similar to: Resume processing after warning handler.

>From https://github.com/HenrikBengtsson/Wishlist-for-R/issues/70 : ... and follow up note from 2018-03-15: Ouch... in R-devel, stopifnot() has become yet 4-5 times slower; ... which is due to a complete rewrite using tryCatch() and withCallingHandlers(). >From https://stat.ethz.ch/pipermail/r-devel/2017-May/074256.html , it seems that 'tryCatch' was used to avoid the following

My points: - The 'withCallingHandlers' construct that is used in current 'stopifnot' code has no effect. Without it, the warning message is the same. The overridden warning is not raised. The original warning stays. - Overriding call in error and warning to 'cl.i' doesn't always give better outcome. The original call may be "narrower" than 'cl.i'. I

Dear expeRts, I am struggling with warning/error handling. I would like to call a function which can produce either a) normal output b) a warning c) an error Since the function is called several (thousand) times in a loop, I would like to proceed "quietly" and collect the warnings and errors [to deal with them at a later point]. I have seen constructs with tryCatch (which can

Not desperately important, but nice to have and possibly of use to others, is the ability to suppress specific warnings rather than suppressing warnings indiscriminately. I often know of a specific warning that I want to ignore (because I know that's it's a false positive/ignorable), but the current design of suppressWarnings() forces me to ignore *any* warnings coming from the

Hello, all, I am running some simulations to estimate power for a complicated epidemiological study, and am using lme and lmer to get these estimates. I have to run a few thousand iterations, and once in a great while, an iteration will create fake data such that the model won't converge. I see from Google searches that this is not an uncommon situation. My question: is there a way to

Hello, 1. The Situation : ------------------------ The stack traceback is not available when error ouccured in a try(....) -- test.R -------------------------------- f<-function(a){ return ( log(a) ) } try(f("A")) traceback() ------------------------------------------- I get the following message : > try(f("A")) Error in log(x) : Non-numeric argument to mathematical

I'd like do a simple xyplot with customized order of panels and try to understand how to use index.cond for that. Several attempts didn't deliver the correct results. Now, I noticed the following: > p <- xyplot(dur~roi|trial, data) > p$index.cond [[1]] [1] 1 2 3 4 5 6 7 8 9 10 These numbers are "valid indexing vector for the integer vector

Hi, folks! I'm trying to pull in data using read.csv("my URL goes here"), and it really works fantastically. Amazing to pull in live data right off the internet, into RAM, and get busy... however... occasionally there is a server problem, or the data are not up yet, and instead of pushing through a nice CSV file, the server sends a 404 "Not Found" page... Since the

Dear list! > gregexpr("a+(b+)", "abcdaabbc") [[1]] [1] 1 5 attr(,"match.length") [1] 2 4 What I want is the offsets of the matches for the group (b+), i.e. 2 and 7, not the offsets of the complete matches. Is there a way in R to get that? I know about gsubgn and strapply, but they only give me the strings matched by groups not their offsets. I could write

Hi list! I have a large matrix which I'd like to partition into blocks and for each block I'd like to compute the mean. Following a example where each letter marks a block of the partition: a a a d g g a a a d g g a a a d g g b b b e h h b b b e h h c c c f i i I'm only interested in the resulting matrix of means. How can this be done efficiently?

Hi list! An operation that I often need is splicing two vectors: > splice(1:3, 4:6) [1] 1 4 2 5 3 6 For numeric vectors I use this hack: splice <- function(x, y) { xy <- cbind(x, y) xy <- t(xy) dim(xy) <- length(x) * 2 return(xy) } So far, so good (?). But I also need splicing for factors and I tried this: splice <- function(x, y) { xy <-

Hi, I have a data frame and want to merge adjacent rows if some condition is met. There's an obvious solution using a loop but it is prohibitively slow because my data frame is large. Is there an efficient canonical solution for that? > head(d) rt dur tid mood roi x 55 5523 200 4 subj 9 5 56 5523 52 4 subj 7 31 57 5523 209 4 subj 4 9 58 5523 188 4 subj 4 7

Hi list, I have a function that detects saccadic eye movements in a time series of eye positions sampled at a rate of 250Hz. This function needs three vectors: x-coordinate, y-coordinate, trial-id. This information is usually contained in a data frame that also has some other fields. The names of the fields are not standardized. > head(eyemovements) time x y trial 51

Dear list, I fitted the same GAM model using directly the function gam(mgcv) ... then as a parameter of another function that capture the warnings messages (see below). In the first case, there is no warning message printed, but in the last one, the function find two warning messages stating "matrix not positive definite" So my question is: Do I have to worry about those warnings and

Hi, I am trying to automate the creation of tables for some simply analyses. There are lots and lots of tables, thus the creation of a user-defined function to make and output them to excel. My problem is that some of the analyses have convergence issues, which I want captured and included in the output so the folks looking at them know how to view those estimates. I am successfully able to do

The suppressMessages and suppressWarnings functions currently suppress all the message or warnings that are generated by the input expression. The ability to suppress only specific messages or warnings is sometimes useful, particularly for cases like file import where there are lots of things that can go wrong. Suppressing only messages that match a regular expression has rightly been rejected

Hi list, I run R on Linux and OSX. On both systems I use R version 2.9.2 (2009-08-24) and reshape version: 0.8.2 (2008-11-04). When I do a melt with na.rm=T on a data frame I get different results on these systems: library(reshape) x <- read.table(textConnection("char trial wn p E10I13D0 4 r E10I13D0 4 a E10I13D0 4 c E10I13D0 4 t E10I13D0 4 i E10I13D0 4 c E10I13D0 4 e E10I13D0

I have a data frame called s3. This data frame has a column called saccade which has two levels 1 and -1. > head(s3$saccade, 100) [1] NA NA NA NA -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 [26] -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 [51] 1 1 1 1 1 1 1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 [76] -1 -1 -1 -1 -1

Hello, I'm trying to install KEGGSOAP with bioconductor but i'm facing this problem: /> biocLite("KEGGSOAP") BioC_mirror: http://bioconductor.org Using R version 2.15, BiocInstaller version 1.4.4. Installing package(s) 'KEGGSOAP' trying URL 'http://www.bioconductor.org/packages/2.10/bioc/src/contrib/KEGGSOAP_1.30.0.tar.gz' Content type

Hello, I try to install pbdMPI. Compilation successful, but load fails with segfault. Is anyone can help me? R version 3.0.0 pbdMPI version 0.1-6 Intel compiler version 13.1.1 OpenMPI version 1.6.4-1 CPU Intel x86_64 # R CMD INSTALL pbdMPI_0.1-6.tar.gz .. .... checking for gcc... icc -std=gnu99 checking whether the C compiler works... yes checking for C compiler default output file name...