?scale -- Bert Gunter
-----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of jim holtman Sent: Wednesday, July 16, 2008 12:14 PM To: rcoder Cc: r-help@r-project.org Subject: Re: [R] Mapping data onto score Try this and see how fast it runs: # x is your input matrix that will be processed by column # y is the scaled output matrix y <- t(apply(x, 2, function(.col){ .rang <- range(.col) (.col - .rang[1]) / (.rang[2] - .rang[1]) * 100 })) On Wed, Jul 16, 2008 at 3:01 PM, rcoder <[EMAIL PROTECTED]> wrote: > > Here's my code: > > nc<-ncol(mat) #setting end point in counter to number of cols in sm > nr<-nrow(mat) > mm <- array(NA, dim=c(2, nc)) #to hold min/max ranges > sc <- array(NA, dim=c(nr, nc)) #to hold percentile scales > for (n in 1:nc) { #now calculate respective ranges for > data matrix > mm[,n]<-range(mat[,n],na.rm=T) #inserts min/max values into sc > matrix > for (m in 1:nr) { > sc[m,n]<-100*(mat[m,n]-mm[1,n])/(mm[2,n]-mm[1,n]) #re-scaling onto > percentile ranking > } > } > rcoder > > > > rcoder wrote: >> >> I am trying to apply the solution you mentioned to all columns in a >> matrix, and output the results to another matrix and append the two using >> the cbind function. >> >> I have written something that works, using a nested For loop to go through >> all the cells in the target matrix, but the trouble is that the process >> takes a while to run (3-4 mins). The matrix is large, about 2000 by 10000, >> so this could be a reason for the slow speed. However, I'm convinced there >> is a faster way of applying this mapping procedure to all columns in a >> matrix and outoutting into columns in a separate matrix. >> >> I would be grateful for any suggestions on this slight modification. >> Otherwise, I can make do with my version. >> >> Thanks, >> >> rcoder >> >> >> rcoder wrote: >>> >>> Thank you Ben! This is very clear. >>> rcoder >>> >>> >>> Ben Tupper wrote: >>>> >>>> >>>> On Jul 15, 2008, at 5:16 PM, rcoder wrote: >>>> >>>>> >>>>> Hi Ben, >>>>> Yes, this is more or less what I want to do. I want to apply this >>>>> data in >>>>> columns in a matrix, and insert the results to additional columns. >>>>> I am not >>>>> entirely aware of a good way of doing this. >>>>> >>>>> e.g. take data from column B, apply normalisation, and feed output >>>>> into >>>>> column C >>>>> >>>> >>>> Oh, >>>> >>>> I think you want to use cbind() to add columns to a matrix. Perhaps >>>> like this which works with the second column... >>>> >>>> v <- matrix(data = rnorm(100), nrow = 10, ncol = 10) >>>> mm <- range(v[,2]) >>>> s <- 10 * (v[,2]-mm[1])/(mm[2]-mm[1]) >>>> v2 <- cbind(v, s) >>>> >>>> Cheers, >>>> Ben >>>> >>>> >>>> >>>>> Thanks, >>>>> >>>>> rcoder >>>>> >>>>> >>>>> >>>>> Ben Tupper wrote: >>>>>> >>>>>> >>>>>> On Jul 15, 2008, at 8:16 AM, rcoder wrote: >>>>>> >>>>>>> >>>>>>> Hi everyone, >>>>>>> >>>>>>> I want to score a set of data (-ve to +ve) using a 0-10 scale. I >>>>>>> have the >>>>>>> data in an R matrix, so I need to add another column, containing >>>>>>> the scores >>>>>>> and resave. >>>>>>> >>>>>> >>>>>> Hi, >>>>>> >>>>>> I am a little fuzzy on what you are asking, but my guess is that you >>>>>> want to normalize the data into the 0-1 range then multiply by 10. >>>>>> >>>>>> values <- rnorm(10) #some numbers >>>>>> mm <- range(values) #the minmax range >>>>>> scaled <- (values-mm[1])/(mm[2]-mm[1]) #normalize into 0-1 >>>>>> scaled10 <- 10 * scaled #scale 0-10 >>>>>> >>>>>> Is that what you seek? >>>>>> Ben >>>>>> >>>>>> ______________________________________________ >>>>>> 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. >>>>>> >>>>>> >>>>> >>>>> -- >>>>> View this message in context: http://www.nabble.com/Mapping-data- >>>>> onto-score-tp18463695p18475083.html >>>>> Sent from the R help mailing list archive at Nabble.com. >>>>> >>>>> ______________________________________________ >>>>> 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. >>>> >>>> Ben Tupper >>>> [EMAIL PROTECTED] >>>> >>>> I GoodSearch for Ashwood Waldorf School. >>>> >>>> Raise money for your favorite charity or school just by searching the >>>> Internet with GoodSearch - www.goodsearch.com - powered by Yahoo! >>>> >>>> ______________________________________________ >>>> 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. >>>> >>>> >>> >>> >> >> > > -- > View this message in context: http://www.nabble.com/Mapping-data-onto-score-tp18463695p18494357.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. > -- Jim Holtman Cincinnati, OH +1 513 646 9390 What is the problem you are trying to solve? ______________________________________________ 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.
