butools.dmap.CheckDMRAPRepresentation
=====================================

.. currentmodule:: butools.dmap

.. np:function:: CheckDMRAPRepresentation

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

        * - Matlab:
          - :code:`r = CheckDMRAPRepresentation(H, prec)`
        * - Mathematica:
          - :code:`r = CheckDMRAPRepresentation[H, prec]`
        * - Python/Numpy:
          - :code:`r = CheckDMRAPRepresentation(H, prec)`

    Checks if the input matrixes define a discrete time MRAP.
    
    All matrices H0...HK must have the same size, the dominant
    eigenvalue of H0 is real and less than 1, and the rowsum of 
    H0+H1+...+HK is 1 (up to the numerical precision).

    Parameters
    ----------
    H : list/cell of matrices, length(K)
        The H0...HK matrices of the DMRAP to check

    Returns
    -------
    r : bool 
        The result of the check

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

    >>> H0 = [0.15, 0.2, 0.18; -0.23, 0.17, 0.22; 0.19, 0.15, 0.16];
    >>> H1 = [0.01, 0.08, 0.16; 0.02, 0.2, 0.07; 0.02, 0.15, 0.17];
    >>> H2 = [0.14, 0.07, 0.01; 0.19, 0.02, 0.34; 0.06, 0.1, 0];
    >>> flag = CheckDMRAPRepresentation({H0, H1, H2});
    >>> disp(flag);
         1

    For Mathematica:

    >>> H0 = {{0.15, 0.2, 0.18},{-0.23, 0.17, 0.22},{0.19, 0.15, 0.16}};
    >>> H1 = {{0.01, 0.08, 0.16},{0.02, 0.2, 0.07},{0.02, 0.15, 0.17}};
    >>> H2 = {{0.14, 0.07, 0.01},{0.19, 0.02, 0.34},{0.06, 0.1, 0}};
    >>> flag = CheckDMRAPRepresentation[{H0, H1, H2}];
    >>> Print[flag];
    True

    For Python/Numpy:

    >>> H0 = ml.matrix([[0.15, 0.2, 0.18],[-0.23, 0.17, 0.22],[0.19, 0.15, 0.16]])
    >>> H1 = ml.matrix([[0.01, 0.08, 0.16],[0.02, 0.2, 0.07],[0.02, 0.15, 0.17]])
    >>> H2 = ml.matrix([[0.14, 0.07, 0.01],[0.19, 0.02, 0.34],[0.06, 0.1, 0]])
    >>> flag = CheckDMRAPRepresentation([H0, H1, H2])
    >>> print(flag)
    True