.. note::
    :class: sphx-glr-download-link-note

    Click :ref:`here <sphx_glr_download_modeling_gallery_spectral_plot_naima.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_modeling_gallery_spectral_plot_naima.py:


.. _naima-spectral-model:

Naima Spectral Model
=======================

This class provides an interface with the models defined in the naima models module.

The model accepts as a positional argument a `Naima <https://naima.readthedocs.io/en/latest/>`_
radiative `~naima.models` instance, used to compute the non-thermal emission from populations of
relativistic electrons or protons due to interactions with the ISM or with radiation and magnetic fields.

One of the advantages provided by this class consists in the possibility of performing a maximum
likelihood spectral fit of the model's parameters directly on observations, as opposed to the MCMC
`fit to flux points <https://naima.readthedocs.io/en/latest/mcmc.html>`_ featured in
Naima. All the parameters defining the parent population of charged particles are stored as
`~gammapy.modeling.Parameter` and left free by default. In case that the radiative model is
`~naima.radiative.Synchrotron`, the magnetic field strength may also be fitted. Parameters can be
freezed/unfreezed before the fit, and maximum/minimum values can be set to limit the parameters space to
the physically interesting region.

Example plot
------------
Here we create and plot a spectral model that convolves an `~gammapy.modeling.models.ExpCutoffPowerLawSpectralModel`
electron distribution with an `InverseCompton` radiative model, in the presence of multiple seed photon fields.


.. code-block:: default


    from astropy import units as u
    import matplotlib.pyplot as plt
    import naima
    from gammapy.modeling.models import Models, NaimaSpectralModel, SkyModel

    particle_distribution = naima.models.ExponentialCutoffPowerLaw(
        1e30 / u.eV, 10 * u.TeV, 3.0, 30 * u.TeV
    )
    radiative_model = naima.radiative.InverseCompton(
        particle_distribution,
        seed_photon_fields=["CMB", ["FIR", 26.5 * u.K, 0.415 * u.eV / u.cm ** 3]],
        Eemin=100 * u.GeV,
    )

    model = NaimaSpectralModel(radiative_model, distance=1.5 * u.kpc)

    opts = {
        "energy_range": [10 * u.GeV, 80 * u.TeV],
        "energy_power": 2,
        "flux_unit": "erg-1 cm-2 s-1",
    }

    # Plot the total inverse Compton emission
    model.plot(label="IC (total)", **opts)

    # Plot the separate contributions from each seed photon field
    for seed, ls in zip(["CMB", "FIR"], ["-", "--"]):
        model = NaimaSpectralModel(radiative_model, seed=seed, distance=1.5 * u.kpc)
        model.plot(label=f"IC ({seed})", ls=ls, color="gray", **opts)

    plt.legend(loc="best")
    plt.grid(which="both")




.. image:: /modeling/gallery/spectral/images/sphx_glr_plot_naima_001.png
    :class: sphx-glr-single-img





YAML representation
-------------------
Here is an example YAML file using the model:


.. code-block:: default


    model = SkyModel(spectral_model=model, name="naima-model")
    models = Models([model])

    print(models.to_yaml())




.. rst-class:: sphx-glr-script-out

 Out:

 .. code-block:: none

    components:
    -   name: naima-model
        type: SkyModel
        spectral:
            type: NaimaSpectralModel
            parameters:
            - {name: amplitude, value: 1.0e+30, unit: eV-1, min: .nan, max: .nan, frozen: false}
            - {name: e_0, value: 10.0, unit: TeV, min: .nan, max: .nan, frozen: false}
            - {name: alpha, value: 3.0, unit: '', min: .nan, max: .nan, frozen: false}
            - {name: e_cutoff, value: 30.0, unit: TeV, min: .nan, max: .nan, frozen: false}
            - {name: beta, value: 1.0, unit: '', min: .nan, max: .nan, frozen: false}






.. _sphx_glr_download_modeling_gallery_spectral_plot_naima.py:


.. only :: html

 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-example



  .. container:: sphx-glr-download

     :download:`Download Python source code: plot_naima.py <plot_naima.py>`



  .. container:: sphx-glr-download

     :download:`Download Jupyter notebook: plot_naima.ipynb <plot_naima.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_