[R] Coarsening the Resolution of a Dataset

jim holtman jholtman at gmail.com
Wed Jul 30 11:32:33 CEST 2008


Can you at least send the output from the script so that we can see
exactly how you are reading in the data and then processing it.  Doing
'str(yourData)' would help to understand what the data looks like.
The exactly error messages would also help.  Is the data entirely
numeric, or does it also contain factors?  So this type of information
is needed to understand the context of where your problem is.

On Wed, Jul 30, 2008 at 4:09 AM, Steve Murray <smurray444 at hotmail.com> wrote:
>
> 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: jholtman at gmail.com
>> To: smurray444 at hotmail.com
>> Subject: Re: [R] Coarsening the Resolution of a Dataset
>> CC: r-help at 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  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?
>
> _________________________________________________________________
> Play and win great prizes with Live Search and Kung Fu Panda
> http://clk.atdmt.com/UKM/go/101719966/direct/01/



-- 
Jim Holtman
Cincinnati, OH
+1 513 646 9390

What is the problem you are trying to solve?



More information about the R-help mailing list