malariaAtlas (version 0.0.4)

autoplot.vector.points: Create a basic plot showing locations of downloaded Vector points

Description

autoplot.vector.points creates a map of Vector points downloaded from MAP.

Usage

# S3 method for vector.points
autoplot(object, ..., shp_df = NULL,
  admin_level = "admin0", map_title = "Vector Survey Locations",
  fill_legend_title = "Raw Vetor Occurrences",
  fill_scale_transform = "identity", facet = NULL, printed = TRUE)

Arguments

object

a vector.points object downloaded using /code/linkgetVecOcc

...

Other arguments passed to specific methods

shp_df

Shapefile(s) (data.frame) to plot with downloaded points. (If not specified automatically uses getShp() for all countries included in vector.points object).

admin_level

the administrative level used for plotting administrative boundaries; either /code"admin0"; /code"admin1" OR /code"both"

map_title

custom title used for the plot

fill_legend_title

Add a title to the legend.

fill_scale_transform

String givning a transformation for the fill aesthetic. See the trans argument in continuous_scale for possible values.

facet

if TRUE, splits map into a separate facet for each malaria species; by default FALSE.

printed

Should the plot be printed to the graphics device.

Value

autoplot.vector.points returns a plots (gg object) for the supplied vector.points dataframe.

Examples

# NOT RUN {
Vector_surveys_NGA_NG <- getVecOcc(country = c("Nigeria", "Niger"))
autoplot(Vector_surveys_NGA_NG)

# Download the predicted distribution of An. dirus species complex Raster and  
#  vector points for Myanmar and visualise these together on a map.

# Download Myanmar shapefile to use for raster download.
MMR_shp <- getShp(ISO = "MMR", admin_level = "admin0")
MMR_shp_df <- as.MAPshp(MMR_shp)

# Download An. dirus predicted distribution Raster & plot this
MMR_An_dirus <- getRaster(surface = "Anopheles dirus species complex", shp = MMR_shp)
MMR_An_dirus_df <- as.MAPraster(MMR_An_dirus)
p <- autoplot_MAPraster(MMR_An_dirus, shp_df = MMR_shp_df, printed = FALSE)

# Download raw occurrence points & plot these over the top of the raster   
species <- getVecOcc(country = "Myanmar", species = "Anopheles dirus")
p[[1]] +
geom_point(data = species,
 aes(longitude,
  latitude,
  colour = species))+
  scale_colour_manual(values = "black", name = "Vector suvery locations")+
scale_fill_distiller(name = "Predicted distribution of An. dirus complex",
 palette = "PuBuGn",
  direction = 1)+
  ggtitle("Vector Survey points\n + The predicted distribution of An. dirus complex")
# }
# NOT RUN {
# }