>>>>> Martin Maechler <maech...@lynne.ethz.ch>
>>>>> on Wed, 25 Sep 2013 11:08:07 +0200 writes:
>>>>> Michel <michelgo...@free.fr>
>>>>> on Tue, 24 Sep 2013 12:22:10 +0200 writes:
>> Hello, Thanks for your answer The file does not contains
>> numbers in high precision but all the calculation applied
>> to these data will be
>> In attachment a text file containing some lines And her
>> few values:
>>
11111.0054014388224326026488598,-68239.4114845811819662912967033,10053.1824584878233990181684021
>>
3.05363891777017837760380136736,-1.40443175474415104684797195311,1.36766960877453817890022497172
> (two lines, typically split by mail writers/readers)
> Aha! But these actually *ARE* of 'high precision', i.e.
> you cannot store them as usual double precision numbers in full accuracy.
> So, I've prepared the following -- 100% reproducible -- script
> to show you how to get such numbers into an Rmpfr matrix :
> ## MM: Reproducible example
> set.seed(17); x <- mpfr(matrix(rnorm(28), 7, 4), precBits=128)
> x <- x^2
> mfile <- tempfile()
> write.table(array(format(x), dim=dim(x)), file = mfile,
> row.names=FALSE, col.names=FALSE, sep=",")
> ## to check:
> writeLines(readLines(mfile) [1:2])
> ## Now, let's assume mfile contains the "high precision" matrix we want
to get as
> ## mpfrMatrix :
> ## 1) Assume you know the number of columns, then this is fastest :
> m.ncol <- 4
> chmat <- matrix(scan(mfile, "", sep=","), ncol = m.ncol )
and -- oops! - the above was missing the ominous 'byrow = TRUE'
i.e. the above needs to be
chmat <- matrix(scan(mfile, "", sep=","), ncol = m.ncol, byrow = TRUE)
... which makes the detour via read.table() even more attractive ...
> ## 2) Nothing is known, ... ok, why not make the detour via read.table():
> chmat <- as.matrix(read.table(mfile, colClasses="character", sep=","))
> ## in both cases:
> require(Rmpfr)# the package
> M <- mpfr(chmat)#-> determines precision *from* the input, here 133 ..
143 bits
> ## or set the precision yourself, high enough:
> M <- mpfr(chmat, precBits = 144)
> ## and e.g. this works:
> crossprod(M) ## == M'M
> -------
> Hoping this helps,
> Martin
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