544875dd8a7fea49a86e5623d37274159b4ba7b5,skopt/optimizer/base.py,,base_minimize,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,20

Before Change

            raise ValueError(
                "`y0` elements should be scalars")

        for i, (x, y) in enumerate(zip(x0, y0)):
            // on the last iteration fit a model so we can start predicting
            // unless there are random points to be evaluated next
            fit_model = i == len(x0) - 1 and n_random_starts == 0
            optimizer.tell(x, y, fit=fit_model)

            if callbacks:
                result = create_result(optimizer.Xi, optimizer.yi,
                                       optimizer.space, optimizer.rng,
                                       specs, optimizer.models)
                for c in callbacks:
                    c(result)

    // Bayesian optimization loop
    for n in range(n_calls - n_init_func_calls):
        // fit model after last random iteration
        fit_model = n >= n_random_starts - 1
        next_x = optimizer.ask()

After Change

    // User suggested points at which to evaluate the objective first
    if x0 and y0 is None:
        y0 = list(map(func, x0))
        if not all(map(np.isscalar, y0)):
            raise ValueError(
                "`y0` elements should be scalars")
        optimizer.tell(x0, y0)

        if callbacks:
            result = create_result(optimizer.Xi, optimizer.yi,

Instances