Exhaustive API Index

Module moveq_core.equity

compute_gini(values, weights) -> float

Calculates the population-weighted Gini coefficient via numerical integration of the Lorenz curve.

• values (np.ndarray | Sequence[float]): 1D array of non-negative service levels.
• weights (np.ndarray | Sequence[float]): 1D array of non-negative population weights (\(\sum w_i > 0\)).
• Raises: ValueError if lengths mismatch, weights contain negatives or sum to 0, values contain negatives, or inputs contain NaN/Inf.

compute_palma_ratio(values, weights) -> float

Calculates the Palma ratio (top 10% mean service / bottom 40% mean service) with continuous boundary splitting.

compute_concentration_index(service, rank, population, *, rank_direction) -> float

Wagstaff Concentration Index. rank_direction is required. Positive is advantage-concentrated; negative is disadvantage-concentrated. Tied ranks share a group-midpoint fractional rank.

Module moveq_core.score

compute_score(terms, weights, *, labels=None, n_areas=None, context=None) -> ScoreResult

Evaluates a weighted 0-100 composite score, dropping missing terms (None) and renormalizing active design weights.

• terms (dict[str, float | None]): Dictionary mapping indicator keys to values in \([0.0, 1.0]\) or None.
• weights (dict[str, float]): Dictionary mapping indicator keys to strictly positive design weights (\(w_i > 0\)).
• Returns: ScoreResult dataclass containing score, components, note, n_areas, context.

Module moveq_catalogue.catalogue

Catalogue(base_sections: list[str], country: str)

Cross-country questionnaire harmonization registry.

• cat.register(section_id, action, replacement_title=None, note=None)
• cat.validate() -> list[str]
• cat.summary() -> dict[str, int]