plotData: Interpolated plot

In SPOT: Sequential Parameter Optimization Toolbox

Interpolated plot

Description

A (filled) contour or perspective plot of a data set with two independent and one dependent variable. The plot is generated by some interpolation or regression model. By default, the loess function is used.

Usage

plotData(
  x,
  y,
  which = 1:2,
  constant = x[which.min(y), ],
  model = buildLOESS,
  modelControl = list(),
  xlab = c("x1", "x2"),
  ylab = "y",
  type = "filled.contour",
  ...
)

Arguments

x	independent variables, or input variables. this should be a matrix of at least two columns and several rows. If more than two columns are present, all will be used for fitting the model. The parameter which will determine which of these will be plotted, and the parameter constant will determine the values of all parameters that are not varied.
y	dependent, or observed output variable to be interpolated/regressed and plotted.
which	a vector with two elements, each an integer giving the two independent variables of the plot (the integers are indices of the respective data set, i.e., columns of x). All other parameters will be fixed to the best known solution, i.e., the one with minimal y-value.
constant	a numeric vector that states for each variable a constant value that it will take on if it is not varied in the plot. This affects the parameters not selected by the which parameter. By default, this will be fixed to the best known solution, i.e., the one with minimal y-value, according to which.min(object$y). The length of this numeric vector should be the same as the number of columns in object$x
model	the model building function to be used, by default buildLOESS.
modelControl	control list of the chosen model building function.
xlab	a vector of characters, giving the labels for each of the two independent variables
ylab	character, the value of the dependent variable predicted by the corresponding model
type	string describing the type of the plot: "filled.contour" (default), "contour", "persp" (perspective), or "persp3d" plot. Note that "persp3d" is based on the plotly package and will work in RStudio, but not in the standard RGui.
...	additional parameters passed to the contour or filled.contour function

See Also

plotFunction, plotModel

Examples

## generate random test data
testfun <- function (x) sum(x^2)
set.seed(1)
k <- 30
x <- cbind(runif(k)*15-5,runif(k)*15)
y <- as.matrix(apply(x,1,testfun))
plotData(x,y)
plotData(x,y,type="contour")
plotData(x,y,type="persp")

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