Display a raster or vector

plot() displays a GRaster or GVector.

This function is essentially a hack, as it it not possible to dependably call the appropriate GRASS modules and display a raster or vector without potential confusion on the user side. Instead, this function 1) simplifies the focal GRaster or GVector to make it smaller when saved to disk; 2) writes the object to disk; 3) (internally) creates a SpatRaster or SpatVector object; then 4) plots the object using terra::plot(). Thus, if you are interested in making maps, it will always be faster to make them directly with terra or sf.

Usage

# S4 method for class 'GRaster,missing'
plot(x, y, simplify = TRUE, ...)

# S4 method for class 'GVector,missing'
plot(x, y, maxGeoms = 10000, ...)

Arguments

x

A GRaster or GVector.

y

Missing–leave as empty.

simplify

Logical: If TRUE (default) and the raster has an x- and/or y-resolution that is greater than the screen resolution, then aggregate() will be applied to the raster before it is saved to reduce the time it takes to save the raster.

...

Other arguments to send to terra::plot().

maxGeoms

Positive integer (vectors only): Maximum number of features before vector simplification is applied before saving to disk then creating a SpatVector for plotting. The default is 10000.

Value

Nothing (displays a raster or vector).

See also

terra::plot()

Examples

if (grassStarted()) {

# Setup
library(terra)

# Example data
madElev <- fastData("madElev") # elevation raster
madLANDSAT <- fastData("madLANDSAT") # multi-layer raster
madRivers <- fastData("madRivers") # lines vector

# Convert SpatRaster to GRaster and SpatVector to GVector
elev <- fast(madElev)
rivers <- fast(madRivers)
landsat <- fast(madLANDSAT)

# Plot:
plot(elev)
plot(rivers, add = TRUE)

# Histograms:
hist(elev)
hist(landsat)

# Plot surface reflectance in RGB:
plotRGB(landsat, 3, 2, 1) # "natural" color
plotRGB(landsat, 4, 1, 2, stretch = "lin") # emphasize near-infrared (vegetation)

# Make composite map from RGB layers and plot in grayscale:
comp <- compositeRGB(r = landsat[[3]], g = landsat[[2]], b = landsat[[1]])
grays <- paste0("gray", 0:100)
plot(comp, col = grays)

}