Tests if geometries in x are within a specified distance of y. Returns
TRUE if geometries are within the distance.
Usage
ddbs_is_within_distance(
x,
y,
distance = NULL,
conn = NULL,
id_x = NULL,
id_y = NULL,
sparse = TRUE,
quiet = FALSE
)Arguments
- x
An
sfspatial object. Alternatively, it can be a string with the name of a table with geometry column within the DuckDB databaseconn. Data is returned from this object.- y
An
sfspatial object. Alternatively, it can be a string with the name of a table with geometry column within the DuckDB databaseconn.- distance
a numeric value specifying the distance for ST_DWithin. Units correspond to the coordinate system of the geometry (e.g. degrees or meters)
- conn
A connection object to a DuckDB database. If
NULL, the function runs on a temporary DuckDB database.- id_x
Character; optional name of the column in
xwhose values will be used to name the list elements. IfNULL, integer row numbers ofxare used.- id_y
Character; optional name of the column in
ywhose values will replace the integer indices returned in each element of the list.- sparse
A logical value. If
TRUE, it returns a sparse index list. IfFALSE, it returns a dense logical matrix.- quiet
A logical value. If
TRUE, suppresses any informational messages. Defaults toFALSE.
Value
A list where each element contains indices (or IDs) of geometries in y that
touch the corresponding geometry in x. See ddbs_predicate() for details.
Details
This is a convenience wrapper around ddbs_predicate() with
predicate = "dwithin".
See also
ddbs_predicate() for other spatial predicates.
Examples
## load packages
library(dplyr)
library(duckspatial)
library(sf)
## read countries data, and rivers
countries_sf <- read_sf(system.file("spatial/countries.geojson", package = "duckspatial"))
countries_filter_sf <- countries_sf |> filter(CNTR_ID %in% c("PT", "ES", "FR", "IT"))
## check countries within 1 degree of distance
ddbs_is_within_distance(countries_filter_sf, countries_sf, 1)
#> ✔ Query successful
#> [[1]]
#> [1] 5 64 73 85 160 177
#>
#> [[2]]
#> [1] 5 19 60 64 71 79 85 90 91 96 173 178 206
#>
#> [[3]]
#> [1] 3 10 60 85 86 90 96 120 178 204 231 235
#>
#> [[4]]
#> [1] 64 160
#>
