gaussian_process.py 文件源码

def k(self, x, y):
    """Kernel function."""
    for arg in [x, y]:
      assert isinstance(arg, (float, np.float32, np.float64)) or \
             (isinstance(arg, np.ndarray) and np.rank(arg) == 1)
    mi = self.offset + np.minimum(x, y)
    return self.theta**2 * (mi**3/3.0 + 0.5*np.abs(x-y)*mi**2)