Two replies:
1. Downsampling?
In case you want to use the Hilbert curve for visualisation, please note
that you will need a graphics device with resolution 65536 x 65536 to
display it. Many people have smaller screens, so binning the genome
(e.g. into bins of 10x10=100nt) could be a practical solution, and more
efficient than computing some large intermediate thing that your
graphics device will then downsample anyway.
2. Long vector
In case you really need the big curve: I just had a look at the C code
in the "HilbertVis" package, which anyway uses long ints, and it does
not look difficult to modify the R wrapper so that it uses a long
vector. I assume that Simon would welcome the patch.
Wolfgang
9.3.17 08:44, Sohaib Ghani scripsit:
I am trying to simulate hilbertcurve (of Bioconductor package) of level 16 in
R. It takes about 4^16=4 Billion points. I want to generate the hilbert curve
of genome (size about 3 billion).
But I am getting this error
long vectors not supported yet: memory.c:1668
I am using 64 bit version (R 3.3.2) so my guess is I can use vectors of length
> 2^31. Also, my RAM is about 350GB.
The command I am using is
itr=4^16
hc = HilbertCurve(1, itr, 16, mode = "pixel", title = "pixel mode",start_from =
"topleft")
Even when I am reading the whole genome sometimes R is crashing in the process.
I have read the other similar questions on this topic but could not find the
solution. Please help me what should I use for this problem.
Thanks
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