plot_uncertainty function

Plot uncertainty

Displays the probability of non-domination in the variable space. In dimension larger than two, projections in 2D subspaces are displayed.

plot_uncertainty(
  model,
  paretoFront = NULL,
  type = "pn",
  lower,
  upper,
  resolution = 51,
  option = "mean",
  nintegpoints = 400
)

Arguments

• model: list of objects of class km, one for each objective functions,
• paretoFront: (optional) matrix corresponding to the Pareto front of size [n.pareto x n.obj],
• type: type of uncertainty, for now only the probability of improvement over the Pareto front,
• lower: vector of lower bounds for the variables,
• upper: vector of upper bounds for the variables,
• resolution: grid size (the total number of points is resolution^d),
• option: optional argument (string) for n > 2 variables to define the projection type. The 3 possible values are "mean" (default), "max" and "min",
• nintegpoints: number of integration points for computation of mean, max and min values.

Details

Function inspired by the function print_uncertainty and print_uncertainty_nd from the package KrigInv-package. Non-dominated observations are represented with green diamonds, dominated ones by yellow triangles.

Examples

## Not run:
 
#---------------------------------------------------------------------------
# 2D, bi-objective function
#---------------------------------------------------------------------------
set.seed(25468)
n_var <- 2 
fname <- P1
lower <- rep(0, n_var)
upper <- rep(1, n_var)
res1 <- easyGParetoptim(fn=fname, lower=lower, upper=upper, budget=15, 
control=list(method="EHI", inneroptim="pso", maxit=20))

plot_uncertainty(res1$model, lower = lower, upper = upper)

#---------------------------------------------------------------------------
# 4D, bi-objective function
#---------------------------------------------------------------------------
set.seed(25468)
n_var <- 4
fname <- DTLZ2
lower <- rep(0, n_var)
upper <- rep(1, n_var)
res <- easyGParetoptim(fn=fname, lower=lower, upper=upper, budget = 40, 
control=list(method="EHI", inneroptim="pso", maxit=40))

plot_uncertainty(res$model, lower = lower, upper = upper, resolution = 31)
## End(Not run)