## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
backup_options <- options()
options(width = 1000)
set.seed(1991)


## ----eval = TRUE, echo = TRUE, message = FALSE,fig.height=4,fig.width=4-------
library(ggplot2)
library(ParBayesianOptimization)
simpleFunction <- function(x) dnorm(x,3,2)*1.5 + dnorm(x,7,1) + dnorm(x,10,2)
maximized <- optim(8,simpleFunction,method = "L-BFGS-B",lower = 0, upper = 15,control = list(fnscale = -1))$par
ggplot(data = data.frame(x=c(0,15)),aes(x=x)) + 
  stat_function(fun = simpleFunction) +
  geom_vline(xintercept = maximized,linetype="dashed")


## -----------------------------------------------------------------------------
bounds <- list(x=c(0,15))
initGrid <- data.frame(x=c(0,5,10))


## -----------------------------------------------------------------------------
FUN <- function(x) list(Score = simpleFunction(x))
optObj <- bayesOpt(
  FUN = FUN
  , bounds = bounds
  , initGrid = initGrid
  , acq = "ei"
  , iters.n = 2
  , gsPoints = 25
)


## -----------------------------------------------------------------------------
getBestPars(optObj)


## -----------------------------------------------------------------------------
simpleFunction(7.023)/simpleFunction(getBestPars(optObj)$x)


## -----------------------------------------------------------------------------
optObj <- addIterations(optObj,iters.n=2,verbose=0)
simpleFunction(7.023)/simpleFunction(getBestPars(optObj)$x)


## ----revert_options, include=FALSE--------------------------------------------
options(backup_options)