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, pXX = TRUE,
legendloc = "topright", maineff = TRUE, mrlayout="both",
rankmax = 20, ...)
```

x

pparts

If `TRUE`

, partition-regions are plotted (default),
otherwise they are not

proj

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.

slice

`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`

map

Optional 2-d map (longitude and latitude) from maps to be shown on top of image plots

center

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"`

as

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"`

layout

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.

main

Optional `character`

string to add to the main title of the plot

xlab

Optional `character`

string to add to the x label of the plots

ylab

Optional `character`

string to add to the y label of the plots

zlab

Optional `character`

string to add to the z label of the plots;
ignored unless `pc = "p"`

pc

Selects perspective-posterior mean and image-error plots
(`pc = "pc"`

, the default) or a double--image plot (```
pc
= "c"
```

)

gridlen

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

span

pXX

scalar logical indicating if `XX`

locations should be
plotted

legendloc

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

maineff

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.

mrlayout

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.

rankmax

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`