geogridfusion.geogridfusion.get#

geogridfusion.geogridfusion.get(source: NestedNamespace, sort: bool = True) → tuple[xarray.core.dataset.Dataset, pandas.core.frame.DataFrame] | Dataset[source]#

Extract a weather xarray dataset and metadata pandas dataframe from your zarr store. get pulls the entire datastore into these objects. PVDeg does not make indexing available at this stage. This is practical because all datavariables are stored in dask arrays so they are loaded lazily instead of into memmory when this is called. Choose the points you need after this method is called by using sel, isel, loc, `iloc.

store.get is meant to match the API of other geospatial weather api’s from pvdeg like pvdeg.weather.get, pvdeg.weather.distributed_weather, GeospatialScenario.get_geospatial_data

Parameters:

  • source (str) – name of store used by geogridfusion to reference the path to your store

  • group (str) –

    name of the group to access from your local zarr store. Groups are created automatically in your store when you save data using pvdeg.store.store.

    From `pvdeg.store.store` docstring Hourly PVGIS data will be saved to “PVGIS-1hr”, 30 minute PVGIS to “PVGIS-30min”, similarly 15 minute PVGIS will be saved to “PVGIS-15min”

  • sort (bool) – sort by gid on load from disk. disable for potentially significant speedup on larger datasets

Returns:

loaded_ds (xr.Dataset) – Dataset loaded as saved Weather data for all locations requested in an xarray.Dataset using a dask array backend. This may be larger than memory.