similar to: R-3.3.3/R-3.4.0 change in sys.call(sys.parent())

Here is a case where the current scheme fails: > with(datasets::mtcars, xyplot(mpg~wt|gear)$call) xyplot(substitute(expr), data, enclos = parent.frame()) Bill Dunlap TIBCO Software wdunlap tibco.com On Thu, May 11, 2017 at 1:09 AM, Deepayan Sarkar <deepayan.sarkar at gmail.com> wrote: > On Wed, May 10, 2017 at 2:36 AM, William Dunlap via R-devel > <r-devel at

On Wed, May 10, 2017 at 2:36 AM, William Dunlap via R-devel <r-devel at r-project.org> wrote: > Some formula methods for S3 generic functions use the idiom > returnValue$call <- sys.call(sys.parent()) > to show how to recreate the returned object or to use as a label on a > plot. It is often followed by > returnValue$call[[1]] <- quote(myName) > E.g., I see

> lm2 <- function(...) lm(...) > lm2(mpg ~ wt, data=mtcars) Call: lm(formula = ..1, data = ..2) Coefficients: (Intercept) wt 37.285 -5.344 > lm2(mpg ~ wt, weights=cyl, data=mtcars) Error in eval(expr, envir, enclos) : ..2 used in an incorrect context, no ... to look in Can anyone explain why this is happening? (Obviously this is a manufactured example, but it

Hi all, It seems that there is a use case for obtaining the environment for the "top" promise. By "top", I mean following the promise chain up the call stack until hitting a non-promise. S4 data containers often mimic the API of base R data structures. This means writing S4 methods for functions that quote their arguments, like with() and subset(). The methods package

This is an expanded version of the question I tried to ask last night - I thought I had it this morning, but it's still not working and I just do not understand what is going wrong. What I am trying to do is write a wrapper for lattice xyplot() that passes a whole bunch of its secondary arguments, so that I can produce similarly formatted graphs for several different data sets. This is what

Hello All, A simple question. I get some return from the R in my C++ program (via Rcpp package). The result come, as SEXP and it should be a simple numeric variable. How to convert it to double? The code, what i use: stringstream ss; ss << "p <- predict(fit_ar11, n.ahead = 2, doplot=FALSE);" << "p$pred[1]"; SEXP ans; int iRet =

Hi, I am using RInside for one of the applications that I'm using. The error that occured is as follows. When I use R.parseEval("xyz") if the parse fails then the mb_m is not cleared and hence all subsequent calls to R.parseEval fail. example: when R.parseEval("stringConcatfactoryrandom") is executed the R instance looks like this (gdb) p R $7 = (RInside &)

That definitely looks like a bug, but not one that anyone will be eager to fix. It's very old code that tried to be clever, and that's the hardest kind of code to fix. Remember Kernighan's Law: "Everyone knows that debugging is twice as hard as writing a program in the first place. So if you?re as clever as you can be when you write it, how will you ever debug it?"

I want to use a strip.custom as with useOuterStrips for three conditioning variables. useOuterStrips restricts this to only two conditioning variables, and I cannot figure out how to write strip.custom properly to do this. library(lattice) mtcars$HP <- equal.count(mtcars$hp) #with two factors x2<-xyplot(mpg ~ disp | HP + factor(cyl), mtcars) useOuterStrips(x2) #with three factors

I am trying to plot a graph but the points on the graph should be different symbols and colors. It should represent what is in the legend. I tried using the points command but this does not work. Is there another command in R that would allow me to use different symbols and colors for the points? Thank you kindly. data(mtcars) plot(mtcars$wt,mtcars$mpg,xlab= "Weight(lbs/1000)",

Hi everyone, I've run into a bit of strange problem with implicit vs explicit printing and the call stack. I've included an example at the bottom of this email. The basic problem is that I have an S3 object with a print method. When the object is implicitly printed (ie. typed directly into the console) the function arguments in the call stack are exploded out to their actual values,

The lattice package uses special logic to allow for multiple left-hand-side variables in a formula, e.g. y1 + y2 ~ x. Is there an elegant way to do this outside of lattice? I'm trying to implement a data summarization function that logically takes multiple dependent variables. The usual invocation of model.frame( ) causes R to try to do arithmetic addition to create a single dependent

Hi, I'm working on some lattice wireframe figures that have two conditioning factors, and I want the strips labelled on the top and left of the entire plot, rather than above each individual panel. useOuterStrips() does this, but it draws internal axis lines, even after I explicitly set axis.line to 0. Is there a way to use useOuterStrips but without axis boxes? I've included a short

Hi, I would like to make a suggestion for a small syntactic modification of FUN argument in the family of functions [lsv]apply(). The idea is to allow one-liner expressions without typing "function(item) {...}" to surround them. The argument to the anonymous function is simply referred as ".". Let take an example. With this new feature, the following call

Dear list, I want the 1st, 2nd, 5th, and 6th columns of mtcars. After copying them, the columns become numeric class rather than data frame. But, when I copy rows, they data frame retains its class. Why is this? I don't see why copying rows vs columns is so different. > class(mtcars) [1] "data.frame" > head(mtcars) mpg cyl disp hp drat wt qsec vs

I'm sure this exists elsewhere, but, as a trade-off, could you achieve what you want with a separate helper function F(expr) that constructs the function you want to pass to [lsv]apply()? Something that would allow you to write: sapply(split(mtcars, mtcars$cyl), F(summary(lm(mpg ~ wt,.))$r.squared)) Such an F() function would apply elsewhere too. /Henrik On Thu, Apr 16, 2020 at 9:30 AM

Before I go and do this another way - can I check if anyone has a way of looping through data in odfWeave (or possibly sweave) to do a repeating analysis on subsets of data? For simplicity lets use mtcars dataset in R to explain. Dataset looks like this: > mtcars mpg cyl disp hp drat wt ... Mazda RX4 21.0 6 160 110 3.90 2.62 ... Mazda RX4 Wag 21.0 6 160 110 3.90

I am using R 2.8.1 and lattice to produce xyplots conditioned on two factors. What I would like is to have the scales be free between values of one factor, but some within. Thus, in the example: xyplot(mpg ~ disp | factor(gear) + factor(cyl), mtcars, scales=list(x=list(relation="free"))) rather than having the x scales be free within a gear as well, I want it to be the same for

Consider this plot: xyplot(mpg ~ disp | cyl, mtcars, strip=F, strip.left=T, layout=c(1, 3), scales=list(relation="free"), par.settings=list(strip.background=list(col="transparent"))) I want to have the "cyl" strip labels on the left side of the axis. Is this possible? Failing that, is it possible to remove the left axis and display it on the right

Hi everyone, This is about documentation for the model.frame() page. The get_all_vars() function (added in R 2.5.0) is a great addition, but the behavior of its '...' argument is different from that of model.frame() with which it is documented and this creates ambiguity. The current docs read: \item{\dots}{further arguments such as \code{data}, \code{na.action}, \code{subset}. Any