We set up hyperparameters similar to the default settings of SQSnobFit: probability a point of class 4 is generated = 0.5; resolution vector "dx" = 10 -5 , i.e., two points are considered to be different if they differ by at least a factor of "dx" with respect to the difference of the upper and lower bounds in at least one coordinate i; unknown uncertainty of function evaluation = "sqrt(numpy.spacing(1))".