How to use the elephant.current_source_density_src.KCSD.KCSD2D function in elephant

if __name__ == '__main__':
    print('Checking 1D')
    ele_pos = np.array(([-0.1],[0], [0.5], [1.], [1.4], [2.], [2.3]))
    pots = np.array([[-1], [-1], [-1], [0], [0], [1], [-1.5]])
    k = KCSD1D(ele_pos, pots,
               gdx=0.01, n_src_init=300,
               ext_x=0.0, src_type='gauss')
    k.cross_validate()
    print(k.values())

    print('Checking 2D')
    ele_pos = np.array([[-0.2, -0.2],[0, 0], [0, 1], [1, 0], [1,1], [0.5, 0.5],
                        [1.2, 1.2]])
    pots = np.array([[-1], [-1], [-1], [0], [0], [1], [-1.5]])
    k = KCSD2D(ele_pos, pots,
               gdx=0.05, gdy=0.05,
               xmin=-2.0, xmax=2.0,
               ymin=-2.0, ymax=2.0,
               src_type='gauss')
    k.cross_validate()
    print(k.values())

    print('Checking MoIKCSD')
    k = MoIKCSD(ele_pos, pots,
                gdx=0.05, gdy=0.05,
                xmin=-2.0, xmax=2.0,
                ymin=-2.0, ymax= 2.0)
    k.cross_validate()

    print('Checking KCSD3D')
    ele_pos = np.array([(0, 0, 0), (0, 0, 1), (0, 1, 0), (1, 0, 0),

Defaults to 0.
            gdx, gdy : float
                space increments in the estimation space
                Defaults to 0.01(xmax-xmin)
                Defaults to 0.01(ymax-ymin)
            lambd : float
                regularization parameter for ridge regression
                Defaults to 0.
        Raises
        ------
        LinAlgError
            Could not invert the matrix, try changing the ele_pos slightly
        KeyError
            Basis function (src_type) not implemented. See basis_functions.py for available
        """
        super(KCSD2D, self).__init__(ele_pos, pots, **kwargs)

h : float
            thickness of slice
        basis_func : method
            Fuction of the basis source
        Returns
        -------
        pot : float
        """
        y = ((x-xp)**2 + yp**2)**(0.5)
        if y < 0.00001:
            y = 0.00001
        dist = np.sqrt(xp**2 + yp**2)
        pot = np.arcsinh(h/y)*basis_func(dist, R)
        return pot

class MoIKCSD(KCSD2D):
    """MoIKCSD - CSD while including the forward modeling effects of saline.

    This estimates the Current Source Density, for a given configuration of
    electrod positions and recorded potentials, in the case of 2D recording
    electrodes from an MEA electrode plane using the Method of Images.
    The method implented here is based on kCSD method by Jan Potworowski
    et.al. 2012, which was extended in Ness, Chintaluri 2015 for MEA.
    """
    def __init__(self, ele_pos, pots, **kwargs):
        """Initialize MoIKCSD Class.
        Parameters
        ----------
        ele_pos : numpy array
            positions of electrodes
        pots : numpy array
            potentials measured by electrodes