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

.. only:: html

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

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

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

.. _sphx_glr_gallery_experiment_cylinder_cylinder_coupling_vs_diameter.py:


InfiniteCylinder: Coupling vs Diameter
======================================

This example demonstrates how to compute and visualize the coupling efficiency as a function of diameter for cylindrical scatterers using PyMieSim.

.. GENERATED FROM PYTHON SOURCE LINES 9-10

Importing the package dependencies: numpy, PyMieSim

.. GENERATED FROM PYTHON SOURCE LINES 10-45

.. code-block:: Python

    import numpy as np
    from PyMieSim.units import ureg

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

    source = Gaussian(
        wavelength=[100, 1200] * ureg.nanometer,  # 1200 nm
        polarization=90 * ureg.degree,  # Polarization angle in ureg.degrees
        optical_power=1e-3 * ureg.watt,  # 1 milliureg.watt
        NA=0.2 * ureg.AU,  # Numerical Aperture
    )

    scatterer = InfiniteCylinder(
        diameter=np.linspace(100, 300, 200) * ureg.nanometer,  # Diameters ranging from 100 nm to 3000 nm
        refractive_index=[1.4] * ureg.RIU,  # Material of the cylinder
        medium_refractive_index=1.0 * ureg.RIU,  # Refractive index of the surrounding medium
        source=source,
    )

    detector = Photodiode(
        NA=[0.1] * ureg.AU,  # Numerical Apertures for the detector
        phi_offset=[-180.0] * ureg.degree,  # Phi offset in ureg.degrees
        gamma_offset=[0.0] * ureg.degree,  # Gamma offset in ureg.degrees
        sampling=600 * ureg.AU,  # Number of sampling points
        polarization_filter=None,  # No polarization filter
    )

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

    dataframe = experiment.get("coupling")

    dataframe.plot(x="scatterer:diameter")



.. image-sg:: /gallery/experiment/cylinder/images/sphx_glr_cylinder_coupling_vs_diameter_001.png
   :alt: cylinder coupling vs diameter
   :srcset: /gallery/experiment/cylinder/images/sphx_glr_cylinder_coupling_vs_diameter_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    <Figure size 800x500 with 1 Axes>




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

   **Total running time of the script:** (0 minutes 0.412 seconds)


.. _sphx_glr_download_gallery_experiment_cylinder_cylinder_coupling_vs_diameter.py:

.. only:: html

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

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

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

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

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

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

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


.. only:: html

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

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