similar to: error using heatmap :"evaluation nested too deeply....."

I'm diverting this to the more appropriate mailing list, R-help, since heatmap() is standard R function. >>>>> "Johan" == Johan Lindberg <johanl at kiev.biotech.kth.se> >>>>> on Fri, 02 Jan 2004 10:04:14 +0100 writes: Johan> I am trying to plot a matrix of m-values in a heatmap Johan> with "average linkage". The rows

Hi netters, I have a matrix X of the size (1000,100). The values are from -3 to +3. When I tried heatmap(X, distfun=function(c),dist(c,method="bin"),hclustfun=function(m),hclust(m,method="average")) I got the error message: Error: evaluation nested too deeply: infinite recursion / options(expressions=)? However, if I used default parameters for distfunction:

Hi, Trying to plot a large dendrogram, I get the recursion limit error Error in match.fun(FUN) : evaluation nested too deeply: infinite recursion / options(expression=)? but setting options(expressions = 10000) or something large enough to solve the infinite recursion limit problem, I get Error: protect(): stack overflow Is there anything that can be done? Thanks Claudio Donati

Hi, I am processing tick data and my code has stopped working as I have increased the size of data being processed. Now I am receiving error for basic tasks in RConsole: > a = c(1:1000) Error: evaluation nested too deeply: infinite recursion / options(expressions=)? My R code worked fine with 50 stocks and 500,000 rows per stock, but when I increased this to 50 stocks and 5,000,000 rows per

I recently started using R (Version 1.3.0 on a Dell machine). After using R for about a week, I started receiving the error message shown below. I can't even run simple commands that I know should work. Is this a bug or did I just mess something up? I've uninstalled and reinstalled R but continue to receive the same errors. The errors are shown below: R : Copyright 2001, The R

I get the error Error : evaluation nested too deeply: infinite recursion / options(expressions=)? during a 'R CMD check ...' on one of my packages. The reason seems to be that this package is mutually dependent on another one (i.e. the DESCRIPTION files of package A lists package B under "Depends" and vice versa). this might be bad design (having bits in both packages needed

Hi guys, I have a code in R and it was work well but when I decrease the epsilon value (indicated in the code) , then I am getting this error Error: evaluation nested too deeply: infinite recursion / options(expressions=)? any help please y = 6.8; w = 7.4; z = 5.7; muy = 7; muw = 7; muz = 6; sigmay = 0.8; sigmaz = 0.76; sigmaw = 0.3; betayx = 0.03; betayz = 0.3; betayw = 0.67 s =

hello all i searched the archives and couldn't get a solution to the following question. i have the following function: F=function(z,v) { if (v==-.5) return(1) else return(2*v/z + 1/Recall(z,v-1)) } and while testing whether it works (ie F(z,v) is approx = besselK(z,1+v)/besselK(z,V). the recursion formula allows one to calculate besselK(z,1+v)/besselK(z,V) for large values of z )

Hi all, Why I am getting, Error: evaluation nested too deeply: infinite recursion / options(expressions=)? Thanks in advance! func <- Vectorize(function(x, a, sad, trunc=0, ...) { result <- function(x) { f1 <- function(n) { dcom <- paste("d", deparse(substitute(sad)), sep="") dots <- c(as.name("n"), list(...)) f <-

hello R-users, I'm trying to port from S+4 a library called S2HTML. generic function HTMLExport, when called for a lm object, uses HTMLExport.lm which itself calls HTMLExport.list to export the summary. My problem is that HTMLExport.list may itself call HTMLExport (and so HTMLExport.list) for components of the lists that are lists themselves (like "terms" component of an lm object).

hello all i searched the archives and couldn't get a solution to the following question. i have the following function: F=function(z,v) { if (v==-.5) return(1) else return(2*v/z + 1/Recall(z,v-1)) } and while testing whether it works (ie F(z,v) is approx = besselK(z,1+v)/besselK(z,V). the recursion formula allows one to calculate besselK(z,1+v)/besselK(z,V) for large values of z )

Open-Xchange Security Advisory 2020-08-12 Affected product: Dovecot IMAP server Internal reference: DOP-1849 (Bug ID) Vulnerability type: Uncontrolled recursion (CWE-674) Vulnerable version: 2.0 Vulnerable component: submission, lmtp, lda Fixed version: 2.3.11.3 Report confidence: Confirmed Solution status: Fix available Vendor notification: 2020-04-23 CVE reference: CVE-2020-12100 CVSS: 7.5

Open-Xchange Security Advisory 2020-08-12 Affected product: Dovecot IMAP server Internal reference: DOP-1849 (Bug ID) Vulnerability type: Uncontrolled recursion (CWE-674) Vulnerable version: 2.0 Vulnerable component: submission, lmtp, lda Fixed version: 2.3.11.3 Report confidence: Confirmed Solution status: Fix available Vendor notification: 2020-04-23 CVE reference: CVE-2020-12100 CVSS: 7.5

Hi all! I¹m just implementing the Ullmann¹s algorithm for searching subgraph isomorphisms in graphNEL objects. The algorithm is running with smaller graphs, but when I¹m calling it i get an R error message saying that functions are nested too deeply in source code. I found out that the problem is in the so called refinement procedure of the algorithm which consists of 10 different functions,

(I have searched the email archives for discussions on this topic but have found nothing.) The help page for heatmap says: By default (scale = "row") the rows are scaled to have mean zero and standard deviation one. There is some empirical evidence from genomic plotting that this is useful. I offer two comments on that. 1. Since the heatmap function is general-purpose (that is, not in

I've just uploaded gregmisc 0.8.6 to CRAN, it should show up in the package tree shortly. It contains both an enhanced barplot() [named barplot2 in my code] and an enhanced heatmap() function that I would like to see propagate to the base and mva packages respectively. I've checked the code for both functions against the code in R 1.8.1, and these functions have all of the latest

I have a huge dataset(15k X 18) and tried to use the heatmap in R to examine the patterns. However, I found that heatmap and heatmap.2 gave me completely different outputs. Here are the codes: ------------ > dim(as.matrix(data.dcpm)) [1] 15462??? 18 > > heatmap(as.matrix(data.dcpm), col=topo.colors(100)) > heatmap.2(as.matrix(data.dcpm), col=topo.colors(100), key=TRUE,

Hi, I am trying to create a heatmap with some specific requirements. Specifically, I need to be able to center the color-scale around 0, and I need to truncate the data so that a few extreme values do not cause the rest of the heatmap to appear black (on a red/green scale). After reading through and experimenting with heatmap, heatmap.2, heatmap_plus, and heatmap_2, I believe heatmap.2 will

Dear R-Helpers, I have a short question related to heatmap.2 function. I wanted to change the dimension of each cell in the heatmap drawn by this function. here is a reproducible example from the help page library(gplots) data(mtcars) x <- as.matrix(mtcars) rc <- rainbow(nrow(x), start=0, end=.3) cc <- rainbow(ncol(x), start=0, end=.3) hv <- heatmap.2(x, col=cm.colors(255),

Dear R users, need help with my heatmap. I will really approciate some help. Given the matrix: > head(x) A B C D time [1,] 0 8 0 0 1 [2,] 0 160 0 0 2 [3,] 0 175 0 0 3 [4,] 0 253 0 0 4 [5,] 79 212 0 0 5 [6,] 6 105 0 0 6 and call: ##------------ Heatmap -------------- library(RColorBrewer) rc <- grey((nrow(x):1)/nrow(x)) heatmap(data.matrix(x[,1:4]),