plot2d: Visualize optimization procedure in 2d contour plot

In PhilippScheller/visualDescend: Visulaization of descent method for multi-dimensional optimization functions

Description

This functions visualizes the steps of the optimization in a 2 dimensional contour plot. The default upper and lower bounds for the plot are set by the box constraints of the respective optimization function.

Usage

plot2d(
  f,
  x1.lower,
  x1.upper,
  x2.lower,
  x2.upper,
  n.x = 30L,
  xmat,
  trueOpt = NULL,
  algoName = NULL,
  plotSegments = FALSE,
  optimError = FALSE
)

Arguments

f	a (multi-) dimensional function to be eptimized.
x1.lower	the lower boundary for the range of the x1 coordinate displayed.
x1.upper	the upper boundary for the range of the x1 coordinate displayed.
x2.lower	the lower boundary for the range of the x2 coordinate displayed.
x2.upper	the upper boundary for the range of the x2 coordinate displayed.
n.x	the number (equidistant) points at which f is evaluated w.r.t x1 and x2 coordinate.
xmat	an object of class list containing the results of the algorithm.
trueOpt	is a numeric vector of the true optimum of the function.
optimError	passed argument from optimization. Specifies if error in gradient occured.
algoNamw	list of strings with names of algorithms. Length must equal length of 'xmat'.

PhilippScheller/visualDescend documentation built on Feb. 5, 2020, 4:04 a.m.