Current location for LV4 Optimization (MDO) algorithms and work.
The archived LV4_Optimization white paper and notebook is essential reading for background info and conceptual explanation. My code follows directly from it and some other archived work.
Note, Openrocket only works on Java 8 and below. Check out the readme in rocket_farm.
1) Install gfortran Required by RocketCEA Ubuntu: apt-get install gfortran Windows: Dual-boot with Ubuntu :) 2) Install anaconda if you don't have it. Save yourself some time and use anaconda for python 3) Use conda to install the environment conda env create -f lv4_mdo_p3p7.yml If you need to update this later use: conda env update --file lv4_mdo_p3p7.yml --prune 4) Load the python environment: conda activate lv4_mdo_p3p7
This MDO has been successfully installed and compiled on Ubuntu and MacOS.
The following required modules are problematic to install on Windows.
Some of them require a fortran compiler.
Each one will have more details below.
This module may be installed with pip install pyhwm2014 but is not recommended.
Instead, download the code from their GitHub repository and install it manually from the source code installation directions.
However, change the last command from pip install -e . --process-dependency-links to pip install -e ./ as shown below:
git clone https://github.com/rilma/pyHWM14.git
cd pyHWM14
pip -q install coveralls
pip install numpy
pip install -e ./Install with pip install nrlmsise00.
Requires fortran compiler.
Install with pip install rocketcea.
Requires fortran compiler.
Install with pip install rbfopt.
This module requires Bonmin, which is distrubuted under the EPL (Eclipse Public License).
Bonmin is dependent on third party solvers which are distributed under different licenses than Bonmin.
Check out Bonmin's pages on Getting Started with Bonmin and Third Party solvers
Install tensorflow with pip install tensorflow
Reinstall all jupyter notebook dependencies
Reinstall pyhwm2014 with the manual instructions above (via cloning the repository and installing from there)
Make sure you install coveralls with pip install coveralls