4af750bec058da0cf5d4a3245a443549b9d7fd33,skopt/dummy_opt.py,,dummy_minimize,#,9

Before Change

    lb, ub = extract_bounds(bounds)

    X = np.zeros((maxiter, n_params))
    y = np.zeros(maxiter)

    for i in range(maxiter):
        X[i] = lb + (ub - lb) * rng.rand(n_params)
        y[i] = func(X[i])

    res = OptimizeResult()
    best = np.argmin(y)
    res.x = X[best]
    res.fun = y[best]

After Change

    lb, ub = extract_bounds(bounds)

    X = lb + (ub - lb) * rng.rand(maxiter, n_params)
    init_y = func(X[0])
    if not np.isscalar(init_y):
        raise ValueError(
            "The function to be optimized should return a scalar")

Instances