.. 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 ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_gallery_experiment_cylinder_cylinder_coupling_vs_diameter.py: Cylinder: 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 10-18 .. code-block:: Python import numpy as np from TypedUnit import ureg from PyMieSim.experiment.detector import Photodiode from PyMieSim.experiment.scatterer import Sphere from PyMieSim.experiment.source import Gaussian from PyMieSim.experiment import Setup .. GENERATED FROM PYTHON SOURCE LINES 19-20 Defining the source .. GENERATED FROM PYTHON SOURCE LINES 20-27 .. code-block:: Python 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 ) .. GENERATED FROM PYTHON SOURCE LINES 28-29 Defining the scatterer distribution .. GENERATED FROM PYTHON SOURCE LINES 29-37 .. code-block:: Python scatterer = Sphere( diameter=np.linspace(100, 300, 200) * ureg.nanometer, # Diameters ranging from 100 nm to 3000 nm property=[1.4] * ureg.RIU, # Material of the cylinder medium_property=1.0 * ureg.RIU, # Refractive index of the surrounding medium source=source, ) .. GENERATED FROM PYTHON SOURCE LINES 38-39 Defining the detector .. GENERATED FROM PYTHON SOURCE LINES 39-47 .. code-block:: Python 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 ) .. GENERATED FROM PYTHON SOURCE LINES 48-49 Setting up the experiment .. GENERATED FROM PYTHON SOURCE LINES 49-51 .. code-block:: Python experiment = Setup(scatterer=scatterer, source=source, detector=detector) .. GENERATED FROM PYTHON SOURCE LINES 52-53 Measuring the coupling efficiency .. GENERATED FROM PYTHON SOURCE LINES 53-55 .. code-block:: Python dataframe = experiment.get("coupling") .. GENERATED FROM PYTHON SOURCE LINES 56-58 Plotting the results Visualizing how the coupling efficiency varies with the cylinder diameter. .. GENERATED FROM PYTHON SOURCE LINES 58-59 .. code-block:: Python 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
.. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.333 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 ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: cylinder_coupling_vs_diameter.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: cylinder_coupling_vs_diameter.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_