mercurial.hierarchy.transition module

Level transition operator for constraint propagation between LADDER levels.

class mercurial.hierarchy.transition.LevelTransitionOperator(coupling_strength: float = 0.1)

Bases: object

Implements T_{i→j}[P] = Π_j ◦ Φ_{i→j} ◦ Π_i^{-1}[P]

where: - Π_i projects onto level i degrees of freedom - Φ_{i→j} is the constraint propagation map

Methods

apply_transition(source_pattern, ...[, ...])	Apply T_{i→j} to source pattern, producing a pattern at target level.
constraint_propagation(source_state, ...)	Φ_{i→j}: Apply constraints from source to target.
project_to_level(pattern, target_level[, ...])	Π_j: Project pattern state variables to a different level's dimensionality.

apply_transition(source_pattern: Pattern, target_level: int, target_constraints: Constraints, current_level: int | None = None) → Pattern

Apply T_{i→j} to source pattern, producing a pattern at target level.

constraint_propagation(source_state: ndarray, target_constraints: Constraints) → ndarray

Φ_{i→j}: Apply constraints from source to target. Simplified: modify target state to satisfy source constraints.

project_to_level(pattern: Pattern, target_level: int, current_level: int | None = None) → ndarray

Π_j: Project pattern state variables to a different level’s dimensionality. Simplified: use linear interpolation/downsampling based on complexity ratio.