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, ..., model = "open")
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,
...,
retain_unique = FALSE,
remove_self = FALSE
)
st_covers(x, y, sparse = TRUE, prepared = TRUE, ..., model = "closed")
st_covered_by(x, y = x, sparse = TRUE, prepared = TRUE, ..., model = "closed")
st_equals_exact(x, y, par, sparse = TRUE, prepared = FALSE, ...)
st_is_within_distance(x, y = x, dist, sparse = TRUE, ..., remove_self = FALSE)
If sparse=FALSE
, st_predicate
(with predicate
e.g. "intersects") returns a dense logical matrix with element i,j
equal to 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
is returned, which is 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 a zero-length integer vector 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.
object of class sf
, sfc
or sfg
object of class sf
, sfc
or sfg
; if missing, x
is used
logical; should a sparse index list be returned (TRUE
) or a dense logical matrix? See below.
Arguments passed on to s2::s2_options
snap
Use s2_snap_identity()
, s2_snap_distance()
, s2_snap_level()
,
or s2_snap_precision()
to specify how or if coordinate rounding should
occur.
snap_radius
As opposed to the snap function, which specifies the maximum distance a vertex should move, the snap radius (in radians) sets the minimum distance between vertices of the output that don't cause vertices to move more than the distance specified by the snap function. This can be used to simplify the result of a boolean operation. Use -1 to specify that any minimum distance is acceptable.
duplicate_edges
Use TRUE
to keep duplicate edges (e.g., duplicate
points).
edge_type
One of 'directed' (default) or 'undirected'.
validate
Use TRUE
to validate the result from the builder.
polyline_type
One of 'path' (default) or 'walk'. If 'walk', polylines that backtrack are preserved.
polyline_sibling_pairs
One of 'discard' (default) or 'keep'.
simplify_edge_chains
Use TRUE
to remove vertices that are within
snap_radius
of the original vertex.
split_crossing_edges
Use TRUE
to split crossing polyline edges
when creating geometries.
idempotent
Use FALSE
to apply snap even if snapping is not necessary
to satisfy vertex constraints.
dimensions
A combination of 'point', 'polyline', and/or 'polygon'
that can used to constrain the output of s2_rebuild()
or a
boolean operation.
logical; prepare geometry for x
, before looping over y
? See Details.
character; polygon/polyline model; one of "open", "semi-open" or "closed"; see Details.
logical; if TRUE
(and y
is missing) return only indexes of points larger than the current index; this can be used to select unique geometries, see examples. This argument can be used for all geometry predicates; see also distinct.sf to find records where geometries AND attributes are distinct.
logical; if TRUE
(and y
is missing) return only indexes of geometries different from the current index; this can be used to omit self-intersections; see examples. This argument can be used for all geometry predicates
numeric; parameter used for "equals_exact" (margin);
distance threshold; geometry indexes with distances smaller or equal to this value are returned; numeric value or units value having distance units.
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 https://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 do not; st_is_within_distance
uses a spatial index for geographic coordinates when sf_use_s2()
is true.
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.
for model
, see https://github.com/r-spatial/s2/issues/32
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.
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))
(mat = st_intersects(pts, pol, sparse = FALSE))
# which points fall inside a polygon?
apply(mat, 1, any)
lengths(lst) > 0
# which points fall inside the first polygon?
st_intersects(pol, pts)[[1]]
# remove duplicate geometries:
p1 = st_point(0:1)
p2 = st_point(2:1)
p = st_sf(a = letters[1:8], geom = st_sfc(p1, p1, p2, p1, p1, p2, p2, p1))
st_equals(p)
st_equals(p, remove_self = TRUE)
(u = st_equals(p, retain_unique = TRUE))
# retain the records with unique geometries:
p[-unlist(u),]
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