About Custom Plot Functions

If none of the plot functions that come with the software is suitable for the output you want to plot, you can write your own custom plot function, which the genetic algorithm calls at each generation to create the plot. This example shows how to create a plot function that displays the change in the best fitness value from the previous generation to the current generation.

Creating the Custom Plot Function

To create the plot function for this example, copy and paste the following code into a new file in the MATLAB^®Editor.

functionstate = gaplotchange(options, state, flag)% GAPLOTCHANGE Plots the logarithmic change in the best score from the% previous generation.%persistentlast_best% Best score in the previous generationif(strcmp(flag,'init'))% Set up the plotxlim([1,options.MaxGenerations]); axx = gca; axx.YScale ='log'; holdon; xlabelGenerationtitle('Log Absolute Change in Best Fitness Value')endbest = min(state.Score);% Best score in the current generationifstate.Generation == 0% Set last_best to best.last_best = best;elsechange = last_best - best;% Change in best scorelast_best = best;ifchange > 0% Plot only when the fitness improvesplot(state.Generation,change,'xr');endend

Save the file asgaplotchange.min a folder on the MATLAB path.

Using the Custom Plot Function

To use the custom plot function, include it in the options.

rng(100)% For reproducibilityoptions = optimoptions('ga','PlotFcn',{@gaplotbestf,@gaplotchange}); [x,fval] = ga(@rastriginsfcn,2,[],[],[],[],[],[],[],options)

Optimization terminated: maximum number of generations exceeded. x = -0.0003 0.0014 fval = 4.2189e-04

The plot shows only changes that are greater than 0, which are improvements in best fitness. The logarithmic scale enables you to see small changes in the best fitness function that the upper plot does not reveal.

How the Plot Function Works

情节功能ion uses information contained in the following structures, which the genetic algorithm passes to the function as input arguments:

The most important lines of the plot function are the following:

The code forgaplotchangecontains many of the same elements as the code forgaplotbestf, the function that creates the best fitness plot.