def start()

in bayesmark/builtin_opt/pysot_optimizer.py [0:0]

• 22 lines of code
• 1 McCabe index (conditional complexity)

    def start(self, max_evals):
        """Starts a new pySOT run."""
        self.history = []
        self.proposals = []

        # Symmetric Latin hypercube design
        des_pts = max([self.batch_size, 2 * (self.opt.dim + 1)])
        slhd = SymmetricLatinHypercube(dim=self.opt.dim, num_pts=des_pts)

        # Warped RBF interpolant
        rbf = RBFInterpolant(
            dim=self.opt.dim,
            lb=self.opt.lb,
            ub=self.opt.ub,
            kernel=CubicKernel(),
            tail=LinearTail(self.opt.dim),
            eta=1e-4,
        )

        # Optimization strategy
        self.strategy = SRBFStrategy(
            max_evals=self.max_evals,
            opt_prob=self.opt,
            exp_design=slhd,
            surrogate=rbf,
            asynchronous=True,
            batch_size=1,
            use_restarts=True,
        )