From haverty.peter at gene.com  Fri Jan 20 18:59:58 2017
From: haverty.peter at gene.com (Peter Haverty)
Date: Fri, 20 Jan 2017 09:59:58 -0800
Subject: [Rd] How to handle INT8 data
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Message-ID: <CAGh0NYrfkRg3QekHtYSpYrdd+BPCrU86Z0bEsgCxEiwsRxqirQ@mail.gmail.com>

For what it is worth, I would be extremely pleased to R's integer type go
to 64bit.  A signed 32bit integer is just a bit too small to index into the
~3 billion position human genome.  The "work arounds" that have arisen for
this specific issue are surprisingly complex.

Pete

____________________
Peter M. Haverty, Ph.D.
Genentech, Inc.
phaverty at gene.com

On Fri, Jan 20, 2017 at 9:47 AM, Nicolas Paris <nicolas.paris at aphp.fr>
wrote:

> Well I definitely cannot use them as numeric because join is the main
> reason of those identifiers.
>
> About int64 and bit64 packages, it's not a solution, because I am
> releasing a dataset for external users. I cannot ask them to install a
> package in order to exploit them.
>
> I have to be very carefull when releasing the data. If a user just use
> read.csv functions, they by default cast the identifiers as numeric.
>
> $ more res.csv
> "col1";"col2"
> "-1311071933951566764";"toto"
> "-1311071933951566764";"tata"
>
>
> > read.table("res.csv",sep=";",header=T)
>            col1 col2
> 1 -1.311072e+18 toto
> 2 -1.311072e+18 tata
>
> >sapply(read.table("res.csv",sep=";",header=T),class)
>      col1      col2
> "numeric"  "factor"
>
> > read.table("res.csv",sep=";",header=T,colClasses="character")
> col1 col2
> 1 -1311071933951566764 toto
> 2 -1311071933951566764 tata
>
> Am I comdemned to provide a R script with the data in order to exploit the
> dataset ?
>
> Le 20 janv. 2017 ? 18h29, Murray Stokely ?crivait :
> > 2^53 == 2^53+1
> > TRUE
> >
> > Which makes joining or grouping data sets with 64 bit identifiers
> problematic.
> >
> > Murray (mobile)
> >
> > On Jan 20, 2017 9:15 AM, "Nicolas Paris" <nicolas.paris at aphp.fr> wrote:
> >
> >     Le 20 janv. 2017 ? 18h09, Murray Stokely ?crivait :
> >     > The lack of 64 bit integer support causes lots of problems when
> dealing
> >     with
> >     > certain types of data where the loss of precision from coercing to
> 53
> >     bits with
> >     > double is unacceptable.
> >
> >     Hello Murray,
> >     Do you mean, by eg. -1311071933951566764 loses in precision during
> >     as.numeric(-1311071933951566764) process ?
> >     Thanks,
> >     >
> >     > Two packages were developed to deal with this:  int64 and bit64.
> >     >
> >     > You may need to find archival versions of these packages if they've
> >     fallen off
> >     > cran.
> >     >
> >     > Murray (mobile phone)
> >     >
> >     > On Jan 20, 2017 7:20 AM, "Gabriel Becker" <gmbecker at ucdavis.edu>
> wrote:
> >     >
> >     >     I am not on R-core, so cannot speak to future plans to
> internally
> >     support
> >     >     int8 (though my impression is that there aren't any, at least
> none
> >     that are
> >     >     close to fruition).
> >     >
> >     >     The standard way of dealing with whole numbers too big to fit
> in an
> >     integer
> >     >     is to put them in a numeric (double down in C land). this can
> >     represent
> >     >     integers up to 2^53 without loss of precision see (
> >     >     http://stackoverflow.com/questions/1848700/biggest-
> >     >     integer-that-can-be-stored-in-a-double).
> >     >     This is how long vector indices are (currently) implemented in
> R. If
> >     it's
> >     >     good enough for indices it's probably good enough for whatever
> you
> >     need
> >     >     them for.
> >     >
> >     >     Hope that helps.
> >     >
> >     >     ~G
> >     >
> >     >
> >     >     On Fri, Jan 20, 2017 at 6:33 AM, Nicolas Paris <
> nicolas.paris at aphp.fr
> >     >
> >     >     wrote:
> >     >
> >     >     > Hello r users,
> >     >     >
> >     >     > I have to deal with int8 data with R. AFAIK  R does only
> handle
> >     int4
> >     >     > with `as.integer` function [1]. I wonder:
> >     >     > 1. what is the better approach to handle int8 ?
> `as.character` ?
> >     >     > `as.numeric` ?
> >     >     > 2. is there any plan to handle int8 in the future ? As you
> might
> >     know,
> >     >     > int4 is to small to deal with earth population right now.
> >     >     >
> >     >     > Thanks for you ideas,
> >     >     >
> >     >     > int8 eg:
> >     >     >
> >     >     >      human_id
> >     >     > ----------------------
> >     >     >  -1311071933951566764
> >     >     >  -4708675461424073238
> >     >     >  -6865005668390999818
> >     >     >   5578000650960353108
> >     >     >  -3219674686933841021
> >     >     >  -6469229889308771589
> >     >     >   -606871692563545028
> >     >     >  -8199987422425699249
> >     >     >   -463287495999648233
> >     >     >   7675955260644241951
> >     >     >
> >     >     > reference:
> >     >     > 1. https://www.r-bloggers.com/r-in-a-64-bit-world/
> >     >     >
> >     >     > --
> >     >     > Nicolas PARIS
> >     >     >
> >     >     > ______________________________________________
> >     >     > R-devel at r-project.org mailing list
> >     >     > https://stat.ethz.ch/mailman/listinfo/r-devel
> >     >     >
> >     >
> >     >
> >     >
> >     >     --
> >     >     Gabriel Becker, PhD
> >     >     Associate Scientist (Bioinformatics)
> >     >     Genentech Research
> >     >
> >     >             [[alternative HTML version deleted]]
> >     >
> >     >     ______________________________________________
> >     >     R-devel at r-project.org mailing list
> >     >     https://stat.ethz.ch/mailman/listinfo/r-devel
> >     >
> >     >
> >
> >     --
> >     Nicolas PARIS
> >
> >
>
> --
> Nicolas PARIS
>
> ______________________________________________
> R-devel at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-devel
>

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[Rd] How to handle INT8 data
Peter Haverty