R: Vector plots of Raster objects.

vectorplot-methods {rasterVis}

R Documentation

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 signature '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, ...)

## S4 method for signature '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, ...)

## S4 method for signature 'Raster'
streamplot(object, layers,
            droplet = list(), streamlet = list(),
            par.settings=streamTheme(),
            isField = FALSE, reverse=FALSE, 
            parallel=TRUE, mc.cores=detectCores(), cl=NULL,
            ...)

## S4 method for signature '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 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`.
`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`.
`reverse`	Logical, TRUE if arrows or streamlets go against the direction of the gradient.
`isField`	If `TRUE` (the object is a vector field), `object` must be a Raster* with two layers, slope and aspect (in this order), following the philosophy of `terrain`. If `isField='dXY'` `object` must be a Raster* with two layers representing the horizontal and the vertical components, respectively.
`unit`	Character, angle units of the `aspect` layer if `isField=TRUE`: 'radians' or 'degrees'.
`...`	Additional arguments for `levelplot`

Author(s)

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

Examples

## Not run: 
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))

## End(Not run)

[Package rasterVis version 0.32 Index]