"""CultivarStabilityScore + EvolutionGate — gate evolutivo de culturas (d3). MARS_SYSTEM_CONTRACT.yaml · operator_decisions.d3_gate_evolution Decisão do operador (2026-09-28): transições de cultura são irreversíveis (batata/trigo consomem solo não-reciclável) — só prossiga por GATE DE DADOS: - algae_to_potato: stability >= 0.90 por 55.7 sols, epsilon < 0.15, reservas energia >= 50%, água >= 60%, nutrientes >= 30% - potato_to_wheat: stability >= 0.95 por 111.4 sols, epsilon < 0.10, reservas energia >= 70%, água >= 80%, nutrientes >= 50%, solo >= 100 m³ Score ponderado: yield_consistency 0.30, contamination_resistance 0.25, energy_efficiency 0.20, nutrient_uptake 0.15, stress_tolerance 0.10. """ from __future__ import annotations from dataclasses import dataclass, field from typing import Dict, List, Tuple import numpy as np STABILITY_WEIGHTS = { "yield_consistency": 0.30, "contamination_resistance": 0.25, "energy_efficiency": 0.20, "nutrient_uptake": 0.15, "stress_tolerance": 0.10, } GATE_THRESHOLDS = { "algae_to_potato": { "stability_score_min": 0.90, "duration_min_sols": 55.7, "epsilon_max": 0.15, "energy_reserve_min": 0.60, # ação E5 (margem black swan) "water_reserve_min": 0.60, "nutrient_reserve_min": 0.30, "max_sectors_per_cycle": 2, "rollback_possible": False, }, "potato_to_wheat": { "stability_score_min": 0.95, "duration_min_sols": 111.4, "epsilon_max": 0.10, "energy_reserve_min": 0.70, "water_reserve_min": 0.80, "nutrient_reserve_min": 0.50, "soil_volume_min_m3": 100.0, "max_sectors_per_cycle": 3, "rollback_possible": False, }, } class CultivarStabilityScore: """Calcula o score de estabilidade [0,1] de uma cultivar para gate.""" def __init__(self, weights: Dict[str, float] | None = None) -> None: self.weights = dict(weights or STABILITY_WEIGHTS) def calculate(self, cultivar_data: Dict) -> Tuple[float, Dict[str, float]]: """Score ponderado a partir de dados históricos da cultivar.""" yield_var = float(np.var(cultivar_data.get("yield_kg_m2_day", [0.0]))) yield_score = 1.0 - min(1.0, yield_var / 0.10) contamination_loss = float(cultivar_data.get("contamination_loss_pct", 100.0)) contamination_score = 1.0 - min(1.0, contamination_loss / 5.0) energy_eff = float(cultivar_data.get("energy_efficiency_pct", 0.0)) / 80.0 energy_score = min(1.0, energy_eff) nutrient_eff = float(cultivar_data.get("nutrient_uptake_efficiency", 0.0)) nutrient_score = min(1.0, nutrient_eff / 0.70) stress_recovery = float(cultivar_data.get("post_storm_recovery_days", 10.0)) stress_score = max(0.0, 1.0 - stress_recovery / 10.0) scores = { "yield_consistency": yield_score, "contamination_resistance": contamination_score, "energy_efficiency": energy_score, "nutrient_uptake": nutrient_score, "stress_tolerance": stress_score, } total = sum(scores[k] * self.weights[k] for k in scores) return float(total), scores @dataclass class EvolutionGate: """Gate de dados para transição de cultura dominante (irreversível).""" stability: CultivarStabilityScore = field(default_factory=CultivarStabilityScore) # Radiação modulada (calibração E2-REF v3 — PDF operador 2026-09-28): # blindagem 0.0 (exposto) a 1.0 (total); a máquina modula a blindagem # para acelerar/desacelerar a mutagênese conforme a necessidade evolutiva. radiation_shielding: float = 0.0 mu_bp: float = 1.5e-6 # wheat cosmic rays 1.79e-6 (PMC9131052) -> Spirulina genome_loci: int = 1000 dose_ref_mSv_gen: float = 50.0 # calibração wheat def effective_dose(self, dose_mars_mSv_day: float = 0.67) -> float: """Dose efetiva após blindagem (regolito/água/compósito).""" return dose_mars_mSv_day * (1.0 - self.radiation_shielding) def mutation_rate(self, dose_effective_mSv_day: float, generation_days: float = 10.0) -> float: """μ_eff = μ_bp × L × (D×t_gen / D_ref) — E2-REF v3 (PDF operador).""" return self.mu_bp * self.genome_loci * (dose_effective_mSv_day * generation_days / self.dose_ref_mSv_gen) def check(self, transition: str, data: Dict) -> Dict: """Avalia o gate para uma transição. data carrega métricas reais.""" if transition not in GATE_THRESHOLDS: raise ValueError(f"transição desconhecida: {transition}") thr = GATE_THRESHOLDS[transition] score, breakdown = self.stability.calculate(data.get("cultivar", {})) checks = { "stability_score": score >= thr["stability_score_min"], "duration_sols": data.get("duration_sols", 0) >= thr["duration_min_sols"], "epsilon": data.get("epsilon", 1.0) < thr["epsilon_max"], "energy_reserve": data.get("energy_reserve", 0.0) >= thr["energy_reserve_min"], "water_reserve": data.get("water_reserve", 0.0) >= thr["water_reserve_min"], "nutrient_reserve": data.get("nutrient_reserve", 0.0) >= thr["nutrient_reserve_min"], } if "soil_volume_min_m3" in thr: checks["soil_volume_m3"] = data.get("soil_volume_m3", 0.0) >= thr["soil_volume_min_m3"] passed = all(checks.values()) return { "transition": transition, "score": round(score, 4), "score_breakdown": {k: round(v, 4) for k, v in breakdown.items()}, "thresholds": thr, "checks": checks, "passed": passed, "irreversible": not thr["rollback_possible"], "max_sectors_per_cycle": thr["max_sectors_per_cycle"], } def food_gate(self, plant_protein_kg_day: float, mealworm_protein_kg_day: float, n_people: int, min_fraction: float = 0.95) -> Dict: """Gate de comida/proteína — conglomerado Lunar Palace 1. LP1 fechou ~100% da comida com plantas + mealworms. Requisito: ~0.06 kg proteína/pessoa-dia; a fração de mealworm no total mede a dependência da cadeia animal (resíduo -> proteína). """ total = plant_protein_kg_day + mealworm_protein_kg_day need = 0.06 * n_people fraction = total / need if need else 0.0 return {"total_protein_kg_day": round(total, 4), "need_kg_day": round(need, 4), "mealworm_fraction": round(mealworm_protein_kg_day / max(total, 1e-9), 4), "fraction_of_need": round(fraction, 4), "passed": fraction >= min_fraction, "min_fraction": min_fraction}