.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "generated/gallery/user_guide/aia_response.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_generated_gallery_user_guide_aia_response.py>`
        to download the full example code.

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

.. _sphx_glr_generated_gallery_user_guide_aia_response.py:


Understanding AIA temperature response with `aiapy`
===================================================

In this example, we will use the `~aiapy` package to convolve
the Fe XVIII contribution function with the instrument response
function to understand the temperature sensitivity of the 94
angstrom channel.

.. GENERATED FROM PYTHON SOURCE LINES 10-25

.. code-block:: Python

    import astropy.constants as const
    import astropy.units as u
    import matplotlib.pyplot as plt
    import numpy as np

    from aiapy.response import Channel
    from astropy.visualization import quantity_support
    from scipy.interpolate import interp1d

    import fiasco

    # sphinx_gallery_thumbnail_number = 2

    quantity_support()





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

 .. code-block:: none


    <astropy.visualization.units.quantity_support.<locals>.MplQuantityConverter object at 0x7fc37ff3e850>



.. GENERATED FROM PYTHON SOURCE LINES 26-28

First, create the `~aiapy.response.Channel` object for the
94 angstrom channel and compute the wavelength response.

.. GENERATED FROM PYTHON SOURCE LINES 28-31

.. code-block:: Python

    ch = Channel(94*u.angstrom)
    response = ch.wavelength_response() * ch.plate_scale





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

 .. code-block:: none


    Files Downloaded:   0%|          | 0/1 [00:00<?, ?file/s]

    aiapy.aia_V8_all_fullinst.genx:   0%|          | 0.00/5.43M [00:00<?, ?B/s]

    aiapy.aia_V8_all_fullinst.genx:  32%|███▏      | 1.74M/5.43M [00:00<00:00, 17.4MB/s]

                                                                                        
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.. GENERATED FROM PYTHON SOURCE LINES 32-33

Plot the wavelength response

.. GENERATED FROM PYTHON SOURCE LINES 33-39

.. code-block:: Python

    plt.plot(ch.wavelength, response)
    plt.xlim(ch.channel + [-4, 4]*u.angstrom)
    plt.axvline(x=ch.channel, ls='--', color='k')
    plt.title(f'{ch.channel.to_string(format="latex")} Wavelength Response')
    plt.show()




.. image-sg:: /generated/gallery/user_guide/images/sphx_glr_aia_response_001.png
   :alt: $94 \; \mathrm{\mathring{A}}$ Wavelength Response
   :srcset: /generated/gallery/user_guide/images/sphx_glr_aia_response_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 40-42

Next, we construct for the `~fiasco.Ion` object for Fe 18. Note
that by default we use the coronal abundances of :cite:t:`feldman_potential_1992`.

.. GENERATED FROM PYTHON SOURCE LINES 42-45

.. code-block:: Python

    temperature = 10.**(np.arange(4.5, 8, 0.05)) * u.K
    fe18 = fiasco.Ion('Fe 18', temperature)








.. GENERATED FROM PYTHON SOURCE LINES 46-53

Compute the contribution function,

.. math:: G(n,T,\lambda) = \mathrm{Ab}\frac{hc}{\lambda}N_{\lambda}A_{\lambda}f\frac{1}{n}

for each transition of Fe 18 at constant pressure of :math:`10^{15}`
K :math:`\mathrm{cm}^{-3}`. Note that we use the ``couple_density_to_temperature``
keyword such that temperature and density vary along the same axis.

.. GENERATED FROM PYTHON SOURCE LINES 53-58

.. code-block:: Python

    constant_pressure = 1e15 * u.K * u.cm**(-3)
    density = constant_pressure / fe18.temperature
    g = fe18.contribution_function(density, include_protons=False,
                                   couple_density_to_temperature=True)








.. GENERATED FROM PYTHON SOURCE LINES 59-60

Get the corresponding transition wavelengths

.. GENERATED FROM PYTHON SOURCE LINES 60-63

.. code-block:: Python

    transitions = fe18.transitions.wavelength[~fe18.transitions.is_twophoton]
    energy = const.h * const.c / transitions / u.photon








.. GENERATED FROM PYTHON SOURCE LINES 64-65

Interpolate the response function to the transition wavelengths

.. GENERATED FROM PYTHON SOURCE LINES 65-68

.. code-block:: Python

    f = interp1d(ch.wavelength, response, fill_value='extrapolate')
    response_transitions = f(transitions) * response.unit








.. GENERATED FROM PYTHON SOURCE LINES 69-79

In order to compute the temperature response function :math:`K_c`, we
integrate the wavelength response function :math:`R_c`, weighted by the
contribution function :math:`G(\lambda,T)`, over wavelength,

.. math:: K_c(T) = \int_0^{\infty}\mathrm{d}\lambda\,G(\lambda,T)R_c(\lambda)

We divide by :math:`hc/\lambda` in order to
convert from units of energy to photons.
For more more information on the AIA wavelength response calculation,
see :cite:t:`boerner_initial_2012`.

.. GENERATED FROM PYTHON SOURCE LINES 79-82

.. code-block:: Python

    K = (g / energy * response_transitions).sum(axis=2) / (4*np.pi*u.steradian)
    K = K.squeeze().to('cm5 ct pix-1 s-1')








.. GENERATED FROM PYTHON SOURCE LINES 83-85

Plot the effective temperature response function for the 94
channel.

.. GENERATED FROM PYTHON SOURCE LINES 85-93

.. code-block:: Python

    plt.plot(temperature, K)
    plt.xscale('log')
    plt.yscale('log')
    plt.ylim(1e-29, 1e-26)
    plt.xlim(1e5, 3e7)
    plt.title(f'{ch.channel.to_string(format="latex")} Response for {fe18.ion_name_roman}')
    plt.show()




.. image-sg:: /generated/gallery/user_guide/images/sphx_glr_aia_response_002.png
   :alt: $94 \; \mathrm{\mathring{A}}$ Response for Fe XVIII
   :srcset: /generated/gallery/user_guide/images/sphx_glr_aia_response_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 94-98

Note that this represents only the contribution of Fe 18 to the 94
angstrom bandpass. In order to construct the full
response functions, one would need to repeat this procedure for every
ion listed in the CHIANTI atomic database and for all AIA channels.


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 9.978 seconds)


.. _sphx_glr_download_generated_gallery_user_guide_aia_response.py:

.. only:: html

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

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

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

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

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


.. only:: html

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

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