search for: ydim

Can anyone help me resolve this? A part of the R function looks like this: print(is.loaded('merge_xtabs_patterns_file')) print(is.loaded('merge_xtabs_patterns_file_')) .Fortran('merge_xtabs_patterns_file_',ydim[1],ydim[2],x=as.integer(as.matrix(y)),na=as.integer(c), maxD=as.integer(maxD),lrowmem=length(rowmem),rowmem=as.integer(rowmem), sequential=as.integer(Sequential),nclust=as.integer(nclust)) The corresponding output: [1] FALSE [1] TRUE Error in .Fortran("merge_xtabs_patterns_file_",...

...foobar and run the main code routine more than 100 times, it crashes R. Or if I call .Call("foobar"....) seperately more than two tims it crashes R. For the most part I am doing matirx multiplies using EXP matrixprod (SEXP x , SEXP y ) { int nrx , ncx , nry , ncy , mode; SEXP xdims , ydims , ans ; char *transa = "N" , *transb = "N" ; double one = 1.0 , zero = 0.0 ; xdims = getAttrib (x , R_DimSymbol ) ; ydims = getAttrib (y , R_DimSymbol ) ; mode = REALSXP; nrx = INTEGER( xdims ) [ 0 ] ; ncx = INTEGER( xdims ) [ 1 ] ; nry = INTEGER( ydims ) [ 0 ] ; ncy = INTEGER(...

...vising, but I'm wondering if there is a built-in way to write and then restore a matrix with not only the dimnames (which write.table/read.table can preserve) but also the names(dimnames)? Example: > M <- matrix(1:4, 2, 2) > dimnames(M) <- list(xdim=c("a", "b"), ydim=c("u", "v")) > M ydim xdim u v a 1 3 b 2 4 -- View this message in context: http://www.nabble.com/write-matrix-M-including-names%28dimnames%28M%29%29-tp24750637p24750637.html Sent from the R help mailing list archive at Nabble.com.

...*transa = "N", *transb = "N"; double one = 1.0, zero = 0.0; F77_CALL(dgemm)(transa, transb, &nrx, &ncy, &ncx, &one, x, &nrx, y, &nry, &zero, z, &nrx); } SEXP trProd2(SEXP x, SEXP y) { int nrx, ncx, nry, ncy, mode, i; SEXP xdims, ydims, ans, ans2, tr; xdims = getAttrib(x, R_DimSymbol); ydims = getAttrib(y, R_DimSymbol); mode = REALSXP; nrx = INTEGER(xdims)[0]; ncx = INTEGER(xdims)[1]; nry = INTEGER(ydims)[0]; ncy = INTEGER(ydims)[1]; PROTECT(ans = allocMatrix(mode, nrx, ncy)); PROTECT(ans2 = allocMatrix(mode,...

...a problem writing a variable to an existing file. Below is a part of my script and how it fails. I can't find "create.var.ncdf" in help Thanks for any help. Mark nc <- open.ncdf(ncname, readunlim=FALSE, write=TRUE ) missing <- 1.e+30 xdim <- nc$dim[["west_east"]] ydim <- nc$dim[["south_north"]] tdim <- nc$dim[["Time"]] lscalevar <- var.def.ncdf(scalenames[ivar], 'gpoints', list(xdim,ydim,tdim), missing ) nc <- var.add.ncdf( nc, lscalevar ) for( i in 1:nt) put.var.ncdf(nc,lscalevar,scale,verbose=TRUE ) #scale is an arr...

...;N"; > double one = 1.0, zero = 0.0; > F77_CALL(dgemm)(transa, transb, &nrx, &ncy, &ncx, &one, > x, &nrx, y, &nry, &zero, z, &nrx); } > > SEXP trProd2(SEXP x, SEXP y) > { > int nrx, ncx, nry, ncy, mode, i; > SEXP xdims, ydims, ans, ans2, tr; > xdims = getAttrib(x, R_DimSymbol); > ydims = getAttrib(y, R_DimSymbol); > mode = REALSXP; > nrx = INTEGER(xdims)[0]; > ncx = INTEGER(xdims)[1]; > nry = INTEGER(ydims)[0]; > ncy = INTEGER(ydims)[1]; > PROTECT(ans = allocMatrix(mode, nrx, nc...

...atrix was 22283 x 8. The 8 samples have 4 controls and 4 experimentals. I transposed the matrix so that its dim are 8 x 22283, and called that "allt." Using the normalize() function from som library, I scaled the data to have mean zero and variance 1. allt.som <- som(allt, xdim=5, ydim=5, topol="hexa", neigh="bubble", alpha=1) plot(allt.som) What I cannot figure out how to do is how to determine where each sample has clustered, since the plot that i'm using does not include labels...I also tried str(allt.som) but cannot determine which attribute calls w...

...er=TRUE, sep=",") # keep only nonzero variance properties rdata <- rdata[, apply(rdata, 2, function(x)any(x[-1] != x[-length(x)])), drop = FALSE] # load SOM package library(class) #set seed for rng set.seed(12345) # calculate SOM gridtopo <- "hexagonal" xdim <- 5 ydim <- 5 gr <- somgrid(xdim = xdim, ydim = ydim, topo = gridtopo) rdata.som <- batchSOM(rdata, gr, c(4, 4, 2, 2, 1, 1, 1, 0, 0)) # write SOM results to stdout rdata.som # write out results write.table(rdata.som$codes, file="c:/temp/A8F.tmp", sep=",", col.names=T, row.na...

...e combinations for each selection sec1 = combinations(4,2,1:4) sec2 = combinations(6,3,5:10) sec3 = combinations(8,5,11:18) I then wrote a function to combine the combinations for each selection. multiperm <-function(x, y) # function to combine combinations { xdim = nrow(x) xcol = ncol(x) ydim = nrow(y) ycol = ncol(y) v1 = matrix( nrow = xdim*ydim, ncol = xcol+ycol ) for ( i in 1:xdim) { for (j in 1:ydim){ v1[i + (j-1)*xdim , ] = c(x[i,], y[j, ])} } v1 = data.frame(v1) # set output as dataframe } This works fine when combining sec1 and sec2, comb = multiperm(sec1,s...

Hello Rprofessionals, The SOM-Obj works very well, when i normalize my data and the plot-function, too ! But i miss or didn't find the possibility , extract the information from the SOMplot "clusterSize" and "mean" for every cluster as quantitative information ( i.e. the DataFrame with an additional column which define the calculate clusters from SOM)? My intention -

...Kind regards Raphael Minimal working example (adapted from netcdf4 manual): library(ncdf4) #---------------- # Make dimensions #---------------- xvals <- 1:360 yvals <- -90:90 nx <- length(xvals) ny <- length(yvals) xdim <- ncdim_def('Lon','degreesE', xvals ) ydim <- ncdim_def('Lat','degreesE', yvals ) tdim <- ncdim_def('Time','days since 1900-01-01', 0, unlim=TRUE ) #--------- # Make var #--------- mv <- 1.e30 # missing value var_temp <- ncvar_def('Temperature','K', list(xdim,ydim,tdim), mv ) #...

...idvalue,height,gridcol as variables of the dataframe. The grid dimensions are 1253 x 2001 (=2507253 data points). My attempts with surface3d fail, mainly because I cannot produce the matrix required for the height input. elev.to.list{CTFS} fails with: "Error in matrix(elevfile$elev, nrow= 1+ydim/gridsize, ncol=1+xdim/gridsize. : attempt to set an attribute on NULL" which I assume means it requires a square grid (=quadrates). Any ideas/help appreciated Thanks Herry Dr Alexander Herr Spatial and statistical analyst CSIRO, Sustainable Ecosystems Davies Laboratory, University Drive, Do...

Hello R users, I'm using SOM() to cluster a gene expression data set the syntax i used was dataGrid <- c(somgrid(xdim = 3, ydim = 3, topo = c("rectangular","hexagonal"))) dataClusters <- SOM(dataMatrix, grid = dataGrid) plot(dataClusters) it seems that this works just fine but the thing i can't figure out is how to determine where each data point has been clustered. any suggestions are welcome...

Dear All, Would you please tell me how to display the sample No. on the map ? ---Below commands don't display the sample No.(from 1 to 150).--- library(som) library(klaR) iris.som3 <- som(iris[,1:4], xdim = 14,ydim = 6) library(klaR); opar<- par(xpd = NA) shardsplot(iris.som3, data.or = iris,label = TRUE) legend(3.5,14.3, col = rainbow(3), xjust =0.5, yjust = 0,legend = levels(iris[, 5]),pch = 16, horiz = TRUE) par(opar) ---------------- Ebi [[alternative HTML version deleted]]

...adapted from netcdf4 manual): > > library(ncdf4) > #---------------- > # Make dimensions > #---------------- > xvals <- 1:360 > yvals <- -90:90 > nx <- length(xvals) > ny <- length(yvals) > xdim <- ncdim_def('Lon','degreesE', xvals ) > ydim <- ncdim_def('Lat','degreesE', yvals ) > tdim <- ncdim_def('Time','days since 1900-01-01', 0, unlim=TRUE ) > #--------- > # Make var > #--------- > mv <- 1.e30 # missing value > var_temp <- ncvar_def('Temperature','K'...

...;-matrix(cos(1:10),nrow=900,ncol=10,byrow=TRUE) InputB<-matrix(sin(5:14),nrow=100,ncol=10,byrow=TRUE) Input<-rbind(InputA,InputB) I though that a small grid of 3*3 would be enough to extract the patterns in such simple matrix : GridWidth<-3 GridLength<-3 gr <- somgrid(xdim=GridWidth,ydim=GridLength,topo = "hexagonal") test.som <- SOM(Input, gr) par(mfrow=c(GridLength,GridWidth)) for(i in 1:(GridWidth*GridLength)) plot(test.som$codes[i,],type="l") Only when I use a larger grid (say for example 7*3 ) I get some of the representatives for the sin pattern. This...

...imnames(x.ggobi)[[2]][ncols+2]<-"Map 2" x.grid<-cbind(x.som$code,x.som$code.sum[,1:2]) dimnames(x.grid)[[2]]<-dimnames(x.ggobi)[[2]] x.clust<-rbind(x.ggobi,x.grid) } f.ggobi.som.net<-function(x.som) { x.net<-NULL for (i in 1:x.som$xdim) { for (j in 1:x.som$ydim) { if (j<x.som$ydim) x.net<-rbind(x.net,c((i-1)*x.som$xdim+j,(i-1)*x.som$xdim+j+1)) if (i<x.som$xdim) x.net<-rbind(x.net,c((i-1)*x.som$xdim+j,i*x.som$xdim+j)) } } return(x.net) } d.music.som<-f.ggobi.som(d.music.std[,-c(1,2)],music.som) d.music.som<-list(Son...

...imnames(x.ggobi)[[2]][ncols+2]<-"Map 2" x.grid<-cbind(x.som$code,x.som$code.sum[,1:2]) dimnames(x.grid)[[2]]<-dimnames(x.ggobi)[[2]] x.clust<-rbind(x.ggobi,x.grid) } f.ggobi.som.net<-function(x.som) { x.net<-NULL for (i in 1:x.som$xdim) { for (j in 1:x.som$ydim) { if (j<x.som$ydim) x.net<-rbind(x.net,c((i-1)*x.som$xdim+j,(i-1)*x.som$xdim+j+1)) if (i<x.som$xdim) x.net<-rbind(x.net,c((i-1)*x.som$xdim+j,i*x.som$xdim+j)) } } return(x.net) } d.music.som<-f.ggobi.som(d.music.std[,-c(1,2)],music.som) d.music.som<-list(Son...

Hi there, I would like to make a 'bumps chart' like the ones described e.g. here: http://junkcharts.typepad.com/junk_charts/bumps_chart/ Purpose: I'd like to plot the proportion of people in select countries living for less then one USD pr day in 1994 and 2004 respectively. I have already constructed a barplot - but I think a bumps chart would be better # The barplot and data

Dear list Has anyone got a recipie at hand to import .bil files into R? From what I understand the .bil files I got contain layered matricies which I would lke to make available in R as an array or list. GIS people seem to be familiar with the .bil format but I am not using any GIS software and would prefer to deal with the data in R. I use the latest version of R on Mac OSX 10.5.8.