OOR (version 0.1.4)

plotStoSOO: Plot 2-D StoSOO result

Description

Plot bivariate tree structure obtained when running StoSOO

Usage

plotStoSOO(
  sol,
  lower = rep(0, length(sol$par)),
  upper = rep(1, length(sol$par)),
  levels = NULL,
  add = FALSE,
  cpch = ".",
  lcols = 1,
  ylim = NULL
)

Arguments

sol

outcome of running StoSOO, with control$light set to FALSE

lower, upper

vectors of bounds on the variables.

levels

which levels to print. Default to all levels

add

if TRUE, use existing plot

cpch

points pch code for the centers

lcols

color at each level, or a single color for all levels (default)

ylim

vector of bounds, required in the 1d case

Examples

#------------------------------------------------------------
# Example 1 : Deterministic optimization with SOO, 1-dimensional function
#------------------------------------------------------------
## Define objective
fun1 <- function(x) return(-guirland(x))

## Optimization
Sol1 <- StoSOO(par = NA, fn = fun1, nb_iter = 1000, 
  control = list(type = "det", verbose = 1, light = FALSE))

## Display objective function and solution found
curve(fun1, n = 1001, ylim = c(-1.3, 0))
abline(v = Sol1$par, col = 'red')
plotStoSOO(Sol1, ylim = c(-1.3, -1.1), add = TRUE)

#------------------------------------------------------------
# Example 2 : Deterministic optimization with SOO, 2-dimensional function
#------------------------------------------------------------
set.seed(42)

## 2-dimensional noiseless objective function, defined on [0, pi/4]^2
fun <- function(x){return(-sin1(x[1]) * sin1(1 - x[2]))}

## Optimizing
Sol <- StoSOO(par = rep(NA, 2), fn = fun, upper = rep(pi/4, 2), nb_iter = 1000,
  control = list(type = 'det', light = FALSE))
  
## Display solution
plotStoSOO(Sol, upper = rep(pi/4, 2))