Skip to main content

PyMieSim logo

Badge

Status

Python versions

Python

Documentation

Documentation Status

Scientific article

Scientific article

Continuous integration

Unittest Status

Test coverage

Unittest coverage

Google Colab

Google Colab

PyPI package

PyPI version

PyPI downloads

PyPI downloads

Anaconda package

Anaconda version

Anaconda downloads

Anaconda downloads

Latest Anaconda release

Latest release date

PyMieSim

PyMieSim is an open-source Python package for fast and flexible Mie scattering simulations. It supports spherical, cylindrical and core–shell particles and provides helper classes for custom sources and detectors. The project targets both quick single-scatterer studies and large parametric experiments.

Try the live webapp

Run Mie scattering simulations in your browser—no installation required.

Launch the PyMieSimX webapp in your browser

Launch the PyMieSimX webapp to configure optical setups, run parameter sweeps, explore individual particles, and download your results as CSV files. The hosted service brings PyMieSim to a graphical interface, making it easy to try simulations before installing the Python package. The interface is developed in PyMieSimX.

Features

  • Solvers for spheres, cylinders and core–shell geometries.

  • Built-in models for plane wave and Gaussian sources.

  • Multiple detector types including photodiodes and coherent modes.

  • Simple data analysis with pandas DataFrame outputs.

Installation

PyMieSim is available on PyPI and Anaconda. Install it with:

pip install PyMieSim
conda install PyMieSim  --channels MartinPdeS

This installs a pre-built wheel when one is available for your operating system, architecture, and Python version. Wheels are the recommended option for using PyMieSim because they include the compiled C++ and Fortran extensions.

Verify the installation with the same Python interpreter that you will use for your simulations:

python -c "import PyMieSim; print(PyMieSim.__version__)"

Named optical materials use PyOptik’s provenance-preserving RefractiveIndex.INFO catalog. Initialize its local snapshot once before using constructors such as SellmeierMaterial("BK7") or TabulatedMaterial("silver"):

python -m PyOptik setup

Building from source is intended for development or platforms without a matching wheel. It requires a C++20 compiler, Fortran, CMake, pybind11, and OpenMP; see troubleshooting if the compiled extension cannot be imported.

First simulation

Create a source, a scatterer, and a Simulation. Physical quantities use the built-in ureg unit registry, while refractive indices are dimensionless real or complex values.

from PyMieSim import (
    Gaussian,
    PolarizationState,
    Simulation,
    Sphere,
    ureg,
)

source = Gaussian(
    wavelength=633 * ureg.nanometer,
    polarization=PolarizationState(angle=0 * ureg.degree),
    optical_power=1e-3 * ureg.watt,
    numerical_aperture=0.2,
)

scatterer = Sphere(
    diameter=200 * ureg.nanometer,
    material=1.5 + 0.01j,
    medium=1.0,
)

simulation = Simulation(scatterer=scatterer, source=source)
qsca = simulation.run("Qsca")
print(qsca)

This prints a dimensionless scattering efficiency, approximately:

0.2080989068292113 dimensionless

Inspect the measures supported by the configured simulation with:

print(simulation.available_measures)

For explicit measure and unit metadata, request a typed result:

result = simulation.run("Qsca", as_result=True)
print(result.measure, result.quantity, result.units)

Units and material conventions

Always attach units to wavelengths, lengths, powers, and angles:

633 * ureg.nanometer
200 * ureg.nanometer
1e-3 * ureg.watt
0 * ureg.degree

Refractive indices are dimensionless. A complex index such as 1.5 + 0.01j represents an absorbing material under PyMieSim’s optical convention. Built-in and tabulated materials have supported wavelength ranges; use load_material and validate_wavelength when working with real material data.

Parameter sweeps

Use Experiment when you want to evaluate several wavelengths, particle sizes, or material parameters. Results retain named dimensions and coordinates, and can be converted to NumPy or pandas explicitly.

import numpy as np
from PyMieSim import (
    Experiment,
    GaussianSet,
    PolarizationSet,
    SphereSet,
    ureg,
)

source = GaussianSet(
    wavelength=np.linspace(500, 700, 5) * ureg.nanometer,
    polarization=PolarizationSet(angles=0 * ureg.degree),
    optical_power=1e-3 * ureg.watt,
    numerical_aperture=0.2,
)
scatterer = SphereSet(
    diameter=np.linspace(100, 500, 9) * ureg.nanometer,
    material=1.5,
    medium=1.0,
)

experiment = Experiment(scatterer_set=scatterer, source_set=source)
result = experiment.get("Qsca")
values = result.as_numpy()
dataframe = result.as_dataframe()

The experiment grid has five wavelength values and nine diameter values, so values.shape is (5, 9). See the parameter sweep guide for multiple measures and plotting.

Detector coupling

Add a detector when you need collected or coupled power rather than only a scatterer property:

from PyMieSim import (
    Gaussian,
    Photodiode,
    PolarizationState,
    Simulation,
    Sphere,
    ureg,
)

single_source = Gaussian(
    wavelength=633 * ureg.nanometer,
    polarization=PolarizationState(angle=0 * ureg.degree),
    optical_power=1e-3 * ureg.watt,
    numerical_aperture=0.2,
)
single_scatterer = Sphere(
    diameter=200 * ureg.nanometer,
    material=1.5 + 0.01j,
    medium=1.0,
)

detector = Photodiode(
    sampling=500,
    numerical_aperture=0.2,
    phi_offset=0 * ureg.degree,
    gamma_offset=0 * ureg.degree,
    medium=1.0,
)
simulation = Simulation(
    scatterer=single_scatterer,
    source=single_source,
    detector=detector,
)
coupling = simulation.run("coupling")
print(coupling)

coupling requires a detector. Other available detector types include CoherentMode and IntegratingSphere; see the detector coupling guide.

Common issues

  • If import PyMieSim fails, run python -m pip show PyMieSim and check that it uses the same Python executable as your script.

  • If a constructor reports a unit error, check that every dimensional input has units and convert it with .to(...) when necessary.

  • If coupling is unavailable, add a detector and inspect simulation.available_measures.

  • For slow or memory-heavy sweeps, print experiment.array_shape and experiment.total_iterations before requesting a result.

  • On servers or in CI, select a non-interactive Matplotlib backend such as Agg before importing plotting code.

See the online documentation for theory, performance guidance, runnable examples, and advanced near-field and far-field workflows.

Scattering efficiency of a 200 nm sphere with refractive index 4.0.

Code structure

Here is the architecture for a standard workflow using PyMieSim:

Code structure of a standard workflow using PyMieSim.

Developer setup

Clone the repository, select the Python interpreter you want to use, install the development and testing dependencies, and build an editable installation:

git clone https://github.com/MartinPdeS/PyMieSim.git
cd PyMieSim
python -m pip install ".[testing,documentation,dev]"
python -m PyOptik setup --no-progress
make PYTHON=python editable

make editable builds the native extensions in the local build directory and installs them into the same environment. Always run tests with that same interpreter:

python -c "import PyMieSim; print(PyMieSim.__version__)"
python -m pytest --config-file=pytest.ini

If the import reports missing native extensions, the build was not completed for this interpreter. Re-run make editable after checking that CMake, Fortran, pybind11, and OpenMP are installed. Do not mix build artifacts from different Python versions or architectures.

Building from source manually

The equivalent lower-level workflow is:

python -m pip install --no-build-isolation -Cbuild-dir=build -e .

The editable workflow is preferred because it keeps the Python sources and compiled extensions aligned. A released wheel does not require a compiler or the native build toolchain.

Testing

After the developer setup, run the unit tests with:

python -m pytest --config-file=pytest.ini

Citing PyMieSim

If you use PyMieSim in academic work, please cite:

@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},
}

Contact

For questions or contributions, contact martin.poinsinet.de.sivry@gmail.com.

Metadata

Release files for PyMieSim 6.0.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for PyMieSim 6.0.4
File
pymiesim-6.0.4-cp314-cp314-win_amd64.whl CPython 3.14 CPython 3.14 Windows x86-64 Details
pymiesim-6.0.4-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.14 CPython 3.14 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
pymiesim-6.0.4-cp314-cp314-macosx_26_0_arm64.whl CPython 3.14 CPython 3.14 macOS 26.0+ ARM64 Details
pymiesim-6.0.4-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
pymiesim-6.0.4-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ x86-64, Linux glibc 2.27+ x86-64 Details
pymiesim-6.0.4-cp313-cp313-macosx_26_0_arm64.whl CPython 3.13 CPython 3.13 macOS 26.0+ ARM64 Details
pymiesim-6.0.4-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
pymiesim-6.0.4-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
pymiesim-6.0.4-cp312-cp312-macosx_26_0_arm64.whl CPython 3.12 CPython 3.12 macOS 26.0+ ARM64 Details
pymiesim-6.0.4-cp311-cp311-win_amd64.whl CPython 3.11 CPython 3.11 Windows x86-64 Details
pymiesim-6.0.4-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.27+ x86-64, Linux glibc 2.28+ x86-64 Details
pymiesim-6.0.4-cp311-cp311-macosx_26_0_arm64.whl CPython 3.11 CPython 3.11 macOS 26.0+ ARM64 Details

Total release size: 98.3 MB

Release files / pymiesim-6.0.4-cp314-cp314-win_amd64.whl

Download URL pymiesim-6.0.4-cp314-cp314-win_amd64.whl
Size 14.2 MB
Tags CPython 3.14 Windows x86-64
SHA-256 checksum
How to use checksums
fff1e886cdf91cbb335511e53cdb6eb49180f254f961dce698391bf2b2cf7649
BLAKE2b-256 checksum
How to use checksums
eba674a32325c13bd94781051d2278a4ea7d8c304644eb3580b83a2ba54670fb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl

Download URL pymiesim-6.0.4-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Size 6.0 MB
Tags CPython 3.14 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
9e3d12e3dd0ae3ae41b05a43dc08b19b1ec99397905f4042c64467e81f900c96
BLAKE2b-256 checksum
How to use checksums
de970e57cf35867a960e6286136357e125283940e3ca503c02e8f4599a5f5e6d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp314-cp314-macosx_26_0_arm64.whl

Download URL pymiesim-6.0.4-cp314-cp314-macosx_26_0_arm64.whl
Size 4.8 MB
Tags CPython 3.14 macOS 26.0+ ARM64
SHA-256 checksum
How to use checksums
80d082b6870d1d5fbec93579f03a46c83ccdefd25d2b1f8470e41bad170e44f1
BLAKE2b-256 checksum
How to use checksums
531b0955d8790df4148e045cfed647ac44d3bfb4c769b893cb869c5f00533951
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp313-cp313-win_amd64.whl

Download URL pymiesim-6.0.4-cp313-cp313-win_amd64.whl
Size 13.7 MB
Tags CPython 3.13 Windows x86-64
SHA-256 checksum
How to use checksums
eda8d5c010a290221ab5539348fd84e52bc1453634f0909e33824c6de23b4d6e
BLAKE2b-256 checksum
How to use checksums
5344fd0f031a97dc05641732621202deb1af5d9f267c534a1e57ba481dd0ff1f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl

Download URL pymiesim-6.0.4-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Size 6.0 MB
Tags CPython 3.13 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
a77c024de24318ec56d1a27c9596c58a6259a41596f20502c323acf20870bf3e
BLAKE2b-256 checksum
How to use checksums
8ace015d52221654cb89316a245d7157fb45d1c53b842ba63572e58512dd6335
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp313-cp313-macosx_26_0_arm64.whl

Download URL pymiesim-6.0.4-cp313-cp313-macosx_26_0_arm64.whl
Size 4.8 MB
Tags CPython 3.13 macOS 26.0+ ARM64
SHA-256 checksum
How to use checksums
45a40e41d669ff8c477226c43c362f47b270a9b74a237fa312ce668e7302f05c
BLAKE2b-256 checksum
How to use checksums
cbcbe238a6388e9329f1acb2088c35daa365b59c7f5bddf2dab414e7515911bb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp312-cp312-win_amd64.whl

Download URL pymiesim-6.0.4-cp312-cp312-win_amd64.whl
Size 13.7 MB
Tags CPython 3.12 Windows x86-64
SHA-256 checksum
How to use checksums
5567ff337acc0d37d45a44c2a203c078bfe377c2609116356d6b6040474da414
BLAKE2b-256 checksum
How to use checksums
f1ec429ee4cf5bf6ed9baa4cce5752c454b8a402b85e5405112be0a8e53bd7cd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl

Download URL pymiesim-6.0.4-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Size 6.0 MB
Tags CPython 3.12 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
588b23facfbc40a9f82f5b05439f8a32d6953ed7cf88e2b2d891b52cf2d32fb7
BLAKE2b-256 checksum
How to use checksums
c845a02fa43087479c05e6f2c323d3c53094dd5c39cded239714523f23bc4c27
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp312-cp312-macosx_26_0_arm64.whl

Download URL pymiesim-6.0.4-cp312-cp312-macosx_26_0_arm64.whl
Size 4.8 MB
Tags CPython 3.12 macOS 26.0+ ARM64
SHA-256 checksum
How to use checksums
c455484bafc86f2fbf95221137c098e26b977a944420321e94bdf94406b86239
BLAKE2b-256 checksum
How to use checksums
df5503fa685d25f1e5da5b639d57369bd997876fcadc68dc9b4b99650a127881
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp311-cp311-win_amd64.whl

Download URL pymiesim-6.0.4-cp311-cp311-win_amd64.whl
Size 13.6 MB
Tags CPython 3.11 Windows x86-64
SHA-256 checksum
How to use checksums
ecb2a088b0f52f7cc620ccbc0ca6a24816ae23ecadc312ecc8c53b52213dcaf1
BLAKE2b-256 checksum
How to use checksums
961d75cb557293505315fa7441fe02d6ce939beaa30b39bbd7b6e9e482c43a84
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl

Download URL pymiesim-6.0.4-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
Size 6.0 MB
Tags CPython 3.11 Linux glibc 2.27+ x86-64 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
d628808f5c93d093aaaf2dc29b2ea165cace012579ffee43f5125c7be00bee91
BLAKE2b-256 checksum
How to use checksums
966d523bc82e2291f7022fe3877700cbddde462959a7172b62f632581b148976
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Release files / pymiesim-6.0.4-cp311-cp311-macosx_26_0_arm64.whl

Download URL pymiesim-6.0.4-cp311-cp311-macosx_26_0_arm64.whl
Size 4.8 MB
Tags CPython 3.11 macOS 26.0+ ARM64
SHA-256 checksum
How to use checksums
fc2051f8dab5fb1fe3845ce8c2e4d653ef71420ce8295906e5c9595337d23e8d
BLAKE2b-256 checksum
How to use checksums
3848943b74a200421dab39cd7ddd26570b952209141031455c5f8db09aa50bfe
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.11.17

Security for PyMieSim 6.0.4

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Release history Release notifications | RSS feed

This release

6.0.4 This release

12 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page