search for: dimx

Dear all, I am trying to learn lapply. I would like, as a test case, to try the lapply alternative for the Shadowlist<-array(data=NA,dim=c(dimx,dimy,dimmaps)) for (i in c(1:dimx)){ Shadowlist[,,i]<-i } ---so I wrote the following--- returni <-function(i,ShadowMatrix) {ShadowMatrix<-i} lapply(seq(1:dimx),Shadowlist[,,seq(1:dimx)],returni) So far I do not get same results with both ways. Could you please help me understand...

What I want to do is create a horizontal bar chart matrix for a set of data that have a common set of variables (e.g., % of As, % of Bs, etc.) listed on the Y-axis and groups (e.g., Classes) on the X-axis. The key here is that the bars for each individual class plot are "centered" rather than left or right-justified. In archaeology plots similar to this are called battleship curves or

...rices at C-level... except for, what probably is the answer, that matrices are in fact vectors with dimensions. This is a sample code I am using at C level: ???????????????????????? # include <R.h> # include <Rinternals.h> # include <R_ext/Rdynload.h> SEXP foo(SEXP x) { SEXP dimx; double *px, *pdimx; PROTECT(dimx = getAttrib(x, R_DimSymbol)); px = REAL(x); UNPROTECT(1); return(dimx); } ???????????????????????? The question is: how to create pointers to dimx (in order to extract individual values)? I tried: pdimx = REAL(dimx); This is where R complain...

Dear all I would like to ask you if an assignment can be done inside a lapply statement. For example I would like to covert a double nested for loop for (i in c(1:dimx)){ for (j in c(1:dimy)){ Powermap[i,j] <- Pr(c(i,j),c(PRX,PRY),f) } } to something like that: ij<-expand.grid(i=seq(1:dimx),j=(1:dimy)) unlist(lapply(1:nrow(ij),function(rowId) { return (Powermap[i,j]<-Pr(c(ij$i[rowId],ij$j[rowId]),c(PRX,PRY),f)) })) as you can see lapp...

Dear R-users I hope someone could help me on this problem. I want to create a multiple kiteChart showing the real values with a scalebar on each indicating the scale . Here are some sample data to show what I want to achieve. Y <- read.table(textConnection("Sample1 Sample2 60 20 150 50 300

Hi, I do not have much R experience just the basics, so please excuse any obvious questions. I would like to create bubble plot that have Categorical data on the x and y axis and then the diameter if the bubble the value related to x and y. Attached to the email is a pic of what I would like to do. I do hope someone can help me. -- Regards/Groete/Mit freundlichen Gr??en/recuerdos/meilleures

hi, I have been trying to do this in R (have implemented it in Excel) but I have been using a very inefficent way (loops etc.). I have matrix A (columns are years and ages are rows) and matrix B (columns are birth yrs and rows are ages) I would like to first turn matrix A into matrix B And then I would like to convert matrix B back again to the original matrix A. (I have left out details of

Hello everyone, I am using ggplot to plot but I am getting the following error which I do not understand Error: geom_text requires the following missing aesthetics: label My code is dimx<-256 library(ggplot2) dev.new() xandy<-expand.grid(seq(1:dimx),seq(1:dimy)) xx<-data.frame(xandy[[1]],xandy[[2]],Powermap=Powermap) subsetxx<-subset(xx, xx$Powermap>threshold) ggplot( (subsetxx ) )+ geom_point(aes(x,y,colour=cut(Powermap,c(0,-1,-10,-20,-30,-40,-50,-...

...e <time.h> #define IA 16807#define IM 2147483647#define AM (1.0/IM)#define IQ 127773 #define IR 2836#define NTAB 32#define NDIV (1+(IM-1)/NTAB)#define EPS 1.2*pow(10,-7)#define RNMX (1.0-EPS) using namespace std;float rand1(long *idum); int main(){ long run=10000,adr=-run,x,y,hapa=0,i=0; int dimx=700,dimy=700,nrg=50, M[dimx][dimy]; double rnd,sum=0; long k[run+1],frekuenca; bool njehsuar[run+1], next; ofstream Txt("EndjeMePengesa2D.txt"); printf("\nProgrami ekzekutohet:\ni=1 ne %d",run); for (i=1;i<=run;i++){ njehsuar[i]=true; k[i]=0; } while (i<nrg){ x=dimx*rand...

Hi, I'm working on some lattice wireframe figures that have two conditioning factors, and I want the strips labelled on the top and left of the entire plot, rather than above each individual panel. useOuterStrips() does this, but it draws internal axis lines, even after I explicitly set axis.line to 0. Is there a way to use useOuterStrips but without axis boxes? I've included a short

I've searched the archives and read the xyplot help but can't figure out the 2 lattice questions below? Consider: library(lattice) DF <- data.frame(x=rnorm(20), y=rnorm(20), g1=rep(letters[1:2], 10), g2=rep(LETTERS[1:2], each=10), g3=rep(rep(letters[3:4],each=5),2)) xyplot(y ~ x | g1 + g2, groups=g3, data=DF) 1) Is there a way to get one strip per row and column

Dear all with image I can plot only one set of values in one plot. Do somebody have any insight how to put those 2 matrices into one picture so that in one cell in image picture are both values from mat[1,1] and mat2[1,1]. mat<-matrix(1:4, 2,2) mat2<-matrix(4:1,2,2) x <-1:2 y <-1:2 image(x, y, mat) image(x, y, mat2) The only way I found is to mix x or y for both matrices let

...;- get.var.ncdf(netcdf_1992_temp, "mrunoff") mrunoff_1993 <- get.var.ncdf(netcdf_1993_temp, "mrunoff") mrunoff_1994 <- get.var.ncdf(netcdf_1994_temp, "mrunoff") mrunoff_1995 <- get.var.ncdf(netcdf_1995_temp, "mrunoff") # Define variable dimensions dimx <- dim.def.ncdf("Lon", "deg E", as.double(longitude)) dimy <- dim.def.ncdf("Lat", "deg N", as.double(latitude)) month <- dim.def.ncdf("Mon", "Months: Jan 86=1, Dec 95=120)", 1:120) year <- dim.def.ncdf("Year", "y...

...get.var.ncdf(netcdf_1992_temp, "mrunoff") mrunoff_1993 <- get.var.ncdf(netcdf_1993_temp, "mrunoff") mrunoff_1994 <- get.var.ncdf(netcdf_1994_temp, "mrunoff") mrunoff_1995 <- get.var.ncdf(netcdf_1995_temp, "mrunoff") # Define variable dimensions dimx <- dim.def.ncdf("Lon", "deg E", as.double(longitude)) dimy <- dim.def.ncdf("Lat", "deg N", as.double(latitude)) month <- dim.def.ncdf("Mon", "Months: Jan 86=1, Dec 95=120)", 1:120) year <- dim.def.ncdf("Year", "y...

Hello, I would like to plot my data in a fashion similar to a boxplot, but plot the true data points without a box, just overlay lines of the summary generated by the boxplot. I have less than 10 observations within each group, so I think showing the actual data would be more effective than the box of the boxplot. I have been unable to find a way to do this. Here is example data: >

Dear all I have the following time stamps (in the following format) MeasurementSet$TimeStamps        [,1] [,2] [,3] [,4] [,5]   [,6]   [1,] 2011    7    2   13   43 48.718   [2,] 2011    7    2   13   43 54.281   [3,] 2011    7    2   13   43 59.843   [4,] 2011    7    2   13   44  5.390   [5,] 2011    7    2   13   44 10.859   [6,] 2011    7    2   13   44 16.375   [7,] 2011    7    2   13   44

...ass(z) <- c(if (is.matrix(y)) c("maov","mlm"), c("aov","lm")) } z$call <- match.call() z$terms <- mt if (model) z$model <- mf z } aov.balanced.fit <- function(x,y,mod.terms,wt=NULL){ x <- as.matrix(x); dimx <- dim(x) xnames <- dimnames(x)[[2]] y <- as.matrix(y); dimy <- dim(y) assn <- attr(x,"assign") df <- c(table(assn), dimy[1]- dimx[2]) D <- diag(1/diag(t(x) %*% x)) dimnames(D) <- list(xnames,xnames) coef <- as.numeric(D %*% t(x) %...

...395 15784 16459.454 15785 16169 114333 1000 c > > So, my best shot on the original problem would now be to either use: > > dim2 <- function(x) dim(x) > foo <- function(x, dim=dim2(x)) { dim } > > or simply avoid the name clash via: > > foo <- function(x, dimx=dim(x)) { dimx } I think you'll find that baseenv()$dim(x) and .BaseNamespaceEnv$dim(x) are about 25 times faster than base::dim(x). This doesn't seem like it should be necessary... Radford

...John lls<-function (pat = "") { lll <- ls(1, pat = pat) for (i in 1:length(lll)) { cat(formatC(eval(parse(t = paste("mode(", lll[i], ")"))), 1, 12), formatC(lll[i], 1, max(nchar(lll)) + 1), eval(parse(t = paste("dimx(", lll[i], ")"))), "\n") } } where dimx<-function (dd) { if (is.null(dim(dd))) { length(dd) } else { dim(dd) } } -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://ww...

...) to force as.matrix to return the appropriate matrix but this also failed and I only got back a vector again Could you please let me understand why this might happening? Best Regards Alex P.S Below you will find part of my code. ...................(lines omitted, declarations) x <- seq(1, dimx, step) y <- seq(1, dimy, step) f <- GaussRF(x=x, y=y, model=model, grid=TRUE,param=c(mean, variance, nugget, scale, alpha)) # image(x, y, f) Displays the matrix # f is a 2x2 matrix of dimension (x,y) r <- raster(nrow=dimx, ncol=dimy) r <- setValues(r,as.matrix(f)) # getValues(r)...