ronenroi / pyshdom4vip-ct

⚠️⚠️⚠️⚠️⚠️ This project is built on the pyshdom project by Aviad Levis & Jesse Loveridge from https://github.com/aviadlevis/pyshdom ⚠️⚠️⚠️⚠️⚠️

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pyshdom

Pyshdom performs 3D reconstruction of cloud microphysical properties from multi-angle, multi-spectral solar reflected radiation using a non-linear optimization procedure [1,2]. The core radiative transfer routines are sourced from the Fortran SHDOM (Spherical Harmonic Discrete Ordinate Method for 3D Atmospheric Radiative Transfer) code by Frank K. Evans [3]. The python package was created by Aviad Levis, Amit Aides (Technion - Israel Institute of Technology) and Jesse Loveridge (University of Illinois).

 

Installation

Installation using using anaconda package management

Start a clean virtual environment

conda create -n pyshdom python=3
source activate pyshdom

Install required packages

conda install anaconda dill tensorflow tensorboard pillow joblib

Install pyshdom distribution with (either install or develop flag)

python setup.py develop

 

Main scripts

For generating cloud data for training VIP-CT see the list below.

• VIP-CT_scripts/generate_data_fixed_imagers.py
• VIP-CT_scripts/generate_data_varying_imagers.py

Change the corresponding config files in VIP-CT_scripts/configs.

• CloudFieldFile: Cloud data raw txt folder.
• satellites_images_path: Output folder.
• GSD: The image ground spatial resolution.
• dx,dy,dz: The imager perturbation magnitude.
• n_formations: Number of imagers

For real-world AirMSPI results, generate cloud data using VIP-CT_scripts/generate_data_airmspi.py. (set the corresponding paths).  

Usage and Contact

If you find this package useful please contact [email protected]. If you use this package in an academic publication please acknowledge the appropriate publications (see LICENSE file).