similar to: shading in image()

Hi Timo, Thanks for commenting. I feel like I have to justify why I don't want to use QEMU, which is fine since my choice is not frozen actually. QEMU is much more than what I need for dynamically instrumenting software. My goal is automated testing to find bugs, which can quickly be intensive in term of computational load. Thus I am trying to get the smallest (and fastest) tool. Even using

I have produced a series of graphs with the png command, however when I have finally printed these out the black text appears to have a colour shadow with blue or red on either side of the letter. I tried increasing my res to 1200 and this improved it somewhat, but the text is still not sharp and occassionally these "shadows" will still print. I initially thought this was an issue with

Alexandre Gouraud <alexandre.gouraud at enst-bretagne.fr> writes: > like to write the same kind of thing, but not using QEMU as they claim in > the paper, but rather with my own pin tool. You could also use valgrind to convert x86 to valgrind's IR and then write a tool to convert that IR to LLVM.

* Timo Juhani Lindfors (timo.lindfors at iki.fi) wrote: > Hi, > > Alexandre Gouraud <alexandre.gouraud at enst-bretagne.fr> writes: > > if it does not already exists, could it mean it is a nonsense, then why? > > Why don't you compile your program directly to LLVM bitcode? - In security-testing you sometimes apply black boxing. I've had a similar idea

Dear R- helpers Following a draft structure of the R script for which I am facing problem Step 1 x <- of type array with original values y <- of type array with original values Step 2 for (ctr in 1:10) { # my problem here the both x and y still show the original values from step 1 # in spite of making changes to the old values of the arrays x and y in the function function

Hallo, I have a set of S4 and S3 classes together in one script. While running this script I create a lot of new functions and objects An example for S3 and S4 classes: ## S3 classes pt <- list(x=1,y=2) class(pt) <- "xypoint" xpos <- function(x, ...) UseMethod("xpos") xpos.xypoint <- function(x) x$x ypos <- function(x, ...) UseMethod("ypos")

Dear R users I need to auto scale the left y axis in the code below, so that when I scroll left or right the left y-axis scale changes to accumulate the range of the displayed data with in the max hight of the y-axis. also how can I make the crosshair horizontal since it is only vertical in this code. this code with a kind help from "Gregory (Greg) L. Snow Ph.D." just

Hi - When using the randomForest function for regression, I get different results for mean-squared error of the predictions depending on whether or not I specify to calculate variable importance. There is an example below. I looked briefly at the source code, but couldn't find anything that would indicate why calculating variable importance would (or should) change predictions. I'm

Are the results dramatically different? The result would be expected to be somewhat different, as setting importance=TRUE would make many calls to the random number generator (for permuting OOB data in each variable), making all but the first tree in the forest different than if importance=FALSE. Cheers, Andy > From: Scott Gilpin > > Hi - > > When using the randomForest

Please see the code below. When I try to run the variogram - vg.deft<-variog(rd,uvec=10) I keep getting this error- variog: computing omnidirectional variogram Error in vector("double", length) : vector size specified is too large Also, when I try to define distance-based neighborhood - nb.tr=dist.neighbors(tr.locs,2) I get this error - Error in vector("double", length) :

Hi thank you for talking the time to help me with this. I have a sequence of numbers in a file and an equal sequence of various character, say(a b c d) each occurs more than once. I need to plot the numbers so that numbers corresponding to a in the other sequence would have green dots, those corresponding to b a red dot, nothing on c and blue square for d. i.e 2 a show a green dot 4 b show a

Hello, I have a question regarding shading regions under curves to display 95% confidence intervals. I generated bootstrap results for the slope and intercept of a simple linear regression model using the following code (borrowed from JJ Faraway 2005): > attach(allposs.nine.d) > x<-model.matrix(~log(d.dist,10))[,-1] > bcoef<-matrix(0,1000,2) > for(i in 1:1000){ +

Hi, I have a data.frame that I need to construct iteratively. At the moment, I'm doing: d<-data.frame(x=c(),y=c(),z=()); # {and, within some loop} d<-rbind(d,data.frame(x=newx,y=newy,z=newz); While this works, it is horribly verbose and probably not efficient, either. My real data.frame has, of course, many more columns, which can be of different modes. I vaguely recall that

Colleagues, I am using "nls" successfully (2.11.1, OS X) but I am having difficulties retrieving part of the output - residual sum of squares. I have assigned the output to FIT: > > FIT > Nonlinear regression model > model: NEWY ~ PMESOR + PAMPLITUDE * cos(2 * pi * (NEWX - POFFSET)/PERIOD) > data: parent.frame() > PMESOR PAMPLITUDE POFFSET >

Good afternoon, Hope you all have a wonderful day. I am glad to be here. Hope you could help me with the following errors that i have been trying to figure it all out since last week. I am using Splus from Insightful, and as i read, R and Splus are very similar. So hope you could help me. I have been continously received these error messages after i ran my small program for couple of

Hello R-users, I'm currently facing a pretty hard problem which I'm hopping you'll be able to help me with. I'm using R to create images. That alone is not the problem, the problem is that I'm using R to create 168 000 images... My code (which is given below) use different package (raster and rgdal) to import a image (size 20gig) and divide it into 168 000 pictures that are

Thanks for the reproducable example. I can confirm that it fails on my machine using survival 2-37.5, the next soon-to-be-released version, The issue is with NextMethod, and my assumption that the called routine inherited everything from the parent, including the environment chain. A simple test this AM showed me that the assumption is false. It might have been true for Splus. Working this

Dear All, I'd like to know if it is possible to create animations with R. To be specific, I attach a code I am using for my research to plot some analytical results in 3D using the lattice package. It is not necessary to go through the code. Simply, it plots some 3D density profiles at two different times selected by the user. I wonder if it is possible to use the data generated for different

Dear all, I am studying a paper (cf below) that says they have written a piece of code to translate x86 instructions to LLVM. I am interested in this, and would like to write the same kind of thing, but not using QEMU as they claim in the paper, but rather with my own pin tool. >From what I have red until now on LLVM, and my relative poor knowledge of assembly, I have the feeling that this is

In one particular situation predict.coxph gives an error message. Namely: stratified data, predict='expected', new data, se=TRUE. I think I found the error but I'll leave that to you to decide. Thanks, Chris ######## CODE library(survival) set.seed(20121221) nn <- 10 # sample size in each group lambda0 <- 0.1 # event rate in group 0 lambda1 <- 0.2 # event rate in group 1