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voiage.factory.create_distributed_large_scale_analysis

create_distributed_large_scale_analysis

Section titled “create_distributed_large_scale_analysis”
create_distributed_large_scale_analysis([positional or keyword] nb_array: np.ndarray | ValueArray = None, [positional or keyword] parameter_samples: np.ndarray | ParameterSet | dict[str, np.ndarray] | None = None, [positional or keyword] chunk_size: int = 10000, [positional or keyword] n_nodes: int = 1, [positional or keyword] workers_per_node: int | None = None, [positional or keyword] scheduler: str = 'process', [positional or keyword] scheduler_address: str | None = None, [positional or keyword] use_processes: bool = True, [positional or keyword] memory_limit_mb: float | None = None) -> tuple[FluentDecisionAnalysis, ClusterExecutionConfig]

Create a large-scale analysis plus a cluster execution configuration.

This keeps the analysis object itself unchanged while making the CPU-cluster execution contract explicit for callers that want to fan work out across nodes, schedulers, or distributed executors.

Parameters:

  • nb_array np.ndarray | ValueArray
  • parameter_samples np.ndarray | ParameterSet | dict[str, np.ndarray] | None (default: None)
  • chunk_size int (default: 10000)
  • n_nodes int (default: 1)
  • workers_per_node int | None (default: None)
  • scheduler str (default: 'process')
  • scheduler_address str | None (default: None)
  • use_processes bool (default: True)
  • memory_limit_mb float | None (default: None)

Returns: tuple[FluentDecisionAnalysis, ClusterExecutionConfig]