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libradtranpy : a libradtran python wrapper

libradtranpy is a python package which has been developped to provide an easy access to the libRadtran radiative simulation package. It is intended to provide an atmospheric transmission model that can be used by the astronomical community for dealing with atmospheric transmission calibration issues.

The use of this interface is quite straight forwared provided the libRadtran installation is correct.

Installation of the two packages:

1) Installation of libradtran

The atmospheric simulation libradtran for multiple site (different altitudes) There are two ways to install this software:

conda install -c conda-forge rubin-libradtran

This documentation assumes libradtran version >=2.0.4 is installed on your computer.

To use libradtran inside librandtranpy wrapper

If libradtran is installed from conda-forge, there is nothing to do. If it is installed from sources, then an environnement variable LIBRADTRANDIR must be set to libRadtran installation path under which one have each of these directories:

  • /bin
  • /share/libRadtran/data
  • /include
  • /lib and
  • /share

from libRadtran installation directory.

example:

>> tree -L 1 libRadtran
libRadtran
├── bin
├── include
├── lib
├── libRadtran-2.0.5
└── share

and the inside the share directory the data/ directory must be available:

>> cd libRadTran
/> tree -L 2 share/
share/
└── libRadtran
    ├── GUI
    ├── data
    ├── doc
    └── examples

and inside the data/ directory you must have libRadtran data installed as folow

>> tree -L 1 data
data
├── aerosol
├── albedo
├── altitude
├── atmmod
├── correlated_k
├── crs
├── filter
├── ic
├── nca_lookup
├── scripts
├── solar_flux
└── wc

2) Installation of libradtranpy

Installation of libradtranpy from configuring setuptools defined in pyproject.toml file. (see https://setuptools.pypa.io/en/latest/userguide/pyproject_config.html) This package is maintained through the tool LINCC Frameworks Python Project Template (https://lincc-ppt.readthedocs.io/en/latest/index.html)

>> cd libradtranpy
# on Linux
>> pip install -e .[dev]
# on Mac M1 or M2 with zsh
>> pip install -e '.[dev]'

3) Run libradtranpy tests

A simple test to check if libradtran is installed correctly runs:

# call unit tests
>> python -m unittest tests/libradtranpy/*.py

or in verbose mode:

# call unit tests in verbose mode
>> python -m unittest -v tests/libradtranpy/*.py

it checks:

  • the existence of the environnement variable LIBRADTRANDIR point to the libradtran installation top directory
  • the existence of the bin directory and the executable uvspec
  • the existence of the share/libRadtran/data directory which hold all the internal data that libRadtranrequires for its execution.
  • the execution of a libradtran simulation works well returning some data.

Standard Use of libradtranpy interface

Two libRadtran running modes are available:

  • visible mode from wavelength range : 250.0 nm - 1200.0 nm
  • thermal mode from wavelength range : 2500 nm - 100000.0 nm

(these ranges are hardcoded, but it will be configurable in future).

Then whe have two interface modules for these modes :

  • libradtranpy.libsimulateVisible.py for the visible mode,
  • libradtranpy.libsimulateThermal.py for the thermal mode.

Use in the shell

if libradtranpy/src/libradtranpy/libsimulateVisible.py is in the python path:

>> libradtranpy/libsimulateVisible.py  [-v] -z <airmass> -w <pwv> -o <oz> -a<aer> -p <P> -c <cld> -m<mod> -q<proc> -s<site>
 	 - z   : airmass from 1.0 to 3.0, typical z=1 
 	 - pwv : precipitable watr vapor in kg per m2 or mm, typical pwv = 5.18 mm
 	 - oz  : ozone in Dobson units from 200 DU to 400 DU
 	 - aer : Aerosols vertical optical depth, typical a=0.04
 	 - p   : Pressure in hPa, typical P=775.3 hPa, optional  
 	 - c   : Cloud vertical optical depth, optional ,typical c=0
 	 - m   : Atmospheric model, typical m='us' 
 	 - q   : Interaction processes, typical q='sa' for scattering and absorption
     - s   : Observation site : LSST, CTIO, ....  
 	 - v   : activate verbose to get atmospheric profile
	 Examples : 
	 	 1) python libsimulateVisible.py -z 1 -w 0 -o 0 -a 0 -s LSST
	 	 2) python libsimulateVisible.py -z 1 -w 4 -o 300 -a 0.3 -c 0 -p 742 -m  us -q sa -s LSST
	 To generate ascii printout of the used atmospheric model table in a log file :
	 	 python libsimulateVisible.py -v -z 1 -w 0 -o 0 -a 0 -s LSST >& output.log

By example just run the following command in the shell:

>> python libsimulateVisible.py -z 1 -w 0 -o 0 -a 0 -s LSST

Outputs of libradtran

Librandtran generate output acii files consisting of rows of (wavelength, transmission).

librandtranpy manages the different simulations and their output files in a hierarchical directories. The top level directory is simulations/.

The output of libradtran can be found in subdirs of simulations/RT/2.0.5/observationsite/pp/.

Use of libradtranpy as python package library

The call of libradtran through libradtranpy can be done as follow:

from libradtranpy import libsimulateVisible

A call without aerosols:

wl,transm=libsimulateVisible.ProcessSimulation(am[index],pwv,ozone,pressure,aer_num=0,
                                                      prof_str='us',proc_str='sa',cloudext=cloudext,altitude="LSST")

A call with aerosols:

wl,transm = libsimulateVisible.ProcessSimulation(am[index],pwv,ozone,aer,pressure,aer_num=aer,angstrom_exponent_num=exponent,
                                                      prof_str='us',proc_str='sa',cloudext=cloudext,altitude="LSST")

The library libsimulateThermal can be used similarly. Please refers to the libradtranpy package documentation.

Documentation on the libradtranpy package

A more detailed series of examples are given in the extensive notebook series in docs/notebooks/intro_notebook.ipynb, showing a numberous use-cases of libradtranpy and a set of tools on atmospher to control its output.

Another source of documentation can be found on the documentation repository readthedocs.

(Note that readthedocs has not compiled the API because it doesn't install libRadtran itself. However the user can compile the docs on his computer by doing:)

>> cd docs
>> make html

and open the doc from file libradtranpy/_readthedocs/html/index.html.

Dev installation Guide from LINCC-Frameworks - Getting Started with python project template

Before installing any dependencies or writing code, it's a great idea to create a virtual environment. LINCC-Frameworks engineers primarily use conda to manage virtual environments. If you have conda installed locally, you can run the following to create and activate a new environment.

>> conda create env -n <env_name> python=3.10
>> conda activate <env_name>

Once you have created a new environment, you can install this project for local development using the following commands:

>> pip install -e .'[dev]'
>> pre-commit install
>> conda install pandoc

Notes:

  1. The single quotes around '[dev]' may not be required for your operating system.
  2. pre-commit install will initialize pre-commit for this local repository, so that a set of tests will be run prior to completing a local commit. For more information, see the Python Project Template documentation on pre-commit <https://lincc-ppt.readthedocs.io/en/latest/practices/precommit.html>_.
  3. Install pandoc allows you to verify that automatic rendering of Jupyter notebooks into documentation for ReadTheDocs works as expected. For more information, see the Python Project Template documentation on Sphinx and Python Notebooks <https://lincc-ppt.readthedocs.io/en/latest/practices/sphinx.html#python-notebooks>_.