GP.plot.curve: Graphical representation of one, two, three-dimensional...

In BayesGPfit: Fast Bayesian Gaussian Process Regression Fitting

Graphical representation of one, two, three-dimensional curves

Description

Graphical representation of one, two, three-dimensional curves

Usage

GP.plot.curve(
  curve,
  xlab = NULL,
  ylab = NULL,
  zlab = NULL,
  xlim = NULL,
  ylim = NULL,
  zlim = NULL,
  col.regions = NULL,
  cut = NULL,
  num_slices = NULL,
  ...
)

Arguments

curve	A list object with two elements: f A vector of real numbers for the curve. x A matrix of real numbers for the grid points where rows are observations and columns are coordinates.
xlab	A character specifying the label of x-axis for 1D, 2D and 3D case. The default value is NULL and set to "x" for 1D case and "x1" for 2D and 3D cases.
ylab	A character specifying the label of y-axis for 1D curve or coords for 2D and 3D case. The default value is NULL and set to "x2" for 2D and 3D cases.
zlab	A character specifying the label of z-axis only for 3D case. The default value is NULL and set to "x3".
xlim	A vector of two real numbers specifying the range of x-axis for 1D, 2D and 3D case. The default value is NULL and set to range(curve$x[,1]).
ylim	A vector of two real numbers specifying the range of y-axis only for 2D, 3D case. The default value is NULL and set to range(curve$x[,2]).
zlim	A vector of two real numbers specifying the range of z-axis only for 3D case. The default value is NULL and set to range(curve$x[,3]).
col.regions	A vector of RGB colors for 2D and 3D plots. See GP.create.cols. The default value is NULL and set to GP.create.cols().
cut	An integer specifying the number of colors in 2D and 3D plots. The default value is NULL and set to length(col.regions)-1.
num_slices	An integer specifying the number of slices cutting through the 3rd dimension to show.
...	All other parameters for plot (1D case) and levelplot (2D and 3D cases).

Value

NULL for 1D case. An object of class "trellis" for 2D and 3D cases.

Author(s)

Jian Kang <[e-mail]>

Examples

library(BayesGPfit)
library(lattice)
set.seed(1224)
##plot 1D curve
x1d = GP.generate.grids(d=1,num_grids = 1000)
curve1d = GP.simulate.curve.fast(x1d,a=0.01,b=0.5,
                              poly_degree=10L)
GP.plot.curve(curve1d,main="Simulated 1D Curve")

##plot 2D curve
x2d = GP.generate.grids(d=2L,num_grids = 100)
curve2d = GP.simulate.curve.fast(x2d,a=0.01,b=0.5,
                              poly_degree=10L)
GP.plot.curve(curve2d,main="Simulated 2D Curve")

##plot 3D curve
x3d = GP.generate.grids(d=3,num_grids = 50)
curve3d = GP.simulate.curve.fast(x3d,a=0.01,b=0.5,
                              poly_degree=10L)
GP.plot.curve(curve3d,main="Simulated 3D Curve",num_slices=10,zlim=c(-0.5,0.5))

BayesGPfit documentation built on Aug. 6, 2022, 5:06 p.m.