Description Usage Arguments Details Methods Author(s) See Also Examples
Plot methods are implemented for simulated random fields (objects of
class RFsp
), explicit covariance models
(objects of class RMmodel
),
empirical variograms (objects of class
RFempVariog
) and fitted models
(objects of class RFfit
).
The plot methods not described here are described together with the
class itself, for instance,
RFfit
,
RFempVariog
RMmodel
.
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 | RFplotSimulation(x, y, MARGIN=c(1,2), MARGIN.slices=NULL,
n.slices = if (is.null(MARGIN.slices)) 1 else 10, nmax=6,
plot.variance = !is.null(x@.RFparams$has.variance) && x@.RFparams$has.variance,
select.variables, zlim, legend=TRUE,
MARGIN.movie = NULL, file=NULL, speed = 0.3,
height.pixel=300, width.pixel=height.pixel,
..., plotmethod="image")
RFplotSimulation1D(x, y, nmax=6,
plot.variance=!is.null(x@.RFparams$has.variance) && x@.RFparams$has.variance,
legend=TRUE, ...)
## S4 method for signature 'RFgridDataFrame,missing'
plot(x, y, ...)
## S4 method for signature 'RFpointsDataFrame,missing'
plot(x, y, ...)
## S4 method for signature 'RFspatialGridDataFrame,missing'
plot(x, y, ...)
## S4 method for signature 'RFspatialPointsDataFrame,missing'
plot(x, y, ...)
## S4 method for signature 'RFgridDataFrame,matrix'
plot(x, y, ...)
## S4 method for signature 'RFpointsDataFrame,matrix'
plot(x, y, ...)
## S4 method for signature 'RFspatialGridDataFrame,matrix'
plot(x, y, ...)
## S4 method for signature 'RFspatialPointsDataFrame,matrix'
plot(x, y, ...)
## S4 method for signature 'RFgridDataFrame,data.frame'
plot(x, y, ...)
## S4 method for signature 'RFpointsDataFrame,data.frame'
plot(x, y, ...)
## S4 method for signature 'RFspatialGridDataFrame,data.frame'
plot(x, y, ...)
## S4 method for signature 'RFspatialPointsDataFrame,data.frame'
plot(x, y, ...)
## S4 method for signature 'RFgridDataFrame,RFgridDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFgridDataFrame,RFpointsDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFpointsDataFrame,RFgridDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFpointsDataFrame,RFpointsDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFspatialGridDataFrame,RFspatialGridDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFspatialGridDataFrame,RFspatialPointsDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFspatialPointsDataFrame,RFspatialGridDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFspatialPointsDataFrame,RFspatialPointsDataFrame'
plot(x, y, ...)
## S4 method for signature 'RFspatialGridDataFrame'
persp(x, ..., zlab="")
## S3 method for class 'RFspatialGridDataFrame'
contour(x, ...)
|
x |
object of class |
y |
ignored in most methods; in case of
|
MARGIN |
vector of two; two integer values giving the coordinate dimensions w.r.t. whether the field or the covariance model is to be plotted; in all other directions, the first index is taken |
MARGIN.slices |
integer value; if [space-time-dimension>2],
|
n.slices |
integer value.
The number of slices to be plotted; if
|
nmax |
the maximal number of the |
MARGIN.movie |
integer. If given a sequence of figures is shown for this direction. This option is in an experimental stage. It works only for grids. |
file, speed, height.pixel, width.pixel |
In case |
... |
arguments to be passed to methods; mainly graphical
arguments, or further models in case of class |
plot.variance |
logical, whether variances should be plotted if available |
select.variables |
vector of integers or list of vectors.
The argument is only of interest for multivariate models.
Here,
|
legend |
logical, whether a legend should be plotted |
zlim |
vector of length 2 with the usual meaning.
In case of multivariate random fields, |
plotmethod |
string or function. Internal. |
zlab |
character. See |
Internally, ...
are passed to image
and
plot.default
, respectively; if, by default, multiple colors,
xlabs or ylabs are used, also vectors of suitable length can be
passed as col
, xlab
and ylab
, respectively.
One exception is the use of ...
in plot
for class
CLASS_CLIST
.
Here, further models might be passed. All models must have names
starting with model
. If '.'
is following in the name,
the part of the name after the dot is shown in the legend. Otherwise
the name is ignored and a standardized name derived from the model
definition is shown in the legend. Note that for the first argument
a name cannot be specified.
signature(x = "RFspatialGridDataFrame", y =
"missing")
Generates nice image plots of simulation results for
simulation on a grid and space-time-dimension >1. If
space-time-dimension >2, plots are on 2-dimensional
subspaces.
Handles multivariate random fields (.RFparams$vdim>1
) as well as
repeated iid simulations (.RFparams$vdim>n
).
signature(x = "RFspatialGridDataFrame", y =
"RFspatialPointsDataFrame")
Similar to method for y="missing"
, but additionally adds the
points of y
. Requires MARGIN.slices=NULL
and
all.equal(x@.RFparams, y@.RFparams)
.
signature(x = "RFspatialGridDataFrame", y =
"matrix")
Similar to method for y="missing"
, but additionally adds the
points of y
. Requires MARGIN.slices=NULL
and
all.equal(x@.RFparams, y@.RFparams)
.
signature(x = "RFspatialPointsDataFrame", y =
"RFspatialGridDataFrame")
Throws an error. Probably x
and y
have been interchanged.
signature(x = "RFspatialPointsDataFrame", y =
"missing")
Similar to method for class
RFspatialGridDataFrame
, but for non-gridded simulation results.
Instead of a grid, only existing points are plotted with colors indicating
the value of the random field at the respective location. Handles
multivariate random fields (.RFparams$vdim>1
) as well as
repeated iid simulations (.RFparams$vdim>n
).
signature(x = "RFspatialPointsDataFrame", y =
"RFspatialPointsDataFrame")
Similar to method for y="missing"
, but additionally adds the
points of y
. Requires
all.equal(x@.RFparams, y@.RFparams)
.
signature(x = "RFgridDataFrame", y = "missing")
Generates plots of simulation results for space-time-dimension =1. Handles different values for the number of repetitions as well as multivariate responses.
signature(x = "RFpointsDataFrame", y = "missing")
Similar
to method for class RFgridDataFrame
, but for non-gridded data.
Alexander Malinowski, \martin
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 | RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
## define the model:
model <- RMtrend(mean=0.5) + # mean
RMstable(alpha=1, var=4, scale=10) + # see help("RMstable")
## for additional arguments
RMnugget(var=1) # nugget
#############################################################
## Plot of covariance structure
plot(model)
plot(model, xlim=c(0, 30))
plot(model, xlim=c(0, 30), fct.type="Variogram")
plot(model, xlim=c(-10, 20), fct.type="Variogram", dim=2)
image(model, xlim=c(-10, 20), fct.type="Variogram")
persp(model, xlim=c(-10, 20), fct.type="Variogram")
#############################################################
## Plot of simulation results
## define the locations:
from <- 0
step <- .1
len <- 50 # nicer if len=100 %ok
x1D <- GridTopology(from, step, len)
x2D <- GridTopology(rep(from, 2), rep(step, 2), rep(len, 2))
x3D <- GridTopology(rep(from, 3), rep(step, 3), rep(len, 3))
## 1-dimensional
sim1D <- RFsimulate(model = model, x=x1D, n=6)
plot(sim1D, nmax=4)
## 2-dimensional
sim2D <- RFsimulate(model = model, x=x2D, n=6)
plot(sim2D, nmax=4)
plot(sim2D, nmax=4, col=terrain.colors(64),
main="My simulation", xlab="my_xlab")
## 3-dimensional
model <- RMmatern(nu=1.5, var=4, scale=2)
sim3D <- RFsimulate(model = model, x=x3D)
plot(sim3D, MARGIN=c(2,3), MARGIN.slices=1, n.slices=4)
#############################################################
## empirical variogram plots
x <- seq(0, 10, 0.05)
bin <- seq(from=0, by=.2, to=3)
model <- RMexp()
X <- RFsimulate(model, x=cbind(x))
ev1 <- RFvariogram(data=X, bin=bin)
plot(ev1)
model <- RMexp(Aniso = cbind(c(10,0), c(0,1)))
X <- RFsimulate(model, x=cbind(x,x))
ev2 <- RFvariogram(data=X, bin=bin, phi=3)
plot(ev2, model=list(exp = model))
#############################################################
## plot Kriging results
model <- RMwhittle(nu=1.2, scale=2)
n <- 200
x <- runif(n, max=step*len/2)
y <- runif(n, max=step*len/2) # 200 points in 2 dimensional space
sim <- RFsimulate(model, x=x, y=y)
interpolate <- RFinterpolate(model, x=x2D, data=sim)
plot(interpolate)
plot(interpolate, sim)
#############################################################
## plotting vector-valued results
model <- RMdivfree(RMgauss(), scale=4)
x <- y <- seq(-10,10, 0.5)
simulated <- RFsimulate(model, x=x, y=y, n=1)
plot(simulated)
plot(simulated, select.variables=list(1, 1:3, 4))
#############################################################
## options for the zlim argument
model <- RMdelay(RMstable(alpha=1.9, scale=2), s=c(0, 4)) +
RMdelay(RMstable(alpha=1.9, scale=2), s=c(4, 0))
simu <- RFsimulate(model, x, y)
plot(simu, zlim=list(data=cbind(c(-6,2), c(-2,1)), var=c(5,6)))
plot(simu, zlim=cbind(c(-6,2), c(-2,1)))
plot(simu, zlim=c(-6,2))
plot(simu, zlim="joint")
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