Skip to content

Pareto fronts

These functions expose the full candidate set a detector selects its final partition from, letting you inspect or re-select solutions yourself. For HP-MOCD, use HpMocd.generate_pareto_front instead.

pymocd.scale_fronts 

scale_fronts(
    graph: Any,
    pop_size: int = 100,
    num_gens: int = 50,
    cross_rate: float = 0.1,
    mut_rate: float = 0.1,
    gap: int = 10,
    beta: float = 0.05,
    adaptive_stop: bool = False,
    conv_pval: float = 0.1,
    refine: bool = True,
    topo_mode: int = 0,
) -> typing.Any

scale's merged rank-1 front (after union-refinement), the candidate set scale selects from. Isolated nodes get -1.

pymocd.mmcomo_fronts 

mmcomo_fronts(
    graph: Any,
    pop_size: int = 100,
    num_gens: int = 50,
    cross_rate: float = 0.1,
    mut_rate: float = 0.1,
    gap: int = 10,
    beta: float = 0.05,
) -> typing.Any

MMCoMO's merged rank-1 front, the candidate set mmcomo selects from. Isolated nodes get -1.