DEXiR (version 1.0.2)

DexiDiscretizeFunction-class: DexiDiscretizeFunction

Description

DexiDiscretizeFunction is a RC class, derived from DexiFunction. Functions of this type discretize numerical values of continuous attributes to qualitative values of discrete attributes. More precisely, a DexiDiscretizeFunction can be defined only for a discrete attribute that has exactly one continuous input. Then, the function discretizes numeric values of the input attribute and maps them to discrete values of the parent attribute.

Fields

attribute

DexiAttribute. The attribute this function is associated with. Requirements: attribute must be discrete (i.e., associated with a DexiDiscreteScale) and must have exactly one continuous input attribute (i.e., associated with a DexiContinuousScale).

values

A list of output values corresponding to each interval defined by bounds. List elements are in general value sets, i.e., integer vectors of value indices w.r.t. attribute$scale.

bounds

A vector of numeric values that partitions the input scale in intervals.

assoc

A vector of strings "up" or "down". For each i in 1:n-1, assoc[[i]] indicates how to map the value of bounds[[i]]: to value[[i]] ("down") or value[[i + 1]] ("up").

Methods

bound_assoc(idx, default = "down")

Given idx, a bounds index, return the corresponing association ("down" or "up").

evaluate(x)

A silent wrapper around value(x); it returns NULL when value(x) fails with an error.

nargs()

Return the number of function arguments.

nvals()

Return the length of values.

to_string()

Return an informative string about this function's values and bounds.

value(x)

Return the function value for arguments x, where arguments are a numeric vector of length equal to att$inputs. Additionally, arguments of a DexiTabularFunctions$value() must be integer numbers, and the argument of DexiDiscretizeFunctions$value() must be a single number.

verify()

Check the correctnes of this function object and its fields. Result: error() or TRUE.

Details

Objects of class DexiDiscretizeFunction define discretization rules in terms of three lists: values, bounds and assoc. Using n <- nvals() to denote the length of values, the required lengths of bounds and assoc are n - 1.

The list bounds refers to values of the input attribute and partitions its scale in n intervals [-Inf, bound[[1]]], [bound[[1]], bound[[2]]], ..., [bound[[n - 1]]], +Inf]. The list values then defines the output values for each interval. The list assoc contains strings "up" or "down" that indicate to which interval, lower or higher, belong the corresponding bounds.

Examples

# Create a DexiDiscretizeFunction (without association to any attributes or scales)
fnc <- DexiDiscretizeFunction(bounds = c(-1, 2), values = list(1, 3, 5), assoc = c("up", "down"))

# Print fields and basic properties of fnc

fnc$verify()
fnc$nargs()
fnc$nvals()
fnc$to_string()

fnc$bound_assoc(1)
fnc$bound_assoc(2)

# Try some discretizations
sapply(c(-1.1, -1, 0, 1, 2, 3), fnc$evaluate)