by Scott Prahl
iadpython will be a pure Python module to do forward and inverse multiple light scattering (radiative transport) in layered materials. Calculations are done using van de Hulst's adding-doubling technique.
The original adding-doubling algorithm was developed by van de Hulst to model light propagation through layered media. I extended it to handle Fresnel reflection at boundaries as well as interactions with integrating spheres.
Finally, the code was further extended to handle lost light using Monte Carlo techniques for inverse calculations.
Version v0.4.0 started the migration to a pure-python implementation. This version includes the ability to do forward calculations of light transport through layered 1D structures.
The long-term goal is rewrite the integrating sphere, inverse algorithm, and lost light calculations in pure python so that one can do inverse calculations (i.e., reflection and transmission measurements to intrinsic absorption and scattering properties).
Both inverse and forward calculations are currently possible using the iadc framework. This is a python interface to the inverse adding-doubling package written in C by Scott Prahl <https://github.com/scottprahl/iad>. This works now but is a nuisance to install and maintain because of its dependence on compiling and installing a C library.
See <https://iadpython.readthedocs.io> for full documentation of iadpython.
The following will do a forward calculation:
import iadpython as iad
mu_s = 10 # scattering coefficient [1/mm]
mu_a = 0.1 # absorption coefficient [1/mm]
g = 0.9 # scattering anisotropy
d = 1 # thickness mm
a = mu_s/(mu_a+mu_s)
b = mu_s/(mu_a+mu_s) * d
# air / glass / sample / glass / air
s = iadpython.Sample(a=a, b=b, g=g, n=1.4, n_above=1.5, n_below=1.5)
ur1, ut1, uru, utu = s.rt()
print('Collimated light incident perpendicular to sample')
print(' total reflection = %.5f' % ur1)
print(' total transmission = %.5f' % ut1)
print('Diffuse light incident on sample')
print(' total reflection = %.5f' % uru)
print(' total transmission = %.5f' % utu)
Use pip:
pip install iadpython
or conda:
conda install -c conda-forge iadpython
or use immediately by clicking the Google Colaboratory button below
As of version 0.5.3, the forward and inverse calculations work fine as long as you do not need to include integrating sphere effects or lost-light calculations.
If you want to do these, then you're probably best served by downloading and compiling the C-code (on unix or macos) or the .exe file for Windows. <https://omlc.org/software/iad/>
Required Python modules: numpy, matplotlib, ctypes, scipy
iadpython is licensed under the terms of the MIT license.