Tessellate a dbSpatial object — tessellate • GiottoDB

Creates a tessellation on the extent of a dbSpatial object with specified parameters. Other input types are forwarded to GiottoClass::tessellate().

Usage

tessellate(x, extent, ...)

# S4 method for class 'dbSpatial,missing'
tessellate(
  x,
  extent,
  geomName = "geom",
  name = "tessellation",
  shape = c("hexagon", "square"),
  shape_size = NULL,
  gap = 0,
  radius = NULL,
  overwrite = FALSE,
  ...
)

Arguments

x: dbSpatial object, or a positional extent-like object supported by GiottoClass::tessellate().
extent: Optional named extent-like object supported by GiottoClass::tessellate().
...: Additional arguments passed to methods.
geomName: character string. The geometry column name in the dbSpatial object. Default: "geom".
name: character string name of table to add to dbSpatial object. Default: "tessellation".
shape: character string. A character string indicating the shape of the tessellation. Options are "hexagon" or "square".
shape_size: numeric. the size of the shape in the tessellation. If NULL, a default size is calculated. See GiottoClass::tessellate for details.
gap: numeric. Value indicating the gap between tessellation shapes. Defaults to 0.
radius: numeric. Value specifying the radius for hexagonal tessellation. This parameter is ignored for square tessellations.
overwrite: logical. Boolean value indicating whether to overwrite an existing tessellation with the same name. Default: FALSE.

Value

dbSpatial object for dbSpatial input, otherwise the result of GiottoClass::tessellate().

Details

tessellate(x = dbSpatial, ...) creates a tessellation over the bounding box of the dbSpatial geometry column and stores the result as a dbSpatial table. tessellate(extent = extent, ...) and tessellate(extent, ...) preserve the GiottoClass::tessellate() extent-based behavior. Supply either x or extent, but not both.

Functions

tessellate(x = dbSpatial, extent = missing): Method for dbSpatial objects

Examples

coordinates <- data.frame(x = c(100, 200, 300), y = c(500, 600, 700))
attributes <- data.frame(id = 1:3, name = c("A", "B", "C"))

# Combine the coordinates and attributes
dummy_data <- cbind(coordinates, attributes)

# Create a duckdb connection
con = DBI::dbConnect(duckdb::duckdb(), ":memory:")
#> duckdb is keeping downloaded extensions in a temporary directory:
#> ℹ /tmp/RtmpIms262/duckdb/extensions
#> This is removed when the R session ends, so extensions are re-downloaded each session.
#> ℹ To keep them, point `options(duckdb.extension_directory =)` or the `DUCKDB_EXTENSION_DIRECTORY` environment variable at a permanent path.

# Create a duckdb table with spatial points
db_points = dbSpatial::dbSpatial(conn = con,
                                 value = dummy_data,
                                 x_colName = "x",
                                 y_colName = "y",
                                 name = "foo",
                                 overwrite = TRUE)

tessellate(db_points, name = "my_tessellation", shape = "hexagon", shape_size = 60)
#> 7 polygons generated
#> # Class:    dbSpatial 
#> # A query:  ?? x 2
#> # Database: DuckDB 1.5.4 [unknown@Linux 6.17.0-1020-azure:R 4.6.1/:memory:]
#>   poly_ID geom                             
#>   <chr>   <chr>                            
#> 1 ID_1    POLYGON ((160 564.641, 190 547...
#> 2 ID_2    POLYGON ((220 564.641, 250 547...
#> 3 ID_3    POLYGON ((130 616.6025, 160 59...
#> 4 ID_4    POLYGON ((190 616.6025, 220 59...
#> 5 ID_5    POLYGON ((250 616.6025, 280 59...
#> 6 ID_6    POLYGON ((160 668.5641, 190 65...
#> 7 ID_7    POLYGON ((220 668.5641, 250 65...