Why do I get Empty Plots during Optimization?

Question

B. Burak 2024-8-10

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评论： Torsten 2024-8-14

Inspired by custom plotting given here, for one-dimensional design variable case, I would like to generalize it to n-dimensional case. I wrote the following code to achieve that:

function state = gaPlotRangeND(options, state, flag)
    %   gaPlotRangeND Plots the mean and the range of the population for n-dimensions.
    %   STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range
    %   (highest and the lowest) of individuals for each variable.  
    generation = state.Generation;
    population = state.Population;
    
    numVars = size(population, 2);
    M = mean(population);
    L = M - min(population);
    U = max(population) - M;
    
    switch flag
    
        case 'init'
            for i = 1:numVars
                subplot(numVars, 1, i);
                set(gca, 'xlim', [1, options.MaxGenerations + 1]);
                plotRange = errorbar(generation, M(:, i), L(:, i), U(:, i));
                set(plotRange, 'Tag', ['Var_' num2str(i)]);
                title(['Range of Population, Mean for Variable ' num2str(i)], 'interp', 'none')
                xlabel('Generation', 'interp', 'none')
            
            end
            
        case 'iter'
            for i = 1:numVars
                subplot(numVars, 1, i);
                plotRange = findobj(get(gca, 'Children'), 'Tag', ['Var_' num2str(i)]);
                newX = [get(plotRange, 'Xdata'), generation];
                newY = [get(plotRange, 'Ydata'), M(:, i)];
                newL = [get(plotRange, 'Ldata'), L(:, i)];
                newU = [get(plotRange, 'Udata'), U(:, i)];       
                set(plotRange, 'Xdata', newX, 'Ydata', newY, 'Ldata', newL, 'Udata', newU);
            end
    
    end
end

When I run it for a simple two-dimensional test problem defined below, it does not work. It just outputs two empty subplots on top of each other during execution of genetic algorithm, and ends with a single empty plot. It is supposed to plot mean and range of population at each iteration for each variable, which is two in this case.

function y = booth_func(x)
    y = (x(1) + 2 * x(2) - 7) ^ 2 + (2 * x(1) + x(2) - 5) ^ 2;
end
options = optimoptions('ga', 'PlotFcn', @gaPlotRangeND);
[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options);

How can I solve this issue? What do I miss here?

3 个评论
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B. Burak 2024-8-11

I added breakpoints to observe as you suggested, but under 'iter' plotRange returns 0x0 empty GraphicsPlaceholder array.

dpb 2024-8-11

编辑：dpb 2024-8-11

在 MATLAB Online 中打开

This is probably going to be complicated, but...in

case 'init' 
  for i = 1:numVars
    subplot(numVars, 1, i);
    set(gca, 'xlim', [1, options.MaxGenerations + 1]);
    ...

You are creating multiple subplot axes and you have not saved the handle to any of them to later be able to address which of them you want...and, using gca simply will return whatever happens to be the current axes at the time it is called which will always be the last one referenced (which might be any one if user clicks on one during code execution).

At a barest minimum you'll need an array of axes handles to the various suplot axes objects and have to address each one in turn inside the iteration case code.

Not having the toolbox, no way can try anything specific here, but there's at least a starting point to try to work out the issues...

I'd suggest it also may be a place to use the tiledlayout instead of subplot()

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Answer 1

Voss 2024-8-14

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https://ww2.mathworks.cn/matlabcentral/answers/2144429-why-do-i-get-empty-plots-during-optimization#answer_1499104

移动：Walter Roberson 2024-8-14

在 MATLAB Online 中打开

Specifying the OutputFcn rather than the PlotFcn seems to provide something like what was intended.

options = optimoptions('ga', 'OutputFcn', @gaPlotRangeND);

[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options)

ga stopped because it exceeded options.MaxGenerations.

x = 1x2

1.0052 3.0107

fval = 0.0012

function y = booth_func(x)

y = (x(1) + 2 * x(2) - 7) ^ 2 + (2 * x(1) + x(2) - 5) ^ 2;

end

function [state,options,optchanged] = gaPlotRangeND(options, state, flag)

% gaPlotRangeND Plots the mean and the range of the population for n-dimensions.

% [STATE,OPTIONS,OPTCHANGED] = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the

% mean and the range (highest and the lowest) of individuals for each variable.

generation = state.Generation;

population = state.Population;

numVars = size(population, 2);

M = mean(population);

L = M - min(population);

U = max(population) - M;

persistent hAx hEB

switch flag

case 'init'

f = figure();

hAx=gobjects(size(M)); % prealloate for axes handles

hEB=gobjects(size(M)); % and for errorbars, too...

for i = 1:numVars

hAx(i)=subplot(numVars, 1, i, 'Parent', f); % create subplot, save handle to each

hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i)); % save handle to ith EB

xlim(hAx(i),[1 options.MaxGenerations+1]);

title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])

xlabel(hAx(i),'Generation')

end

case 'iter'

for i = 1:numVars

newX=[hEB(i).XData, generation]; % return existing data

newY=[hEB(i).XData, M(:, i)];

newL=[hEB(i).YNegativeDelta,L(:, i)]; % must use correct field names...

newU=[hEB(i).YPositiveDelta,U(:, i)];

set(hEB(i),'Xdata',newX,'Ydata',newY,'YNegativeDelta',newL,'YPositiveDelta',newU);

end

optchanged = false;

end

3 个评论
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B. Burak 2024-8-14

移动：Walter Roberson 2024-8-14

@Voss -- This is amazing! I think your original reply deserves to be accepted as solution to my query. If you separately post it as an answer to this thread, I would be glad to accept it as answer.

Torsten 2024-8-14

Strange behaviour of "ga" for the problem at hand ...

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Answer 2

dpb 2024-8-11

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https://ww2.mathworks.cn/matlabcentral/answers/2144429-why-do-i-get-empty-plots-during-optimization#answer_1497599

编辑：dpb 2024-8-12

在 MATLAB Online 中打开

Per the above comments, at least a start would be something more like...

function state = gaPlotRangeND(options, state, flag)
    %   gaPlotRangeND Plots the mean and the range of the population for n-dimensions.
    %   STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range
    %   (highest and the lowest) of individuals for each variable.  
    generation = state.Generation;
    population = state.Population;
    numVars = size(population, 2);
    M = mean(population);
    L = M - min(population);
    U = max(population) - M;
    
    switch flag
        case 'init'
          hAx=gobjects(size(M));                                        % prealloate for axes handles
          hEB=gobjects(size(M));                                        % and for errorbars, too...
          for i = 1:numVars
            hAx(i)=subplot(numVars, 1, i);                              % create subplot, save handle to each
            set(hAx(i), 'xlim', [1, options.MaxGenerations+1]);
            hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i));     % save handle to ith EB
            title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])
            xlabel(hAx(i),'Generation')
          end
        case 'iter'
          for i = 1:numVars
            newX=[hEB(i).XData, generation];                            % return existing data
            newY=[hEB(i).XData, M(:, i)];
            newL=[hEB(i).YNegativeData,L(:, i)];                        % must use correct field names...
            newU=[hEB(i).YPositiveData,U(:, i)];       
            set(hEB(i),'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);
          end
    end
end

Should at least have a chance...

34 个评论
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Walter Roberson 2024-8-11

在 MATLAB Online 中打开

function state = gaPlotRangeND(options, state, flag)
    %   gaPlotRangeND Plots the mean and the range of the population for n-dimensions.
    %   STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range
    %   (highest and the lowest) of individuals for each variable.  
    generation = state.Generation;
    population = state.Population;
    numVars = size(population, 2);
    M = mean(population);
    L = M - min(population);
    U = max(population) - M;
    persistent hAx hEb
    
    switch flag
        case 'init'
          delete(hEB);  %get rid of lingering objects
          delete(hAx);  %get rid of lingering objects
          hAx=gobjects(size(M));                                        % prealloate for axes handles
          hEB=gobjects(size(M));                                        % and for errorbars, too...
          for i = 1:numVars
            hAx(i)=subplot(numVars, 1, i);                              % create subplot, save handle to each
            set(hAx(i), 'xlim', [1, options.MaxGenerations+1]);
            hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i));     % save handle to ith EB
            title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])
            xlabel(hAx(i),'Generation')
          end
        case 'iter'
          for i = 1:numVars
            newX=[hEB(i).Xdata, generation];                            % return existing data
            newY=[hEB(i).Xdata, M(:, i)];
            newL=[hEB(i).YNegativeData,L(:, i)];                        % must use correct field names...
            newU=[hEB(i).YPositiveData,U(:, i)];       
            set(hEB(i),'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);
          end
    end
end

dpb 2024-8-12

在 MATLAB Online 中打开

Alternatively, without the need for persistent on the original lines @B. Burak was trying to follow...

function state = gaPlotRangeND(options, state, flag)
    %   gaPlotRangeND Plots the mean and the range of the population for n-dimensions.
    %   STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range
    %   (highest and the lowest) of individuals for each variable.  
    generation = state.Generation;
    population = state.Population;
    numVars = size(population, 2);
    M = mean(population);
    L = M - min(population);
    U = max(population) - M;
    persistent hAx hEb
    
    switch flag
        case 'init'
          hAx=gobjects(size(M));                                        % prealloate for axes handles
          hEB=gobjects(size(M));                                        % and for errorbars, too...
          for i = 1:numVars
            hAx(i)=subplot(numVars, 1, i);                              % create subplot, save handle to each
            set(hAx(i), 'xlim', [1, options.MaxGenerations+1]);
            hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i));     % save handle to ith EB
            title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])
            xlabel(hAx(i),'Generation')
          end
        case 'iter'
          for i = 1:numVars
            hAxi=subplot(numVars,1,i);                                  % the axes handle 
            hEBi=findobj(hAxi,'Type','ErrorBar');                       % find the EB object
            newX=[hEBi.Xdata, generation];                            % return existing data
            newY=[hEBi.Xdata, M(:, i)];
            newL=[hEBi.YNegativeData,L(:, i)];                        % must use correct field names...
            newU=[hEBi.YPositiveData,U(:, i)];       
            set(hEBi,'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);
          end
    end
end

Will be just a little less efficient in having to find the error bar object handle every time through...

Torsten 2024-8-12

编辑：Torsten 2024-8-12

在 MATLAB Online 中打开

@Walter Roberson

options = optimoptions('ga', 'PlotFcn', @gaPlotRangeND);

[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options);

Unrecognized function or variable 'hEB'.

Error in solution>gaPlotRangeND (line 22)
delete(hEB); %get rid of lingering objects

Error in gadsplot>callOnePlotFcn (line 228)
optimValues = plotfcn(varargin{1:end});

Error in gadsplot (line 158)
[state,optimValues] = callOnePlotFcn(fname,plotNames{i},state,options.OutputPlotFcnOptions,optimValues,'init',args{i}{:});

Error in gaunc (line 61)
state = gadsplot(options,state,currentState,gaPlotTitle);

Error in ga (line 417)
[x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...

function y = booth_func(x)

y = (x(1) + 2 * x(2) - 7) ^ 2 + (2 * x(1) + x(2) - 5) ^ 2;

end

function state = gaPlotRangeND(options, state, flag)

% gaPlotRangeND Plots the mean and the range of the population for n-dimensions.

% STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range

% (highest and the lowest) of individuals for each variable.

generation = state.Generation;

population = state.Population;

numVars = size(population, 2);

M = mean(population);

L = M - min(population);

U = max(population) - M;

persistent hAx hEb

switch flag

case 'init'

delete(hEB); %get rid of lingering objects

delete(hAx); %get rid of lingering objects

hAx=gobjects(size(M)); % prealloate for axes handles

hEB=gobjects(size(M)); % and for errorbars, too...

for i = 1:numVars

hAx(i)=subplot(numVars, 1, i); % create subplot, save handle to each

set(hAx(i), 'xlim', [1, options.MaxGenerations+1]);

hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i)); % save handle to ith EB

title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])

xlabel(hAx(i),'Generation')

end

case 'iter'

for i = 1:numVars

newX=[hEB(i).Xdata, generation]; % return existing data

newY=[hEB(i).Xdata, M(:, i)];

newL=[hEB(i).YNegativeData,L(:, i)]; % must use correct field names...

newU=[hEB(i).YPositiveData,U(:, i)];

set(hEB(i),'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);

end

Torsten 2024-8-12

编辑：Torsten 2024-8-12

在 MATLAB Online 中打开

@dpb

options = optimoptions('ga', 'PlotFcn', @gaPlotRangeND);

[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options);

Unrecognized method, property, or field 'Xdata' for class 'matlab.graphics.GraphicsPlaceholder'.

Error in solution>gaPlotRangeND (line 35)
newX=[hEBi.Xdata, generation]; % return existing data

Error in gadsplot>callOnePlotFcn (line 228)
optimValues = plotfcn(varargin{1:end});

Error in gadsplot (line 165)
[state,optimValues] = callOnePlotFcn(fname,plotNames{i},state,options.OutputPlotFcnOptions,optimValues,flag,args{i}{:});

Error in gaunc (line 116)
state = gadsplot(options,state,currentState,gaPlotTitle);

Error in ga (line 417)
[x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...

function y = booth_func(x)

y = (x(1) + 2 * x(2) - 7) ^ 2 + (2 * x(1) + x(2) - 5) ^ 2;

end

function state = gaPlotRangeND(options, state, flag)

% gaPlotRangeND Plots the mean and the range of the population for n-dimensions.

% STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range

% (highest and the lowest) of individuals for each variable.

generation = state.Generation;

population = state.Population;

numVars = size(population, 2);

M = mean(population);

L = M - min(population);

U = max(population) - M;

persistent hAx hEb

switch flag

case 'init'

hAx=gobjects(size(M)); % prealloate for axes handles

hEB=gobjects(size(M)); % and for errorbars, too...

for i = 1:numVars

hAx(i)=subplot(numVars, 1, i); % create subplot, save handle to each

set(hAx(i), 'xlim', [1, options.MaxGenerations+1]);

hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i)); % save handle to ith EB

title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])

xlabel(hAx(i),'Generation')

end

case 'iter'

for i = 1:numVars

hAxi=subplot(numVars,1,i); % the axes handle

hEBi=findobj(hAxi,'Type','ErrorBar'); % find the EB object

newX=[hEBi.Xdata, generation]; % return existing data

newY=[hEBi.Xdata, M(:, i)];

newL=[hEBi.YNegativeData,L(:, i)]; % must use correct field names...

newU=[hEBi.YPositiveData,U(:, i)];

set(hEBi,'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);

end

Torsten 2024-8-12

在 MATLAB Online 中打开

The MATLAB example works for one variable:

options = optimoptions('ga','PlotFcn',@gaplot1drange);

[x,fval] = ga(@two_min,1,[],[],[],[],[],[],[],options)

ga stopped because the average change in the fitness value is less than options.FunctionTolerance.

x = 0.0559

fval = -1.0000

function y = two_min(x)

if x <= 100

y = -exp(-(x/100)^2);

else

y = -exp(-1) + (x-100)*(x-102);

end

function state = gaplot1drange(options,state,flag)

%gaplot1drange Plots the mean and the range of the population.

% STATE = gaplot1drange(OPTIONS,STATE,FLAG) plots the mean and the range

% (highest and the lowest) of individuals (1-D only).

%

% Example:

% Create options that use gaplot1drange

% as the plot function

% options = optimoptions('ga','PlotFcn',@gaplot1drange);

if isinf(options.MaxGenerations) || size(state.Population,2) > 1

title('Plot Not Available','interp','none');

return;

end

generation = state.Generation;

score = state.Population;

smean = mean(score);

Y = smean;

L = smean - min(score);

U = max(score) - smean;

switch flag

case 'init'

set(gca,'xlim',[1,options.MaxGenerations+1]);

plotRange = errorbar(generation,Y,L,U);

set(plotRange,'Tag','gaplot1drange');

title('Range of Population, Mean','interp','none')

xlabel('Generation','interp','none')

case 'iter'

plotRange = findobj(get(gca,'Children'),'Tag','gaplot1drange');

newX = [get(plotRange,'Xdata') generation];

newY = [get(plotRange,'Ydata') Y];

newL = [get(plotRange,'Ldata') L];

newU = [get(plotRange,'Udata') U];

set(plotRange,'Xdata',newX,'Ydata',newY,'Ldata',newL,'Udata',newU);

end

B. Burak 2024-8-12

在 MATLAB Online 中打开

I think persistent option does not work either. By the way, there are misnamed properties of each hEB(i) object above. That is, there are no Xdata, Ydata properties, but XData, YData. For the final code below:

function state = gaPlotRangeND(options, state, flag)
    %   gaPlotRangeND Plots the mean and the range of the population for n-dimensions.
    %   STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range
    %   (highest and the lowest) of individuals for each variable.  
    generation = state.Generation;
    population = state.Population;
    
    numVars = size(population, 2);
    M = mean(population);
    L = M - min(population);
    U = max(population) - M;
    persistent hAx hEB
    switch flag
    
        case 'init'
            
            hAx = gobjects(size(M));
            hEB = gobjects(size(M));
            for i = 1:numVars
                hAx(i) = subplot(numVars, 1, i);
                set(hAx(i), 'xlim', [1, options.MaxGenerations + 1]);
                hEB(i) = errorbar(generation, M(:, i), L(:, i), U(:, i));
                title(hAx(i), ['Range of Population, Mean for Variable ' num2str(i)])
                xlabel(hAx(i), 'Generation')
            end
            
        case 'iter'
            
            for i = 1:numVars
                newX = [hEB(i).XData, generation];
                newY = [hEB(i).YData, M(:, i)];
                newL = [hEB(i).YNegativeDelta, L(:, i)];
                newU = [hEB(i).YPositiveDelta, U(:, i)];       
                set(hEB(i), 'XData', newX, 'YData', newY, 'YNegativeDelta', newL, 'YPositiveDelta', newU);
            end
    
    end
end

Error:

Invalid or deleted object.
Error in gaPlotRangeND (line 41)
                newX = [hEB(i).XData, generation];
Error in gadsplot>callOnePlotFcn (line 228)
        optimValues = plotfcn(varargin{1:end});
Error in gadsplot (line 165)
        [state,optimValues] = callOnePlotFcn(fname,plotNames{i},state,options.OutputPlotFcnOptions,optimValues,flag,args{i}{:});
Error in gaunc (line 116)
        state = gadsplot(options,state,currentState,gaPlotTitle);
Error in ga (line 417)
            [x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...
Error in test_case (line 251)
[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options);

dpb 2024-8-12

编辑：dpb 2024-8-12

Are you sure the initialization code ran? Set breakpoints...looks as though should work if so.

You need to determine precisely which variable/object and which pass through the loop it is that is throwing the error...is it actually the graphics handle or the other variables on the callback?

I keep forgetting the capitalization for X|YData, sorry. I'm used to the days before the property names were made to be case-sensitive...personally, I think they still should be (case insensitive, that is), but The Mathworks didn't ask my opinion. :)

ADDENDUM:

I posted an alternate that shouldn't rely on saving the handles, but it isn't yet clear what is going bad with this...

ADDENDUM SECOND:

There isn't any other code that might be doing something else to the figure by any chance, is there? We only have the callback function to look at, if something elsewhere in the code is also trying to do graphics, all bets are off...

ADDENDUM THIRD:

The initialization code of @Walter Roberson will need either a try...catch...end block around the attempt to delete the handle variables or a test whether they have yet been created and are extant or not to avoid the error @Torsten showed.

I'm not positive what the examples posted by @Torsten are intended to show, the problems still remain about there being the multiple handles/objects in this case but only one in the MATLAB sample. Perhaps the brute-force technique showed above that returns the handle by calling subplot again each time will work similarly...

B. Burak 2024-8-12

在 MATLAB Online 中打开

When I debugged it with breakpoints for both 'init' and 'iter' cases and went step by step, I took note of some points down below. I checked variables that we defined and got the following results.

Firstly, for 'init' case at the end of first for-loop iteration:

hAx
hAx = 
  1x2 graphics array:
    Axes                   GraphicsPlaceholder
hEB
hEB = 
  1x2 graphics array:
    ErrorBar               GraphicsPlaceholder

At the end of second for-loop iteration under 'init' case, I get:

hAx
hAx = 
  1x2 Axes array:
    Axes    Axes
hEB
hEB = 
  1x2 ErrorBar array:
    ErrorBar    ErrorBar

Under 'iter' case said error pops up:

Invalid or deleted object.
Error in gaPlotRangeND (line 43)
                newX = [hEB(i).XData, generation];
Error in gadsplot>callOnePlotFcn (line 228)
        optimValues = plotfcn(varargin{1:end});
Error in gadsplot (line 165)
        [state,optimValues] = callOnePlotFcn(fname,plotNames{i},state,options.OutputPlotFcnOptions,optimValues,flag,args{i}{:});
Error in gaunc (line 116)
        state = gadsplot(options,state,currentState,gaPlotTitle);
Error in ga (line 417)
            [x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...
Error in test_case (line 251)
[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options);

dpb 2024-8-12

编辑：dpb 2024-8-13

@Mario Malic, the plots are described by the plotting function init routine -- an errorbar() plot for each of the N dimensions of the problem each as a Nx1 subplot().

The above reply by @B. Burak shows the two were created because hEB contains two errorbar objects although we weren't provided with screen shot nor description of what was/was not as expected initially -- only that it blows up after that -- although again, we don't yet know just what, precisely, it is that is the problem...we suspect it's one of the handles, but it isn't conclusive as yet with what debugging information has been provided.

It's looking more and more to me as though there must be some other plotting code in the rest of the code that we haven't seen or there is some magic behind the scenes in the optimization toolbox graphics callback code that is munging on the state of the graphics or there's some undocumented "feature" about persistent variables and callback functions...at the moment, not enough info to tell and I don't have the Global Optimization TB to try to create a GA call example...

dpb 2024-8-13

编辑：dpb 2024-8-13

"...'iter' stage right before newX = [hEB(i).XData, generation]; ... I have them again, but they vanish with the error encountered."(*)

That's pretty-much conclusive evidence that the ga function is doing stuff behind the scenes that isn't documented and that is munging on the state of the HG environment, then.

I discovered the same thing in the documentation that @Torsten just commented on and was on my way here to post that tidbit as well; it appears trying to "roll your own" subplots is not feasible and you'll have to follow the documented route. This will be klunky if you are going to have very many possible values of N to have N subplots by having N different functions and list those specifically based on the value of N, but it appears may be the only way around the manner in which Mathworks has implemented the graphics callbacks.

Clever use of an array of function handles may make actual coding more generic than N unique, specific functions, but I've not thought about how(+); try the explicit two-function technique and get it to work first.

(*) I'd stop on entry to the CASE statement before continuing and then poke around in the debugger -- seeing what gca returns and comparing to the value(s) in the hAX array and looking for the children and all might be illuminating and it possibly could lead to being able to find out how to write code that will work, but if those handles are no longer valid references to the axes created in the initialization routine(**), something really peculiar is going on internally and there well may be no recourse at the user level to what MATLAB is doing internally that have no access to.

(+) Whether you can get clever and pass a cell array of elements set up programmatically, or whether it requires the explicit list, etc., etc., ... Like @Torsten, I've not ever used these callbacks so haven't ever investigated just how far can push. Apparently, we've found one limitation already...

(**) That may explain why all the sample code uses gca to retrieve the current axes object because the system internally will know what it is even if it has gotten reallocated and redefined internally from what it was originally by the time the iter call arrives. That, of course, would appear to be a potential problem if there is any other interaction going on while the optimization is running that could alter focus.

dpb 2024-8-14

在 MATLAB Online 中打开

First try with saving handles, including setting "hold on" would be

function state = gaPlotRangeND(options, state, flag)
% gaPlotRangeND Plots the mean and the range of the population for n-dimensions.
% STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range
% (highest and the lowest) of individuals for each variable.  
  generation = state.Generation;
  population = state.Population;
  numVars = size(population, 2);
  M = mean(population);
  L = M - min(population);
  U = max(population) - M;
  persistent hAx hEb
  switch flag
    case 'init'
      try                                                           % get rid of lingering objects if already extant
        delete(hEB);
        delete(hAx);
      catch
      end
      hAx=gobjects(size(M));                                        % prealloate for axes handles
      hEB=gobjects(size(M));                                        % and for errorbars, too...
      for i = 1:numVars
        hAx(i)=subplot(numVars, 1, i);                              % create subplot, save handle to each
        hold(hAx(i),'on')                                           % hold on to add more later
        xlim(hAx(i),[1 options.MaxGenerations+1]);
        hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i));     % save handle to ith EB
        title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])
        xlabel(hAx(i),'Generation')
      end
    case 'iter'
      for i = 1:numVars
        newX=[hEB(i).Xdata, generation];                            % return existing data
        newY=[hEB(i).Xdata, M(:, i)];
        newL=[hEB(i).YNegativeData,L(:, i)];                        % must use correct field names...
        newU=[hEB(i).YPositiveData,U(:, i)];       
        set(hEB(i),'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);
      end
  end
end

The proposed alternate attempt for the 'iter' case was

function state = gaPlotRangeND(options, state, flag)
  % gaPlotRangeND Plots the mean and the range of the population for n-dimensions.
  % STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range
  % (highest and the lowest) of individuals for each variable.  
  generation = state.Generation;
  population = state.Population;
  numVars = size(population, 2);
  M = mean(population);
  L = M - min(population);
  U = max(population) - M;
  switch flag
    case 'init'
      hAx=gobjects(size(M));                                        % prealloate for axes handles
      hEB=gobjects(size(M));                                        % and for errorbars, too...
      for i = 1:numVars
        hAx(i)=subplot(numVars, 1, i);                              % create subplot, save handle to each
        hold(hAx(i),'on')                                           % hold on to add more later
        xlim(hAx(i),[1 options.MaxGenerations+1])
        hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i));     % save handle to ith EB
        title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])
        xlabel(hAx(i),'Generation')
      end
    case 'iter'
      for i = 1:numVars
        hAxi=subplot(numVars,1,i);                                  % the axes handle 
        hEBi=findobj(hAxi,'Type','ErrorBar');                       % find the EB object
        newX=[hEBi.XData, generation];                              % return existing data
        newY=[hEBi.XData, M(:, i)];
        newL=[hEBi.YNegativeData,L(:, i)];                          % must use correct field names...
        newU=[hEBi.YPositiveData,U(:, i)];       
        set(hEBi,'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);
      end
  end
end

Torsten 2024-8-14

在 MATLAB Online 中打开

Unfortunately no success with option 1:

options = optimoptions('ga', 'PlotFcn', @gaPlotRangeND);

[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options);

Unrecognized function or variable 'hEB'.

Error in solution>gaPlotRangeND (line 38)
newX=[hEB(i).Xdata, generation]; % return existing data

Error in gadsplot>callOnePlotFcn (line 228)
optimValues = plotfcn(varargin{1:end});

Error in gadsplot (line 165)
[state,optimValues] = callOnePlotFcn(fname,plotNames{i},state,options.OutputPlotFcnOptions,optimValues,flag,args{i}{:});

Error in gaunc (line 116)
state = gadsplot(options,state,currentState,gaPlotTitle);

Error in ga (line 417)
[x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...

function y = booth_func(x)

y = (x(1) + 2 * x(2) - 7) ^ 2 + (2 * x(1) + x(2) - 5) ^ 2;

end

function state = gaPlotRangeND(options, state, flag)

% gaPlotRangeND Plots the mean and the range of the population for n-dimensions.

% STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range

% (highest and the lowest) of individuals for each variable.

generation = state.Generation;

population = state.Population;

numVars = size(population, 2);

M = mean(population);

L = M - min(population);

U = max(population) - M;

persistent hAx hEb

switch flag

case 'init'

try % get rid of lingering objects if already extant

delete(hEB);

delete(hAx);

catch

end

hAx=gobjects(size(M)); % prealloate for axes handles

hEB=gobjects(size(M)); % and for errorbars, too...

for i = 1:numVars

hAx(i)=subplot(numVars, 1, i); % create subplot, save handle to each

hold(hAx(i),'on') % hold on to add more later

xlim(hAx(i),[1 options.MaxGenerations+1]);

hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i)); % save handle to ith EB

title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])

xlabel(hAx(i),'Generation')

end

case 'iter'

for i = 1:numVars

newX=[hEB(i).Xdata, generation]; % return existing data

newY=[hEB(i).Xdata, M(:, i)];

newL=[hEB(i).YNegativeData,L(:, i)]; % must use correct field names...

newU=[hEB(i).YPositiveData,U(:, i)];

set(hEB(i),'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);

end

Torsten 2024-8-14

在 MATLAB Online 中打开

Same for option 2:

options = optimoptions('ga', 'PlotFcn', @gaPlotRangeND);

[x, fval] = ga(@booth_func, 2, [], [], [], [], [], [], [], options);

Unrecognized method, property, or field 'XData' for class 'matlab.graphics.GraphicsPlaceholder'.

Error in solution>gaPlotRangeND (line 34)
newX=[hEBi.XData, generation]; % return existing data

Error in gadsplot>callOnePlotFcn (line 228)
optimValues = plotfcn(varargin{1:end});

Error in gadsplot (line 165)
[state,optimValues] = callOnePlotFcn(fname,plotNames{i},state,options.OutputPlotFcnOptions,optimValues,flag,args{i}{:});

Error in gaunc (line 116)
state = gadsplot(options,state,currentState,gaPlotTitle);

Error in ga (line 417)
[x,fval,exitFlag,output,population,scores] = gaunc(FitnessFcn,nvars, ...

function y = booth_func(x)

y = (x(1) + 2 * x(2) - 7) ^ 2 + (2 * x(1) + x(2) - 5) ^ 2;

end

function state = gaPlotRangeND(options, state, flag)

% gaPlotRangeND Plots the mean and the range of the population for n-dimensions.

% STATE = gaPlotRangeND(OPTIONS, STATE, FLAG) plots the mean and the range

% (highest and the lowest) of individuals for each variable.

generation = state.Generation;

population = state.Population;

numVars = size(population, 2);

M = mean(population);

L = M - min(population);

U = max(population) - M;

switch flag

case 'init'

hAx=gobjects(size(M)); % prealloate for axes handles

hEB=gobjects(size(M)); % and for errorbars, too...

for i = 1:numVars

hAx(i)=subplot(numVars, 1, i); % create subplot, save handle to each

hold(hAx(i),'on') % hold on to add more later

xlim(hAx(i),[1 options.MaxGenerations+1])

hEB(i)=errorbar(generation, M(:, i), L(:, i), U(:, i)); % save handle to ith EB

title(hAx(i),['Range of Population, Mean for Variable ' num2str(i)])

xlabel(hAx(i),'Generation')

end

case 'iter'

for i = 1:numVars

hAxi=subplot(numVars,1,i); % the axes handle

hEBi=findobj(hAxi,'Type','ErrorBar'); % find the EB object

newX=[hEBi.XData, generation]; % return existing data

newY=[hEBi.XData, M(:, i)];

newL=[hEBi.YNegativeData,L(:, i)]; % must use correct field names...

newU=[hEBi.YPositiveData,U(:, i)];

set(hEBi,'Xdata',newX,'Ydata',newY,'YNegativeData',newL,'YPositiveData',newU);

end

dpb 2024-8-14

编辑：dpb 2024-8-14

That's truly bizarre! ga has to be mucking around with the HG environment behind the scenes...

I don't suppose you put a breakpoint into the 'iter' case to see what gca returns as compared to the saved hAx, did you? It's truly mind-boggling that those are really no longer valid handles to the initially-created axes...

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