View source: R/autoplot.SpatRaster.R
autoplot.SpatRaster | R Documentation |
autoplot.SpatRaster
creates a map of all rasters in a SpatRaster object and
displays these in a grid.
## S3 method for class 'SpatRaster'
autoplot(
object,
...,
shp_df = NULL,
legend_title = "",
plot_titles = TRUE,
fill_scale_transform = "identity",
fill_colour_palette = "RdYlBu",
printed = TRUE
)
object |
SpatRaster object to be visualised. |
... |
Other arguments passed to specific methods |
shp_df |
Shapefile(s) (data.frame) to plot with downloaded raster. |
legend_title |
String used as title for all colour scale legends. |
plot_titles |
Plot name of raster object as header for each individual raster plot? |
fill_scale_transform |
String givning a transformation for the fill aesthetic.
See the trans argument in |
fill_colour_palette |
String referring to a colorbrewer palette to be used for raster colour scale. |
printed |
Logical vector indicating whether to print maps of supplied rasters. |
autoplot.SpatRaster
returns a list of plots (gg objects) for each
supplied raster.
getRaster
:
to download rasters directly from MAP.
## Not run:
# Download PfPR2-10 Raster (Bhatt et al 2015) and raw survey points
# for Madagascar in 2013 and visualise these together on a map.
# Download madagascar shapefile to use for raster download.
MDG_shp <- getShp(ISO = "MDG", admin_level = "admin0")
# Download PfPR2-10 Raster for 2013 & plot this
MDG_PfPR2_10 <- getRaster(surface = "Plasmodium falciparum PR2-10",
shp = MDG_shp, year = 2013)
p <- autoplot(MDG_PfPR2_10, shp_df = MDG_shp)
# Download raw PfPR survey points & plot these over the top of the raster
pr <- getPR(country = c("Madagascar"), species = "Pf")
# p[[1]] + geom_point(data = pr[pr$year_start==2013,],
# aes(longitude, latitude, fill = positive / examined,
# size = examined), shape = 21) +
# scale_size_continuous(name = "Survey Size") +
# scale_fill_distiller(name = "PfPR", palette = "RdYlBu") +
# ggtitle("Raw PfPR Survey points\n +
# Modelled PfPR 2-10 in Madagascar in 2013")
# Download global raster of G6PD deficiency (Howes et al 2012) and visualise this on a map.
G6PDd_global <- getRaster(surface = "G6PD Deficiency Allele Frequency")
autoplot(G6PDd_global)
## End(Not run)
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