[R] populating a large matrix

[Oliver Ruebenacker]

     Hello,

  For an optimization strategy, we need to know more: do you have many
variables? do you have many different formulae? do you re-calculate
after changing only one variable?

     Take care
     Oliver

On Tue, Jun 19, 2012 at 11:10 PM, Nick Matzke <matzke at berkeley.edu> wrote:
> Hi all,
>
> This question is slightly weird.  I am trying to populate a matrix with
> equations.  The matrix represents transition probabilities between states.
>  A simple example is:
>
>        state1  state2  state3
> state1  s       d       d*d
> state2  e       s       d*e
> state3  e*e     e*d     s
>
> The parameters s, d, and e need to be optimized with an iterative algorithm.
>  This means I have to modify, say, d, and then recalculate the transition
> probabilities for each cell.
>
> Currently, I do this by making a matrix with the equations in character
> format, setting s, e, and d to values, and then running each cell through
> parse(eval(text=celltxt)). As follows:
>
> #################################
> # Test code:
> # Make the text matrix
> txtmat = matrix(c("s", "d", "d*d", "e", "s", "d*e", "e*e", "e*d", "e*d"),
> nrow=3, byrow=TRUE)
>
> s=0.7
> d=0.2
> e=0.1
>
> doit <- function(celltxt)
>        {
>        cellval = eval(parse(text=celltxt))
>        return(cellval)
>        }
>
> # Calculate the matrix with numerical values
> matrix_vals = sapply(X=txtmat, FUN=doit)
> valmat = matrix(matrix_vals, nrow=3, byrow=TRUE)
> valmat
> # End test code
> #################################
>
>
> ...however, this seems to get slow for large matrices. Since I have to
> optimize all the parameters I need something that updates the matrix quickly
> when s, d, or e is changed.  Perhaps this is a job for pointers in C++ or
> something, but I figure there must be a better way in R.
>
> Can anyone think of something more sophisticated than my current method?
>
> Thanks in advance for any and all help!!
>
> Cheers,
> Nick
>
>
>
>
> --
> ====================================================
> Nicholas J. Matzke
> Ph.D. Candidate, Graduate Student Researcher
>
> Huelsenbeck Lab
> Center for Theoretical Evolutionary Genomics
> 4151 VLSB (Valley Life Sciences Building)
> Department of Integrative Biology
> University of California, Berkeley
>
> Graduate Student Instructor, IB200B
> Principles of Phylogenetics: Ecology and Evolution
> http://ib.berkeley.edu/courses/ib200b/
> http://phylo.wikidot.com/
>
>
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>
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>
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>
> -----------------------------------------------------
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> thought the earth was spherical, they were wrong. But if you think that
> thinking the earth is spherical is just as wrong as thinking the earth is
> flat, then your view is wronger than both of them put together."
>
> Isaac Asimov (1989). "The Relativity of Wrong." The Skeptical Inquirer,
> 14(1), 35-44. Fall 1989.
> http://chem.tufts.edu/AnswersInScience/RelativityofWrong.htm
>
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-- 
Oliver Ruebenacker, Bioinformatics and Network Analysis Consultant
President and Founder of Knowomics
(http://www.knowomics.com/wiki/Oliver_Ruebenacker)
Consultant at Predictive Medicine
(http://predmed.com/people/oliverruebenacker.html)
SBPAX: Turning Bio Knowledge into Math Models (http://www.sbpax.org)