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voiage

voiage.factory.create_large_scale_analysis

create_large_scale_analysis

Section titled “create_large_scale_analysis”
create_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_workers: int | None = None, [positional or keyword] memory_limit_mb: float | None = None) -> FluentDecisionAnalysis

Create a large-scale VOI analysis with parallel processing and memory optimization.

This factory method creates a FluentDecisionAnalysis object configured for handling large datasets with chunked processing and parallel execution. For explicit CPU-cluster or distributed execution, use create_distributed_large_scale_analysis to obtain the matching ClusterExecutionConfig alongside the analysis object.

Args: nb_array: Net benefit array parameter_samples: Parameter samples for EVPPI calculation chunk_size: Size of chunks for incremental computation n_workers: Number of parallel workers memory_limit_mb: Memory limit in MB

Returns

Section titled “Returns”

FluentDecisionAnalysis: Configured large-scale analysis object

Parameters:

  • nb_array np.ndarray | ValueArray
  • parameter_samples np.ndarray | ParameterSet | dict[str, np.ndarray] | None (default: None)
  • chunk_size int (default: 10000)
  • n_workers int | None (default: None)
  • memory_limit_mb float | None (default: None)

Returns: FluentDecisionAnalysis