Dear James
Thank you. What would the saved time be (e.g. compared to the overall runtime
of arrayQualityMetrics)? I would be surprised if the saving was worth the added
complexity, but am always happy to be surprised.
A patch of the .R and .Rd file would be most welcome and expedite the change.
Btw, colSums apparently also works with 3-dim arrays, so both loops (over i and
j) could be vectorised, however afaIcs at the cost of constructing an object of
size nrow(x)^3 in memory, which might again break performance.
Best wishes
Wolfgang
Il giorno Mar 12, 2013, alle ore 4:43 PM, James F. Reid <rei...@gmail.com> ha
scritto:
> Dear bioc-devel,
>
> the dist2 function in genefilter defined as:
>
> dist2 <- function (x, fun = function(a, b) mean(abs(a - b), na.rm = TRUE),
> diagonal = 0) {
>
> if (!(is.numeric(diagonal) && (length(diagonal) == 1L)))
> stop("'diagonal' must be a numeric scalar.")
> res = matrix(diagonal, ncol = ncol(x), nrow = ncol(x))
> colnames(res) = rownames(res) = colnames(x)
> if (ncol(x) >= 2) {
> for (j in 2:ncol(x)) for (i in 1:(j - 1)) res[i, j] = res[j,
> i] = fun(x[, i], x[, j])
> }
> return(res)
> }
>
> could have it's default function vectorized as:
>
> res <- apply(x, 2, function(i) colMeans(abs(x - i), na.rm=TRUE))
>
> to improve performance for example in the ArrayQualityMetrics package.
>
> Best.
> James.
>
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