GVectors represent two types of "geometries". In "singlepart" geometries, each point, set of connected line segments, or polygon is treated like its own feature and has its own row in an attribute table. For example, a province might be composed of islands. In this case, each island would be represented as its own feature and could have its own row in the attribute indicating, say, the name and area of each island.
In "multipart" geometries, features are collected together and thu manipulated as if they were a single feature and have a singe line in an attribute table. Each multipart feature can contain one or more singlepart features. For example, all of the islands comprising province would be collated together and have a single row in the attribute table indicating the name of the province and the area of the entire province.
ngeom() returns the number of geometries. Singlepart features are treated as one geometry each, and multipart features are treated as one geometry each.
nsubgeom() Returns the number of subgeometries. Singlepart geometries each represent a single subgeometry. Multipart geometries represent one or more subgeometries. The number of subgeometries will thus always be the same as or more than the number of geometries.
Examples
if (grassStarted()) {
# Setup
library(sf)
# Example data:
madCoast4 <- fastData("madCoast4")
madRivers <- fastData("madRivers")
madDypsis <- fastData("madDypsis")
# Convert sf vectors to GVectors:
coast <- fast(madCoast4)
rivers <- fast(madRivers)
dypsis <- fast(madDypsis)
# Geographic properties:
ext(rivers) # extent
crs(rivers) # coordinate reference system
st_crs(rivers) # coordinate reference system
coordRef(rivers) # coordinate reference system
# Column names and data types:
names(coast)
datatype(coast)
# Points, lines, or polygons?
geomtype(dypsis)
geomtype(rivers)
geomtype(coast)
is.points(dypsis)
is.points(coast)
is.lines(rivers)
is.lines(dypsis)
is.polygons(coast)
is.polygons(dypsis)
# Number of dimensions:
topology(rivers)
is.2d(rivers) # 2-dimensional?
is.3d(rivers) # 3-dimensional?
# Just the data table:
as.data.frame(rivers)
as.data.table(rivers)
# Top/bottom of the data table:
head(rivers)
tail(rivers)
# Vector or table with just selected columns:
names(rivers)
rivers$NAME
rivers[[c("NAM", "NAME_0")]]
rivers[[c(3, 5)]]
# Select geometries/rows of the vector:
nrow(rivers)
selected <- rivers[2:6]
nrow(selected)
# Plot:
plot(coast)
plot(rivers, col = "blue", add = TRUE)
plot(selected, col = "red", lwd = 2, add = TRUE)
# Vector math:
hull <- convHull(dypsis)
un <- union(coast, hull)
sameAsUnion <- coast + hull
plot(un)
plot(sameAsUnion)
inter <- intersect(coast, hull)
sameAsIntersect <- coast * hull
plot(inter)
plot(sameAsIntersect)
er <- erase(coast, hull)
sameAsErase <- coast - hull
plot(er)
plot(sameAsErase)
xr <- xor(coast, hull)
sameAsXor <- coast / hull
plot(xr)
plot(sameAsXor)
# Vector area and length:
expanse(coast, unit = "km") # polygons areas
expanse(rivers, unit = "km") # river lengths
### Fill holes
# First, we will make some holes by creating buffers around points.
buffs <- buffer(dypsis, 500)
holes <- coast - buffs
plot(holes)
filled <- fillHoles(holes, fail = FALSE)
}