knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The goal of grd is to do provide data structures and a minimal set of generics to work with grids of points or rectangles (i.e., raster data). The grd package is built on top of wk and uses the rct()
and xy()
structures heavily.
You can install the development version from GitHub with:
# install.packages("remotes") remotes::install_github("paleolimbot/grd")
Use grd_rct()
or grd_xy()
to construct a grid from a matrix and a wk::rct()
.
library(grd) bbox <- rct( 5917000, 1757000 + 870, 5917000 + 610, 1757000, crs = "EPSG:2193" ) grid <- grd_rct(volcano, bbox) plot(grid)
You can use grd_crop()
, grd_extend()
, or grd_subset()
to select parts of a grid whilst keeping each cell's relationship to space:
plot(grd_subset(grid, 1:30, 1:30)) plot(grd_crop(grid, rct(5917000, 1757600, 5917300, 1757800)))
Use grd_cell()
or grd_cell_range()
to find cell indices based on a spatial query; use grd_cell_rct()
or grd_cell_xy()
to get information about specific cells:
(cell_ids <- grd_cell(grid, xy(5917100, 1757700))) grd_cell_xy(grid, cell_ids) grd_cell_rct(grid, cell_ids)
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