rasclass (version 0.2.2)

buildFormula: Build a formula for Raster Classification

Description

This function builds a formula from the dataframe from the data slot in the specified rasclass object.

Usage

buildFormula(object, varlist = NULL)

Arguments

object

A rasclass-class object with non-empty data and samplename slots.

varlist

An optional character vector containing the names of the variables that shall be used in the classification algorithms.

Value

A rasclass-class object with the newly built formula in the formula slot.

Details

A formula is built automatically using all the columns in the dataframe from the data slot of the specified object. The formula is stored in the call slot of the rasclass-class object. The dependent variable in the formula will be the name specified in the samplename slot of the given input object.

If not all columns from the data slot should be used for classifiaction, the list of variables to include can be specified using the optional argument varlist. The samplename is specified previously when adding data to the rasclass-class object with the corresponding functions and should not be included in the varlist argument.

See Also

rasclass-package, rasclass-class, rasclassRaster-class,

readRaster, writeRaster,

readRasterFolder, setRasclassData,

checkRasclass,

rasclassMlc, classifyRasclass

Examples

## 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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