# normalise: Normalise points In eaf: Plots of the Empirical Attainment Function

## Description

Normalise points per coordinate to a range, e.g., `c(1,2)`, where the minimum value will correspond to 1 and the maximum to 2. If bounds are given, they are used for the normalisation.

## Usage

 `1` ```normalise(data, to.range = c(1, 2), lower = NA, upper = NA, maximise = FALSE) ```

## Arguments

 `data` (`matrix` | `data.frame`) Matrix or data frame of numerical values, where each row gives the coordinates of a point. `to.range` Normalise values to this range. If the objective is maximised, it is normalised to `c(to.range, to.range)` instead. `lower, upper` Bounds on the values. If NA, the maximum and minimum values of each coordinate are used. `maximise` (`logical()` | `logical(1)`) Whether the objectives must be maximised instead of minimised. Either a single logical value that applies to all objectives or a vector of logical values, with one value per objective.

## Value

A numerical matrix

## Author(s)

Manuel López-Ibáñez

## Examples

 ```1 2 3 4 5 6 7``` ```data(SPEA2minstoptimeRichmond) # The second objective must be maximized head(SPEA2minstoptimeRichmond[, 1:2]) head(normalise(SPEA2minstoptimeRichmond[, 1:2], maximise = c(FALSE, TRUE))) head(normalise(SPEA2minstoptimeRichmond[, 1:2], to.range = c(0,1), maximise = c(FALSE, TRUE))) ```

eaf documentation built on May 7, 2021, 5:06 p.m.