Geometric binary predicates on pairs of simple feature geometry sets

st_intersects(x, y, sparse = TRUE, ...)

st_disjoint(x, y = x, sparse = TRUE, prepared = TRUE)

st_touches(x, y, sparse = TRUE, prepared = TRUE)

st_crosses(x, y, sparse = TRUE, prepared = TRUE)

st_within(x, y, sparse = TRUE, prepared = TRUE)

st_contains(x, y, sparse = TRUE, prepared = TRUE)

st_contains_properly(x, y, sparse = TRUE, prepared = TRUE)

st_overlaps(x, y, sparse = TRUE, prepared = TRUE)

st_equals(x, y, sparse = TRUE, prepared = FALSE)

st_covers(x, y, sparse = TRUE, prepared = TRUE)

st_covered_by(x, y, sparse = TRUE, prepared = TRUE)

st_equals_exact(x, y, par, sparse = TRUE, prepared = FALSE)

st_is_within_distance(x, y, dist, sparse = TRUE)

Arguments

x	object of class `sf`, `sfc` or `sfg`
y	object of class `sf`, `sfc` or `sfg`; if missing, `x` is used
sparse	logical; should a sparse index list be returned (TRUE) or a dense logical matrix? See below.
...	ignored
prepared	logical; prepare geometry for x, before looping over y? See Details.
par	numeric; parameter used for "equals_exact" (margin);
dist	distance threshold; geometry indexes with distances smaller or equal to this value are returned; numeric value or units value having distance units.

Value

If sparse=FALSE, st_predicate (with predicate e.g. "intersects") returns a dense logical matrix with element i,j TRUE when predicate(x[i], y[j]) (e.g., when geometry of feature i and j intersect); if sparse=TRUE, an object of class sgbp with a sparse list representation of the same matrix, with list element i an integer vector with all indices j for which predicate(x[i],y[j]) is TRUE (and hence integer(0) if none of them is TRUE). From the dense matrix, one can find out if one or more elements intersect by apply(mat, 1, any), and from the sparse list by lengths(lst) > 0, see examples below.

Details

If prepared is TRUE, and x contains POINT geometries and y contains polygons, then the polygon geometries are prepared, rather than the points.

For most predicates, a spatial index is built on argument x; see http://r-spatial.org/r/2017/06/22/spatial-index.html. Specifically, st_intersects, st_disjoint, st_touches st_crosses, st_within, st_contains, st_contains_properly, st_overlaps, st_equals, st_covers and st_covered_by all build spatial indexes for more efficient geometry calculations. st_relate, st_equals_exact, and st_is_within_distance do not.

If y is missing, `st_predicate(x, x)` is effectively called, and a square matrix is returned with diagonal elements `st_predicate(x[i], x[i])`.

Sparse geometry binary predicate (sgbp) lists have the following attributes: region.id with the row.names of x (if any, else 1:n), ncol with the number of features in y, and predicate with the name of the predicate used.

`st_contains_properly(A,B)` is true if A intersects B's interior, but not its edges or exterior; A contains A, but A does not properly contain A.

See also st_relate and https://en.wikipedia.org/wiki/DE-9IM for a more detailed description of the underlying algorithms.

st_equals_exact returns true for two geometries of the same type and their vertices corresponding by index are equal up to a specified tolerance.

Note

For intersection on pairs of simple feature geometries, use the function st_intersection instead of st_intersects.

Examples

pts = st_sfc(st_point(c(.5,.5)), st_point(c(1.5, 1.5)), st_point(c(2.5, 2.5)))
pol = st_polygon(list(rbind(c(0,0), c(2,0), c(2,2), c(0,2), c(0,0))))
(lst = st_intersects(pts, pol))
#> Sparse geometry binary predicate list of length 3, where the predicate was `intersects'
#>  1: 1
#>  2: 1
#>  3: (empty)
(mat = st_intersects(pts, pol, sparse = FALSE))
#>       [,1]
#> [1,]  TRUE
#> [2,]  TRUE
#> [3,] FALSE
# which points fall inside a polygon?
apply(mat, 1, any)
#> [1]  TRUE  TRUE FALSE
lengths(lst) > 0
#> [1]  TRUE  TRUE FALSE
# which points fall inside the first polygon?
st_intersects(pol, pts)[[1]]
#> [1] 1 2