Tarmo Remmel wrote on 09/20/2011 09:51:45 AM:>
> Hello list members,
>
> I am working with simulated data for landscape pattern analysis. I have
> 1000 replicates of binary (2 colour) gridded landscapes at each
combination> of 9 levels of class proportion and 11 levels of spatial
autocorrelation.> The results are stored in an array as follows:
>
> > dim(surfaces)
> [1] 38 9 11 1000
>
> The dimensions are defined as follows:
> [x,,,] 1:38, integers that identify a measurement type (landscape
pattern> metrics)
> [,x,,] 1:9, integers that identify levels of class proportion
> [,,x,] 1:11, integers that identify levels of spatial autocorrelation
> [,,,x] floating point values for the specific landscape metric
>
> I would like a simple way to produce boxplots of the 1000 metric values
for> a specific landscape metric and level of spatial autocorrelation across
the> 9 levels of proportion. Thus, I want to fix the first dimension (say as
10)> and fix the third dimension (say as 1), and then use the second
dimension as> factors (1:9) to produce boxplots of the values in the 4th dimension. Is
> there a simple way to do this?
>
> I have been playing with boxplot() and apply() but am getting some
> dimensions mixed up and thought that this would be a good time to seek
some> help. Any help with this would be greatly appreciated.
>
> Thank you,
>
> Tarmo
>
>
> _____________________________________
> Tarmo K Remmel PhD
> Associate Professor, Department of Geography
> York University, N413A Ross Building
> 4700 Keele Street, Toronto, Ontario, M3J 1P3
> Tel: 416-736-2100 x22496, Fax: 416-736-5988
> Skype: tarmoremmel
Try this:
mybox <- function(arr, type, autocorr) {
y <- arr[type, , autocorr, ]
class <- as.factor(as.vector(row(y)))
metric <- as.vector(y)
plot(class, metric)
}
mybox(surfaces, 10, 1)
Jean
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