## ----raster-5, fig=TRUE , echo=TRUE-------------------------------------------
library(raster)
r <- raster()
r[] <- 1:ncell(r)
ra <- aggregate(r, 10)
r1 <- crop(r, extent(-180,0,0,30))
r2 <- crop(r, extent(-10,180,-20,10))
m <- merge(r1, r2, filename='test.grd', overwrite=TRUE)
plot(m)


## ----raster-6-----------------------------------------------------------------
r <- raster(ncol=3, nrow=2)
values(r) <- 1:ncell(r)
getValues(r)
s <- calc(r, fun=function(x){ x[x < 4] <- NA; return(x)} )
as.matrix(s)
t <- overlay(r, s, fun=function(x, y){ x / (2 * sqrt(y)) + 5 } )
as.matrix(t)
u <- mask(r, t)
as.matrix(u)
v <- u==s
as.matrix(v)
w <- cover(t, r)
as.matrix(w)
x <- reclassify(w, c(0,2,1,  2,5,2, 4,10,3))
as.matrix(x)
y <- subs(x, data.frame(id=c(2,3), v=c(40,50)))
as.matrix(y)


## ----raster-7-----------------------------------------------------------------
r <- raster(nrow=45, ncol=90)
r[] <- round(runif(ncell(r))*3)
a <- area(r)
zonal(a, r, 'sum')


## ----raster-10----------------------------------------------------------------
r <- raster(ncol=36, nrow=18)
r[] <- runif(ncell(r))
cellStats(r, mean)
s = r
s[] <- round(runif(ncell(r)) * 5)
zonal(r, s, 'mean')
freq(s)
freq(s, value=3)
crosstab(r*3, s)