[R] read.table() and precision?

Prof Brian Ripley ripley at stats.ox.ac.uk
Tue Dec 18 11:20:24 CET 2007

On Mon, 17 Dec 2007, Moshe Olshansky wrote:

> Dear List,
> Following the below question I have a question of my
> own:
> Suppose that I have large matrices which are produced
> sequentially and must be used sequentially in the
> reverse order. I do not have enough memory to store
> them and so I would like to write them to disk and
> then read them. This raises two questions:
> 1) what is the fastest (and the most economic
> space-wise) way to do this?

Using save/load is the simplest.  Don't worry about finding better 
solutions until you know those are not good enough.  (serialize / 
unserialize is another interface to the same underlying idea.)

> 2) functions like write, write.table, etc. write the
> data the way it is printed and this may result in a
> loss of accuracy. Is there any way to prevent this,
> except for setting the "digits" option to a higher
> value or using format prior to writing the data?

Do please read the help before making false claims. ?write.table says

      Real and complex numbers are written to the maximal possible

OTOH, ?write says it is a wrapper for cat, whose help says

      'cat' converts numeric/complex elements in the same way as 'print'
      (and not in the same way as 'as.character' which is used by the S
      equivalent), so 'options' '"digits"' and '"scipen"' are relevant.
      However, it uses the minimum field width necessary for each
      element, rather than the same field width for all elements.

so this hints as.character() might be a useful preprocessor.

> Is it possible to write binary files (similar to Fortran)?

See ?writeBin.  save/load by default write binary files, but use of 
writeBin can be faster (and less flexible).

> Any suggestion will be greatly appreciated.

Somehow you have missed a great deal of information about R I/O.
Try help.start() and reading the sections the search engine shows you 
that look relevant.

Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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