## Not run:
# # Load data from external folder
# object <- readRasterFolder(path = "mypath", samplename = "mysample",
# filenames = c('myvar1.asc', 'myvar2.asc'))
# ## End(Not run)
# For this example, create artificial data
mysample <- c(rep(rep(c(1,2), each = 25), 25), rep(rep(c(3,4), each = 25), 25))
mysample <- mysample + sample(c(0, NA), 2500, replace = TRUE, prob = c(1, 10))
myvar1 <- rep(1:50, each = 50) + rnorm(2500, 0, 5)
myvar2 <- rep(rep(1:50), 50) + rnorm(2500, 0, 5)
myvar3 <- sample(1:2500)
newdata <- data.frame(mysample, myvar1, myvar2, myvar3)
# Prepare a rasclass object using the dataframe and specifying raster properties
object <- new('rasclass')
object <- setRasclassData(newdata, ncols = 50, nrows = 50,
xllcorner = 0, yllcorner = 0, cellsize = 1, NAvalue = -9999,
samplename = 'mysample')
# Classify and show results using all columns
object <- classifyRasclass(object)
summary(object)
# Change formula to exclude one variable
object <- buildFormula(object, varlist = c('myvar1', 'myvar3'))
# Classify and show results
object <- classifyRasclass(object)
summary(object)
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