similar to: Convolution confusion:

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?

I want to generate the following outcome using convolution of two sequences. x <- c(1,2,3,4,5) y <- c(6,7,8,9) The resulting convolution vector is 6 19 40 70 100 94 76 45 When using convolve(), it is hard to produce the result above. Would you help me out to get that? Best regards Moohwan Kim

Dear R-Helpers, I want to try the 2D (two-dimensional) convolution in R. For example, let us we have the following kernel and data. kernel <- (1,2,3,2,1) data <- array(1:100, dim=c(10,10)) I know the function 'convolve' only for one-dimensional convolution, but it is just for a 1D sequence. Is there any function for 2D convolution? For theory, please refer to the following link:

I have been experimenting with convolve(). What I know about convolution I learned from engineering (they call this stuff linear systems theory), not statistics, so maybe this is all just a matter of different conventions. BUT I notice very weird things with convolve(). 1. First example, from the classic Bracewell The Fourier transform and its applications, chap 3 (p.32 in 2nd edition): {2 2 3 3

Hi, Man page for 'convolve' says: conj: logical; if 'TRUE', take the complex _conjugate_ before back-transforming (default, and used for usual convolution). The complex conjugate of 'x', of 'y', of both? In fact it seems that it takes the complex conjugate of 'y' only which is OK but might be worth mentioning because (1) conj=TRUE is the

We obtained some disturbing results from convolve() (inaccuracies and negative probabilities). We'll try to make the context clear in as few lines as possible... Our function panjer() (code below) basically computes recursively the probability mass function of a compound Poisson distribution. When the Poisson parameter lambda is very large, the starting value of the recursive scheme ---

Dear R People: Here is something that I am sure is very simple. I'm just trying to re-create the C convolution example in the Extensions manual. Here is the subroutine: void convolve(double *a, int *na, double *b, int *nb, double *ab) { R_len_t i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j < *nb; j++) ab[i + j] += a[i] *

Full_Name: Bill Simpson Version: 65.1 , 0.90.1 OS: Linux Submission from: (NULL) (193.62.250.209) I reported this on r-help, but here is official bug report. The present convolve() does not do convolution by default. Its default behaviour is correlation. This is a bug. The default argument conj should be set to FALSE. The zero-padding should be on the right for linear convolution (don't

Dear R-ophiles, I've found something very odd when I apply convolve to ever larger vectors. Here is an example below with vectors ranging from 2^11 to 2^17. There is a funny bump up at 2^12. Then it gets very slow at 2^16. > for( i in 11:20 )print( system.time(convolve(1:2^i,1:2^i,type="o"))) user system elapsed 0.002 0.000 0.002 user system elapsed 0.373

Jeff Brown wrote: > > Hi, > > I'm trying to learn to use .C, which lets one invoke compiled C code from > within R. To do that, one has to first get the C code into R as a shared > object, which (I think) means first compiling it (with COMPILE or SHLIB) > and then loading it (with dyn.load()). > I would suggest taking it a step further and building an R package

Hi I have made a R function 'convolve2' for convolution of two real valued vectors based on Rs 'convolve' with option type="open" - see below. (exp.length and irf.length are variables set in another part of the program) I wish to implement the function convolve2 in C and use it in a function used from R with .Call - e.g. I need to call fft in C. All I can find in the

To add to the wish-list for "convolve": For modeling processes that decay exponentially in time, e.g., fluorescence, it is desirable to have a function that convolves an arbitrary vector with an exponential using an iterative method. In the TIMP package (which won't be on CRAN till R 2.5.0 is official, but is for now at www.nat.vu.nl/~kate/TIMP) we implemented this special-purpose

Dear R users, I want to call C code via the .C or .Call interface. This works fine with integer values but using doubles the array received in C will be set to zeros. I have tried the convolve examples (Writing R extensions, chapter 5.2) and still the resulting array consists of zeros. My code (shortened for my purposes. Original did not work either):

Hi, the function stats::convolve does not mention efficient usage of the underlying FFT algorithm, such as (a) if type="circular", then length(x)=length(y) should have many factors (e.g. length(x) = length(y) = 2^n) (b) if type="open" or "filter", then length(x)+length(y)-1 should have many factors (e.g. length(x)+length(y)-1 = 2^n) In particular the latter may

Hi, I compiled a C program file on Borland C++ 5.5 compiler to get one dll output (as instructed in the file readme.package). The C program file is just the example on page 31 of "writing R extensions": void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j

Hi, Although this is not directly an R-related question, it is relevant as I am trying to port some R code to C to speed things up in a computation. I am working through my first attempts to generate and link compiled C code in R. I could make the 'convolve' function to work and similar functions that take vectors as arguments. In my application I need to pass a couple of matrices to

Dear all, I'm studing how to include .c code in my .r functions . In the R-exts.pdf manual I have found the following code. At one point the author write "called from R by"... How can I load a .c file on R? ( I am using a xp windows as so.) Thank you ale void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++)

Hi all, i have some problem in using shared objects. I tried the example found in "Writing R Extension", pg. 33 I used the .c file prova.c : ------------------------------------------------------------------- #include <R.h> #include <Rinternals.h> void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j , nab = *na + *nb - 1; for (i = 0; i < nab;

Hi, I am hoping some one can help me. I am learning to use C and would like to learn how to call c code in R. I have look at Writing R Extensions and I tried to copy the example on page 38 void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0; i < nab; i++) ab[i] = 0.0; for(i = 0; i < *na; i++) for(j = 0; j <

Hi everyone! I'm trying to lear how to call external C code in R but even the R help web-page example is drive me crazy. I copy-paste the example at: http://stat.ethz.ch/R-manual/R-patched/doc/manual/R-exts.html#Interface%20functions%20.C%20and%20.Fortran here is the example: void convolve(double *a, int *na, double *b, int *nb, double *ab) { int i, j, nab = *na + *nb - 1; for(i = 0;