Thank you for the suggestions (off-list as well). I think the best
option may eventually be an explicit for loop to make things clearer.
To clarify a bit, I've used the plot function in the example where in
fact it is a numerical integration (which is why I need to pass an
additional variable in the second apply call),
intg <- function (y, x)
{
n <- length(x)
index <- order(x)
dx <- diff(sort(x))
z <- y[index]
ys <- (z[1:(n - 1)] + z[2:n])/2
sum(ys * dx)
}
<environment: namespace:PROcess>
Thanks again for the suggestions,
baptiste
On 30 May 2008, at 10:02, [EMAIL PROTECTED] wrote:
I need to apply a function on each column of each matrix contained in
a list. Consider the following code,
x <- 1:3
my.data <- list(matrix(c(1,2,3,4,5,6),ncol=2),
matrix(c(4,5,6,7,8,9),ncol=2))
par(mfrow=c(2,2))
results <- sapply(1:length(my.data),
function(ii) apply(my.data[[ii]], 2, function(y) plot
(x,y) ))
#
plot is for demonstration purposes
It works, but I think this is quite dirty code. Is there a simpler
way of achieving this?
The last line can be simplified
results <- sapply(my.data, function(x) apply(x,2,sum))
(It is perhaps a little clearer what is going on when you use sum
rather
than plot as the example function.)
Regards,
Richie.
Mathematical Sciences Unit
HSL
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