At every increment step, each model outputs its data for that increment step as a dictionary. The dictionary maps geographic IDs to values for the corresponding region. The particular IDs will depend on the geographic granularity. This dictionary is stored as a JSON document in a Mongo database. Since the data maps each region to a single value, it can be visualized on a choropleth map.
SIMoN stores all of the data outputs from the models as documents in a Mongo database (the simon_mongodb container). You can retrieve a single document and save it as a JSON file using the export.sh bash script in the viz directory.
./export.sh <model_name> <year>
where year will be equal to its corresponding increment step plus the initial year. For example,
./export.sh gfdl_cm3 2035
will retrieve the annual data that the GFDL CM3 model projected for the year 2035. (If the initial year, increment step 0, is 2016, then 2035 is increment step 19.)
Plot data (requires Python 3.6+)
Once you've retrieved a document and saved it as a JSON file, plot the data on a choropleth map using the plot.py script in the viz directory. (You can also use the Plot.ipynb Jupyter notebook.) Just make sure to pip install requirements.txt first.
pip install -r requirements.txt
python plot.py --data <your_mongo_doc>.json
For example,
python plot.py --data 2035_gfdl_cm3.json
Other command line options:
--data: path to the JSON file created byexport.sh.--shapefile_dir: path to the directory of shapefiles.--projection: EPSG coordinate reference system to use for plotting.--width: pixel width of the plot.--height: pixel height of the plot.--show: display the plot.--save: write the plot to a file.
A new HTML file will be created in the viz directory. Open this file in a web browser to display the Bokeh visualization.
