Class Linear

gpflow/functions.py:96–126

y_i = A x_i + b

class Linear(MeanFunction, Function):
    """
    y_i = A x_i + b
    """

    @check_shapes(
        "A: [broadcast D, broadcast Q]",
        "b: [broadcast Q]",
    )
    def __init__(self, A: TensorType = None, b: TensorType = None) -> None:
        """
        A is a matrix which maps each element of X to Y, b is an additive
        constant.
        """
        MeanFunction.__init__(self)
        A = np.ones((1, 1), dtype=default_float()) if A is None else A
        b = np.zeros(1, dtype=default_float()) if b is None else b
        if isinstance(A, Parameter):
            if len(A._shape) >= 2:
                self.A = A
            else:
                raise ValueError(
                    "Error 'gpflow.funcitons.Linear()' mean function. A has not the correct shape (at least 2d)."
                )
        else:
            self.A = Parameter(np.atleast_2d(A))
        self.b = Parameter(b)

    @inherit_check_shapes
    def __call__(self, X: TensorType) -> tf.Tensor:
        return tf.tensordot(X, self.A, [[-1], [0]]) + self.b


class Identity(Linear, Function):