Description Usage Arguments Details Note Author(s) See Also Examples
Plots the interpolated grid.
1 2 3 | grid.image(intpl, grid, breaks=10, ic=1, colFUN=heat.colors,
main=colnames(intpl)[ic], xlab=colnames(grid)[1],
ylab=colnames(grid)[2], sclab=NA, ...)
|
intpl |
A matrix or vector with interpolation results. |
grid |
A table containing longitude and latitude of interpolated locations. |
breaks |
Number of breaks in the scale. |
ic |
Column index or name from 'intpl' table to show. Defaults to the first column. Can be used to plot standard deviation or any other column. This value is ignored of 'intpl' is a vector. |
colFUN |
Function to process colors. Can be any of R base color functions (e.g.
|
main |
Main title. |
xlab |
X axis label. Defaults to name of the first 'grid' column. |
ylab |
Y axis label. Defaults to name of the secont 'grid' column. |
sclab |
Scale label to plot under the scale bar. |
... |
Futher arguments to be passed to par. Most used is 'cex' to control the font size. |
This function may be used to produce a simple plot of the interpolated grid. It has some customizable features and it plots a scale bar of the Z values shown.
Does not work with multiple plots (e.g. with 'layout').
Pedro Tarroso <ptarroso@cibio.up.pt>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | data(vipers)
data(d.gen)
# create a grid of the sampled area for inteprolation
grid <- expand.grid(x=seq(-9.5,3,0.25), y=seq(36, 43.75, 0.25))
# create a distance matrix between samples
r.dist <- dist(vipers[,1:2])
# fit a model with defaults (shperical model) and estimation of range
gv <- gen.variogram(r.dist, d.gen, 0.25)
gv <- gv.model(gv)
# interpolation of the distances to first sample with ordinary kriging
int.krig <- krig(d.gen[,1], vipers[,1:2], grid, gv)
#plot the interpolation results
grid.image(int.krig, grid, main='Krigging Interpolation',
xlab='Longitude',ylab = 'Latitude',
sclab=paste('Genetic distance to sample',
colnames(d.gen)[1]))
# User can add extra elements to the main plot.
points(vipers[,1:2], cex=d.gen[,1]*15+0.2)
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