Measurements measurements

Measurement plugins for pyCIF.

A measurement plugin is responsible for assembling a CIF-compatible observation data store from raw data sources. It acts as the bridge between external observation files (or synthetic generators) and the observation vector (ObsVect) consumed by the inversion.

Each measurement plugin exposes a single entry-point function:

• parse_tracers(self, datei, datef, ...) — reads or generates observations for a given tracer and time window and returns a multi-index pandas DataFrame with (maindata, metadata) column groups.

Available plugins

• standard — assembles observations from one or more obsparser providers.

• random/param — generates synthetic random observations within the model domain, useful for Observing System Simulation Experiments (OSSEs).

Available Measurements measurements

The following measurements are implemented in pyCIF so far:

• Concatenation of observations from parsers standard/std
• Random generation of observations random/param