NEDAS.models.qg.python.qg_python_model module

NEDAS Model interface for the Python QG spectral model.

Mirrors QGFortranModel in structure; runs QGModel in-process (no external executable). Supports both offline (file-based .npy) and online (in-memory) IO modes.

File format

Each snapshot is stored as a single NumPy .npy file containing the full spectral streamfunction psi of shape (nz, nky, nkx), complex128. Filename: <path>/<member_str>/output_<YYYYMMDD_HH>.npy

Array conventions

Physical variables returned to / received from NEDAS have shape (ny, nx) for scalars or (2, ny, nx) for vector (u, v), in NEDAS grid convention where axis-0 = y direction and axis-1 = x direction.

The QG spectral model internally uses spec2grid() which returns (nx, ny) with axis-0 = x direction, so _derive_var() and _psi_from_var() apply .T when crossing the boundary between the two conventions.

class NEDAS.models.qg.python.qg_python_model.QGPythonModel(**kwargs)

Bases: Model

NEDAS Model interface for the pure-Python QG spectral model.

Configuration mirrors QGFortranModel and the QGModel dataclass. All physics parameters (kmax, nz, F, beta, bot_drag, …) are read from default.yml and overridden by the user YAML / CLI args via parse_config().

kmax: int

nz: int

restart_dt: float

F: float

beta: float

filename(**kwargs)

read_var_from_file(**kwargs)

write_var_to_file(var, **kwargs)

read_var_from_memory(**kwargs)

write_var_to_memory(var, **kwargs)

read_grid(**kwargs)

Read the grid information from the model output.

Parameters:

**kwargs – Keyword arguments for reading the grid.

read_mask(**kwargs)

z_coords(**kwargs)

Get the vertical coordinates of the model.

Parameters:

**kwargs – Keyword arguments for getting the vertical coordinates.

Returns:

The vertical coordinates.

Return type:

np.ndarray

preprocess(*args, **kwargs)

Preprocess the model data.

Parameters:

**kwargs – Keyword arguments for preprocessing.

postprocess(*args, **kwargs)

Postprocess the model data.

Parameters:

**kwargs – Keyword arguments for postprocessing.

run(*args, **kwargs)

Run the model forward in time.

Parameters:

• *args – Arguments

• **kwargs – Keyword arguments

Keyword Arguments:

• time (datetime) – current time when forecast starts

• restart_dir (str) – directory where restart files are located

• forecast_period (int) – forecast period in hours

If self.ens_run_strategy == ‘batch’, the method will run all ensemble members in one go, expect additional kwargs[‘nens’] to be the ensemble size. If self.ens_run_strategy == ‘scheduler’, the method runs a single member indexed by kwargs[‘member’], and kwargs[‘worker_id’] is the pid assigned by the scheduler to run this method.

generate_truth(*args, **kwargs) → None

Generate truth (nature run) model states. Use for running synthetic observation experiments.

generate_init_ensemble(*args, **kwargs) → None

Generate initial perturbed model states for ensemble forecasts.

Parameters:

• nens (int) – ensemble size

• **kwargs