Extract values from 'tripGrid' output for Mantel test?

Hello, tripGrid returns a SpatialGridDataFrame (package sp) and so
from that step you only need to know about that class.

I'll use a data set in sp to create an object like yours:

library(sp)
data(meuse.grid)
coordinates(meuse.grid) <- ~x+y
gridded(meuse.grid) <- TRUE
fullgrid(meuse.grid) <- TRUE
class(meuse.grid)
tpc.for <- meuse.grid

class(tpc.for)
[1] "SpatialGridDataFrame"
attr(,"package")
[1] "sp"


Notice that this object can contain multiple attributes, and this
example data does:

names(tpc.for)
[1] "part.a" "part.b" "dist"   "soil"   "ffreq"

but tripGrid just returns a grid with one attribute named "z". You can index the
layers by name or number e.g. tpc.for[1] or tpc.for["part.a"], and plotting will
assume just using the first.

So to get data as an R matrix, you can use either of these, keeping in mind the
different orientation conventions. I prefer the image() based one
simply because I'm
used to how it works, but they are just the transpose of each other:

ff1 <- as.matrix(tpc.for[1])
ff2 <- as.image.SpatialGridDataFrame(tpc.for[1])$z

(as.image... uses the same x,y,z name convention as image() which is
partly why tripGrid
unhelpfully uses that as well).

Compare these which show that one is the column-reversed version of
the other, and that
image()'s orientation is not quite obvious:

par(mfrow = c(2,2))
image(ff1, main = "ff1 <- as.matrix(x)")
image(ff2, main = "ff2 <- as.image.SpatialGridDataFrame(x)$z")
image(ff2[,ncol(ff2):1], main = "ff2[,ncol(ff2):1]")

I hope that helps, it probably does not matter which one you use but
it's important
to know the difference.

Cheers, Mike.

Hi,

I am testing levels of association between an environmental variable,
extracted from a raster, and a time spent per unit area grid, created using
the 'trip' package to determine whether the habtiat variable influences the
amount of time spent in that grid cell by an animal.  Both grids have been
set to the same resolution.  I would like to use a Mantel test to assess
levels of 2D correlation.  I have created a dissimilarity matrix using
values extracted from the raster and now need a comparable matrix
describing the 'time spent' data.

These 'time spent' data are arranged as a slot in a SpatialGridDataFrame,
known here as tpc.for at data$z.  When I try to extract these data as a matrix:

ff <- as.matrix(tpc.for at data$z)

the resultant object is only one-dimensional and then when I try to apply
the function 'distance' from package 'ecodist', to calculate dissimilarity
matrix, I get the following error:

gg <- distance(ff, "bray-curtis")

Error in numeric(N * N * P) : vector size cannot be NA
In addition: Warning message:
In N * N : NAs produced by integer overflow

Any ideas on how I can extract the time spent values from the 'trip' object
as a matrix, the dimensions of which will match the raster dimensions?
Using 'image' plots the values at the same resolution.

Any help would be very much appreciated.

Kylie Scales

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Michael Sumner
Hobart, Australia
e-mail: mdsumner at gmail.com