.. _tutorial-model:

===================================
Model for post-processing tutorials
===================================

The concepts shown in the tutorials can be applied to any model you
run, but the specific examples assume the following simple model. You
can create the model by running the following script::

    import numpy as np

    from hyperion.model import Model
    from hyperion.util.constants import pc, lsun

    # Initialize model
    m = Model()

    # Set one-cell cartesian grid
    w = np.linspace(-pc, pc, 32)
    m.set_cartesian_grid(w, w, w)

    # Add density grid with constant density
    m.add_density_grid(np.ones(m.grid.shape) * 4.e-20, 'kmh_lite.hdf5')

    # Add a point source in the center
    s = m.add_point_source()
    s.luminosity = 1000 * lsun
    s.temperature = 6000.

    # Add 10 SEDs for different viewing angles
    image = m.add_peeled_images(sed=True, image=False)
    image.set_wavelength_range(250, 0.01, 5000.)
    image.set_viewing_angles(np.linspace(0., 90., 10), np.repeat(20., 10))
    image.set_track_origin('basic')

    # Add multi-wavelength image for a single viewing angle
    image = m.add_peeled_images(sed=False, image=True)
    image.set_wavelength_range(30, 1., 1000.)
    image.set_viewing_angles([30.], [20.])
    image.set_image_size(200, 200)
    image.set_image_limits(-1.5 * pc, 1.5 * pc, -1.5 * pc, 1.5 * pc)

    # Add a fly-around at 500 microns
    image = m.add_peeled_images(sed=False, image=True)
    image.set_wavelength_range(1, 499., 501.)
    image.set_viewing_angles(np.repeat(45., 36), np.linspace(5., 355., 36))
    image.set_image_size(200, 200)
    image.set_image_limits(-1.5 * pc, 1.5 * pc, -1.5 * pc, 1.5 * pc)

    # Set runtime parameters
    m.set_n_initial_iterations(5)
    m.set_raytracing(True)
    m.set_n_photons(initial=1e6, imaging=1e7,
                    raytracing_sources=1e6, raytracing_dust=1e6)

    # Write out input file
    m.write('tutorial_model.rtin')

Copy the above script into a file, say ``setup.py``, and download the :download:`kmh_lite.hdf5 <kmh_lite.hdf5>` dust file into the same
directory (**disclaimer**: do not use this dust file outside of these tutorials!), then set up the model with::

    $ python setup.py

This will create a file named ``tutorial_model.rtin``. You can then
run the model either with::

    $ hyperion tutorial_model.rtin tutorial_model.rtout

or if you want to use the parallel version of the code::

    $ hyperion -m 24 tutorial_model.rtin tutorial_model.rtout

In the above case, the model would run on 24 cores, but you can change this to
match the number of cores you can use. This will create a file named
``tutorial_model.rtout``. You are now ready to follow the
:ref:`tutorials-post-processing` tutorials!

.. note:: The model will take a little while to run (~1 hour on one
          core, 5 minutes on 12 cores) since it is computing many
          viewing angles for a fly-around, so if you are impatient, just
          reduce all the photon numbers::

              m.set_n_photons(initial=1e6, imaging=1e7,
                              raytracing_sources=1e6, raytracing_dust=1e6)

          by an order of magnitude::

              m.set_n_photons(initial=1e5, imaging=1e6,
                              raytracing_sources=1e5, raytracing_dust=1e5)

          and it should run much faster.