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');
result = bayesopt(fun,[x1,x2],...
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