Hi - thanks for the advice - I am however applying this to the whole data frame. And the code that I'm using is just to read in the data (using read.table) and then the code that you supplied. I could send you the actual dataset if you don't mind a file ~50MB?!
Thanks again, Steve > Date: Tue, 29 Jul 2008 15:34:31 -0400 > From: [EMAIL PROTECTED] > To: [EMAIL PROTECTED] > Subject: Re: [R] Coarsening the Resolution of a Dataset > CC: r-help@r-project.org > > I assume that you are doing this on one column of the matrix which > should only have 2160 entries in it. can you send the actual code you > are using. I tried it with 10,000 samples and it works fine. So I > need to understand the data structure you are using. Also the > infinite recursion sounds strange; do you have function like 'cut' or > 'c' redefined? So it would help if you could supply a reproducible > example. > > On Tue, Jul 29, 2008 at 10:09 AM, Steve Murray <[EMAIL PROTECTED]> wrote: > > > > Unfortunately, when I get to the 'myCuts' line, I receive the following > > error: > > > > Error: evaluation nested too deeply: infinite recursion / > > options(expressions=)? > > > > ...and I also receive warnings about memory allocation being reached (even > > though I've already used memory.limit() to maximise the memory) - this is a > > fairly sizeable dataset afterall, 2160 rows by 4320 columns. > > > > Therefore I was wondering if there are any alternative ways of coarsening a > > dataset? Or are there any packages/commands built for this sort of thing? > > > > Any advice would be much appreciated! > > > > Thanks again, > > > > Steve > > > > > > _________________________________________________________________ > > Find the best and worst places on the planet > > http://clk.atdmt.com/UKM/go/101719807/direct/01/ > > > > -- > Jim Holtman > Cincinnati, OH > +1 513 646 9390 > > What is the problem you are trying to solve? _________________________________________________________________ 100s of Nikon cameras to be won with Live Search [[alternative HTML version deleted]]
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