to set \emph{plans}, and improve the speed with multiple calls to \texttt{fftw} when using data sets of the same size, see \cite{FFTW05}. \section{Timing Example} We begin with a demonstration of the speed difference between a simple call to \texttt{fftw} and the default \texttt{fft} function. The performance improvement is visible with large data sets. Using the example below with $2^{20},$ over one million, data points I observed the following execution times: \begin{itemize} \item \texttt{R}'s \texttt{fft}: 19.069 seconds \item \texttt{fftw} default call: 8.804 seconds \item \texttt{fftw} with \texttt{HermConj} set to \texttt{FALSE}: 7.594 seconds. \end{itemize} You can test timing at any size and decide which function to use. As the speed advantage from the use of the package \texttt{fftw} is only seen in large examples, I currently use the \texttt{R} \texttt{fft} functions, and I change to \texttt{fftw} only when I encounter significantly large data sets and speed becomes a concern. To reduce the check and install times of this package, I reduced \texttt{fftLength} from $2^{20}$ to $2^8$ in the code shown in this vignette. The standard \texttt{R} routine is faster using this number of samples, but it is \emph{not} faster with very large data sets. To compare times, first we look at the time required for the default \texttt{R} \texttt{fft} routine. <>= library("fftwtools") ## We increment by powers of 2, but one can use other incrementes ## We choose fftlength = 2^20, but ## **this was reduced to 2^8 for the vignette distribution.** fftLength <- 2^8 set.seed(10) g <- rnorm(fftLength) ##Start the clock ptm <- proc.time() ## Loop through for (i in 1:100){ fft(g) } ## Stop the clock proc.time() - ptm @ Next we look at replacing \texttt{fft} with \texttt{fftw} without any other changes. <<>= ##timing # Start the clock! ptm <- proc.time() # Loop through for (i in 1:100){ fftw(g) } # Stop the clock proc.time() - ptm @ Finally we look to see how much additional improvement can by had by not returning the complex conjugate which is not required for real data. It is likely this speed up is partially due to decreased memory allocation. <<>= ## Start the clock! ptm <- proc.time() ## Loop through for (i in 1:100){ fftw(g, HermConj=FALSE) } ## Stop the clock proc.time() - ptm @ \section{Replace R's \texttt{fft} call with \texttt{fftw}} The following is a quick and dirty way to replace \texttt{fftw} with \texttt{fftw} in existing code. It is more appropriate to use a conditional statement in the replacement functions to call \texttt{fftw} and \texttt{mvfftw} when the length of $z$ is appropriately large. <>= ## basic option ot overwrite calls fft <- function(z, inverse = FALSE) { fftwtools::fftw(z, inverse=inverse) } mvfft <- function(z, inverse=FALSE) { fftwtools::mvfftw(z, invese=inverse) } @ The above is a simple method of replacing all \texttt{fft} calls with \texttt{fftw} calls in the \texttt{multitaper} package which I maintain. If you are interested in the additional improvement available from not returning the unnecessary complex conjugate when using real data, you can overwrite the call setting \texttt{HermConj} to \texttt{FALSE}. <<>= fft <- function(z, inverse = FALSE) { fftwtools::fftw(z, inverse=inverse, HermConj=FALSE) } @ The last method is only valid when the input is not complex, and it may break certain calls depending on when the complex conjugate is discarded. If you discard the complex conjugate, you will need the length of the original data to perform an inverse Fourier transform. If you are using the latter method then it may be wise to look into further functionality provided in the \texttt{R} packages \texttt{FFTW} and \texttt{fftwtools}. \subsection{Clean up} If you replace the \texttt{R}'s call to \texttt{fft} with \texttt{fftw} then it is good practice to clean up the replacement and restore calls to \texttt{fft} and \texttt{mvfft} to the standard \texttt{R} routine when you are finished using \texttt{fftw}. The following code shows how this cleanup is performed. <>= rm(fft, mvfft) @ \bibliographystyle{plain} \bibliography{testTimeAndSimpleUse} \end{document} fftwtools/R/0000755000176200001440000000000014014563614012506 5ustar liggesusersfftwtools/R/fftwtools.R0000644000176200001440000002245614014563614014671 0ustar liggesusers## The fftwtools R package ## fftw2d and general mvfftw tools in R ## Copyright (C) 2013 Karim Rahim ## This file is part of the fftwtools package for R. ## The fftwtools package is free software: you can redistribute it and ## /or modify ## it under the terms of the GNU General Public License as published by ## the Free Software Foundation, either version 2 of the License, or ## any later version. ## The fftwtools package is distributed in the hope that it will be ## useful, but WITHOUT ANY WARRANTY; without even the implied warranty ## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ## GNU General Public License for more details. ## You should have received a copy of the GNU General Public License ## along with Foobar. If not, see . ## If you wish to report bugs please contact the author. ## karim.rahim@gmail.com ## Jeffery Hall, Queen's University, Kingston Ontario ## Canada, K7L 3N6 ##generic function to call fftw3 ## we recommend the FFTW library for setting the plan fftw <- function(data, inverse=0, HermConj=1, n=NULL) { res <- NULL if(inverse==0) { if(!is.complex(data)) { res <- fftw_r2c(data, HermConj=HermConj) } else { res <- fftw_c2c(data, inverse=0) } } else { if(HermConj==0 && is.complex(data) && is.numeric(n)) { res <- fftw_c2r(data, HermConj=HermConj, n=n) } else{ res <- fftw_c2c(data, inverse=1) } } return(res) } ##generic 2d fft fftw2d <- function(data, inverse=0, HermConj=1) { res <- NULL if(inverse==0) { if(!is.complex(data)) { res <- fftw_r2c_2d(data, HermConj=HermConj) } else { res <- fftw_c2c_2d(data, inverse=0) } } else { res <- fftw_c2c_2d(data, inverse=1) } return(res) } ##generic 3d fft fftw3d <- function(data, inverse=0, HermConj=1) { res <- NULL if(inverse==0) { if(!is.complex(data)) { res <- fftw_r2c_3d(data, HermConj=HermConj) } else { res <- fftw_c2c_3d(data, inverse=0) } } else { res <- fftw_c2c_3d(data, inverse=1) } return(res) } ##generic function to call multicol fftw3 mvfftw <- function(data, inverse=0, HermConj=1, n=NULL, fftplanopt=0) { res <- NULL if(inverse==0) { if(!is.complex(data)) { res <- mvfftw_r2c(data, HermConj=HermConj, fftplanopt=fftplanopt) } else { res <- mvfftw_c2c(data, inverse=0, fftplanopt=fftplanopt) } } else { if(HermConj==0 && is.complex(data) && is.numeric(n)) { res <- mvfftw_c2r(data, HermConj=HermConj, n=n, fftplanopt=fftplanopt) } else { res <- mvfftw_c2c(data, inverse=1, fftplanopt=fftplanopt) } } return(res) } fftw_r2c <- function(data, HermConj=1) { n <- length(data) nc <- NULL if(HermConj ==1) { nc <- n } else { nc <- as.integer(n/2) +1 } out <- .C("cfft_r2c", as.integer(n), as.double(data), res=complex(nc), as.integer(HermConj), PACKAGE="fftwtools") return(out$res) } fftw_c2r <- function(data, HermConj=1, n=NULL) { ##when HermConj == 0, we need the length of the original ## data set. len <- length(data) nc <- NULL if(HermConj==0) { stopifnot(is.numeric(n)) nc <- as.integer(n/2) + 1 stopifnot(nc == len) } else { n <- len nc <- as.integer(n/2) + 1 } ## only pass what is needed to the C function out <- .C("cfft_c2r", as.integer(n), as.complex(data[1:nc]), res=double(n), PACKAGE = "fftwtools") return(out$res) } fftw_c2c <- function(data, inverse=0) { n <- length(data) out <- .C("cfft_c2c", as.integer(n), as.complex(data), res=complex(n), as.integer(inverse), PACKAGE = "fftwtools") return(out$res) } mvfftw_r2c <- function(data, HermConj=1, fftplanopt=0) { data <- as.matrix(data) n <- dim(data)[1] m <- dim(data)[2] ## ncol nc <- as.integer(n/2) +1 out <- .C("cmvfft_r2c", as.integer(n), as.integer(m), as.double(data), res=matrix(as.complex(0), nc, m), as.integer(fftplanopt), PACKAGE="fftwtools") res <- as.matrix(out$res) ## moving this routine to C requires making space at the end each column, ## but the data is stored in a contiguous format when returned from ## fftw, and it is easier to manipulate this in R. if(HermConj==1) { ## if( n %% 2 == 0) { ## res <- rbind(res, Conj(res[(nc-1):2,])) ## } else { ## res <- rbind(res, Conj(res[nc:2,])) ## } idx <- n-nc+1 res <- rbind(res, Conj(res[idx:2,])) } return(res) } mvfftw_c2r <- function(data, HermConj=1, n=NULL, fftplanopt=0) { ##HermConj is used to determine the true length, n, of the ##input, fftw does not use the the Hermitian conjugate ## in this case the Hermatian conjugate must be stripped from the data. data <- as.matrix(data) ##n <- length(data[,1]) len <- dim(data)[1] m <- dim(data)[2] nc <- NULL if(HermConj==0) { stopifnot(is.numeric(n)) nc <- as.integer(n/2) + 1 stopifnot(nc == len) } else{ n <- len nc <- as.integer(n/2) + 1 } out <- .C("cmvfft_c2r", as.integer(n), as.integer(m), as.complex(data[1:nc,]), res=matrix(as.double(0), n, m), as.integer(fftplanopt), PACKAGE="fftwtools") return(out$res) } mvfftw_c2c <- function(data, inverse=0, fftplanopt=0) { data <- as.matrix(data) n <- dim(data)[1] m <- dim(data)[2] out <- .C("cmvfft_c2c", as.integer(n), as.integer(m), as.complex(data), res=matrix(as.complex(0), n, m), as.integer(inverse), as.integer(fftplanopt), PACKAGE="fftwtools") return(out$res) } fftw_r2c_2d <- function(data, HermConj=1) { ## can be done with two mvfft's t(mvfft(t(mvfft(a)))) ## == mvfft(t(mvfft(t(a)))) data <- as.matrix(data) nR <- dim(data)[1] nC <- dim(data)[2] nRdiv2 <- nR/2 nRc <- floor(nRdiv2) +1 idxRowAppend <- ceiling(nRdiv2):2 ##correct for the fact the c call is column-major out <- .C("cfft_r2c_2d", as.integer(nC), as.integer(nR), as.double(data), res=matrix(as.complex(0), nRc , nC), PACKAGE="fftwtools") res <- as.matrix(out$res) if(HermConj==1 && nR > 2) { if(length(idxRowAppend) == 1) { ##If the number of rows to append is one, R ##will create a column vector for cbind unless ##we transpose. res <- rbind(res, Conj(cbind(res[2,1], t(res[2,nC:2])))) } else { ##With the exception of the first row, the ## resulting matrix is Hermatian --conjugate symmetric res <- rbind(res, Conj(cbind(res[idxRowAppend,1], res[idxRowAppend,nC:2]))) } } return(res) } fftw_c2c_2d <- function(data, inverse=0) { ## can be done with two mvfft's t(mvfft(t(mvfft(a)))) ## == mvfft(t(mvfft(t(a)))) data <- as.matrix(data) nR <- dim(data)[1] nC <- dim(data)[2] ##we correct for the fact the c call is column-major out <- .C("cfft_c2c_2d", as.integer(nC), as.integer(nR), as.complex(data), res=matrix(as.complex(0), nR , nC), as.integer(inverse), PACKAGE="fftwtools") return(out$res) } fftw_r2c_3d <- function(data, HermConj=1) { n1 <- dim(data)[1] n2 <- dim(data)[2] n3 <- dim(data)[3] n1div2 <- n1/2 n1c <- floor(n1div2) +1 idx1Append <- ceiling(n1div2):2 ##correct for the fact the c call is column-major out <- .C("cfft_r2c_3d", as.integer(n3), as.integer(n2), as.integer(n1), as.double(data), res=array(as.complex(0), dim=c(n1c,n2,n3)), PACKAGE="fftwtools") if (HermConj==1 && n1 > 2) { ##With the exception of the first row, the ##resulting array is Hermatian --conjugate symmetric i2 <- if (n2 > 1) c(1,n2:2) else 1 i3 <- if (n3 > 1) c(1,n3:2) else 1 res <- array(NA, c(n1,n2,n3)) res[1:n1c,,] <- out$res res[(n1c+1):n1,,] <- Conj(out$res[idx1Append,i2,i3]) } else { res <- out$res } return(res) } fftw_c2c_3d <- function(data, inverse=0) { n1 <- dim(data)[1] n2 <- dim(data)[2] n3 <- dim(data)[3] ##we correct for the fact the c call is column-major out <- .C("cfft_c2c_3d", as.integer(n3), as.integer(n2), as.integer(n1), as.complex(data), res=array(as.complex(0), dim=dim(data)), as.integer(inverse), PACKAGE="fftwtools") return(out$res) } fftw_c2c_xd <- function(data, inverse=0) { n <- dim(data) r <- length(n) ##we correct for the fact the c call is column-major n <- rev(n) out <- .C("cfft_c2c_xd", as.integer(r), as.integer(n), as.complex(data), res=array(as.complex(0), rev(n)), as.integer(inverse)) return(out$res) } fftwtools/MD50000644000176200001440000000223714017172673012625 0ustar liggesusers880e7c17a01d05accd08dfc8f9966c47 *DESCRIPTION ed0c7521c81d8c7ac99c93f58609af4a *NAMESPACE 74f20ccee3bc60f65060a4d9de87067c *R/fftwtools.R f6871ad95b2e7305354060498756f71d *build/vignette.rds 6e19154c3565f0fcb6bff424ce27bcc4 *cleanup 3d28827abf3132c57f3e92b740c58991 *configure def24f31086da00197d4071f2d5d6d22 *configure.ac 8129170e1bd97b1932d2f25d9167a3cc *inst/doc/testTimeAndSimpleUse.R 25fc2522f2c2e411f178cfb997799d65 *inst/doc/testTimeAndSimpleUse.Rnw c0499138582a6b229430db0301e77b22 *inst/doc/testTimeAndSimpleUse.pdf bc3f7c554e70ad7cb85552bf81856e9f *man/fftw.Rd 9529a1969b1ad42bdd1944a3f9e8c935 *man/fftw2d.Rd 3e03fe7785e20fc6c7cb2d655df7443c *man/fftw3d.Rd 33fdd77263f8d69c628964ef8a7c3bda *man/mvfftw.Rd fddcac97c20ad4f8a5d394372488e106 *src/Makevars.in d27e1aad57007768487364be2f23ec36 *src/Makevars.win 3ce7ba6ecf4392dbff43fdfe3d103831 *src/fftwtools.c a85f485d79bcdb5f03d2d51aafad68ff *src/fftwtools.h 3788861d0d869dfc145b7d4546b03714 *src/fftwtools_init.c 0de9eb21a9d5e2d07cf66ad81b4c9f66 *vignettes/auto/testTimeAndSimpleUse.el 25fc2522f2c2e411f178cfb997799d65 *vignettes/testTimeAndSimpleUse.Rnw 685d56ce46c314a52ce2c24be889201e *vignettes/testTimeAndSimpleUse.bib fftwtools/inst/0000755000176200001440000000000014016547506013266 5ustar liggesusersfftwtools/inst/doc/0000755000176200001440000000000014016547506014033 5ustar liggesusersfftwtools/inst/doc/testTimeAndSimpleUse.R0000644000176200001440000000406314016547506020231 0ustar liggesusers### R code from vignette source 'testTimeAndSimpleUse.Rnw' ################################################### ### code chunk number 1: foo ################################################### options(keep.source = TRUE, width = 60) fftwtools1 <- packageDescription("fftwtools") ################################################### ### code chunk number 2: timing1 ################################################### library("fftwtools") ## We increment by powers of 2, but one can use other incrementes ## We choose fftlength = 2^20, but ## **this was reduced to 2^8 for the vignette distribution.** fftLength <- 2^8 set.seed(10) g <- rnorm(fftLength) ##Start the clock ptm <- proc.time() ## Loop through for (i in 1:100){ fft(g) } ## Stop the clock proc.time() - ptm ################################################### ### code chunk number 3: > stream xڵZ[~X4kɡ{"Flkq p%jIܒ7N|m.ZZr8Ùs?9ܿ\-t.ֹҵ*KWxi\~?ygx za6kvi?9pme+ zcj WEaBUΖLߑޟ[b8w`˫Uyf&Wy噟;3kodhOUGztiЖDBJU\ͻBgF($wrWKS>op}/r|T5w_8eAr~ oOp["i^!1Sw\0_rvu:U ykc*AղxgaCZfqf&C[0♻Cn"D= 0A5kA;de&7`gLwzHBt(-)S)iWz]e{-НV6sY *ᄒ"S pvtx3TىN~5E^?MRpS2`bjUbf! pVBҫ^'t u`z|aÞ/V bJmEZettjSlaanǵh~bOZחZ'؄ T'lo#Fip:'"p#y {-?ʾg AO[NHX bȸR=,Y,h9skCLBqeS%2mOuW*bJ-26SV_NidFߋg:'.~=Z^*϶VUua "0tu G @a) edW>n<8lyHu|;be T`u7 q2mMQynM̄k^C-zHX/UGmJ{'b73Puܰ>W>5<&x5p'|f[m h-@j#jf_32}~4ۑLbwsgc{$錃YQ&+G.iCNl+Uy5mt#^JNUPbR$Fu q/:A&6FR@Oʓ fSnLVQic̜}?4x ~_>ϿؓIEN|XڅK,C鞗p91AOuD)v!nER qqr˨Xa^ -6ن) [>}"^D(G BcR"[]m8 _x֘}\>%>1CҖWˑʑp8i *(7MNʞqzKRy.t`.>IO*n3l  ;nO8y;pxyyØxADs$+dAQX=_bL#w 5VEc; {m& endstream endobj 40 0 obj << /Length 1313 /Filter /FlateDecode >> stream xˮDt" SW!p'7$pwc;qn>$*e̙~9nZv4["iOy&__NoL~0FSU|>hX5֎Ax1Z0pܗ\%W6DRB4?okOnøX*P+!YN ":? 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Rahim} \maketitle \section{Overview} The package \texttt{fftwtool} provides a wrapper for \texttt{FFTW} code discussed in \cite{FFTW05}. This vignette provides example code for comparing execution times of \texttt{fftw} from the package \texttt{fftwtools} to the standard \texttt{R} \texttt{fft} function, and it demonstrates how to replace the \texttt{R} function \texttt{fft} with \texttt{fftw}. The functions \texttt{fftw} and \texttt{mvfftw} mimic the behaviour of the \texttt{R} functions \texttt{fft} and \texttt{mvfft}. There is an \texttt{R} package called \texttt{FFTW} which offers different functionality than fftwtools, specifically it allows the user to set \emph{plans}, and improve the speed with multiple calls to \texttt{fftw} when using data sets of the same size, see \cite{FFTW05}. \section{Timing Example} We begin with a demonstration of the speed difference between a simple call to \texttt{fftw} and the default \texttt{fft} function. The performance improvement is visible with large data sets. Using the example below with $2^{20},$ over one million, data points I observed the following execution times: \begin{itemize} \item \texttt{R}'s \texttt{fft}: 19.069 seconds \item \texttt{fftw} default call: 8.804 seconds \item \texttt{fftw} with \texttt{HermConj} set to \texttt{FALSE}: 7.594 seconds. \end{itemize} You can test timing at any size and decide which function to use. As the speed advantage from the use of the package \texttt{fftw} is only seen in large examples, I currently use the \texttt{R} \texttt{fft} functions, and I change to \texttt{fftw} only when I encounter significantly large data sets and speed becomes a concern. To reduce the check and install times of this package, I reduced \texttt{fftLength} from $2^{20}$ to $2^8$ in the code shown in this vignette. The standard \texttt{R} routine is faster using this number of samples, but it is \emph{not} faster with very large data sets. To compare times, first we look at the time required for the default \texttt{R} \texttt{fft} routine. <>= library("fftwtools") ## We increment by powers of 2, but one can use other incrementes ## We choose fftlength = 2^20, but ## **this was reduced to 2^8 for the vignette distribution.** fftLength <- 2^8 set.seed(10) g <- rnorm(fftLength) ##Start the clock ptm <- proc.time() ## Loop through for (i in 1:100){ fft(g) } ## Stop the clock proc.time() - ptm @ Next we look at replacing \texttt{fft} with \texttt{fftw} without any other changes. <<>= ##timing # Start the clock! ptm <- proc.time() # Loop through for (i in 1:100){ fftw(g) } # Stop the clock proc.time() - ptm @ Finally we look to see how much additional improvement can by had by not returning the complex conjugate which is not required for real data. It is likely this speed up is partially due to decreased memory allocation. <<>= ## Start the clock! ptm <- proc.time() ## Loop through for (i in 1:100){ fftw(g, HermConj=FALSE) } ## Stop the clock proc.time() - ptm @ \section{Replace R's \texttt{fft} call with \texttt{fftw}} The following is a quick and dirty way to replace \texttt{fftw} with \texttt{fftw} in existing code. It is more appropriate to use a conditional statement in the replacement functions to call \texttt{fftw} and \texttt{mvfftw} when the length of $z$ is appropriately large. <>= ## basic option ot overwrite calls fft <- function(z, inverse = FALSE) { fftwtools::fftw(z, inverse=inverse) } mvfft <- function(z, inverse=FALSE) { fftwtools::mvfftw(z, invese=inverse) } @ The above is a simple method of replacing all \texttt{fft} calls with \texttt{fftw} calls in the \texttt{multitaper} package which I maintain. If you are interested in the additional improvement available from not returning the unnecessary complex conjugate when using real data, you can overwrite the call setting \texttt{HermConj} to \texttt{FALSE}. <<>= fft <- function(z, inverse = FALSE) { fftwtools::fftw(z, inverse=inverse, HermConj=FALSE) } @ The last method is only valid when the input is not complex, and it may break certain calls depending on when the complex conjugate is discarded. If you discard the complex conjugate, you will need the length of the original data to perform an inverse Fourier transform. If you are using the latter method then it may be wise to look into further functionality provided in the \texttt{R} packages \texttt{FFTW} and \texttt{fftwtools}. \subsection{Clean up} If you replace the \texttt{R}'s call to \texttt{fft} with \texttt{fftw} then it is good practice to clean up the replacement and restore calls to \texttt{fft} and \texttt{mvfft} to the standard \texttt{R} routine when you are finished using \texttt{fftw}. The following code shows how this cleanup is performed. <>= rm(fft, mvfft) @ \bibliographystyle{plain} \bibliography{testTimeAndSimpleUse} \end{document} fftwtools/cleanup0000755000176200001440000000023014016547507013662 0ustar liggesusers#!/bin/sh rm -rf fftwtools.Rcheck/ \ autom4te.cache/ \ config.log \ config.status \ src/*.o \ src/*.dll \ src/*.so \ src/Makevars fftwtools/configure0000755000176200001440000037375414016547507014244 0ustar liggesusers#! /bin/sh # Guess values for system-dependent variables and create Makefiles. # Generated by GNU Autoconf 2.69 for fftwtools 0.9-10. # # # Copyright (C) 1992-1996, 1998-2012 Free Software Foundation, Inc. # # # This configure script is free software; the Free Software Foundation # gives unlimited permission to copy, distribute and modify it. ## -------------------- ## ## M4sh Initialization. ## ## -------------------- ## # Be more Bourne compatible DUALCASE=1; export DUALCASE # for MKS sh if test -n "${ZSH_VERSION+set}" && (emulate sh) >/dev/null 2>&1; then : emulate sh NULLCMD=: # Pre-4.2 versions of Zsh do word splitting on ${1+"$@"}, which # is contrary to our usage. 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