## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(fig.width=10, fig.height=10,fig.asp = 0.618, out.width = "95%", fig.align = "center", fig.dpi = 150, collapse = FALSE, comment = "#") 
#knitr::opts_chunk$set(dev = 'pdf')

## ----results='hide', message=FALSE, warning=FALSE-----------------------------
require(rasterdiv)
require(terra)
require(rasterVis)
require(RColorBrewer)
require(viridis)
require(latticeExtra)
require(ggplot2)

## ----results='hide', message=FALSE, warning=FALSE, eval=FALSE-----------------
#  copNDVI <- load_copNDVI()
#  copNDVIlr <- terra::aggregate(copNDVI, fact=10)
#  values(copNDVIlr) <- as.integer(values(copNDVIlr))
#  world <- load_world()

## ----echo = T, results = 'hide', warning=FALSE, message=FALSE, eval=FALSE-----
#  RaoC <- paRao(x=copNDVIlr, area=world, field='CONTINENT', alpha=c(1,2))

## ----fig01, warning=FALSE, message=FALSE, eval=FALSE, eval=FALSE--------------
#  #Plot classic area-based Rao's index
#  plot(RaoC, col=hcl(RaoC$alpha.1*10), main="Classic Rao's index per continent alpha 1")
#  text(RaoC, label=paste("Rao'Q =", round(RaoC$alpha.1,1)), col="black", family="Arial", halo=TRUE)

## ----echo = T, results = 'hide', warning=FALSE, message=FALSE, eval=FALSE-----
#  # Adding a second "noise" SpatRaster layer
#  # copNDVIlr <- terra::aggregate(copNDVI, fact=20)
#  values(copNDVIlr) <- as.integer(values(copNDVIlr))
#  noise = rast(copNDVIlr)
#  noise[] = as.integer(runif(n=ncell(noise),min=1, max=10))
#  RaoMC <- paRao(x=c(copNDVIlr,noise), area=world, field='CONTINENT', alpha=2, method="multidimension", simplify=0)

## ----fig02, warning=FALSE, message=FALSE, eval=FALSE--------------------------
#  #Plot area-based Rao's index
#  plot(RaoMC, col=hcl(RaoMC$alpha.2*10000), main="Multidimension Rao's index per continent alpha 10")
#  text(RaoMC, label=paste("Rao'Q =", round(RaoMC$alpha.2,3)), col="black", family="Arial", halo=TRUE)

## ----include-figure02, echo=FALSE, fig.align='center', fig.cap='', out.width='80%', eval=FALSE----
#  knitr::include_graphics("Rao_areabased_multidimensional.png")

## ----echo = T, results = 'hide', warning=FALSE, message=FALSE, eval=FALSE-----
#  #Subset
#  africa <- subset(world, world$CONTINENT=="Africa")
#  
#  #Make the raster grid
#  africa.r <- rast(ext(africa), nrow=20, ncol=20, crs = "+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +towgs84=0,0,0")
#  africa.r[] <- 1:ncell(africa.r)
#  
#  #Vectorise the SpatRaster
#  africa.v = as.polygons(africa.r)

## ----echo = T, results = 'hide', warning=FALSE, message=FALSE, eval=FALSE-----
#  #Derive Rao's (alpha=2) for each grid cell
#  RaoGRID <- paRao(x=copNDVIlr, area=africa.v, field='lyr.1', alpha=2, simplify=0, na.tolerance=0.2)

## ----results='hide', message=FALSE, warning=FALSE, include = FALSE, eval=FALSE----
#  RaoGRID <- readRDS("RaoGRID.RDS")

## ----echo = T, results = 'hide', warning=FALSE, message=FALSE, eval=FALSE-----
#  #Transform the spatial polygon data frame in a raster layer that can be used in levelplot
#  rr <- rast(RaoGRID, ncol=20, nrow=20)
#  values(rr) <- RaoGRID$alpha.2

## ----fig03, echo = T, results = 'hide', warning=FALSE, message=FALSE, eval=FALSE----
#  #Plot Rao's per grid cell
#  ggplot() +
#    geom_raster(data = as.data.frame(rr, xy=TRUE), aes(x = x, y = y, fill = lyr.1)) +
#    scale_fill_viridis(option = "D", direction = 1) +
#     geom_polygon(data = fortify(as(africa.v, "Spatial")), aes(x = long, y = lat, group = group), fill = NA, color = "grey", linewidth=0.3) +
#    geom_polygon(data = fortify(as(world, "Spatial")), aes(x = long, y = lat, group = group), fill = NA, color = "black", , linewidth=0.5) +
#    theme(legend.position = "none", aspect.ratio = 0.5)

## ----include-figure03, echo=FALSE, fig.align='center', fig.cap='', out.width='100%', eval=FALSE----
#  knitr::include_graphics("vignette02fig03.png")