This is where <<- is helpful: > N <- 0 ; trace(solve, quote(N <<- N + 1), print=FALSE) Tracing function "solve" in package "base" [1] "solve" > lapply(3:0, function(i)solve(diag(i,3), 1:3)) Error in solve.default(diag(i, 3), 1:3) : Lapack routine dgesv: system is exactly singular: U[1,1] = 0 > N [1] 4
You can also set options(error=recover) to look at the state of things when the error occurs. Bill Dunlap Spotfire, TIBCO Software wdunlap tibco.com > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf > Of Simon Zehnder > Sent: Tuesday, February 26, 2013 2:53 AM > To: r-help@r-project.org help > Subject: [R] Count function calls > > Dear R-users, > > I have the following problem: I am running the function 'pvcm' from the 'plm' > Panel Data > package. Inside this function 'solve' is called and gives for a certain > individual data series > an exception because of singularity. I would like to know which individual > data series > causes this error. I tried to debug it, but this is truly painful, as solve > is called inside of > 'lapply' and there are over 5,000 individual data series in the panel. > > Now, what I would like to do is to count the calls to 'solve' inside the > function, so I can > see, where the function throws the exception. I tried to use 'trace' with a > count variable, > but I have no clue how to define a global variable to be used by trace and > updated at > every call.....is there another approach? > > > Best > > Simon > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.