Matthew, Precisely. That's what I was thinking as well. But was hesitant to tell as I dint know how complex it would be to implement / change it. Since the join requires tolerance, sorting could be still done in the "right" order (by disregarding tolerance during sort).
Arun On Tuesday, April 30, 2013 at 4:22 PM, Matthew Dowle wrote: > > Maybe it doesn't actually need to sort within machine tolerance. If it was > precise, the sort would be faster, that's for sure. But at the time, I > remember thinking that it should preserve the order of rows within a group of > values within machine tolerance (e.g. 3.99999999, 4.00000001, 3.99999999 > should be consider 4.0 and order of those 3 rows maintained). But maybe > sorting them to 3.99999999, 3.99999999, 4.00000001 is ok as it's just the > join that should be within machine tolerance? > Interested in how fast order(y) is, though. Compared to data.table sorting > of doubles. > Matthew > > On 30.04.2013 15:16, Arunkumar Srinivasan wrote: > > Matthew, > > I see. I din't think about tolerance. Although > > dt[with(dt, order(y)), ] > > seems to do the task right (similar to data.frame). I'm glad that I don't > > have to convert to data.frame to perform the order. I am not keying by this > > column. Unless one needs this column for keying, I don't think a tolerance > > option is essential. Although, having it definitely would be only nicer. > > Arun > > > > > > On Tuesday, April 30, 2013 at 4:09 PM, Matthew Dowle wrote: > > > > > > > > Hi, > > > data.table sorts double within machine tolerance : > > > > sqrt(.Machine$double.eps) > > > [1] 1.490116e-08 > > > > > > > > > > i.e. numbers closer than this are considered equal. > > > > > > Otherwise we wouldn't be able to do things like DT[.(3.14)]. > > > > > > I had a quick look, see arguments of data.table:::ordernumtol which takes > > > "tol" but there is no option provided (yet) to change this. Do we need > > > one? > > > > > > In the examples section of one of the help pages it has an example which > > > generates a series of numers very close together using pi. Note that your > > > numbers are both close together, and, very close to 0. > > > > > > Matthew > > > > > > On 30.04.2013 14:52, Arunkumar Srinivasan wrote: > > > > Hi there, > > > > I just saw something strange when I was sorting a column of p-values. I > > > > checked the data.table bug tracker for words "sort" and "floating > > > > point" and there were no hits for this case. There's a bug for "integer > > > > 64" sort on a column though. > > > > So, here's a reproducible example. I'd be glad to file a bug, if it is > > > > and be corrected if it's something I am doing wrong. > > > > set.seed(45) > > > > dt <- data.table(x=sample(50), y= sample(c(seq(0, 1, length.out=1000), > > > > 7000000:7000100), 50)/1e7) > > > > head(dt) > > > > x y > > > > 1: 32 5.395395e-08 > > > > 2: 16 6.956957e-08 > > > > 3: 12 2.142142e-08 > > > > 4: 18 5.855856e-08 > > > > 5: 17 6.216216e-08 > > > > 6: 14 5.025025e-08 > > > > setkey(dt, "y") # sort by column y > > > > head(dt, 10) > > > > x y > > > > 1: 47 1.401401e-09 > > > > 2: 12 2.142142e-08 > > > > 3: 24 1.391391e-08 > > > > 4: 43 9.809810e-09 <~~~ obviously false > > > > 5: 1 2.932933e-08 > > > > 6: 48 2.562563e-08 > > > > 7: 49 1.891892e-08 > > > > 8: 40 2.182182e-08 > > > > 9: 9 7.307307e-09 <~~~ obviously false > > > > 10: 45 2.482482e-08 > > > > > > > > Best, > > > > Arun > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >
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