scenarioflow

Assemble the time-dependent inputs to numerical models from historical, real-time, forecast, climatology and planning components.

A scenario is not usually one data set. A model input such as a river flow may be a historical archive, joined to a provisional or real-time head, followed by a forecast or planning assumption. scenarioflow makes that assembly explicit in a YAML recipe: each component is read and transformed independently, then spliced in time at visible effective dates.

• Documentation: https://cadwrdeltamodeling.github.io/scenarioflow
• Source: https://github.com/CADWRDeltaModeling/scenarioflow

Quick start

conda install -c cadwr-dms -c conda-forge scenarioflow
cd examples/sac_sjr_flux
sflow plot scenario.yml -o figs

from scenarioflow import Scenario, load_yaml

sc = Scenario.from_config(load_yaml("scenario.yml"))
results = sc.run()          # {"sac": DataFrame, "sjr": DataFrame}

License

MIT. See LICENSE.