plot.gstatVariogram: Plot a sample variogram, and possibly a fitted model

In gstat: Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and Simulation

Plot a sample variogram, and possibly a fitted model

Description

Creates a variogram plot

Usage

## S3 method for class 'gstatVariogram'
plot(x, model = NULL, ylim, xlim, xlab = "distance", 
	ylab = attr(x, "what"), panel = vgm.panel.xyplot, multipanel = TRUE, 
	plot.numbers = FALSE, scales, ids = x$id, group.id = TRUE, skip, 
	layout, ...)
## S3 method for class 'variogramMap'
plot(x, np = FALSE, skip, threshold, ...)
## S3 method for class 'StVariogram'
plot(x, model = NULL, ..., col = bpy.colors(), xlab, ylab, 
	map = TRUE, convertMonths = FALSE, as.table = TRUE, wireframe = FALSE, 
	diff = FALSE, all = FALSE)

Arguments

x	object obtained from the method variogram, possibly containing directional or cross variograms, space-time variograms and variogram model information
model	in case of a single variogram: a variogram model, as obtained from vgm or fit.variogram, to be drawn as a line in the variogram plot; in case of a set of variograms and cross variograms: a list with variogram models; in the spatio-temporal case, a single or a list of spatio-temporal models that will be plotted next to each other for visual comparison.
ylim	numeric; vector of length 2, limits of the y-axis
xlim	numeric; vector of length 2, limits of the x-axis
xlab	character; x-axis label
ylab	character; y-axis label
panel	panel function
multipanel	logical; if TRUE, directional variograms are plotted in different panels, if FALSE, directional variograms are plotted in the same graph, using color, colored lines and symbols to distinguish them
plot.numbers	logical or numeric; if TRUE, plot number of point pairs next to each plotted semivariance symbol, if FALSE these are omitted. If numeric, TRUE is assumed and the value is passed as the relative distance to be used between symbols and numeric text values (default 0.03).
scales	optional argument that will be passed to xyplot in case of the plotting of variograms and cross variograms; use the value list(relation = "same") if y-axes need to share scales
ids	ids of the data variables and variable pairs
group.id	logical; control for directional multivariate variograms: if TRUE, panels divide direction and colors indicate variables (ids), if FALSE panels divide variables/variable pairs and colors indicate direction
skip	logical; can be used to arrange panels, see xyplot
layout	integer vector; can be used to set panel layout: c(ncol,nrow)
np	logical (only for plotting variogram maps); if TRUE, plot number of point pairs, if FALSE plot semivariances
threshold	semivariogram map values based on fewer point pairs than threshold will not be plotted
...	any arguments that will be passed to the panel plotting functions (such as auto.key in examples below)
col	colors to use
map	logical; if TRUE, plot space-time variogram map
convertMonths	logical; if TRUE, yearmon time lags will be unit converted and plotted as (integer) months, and no longer match the numeric representation of yearmon, which has years as unit
as.table	controls the plotting order for multiple panels, see xyplot for details.
wireframe	logical; if TRUE, produce a wireframe plot
diff	logical; if TRUE, plot difference between model and sample variogram; ignores all.
all	logical; if TRUE, plot sample and model variogram(s) in single wireframes.

Details

Please note that in the spatio-temporal case the levelplot and wireframe plots use the spatial distances averaged for each time lag avgDist. For strongly varying spatial locations over time, please check the distance columns dist and avgDist of the spatio-temporal sample variogram. The lattice::cloud function is one option to plot irregular 3D data.

Value

returns (or plots) the variogram plot

Note

currently, plotting models and/or point pair numbers is not supported when a variogram is both directional and multivariable; also, three-dimensional directional variograms will probably not be displayed correctly.

Author(s)

Edzer Pebesma

References

http://www.gstat.org

See Also

variogram, fit.variogram, vgm variogramLine,

Examples

library(sp)
data(meuse)
coordinates(meuse) = ~x+y
vgm1 <- variogram(log(zinc)~1, meuse)
plot(vgm1)
model.1 <- fit.variogram(vgm1,vgm(1,"Sph",300,1))
plot(vgm1, model=model.1)
plot(vgm1, plot.numbers = TRUE, pch = "+")
vgm2 <- variogram(log(zinc)~1, meuse, alpha=c(0,45,90,135))
plot(vgm2)
# the following demonstrates plotting of directional models:
model.2 <- vgm(.59,"Sph",926,.06,anis=c(0,0.3))
plot(vgm2, model=model.2)
 
g = gstat(NULL, "zinc < 200", I(zinc<200)~1, meuse)
g = gstat(g, "zinc < 400", I(zinc<400)~1, meuse)
g = gstat(g, "zinc < 800", I(zinc<800)~1, meuse)
# calculate multivariable, directional variogram:
v = variogram(g, alpha=c(0,45,90,135))
plot(v, group.id = FALSE, auto.key = TRUE) # id and id pairs panels
plot(v, group.id = TRUE, auto.key = TRUE)  # direction panels

# variogram maps:
plot(variogram(g, cutoff=1000, width=100, map=TRUE),
    main = "(cross) semivariance maps")
plot(variogram(g, cutoff=1000, width=100, map=TRUE), np=TRUE,
    main = "number of point pairs")

gstat documentation built on Sept. 11, 2024, 7:46 p.m.