similar to: Why is model.matrix creating 2 columns for boolean?

Apparently Scheme is clever and can turn certain apparently recursive function calls into into non-recursive evaluations. Does R do anything like that? I could find no reference to it in the language manual. What I'm wondering is whether there are desirable ways to express recursion in R. Thanks. -- Ross Boylan wk: (415) 514-8146 185 Berry St #5700

Is there any good source of information on how S4 classes (and methods) work from C? E.g., for reading how to read a slot value how to invoke a method how to test if you have an s4 object For writing, how to make a new instance of an S4 object. I've found scattered hints in the archive, including a link to a talk on this subject "I am using C code to create an S4 object based on

I'd like to evaluate a function at each point on a 2 or 3-D grid. Is there some function that already does this, or generates the grid of points? My search has led me to the grid and lattice packages, and I found a reference to the sp package (e.g., SpatialGrid) for this. There are things in there that might be relevant, but at first blush many of them are embedded in other concepts (grobs,

Is there a way to control the aspect ratio of plots using ggplot? Specifically, I'm using the formula=a~b argument to produce a grid of plots, but the overall width of the result seems to vary for reasons that are obscure to me. This affects not only the appearance of the plots but the amount of space available for the title (which seems to be right justified relative to the right edge of the

I would like to define a function using symbols, but freeze the symbols at their current values at the time of definition. Both symbols referring to the global scope and symbols referring to arguments are at issue. Consider this (R 2.4.0): > k1 <- 5 > k [1] 100 > a <- function(z) function() z+k > a1 <- a(k1) > k1 <- 2 > k <- 3 > a1() [1] 5 > k <- 10 >

I'm invoking R from withing a shell script like this R --no-save --no-restore --gui=none > `hostname` 2>&1 <<BYE # various commands here BYE I would like to regain control from the invoking terminal at some point. I tried source(stdin()) but got a syntax error, presumably stdin is the little shell here snippet (the part between <<BYE and BYE). Is there some way to

Hi, I've been investigating the StructurizeCFG pass, and it looks like it has trouble handling CFG edges that break out of a loop and go directly to the function exit. Am I running up against a bug in the structurizer, or a general limitation of the algorithm used? As an aside, is there any documentation for the algorithm used? Is it based on a published paper? The input IR I have is the

I would like to checkpoint some of my calculations in R, specifically those using optim. As far as I can tell, R doesn't have this facility, and there seems to have been little discussion of it. checkpointing is saving enough of the current state so that work can resume where things were left off if, to take my own example, the system crashes after 8 days of calculation. My thought is that

Eli, Using the variables from the original IR, assuming tmp == tmp1 and assume the value is not nan ogt(tmp, tmp1) is !isnan(tmp) && !isnan(tmp1) && tmp > tmp1, or false ule(tmp, tmp1) is isnan(tmp) || isnan(tmp1) || tmp <= tmp1, or true So, this is invalid, or am I misunderstanding what ogt and ule stand for? Assuming this is valid, why convert comparison instructions

During R CMD check I get this: ** building package indices ... Error in eval(expr, envir, enclos) : could not find function "readingError" Execution halted ERROR: installing package indices failed The check aborts there. readingError is a function I just added; for reference setClass("readingError", contains="matrix") readingError <- function(...)

I have some calculations that require persistent state. For example, they retain most of the data across calls with different parameters. They retain parameters across calls with different subsets of the cases (this is for distributed computation). They retain early analysis of the problem to speed later computations. I've created an S4 object, and the stylized code looks like this calc

I've run into an unpleasant oddity involving the interaction of environments and generic functions. I want to check my diagnosis, and see if there is a good way to avoid the problem. Problem: A library defines "foo" <- function(object) 1 setMethod("foo", c("matrix"), function(object) 30) After loading the library foo(0) is 1 foo(matrix()) is 30 foo is a

I have some C data I want to pass back to R opaquely, and then back to C. I understand external pointers are the way to do so. I'm trying to find how they interact with garbage collection and object lifetime, and what I need to do so that the memory lives until the calling R process ends. Could anyone give me some pointers? I haven't found much documentation. An earlier message

On Thu, Nov 8, 2018 at 11:35 PM Fabian Giesen via llvm-dev < llvm-dev at lists.llvm.org> wrote: > What is so complicated about these? Shouldn't they just correspond to > two compares + selects? > > To give a concrete example, x86 MIN[SP][SD] and MAX[SP][SD], > respectively, correspond exactly to > > MIN*: select(a < b, a, b) (i.e. "a < b ? a : b")

On Mon, Nov 10, 2008 at 5:00 PM, Villmow, Micah <Micah.Villmow at amd.com> wrote: > Eli, > Using the variables from the original IR, > assuming tmp == tmp1 and assume the value is not nan > ogt(tmp, tmp1) is !isnan(tmp) && !isnan(tmp1) && tmp > tmp1, or false > ule(tmp, tmp1) is isnan(tmp) || isnan(tmp1) || tmp <= tmp1, or true Correct; in fact, ogt and

1. promptClass generated a file that included \section{Methods}{ No methods defined with class "mspathDistributedCalculator" in the signature. } Yet there are such methods. Is this a not-working yet feature, or is something funny going on (maybe I have definitions in the library and in the global workspace...)? 2. Is the \code{\link{myS4class-class}} the proper way to cross-reference a

In the documentation for my package I would like to reference the Rmpi documentation. I started with \link{Rmpi}, which caused R CMD check to complain that it could not resolve the link. Since Rmpi wasn't loaded, this isn't surprising. Ideally the user would see Rmpi, but the link would go to Rmpi's Rmpi-pkg. It's not clear to me if this is possible. I've combined two

I discovered the following behavior when source'ing the same file repeatedly as I edited it. My generic stopped acting like a generic. I can't tell from the docs what, if any, behavior is expected in this case. R 2.4.0 > foo <- function(object) 3 > isGeneric("foo") [1] FALSE > setMethod("foo", "matrix", function(object) 4) Creating a new

I have a single data file inputs.RData that contains 3 objects. I generated an Rd page for each object using prompt(). When I run R CMD check I get * checking for code/documentation mismatches ... WARNING Warning in utils::data(list = al, envir = data_env) : data set 'gold' not found (gold is one of the objects). This appears to be coming from the codocData function defined in

I've made a package for which R CMD build isn't producing very satisfactory results. I'll get to the details in a moment. I wonder if it would make sense to have my own makefiles (which already exist and are doing quite a lot) produce the .tar.gz file ordinarily produced by R CMD build. As far as I can tell, R CMD build basically tars up of the project directory after running some