similar to: Concat Multiple Plots into one PNG figure

Hi, Suppose I have the following data frame. __BEGIN__ > library(MASS) > data(crabs) > crab.pca <- prcomp(crabs[,4:8],retx=TRUE) > crab.pca$rotation PC1 PC2 PC3 PC4 PC5 FL 0.2889810 0.3232500 -0.5071698 0.7342907 0.1248816 RW 0.1972824 0.8647159 0.4141356 -0.1483092 -0.1408623 CL 0.5993986 -0.1982263 -0.1753299 -0.1435941 -0.7416656 CW

Hi all, I am trying to capture lines of a file that DO NOT start with the following header: !, #, ^ But somehow my regex used under grep doesn't work. Please advice what's wrong with my code below. __BEGIN__ in_fname <- paste("mydata.txt,".soft",sep="") data_for_R <- paste("data_for_R/", args[3], ".softR", sep="") # my regex

Hi there, After being extremely impressed from implementing it in some customer installations, I've decided to migrate our mail infrastructure to dovecot. Being able to have /bin/checkpassword support across the board for pop, imap, and smtp authentication, as well as being able to ditch stunnel for the SSL layer...where were you in 2001?!? :) I have two concerns, the first is about the

I've tested this only with a test user. http://dovecot.org/tools/courier-dovecot-migrate.pl http://wiki.dovecot.org/Migration/Courier # Migrate Courier IMAP (any version) and Courier POP3 (v0.43+) to Dovecot v1.0 # by Timo Sirainen. This is public domain. # Usage: [--quiet] [--convert] [--overwrite] [--recursive] [<conversion path>] # --quiet: Print only errors # --convert: Do

Hi, I have two figures where I stacked together as one PNG. Top -> scatter plot Bottom -> density plot. However these two figures are squeezed together as rectangle figures each. (i.e. the y axes are compressed) Is there a way I can resize the figure? So that it can show proportional and complete plots? The code I have is the following: (I can also provide the figure if needed).

Dear all, For example I want to process set of files. Typically Perl's idiom would be: __BEGIN__ @files = glob("/mydir/*.txt"); foreach my $file (@files) { # process the file } __END__ What's the R's way to do that? - Gundala Viswanath Jakarta - Indonesia

Hi, Currently I have a density plot generated with this snippet. Is there a way I can add a line curve on top of it? I mean in one figure __BEGIN__ myhist <- hist(x col="blue", main = "Density Plot", xlab = "Exp Level", ) __END__ - Gundala Viswanath Jakarta - Indonesia

Dear all, Does R has any function/package that can pack and unpack string into bit size? The reason I want to do this in R is that R has much more native statistical function than Perl. Yet the data I need to process is so large that it required me to compress it into smaller unit -> process it -> finally recover them back again into string with new information. In Perl the

Hi, How can I partitioned an example vector like this > print(myvector) [1] 30.9 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 into the following pairwise partition: PAIR1 part1 = 30.9 part2 = 60.1 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 PAIR2 part1 = 30.9 60.1 part2 = 70.0 73.0 75.0 83.9 93.1 97.6 98.8 113.9 .... PAIR9 part1 = 30.9

Hi all, I have the following named list: > print(y) $`200052_s_at` [1] -1066.975 -1063.893 -1062.815 -1062.121 -1059.004 $`200071_at` [1] -959.823 -953.980 -953.886 -948.781 -974.890 $`200084_at` [1] -1135.804 -1132.863 -1128.197 -1128.633 -1125.890 What I want to do is to iterate this name list and process its members. To do that I attempt the following code (but failed): __BEGIN__ ny

Dear all, I found that printing with 'cat' is very slow. For example in my machine this snippet __BEGIN__ # I need to resolve to use this type of loop. # because using write(), I need to create a matrix which # consumes so much memory. Note that "foo, bar, qux" object # is already very large (>2Gb) for ( s in 1:length(x) ) {

Hi, I have the following dataset (simplified for example). __DATA__ 300.35 200.25 104.30 22.00 31.12 89.99 444.50 22.10 43.00 22.10 200.55 66.77 Now from that I wish to do the following: 1. Compute variance of each row 2. Pick top-2 row with highest variance 3. Store those selected rows for further processing To achieve this, I tried to: a) read the table and compute variance for each row,

Hi, With the following codes, I attempt to convert the data.frame into a matrix. However I notice that data.matrix function doesn't seem to work. __ BEGIN__ dat <- read.table("mydata", comment.char = "!" , na.strings = "null"); # Select n-genes by random sample # n = 1 nosamp <- 1 geneid <- sequence(nrow(dat)) geneid.samp <- sample(geneid,nosamp)

Hi all, I have the following data in which I want to parse and store them in a list __DATA__ > print(comp.ll) [1] "\tGene 11340 211952_at RANBP5 k= 1 LL= -970.692 " [2] "\tGene 11340 211952_at RANBP5 k= 2 LL= -965.35 " [3] "\tGene 11340 211952_at RANBP5 k= 3 LL= -963.669 " [4] "\tGene 12682 213301_x_at TRIM24 k= 1 LL= -948.527 "

I've been working on a revised version of prcomp and princomp. Below is my current draft of prcomp, which is marginally different from V&R. I've added center and scale as optional arguments. However, scale causes the following: > zi _ prcomp(iris[,,2]) Warning: ignored non function "scale" because scale is both a variable and a function. Is there any way to avoid this

How does one rotate the loadings from a principal component analysis? Help on function prcomp() from package mva mentions rotation: Arguments retx a logical value indicating whether the rotated variables should be returned. Values rotation the matrix of variable loadings (i.e., a matrix whose olumns contain the eigenvectors). The function princomp returns this in the element

Hi, I'm having a mental block as to how I can automatically assign filenames to the output of the following code. I am wishing to create a separate .png file for every image created, each of them having a sequential filename ie "sourcefile_index.png" so that I can create a movie from them. Please could someone tell me where I am going wrong? the following code works fine and

Dear R users, i would like to apply a PCA on image data for data reduction. The image data is available as three matrices for the RGB values. At the moment i use x <- data.frame(R,G,B)#convert image data to data frame pca<-princomp(x,retx = TRUE) This is working so far. >From this results then i want to create a new matrix from the first (second..) principal component. Here i stuck.

Hi all, After running this code (attaches is the input file): dat <- read.table("gene_prob.txt", sep = "\t") n <- length(dat$V1) print(n) print(dat$V1) I get this print out. ...... [8541] LOC552889 GPR15 SLC2A11 GRIP2 SGEF [8546] PIK3IP1 RPS27 AQP7 8548 Levels: 3.8-1 A2M A4GALT A4GNT AAAS AAK1 AAMP AANAT AARSD1 AASS ...

Dear all, In general practice one would slurp the whole file using this method before processing the data: dat <- read.table(filename) or variations of it. Is there a way we can access the file line by line without slurping/storing them into object? I am thinking something like this in Perl: __BEGIN__ open INFILE, '<' , 'filename.txt' or die $!; while (<INFILE>) {