designLHD: Latin Hypercube Design Generator

In SPOT: Sequential Parameter Optimization Toolbox

Latin Hypercube Design Generator

Description

Creates a latin Hypercube Design (LHD) with user-specified dimension and number of design points. LHDs are created repeatedly created at random. For each each LHD, the minimal pair-wise distance between design points is computed. The design with the maximum of that minimal value is chosen.

Usage

designLHD(x = NULL, lower, upper, control = list())

Arguments

x	optional matrix x, rows for points, columns for dimensions. This can contain one or more points which are part of the design, but specified by the user. These points are added to the design, and are taken into account when calculating the pair-wise distances. They do not count for the design size. E.g., if x has two rows, control$replicates is one and control$size is ten, the returned design will have 12 points (12 rows). The first two rows will be identical to x. Only the remaining ten rows are guaranteed to be a valid LHD.
lower	vector with lower boundary of the design variables (in case of categorical parameters, please map the respective factor to a set of contiguous integers, e.g., with lower = 1 and upper = number of levels)
upper	vector with upper boundary of the design variables (in case of categorical parameters, please map the respective factor to a set of contiguous integers, e.g., with lower = 1 and upper = number of levels)
control	list of controls: size number of design points retries number of retries during design creation types this specifies the data type for each design parameter, as a vector of either "numeric","integer","factor". (here, this only affects rounding) inequalityConstraint inequality constraint function, smaller zero for infeasible points. Used to replace infeasible points with random points. replicates integer for replications of each design point. E.g., if replications is two, every design point will occur twice in the resulting matrix.

Value

matrix design
- design has length(lower) columns and (size + nrow(x))*control$replicates rows. All values should be within lower <= design <= upper

Author(s)

Original code by Christian Lasarczyk, adaptations by Martin Zaefferer

Examples

set.seed(1) #set RNG seed to make examples reproducible 
design <- designLHD(,1,2) #simple, 1-D case
design
design <- designLHD(,1,2,control=list(replicates=3)) #with replications
design
design <- designLHD(,c(-1,-2,1,0),c(1,4,9,1),
	control=list(size=5, retries=100, types=c("numeric","integer","factor","factor")))
design
x <- designLHD(,c(1,-10),c(2,10),control=list(size=5,retries=100))
x2 <- designLHD(x,c(1,-10),c(2,10),control=list(size=5,retries=100))
plot(x2)
points(x, pch=19)

SPOT documentation built on June 26, 2022, 1:06 a.m.