Hello, I'm trying to bin a quantity into 2-3 bins for calculating entropy and mutual information. One of the approaches I'm exploring is the cut() function, which is what the mutualInfo function in binDist uses. When it's called in the format cut(data, breaks=n), it somehow splits the data into n distinct bins. Can anyone tell me how cut() decides where to cut? Thanks, Melissa --------------------------------------------------------------- Melissa Cline, Independent Investigator MCD Biology, UCSC [[alternative HTML version deleted]]
melissa cline wrote:> Hello, > > I'm trying to bin a quantity into 2-3 bins for calculating entropy and > mutual information. One of the approaches I'm exploring is the cut() > function, which is what the mutualInfo function in binDist uses. When it's > called in the format cut(data, breaks=n), it somehow splits the data into n > distinct bins. Can anyone tell me how cut() decides where to cut? > >This is one case where reading the actual R code is easier that explaining what it does. From cut.default if (length(breaks) == 1) { if (is.na(breaks) | breaks < 2) stop("invalid number of intervals") nb <- as.integer(breaks + 1) dx <- diff(rx <- range(x, na.rm = TRUE)) if (dx == 0) dx <- rx[1] breaks <- seq.int(rx[1] - dx/1000, rx[2] + dx/1000, length.out = nb) } so basically it takes the range, extends it a bit and splits in into <breaks> equally long segments. (For the sometimes more attractive option of splitting into groups of roughly equal size, there is cut2 in the Hmisc package, or use quantile()) -- O__ ---- Peter Dalgaard ?ster Farimagsgade 5, Entr.B c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907
cut(data, breaks=n)
splits the data in n bins of (approximately) the same size.
The used size is obtained by:
max(data) - min(data)
------------------------------------
n
> x=rnorm(x)
> cut(x,breaks=3)
[1] (1.79,9.97] (-6.39,1.79] (9.97,18.2] (9.97,18.2] (-6.39,1.79]
[6] (1.79,9.97] (-6.39,1.79] (1.79,9.97] (-6.39,1.79] (-6.39,1.79]
Levels: (-6.39,1.79] (1.79,9.97] (9.97,18.2]
Then you have:
> 18.2-9.97
[1] 8.23
> 9.97-1.79
[1] 8.18
> 1.79+6.39
[1] 8.18
>
> (max(x)-min(x))/3
[1] 8.164187
I don't know the reasons for the little differences (I am wondering about).
I hope it is useful.
domenico
melissa cline wrote:> Hello,
>
> I'm trying to bin a quantity into 2-3 bins for calculating entropy and
> mutual information. One of the approaches I'm exploring is the cut()
> function, which is what the mutualInfo function in binDist uses. When
it's
> called in the format cut(data, breaks=n), it somehow splits the data into n
> distinct bins. Can anyone tell me how cut() decides where to cut?
>
> Thanks,
>
> Melissa
>
>
>
> ---------------------------------------------------------------
> Melissa Cline, Independent Investigator
> MCD Biology, UCSC
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
Peter Dalgaard wrote:> melissa cline wrote: >> Hello, >> >> I'm trying to bin a quantity into 2-3 bins for calculating entropy and >> mutual information. One of the approaches I'm exploring is the cut() >> function, which is what the mutualInfo function in binDist uses. When it's >> called in the format cut(data, breaks=n), it somehow splits the data into n >> distinct bins. Can anyone tell me how cut() decides where to cut? >> >> > This is one case where reading the actual R code is easier that > explaining what it does. From cut.default > > if (length(breaks) == 1) { > if (is.na(breaks) | breaks < 2) > stop("invalid number of intervals") > nb <- as.integer(breaks + 1) > dx <- diff(rx <- range(x, na.rm = TRUE)) > if (dx == 0) > dx <- rx[1] > breaks <- seq.int(rx[1] - dx/1000, rx[2] + dx/1000, length.out = nb) > } > > so basically it takes the range, extends it a bit and splits in into > <breaks> equally long segments. > > (For the sometimes more attractive option of splitting into groups of > roughly equal size, there is cut2 in the Hmisc package, or use quantile()) >It can be a bit dangerous to use quantile() to provide breaks for cut(), because quantiles can be non-unique, which cut() doesn't like:> x1 <- c(1,1,1,1,1,1,1,1,1,2) > cut(x1, breaks=quantile(x1, (0:2)/2))Error in cut.default(x1, breaks = quantile(x1, (0:2)/2)) : 'breaks' are not unique>However, cut2() in Hmisc handles this situation gracefully:> library(Hmisc)Attaching package: 'Hmisc' The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units> cut2(x1, g=2)[1] 1 1 1 1 1 1 1 1 1 2 Levels: 1 2>(Additionally, a potentially dangerous peculiarity of quantile() for this kind of purpose is that its return values can be out of order (i.e., diff(quantile(...))<0, at rounding error level), but this doesn't actually upset cut() in R because cut() sorts the breaks prior to using them.) -- Tony Plate