p, step)`` inside of the brackets. However, if
    ``step`` is an imaginary number (i.e. 100j) then its integer portion is
    interpreted as a number-of-points desired and the start and stop are
    inclusive. In other words ``start:stop:stepj`` is interpreted as
    ``np.linspace(start, stop, step, endpoint=1)`` inside of the brackets.
    After expansion of slice notation, all comma separated sequences are
    concatenated together.

    Optional character strings placed as the first element of the index
    expression can be used to change the output. The strings 'r' or 'c' result
    in matrix output. If the result is 1-D and 'r' is specified a 1 x N (row)
    matrix is produced. If the result is 1-D and 'c' is specified, then a N x 1
    (column) matrix is produced. If the result is 2-D then both provide the
    same matrix result.

    A string integer specifies which axis to stack multiple comma separated
    arrays along. A string of two comma-separated integers allows indication
    of the minimum number of dimensions to force each entry into as the
    second integer (the axis to concatenate along is still the first integer).

    A string with three comma-separated integers allows specification of the
    axis to concatenate along, the minimum number of dimensions to force the
    entries to, and which axis should contain the start of the arrays which
    are less than the specified number of dimensions. In other words the third
    integer allows you to specify where the 1's should be placed in the shape
    of the arrays that have their shapes upgraded. By default, they are placed
    in the front of the shape tuple. The third argument allows you to specify
    where the start of the array should be instead. Thus, a third argument of
    '0' would place the 1's at the end of the array shape. Negative integers
    specify where in the new shape tuple the last dimension of upgraded arrays
    should be placed, so the default is '-1'.

    Parameters
    ----------
    Not a function, so takes no parameters


    Returns
    -------
    A concatenated ndarray or matrix.

    See Also
    --------
    concatenate : Join a sequence of arrays along an existing axis.
    c_ : Translates slice objects to concatenation along the second axis.

    Examples
    --------
    >>> np.r_[np.array([1,2,3]), 0, 0, np.array([4,5,6])]
    array([1, 2, 3, ..., 4, 5, 6])
    >>> np.r_[-1:1:6j, [0]*3, 5, 6]
    array([-1. , -0.6, -0.2,  0.2,  0.6,  1. ,  0. ,  0. ,  0. ,  5. ,  6. ])

    String integers specify the axis to concatenate along or the minimum
    number of dimensions to force entries into.

    >>> a = np.array([[0, 1, 2], [3, 4, 5]])
    >>> np.r_['-1', a, a] # concatenate along last axis
    array([[0, 1, 2, 0, 1, 2],
           [3, 4, 5, 3, 4, 5]])
    >>> np.r_['0,2', [1,2,3], [4,5,6]] # concatenate along first axis, dim>=2
    array([[1, 2, 3],
           [4, 5, 6]])

    >>> np.r_['0,2,0', [1,2,3], [4,5,6]]
    array([[1],
           [2],
           [3],
           [4],
           [5],
           [6]])
    >>> np.r_['1,2,0', [1,2,3], [4,5,6]]
    array([[1, 4],
           [2, 5],
           [3, 6]])

    Using 'r' or 'c' as a first string argument creates a matrix.

    >>> np.r_['r',[1,2,3], [4,5,6]]
    matrix([[1, 2, 3, 4, 5, 6]])

    c