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These instructions are for setting up realtime LPT from scratch on a Linux system with an Anaconda Python environment.
First, download Anaconda Python for Linux using the download link at https://www.anaconda.com/. The current version is for Python 3.7. Subsequent Python versions should work as long as they maintain backwards compatibility. The current direct download link is here.
This is usually done by running the installer script (e.g., Anaconda3-2020.02-Linux-x86_64.sh). The script will ask for a directory where to install Python environments. Generally your home directory on your system will do. The Python environment on my system takes up 1.7 GB of space.
To set up a Python environment with the modules needed to run LPT, you can issue the following command:
conda create --name lpt numpy pandas matplotlib basemap netCDF4 h5py scipy wrf-python gdal
The command may first ask you to update Anaconda (optional). Answer yes when prompted with the list of modules to be installed, and it will install the environment. To activate the environment before running LPT, use source activate lpt.
The code is on GitHub here.
Navigate to a directory where you want to run LPT, and get the code using the following:
git clone https://github.com/brandonwkerns/lpt-python-public.git
This should download the code and put it under the directory lpt-python-public/.
NOTE: If you want to use a different directory name, you can call the git clone command like this:
git clone https://github.com/brandonwkerns/lpt-python-public.git custom_directory_name
When/if code updates are needed, doing a git pull anywhere under the directory should update all of the relevant files.
The code repository has "MASTER" files which are to be copied and edited. The idea is that the MASTER files may be updated on the GitHub repository. If you directly edit the "MASTER" files, it may cause issues when git pull is used.