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

.. only:: html

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

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

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

.. _sphx_glr_gallery_extras_coupling_heatmap.py:


Coupling heatmap of a sphere
=================================

PyMieSim makes it easy to create a source and a scatterer. With these objects
defined, it is possible to use PyMieSim to find the scattering efficiency of the
scatterer. This feature can be used to plot a graph of the scattering efficiency
of a sphere as a function of the permittivity and the size parameter.

.. GENERATED FROM PYTHON SOURCE LINES 10-61



.. image-sg:: /gallery/extras/images/sphx_glr_coupling_heatmap_001.png
   :alt: Coupling power [Watt]
   :srcset: /gallery/extras/images/sphx_glr_coupling_heatmap_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    import numpy
    from TypedUnit import ureg
    import matplotlib.pyplot as plt

    from PyMieSim.experiment.detector import Photodiode
    from PyMieSim.experiment.scatterer import Sphere
    from PyMieSim.experiment.source import Gaussian
    from PyMieSim.experiment import Setup


    index = numpy.linspace(1.3, 2.1, 100) * ureg.RIU

    diameter = numpy.linspace(1, 2000, 100) * ureg.nanometer

    source = Gaussian(
        wavelength=400 * ureg.nanometer,
        polarization=90 * ureg.degree,
        optical_power=1e-3 * ureg.watt,
        NA=0.2 * ureg.AU,
    )


    scatterer = Sphere(
        diameter=diameter, property=index, medium_property=1 * ureg.RIU, source=source
    )


    detector = Photodiode(
        polarization_filter=0 * ureg.degree,
        NA=0.3 * ureg.RIU,
        phi_offset=0 * ureg.degree,
        gamma_offset=0 * ureg.degree,
        sampling=400 * ureg.AU,
    )

    experiment = Setup(scatterer=scatterer, source=source, detector=detector)

    dataframe = experiment.get("coupling", add_units=False)

    values = dataframe.values.reshape([diameter.size, index.size])

    figure, ax = plt.subplots(1, 1)

    image = ax.pcolormesh(index, diameter * 1e6, values, shading="auto")
    ax.set(
        xlabel="Permittivity", ylabel=r"Diameter [$\mu$m]", title="Coupling power [Watt]"
    )
    plt.colorbar(mappable=image)

    plt.show()


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

   **Total running time of the script:** (0 minutes 2.010 seconds)


.. _sphx_glr_download_gallery_extras_coupling_heatmap.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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