def METHOD_NAME(self, axes=None, columns=None, names=3, **kwargs):
    """
    Plots the LYRA data.
    Parameters
    ----------
    axes : array of `matplotlib.axes.Axes`, optional
        The axes on which to plot the TimeSeries.
    columns : list[str], optional
        If provided, only plot the specified columns.
    names : `int`, optional
        The number of columns to plot. Defaults to 3.
    **kwargs : `dict`
        Additional plot keyword arguments that are handed to `~matplotlib.axes.Axes.plot` functions.
    Returns
    -------
    array of `~matplotlib.axes.Axes`
        The plot axes.
    """
    axes, columns = self._setup_axes_columns(axes, columns, subplots=True)
    lyranames = ({'CHANNEL1': 'Lyman alpha', 'CHANNEL2': 'Herzberg cont.',
                  'CHANNEL3': 'Al filter', 'CHANNEL4': 'Zr filter'},
                 {'CHANNEL1': '120-123nm', 'CHANNEL2': '190-222nm',
                  'CHANNEL3': '17-80nm + <5nm', 'CHANNEL4': '6-20nm + <2nm'})
    for i, name in enumerate(columns):
        axes[i].METHOD_NAME(self._data[columns[i]],
                     label=columns[i])
        axes[i].legend(loc="upper right")
        if names < 3:
            name = lyranames[names][columns[i]]
        else:
            name = lyranames[0][columns[i]] + ' \n (' + lyranames[1][columns[i]] + ')'
        axes[i].set_ylabel(f"{name} \n (W/m**2)", fontsize=9.5)
    self._setup_x_axis(axes)
    return axes