if (grassStarted()) {
# Setup
library(sf)
library(terra)
# Example data
madChelsa <- fastData("madChelsa")
# Convert a SpatRaster to a GRaster
chelsa <- fast(madChelsa)
chelsa # 4 layers
# Central tendency
mean(chelsa)
mmode(chelsa)
median(chelsa)
# Statistics
nunique(chelsa)
sum(chelsa)
count(chelsa)
min(chelsa)
max(chelsa)
range(chelsa)
skewness(chelsa)
kurtosis(chelsa)
stdev(chelsa)
stdev(chelsa, pop = FALSE)
var(chelsa)
varpop(chelsa)
# Which layers have maximum/minimum?
which.min(chelsa)
which.max(chelsa)
# Regression
# Note the intercept is different for fasterRaster::regress().
regress(chelsa)
regress(madChelsa, 1:nlyr(madChelsa))
# Note: To get quantiles for each layer, use
# global(x, "quantile", probs = 0.2).
quantile(chelsa, 0.1)
# NAs
madForest2000 <- fastData("madForest2000")
forest2000 <- fast(madForest2000)
forest2000 <- project(forest2000, chelsa, method = "near")
chelsaForest <- c(chelsa, forest2000)
nas <- anyNA(chelsaForest)
plot(nas)
allNas <- allNA(chelsaForest)
plot(allNas)
}
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