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Adding Data

The Seedlot Selection Tool depends on three types of data: climate data, as NetCDF files; region boundary data, as shapefiles; and seed zone data, also as shapefiles.

Climate Data

Climate data is represented as ncdjango services. To import the data, first place your data in your NC_SERVICE_DATA_ROOT directory (see :ref:`setup-install`) under a directory named regions. The data should be in a directory matching the region the data are for. The DEM should be placed in the directory for the region and named <region>_dem.nc. Sub-directories should be created for each year / climate scenario. For example, the directory structure for the west2 region should be:

<NC_SERVICE_DATA_ROOT>
+-- regions
|   +-- west2
|   |   +-- 1961_1990Y
|   |   +-- 1991_2010Y
|   |   +-- rcp45_2025Y
|   |   +-- rcp45_2055Y
|   |   +-- rcp45_2085Y
|   |   +-- rcp85_2025Y
|   |   +-- rcp85_2055Y
|   |   +-- rcp85_2085Y
|   |   +-- west2_dem.nc

Inside each directory for a year/scenario, each climate variable dataset should be named according to region, RCP, year, and variable name in the following format: <region>_<rcp45/rcp85>_<year>Y_<variable>.nc. The current (1961_1990) and historic (1981_2010) years should not include an RCP. For example, the contents of the 1961_1990Y and rcp45_2025Y directories for the west2 region should be:

.
+-- 1961_1990Y
|   +-- west2_1961_1990Y_AHM.nc
|   +-- west2_1961_1990Y_bFFP.nc
|   +-- west2_1961_1990Y_CMD.nc
|   +-- <...>
+-- rcp45_2025Y
|   +-- west2_rcp45_2025Y_AHM.nc
|   +-- west2_rcp45_2025Y_bFFP.nc
|   +-- west2_rcp45_2025Y_CMD.nc

Run the following command to import the region elevation and all climate variables:

$ python source/manage.py populate_climate_data <region>

The command will assume the variables: 'MAT', 'MWMT', 'MCMT', 'TD', 'MAP', 'MSP', 'AHM', 'SHM', 'DD_0', 'DD5', 'FFP', 'PAS', 'EMT', 'EXT', 'Eref', 'CMD' and the years: '1961_1990', '1981_2010', 'rcp45_2025', 'rcp45_2055', 'rcp45_2085', 'rcp85_2025', 'rcp85_2055', 'rcp85_2085'. If you are using different variables and/or years, you will need to edit the script, which is located at source/seedsource/management/commands/populate_climate_data.py.

Region Boundary Data

You should simplify your boundary data before importing it into the tool. Next, import the region into the tool:

$ python source/manage.py add_region <region> <path to shapefile>

You should also convert the region boundary to GeoJSON and, it to the directory sst/static/geometry/<region>_boundary.json, and re-run:

$ npm run-script merge-regions

Seed Zone Data

Seed zones are expected to be contained in data/seedzones. You can configure this by setting the value of SEEDZONES_LOCATION in your custom.py settings file (described in :ref:`setup-install` setup document).

Seed zones are stored in a ZIP file, which includes a config.py file with configuration options for the seed zones.

You can import a prepared seed zone set with the following command:

$ python source/manage.py import_seedzones <base name of seed zones zipfile>

After importing the zones, you should run the calculate_zone_transfers command to generate transfer limits for each zone and elevation band (you will need to have service data for the appropriate region loaded first). Running the command with no arguments will process all zone sets:

$ python manage.py calculate_zone_transfers

Running the command with a source argument will process only zones for a single set:

$ python manage.py calculate_zone_transfers region9