R

Level and contour plots of Raster objects.

calsalmon February 21, 2014

Description

Level and contour plots of Raster objects with lattice methods and marginal plots with grid objects.

Usage

## S4 method for signature 'Raster,missing'
levelplot(x, data=NULL, layers,
            margin=!(any(is.factor(x))), FUN.margin=mean, 
            maxpixels=1e5,
            par.settings=rasterTheme(),
            between=list(x=0.5, y=0.2),
            as.table=TRUE,
            xlab='', ylab='', main='',
            names.attr,
            scales=list(), scales.margin=NULL,
            xscale.components=xscale.raster,
            yscale.components=yscale.raster,
            zscaleLog=NULL,
            colorkey=list(space='right'),
            panel=panel.levelplot,
            contour=FALSE, region=TRUE, labels=FALSE,
            ...)

## S4 method for signature 'Raster,missing'
contourplot(x, data=NULL, layers, ...)

Arguments

x A Raster object.
data Not used.
layers A numeric or character which should indicate the layers to be displayed.
margin logical, if TRUE a marginal plot of the FUN.margin function to each coordinate will be displayed.
FUN.margin A function to be applied to each coordinate.
scales.margin A list with components x and y. Each of these components is a numeric vector of length 2 defining the range for each marginal plot. If scales.margin=NULL the range is internally computed.
maxpixels A numeric, for sampleRegular.
xlab, ylab, main Arguments for levelplot.
names.attr Character, names to use in each panel. If missing its default value is the result of names(x) (after subsetting the layers to be displayed).
xscale.components, yscale.components See xscale.raster and yscale.raster.
between, as.table, par.settings, scales, colorkey, panel, contour, region, labels Graphical parameters of lattice. See xyplot for details.
zscaleLog Controls whether the Raster* will be log transformed before being passed to the panel function. Defaults to ???NULL???, in which case the Raster* is not transformed. Other possible values are any number that works as a base for taking logarithm, ???TRUE??? (which is equivalent to 10), and ???”e”??? (for the natural logarithm). As a side effect, the colorkey is labeled differently.
... Additional arguments for levelplot

Details

The result of the levelplot method is similar to the spplot method for Raster objects defined in the raster package. However, this method does not use the spplot of the sp package and, therefore, no conversion between classes is needed.

The contourplot method is a wrapper for levelplot with the next additional default settings: cuts=7, labels=TRUE, contour=TRUE,pretty=TRUE, region=TRUE and colorkey=TRUE (see the help of contourplot for details.)

levelplot displays categorical data with a convenient legend. You should use ratify to define a layer as a categorical variable. It is able to display multilayer categorical rasters only if they share the same RAT (Raster Attribute Table). levelplot is not able to display multilayer rasters with factor and numeric layers. See ratify and the examples below for details.

Author(s)

Oscar Perpi????n Lamigueiro

See Also

spplot, levelplot

Examples

f <- system.file("external/test.grd", package="raster")
r <- raster(f)
levelplot(r)

## With subticks
levelplot(r, xscale.components=xscale.raster.subticks,
             yscale.components=yscale.raster.subticks)

levelplot(r, xscale.components=xscale.raster.subticks,
             yscale.components=yscale.raster.subticks,
             scales=list(x=list(rot=30, cex=0.8)))

## defining the scales for the marginal plot
levelplot(r, scales.margin=list(x=c(100, 600), y=c(100, 1000)))
## if a component of the list is null, it is internally calculated
levelplot(r, scales.margin=list(x=c(100, 1000)))

## log-scale
levelplot(r^2, zscaleLog=TRUE, contour=TRUE)

s <- stack(r, r+500, r-500)
levelplot(s, contour=TRUE)
contourplot(s, labels=list(cex=0.4), cuts=12)

levelplot(s, names.attr=c('R', 'R + 500', 'R - 500'))

## Add a layer of sampling points
## and change the theme
pts <- sampleRandom(r, size=20, sp=TRUE)

## Using +.trellis and layer from latticeExtra
levelplot(r, par.settings = BTCTheme) + layer(sp.points(pts, col = 'red'))
contourplot(r, labels = FALSE) + layer(sp.points(pts, col = 'red'))

## or with a custom panel function
levelplot(r, par.settings=BTCTheme,
          panel=function(...){
            panel.levelplot(...)
            sp.points(pts, col='red')
            })

## Categorical data
r <- raster(nrow=10, ncol=10)
r[] = 1
r[51:100] = 3
r[3:6, 1:5] = 5
r <- ratify(r)

rat <- levels(r)[[1]]
rat$landcover <- c('Pine', 'Oak', 'Meadow')
levels(r) <- rat
r

levelplot(r, col.regions=c('palegreen', 'midnightblue', 'indianred1'))

r2 <- raster(r)
r2[] = 3
r2[51:100] = 1
r2[3:6, 1:5] = 5

r3 <- init(r, function(n)sample(c(1, 3, 5), n, replace=TRUE))

## Multilayer categorical Raster* are displayed only if their RATs are the same
levels(r2) <- levels(r3) <- levels(r)

s <- stack(r, r2, r3)
names(s) <- c('A', 'B', 'C')

levelplot(s)

## Not run: 
##Solar irradiation data from CMSAF
##Data available from http://www.box.net/shared/rl51y1t9sldxk54ogd44

old <- getwd()
##change to your folder...
setwd('CMSAF')
listFich <- dir(pattern='2008')
stackSIS <- stack(listFich)
stackSIS <- stackSIS*24 ##from irradiance (W/m2) to irradiation Wh/m2
setwd(old)

idx <- seq(as.Date('2008-01-15'), as.Date('2008-12-15'), 'month')

SISmm <- setZ(stackSIS, idx)
names(SISmm) <- month.abb

levelplot(SISmm)

levelplot(SISmm, layers=1, FUN.margin=median, contour=TRUE)

## End(Not run)

Results

R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-unknown-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(rasterVis)
Loading required package: raster
Loading required package: sp
Loading required package: lattice
Loading required package: latticeExtra
Loading required package: RColorBrewer
Loading required package: hexbin
Loading required package: grid
> png(filename="/home/oogasawa/snapshot/RGM3/R_CC/result/rasterVis/levelplot-methods.Rd_%03d_medium.png", width=480, height=480)
> ### Name: levelplot-methods
> ### Title: Level and contour plots of Raster objects.
> ### Aliases: levelplot contourplot levelplot,Raster,missing-method
> ###   contourplot,Raster,missing-method
> ### Keywords: methods spatial
> 
> ### ** Examples
> 
> f <- system.file("external/test.grd", package="raster")
> r <- raster(f)
> levelplot(r)
> 
> ## With subticks
> levelplot(r, xscale.components=xscale.raster.subticks,
+              yscale.components=yscale.raster.subticks)
> 
> levelplot(r, xscale.components=xscale.raster.subticks,
+              yscale.components=yscale.raster.subticks,
+              scales=list(x=list(rot=30, cex=0.8)))
> 
> ## defining the scales for the marginal plot
> levelplot(r, scales.margin=list(x=c(100, 600), y=c(100, 1000)))
> ## if a component of the list is null, it is internally calculated
> levelplot(r, scales.margin=list(x=c(100, 1000)))
> 
> ## log-scale
> levelplot(r^2, zscaleLog=TRUE, contour=TRUE)
> 
> s <- stack(r, r+500, r-500)
> levelplot(s, contour=TRUE)
> contourplot(s, labels=list(cex=0.4), cuts=12)
> 
> levelplot(s, names.attr=c('R', 'R + 500', 'R - 500'))
> 
> ## Add a layer of sampling points
> ## and change the theme
> pts <- sampleRandom(r, size=20, sp=TRUE)
> 
> ## Using +.trellis and layer from latticeExtra
> levelplot(r, par.settings = BTCTheme) + layer(sp.points(pts, col = 'red'))
> contourplot(r, labels = FALSE) + layer(sp.points(pts, col = 'red'))
> 
> ## or with a custom panel function
> levelplot(r, par.settings=BTCTheme,
+           panel=function(...){
+             panel.levelplot(...)
+             sp.points(pts, col='red')
+             })
> 
> 
> ## Categorical data
> r <- raster(nrow=10, ncol=10)
> r[] = 1
> r[51:100] = 3
> r[3:6, 1:5] = 5
> r <- ratify(r)
>      
> rat <- levels(r)[[1]]
> rat$landcover <- c('Pine', 'Oak', 'Meadow')
> levels(r) <- rat
> r
class       : RasterLayer 
dimensions  : 10, 10, 100  (nrow, ncol, ncell)
resolution  : 36, 18  (x, y)
extent      : -180, 180, -90, 90  (xmin, xmax, ymin, ymax)
coord. ref. : +proj=longlat +datum=WGS84 
data source : in memory
names       : layer 
values      : 1, 5  (min, max)
attributes  :
 ID landcover
  1      Pine
  3       Oak
  5    Meadow

> 
> levelplot(r, col.regions=c('palegreen', 'midnightblue', 'indianred1'))
> 
> r2 <- raster(r)
> r2[] = 3
> r2[51:100] = 1
> r2[3:6, 1:5] = 5
> 
> r3 <- init(r, function(n)sample(c(1, 3, 5), n, replace=TRUE))
> 
> ## Multilayer categorical Raster* are displayed only if their RATs are the same
> levels(r2) <- levels(r3) <- levels(r)
> 
> s <- stack(r, r2, r3)
> names(s) <- c('A', 'B', 'C')
> 
> levelplot(s)
> 
> 
> ## Not run: 
> ##D ##Solar irradiation data from CMSAF
> ##D ##Data available from http://www.box.net/shared/rl51y1t9sldxk54ogd44
> ##D 
> ##D old <- getwd()
> ##D ##change to your folder...
> ##D setwd('CMSAF')
> ##D listFich <- dir(pattern='2008')
> ##D stackSIS <- stack(listFich)
> ##D stackSIS <- stackSIS*24 ##from irradiance (W/m2) to irradiation Wh/m2
> ##D setwd(old)
> ##D 
> ##D idx <- seq(as.Date('2008-01-15'), as.Date('2008-12-15'), 'month')
> ##D 
> ##D SISmm <- setZ(stackSIS, idx)
> ##D names(SISmm) <- month.abb
> ##D 
> ##D levelplot(SISmm)
> ##D 
> ##D levelplot(SISmm, layers=1, FUN.margin=median, contour=TRUE)
> ## End(Not run)
> 
> 
> 
> 
> dev.off()
null device 
          1 
>