similar to: mvfft (PR#176)

This message is in MIME format --_=XFMail.1.3.p0.Linux:990422185944:4782=_ Content-Type: text/plain; charset=us-ascii R-0.64.0 on RedHat Linux 5.1 Some problems with multivariate fast fourier transform. I have attached the dump of a 30 x 3 matrix that seems to reliably reproduce these problems 1) mvfft doesn't like vectors. It complains about not having enough memory: R>

R 1.4.1, Linux and Windows for(i in 1:1000) { X <- rnorm(i) XX <- fft(fft(X), inverse=T)/i if(max(Mod(XX-X)) > 1e-10) print(i) } [1] 392 [1] 588 [1] 968 [1] 980 and I then get a segfault during gc(). The answers are way off, with imaginary parts 1e10 or more. These numbers are all multiples of 7^2 or 11^2. (Based on a report to R-help Date: Thu, 28 Mar 2002 09:37:34

Hi, I have problems when calling fft_factor and fft_work directly in my C-code. Martin Maechler already told me that I should not do this -- anyway, the code works fine if the length of the vector is a multiple of 2,3,5. If the length of the vector has different form I get, in some cases, a segmentation fault when work and iwork are freed (I use C's malloc to allocate memory for work and

Hi, I am new to R. and even though I've made my code to run and do what it needs to . It is taking forever and I can't use it like this. I was wondering if you could help me find ways to fix the code to run faster. Here are my codes.. the data set is a bunch of 0s and 1s in a data.frame. What I am doing is this. I pick a column and make up a new column Y with values associated with that

I have very large csv files (up to 1GB each of ASCII text). I'd like to be able to read them directly in to R. The problem I am having is with the variable length of the data in each record. Here's a (simplified) example: $ cat foo.csv Name,Start Month,Data Foo,10,-0.5615,2.3065,0.1589,-0.3649,1.5955

There is a problem with 'default argument evaluation' when I use an existing function name as argument name : sintest <- function(x, y = 2, sin= sin(pi/4)) { ## Purpose: Test of "default argument evaluation" ## -------- Fails for R-0.49. Martin Maechler, Date: 9 May 97. c(x=x, y=y, sin=sin) } ## R-0.49: R> sintest(1) ##> Error in sintest(1) : recursive

I am trying to compile R-2.4.1 in 64-bit on Solaris 10 running on AMD hardware. I am trying to do this with Sun Studio 11. My config.site looks like this: #! /bin/sh AR="/usr/ccs/bin/ar" TEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/tex" LATEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/latex" PDFTEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/pdftex"

I am trying to compile R-2.4.1 in 64-bit on Solaris 10 running on AMD hardware. I am trying to do this with Sun Studio 11. My config.site looks like this: #! /bin/sh AR="/usr/ccs/bin/ar" TEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/tex" LATEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/latex" PDFTEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/pdftex"

Hi All, I found "mvfft" in R and "fft2" in Matlab give different result and can't figure out why. My example is: In R: > matrix(c(1,4,2,20), nrow=2) [,1] [,2] [1,] 1 2 [2,] 4 20 > mvfft(matrix(c(1,4,2,20), nrow=2)) [,1] [,2] [1,] 5+0i 22+0i [2,] -3+0i -18+0i In Matlab: >fft2([1,2;4,20]) ans= 27 -17 -21 15 Does any function in R

Hi Developers, I am looking for another new project to help me get more up to speed on R and to learn something outside of R internals. One recent R issue I have run into is finding a fast implementations of the equivalent to the following SAS code: /* MDPC is an integer sort key made from two integer columns */ MDPC = (MD * 100000) + PCO; /* sort the dataset by the key */ PROC SORT;

hi, i am getting an error when calling the impute.knn function (see the screenshot below). what is the problem here and how can it be solved? screenshot: ################## *** caught segfault *** address 0x513c7b84, cause 'memory not mapped' Traceback: 1: .Fortran("knnimp", x, ximp = x, p, n, imiss = imiss, irmiss, as.integer(k), double(p), double(n), integer(p),

Dear all, I have an image that I need to filter, and so I'm looking for a method to convolve it with a matrix. If I understood the docs for convolve correctly, it only works in 1D (and I have tried to convolve, it didn't look good). So, I wondered if anybody have implemented 2D convolution in R, or have any good advices to share (beyond having a look at mvfft), before I go hacking?

Dear all, I am trying to upgrade R-1.6.2 to R-1.7.0 on an SGI running IRIX6.5. Everything compiles but I get an error in the testing phase: [snip] running regression tests make[3]: Entering directory `/usr/local/src/R-1.7.0/tests' running code in 'reg-tests-1.R' ...make[3]: *** [reg-tests-1.Rout] Error 1 make[3]: Leaving directory `/usr/local/src/R-1.7.0/tests' make[2]: ***

I think the code is part of the RTAQ package but is not included in it, as I obtained it from https://r-forge.r-project.org/scm/viewvc.php/pkg/RTAQ/R/HAR_model.R?view=markup&root=blotter&sortby=author&pathrev=1028. It is not my code and I make no claim to other's good work, and apologize if I should even be posting it I am not sure, but in the transform function it allows to

Hi all, I am a beginner trying to use R to work with large amounts of oceanographic data, and I find that computations can be VERY slow. In particular, computational speed seems to depend strongly on the number and size of the objects that are loaded (when R starts up). The same computations are significantly faster when all but the essential objects are removed. I am running R on a machine

I am working with xts dependent data, and my code is as follows (the problem is explained throughout): dat <- getdat("prices") dat <- read.zoo(dat, sep = "",format="%d/%m/%Y %H:%M", tz="", FUN=NULL, regular=TRUE, header=TRUE, index.column=1, colClasses=c("character", "numeric")) dat <- as.xts(dat)

Hello, I propose two small changes to spec.pgram to get modest speedup when dealing with input (x) having multiple columns. With plot = FALSE, I commonly see ~10-20% speedup, for a two column input matrix and the speedup increases for more columns with a maximum close to 45%. In the function as it currently exists, only the upper right triangle of pgram is necessary and pgram is not returned by

Problem compiling R. version: 0.64.2 machine: SGI O2 OS: IRIX6.5 CC cc FC f77 MAKE GNU make 3.75 Here is part of the the output for make. make[2]: Leaving directory `/usr/people/faculty/math/mgass/stage/R/R-0.64.2/src/include' make[2]: Entering directory `/usr/people/faculty/math/mgass/stage/R/R-0.64.2/src/appl' cc -g -OPT:IEEE_NaN_inf=ON -I../include

I have done a fair bit of spectral analysis, and hadn't finished collecting my thoughts for a reply, so hadn't replied yet. What exactly do you mean by normalize? I have not used the functons periodogram or spectrum, however from the description for periodogram it appears that it returns the spectral density, which is already normalized by frequency, so you don't have to worry about

I am trying to compile R-2.4.1 in 64-bit on Solaris 10 running on AMD hardware. I am trying to do this with Sun Studio 11. My config.site looks like this: #! /bin/sh AR="/usr/ccs/bin/ar" TEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/tex" LATEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/latex" PDFTEX="/usr/local/teTeX/bin/i386-pc-solaris2.10/pdftex"