The data and scripts found in this repository can be installed by running
git clone https://github.com/Chamberpain/ARGONE.git
Or by downloading this package from the link above.
This will create a directory in whatever folder you were named ARGONE that will contain everything in this repository. I recommend using conda for package management and to create a new environment to run this code. Instruction for how to create a new environment in Conda can be found here. After activating your new environment, you will need to install some dependencies to run this code. If you are running conda, these dependencies can be installed with the following commands:
conda install ipython
conda install pandas
conda install scipy
conda install matplotlib
conda install -c conda-forge geopy
conda install shapely
conda install -c conda-forge folium
Alternatively, for installing dependancies using pip:
pip install ipython
pip install pandas
pip install scipy
pip install matplotlib
pip install geopy
pip install shapely
pip install folium
To test your code is working, type in the terminal
python main.py test 150
A map of the probability distribution of 4 argo floats should appear.
main.py looks for csv data files in the Data folder of a specified filename. The csv files should have rows equal to the number of floats in your array with the latitude of the float locations recorded in the latitude column and the longitude recorded in the longitude column. An example of a working csv file is shown in test.csv.
The output of the script is a interactive folium map that is found the Output and a csv file that contains the future probality density function of the array. Note that both time and space is descritized to the spatial and temporal resolution of the transition matrix (2 degrees in latitude and longitude and 90 day timesteps).
The syntax for running the script is
python main.py (filename of csv file) (timestep)
for example, in the test case we executed
python main.py test 150
where test.csv is the csv file we want to open and we want to consider a 150 day propogation (the code automatically rounds up to 180 days).
The Argovis fork of this repo populates Argovis' MongoDB instance rather than output text files. Populate for a single lat / long with:
cat <<EOF > Data/test.csv
Latitude,Longitude
-44,-178
EOF
python -u main.py test
Or all of them via build_covariance.sh