Hi,
I wonder whether similarly to the very quick rowSums and colSums
functions in the base package, one could add quick functions that
calculate the min or max over rows / cols in a matrix. While
apply(x,1,min) works, I found out by profiling a program of mine that it
is rather slow for matrices with a very large number of rows. A quick
functionality seems to be already there in the functions pmax and pmin,
but it is rather cumbersume to apply them to all columns of a matrix (if
one does not know how many columns the matrix has). Below, I have some
code that shows a very unelegant implementation that illustrates
possible speed gains if apply could be avoided:
rowMin = function(x) {
# Construct a call pmin(x[,1],x[,2],...x[,NCOL(x)])
code = paste("x[,",1:(NCOL(x)),"]",sep="",collapse=",")
code = paste("pmin(",code,")")
return(eval(parse(text=code)))
}
# Speed comparison: Taking rowMin of a 1,000,000 x 10 matrix
x = matrix(rnorm(1e7),1e6,10)
# The traditional apply method
y=apply(x,1,min) # Runtime ca. 12 seconds
# My unelegant rowMin function
z=rowMin(x) # Runtime ca 0.5 seconds
Of course, the way the function rowMin is constructed is highly
ineffective if the matrix x has many columns, but maybe there is a
simple way to adapt the code from pmin and pmax to create quick rowMin,
rowMax,... functions. I don't know whether it is worth the effort, but I
guess taking minima and maxima over rows is a common task.
Best wishes,
Sebastian
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