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Hi All, I want to know how to run an R file on my computer in R-Fiddle? I tried source("filename.r"), but not working. thanks, Frank [[alternative HTML version deleted]]

Hi Frank, You could upload your R source file to a public URL, for example to github and read via RCurl, as source do not support https as far as I know. Here is a working example. library('RCurl') tmatrix <- getURL("https://raw.githubusercontent.com/msuzen/isingLenzMC/master/R/isingUtils.R") eval(parse(text=tmatrix)) Not that you need to use raw URL for github file. Best, -m On 30 October 2017 at 01:56, Frank Mei <frank.ye.mei at gmail.com> wrote: > Hi All, > > I w...

...th the dendrogram I want appearing at the top of the heatmap If I use either of these orders the ordering works: order <- c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24) order2 <- c(24,23,22,21,20,19,18,17,16,15,14,13,12,11,10,9,8,7,6,5,4,3,2,1) using the command: heatmap.2(tmatrix, clusteredmatrixasdendrogram, col=bluered600, dendrogram="column", scale="none", trace="none", Rowv=order) however If I start mixing the numbers up e.g: order3 <- c(1,4,7,10,2,5,8,11,3,6,9,12,13,16,19,22,14,17,20,23,15,18,21,24) or order4 <- c(24,21,18,15,23,20...

...ily so I proceeded. I find the TsparseMatrix indexing easier for my more naive notion of sparsity, although thinking about it now, I think I can see that the CsparseMatrix more closely resembles the "folded vector" design of dense R matrices. I will sometimes coerce CMatrix objeccts to TMatrix objects if I am working on the "inner" indices. I should probably stop doing that. I sincerely hope my stumbling efforts have not caused any delays. -- David. > >>> cap-shape=bell cap-shape=conical >>> 369 3 >>...

>>>>> C W <tmrsg11 at gmail.com> >>>>> on Fri, 20 Oct 2017 15:51:16 -0400 writes: > Thank you for your responses. I guess I don't feel > alone. I don't find the documentation go into any detail. > I also find it surprising that, >> object.size(train$data) > 1730904 bytes >>

Thank you for your responses. I guess I don't feel alone. I don't find the documentation go into any detail. I also find it surprising that, > object.size(train$data) 1730904 bytes > object.size(as.matrix(train$data)) 6575016 bytes the dgCMatrix actually takes less memory, though it *looks* like the opposite. Cheers! On Fri, Oct 20, 2017 at 3:22 PM, David Winsemius