knitr::opts_chunk$set( collapse = TRUE, comment = "#>", message = FALSE, warning = FALSE, out.width = "100%" )
Starting with rasterpic
is very easy! You just need a image (png
, jpeg/jpg
or tif/tiff
) and a spatial object (from the sf
or the terra
) package to
start using it.
We use here as an example the shape of Austria:
library(sf) library(terra) library(rasterpic) # Plot library(tidyterra) library(ggplot2) # Shape and image x <- read_sf(system.file("gpkg/austria.gpkg", package = "rasterpic")) img <- system.file("img/vertical.png", package = "rasterpic") # Create! default <- rasterpic_img(x, img) autoplot(default) + geom_sf(data = x)
The function provides several options for expanding, alignment and cropping.
With this option the image is zoomed out of the spatial object:
expand <- rasterpic_img(x, img, expand = 1) autoplot(expand) + geom_sf(data = x)
Decide where to align the image:
bottom <- rasterpic_img(x, img, valign = 0) autoplot(bottom) + geom_sf(data = x)
Create impressive maps!:
mask <- rasterpic_img(x, img, crop = TRUE, mask = TRUE) autoplot(mask) maskinverse <- rasterpic_img(x, img, crop = TRUE, mask = TRUE, inverse = TRUE) autoplot(maskinverse)
Spatial object of the sf
package: sf
, sfc
, sfg
or bbox
.
Spatial objects of the terra
package: SpatRaster
, SpatVector
,
SpatExtent
.
A vector of coordinates with the form c(xmin, ymin, xmax, yman)
rasterpic
can parse the following image formats:
png
files.jpg/jpeg
files.tif/tiff
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