Date: Dec 22, 2024, Version: 3.1.1.1

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PyMieSim#

PyMieSim is a Python library designed to provide a robust and flexible framework for performing Mie scattering simulations. The software is easy to install and operate, making it accessible to both new users and experienced researchers. PyMieSim enables users to explore the scattering properties of particles under various configurations, and is tailored for investigating single scattering events, as well as conducting large-scale parametric experiments.

At its core, PyMieSim includes three solvers optimized for different types of scatterers:

Spherical particles
Infinite cylindrical particles
Core-shell spherical particles

The software also allows the user to customize the light source and detector attributes, depending on the specific simulation needs. The package is modular and provides an intuitive interface for users to model complex scattering scenarios with minimal effort.

Main Submodules#

PyMieSim is organized into two primary submodules:

single: Focused on analyzing individual scattering events, such as: - Far-field distributions - Scattering phase functions - Stokes parameters
experiment: Designed for exploring how scattering parameters, such as Qsca, Qext, g, and coupling (power), behave over large datasets, incorporating variations in sources, scatterers, and detectors.

Both submodules work seamlessly together, making PyMieSim adaptable for a wide range of scattering simulations.

Getting Started#

To use PyMieSim in Python, simply install the package and begin incorporating it into your scripts.

Installation#

PyMieSim supports Windows, Linux, macOS (including Apple M1/M2 chips), and ARM architectures. To install the package, use pip:

pip install PyMieSim (using pip package manager)

conda install PyMieSim (using conda environment manager)

For more details, visit the documentation for a comprehensive guide on how to use the package.

Example Code#

Here is an example of how to use PyMieSim for a simple Mie scattering simulation. This example demonstrates how to configure a light source, scatterer, and detector, and retrieve the scattering data:

import numpy as np

from PyMieSim.experiment.scatterer import Sphere
from PyMieSim.experiment.source import Gaussian
from PyMieSim.experiment import Setup
from PyMieSim.units import nanometer, degree, watt, AU, RIU

source = Gaussian(
    wavelength=np.linspace(400, 1000, 500) * nanometer,
    polarization=0 * degree,
    optical_power=1e-3 * watt,
    NA=0.2 * AU
)

scatterer = Sphere(
    diameter=[200] * nanometer,
    property=[4] * RIU,
    medium_property=1 * RIU,
    source=source
)

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

dataframe = experiment.get('Qsca')

dataframe.plot_data(x="source:wavelength")

It produces the following figure which is equivalent to the one found on wikipedia.

This is just one example of PyMieSim in action. You can find more examples in the examples section of the documentation.

Examples#

Here are a few more examples showcasing the capabilities of PyMieSim:

Example 1: Plasmonic Resonances for CoreShell Particles#

Example 2: Scattering Efficiency vs Diameter for Spherical Particles#

Manual Building#

If you prefer or need to build the project manually (e.g., for Apple silicon devices), ensure you have a C++ compiler (such as gcc) and Fortran installed, as well as Python 3.7+.

Build Instructions#

Linux/MacOS#

git clone https://github.com/MartinPdeS/PyMieSim.git
cd PyMieSim
git submodule init && git submodule update
mkdir build
cd build
cmake ../ -G"Unix Makefiles"
sudo make install
cd ..
python -m pip install .

For Windows, use MinGW Makefiles instead of Unix Makefiles when invoking CMake.

Testing#

You can test the local version of PyMieSim by running the following commands:

git clone https://github.com/MartinPdeS/PyMieSim.git
cd PyMieSim
pip install PyMieSim[testing]
pytest

This will run the suite of unit tests and provide coverage details.

Google Colab#

In 2024, running code on your local machine is optional! You can leverage the power of Google Colab to run PyMieSim remotely. Use the provided Colab notebook for an interactive experience.

Citing PyMieSim#

If PyMieSim contributes to your research, we kindly ask that you cite the following paper:

@article{PoinsinetdeSivry-Houle:23,
    author = {Martin Poinsinet de Sivry-Houle and Nicolas Godbout and Caroline Boudoux},
    journal = {Opt. Continuum},
    title = {PyMieSim: an open-source library for fast and flexible far-field Mie scattering simulations},
    volume = {2},
    number = {3},
    pages = {520--534},
    year = {2023},
    doi = {10.1364/OPTCON.473102},
}

You can access the full article here

Experimental Graphical User Interface (GUI)#

Since version 1.7.0, PyMieSim offers an experimental GUI for users who prefer a graphical approach to simulations. While still under development, the GUI can be installed and accessed as follows:

pip install PyMieSim
python -m  PyMieSim

The GUI is not yet as robust as the core Python API, but it provides a simplified interface for generating simulations.

Contact Information#

PyMieSim is actively developed and maintained by Martin Poinsinet de Sivry-Houle. If you’re interested in contributing or have questions, feel free to reach out.

Email: martin.poinsinet.de.sivry@gmail.ca

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