earth2studio.models.px.FCN#
- class earth2studio.models.px.FCN(core_model, center, scale)[source]#
FourCastNet global prognostic model. Consists of a single model with a time-step size of 6 hours. FourCastNet operates on 0.25 degree lat-lon grid (south-pole excluding) equirectangular grid with 26 variables.
Note
This model is a retrained version on more atmospgeric variables from the FourCastNet paper. For additional information see the following resources:
- Parameters:
core_model (torch.nn.Module) – Core PyTorch model with loaded weights
center (torch.Tensor) – Model center normalization tensor of size [26]
scale (torch.Tensor) – Model scale normalization tensor of size [26]
- __call__(x, coords)[source]#
Runs prognostic model 1 step.
- Parameters:
x (torch.Tensor) – Input tensor
coords (CoordSystem) – Input coordinate system
- Returns:
Output tensor and coordinate system 6 hours in the future
- Return type:
tuple[torch.Tensor, CoordSystem]
- 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]]]
