a list that can be used as model with the
modelPredict function of the DiceEval
package.
center
optional coordinates (as a list or data
frame) of the center of the section view if the model's
dimension is > 1.
axis
optional matrix of 1-axis combinations to
plot, one by row. The value NULL leads to all
possible combinations i.e. 1:D.
npoints
an optional number of points to discretize
plot of response surface and uncertainties.
col_points
color of points.
col_surf
color for the section.
bg_blend
an optional factor of alpha (color
channel) blending used to plot design points outside from
this section.
mfrow
an optional list to force par(mfrow =
...) call. Default (NULL value) is automatically set for
compact view.
xlim
an optional list to force x range for all
plots. The default value NULL is automatically set
to include all design points.
ylim
an optional list to force y range for all
plots. The default value NULL is automatically set
to include all design points.
Xname
an optional list of string to overload names
for X.
yname
an optional string to overload name for y.
Xscale
an optional factor to scale X.
yscale
an optional factor to scale y.
title
an optional overload of main title.
add
to print graphics on an existing window.
...
optional arguments passed to the first call
of plot().
Details
A multiple rows/columns plot is produced. Experimental
points are plotted with fading colors. Points that fall
in the specified section (if any) have the color
specified col_points while points far away from
the center have shaded versions of the same color. The
amount of fading is determined using the Euclidean
distance between the plotted point and center.
Author(s)
Yann Richet, IRSN
See Also
See sectionview3d.list for a 3d version,
and the modelPredict function in
the DiceEval package.
Examples
## A 2D example: Branin-Hoo function. See the DiceKriging package manual
## a 16-points factorial design, and the corresponding response
d <- 2; n <- 16
design.fact <- expand.grid(seq(0, 1, length = 4), seq(0, 1, length = 4))
design.fact <- data.frame(design.fact); names(design.fact) <- c("x1", "x2")
y <- branin(design.fact)
## linear model
m1 <- modelFit(design.fact, y$x1, type = "Linear", formula = "Y~.")
sectionview.list(m1, center = c(.333,.333))
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(DiceView)
Loading required package: DiceKriging
Loading required package: DiceEval
Loading required package: rgl
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DiceView/sectionview.list.Rd_%03d_medium.png", width=480, height=480)
> ### Name: sectionview.list
> ### Title: Plot a section view of a model, including design points
> ### Aliases: sectionview.list
> ### Keywords: models
>
> ### ** Examples
>
> ## A 2D example: Branin-Hoo function. See the DiceKriging package manual
> ## a 16-points factorial design, and the corresponding response
> d <- 2; n <- 16
> design.fact <- expand.grid(seq(0, 1, length = 4), seq(0, 1, length = 4))
> design.fact <- data.frame(design.fact); names(design.fact) <- c("x1", "x2")
> y <- branin(design.fact)
>
> ## linear model
> m1 <- modelFit(design.fact, y$x1, type = "Linear", formula = "Y~.")
>
> sectionview.list(m1, center = c(.333,.333))
>
>
>
>
>
> dev.off()
null device
1
>