418831c50506840b10bce58960b1ffd75080381e,elfi/methods/bo/utils.py,,minimize,#Any#Any#Any#Any#Any#Any#Any#,64

Before Change

    else:
        // Sample priors for initialization points
        prior_names = [p.name for p in priors]
        inits_dict = priors[0].model.generate(n_inits, outputs=prior_names)
        for ii, n in enumerate(prior_names):
            inits[:, ii] = inits_dict[n]
            inits[:, ii] = np.clip(inits[:, ii], *bounds[ii])

    locs = []
    vals = np.empty(n_inits)

    // Run optimization from each initialization point

After Change

        for i in range(ndim):
            start_points[:, i] = random_state.uniform(*bounds[i], n_start_points)
    else:
        start_points = prior.rvs(n_start_points)
        for i in range(ndim):
            start_points[:, i] = np.clip(start_points[:, i], *bounds[i])

    locs = []

Instances