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Below is an example of using backtrace() obtained from man backtrace and the test results: $ gcc bt.c -o bt-gcc $ ./bt-gcc 4 backtrace() returned 4 addresses ./bt-gcc() [0x4007e3] ./bt-gcc() [0x400874] ./bt-gcc() [0x40089b] ./bt-gcc() [0x400894] $ llvm-gcc bt.c -o bt-llvm-gcc $ ./bt-llvm-gcc 4 backtrace() returned 4 addresses ./bt-llvm-gcc() [0x40074b] ./bt-llvm-gcc() [0x400809]

Hi James, We've indeed passed the appropriate (and even excessive) flags to the appropriate pipeline parts, that is: llvm-gcc -O1 -fno-omit-frame-pointers -g $in -emit-llvm -S -o $name.ll llc --disable-fp-elim $name.ll -o $name.S g++ -fno-omit-frame-pointers -c $name.S , but that didn't work Alex On Tue, Apr 5, 2011 at 4:40 PM, James Molloy <James.Molloy at arm.com> wrote:

On Tue, 6 Jun 2006, Lan Bai wrote: > Hi Chris, I want to use some new call inst to initialize some new global > variables at runtime (assign the return value of the call inst to the global > variable). > > Now I have successfully inserted the new global variables to the global list, > and inserted the new call instructions to the instruction list. But I don't > know

I've defined the following for objects of a class called jml summary.jml <- function(object, ...){ tab <- cbind(Estimate = coef(object), StdError = object$se, Infit = object$Infit, Outfit = object$Outfit) res <- list(call = object$call, coefficients = tab, N = nrow(object$Data), iter = object$Iterations) class(res) <- "summary.jml" res }

> On Jan 26, 2018, at 9:51 AM, MacQueen, Don <macqueen1 at llnl.gov> wrote: > > What Dave said, plus here's a hint. Try this example (which uses base graphics): > > plot(1:5) > plot(1:5, cex.lab=2) > > Then look at the help page for par > help('par') > or > ?par > to search for other graphics parameters (base graphics) you can use to

What Dave said, plus here's a hint. Try this example (which uses base graphics): plot(1:5) plot(1:5, cex.lab=2) Then look at the help page for par help('par') or ?par to search for other graphics parameters (base graphics) you can use to change various things. Success will depend, as Dave indicated, on how the package author handled the plotting options in rsFit(). -Don --

I don't understand why I get the following results. I define two classes 'Base' and 'Derived', the latter of which 'contains' the first. I then define a generic method 'test' and overload it for each of these classes. I call 'callNextMethod()' in the overload for Derived. From the output, it appears that the overload for Base gets called twice. Why is

Hello, How does one specify a formula to lm inside a function (with variable names not known in advance) and have the formula appear explicitly in the output? For example, f <- function(d) { in.model <- sample(c(0,1), ncol(d)-1, replace=T) current.model <- lm(paste(names(d)[1], "~", paste(names(d[2:ncol(d)])[which(in.model == 1)], collapse= "+")), data=d) #***

Hi I have a couple of functions that work on the object created by another R command and then print out or summarise the results of this work. The main function is defined as: hotelling.t <- function(obj) { #internal commands } I then have print.hotelling.t() that takes the list returned by hotelling.t and prints it with some extra significance calculations, formatting, etc. I want to

I run a hotdesking system based on the example from Asterisk: The Definitive Guide. Calls come into the [hotdesk] context, which verifies the phone has a logged in user and sends the call to users,${EXTEN},1 if there is a user logged in. The [users] context then includes several other contexts for internal/external call handling, as follows: [users] include => internal include =>

Dear R-devel list members, Ben Fairbank draw it to my attention that factanal() (in the stats package) doesn't report factor correlations for oblique rotations. Looking at the source, I see that factanal also doesn't save the factor-transformation (rotation) matrix from which these correlations can be computed. I've modified the source, attached below, so that the transformation

Dear all, After a thorough research, I still find myself unable to find a function that does linear regression of 2 vectors of data using the "total least squares", also called "orthogonal regression" (see : http://en.wikipedia.org/wiki/Total_least_squares) instead of the "ordinary least squares" method. Indeed, the "lm" function has a

R developers, I have a first attempt to make an aov function. Eventually I want to build in Error() structure, but first I am trying to get this presentable for balanced data with only a single stratum, just using residual error. I am following R. M. Heiberger's Computation for the Analysis of Designed Experiments, Wiley (1989) I a using a wrapper (aov.bal) to call the

--=-hiYzUeWcRJ/+kx41aPIZ Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: 8bit Hi, on March 10 I filed a wishlist bug report asking for the inclusion of some changes to factanal() and the associated print method. The changes were originally proposed by John Fox in 2005; they make print.factanal() display factor correlations if factanal() is called with rotation =