.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "user-guide/model-gallery/temporal/plot_gaussian_temporal.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_user-guide_model-gallery_temporal_plot_gaussian_temporal.py>`
        to download the full example code. or to run this example in your browser via Binder

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_user-guide_model-gallery_temporal_plot_gaussian_temporal.py:


.. _gaussian-temporal-model:

Gaussian temporal model
=======================

This model parametrises a gaussian time model.

.. math::
    F(t) = \exp \left( -0.5 \cdot \frac{ (t - t_{\rm{ref}})^2 } { \sigma^2 } \right)

.. GENERATED FROM PYTHON SOURCE LINES 15-18

Example plot
------------
Here is an example plot of the model:

.. GENERATED FROM PYTHON SOURCE LINES 18-36

.. code-block:: Python


    from astropy import units as u
    from astropy.time import Time
    import matplotlib.pyplot as plt
    from gammapy.modeling.models import (
        GaussianTemporalModel,
        Models,
        PowerLawSpectralModel,
        SkyModel,
    )

    sigma = "3 h"
    t_ref = Time("2020-10-01")
    time_range = [t_ref - 0.5 * u.d, t_ref + 0.5 * u.d]
    gaussian_model = GaussianTemporalModel(t_ref=t_ref.mjd * u.d, sigma=sigma)
    gaussian_model.plot(time_range)
    plt.grid(which="both")




.. image-sg:: /user-guide/model-gallery/temporal/images/sphx_glr_plot_gaussian_temporal_001.png
   :alt: plot gaussian temporal
   :srcset: /user-guide/model-gallery/temporal/images/sphx_glr_plot_gaussian_temporal_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 37-40

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

.. GENERATED FROM PYTHON SOURCE LINES 40-49

.. code-block:: Python


    model = SkyModel(
        spectral_model=PowerLawSpectralModel(),
        temporal_model=gaussian_model,
        name="gaussian_model",
    )
    models = Models([model])

    print(models.to_yaml())




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

 .. code-block:: none

    components:
    -   name: gaussian_model
        type: SkyModel
        spectral:
            type: PowerLawSpectralModel
            parameters:
            -   name: index
                value: 2.0
            -   name: amplitude
                value: 1.0e-12
                unit: cm-2 s-1 TeV-1
            -   name: reference
                value: 1.0
                unit: TeV
        temporal:
            type: GaussianTemporalModel
            parameters:
            -   name: t_ref
                value: 59123.0
                unit: d
            -   name: sigma
                value: 3.0
                unit: h
            scale: utc
    metadata:
        creator: Gammapy 1.3
        date: '2024-11-26T10:08:53.275604'
        origin: null






.. _sphx_glr_download_user-guide_model-gallery_temporal_plot_gaussian_temporal.py:

.. only:: html

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

    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/gammapy/gammapy-webpage/v1.3?urlpath=lab/tree/notebooks/1.3/user-guide/model-gallery/temporal/plot_gaussian_temporal.ipynb
        :alt: Launch binder
        :width: 150 px

    .. container:: sphx-glr-download sphx-glr-download-jupyter

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

    .. container:: sphx-glr-download sphx-glr-download-python

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

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_gaussian_temporal.zip <plot_gaussian_temporal.zip>`


.. only:: html

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

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