plot_isofluxlines
=================

.. py:method:: luminet.black_hole.BlackHole.plot_isofluxlines(mask_inner=True, mask_outer=True, normalize=True, order=0, ax=None, **kwargs) -> matplotlib.axes.Axes

   Plot lines of equal flux.

   :Parameters: * **normalize** (*bool*) -- Whether to normalize the fluxlines by the maximum flux or not. Defaults to True.
                * **mask_inner** (*bool*) -- Whether to place a mask over the apparent inner edge, where the direct image produces no flux.
                  Useful to mitigate matplotlib tricontour artifacts. Default is ``True``
                * **mask_outer** (*bool*) -- Whether to place a mask over the apparent outer edge, where we are not capturing photons from.
                  Useful to mitigate matplotlib tricontour artifacts. Default is ``True``.
                * **order** (*int*) -- The order of the image to plot siofluxlines for. Default is :math:`0`.
                * **ax** (:class:`~matplotlib.axes.Axes`, optional) -- Axes object to plot on.
                  Useful for when you want to plot multiple things one a single canvas.
                * **kwargs** (*optional*) -- Other keyword arguments to pass to :py:func:`~matplotlib.pyplot.tricontour`.

   .. hint:: Normalizing the isofluxlines makes it easier to define specific levels.

   .. hint:: Levels in logspace tend to produce nicer results than linearly increasing levels.

   Example::

       from luminet.black_hole import BlackHole

       bh = BlackHole(incl=1.4, radial_resolution=200)
       levels = [.05, .1, .15, .2, .25, .3, .6, .9, 1.2, 1.5, 1.8, 2.1]
       ax = bh.plot_isofluxlines(colors='white', levels=levels, linewidths=1)

   .. image:: /../_static/_images/isofluxlines.png
      :align: center

   :returns: :class:`matplotlib.axes.Axes` -- The plotted isofluxlines.