butools.map.MarginalMomentsFromMMAP
===================================

.. currentmodule:: butools.map

.. np:function:: MarginalMomentsFromMMAP

    .. list-table::
        :widths: 25 150

        * - Matlab:
          - :code:`moms = MarginalMomentsFromMMAP(D, K, precision)`
        * - Mathematica:
          - :code:`moms = MarginalMomentsFromMMAP[D, K, precision]`
        * - Python/Numpy:
          - :code:`moms = MarginalMomentsFromMMAP(D, K, precision)`

    Returns the moments of the marginal distribution of a 
    marked Markovian arrival process.

    Parameters
    ----------
    D : list/cell of matrices of shape(M,M), length(N)
        The D0...DN matrices of the MMAP
    K : int, optional
        Number of moments to compute. If K=0, 2*M-1 moments
        are computed. The default value is K=0.
    precision : double, optional
        Numerical precision for checking if the input is valid.
        The default value is 1e-14

    Returns
    -------
    moms : row vector of doubles, length K
        The vector of moments.

    Examples
    ========
    For Matlab:

    >>> D0 = [-1.78, 0.29; 0.07, -0.92];
    >>> D1 = [0.15, 0.49; 0.23, 0.36];
    >>> D2 = [0.11, 0.2; 0.01, 0];
    >>> D3 = [0.14, 0.4; 0.11, 0.14];
    >>> moms = MarginalMomentsFromMMAP({D0, D1, D2, D3});
    >>> disp(moms);
           1.0007       2.1045       6.8277

    For Mathematica:

    >>> D0 = {{-1.78, 0.29},{0.07, -0.92}};
    >>> D1 = {{0.15, 0.49},{0.23, 0.36}};
    >>> D2 = {{0.11, 0.2},{0.01, 0}};
    >>> D3 = {{0.14, 0.4},{0.11, 0.14}};
    >>> moms = MarginalMomentsFromMMAP[{D0, D1, D2, D3}];
    >>> Print[moms];
    {1.000667111407605, 2.1044966311760755, 6.827688149434602}

    For Python/Numpy:

    >>> D0 = ml.matrix([[-1.78, 0.29],[0.07, -0.92]])
    >>> D1 = ml.matrix([[0.15, 0.49],[0.23, 0.36]])
    >>> D2 = ml.matrix([[0.11, 0.2],[0.01, 0]])
    >>> D3 = ml.matrix([[0.14, 0.4],[0.11, 0.14]])
    >>> moms = MarginalMomentsFromMMAP([D0, D1, D2, D3])
    >>> print(moms)
    [1.0006671114076049, 2.1044966311760755, 6.8276881494346]