If you want indexes, i.e. 1, 2, 3, ... instead of the values in v you can still use split -- just split on seq_along(v) instead of v (or if v had names you might want to split along names(v)):
split(seq_along(v), ct) and if you only want to retain groups with 2+ elements then you can just Filter then out: twoplus <- function(x) length(x) >= 2 Filter(twoplus, split(seq_along(v), ct)) On Dec 22, 2007 5:12 AM, Johannes Graumann <[EMAIL PROTECTED]> wrote: > But cutree does away with the indexes from the original input, which > rect.hclust retains. > I will have no other choice and match that input with the 'values' contained > in the clusters ... > > Joh > > > Gabor Grothendieck wrote: > > > If we don't need any plotting we don't really need rect.hclust at > > all. Split the output of cutree, instead. Continuing from the > > prior code: > > > >> for(el in split(unname(vv), names(vv))) print(el) > > [1] 0.00 0.45 > > [1] 1 > > [1] 2 > > [1] 3.00 3.25 3.33 3.75 4.10 > > [1] 5 > > [1] 6.00 6.45 > > [1] 7.0 7.1 > > [1] 8 > > > > On Dec 21, 2007 3:24 PM, Johannes Graumann <[EMAIL PROTECTED]> > > wrote: > >> Hm, hm, rect.hclust doesn't accept "plot=FALSE" and cutree doesn't retain > >> the indexes of membership ... anyway short of ripping out the guts of > >> rect.hclust to achieve the same result without an active graphics device? > >> > >> Joh > >> > >> > >> >> # cluster and plot > >> >> hc <- hclust(dist(v), method = "single") > >> >> plot(hc, lab = v) > >> >> cl <- rect.hclust(hc, h = .5, border = "red") > >> >> > >> >> # each component of list cl is one cluster. Print them out. > >> >> for(idx in cl) print(unname(v[idx])) > >> > [1] 8 > >> > [1] 7.0 7.1 > >> > [1] 6.00 6.45 > >> > [1] 5 > >> > [1] 3.00 3.25 3.33 3.75 4.10 > >> > [1] 2 > >> > [1] 1 > >> > [1] 0.00 0.45 > >> > > >> >> # a different representation of the clusters > >> >> vv <- v > >> >> names(vv) <- ct <- cutree(hc, h = .5) > >> >> vv > >> > 1 1 2 3 4 4 4 4 4 5 6 6 7 7 > >> > 8 > >> > 0.00 0.45 1.00 2.00 3.00 3.25 3.33 3.75 4.10 5.00 6.00 6.45 7.00 7.10 > >> > 8.00 > >> > > >> > > >> > On Dec 21, 2007 4:56 AM, Johannes Graumann <[EMAIL PROTECTED]> > >> > wrote: > >> >> <posted & mailed> > >> >> > >> >> Dear all, > >> >> > >> >> I'm trying to solve the problem, of how to find clusters of values in > >> >> a vector that are closer than a given value. Illustrated this might > >> >> look as follows: > >> >> > >> >> vector <- c(0,0.45,1,2,3,3.25,3.33,3.75,4.1,5,6,6.45,7,7.1,8) > >> >> > >> >> When using '0.5' as the proximity requirement, the following groups > >> >> would result: > >> >> 0,0.45 > >> >> 3,3.25,3.33,3.75,4.1 > >> >> 6,6.45 > >> >> 7,7.1 > >> >> > >> >> Jim Holtman proposed a very elegant solution in > >> >> http://tolstoy.newcastle.edu.au/R/e2/help/07/07/21286.html, which I > >> >> have modified and perused since he wrote it to me. The beauty of this > >> >> approach is that it will not only work for constant proximity > >> >> requirements as above, but also for overlap-windows defined in terms > >> >> of ppm around each value. Now I have an additional need and have found > >> >> no way (short of iteratively step through all the groups returned) to > >> >> figure out how to do that with Jim's approach: how to figure out that > >> >> 6,6.45 and 7,7.1 are separate clusters? > >> >> > >> >> Thanks for any hints, Joh > >> >> > > > > > ______________________________________________ > > 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. > ______________________________________________ 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.
