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42 lines
2.0 KiB
Markdown
42 lines
2.0 KiB
Markdown
# SIMoN Visualization
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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.
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## Export data
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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.
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```
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./export.sh <model_name> <year>
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```
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where `year` will be equal to its corresponding increment step plus the initial year. For example,
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```
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./export.sh gfdl_cm3 2035
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```
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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.)
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## Plot data (requires [Python 3.6+](https://www.python.org/downloads/))
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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.
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```
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pip install -r requirements.txt
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python plot.py --data <your_mongo_doc>.json
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```
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For example,
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```
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python plot.py --data 2035_gfdl_cm3.json
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```
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Other command line options:
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* `--data`: path to the JSON file created by `export.sh`.
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* `--shapefile_dir`: path to the directory of shapefiles.
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* `--projection`: EPSG coordinate reference system to use for plotting.
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* `--width`: pixel width of the plot.
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* `--height`: pixel height of the plot.
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* `--show`: display the plot.
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* `--save`: write the plot to a file.
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A new HTML file will be created in the `viz` directory. Open this file in a web browser to display the Bokeh visualization.
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