1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/generateDesign.R
\name{generateDesign}
\alias{generateDesign}
\title{Generates a statistical design for a parameter set.}
\usage{
generateDesign(
n = 10L,
par.set,
fun,
fun.args = list(),
trafo = FALSE,
augment = 20L
)
}
\arguments{
\item{n}{(\code{integer(1)})\cr
Number of samples in design.
Default is 10.}
\item{par.set}{\link{ParamSet}\cr
Parameter set.}
\item{fun}{(\code{function})\cr
Function from package lhs.
Possible are: \code{\link[lhs:maximinLHS]{lhs::maximinLHS()}}, \code{\link[lhs:randomLHS]{lhs::randomLHS()}},
\code{\link[lhs:geneticLHS]{lhs::geneticLHS()}}, \code{\link[lhs:improvedLHS]{lhs::improvedLHS()}}, \code{\link[lhs:optAugmentLHS]{lhs::optAugmentLHS()}},
\code{\link[lhs:optimumLHS]{lhs::optimumLHS()}}
Default is \code{\link[lhs:randomLHS]{lhs::randomLHS()}}.}
\item{fun.args}{(\code{list})\cr
List of further arguments passed to \code{fun}.}
\item{trafo}{(\code{logical(1)})\cr
Transform all parameters by using theirs respective transformation
functions. Default is \code{FALSE}.}
\item{augment}{(\code{integer(1)})\cr
Duplicated values and forbidden regions in the parameter space can lead to
the design becoming smaller than \code{n}. With this option it is possible to
augment the design again to size \code{n}. It is not guaranteed that this always
works (to full size) and \code{augment} specifies the number of tries to
augment. If the the design is of size less than \code{n} after all tries, a
warning is issued and the smaller design is returned. Default is 20.}
}
\value{
\link{data.frame}. Columns are named by the ids of the parameters. If the
\code{par.set} argument contains a vector parameter, its corresponding column
names in the design are the parameter id concatenated with 1 to dimension
of the vector. The result will have an \code{logical(1)} attribute
\dQuote{trafo}, which is set to the value of argument \code{trafo}.
}
\description{
The following types of columns are created:
\tabular{ll}{
numeric(vector) \tab \code{numeric} \cr
integer(vector) \tab \code{integer} \cr
discrete(vector) \tab \code{factor} (names of values = levels) \cr
logical(vector) \tab \code{logical}
}
If you want to convert these, look at \code{\link[BBmisc:convertDataFrameCols]{BBmisc::convertDataFrameCols()}}.
Dependent parameters whose constraints are unsatisfied generate \code{NA} entries in their
respective columns.
For discrete vectors the levels and their order will be preserved, even if not all levels are present.
Currently only lhs designs are supported.
The algorithm currently iterates the following steps:
\enumerate{
\item{We create a space filling design for all parameters, disregarding \code{requires},
a \code{trafo} or the forbidden region.}
\item{Forbidden points are removed.}
\item{Parameters are trafoed (potentially, depending on the setting of argument \code{trafo});
dependent parameters whose constraints are unsatisfied are set to \code{NA} entries.}
\item{Duplicated design points are removed. Duplicated points are not generated in a
reasonable space-filling design, but the way discrete parameters and also parameter dependencies
are handled make this possible.}
\item{If we removed some points, we now try to augment the design in a space-filling way
and iterate.}
}
Note that augmenting currently is somewhat experimental as we simply generate
missing points via new calls to \code{\link[lhs:randomLHS]{lhs::randomLHS()}}, but do not add points so
they are maximally far away from the already present ones. The reason is that
the latter is quite hard to achieve with complicated dependencies and
forbidden regions, if one wants to ensure that points actually get added...
But we are working on it.
Note that if you have trafos attached to your params, the complete creation
of the design (except for the detection of invalid parameters w.r.t to their
\code{requires} setting) takes place on the UNTRANSFORMED scale. So this function
creates, e.g., a maximin LHS design on the UNTRANSFORMED scale, but not
necessarily the transformed scale.
\code{generateDesign} will NOT work if there are dependencies over multiple levels
of parameters and the dependency is only given with respect to the
\dQuote{previous} parameter. A current workaround is to state all
dependencies on all parameters involved. (We are working on it.)
}
\examples{
ps = makeParamSet(
makeNumericParam("x1", lower = -2, upper = 1),
makeIntegerParam("x2", lower = 10, upper = 20)
)
# random latin hypercube design with 5 samples:
generateDesign(5, ps)
# with trafo
ps = makeParamSet(
makeNumericParam("x", lower = -2, upper = 1),
makeNumericVectorParam("y", len = 2, lower = 0, upper = 1, trafo = function(x) x / sum(x))
)
generateDesign(10, ps, trafo = TRUE)
}
|
