README

This code computes Qabs, Qsca, and Qext from the refractive index or the dialectric constant using Mie's theory.
It also compute opacity for coated materials.

Getting started

Basic usage to load a material and compute its opacity for a grain size distribution is (see test_01.py file)

from qabsmanager import QabsManager

# create object
q = QabsManager()


# load core data from file
core = q.load_material("data/eps_carb_P93.dat", labels=["wlen", "real_m", "im_m"])

# compute opacity for core material
core.compute_kappa()

# print some info to screen
q.report()

# save opacity to plot
core.plot_kappa("kappa_01.png")

Different file formats

To load data from files with different formats, for example a file with wavelength, real and imaginary part of dielectric:

from qabsmanager import Qabs_utils

# create object
q = Qabs_utils()

# load data from file with given format
q.load_eps("eps_CO.dat", labels=["wlen", "real_eps1", "im_eps"])

The file can be both space- or tab-separated.

labs are
wlen: wavelength in micron
real_eps1: real part of dialectric - 1
real_eps: real part of dialectric
im_eps: imaginary part of dielectric
real_m1: real part of refractive index - 1
real_m: real part of refractive index
im_m: imaginary part of refractive index

Composite material

It is possible to use coated materials by loading their optical properties (see test03.py).

from qabsmanager import QabsManager

# create object
q = QabsManager()

q.clear_plots()

# load core data from file
core = q.load_material("data/eps_carb_P93.dat", labels=["wlen", "real_m", "im_m"])

# load ice data from file
mantle = q.load_material("data/eps_H93.dat", labels=["wlen", "real_m", "im_m"])

# create new material from core and mantle
composite = q.make_optical([core, mantle])

# set size ratio silicon/ice material
composite.dust.aratio = 0.15

# compute opacity of the composite material
composite.compute_kappa()

# plot opacity
composite.add_plot_kappa("kappa_03.png", postfix="coated", xlim=(5e1, 1e3), ylim=(1, 1e3))

Benchmark

The code has been benchmarked against the Original Astronomical Silicate (Draine & Lee 1984; Laor & Draine 1993) link.
See test_02.py

from qabsmanager import Qabs_utils

# create object
q = Qabs_utils()

# do benchmark
q.benchmark()