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earth2studio.models.px.Persistence#

class earth2studio.models.px.Persistence(variable, domain_coords, history=1, dt=numpy.timedelta64(6, 'h'))[source]#

Persistence model that generates a forecast by applying the identity operator on the initial condition and indexing the lead time by 6 hours. Primarily used in testing.

Parameters:
  • variable (Union[str, List[str]]) – The variable or list of variables predicted by the model.

  • domain_coords (CoordSystem) – The coordinates representing the domain for this model to operate on.

  • history (int)

  • dt (timedelta64)

__call__(x, coords)[source]#

Runs prognostic model 1 step.

Parameters:
  • x (torch.Tensor) – Input tensor

  • coords (CoordSystem) – Coordinate system, should have dimensions [time, variable, *domain_dims]

Returns:

  • x (torch.Tensor)

  • coords (CoordSystem)

Return type:

tuple[Tensor, OrderedDict[str, ndarray]]

create_iterator(x, coords)[source]#

Creates a iterator which can be used to perform time-integration of the prognostic model. Will return the initial condition first (0th step).

Parameters:
  • x (torch.Tensor) – Input tensor

  • coords (CoordSystem) – Input coordinate system

Yields:

Iterator[tuple[torch.Tensor, CoordSystem]] – Iterator that generates time-steps of the prognostic model container the output data tensor and coordinate system dictionary.

Return type:

Iterator[tuple[Tensor, OrderedDict[str, ndarray]]]