.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "gallery/validation/pymiescatt/sphere_1.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_gallery_validation_pymiescatt_sphere_1.py>`
        to download the full example code.

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

.. _sphx_glr_gallery_validation_pymiescatt_sphere_1.py:


Sphere Particles: 1
===================

.. GENERATED FROM PYTHON SOURCE LINES 6-72



.. image-sg:: /gallery/validation/pymiescatt/images/sphx_glr_sphere_1_001.png
   :alt: Scattering Efficiency Comparison for Sphere Particles
   :srcset: /gallery/validation/pymiescatt/images/sphx_glr_sphere_1_001.png
   :class: sphx-glr-single-img





.. code-block:: Python


    # Standard library imports
    import numpy as np
    import pandas as pd
    import matplotlib.pyplot as plt

    # PyMieSim imports
    from PyMieSim.experiment.scatterer import Sphere
    from PyMieSim.experiment.source import Gaussian
    from PyMieSim.experiment import Setup
    from PyMieSim.units import degree, watt, AU, RIU, nanometer
    from PyMieSim.directories import validation_data_path
    from MPSPlots.styles import mps


    # Define parameters
    wavelength = 632.8 * nanometer  # Wavelength of the source in meters
    index = (1.4 + 0.2j) * RIU  # Refractive index of the sphere
    medium_index = 1.2 * RIU  # Refractive index of the medium
    optical_power = 1 * watt  # Power of the light source in watts
    NA = 0.2 * AU  # Numerical aperture
    diameters = np.geomspace(10, 6_000, 800) * nanometer  # Diameters from 10 nm to 6 μm

    # Configure the Gaussian source
    source = Gaussian(
        wavelength=wavelength,
        polarization=0 * degree,
        optical_power=optical_power,
        NA=NA
    )

    # Setup spherical scatterer
    scatterer = Sphere(
        diameter=diameters,
        property=index,
        medium_property=medium_index,
        source=source
    )

    # Create experimental setup
    experiment = Setup(scatterer=scatterer, source=source)

    comparison_measures = ['Qsca', 'Qext', 'Qabs', 'g', 'Qpr', 'Qback']

    # Compute PyMieSim scattering efficiency data
    pymiesim_dataframe = experiment.get(*comparison_measures).pint.dequantify().reset_index().pint.quantify()

    pymiescatt_dataframe = pd.read_csv(validation_data_path / 'pymiescatt/example_shpere_1.csv')

    # Plot results
    with plt.style.context(mps):
        figure, ax = plt.subplots(1, 1)


    pymiescatt_dataframe.diameter *= 1e9

    pymiescatt_dataframe.plot(x='diameter', y=comparison_measures, ax=ax, linewidth=3)
    pymiesim_dataframe.plot(x='scatterer:diameter', ax=ax, color='black', linestyle='--', linewidth=1.5)

    ax.set(
        xlabel=r'Diameter [$\mu$m]',
        ylabel='Scattering Efficiency',
        title='Scattering Efficiency Comparison for Sphere Particles'
    )
    plt.legend()
    plt.show()


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

   **Total running time of the script:** (0 minutes 0.782 seconds)


.. _sphx_glr_download_gallery_validation_pymiescatt_sphere_1.py:

.. only:: html

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

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

      :download:`Download Jupyter notebook: sphere_1.ipynb <sphere_1.ipynb>`

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

      :download:`Download Python source code: sphere_1.py <sphere_1.py>`

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

      :download:`Download zipped: sphere_1.zip <sphere_1.zip>`


.. only:: html

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

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