AeroML is a set of python modules (some built with f2py) for implementing machine learning algorithms for aerosol retrievals. The final goal is to assimilate these data into the GEOS Easrth System Model.
In your .bashrc or .tcshrc or other rc file add a line:
module use -a /discover/swdev/gmao_SIteam/modulefiles-SLES12
module use -a /nobackup/gmao_SIteam/modulefiles
On the GMAO desktops, the SI Team modulefiles should automatically be
part of running module avail but if not, they are in:
module use -a /ford1/share/gmao_SIteam/modulefiles
Also do this in any interactive window you have. This allows you to get module files needed to correctly checkout and build the model.
Now load the GEOSenv module:
module load GEOSenv
which obtains the latest git, CMake, etc. modules needed to build.
Mepo is a multiple repository tool available on github.
mepo clone [email protected]:GEOS-ESM/AeroML.git
On tcsh:
source @env/g5_modules
or on bash:
source @env/g5_modules.sh
We currently do not allow in-source builds of GEOSgcm. So we must make a directory:
mkdir build
The advantages of this is that you can build both a Debug and Release version with the same clone if desired.
CMake generates the Makefiles needed to build the model.
cd build
cmake .. -DBASEDIR=$BASEDIR/Linux -DCMAKE_Fortran_COMPILER=ifort -DCMAKE_INSTALL_PREFIX=../install
This will install to a directory parallel to your build directory. If you prefer to install elsewhere change the path in:
-DCMAKE_INSTALL_PREFIX=<path>
and CMake will install there.
To build with debugging flags add:
-DCMAKE_BUILD_TYPE=Debug
to the cmake line.
make -j6 install
Please check out our contributing guidelines.
All files are currently licensed under the Apache-2.0 license, see LICENSE.
Previously, the code was licensed under the NASA Open Source Agreement, Version 1.3.
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