MIEX-Python

is a Mie scattering code for large grains written in Python and based on MIEX by Wolf & Voshchinnikov (2004).

The following quantities for

1. single grain sizes / chemical components and
2. mixtures of chemically different grains with a size distribution

can be calculated:

• Scattering matrix elements $S_{11}$, $S_{12}$, $S_{33}$, and $S_{34}$,
• Extinction efficiency factor ($Q_\mathrm{ext}$) and Extinction cross-section ($C_\mathrm{ext}$),
• Scattering efficiency factor ($Q_\mathrm{sca}$) and Scattering cross-section ($C_\mathrm{sca}$),
• Absorption efficiency factor ($Q_\mathrm{abs}$) and Absorption cross-section ($C_\mathrm{abs}$),
• Backscattering efficiency factor ($Q_\mathrm{bk}$) and Backscattering cross-section ($C_\mathrm{bk}$),
• Radiation pressure efficiency factor ($Q_\mathrm{pr}$),
• Albedo,
• Scattering asymmetry factor ($g$).

Modified and ported to Python with permission of S. Wolf. For the original source code of MIEX written in FORTRAN90, we refer to

Requirements

To run MIEX-Python, at least Python 3.6 and the following packages are required:

• numba
• numpy

To check the current version or to install the packages, run:

python3 --version
pip3 install -r requirements.txt

Installation

The package can be installed via pip, change into the directory MIEX-Python and run:

pip install .

Use MIEX-Python

Run MIEX-Python via streamlit

miex_app.py can be used as a simple Streamlit web app: https://miex-python.streamlit.app/.

Alternatively, install Streamlit

pip3 install streamlit

and start the web app locally:

streamlit run miex_app.py

Import MIEX-Python

After installation, MIEX-Python can be imported via import miex and used in any python script (see jupyter notebook 1).

To calculate the efficiency factors and scattering amplitude functions (optionally), use e.g.,

result = miex.get_mie_coefficients(x=1.0, m=complex(1.5, 0.0), nang=91, doSA=True)

Variable	Input Parameter	Type
x	Size parameter	float
m	Complex refractive index	complex
nang=2	Half number of scattering angles in the interval [0, 90]	int, optional
doSA=False	Calculate scattering amplitude functions	bool, optional
nterm=2e7	Maximum number of terms to be considered	int, optional
eps=1.0e-20	Accuracy to be achieved	float, optional
xmin=1.0e-6	Minimum size parameter	float, optional

The function returns a dictionary with the following entries:

Entry	Output Parameter	Type
Q_ext	Extinction efficiency	float
Q_abs	Absorption efficiency	float
Q_sca	Scattering efficiency	float
Q_bk	Backscattering efficiency	float
Q_pr	Radiation pressure efficiency	float
Albedo	Single scattering albedo	float
g_sca	Scattering asymmetry factor	float
SA_1	Scattering amplitude function	ndarray, complex
SA_2	Scattering amplitude function	ndarray, complex
theta	Scattering angles [rad]	ndarray

The scattering amplitude functions are an array with size 2*nang-1.

To calculate the scattering matrix elements, use

scat_mat = miex.get_scattering_matrix(S1, S2)

where $S_1$ and $S_2$​ are the scattering amplitude functions. The function returns a dictionary with the scattering matrix elements $S_{11}$​, $S_{12}$​, $S_{33}$​, $S_{34}$ as entries for instance scat_mat["S_11"].

Test MIEX-Python

test_miex.py includes some test routines. The results are compared with results by Bohren & Huffman (1998) and by Wiscombe (1979):

python3 test_miex.py

Project structure

.
├── ri-data                                  # Input data used by MIEX-Python
├── README.me
├── miex
│   └── miex.py                              # Source code of MIEX-Python
├── miex_app.py                              # Python script to run MIEX-Python via Streamlit
├── miex_notebook_1.ipynb                    # Jupyter notebook on how to use MIEX-Python
├── requirements.txt                         # Required python packages for MIEX-Python
└── test_miex.py                             # Python script for test purposes

Copyright

The original source code of MIEX written in FORTRAN90 is distributed under the CPC license. Modified and ported to Python with permission of S. Wolf.