rasterVis (version 0.31)

vectorplot-methods: Vector plots of Raster objects.

Description

vectorplot displays vector fields from Raster objects using arrows.

streamplot displays streamlines with a procedure inspired by the FROLIC algorithm (see references): for each point (droplet) of a jittered regular grid, a short streamline portion (streamlet) is calculated by integrating the underlying vector field at that point. The main color of each streamlet indicates local vector magnitude (slope). Streamlets are composed of points whose sizes, positions and color degradation encode the local vector direction (aspect).

Usage

## S3 method for class 'Raster':
vectorplot(object, layers,
            narrows=2e3, lwd.arrows=0.6, col.arrows='black',
            length=unit(5e-2, 'npc'),
            maxpixels=1e5, region=TRUE, margin=FALSE,  
            isField=FALSE, reverse=FALSE,
            unit='radians', scaleSlope=TRUE,
            aspX=0.08, aspY=aspX, ...)
## S3 method for class 'RasterStack':
vectorplot(object, layers,
            narrows=2e3, lwd.arrows=0.6, col.arrows='black',
            length=unit(5e-2, 'npc'),
            maxpixels=1e5, region=TRUE, margin=FALSE,
            isField=FALSE, reverse=FALSE,
            unit='radians', scaleSlope=TRUE,
            aspX=0.08, aspY=aspX,
            uLayers, vLayers, ...)
## S3 method for class 'Raster':
streamplot(object, layers,
            droplet = list(), streamlet = list(),
            par.settings=streamTheme(),
            isField = FALSE, reverse=FALSE, 
            parallel=TRUE, mc.cores=detectCores(), cl=NULL,
            ...)
## S3 method for class 'RasterStack':
streamplot(object, layers,
            droplet = list(), streamlet = list(),
            par.settings=streamTheme(),
            isField = FALSE, reverse=FALSE, 
            parallel=TRUE, mc.cores=detectCores(), cl=NULL,
            ...)

Arguments

object

A Raster object. If isField=FALSE the vector field is calculated internally from the result of terrain.

layers

A numeric or character which should indicate the layers to be displayed.

maxpixels

A numeric, number of cells to be shown if region=TRUE or if region is a Raster* object.

narrows

A numeric, number of arrows.

lwd.arrows

Numeric, width of the lines of the arrows

col.arrows

character, color of the arrows

length

Unit, extent of the arrow head.

margin

Logical, if TRUE two marginal graphics show the summaries of the object.

scaleSlope

Logical or numeric. If TRUE the slope is scaled (but not centered) with its standard deviation. If it is a numeric, the slope is scaled with this value. It is not used if isField='dXY'.

aspX, aspY

Numeric. Multipliers to convert the slope values into horizontal (aspX) and vertical (aspY) displacements.

uLayers, vLayers

Numeric, indexes of layers with horizontal and vertical components, respectively, when isField='dXY' and the RasterStack has more than 2 layers. If missing, the horizontal components are the layers of the first half of the

droplet

A list whose elements define the droplet configuration:

• cropExtent: Percentage of the object extent to be cropped (default .97) to avoid droplets at boundaries

pc: A numeric. It is the percentage of cells used to compute drople

item

• streamlet
• h: streamlet calculation step (default mean(res(object))).
• par.settings
• parallel
• cl
• mc.cores
• region
• reverse
• isField
• unit
• ...

itemize

• L: length of the streamlet (number of points, default 10)

code

levelplot

References

R. Wegenkittl and E. Gröller, Fast Oriented Line Integral Convolution for Vector Field Visualization via the Internet, Proceedings IEEE Visualization ’97, 1997, http://www.cg.tuwien.ac.at/research/vis-dyn-syst/frolic/frolic_crc.pdf

See Also

panel.arrows, levelplot, terrain, mclapply, parLapply

Examples

proj <- CRS('+proj=longlat +datum=WGS84')

df <- expand.grid(x=seq(-2, 2, .01), y=seq(-2, 2, .01))
df$z <- with(df, (3*x^2 + y)*exp(-x^2-y^2))
r1 <- rasterFromXYZ(df, crs=proj)
df$z <- with(df, x*exp(-x^2-y^2))
r2 <- rasterFromXYZ(df, crs=proj)
df$z <- with(df, y*exp(-x^2-y^2))
r3 <- rasterFromXYZ(df, crs=proj)
s <- stack(r1, r2, r3)
names(s) <- c('R1', 'R2', 'R3')

vectorplot(r1)
vectorplot(r2, par.settings=RdBuTheme())
vectorplot(r3, par.settings=PuOrTheme())

## scaleSlope, aspX and aspY
vectorplot(r1, scaleSlope=FALSE)
vectorplot(r1, scaleSlope=1e-5)
vectorplot(r1, scaleSlope=5e-6, alpha=0.6)
vectorplot(r1, scaleSlope=TRUE, aspX=0.1, alpha=0.6)
vectorplot(r1, scaleSlope=TRUE, aspX=0.3, alpha=0.3)

## A vector field defined with horizontal and vertical components
u <- v <- raster(xmn=0, xmx=2, ymn=0, ymx=2, ncol=1e3, nrow=1e3)
x <- init(u, v='x')
y <- init(u, v='y')
u <- y * cos(x)
v <- y * sin(x) 
field <- stack(u, v)
names(field) <- c('u', 'v')

vectorplot(field, isField='dXY', narrows=5e2)

## We can display both components as the background
vectorplot(field, isField='dXY', narrows=5e2, region=field)

## Or even compute the slope and use it as the background region
slope <- sqrt(u^2 + y^2)
vectorplot(field, isField='dXY', narrows=5e2,
           region=slope, par.settings=BTCTheme())


## It is also possible to use a RasterStack
## with more than 2 layers when isField='dXY'
u1 <- cos(y) * cos(x)
v1 <- cos(y) * sin(x)
u2 <- sin(y) * sin(x)
v2 <- sin(y) * cos(x)
field <- stack(u, u1, u2, v, v1, v2)
names(field) <- c('u', 'u1', 'u2', 'v', 'v1', 'v2')

vectorplot(field, isField='dXY',
           narrows=300, lwd.arrows=.4,
           par.settings=BTCTheme(),
           layout=c(3, 1))

## uLayer and vLayer define which layers contain
## horizontal and vertical components, respectively
vectorplot(field, isField='dXY',
           narrows=300,
           uLayer=1:3,
           vLayer=6:4)

##################################################################
## Streamplot
##################################################################
## If no cluster is provided, streamplot uses parallel::mclapply except
## with Windows. Therefore, next code could spend a long time under
## Windows.
streamplot(r1)

## With a cluster
hosts <- rep('localhost', 4)
cl <- makeCluster(hosts)
streamplot(r2, cl=cl,
           par.settings=streamTheme(symbol=brewer.pal(n=5,
                                                      name='Reds')))
stopCluster(cl)

## Without parallel
streamplot(r3, parallel=FALSE,
           par.settings=streamTheme(symbol=brewer.pal(n=5,
                                                      name='Greens')))

## Configuration of droplets and streamlets
streamplot(s, layout=c(1, 3), droplet=list(pc=.2), streamlet=list(L=20),
           par.settings=streamTheme(cex=.6))