It seems that .compressTipLabel's running times are proportional to N
(number of trees) and to log(n) (n: nb of tips).
R> tr <- rmtree(1e4, 1e4) # takes ~5 minutes
R> system.time(a <- .compressTipLabel(tr))
utilisateur système écoulé
20.904 0.376 21.275
R>
Hi Yan,
Joseph was right. In read.nexus you need a TRANSLATE block, just a
TAXLABELS is not enough. Then read.nexus returns the compressed object and
is 10x faster to read in (for 1000 trees with 1000 taxa on my machine).
There is also the package rncl (Nexus Class Library), it is faster to read
On 14 Dec 2016, at 21:06, Emmanuel Paradis wrote:
> If the trees are in a NEXUS file with a TRANSLATE block, then the output is a
> compressed list. So applying .compressTipLabel returns the list unmodified
> (which should be almost instantaneous).
Ah, I see what I
If the trees are in a NEXUS file with a TRANSLATE block, then the output
is a compressed list. So applying .compressTipLabel returns the list
unmodified (which should be almost instantaneous).
Best,
Emmanuel
Le 14/12/2016 à 16:51, Yan Wong a écrit :
On 14 Dec 2016, at 15:33, Joseph W.
Hi Yan,
I tried with 10,000 trees each with 1000 tips and it took a bit more
than 1 sec:
R> tr <- rmtree(1, 1000)
R> system.time(a <- .compressTipLabel(tr))
utilisateur système écoulé
1.124 0.036 1.161
And yes the memory footprint is substantially decreased:
On 14 Dec 2016, at 15:33, Joseph W. Brown wrote:
> I wonder if reading in a Nexus file with a translation table bypasses this
> problem?
Cheers,
If I try read.nexus with a TAXLABELS entry, it still (oddly) results in a
multiPhylo structure of the same size as before
I wonder if reading in a Nexus file with a translation table bypasses this
problem?
JWB
Joseph W. Brown
Post-doctoral Researcher, Smith Laboratory
University of Michigan
Department of Ecology & Evolutionary Biology
Room 2071, Kraus Natural Sciences
Hi,
I’m reading in a large number of newick trees with the same tips, all from a
single file. If I do trees<-read.trees() followed by trees <-
.compressTipLabel(trees), it reduces the memory footprint well, but takes an
age to run. I can’t help thinking this could be sped up during the reading