Not enough input arguments for multivariable function when using bayesopt.

I want bayesopt to minimize two variables in a particular function. This piece of code works with one function (just var,) but the second I try to add var1 and its corresponding y input into the function all I get is "not enough input arguments." The error sites the "fun = ..." line as the one with the error.

Here is my code and its corresponding error:

var = optimizableVariable('theta',[1,10],'Type','real');
var1 = optimizableVariable('alpha',[1,10],'Type','real');

fun = @(x,y)objfunxx(x.theta, y.alpha); %Create Function Handles
results = bayesopt(fun,[var,var1]);

Not enough input arguments.

Error in solution>@(x,y)objfunxx(x.theta,y.alpha) (line 4)
fun = @(x,y)objfunxx(x.theta, y.alpha); %Create Function Handles

Error in BayesianOptimization/callObjNormally (line 13)
Objective = this.ObjectiveFcn(conditionalizeX(this, X));

Error in BayesianOptimization/callObjFcn (line 25)
= callObjNormally(this, X);

Error in BayesianOptimization/runSerial (line 24)
ObjectiveFcnObjectiveEvaluationTime, ObjectiveNargout] = callObjFcn(this, this.XNext);

Error in BayesianOptimization/run (line 9)
this = runSerial(this);

Error in BayesianOptimization (line 184)
this = run(this);

Error in bayesopt (line 323)
Results = BayesianOptimization(Options);

function f = objfunxx(x,y)
f=y*sin(x);
end

Answer 1

[Walter Roberson]

bayesopt

fun accepts x, a 1-by-D table of variable values, and returns objective, a real scalar representing the objective function value fun(x).

You on the other hand are expecting the function to be passed two objects