search for: convergi

Anyone have luck with pxechn32 and bootmgfw.efi? I'm getting the "Unable to retrieve first package" issue as reported by others. Really, any advice for UEFI booting into a winpe environment off of pxelinux 6.03 would be beneficial. Jason Jones Sr. Associate, Network Services | End User Computing 3947 N Oak St Ext | Valdosta, GA 31605 O +15137844955 E jason.s.jones at

Thanks a lot, James!! The problem is fixed. On the version 1.4.0 Mac/darwin (the latest available version for this system) the function read.table (which is called from read.delim etc., too) has the bug you explained. Inserting the row nlines <- nlines+1 after lines <- c(lines, line) removes this bug. M. On Friday, February 22, 2002, at 02:33 PM, james.holtman at convergys.com

I generated a PDF output file of 10 plots. When I try to view it with Adobe reader (R4 & R5), it will lockup the reader (it is consuming 100% of the CPU) after presenting the 4th plot. I can generate the plots just fine in Windows and as a postscript file reading it with GSview. Is there anyway to tell what might be wrong with the PDF output? The file is 890KB in size if anyone would like

Hi all, I've got a matrix of fractional data that is all positive and greater than zero that I would like to "loosely" classify, for lack of a better word. It looks something like this : 1.07 1.11 1.27 1.59 0.97 0.76 2.23 0.98 0.71 0.88 1.19 1.02 What I'm looking for is a way to round these numbers to the nearest 0.25, i.e. the above matrix would be

I have a function that does some plotting. I then add lines to the plot. If executed one line at a time, there is not a problem. If I execute the function, though, I get: Error in ans[[1]] : subscript out of bounds This always occurs after the second lines command, and doesn't happen with all of my data points (some do not have errors). Any ideas? Thanks, Sean

Dear R users and Helpers I am beginner with using R and interested in carrying out certain task for my statistical research. I am reading data for a text file, which could contain data in following pattern x y 8 10 11 14 16 16 18 15 6 20 4 4 20 18 As per the example I have two columns and 7 rows of data in each. However is real life data situation I may not know how many columns are present

Dear R-Helpers, I have a matrix where the first column is known. The second column is the result of multiplying this first column with a constant "const". The third column is the result of multiplying the second column with "const"..... So far, I did it like this (as a simplified example): nr.of.columns <- 4 myconstant <- 27.5 mymatrix <- matrix(numeric(0), nrow=5,

hi, I'd like to extract data from very large files (ca 1-2 Mio lines), and I already know which lines of these files I need. Is there a way to do it without filling the memory with the whole file content? The lines I need are randomly distributed within the files. Thanks, Marc -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at

what about using "mapply"? splitted.value<-with(x.1, split(VALUE, GROUP)) splitted.freq<-with(x.1, split(FREQUENCY, GROUP)) mapply(weighted.mean, splitted.value, w=splitted.freq) Stefano >-----Messaggio originale----- >Da: r-help-bounces at stat.math.ethz.ch >[mailto:r-help-bounces at stat.math.ethz.ch]Per conto di >james.holtman at convergys.com

I'm clustering using kmeans, and it doesn't accept NA. if NA occurs in a column of the data frame, it occurs in every column, including column 1. they say that a (good) programmer can write FORTRAN in any language, so I came up with this, where tbl is the data frame containing NA - > newtbl<-NULL > for (i in 1:length(tbl)){if (!is.na(tbl[1,i])){ + newtbl<-if

I have been using SPLUS on UNIX to do performance analysis of our computers and have some matrices that are about 15M rows with 8 columns. These are 'integers' and therefore take up about 500M of memory. I run on a system with 2G of memory and will utilize over a 1G when processing this data. I am considering using R and was wondering how large addresses spaces are handled under

The following script works fine in R 1.9.1. It was creating a PDF file with the graphs in it. In R 2.0.0, I got the error message below. I tried the same script just outputting to Windows and postscript and the output was OK. The error message only showed up when trying to create a PDF file. > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386,

James, thanks for the response. I understand now my puzzle. tmp <- data.frame(y1=1:4, f1=factor(c("A", "B", "C", "D"))) tmp$y2 <- NA tmp[1:2, "y2"] <- 2 Does the job. I see that I should add a full column. In my case adding full column of NAs and then adding values, solves my problems. Thanks to all. james.holtman at convergys.com

Hi, is there a way to reference to a data object without copying it? For example I have a huge matrix called dist and I want two objects obj1 and obj2 to have a memeber dist that points to the matrix, but I don't want, for memory reasons, to copy the matrix twice. As far as I understand the following code will generate three copies of my data: dist <- some_code_that_generates_data

Hi All, I have a function, f(x,y) I have a matrix of data, m, with the 1st column is x and the 2nd column is y What's the best way to get f(x,y) for each row of the matrix? I tried result<-f(m[,1],m[,2]) but it doesn't work. Thanks! Bing --------------------------------- 1060 Commerce Park Oak Ridge National Laboratory P.O. Box 2008, MS 6480 Oak Ridge, TN 37831-6480 Phone:

I am using Version 1.3.0 (2001-06-22) on Windows/2000. Had loaded the 'lattice' and 'grid' libraries and was trying the example on densityplot: data(singer) densityplot( ~ height | voice.part, data = singer, layout = c(2, 4), xlab = "Height (inches)", bw = 5) ## Using a predefined panel function to fit a normal distribution

Hi, there, I am using PC window version R and dealing with big dataset usually. May anyone let me whether the maximal dataset size in R is limited by computer memory or hard drive capacity? Thanks in advance. Yiling Cheng, M.D., Ph.D. Project Manager The Cooper Institute for Aerobics Research 12330 Preston Road, Dallas, Texas 75230 phone: (972) 3413248; Fax: (972) 3413224

This sequence of commands worked fine in R.1.4.1. The data file was the same in both instances: > acct.log <- read.table(file, col.names=c('cmd', 'user', 'start', 'end', + 'elapsed', 'sys', 'usr', 'cpu', 'char', 'blocks'), + colClasses=c('NA', 'NA', rep('numeric',

I was trying to read in a file and delete lines that did not have the correct number of fields on them. I was reading the file as one character vector per line using 'scan' with sep='\n'. I was then using 'count.fields' with 'textConnection' to the object I just read in. I thought at first the system was locked up, but further testing showed that the

The 'read.table' function appears to be up to 10X slower in R 1.4.0 than R 1.3.1 for some of the data sets I read in. I was comparing the source code for the 2 versions and see that it was rewritten in R 1.4.0. I think I found out what part of the problem might be. I was comparing R1.3.1 and R1.4.0 code and it appears that a statement is missing in some of the code for R 1.4. This is