rasterVis (version 0.51.6)

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

# S4 method for Raster
vectorplot(object, layers,
            narrows=2e3, lwd.arrows=0.6, col.arrows='black',
            length=unit(1e-2, 'npc'),
            maxpixels=1e5, region=TRUE, margin=FALSE,  
            isField=FALSE, reverse=FALSE,
            unit='radians', scaleSlope=TRUE,
            aspX=0.08, aspY=aspX,
            key.arrow = NULL,
            ...)
# S4 method for RasterStack
vectorplot(object, layers,
            narrows=2e3, lwd.arrows=0.6, col.arrows='black',
            length=unit(1e-2, 'npc'),
            maxpixels=1e5, region=TRUE, margin=FALSE,
            isField=FALSE, reverse=FALSE,
            unit='radians', scaleSlope=TRUE,
            aspX=0.08, aspY=aspX,
            key.arrow = NULL,
            uLayers, vLayers, ...)
# S4 method for Raster
streamplot(object, layers,
            droplet = list(), streamlet = list(),
            par.settings = streamTheme(),
            colorkey = FALSE,
            isField = FALSE, reverse = FALSE, 
            parallel = TRUE, mc.cores = detectCores(), cl = NULL,
            ...)
# S4 method for RasterStack
streamplot(object, layers,
            droplet = list(), streamlet = list(),
            par.settings=streamTheme(),
            colorkey = FALSE,
            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 (vector magnitude) 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.

key.arrow

A reference (or legend) vector. If is not NULL, it is a list with two named components, size, a numeric to define the length of the arrow (default 1), and label, a character to define the label (default '').

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 object, and the vertical components are the layers of the second half.

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 droplets. Its default value is 0.5. Therefore, only the 0.5% of the cells are used. For example, if you use a Raster with 180 rows and 360 columns (64800 cells), with this default value streamplot will produce 324 droplets.

streamlet

A list whose elements define the streamlet configuration:

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

• h: streamlet calculation step (default mean(res(object))).

par.settings

A list to define the graphical parameters. For streamplot there is an specific theme, streamTheme.

colorkey

A logical specifying whether a color key is to be drawn alongside the plot (default is FALSE), or a list describing the color key (see the colorkey section of the help page of levelplot for details).

parallel

Logical, TRUE (default) to use parallel package.

cl

a cluster object. Read the help page of parLapply for details.

mc.cores

The number of cores to use if parallel=TRUE and no cl is provided. Read the help page of mclapply for details.

region

Logical, if TRUE the region is displayed as the background using levelplot. It can be a Raster* with the same extent and resolution as object.

isField

If TRUE the object is a vector field. Thus, object must be a Raster* with two layers, slope (local vector magnitude) and aspect (local vector direction), in this order. The aspect angle, following the conventions of raster::terrain, must be computed clockwise from 0 (due north). The slope layer will be used as the background if region is TRUE.

If isField='dXY' object must be a Raster* with two layers representing the horizontal and the vertical components, respectively. The slope is computed and used as the background if region is TRUE.

unit

Character, angle units of the aspect layer if isField=TRUE: 'radians' or 'degrees'.

reverse

Logical, if isField=TRUE and reverse=TRUE, arrows or streamlets go against the direction of the gradient.

...

Additional arguments for levelplot

Author

Oscar Perpiñán Lamigueiro

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

if (FALSE) {
library(raster)

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)


## Reference vector
# Default size (1)
vectorplot(r1, region = FALSE,
           key.arrow = list(label = 'm/s'))
vectorplot(r1, region = FALSE,
           key.arrow = list(size = 2, label = 'm/s'))

## 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 <- raster::init(u, fun='x')
y <- raster::init(u, fun='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)

## 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 <- parallel::makeCluster(hosts)
palRed <- RColorBrewer::brewer.pal(n = 5, name = 'Reds')
streamplot(r2, cl=cl,
           par.settings=streamTheme(symbol= palRed))
parallel::stopCluster(cl)

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

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