neural_lam.create_graph_with_wmg#
Create neural-lam graphs by delegating construction to weather-model-graphs.
Builds the g2m/m2m/m2g graph components with weather-model-graphs (wmg) and
saves them to disk in neural-lam’s tensor-on-disk format, replacing the
duplicated logic in create_graph.py.
Attributes#
Functions#
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Command-line interface for graph creation using weather-model-graphs. |
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Create graph using weather-model-graphs and save in neural-lam format. |
Module Contents#
- neural_lam.create_graph_with_wmg.cli(input_args: list[str] | None = None) None[source]#
Command-line interface for graph creation using weather-model-graphs.
- neural_lam.create_graph_with_wmg.create_graph_from_datastore(datastore: neural_lam.datastore.base.BaseDatastore, output_root_path: str, archetype: str = 'keisler', mesh_node_distance: float | None = None, mesh_grid_distance_ratio: float = 3.0, level_refinement_factor: int = 3, max_num_levels: int | None = None) None[source]#
Create graph using weather-model-graphs and save in neural-lam format.
- Parameters:
datastore (BaseDatastore) – Datastore providing grid coordinates.
output_root_path (str) – Directory where the .pt graph files will be saved.
archetype (str) – Graph archetype to create:
"keisler","graphcast", or"hierarchical".mesh_node_distance (float or None) – Distance between created mesh nodes (in coordinate units). If None, the grid node distance is estimated automatically from the grid coordinates and multiplied by
mesh_grid_distance_ratio.mesh_grid_distance_ratio (float) – Ratio of mesh node distance to grid node distance. Only used when
mesh_node_distanceis None. Default is 3.0.level_refinement_factor (int) – Refinement factor between mesh hierarchy levels. Only used for
"graphcast"and"hierarchical"archetypes.max_num_levels (int or None) – Maximum number of mesh hierarchy levels. Only used for
"graphcast"and"hierarchical"archetypes.
- neural_lam.create_graph_with_wmg.ARCHETYPE_FUNCTIONS#