gstat (version 1.0-2)

plot.gstatVariogram: 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, ..., col = bpy.colors(), xlab, ylab, map = TRUE,
		convertMonths = FALSE, wireframe = FALSE, both = 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 vari
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
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-tim 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
wireframe
logical; if TRUE, produce a wireframe plot
both
logica; if TRUE, plot model and sample variogram in a single wireplot

Value

  • returns (or plots) the variogram plot

References

http://www.gstat.org

See Also

variogram, fit.variogram, vgm variogramLine,

Examples

Run this code
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")

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