Plot a Spatially Sampled Function
Plot a spatially sampled function object.
## S3 method for class 'ssf'
plot(x, ...,
how = c("smoothed", "nearest", "points"),
style = c("image", "contour", "imagecontour"),
sigma = NULL, contourargs=list())
## S3 method for class 'ssf'
image(x, ...)
## S3 method for class 'ssf'
contour(x, ..., main, sigma = NULL)x |
Spatially sampled function (object of class |
... |
Arguments passed to |
how |
Character string determining whether to display the
function values at the data points ( |
style |
Character string indicating whether to plot the smoothed function as a colour image, a contour map, or both. |
contourargs |
Arguments passed to |
sigma |
Smoothing bandwidth for smooth interpolation. |
main |
Optional main title for the plot. |
An object of class "ssf" represents a
function (real- or vector-valued) that has been
sampled at a finite set of points.
For plot.ssf there are three types of display.
If how="points" the exact function values
will be displayed as circles centred at the locations where they
were computed. If how="smoothed" (the default) these
values will be kernel-smoothed using Smooth.ppp
and displayed as a pixel image.
If how="nearest" the values will be interpolated
by nearest neighbour interpolation using nnmark
and displayed as a pixel image.
For image.ssf and contour.ssf the values are
kernel-smoothed before being displayed.
NULL.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au.
Baddeley, A. (2017) Local composite likelihood for spatial point processes. Spatial Statistics 22, 261–295.
Baddeley, A., Rubak, E. and Turner, R. (2015) Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC Press.
a <- ssf(cells, nndist(cells, k=1:3)) plot(a, how="points") plot(a, how="smoothed") plot(a, how="nearest")
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.