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

    import fiasco


    quantity_support()





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

 .. code-block:: none


    <astropy.visualization.units.quantity_support.<locals>.MplQuantityConverter object at 0x7ce9e01200b0>



.. GENERATED FROM PYTHON SOURCE LINES 27-29

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

.. GENERATED FROM PYTHON SOURCE LINES 29-34

.. code-block:: Python

    ch = Channel(94*u.angstrom)
    correction_table = get_correction_table("jsoc")
    response = ch.wavelength_response(correction_table=correction_table)
    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:   9%|▉         | 493k/5.43M [00:00<00:01, 4.33MB/s]

    aiapy.aia_V8_all_fullinst.genx:  99%|█████████▉| 5.36M/5.43M [00:00<00:00, 29.0MB/s]

                                                                                        
    Files Downloaded: 100%|██████████| 1/1 [00:00<00:00,  3.73file/s]
    Files Downloaded: 100%|██████████| 1/1 [00:00<00:00,  3.73file/s]




.. GENERATED FROM PYTHON SOURCE LINES 35-36

Plot the wavelength response

.. GENERATED FROM PYTHON SOURCE LINES 36-42

.. 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 43-45

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 45-48

.. code-block:: Python

    temperature = 10.**(np.arange(4.5, 8, 0.1)) * u.K
    fe18 = fiasco.Ion('Fe 18', temperature)








.. GENERATED FROM PYTHON SOURCE LINES 49-56

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 56-61

.. 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)





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

 .. code-block:: none

    WARNING: No rate data available for recombining ion Fe 19. Using single-ion model for Fe 18. [fiasco.ions]
    2026-03-10 17:54:46 - fiasco - WARNING: No rate data available for recombining ion Fe 19. Using single-ion model for Fe 18.




.. GENERATED FROM PYTHON SOURCE LINES 62-63

Get the corresponding transition wavelengths

.. GENERATED FROM PYTHON SOURCE LINES 63-66

.. code-block:: Python

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








.. GENERATED FROM PYTHON SOURCE LINES 67-68

Interpolate the response function to the transition wavelengths

.. GENERATED FROM PYTHON SOURCE LINES 68-71

.. code-block:: Python

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








.. GENERATED FROM PYTHON SOURCE LINES 72-82

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 82-85

.. code-block:: Python

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








.. GENERATED FROM PYTHON SOURCE LINES 86-88

Plot the effective temperature response function for the 94
channel.

.. GENERATED FROM PYTHON SOURCE LINES 88-96

.. 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 97-101

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 5.492 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>`

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

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


.. only:: html

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

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