Bug in bayesopt() function? Initial evaluation points table being incorrectly evaluated?
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Hi, I'm using the bayesopt() function in the Global Optimization Toolbox for a problem with integer variables. I'm providing my own initial points in the solution space for the algorithm to start from. I'm doing this in the way described in the documentation, i.e:
x1=optimizableVariable('x1',[0 3],'Type', 'integer');
x2=optimizableVariable('x2',[0 3],'Type', 'integer');
InitialX= table([int8(0),int8(1)],[int8(0),int8(1)]);
result = bayesopt(fun,[x1,x2],.....'InitialX',InitialX);
As you can see I have stated x1 and x2 to be optimizableVariables of type 'integer'. I have been careful to cast my values in InitialX as integers also. However when I run my code I get the following error message:
"Error using bayesoptim.BayesoptOptions/checkInitialX (line 413) Column 1 of InitialX is declared to be integer in the VariableDescriptions argument but contains some non-integer data."
When I investigated the code in bayesoptim.BayesoptOptions/checkInitialX I found that the error is being thrown because the function bayesoptim.isInteger() is evaluating the first column of my IntialX table to contain non-integers. When I checked this against the isinteger() function (in the same workspace) it found the same argument to be only integers. The screenshot shows this more clearly.
I'm surprised by this. I cant get a look at whats going on int bayesoptim.isInteger() so can't explain why it is evaluating differently to isinteger(), but surely this is wrong? Can anyone help me with fixing my problem so that I can use my InitialX table? Thanks
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Don Mathis
2017-9-29
Hi Bob, You're running into a bug in bayesoptim.isInteger. You should be able to view that code by typing
edit bayesoptim.isInteger
It should look like this:
function tf = isInteger(x)
% Copyright 2016 The MathWorks, Inc.
tf = isscalar(x) && isnumeric(x) && isreal(x) && x==floor(x);
end
Change line 5 to this, and then save the file:
tf = isnumeric(x) & isreal(x) & x==floor(x);
After that, pass your InitialX as doubles, as Alan suggested, not as actual integer datatypes.
And please let us know how it goes.
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Don Mathis
2017-9-29
Ok, I think modifying permissions is going to depend on Windows versions and other settings, so I have a different suggestion.
You can override the bayesoptim.isInteger function by putting a replacement into a new folder that you will call +bayesoptim, and putting its enclosing folder on your MATLAB path.
The file should be named "isInteger.m" and contain this:
function tf = isInteger(x)
tf = isnumeric(x) & isreal(x) & x==floor(x);
end
Place that file in a new folder called +bayesoptim. That will define the function bayesoptim.isInteger for you. The directory into which you put this new folder must be on your MATLAB path. You could add it explicitly, or you could just put +bayesoptim in your current directory, because that is automatically on your path.
For example, suppose you want to run your MATLAB program from a folder called "MyProgram\". Put your new +bayesoptim folder into MyProgram\, navigate to MyProgram\ in MATLAB and run your program.
Does that make sense?
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Alan Weiss
2017-9-28
Your InitialX is a 1-by-2 table with contents
x1 = [0 1]
x2 = [0 1]
This is not what bayesopt expects. According to the documentation, InitialX should be an N-by-D table, where D = 2 in your case. Something like (for N = 2)
initable = table([0;1],[0;1],'VariableNames',{'x1','x2'});
Alan Weiss
MATLAB mathematical toolbox documentation
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