Getting Started
===============

Installation
------------

To use SNEWPY, first install it using pip:

.. code-block:: console

   $ pip install snewpy


.. _sec-download_models:

Download Supernova Models
-------------------------

SNEWPY includes a large number of supernova models from different simulation groups.
Since these models have a size of several 100 MB, they are not included in the initial install.
Instead, SNEWPY automatically loads these files the first time you use a model. 
Alternatively, you can run the following command to bulk download model files:

.. code-block:: console

   $ python -c 'import snewpy; snewpy.get_models()'

Files are downloaded to a hidden directory given by ``snewpy.model_path``.

.. note::

   The documentation for each model includes more information, including a reference to the corresponding publication
   (e.g. DOI or arXiv identifier). If you use one of these models, please always cite the appropriate reference.


Usage
-----

This example script shows how to use SNEWPY to compare the luminosity of two different supernova models:

.. code-block:: python

   import astropy.units as u
   import matplotlib as mpl
   import matplotlib.pyplot as plt

   import snewpy
   from snewpy.models.ccsn import Nakazato_2013, Bollig_2016
   from snewpy.neutrino import Flavor

   mpl.rc('font', size=16)
   %matplotlib inline

   # Initialise two different models. This automatically downloads the required data files.
   nakazato = Nakazato_2013(progenitor_mass=20*u.solMass, revival_time=100*u.ms, metallicity=0.004, eos='shen')
   bollig = Bollig_2016(progenitor_mass=27*u.solMass)

   # Plot luminosity of both models
   fig, ax = plt.subplots(1, figsize=(10, 6))

   for flavor in Flavor:
       ax.plot(nakazato.time, nakazato.luminosity[flavor]/1e51,  # Report luminosity in units foe/s
               label=flavor.to_tex() + ' (Nakazato)',
               color='C0' if flavor.is_electron else 'C2',
               ls='-' if flavor.is_neutrino else '--',
               lw=2)

   for flavor in Flavor:
       ax.plot(bollig.time, bollig.luminosity[flavor]/1e51,  # Report luminosity in units foe/s
               label=flavor.to_tex() + ' (Bollig)',
               color='C1' if flavor.is_electron else 'C3',
               ls='-' if flavor.is_neutrino else '--',
               lw=1)

   ax.set(xlim=(-0.05, 0.5), xlabel=r'$t-t_{\rm bounce}$ [s]', ylabel=r'luminosity [foe s$^{-1}$]')
   ax.grid()
   ax.legend(loc='upper right', ncol=2, fontsize=18)

This will generate the following figure:

.. image:: luminosity-comparison.*


The SNEWPY repository contains many Jupyter notebooks in ``doc/source/nb/`` with sample code
showing different models or how to apply flavor transformations to the neutrino fluxes.

More advanced usage of SNEWPY requires SNOwGLoBES and is described in the following section.