PyMieSim is a very easy to install/use tool for extensive Mie scattering analysis. It allows to study the light scattering on different kind of objects (scatterer) though at the moment, only spherical scatterers are implemented. Using this package, one can easily set a Source a Scatterer and a Detector within a very wide range of parameters such as:
Source structure (e.g. plane wave or Gaussian focused)
Scatterer refractive index
Medium refractive index
Detector type (photodiode or LPMode)
Detector numerical aperture
Detector angle offset in polarization parallel axis (\(\phi\))
Detector angle offset in polarization perpendicular axis (\(\theta\))
Detector coupling mode (Mean coupling or centered coupling)
The package also lets you construct an Experiment using ScattererSet, SourceSet and DetectorSet. Those class define the type of scatterers, light sources and detectors you want to study.
All the latest available documentation is available here or you can click the following badge:
It’s 2021, you don’t need to run all your code on you computer anymore. Google Colab is a platform which allows to write/use python scripts remotely. You can open the PyMieSim.ipynb in the file to access it or click on the following “Open in Colab” badge:
To run the Unit-tests, one need the coverage library.
python -m unittest tests/Unittest.py
Here is an example on how to use the library.
from PyMieSim.Source import PlaneWave from PyMieSim.Detector import LPmode from PyMieSim.Scatterer import Sphere Source = PlaneWave(Wavelength = 450e-9, Polarization = 0, E0 = 1) Detector = LPmode(Mode = (0, 1), Rotation = 0., Sampling = 201, NA = 0.2, GammaOffset = 0, PhiOffset = 0, CouplingMode = 'Centered') Scat = Sphere(Diameter = 300e-9, Source = Source, Index = 1.4) Coupling = Detector.Coupling(Scatterer = Scat) print(Coupling) # output: 1.66e+02 nWatt
For more examples, I invite you to check the examples section of the documentation.
A large set of examples are avaialble in the test/Examples folder. You can also see them in the examples section of the documentation
Adding dumb-proof assertions
Adding Stokes parameter representations [DONE]
Multiprocess Experiment class
Adding more unittests
Adding monotonic metric to optimizer class [DONE]
Comments on c++ codes
Multiclass c++ codes
verify if changes of NA for <LPmode> class can be simplified [DONE]
adding travis and codecov [DONE]
adding material Sellmeier boundary
Citing this work?¶
(Is this the new “like, comment and share” ?)
I have worked out a Dockerfile (see the PyMieSim Git) to install all the necessaries library.
I you prefer to directly install in your computer the files you can do the following
Submodules install If you want to clone this repository do not forget to init and update the submodules.
>>> git submodules init >>> git submodules update
Fortran wrapper Be sure to have a fortran compiler installed such as “gfortran”.
>>> sudo apt-get install gfortran
You have to compile and install the code yourself. You can either follow the instruction as showed here or do the following:
>>> cd extern/complex_bessel && cmake . && make install
C++ wrapper You now need to compile the c++ code for your specific python version. If no prefered version leave DVERSION blank.
>>> cmake . -DVERSION=3.8 >>> make all