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Copy file name to clipboardExpand all lines: R/geom-predicates.R
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@@ -81,7 +81,7 @@ st_geos_binop = function(op, x, y, par = 0.0, pattern = NA_character_,
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#' @param y object of class \code{sf}, \code{sfc} or \code{sfg}
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#' @param pattern character; define the pattern to match to, see details.
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#' @param sparse logical; should a sparse matrix be returned (`TRUE`) or a dense matrix?
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#' @return In case \code{pattern} is not given, \code{st_relate} returns a dense \code{character} matrix; element `[i,j]` has nine characters, referring to the DE9-IM relationship between `x[i]` and `y[j]`, encoded as IxIy,IxBy,IxEy,BxIy,BxBy,BxEy,ExIy,ExBy,ExEy where I refers to interior, B to boundary, and E to exterior, and e.g. BxIy the dimensionality of the intersection of the the boundary of `x[i]` and the interior of `y[j]`, which is one of: 0, 1, 2, or F; digits denoting dimensionality of intersection, F denoting no intersection. When \code{pattern} is given, a dense logical matrix or sparse index list returned with matches to the given pattern; see \link{st_intersection} for a description of the returned matrix or list. See also \url{https://en.wikipedia.org/wiki/DE-9IM} for further explanation.
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#' @return In case \code{pattern} is not given, \code{st_relate} returns a dense \code{character} matrix; element `[i,j]` has nine characters, referring to the DE9-IM relationship between `x[i]` and `y[j]`, encoded as IxIy,IxBy,IxEy,BxIy,BxBy,BxEy,ExIy,ExBy,ExEy where I refers to interior, B to boundary, and E to exterior, and e.g. BxIy the dimensionality of the intersection of the the boundary of `x[i]` and the interior of `y[j]`, which is one of: 0, 1, 2, or F; digits denoting dimensionality of intersection, F denoting no intersection. When \code{pattern} is given, a dense logical matrix or sparse index list returned with matches to the given pattern; see \link{st_intersects} for a description of the returned matrix or list. See also \url{https://en.wikipedia.org/wiki/DE-9IM} for further explanation.
#' @param prepared logical; prepare geometry for `x`, before looping over `y`? See Details.
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#' @details If \code{prepared} is \code{TRUE}, and \code{x} contains POINT geometries and \code{y} contains polygons, then the polygon geometries are prepared, rather than the points.
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#' @return If \code{sparse=FALSE}, \code{st_predicate} (with \code{predicate} e.g. "intersects") returns a dense logical matrix with element \code{i,j} \code{TRUE} when \code{predicate(x[i], y[j])} (e.g., when geometry of feature i and j intersect); if \code{sparse=TRUE}, an object of class \code{\link{sgbp}} with a sparse list representation of the same matrix, with list element \code{i} an integer vector with all indices j for which \code{predicate(x[i],y[j])} is \code{TRUE} (and hence a zero-length integer vector if none of them is \code{TRUE}). From the dense matrix, one can find out if one or more elements intersect by \code{apply(mat, 1, any)}, and from the sparse list by \code{lengths(lst) > 0}, see examples below.
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#' @return If \code{sparse=FALSE}, \code{st_predicate} (with \code{predicate} e.g. "intersects") returns a dense logical matrix with element \code{i,j} equal to \code{TRUE} when \code{predicate(x[i], y[j])} (e.g., when geometry of feature i and j intersect); if \code{sparse=TRUE}, an object of class \code{\link{sgbp}} is returned, which is a sparse list representation of the same matrix, with list element \code{i} an integer vector with all indices \code{j} for which \code{predicate(x[i],y[j])} is \code{TRUE} (and hence a zero-length integer vector if none of them is \code{TRUE}). From the dense matrix, one can find out if one or more elements intersect by \code{apply(mat, 1, any)}, and from the sparse list by \code{lengths(lst) > 0}, see examples below.
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#' @details For most predicates, a spatial index is built on argument \code{x}; see \url{https://r-spatial.org/r/2017/06/22/spatial-index.html}.
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#' Specifically, \code{st_intersects}, \code{st_disjoint}, \code{st_touches} \code{st_crosses}, \code{st_within}, \code{st_contains}, \code{st_contains_properly}, \code{st_overlaps}, \code{st_equals}, \code{st_covers} and \code{st_covered_by} all build spatial indexes for more efficient geometry calculations. \code{st_relate}, \code{st_equals_exact}, and do not; \code{st_is_within_distance} uses a spatial index for geographic coordinates when \code{sf_use_s2()} is true.
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