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...: 00 Id: 00 Lun: 00 Vendor: HP Model: Ultrium 5-SCSI Rev: Z58Z Type: Sequential-Access ANSI SCSI revision: 06 Host: scsi0 Channel: 00 Id: 00 Lun: 01 Vendor: QUANTUM Model: Scalar i40-i80 Rev: 135G Type: Medium Changer ANSI SCSI revision: 03 # mtx -f /dev/sg0 inquiry mtx: Request Sense: Long Report=yes mtx: Request Sense: Valid Residual=no mtx: Request Sense: Error Code=70 (Current) mtx: Request Sense: Sense Key=Illegal Request mtx: Request Sense: FileMark=no mtx: Request Sense: EOM=no mtx: Request Sense: ILI=no mtx: Request Sense: Additiona...

...of the matrix in a vector. I tried to do the job by using two for-loops but it doens't seem to be a clever way, and I'd like to know a more efficient code for a large matrix of thousands of rows and columns. Below is my code for your reference. Thanks a lot. John #################### # mtx.sym is a symmetric matrix > my.ftn <- function(size_mtx, mtx) { + my.vector <- c() + for ( i in 1:size_mtx ) { + cat(".") + for ( j in 1:size_mtx ) { + if ( upper.tri(mtx)[i,j] ) { + my.vector <- c(my.vector, mtx[i,j]) + }}} + cat("\n") + } > # if I have a matrix...

...) / ((k-1) * ((n-1) - (k-1)*epsiGG)) c(epsiGG,epsiHF) } # three factors, facROI,facCond,facSubj # facROI,facCond are main effects, facSubj is "repeatedness" # G-G and H-F corrections for a main effect # we do the gghf stuff for the ROI, which means ROIs in columns, # subjects in rows mtx <- NULL for (iROI in 1:length(unique( facROI ))) { for (iSubj in 1:length(unique( facSubj ))) { mtx <- c(mtx, mean(vecData[facROI==unique(facROI)[iROI] & facSubj==unique(facSubj)[iSubj]]) ) } } mtx <- matrix(mtx,ncol=length(unique( facROI )),byro...

...) / ((k-1) * ((n-1) - (k-1)*epsiGG)) c(epsiGG,epsiHF) } # three factors, facROI,facCond,facSubj # facROI,facCond are main effects, facSubj is "repeatedness" # G-G and H-F corrections for a main effect # we do the gghf stuff for the ROI, which means ROIs in columns, # subjects in rows mtx <- NULL for (iROI in 1:length(unique( facROI ))) { for (iSubj in 1:length(unique( facSubj ))) { mtx <- c(mtx, mean(vecData[facROI==unique(facROI)[iROI] & facSubj==unique(facSubj)[iSubj]]) ) } } mtx <- matrix(mtx,ncol=length(unique( facROI )),byro...

...eat ways to deal with them. (a) When using "apply" row-wise to a matrix, it returns the results column-wise, and to preserve the original orientation, I've to do a transpose. E.g. I've to keep doing a transpose, which I consider to be quite annoying. transformed.mtx <- t(apply( mtx, 1, exp)) (b) When extracting 2 or more columns of a matrix, R returns the result as a matrix, BUT when extracting just one column, it returns a vector/array, rather than a matrix, so I've to keep doing as.matrix, which is annoying. sub.mtx <- as.matrix(mtx...

Hi Suppose I have a matrix (cohort are rows and years are columns) [2000] [2001] [2002] [2003] [C1] 0.01 0.03 0.02 0.09 [C2] 0.06 0.05 0.07 0.11 [C3] 0.1 0.5 0.4 0.98 [C4] 0.7 0.6 0.2 0.77 I want to extracts the diagonals to get a matrix which looks like this (C1 becomes C2 in 2002, C2 becomes C3 in 2003

...e blue "bedGz" category. What I would like is that categorical points are joined by lines in lexicographic order, to match ordering of labels on the x-axis. How do I modify the xyplot command so that the lines are joined in correct order? Here is the code I am using to draw my xyplot: mtx <- read.table(mtxf.in, as.is=F, sep="\t", quote='', header=T, stringsAsFactors=T) attach(mtx)...

My unit's firmware: library 05.03, tape d22h, shows the device as set to random mode. But mtx -f /dev/st0 status gives an error that google says the device is in sequential mode. dmesg|grep -i hp does reflect CentOS thinks the device is a sequential unit. I've tried this with Fedora 8, too, and both show the same, so it is either an issue with CentOS/Fedora RPMs, or the version of...

Hello all, To calculate the power of a matrix, I used the command "mtx.exp(X, n)", but there is an error saying "Error: couldn't find function "mtx.exp"". How can I deal with this problem? Jing

Dear all, I would like to compute power of a square non symmetric matrix. This is a part of a simulation study. Matrices are quite large (e.g., 900 by 900), and contains many 0 (more than 99 %). I have try the function mtx.exp of the Biodem package: library(Biodem) m <- matrix(0, 900, 900) i <- sample(1:900, 3000, replace = T) j <- sample(1:900, 3000, replace = T) for(x in 1:3000) m[i[x],j[x]] <- runif(1) system.time(mtx.exp(m, 20)) This returns (sorry, in french): utilisateur syst?me ?c...

Hello, I'm new on this list. First of all, thank you to all the developers of this great project! At the moment there is only an application that keeps me on both macos and windows, its name is PWGL a free environment for computer assisted composition in openGL. (http://www2.siba.fi/PWGL/) I'm running Ubuntu 8.04 and wine 0.9.59. I have to say that I also installed vcrun2005 and

...e a data.frame or matrix that has the indices" Actually, it must be a matrix, indices can't be of type list. A way to avoid loops/apply altogether, and much faster, is the one creating K3 (K is the result from the op.) n <- 20 t2 <- system.time({ K2 <- array(0,dim=c(n,n,n,n)) mtx <- data.matrix( expand.grid(x1=1:n,x2=1:n,y1=1:n,y2=1:n) ) K2[mtx] <- apply(mtx, 1, function(x) x["x1"]*x["y2"] - sin(x['x2']*x['y1']) ) }) t3 <- system.time({ K3 <- array(0,dim=c(n,n,n,n)) mtx <- data.matrix( expand.grid(x1=1:n,x2=1:n,y1=1:n,y2=...

Dear all, I have a population with three age-classes, at time t=0 the population is: n.zero <- c(1,0,0) I have a transition matrix A which denotes "fertility" and "survival": A <- matrix(c(0,1,5, 0.3,0,0, 0,0.5,0), ncol=3, byrow=TRUE) To obtain the population at t=1, I calculate: A %*% n.zero To obtain the population t=2, I calculate: A %*% (A %*% n.zero) ... and so

Dear R colleagues, as a result of my calculations regarding the inter-observer-variability in bronchoscopy, I get a confusion matrix like the following: 0 1 1001 1010 11 0 609 11 54 36 6 1 1 2 6 0 2 10 14 0 0 8 4 100 4 0 0 0 0 1000 23 7 12 10 5 1001 0 0 4 0 0 1010 4 0 0 3 0 1011 1 0 1 0 2 11

...out it. I've tried to do it in several ways, but this is the only one that gives a somewhat reasonable result. Can anyone give me a suggestion of how I could do this, where I could find information about it etc? Google doesn't help much except more SAS examples...:-( hf <- function(mtxCov,ncol,nrow) { X <- mtxCov*(nrow-1) r <- length(X[,1]) D <- 0 for (i in 1: r) D<- D+ X[i,i] D <- D/r SPm <- mean(X) SPm2 <- sum(X^2) SSrm <- 0 for (i in 1: r) SSrm<- SSrm + mean(X[i,])^2 epsilon <- (ncol^2*(D-SPm)^2) / ((ncol-1) * (SPm2 - 2*ncol*S...

I have an array with names which contain multibyte characters. ?When I try to write the array to a file using write.table and row.names = T I receive an error message when the first such name is encountered, saying that I have not specified the option to generate NA instead. ?I really would be satisfied if the row name in the file were exactly what is displayed when I print the array on the

...ll! First of all, I'd like to apologize for my poor English. It's for years I don't use it. This is a R-version of a function I wrote a long ago for my HP48 calculator. It works with the binary expression of the power and just need to duplicate the mem used by X. Hope this helps. mtx.exp<-function(X,n) #Function to calculate the n-th power of a matrix X; { phi <- diag(rep(1,length(X[1,]))) pot <- X #This is the first power of the matrix. while (n > 0) { if (n%%2) { phi <- phi%*%pot; } n <- n%/%2; pot <- pot %*% pot; } return(phi);...

Hello! im testing lazy_expunge_only_last_instance here and it seems it works wrong with IMAP MOVE IN: 14 uid move 13 "INBOX" OUT: * OK [COPYUID 1188569061 13 34] Moved UIDs. * 5 EXPUNGE 14 OK Move completed. dovecot.log: 2013-06-14 10:56:06 imap(test13 at mtx.ru): Info: copy from Test: box=INBOX, uid=34, msgid=<1294858169.32435.3.camel at int.office.matrix>, size=996, from=Pavel Volkovitskiy <int at mtx.ru>, subject=test, flags=(\Seen) 2013-06-14 10:56:06 imap(test13 at mtx.ru): Info: copy from Test: box=.EXPUNGED/Test, uid=9, msgid=<1294...

...via the following code: ## observations of the reference obsValues<-factor(unlist(input[,-c(1,ncol(input))])) ## observations of the observers refValues<-factor(input[,ncol(input)]) ## data.frame that relates observations of observers and reference RefObs<-data.frame(refValues, obsValues) mtx<-table( RefObs$obsValues, RefObs$refValues, dnn=c("observers", "reference"), useNA=c("always") ) And now the problem: I need to sort the levels/classes of the table. Both axes shall be ordered 1st according to...

...l has >> the appropriate values of that area. >> >> A+B => Combine these two and have a function that returns the >> appropriate value of a subarea given its coords. Attention my area >> spans from -1 to 1 in y plane and from -1 to 1 in the x plane. > > mtx <- matrix(seq(1:36), nrow=6, byrow=TRUE, dimnames=list(x=seq(-1, 1, length=7)[-7], y=seq(-1, 1, length=7)[-7]) ) > mtx y x -1 -0.666666666666667 -0.333333333333333 0 0.333333333333333 0.666666666666667 -1 1 2...