search.py 文件源码

def __init__(self, param_priors, param_hyperparameters, n_iter):
        self.hyperparameters = collections.OrderedDict(sorted(param_hyperparameters.items()))
        self.n_iter = n_iter
        self.param_index = []
        self.distributions = {}

        kde_data = None
        for name, hyperparameter in param_hyperparameters.items():
            if isinstance(hyperparameter, UniformFloatHyperparameter):
                self.param_index.append(name)
                data = np.array(param_priors[name])
                if hyperparameter.log:
                    data = np.log2(data)
                if kde_data is None:
                    kde_data = np.reshape(np.array(data), (1, len(data)))
                else:
                    reshaped = np.reshape(np.array(data), (1, len(data)))
                    kde_data = np.concatenate((kde_data, reshaped), axis=0)
            elif isinstance(hyperparameter, UniformIntegerHyperparameter):
                raise ValueError('UniformIntegerHyperparameter not yet implemented:', name)
            elif isinstance(hyperparameter, CategoricalHyperparameter):
                self.distributions[name] = openmlpimp.utils.rv_discrete_wrapper(name, param_priors[name])
            else:
                raise ValueError()
        if len(self.param_index) < 2:
            raise ValueError('Need at least 2 float hyperparameters')
        self.kde = gaussian_kde(kde_data)