similar to: write matrix M including names(dimnames(M))

Hello, I have 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"]]

Hi all, I originally posted this to the bioconductor group, but maybe it's better suited to the r-help... I'm using som() to partition samples of gene expression data into clusters. The point is to classify control vs. experimental cases (sample clustering). The original matrix was 22283 x 8. The 8 samples have 4 controls and 4 experimentals. I transposed the matrix so that its dim

Dear all I'm a newbie regarding netcdf data. Today I realized that I maybe do not understand some basics of the netcdf. I want to create a *.nc file containing three variables for Switzerland. All data outside of the country are NAs. The third variable is calculated from the first two variables. Basically there is no problem to do that. I copy the file with the data of the first variable,

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 =

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

On Mon, Aug 14, 2017 at 5:29 AM, <raphael.felber at agroscope.admin.ch> wrote: Dear all > > I'm a newbie regarding netcdf data. Today I realized that I maybe do not > understand some basics of the netcdf. I want to create a *.nc file > containing three variables for Switzerland. All data outside of the country > are NAs. The third variable is calculated from the first two

Hi List, I am trying to plot a grid with an overlayed height. I have a dataframe with four variables: x,y,gridvalue,height. The dataframe has 2.5mio observations (ie grid points), I assign colors through the gridvalue using map_color_gradient thus producing: x,y,gridvalue,height,gridcol as variables of the dataframe. The grid dimensions are 1253 x 2001 (=2507253 data points). My attempts with

I am trying to understand how the SOM algorithm works using library(class) SOM function. I have a 1000*10 matrix and I want to be able to summarize the different types of 10-element vectors. In my real world case it is likely that most of the 1000 values are of one kind the rest of other (this is an oversimplification). Say for example: InputA<-matrix(cos(1:10),nrow=900,ncol=10,byrow=TRUE)

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 -

I have written a function which returns an "incorrect number of subscriptions error" and am unable to identify why this should happen. Any help would be gratefully received. The problem: I would like to generate combinations/permutations across different selections - for example all the combinations of "3 chosen from 6" combined with "5 chosen from 8" combined with

Has the algorithm used by batchSOM for hexagonal topology changed in some way between R 1.9.1 and 2.0.1? In comparing between the two versions, I get identical results for rectangular topology, but very different results for hexagonal topology. (I tried to find release notes for the VR bundle that might explain the changes, but was unable to locate these anywhere.) Here's the script I

Good day everyone. I have a question concerning *ggobi* and *rggobi*package. I am using R version 2.13.2 and Ubuntu 11.04. I am new to ggobi and I'm reading the book *Interactive and Dynamic Graphics for Data Analysis *. The book was published 2007. My question is: how can I export a graph for *rggobi* to pdf to include it in latex. For example: I have lots of variables in ggobi and I need to

Why when I assign 0 to an element of an integer vector does the type change to numeric? Here is a particularly perplexing example: > v <- 0:10 > v [1] 0 1 2 3 4 5 6 7 8 9 10 > class(v) [1] "integer" > v[1] <- 0 > class(v) [1] "numeric" #!! > -- View this message in context:

Why when I assign 0 to an element of an integer vector does the type change to numeric? Here is a particularly perplexing example: > v <- 0:10 > v [1] 0 1 2 3 4 5 6 7 8 9 10 > class(v) [1] "integer" > v[1] <- 0 > class(v) [1] "numeric" #!! > -- View this message in context:

Good day everyone. I have a question concerning *ggobi* and *rggobi*package. I am using R version 2.13.2 and Ubuntu 11.04. I am new to ggobi and I'm reading the book *Interactive and Dynamic Graphics for Data Analysis *. The book was published 2007. My question is: how can I export a graph for *rggobi* to pdf to include it in latex. For example: I have lots of variables in ggobi and I need to

I'd like to write some objects (eg arrays) to a log file. cat() flattens them out. I'd like them formatted as in 'print' but print only writes to stdout. Is there a simple way to achieve this result? Thanks -- View this message in context: http://www.nabble.com/print%28%29-to-file--tp24397445p24397445.html Sent from the R help mailing list archive at Nabble.com.

Suppose I have an n-diml array A and I want to extract the first "row" -- ie all elements A[1, ...] Interactively if I know 'n' I can write A[1,,,,,] with (n-1) commas. How do I do the same more generally, eg in a script? (I can think of doing this by converting A to a vector then extracting the approp elements then reshaping it to an array, but I wonder if there isn't a

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),

I have ported some R code to C to make it faster. I can perform .Call("foobar",....) once and it works fine. Absolutely correct answer. If I put a loop inside 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

Hello, I'm running into a very strange problem: > xrange <- c(-2.5,2.5) > xdim <- 100 > mobility <- 0.1 > slope <- 1.16 > urange <- slope*xrange > udim <- max(slope*xdim,5) > du <- (urange[2]-urange[1])/udim > uvec <- urange[1]+(1:udim-0.5)*du > # type dependent weight function > ckern <-