Visualizing physical quantities for regular 3-d grids ===================================================== As described in :doc:`../postprocessing/extracting_quantities`, it is easy to extract quantities such as density, specific_energy, and temperature from the output model files. In this tutorial, we see how to visualize this information efficiently. Cartesian grid example ---------------------- We first set up a model of a box containing 100 sources heating up dust: .. literalinclude:: scripts/quantity_cartesian_setup.py :language: python .. note:: If you want to run this model you will need to download the :download:`kmh_lite.hdf5 ` dust file into the same directory as the script above (**disclaimer**: do not use this dust file outside of these tutorials!). We can then use the ``get_quantities`` method described above to produce a density-weighted temperature map collapsed in the z direction: .. literalinclude:: scripts/quantity_cartesian_viz.py :language: python :end-before: # show image .. image:: scripts/weighted_temperature_cartesian.png Of course, we can also plot individual slices: .. literalinclude:: scripts/quantity_cartesian_viz.py :language: python :start-after: # show image .. image:: scripts/sliced_temperature_cartesian.png Spherical polar grid example ---------------------------- Polar grids are another interest case, because one might want to plot the result in polar or cartesian coordinates. To demonstrate this, we set up a simple example with a star surrounded by a flared disk: .. literalinclude:: scripts/quantity_spherical_setup.py :language: python .. note:: If you want to run this model you will need to download the :download:`kmh_lite.hdf5 ` dust file into the same directory as the script above (**disclaimer**: do not use this dust file outside of these tutorials!). Making a plot of temperature in (r, theta) space is similar to before: .. literalinclude:: scripts/quantity_spherical_viz.py :language: python :end-before: # show image .. image:: scripts/temperature_spherical_rt.png Making a plot in spherical coordinates instead is in fact also straightforward: .. literalinclude:: scripts/quantity_spherical_viz.py :language: python :start-after: # show image .. image:: scripts/temperature_spherical_xz.png :width: 800px