public (NDarray, NDarray, NDarray) Transform(NDarray X)
{
var k = GaussProcessRegressor.RBF(this.xTrain, this.xTrain, this.Option.l, this.Option.sigma) + this.Option.noise * this.Option.noise * np.eye(this.xTrain.len);
var k_s = GaussProcessRegressor.RBF(this.xTrain, X, this.Option.l, this.Option.sigma);
var k_ss = GaussProcessRegressor.RBF(X, X, this.Option.l, this.Option.sigma) + 1e-8 * np.eye(X.len);
var k_inv = np.linalg.inv(k);
var mean_s = k_s.T.dot(k_inv).dot(this.yTrain);
var cov_s = k_ss - k_s.T.dot(k_inv).dot(k_s);
var res = np.random.multivariate_normal(mean_s.ravel(), cov_s);
return(res, mean_s, cov_s);
}
public GaussProcessSweeper(Option option)
{
this._option = option;
this._generated = new HashSet <IDictionary <string, string> >();
this._runHistory = new List <IRunResult>();
var randomSweeperOption = new UniformRandomSweeper.Option()
{
Retry = option.Retry,
};
this._randomSweeper = new UniformRandomSweeper(randomSweeperOption);
var gpOption = new GaussProcessRegressor.Options()
{
l = option.L,
sigma = option.Sigma,
noise = option.Noise,
};
this._regressor = new GaussProcessRegressor(gpOption);
}
