dycove.sim.outputs.OutputManager

class dycove.sim.outputs.OutputManager(engine, save_freq=1, save_mort=True)

For saving VegCohort instances to output files.

__init__(engine, save_freq=1, save_mort=True)

Methods

__init__(engine[, save_freq, save_mort])
cohort_indexing(year, ets)	Log the year/ets combo and create (or append to) list for cohort file names
reconcile_vegetation_output(simstate)	Merge vegetation outputs across MPI subdomains into single files.
save_cohort_index()
save_netcdf(directory, filename, data[, ...])	Save dict-like data as a NetCDF file using xarray
save_simulation_metadata(simstate)	Save record of ecological time inputs for easier post-processing
save_vegetation_step(simstate, vts)	Save vegetation cohort state for a given ecological timestep
update_file_counts()	Update file count for each cohort based on current number of cohorts.

cohort_indexing(year, ets)

Log the year/ets combo and create (or append to) list for cohort file names

reconcile_vegetation_output(simstate)

Merge vegetation outputs across MPI subdomains into single files.

We want one output file per cohort, per ecological timestep.

This executes on main processor only and can take a while for giant domains.

Method is part of the engine class because it uses domain-specific info to re-map files, but we should keep this access point in OutputManager for now because we may add other similar tasks here later (and b/c it involves I/O and directory access).

save_netcdf(directory: Path, filename: str, data: dict, eco_year: int | None = None, ets: int | None = None, cohort_id: int | None = None, saved_attrs: dict | None = None)

Save dict-like data as a NetCDF file using xarray

save_simulation_metadata(simstate)

Save record of ecological time inputs for easier post-processing

save_vegetation_step(simstate, vts)

Save vegetation cohort state for a given ecological timestep

update_file_counts()

Update file count for each cohort based on current number of cohorts.