A generic function for plotting of "tgp"
-class objects.
1-d posterior mean and error plots, 2-d posterior mean and
error image and perspective plots, and 3+-dimensional mean and error
image and perspective plots are supported via projection
and slicing.
# S3 method for tgp
plot(x, pparts = TRUE, proj = NULL, slice = NULL,
map = NULL, as = NULL, center = "mean", layout = "both",
main = NULL, xlab = NULL, ylab = NULL, zlab = NULL, pc = "pc",
gridlen = c(40,40), span = 0.1,
legendloc = "topright", maineff = TRUE, mrlayout="both",
rankmax = 20, ...)
If TRUE
, partition-regions are plotted (default),
otherwise they are not
1-or-2-Vector describing the dimensions to be shown in a
projection. The argument is ignored for 1-d data, i.e., if x$d
== 1
. For 2-d data, no projection needs be specified--- the
default argument (proj = NULL
) will result in a 2-d perspective
or image plot. 1-d projections of 2-d or higher data are are
supported, e.g., proj = c(2)
would show the second variable
projection. For 3-d data or higher, proj=NULL
defaults to
proj = c(1,2)
which plots a 2-d projection for the first two
variables. Slices have priority over the projections---
see next argument (slice
)--- when non-null arguments are
provided for both.
list
object with x
and z
fields, which
are vectors of equal length describing the slice to be plotted, i.e.,
which z-values of the x$d - 2
inputs x$X
and
x$XX
should be fixed to in order to obtain a 2-d visualization.
For example, for 4-d data, slice = list(x=(2,4), z=c(0.2, 1.5)
will
result in a 2-d plot of the first and third dimensions which have
the second and fourth slice fixed at 0.5 and 1.5. The default is
NULL
, yielding to the proj
argument. Argument is
ignored for 1-d data, i.e., if x$d == 1
Optional 2-d map (longitude and latitude) from maps to be shown on top of image plots
Default center = "mean"
causes the posterior
predictive mean to be plotted as the centering statistic.
Otherwise the median can be used with center = "med"
, or the
kriging mean with center = "km"
Optional string indicator for plotting of adaptive sampling
statistics: specifying as = "alm"
for ALM, as = "s2"
for predictive variance, as = "ks2"
for expected kriging
variance, as = "alc"
for ALC,
and as = "improv"
for expected improvement (about the
minimum, see the rankmax
argument below).
The default as = NULL
plots error-bars (1d-plots) or
error magnitudes (2d-plots), which is essentially the same as
as = "alm"
Specify whether to plot the mean predictive surface
(layout = "surf"
), the error or adaptive sampling statistics
(layout = "as"
), or default (layout = "both"
) which
shows both. If layout = "sens"
, plot the results of a
sensitivity analysis (see sens
) in a format determined
by the argument maineff
below.
Optional character
string to add to the main title of the plot
Optional character
string to add to the x label of the plots
Optional character
string to add to the y label of the plots
Optional character
string to add to the z label of the plots;
ignored unless pc = "p"
Selects perspective-posterior mean and image-error plots
(pc = "pc"
, the default) or a double--image plot (pc
= "c"
)
Number of regular grid points for 2-d slices and
projections in x and y. The default of gridlen = c(40,40)
causes a 40 * 40
grid of X
, Y
, and Z
values to be computed.
Ignored for 1-d plots and projections
Location of the legend
included in the
plots of sensitivity analyses produced with layout = "sens"
,
or 1-d plots of multi-resolution models (with corr = "mrexpsep"
)
and option mrlayout = "both"
; otherwise the argument is ignored
Format for the plots of sensitivity analyses produced
with layout = "sens"
; otherwise the argument is ignored.
If maineff=TRUE
main effect plots are produced
alongside boxplots for posterior samples of the sensitivity indices,
and if FALSE
only the boxplots are produced. Alternatively,
maineff
can be a matrix containing input dimensions in the
configuration that the corresponding main effects are to be plotted;
that is, mfrow=dim(maineff)
. In this case, a 90 percent
interval is plotted with each main effect and the sensitivity index
boxplots are not plotted.
The plot layout for double resolution
tgp objects with params$corr == "mrexpsep"
. For the default
mrlayout="both"
, the coarse and fine fidelity are plotted
together, either on the same plot for 1D inputs or through
side-by-side image plots of the predicted center
with axis
determined by proj
for inputs of greater dimension.
Note that many of the standard arguments -- such as slice
,
pc
, and map
-- are either non-applicable or
unsupported for mrlayout="both"
. If mrlayout="coarse"
or mrlayout="fine"
, prediction for the respective fidelity is
plotted as usual and all of the standard options apply.
When as = "improv"
is provided, the posterior
expected improvements are plotted according the the first column
of the improv
field of the "tgp"
-class object.
Text is added to the plot near the XX
positions of the first
1:rankmax
predictive locations with the highest ranks in the
second column of the improv
field.
Extra arguments to 1-d (plot
) and 2-d plotting
functions persp
and image
The only output of this function is beautiful plots
plot
, bgpllm
, btlm
,
blm
, bgp
, btgpllm
,
predict.tgp
,
tgp.trees
, mapT
, loess
, sens