Merge branch 'feature/MultiWellAutoFit-20260805' into develop
# Conflicts: # Bin/Config/Lang/cn/nmNum_cn.qm resolved by feature/MultiWellAutoFit-20260805 versionfeature/PebiSolver-Integration-20260818
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#ifndef NMCALCULATIONAUTOFITGA_H
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#define NMCALCULATIONAUTOFITGA_H
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#include <QObject>
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#include <QVector>
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#include <QPointF>
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#include <QString>
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#include <QTimer>
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#include <QApplication>
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#include <QDateTime>
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#include <QCoreApplication>
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#include <QDir>
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#include <QDebug>
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#include <QTime>
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#include "nmCalculation_global.h"
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class nmDataWellBase;
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enum StopReasonGA {
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GA_CONTINUE_OPTIMIZATION = 0,
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GA_TARGET_ACHIEVED,
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GA_TRUE_CONVERGENCE,
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GA_LOCAL_OPTIMUM,
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GA_MAX_ITERATIONS,
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GA_USER_STOPPED,
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GA_CONSECUTIVE_FAILURES,
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GA_OPTIMIZATION_FAILED
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};
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struct GAIndividual
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{
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QVector<double> genes; // 基因（参数值）
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double fitness; // 适应度值
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bool isEvaluated; // 是否已评估
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GAIndividual() : fitness(1e10), isEvaluated(false) {}
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};
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class NMCALCULATION_EXPORT nmCalculationAutoFitGA : public QObject
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{
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Q_OBJECT
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public:
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explicit nmCalculationAutoFitGA(QObject* parent = nullptr);
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virtual ~nmCalculationAutoFitGA();
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// ==================== 公共接口方法 ====================
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void setTargetLogLogData(const QVector<QVector<double>>& targetData);
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bool startAutoFitting();
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void stopFitting();
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bool isRunning() const;
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int getCurrentGeneration() const;
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QVector<double> getBestSolution() const;
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double getBestFitness() const;
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QString getLastError() const;
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void resetOptimizer();
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void setGATargetWellName(const QString& wellName);
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signals:
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void progressUpdated(int generation, double bestFitness);
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void fittingFinished(bool success, const QString& message);
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void logMessageGenerated(const QString& message);
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private slots:
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void updateProgress();
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private:
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// 临时目录管理
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void initializeTemporaryDirectory();
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void cleanupTemporaryDirectory();
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bool removeDirectoryRecursively(const QString& path);
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// ==================== 数据加载方法 ====================
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// 从数据管理器加载所有配置
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bool loadAllConfigFromDataManager();
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// 加载优化配置
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void loadOptimizationConfig();
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// 加载参数边界
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void loadParameterBounds();
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// 提取用户初始值
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void extractUserInitialValues();
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// ==================== 遗传算法核心方法 ====================
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// 初始化种群
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void initializePopulation();
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// 评估基因
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double evaluateGenes(const QVector<double>& genes);
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// 评估个体
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double evaluateIndividual(GAIndividual& individual);
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// 评估种群
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void evaluatePopulation();
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// 选择操作
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int tournamentSelection();
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int rouletteWheelSelection();
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// 交叉操作
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void crossover(const GAIndividual& parent1, const GAIndividual& parent2,
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GAIndividual& offspring1, GAIndividual& offspring2);
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void singlePointCrossover(const GAIndividual& parent1, const GAIndividual& parent2,
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GAIndividual& offspring1, GAIndividual& offspring2);
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void uniformCrossover(const GAIndividual& parent1, const GAIndividual& parent2,
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GAIndividual& offspring1, GAIndividual& offspring2);
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// 变异操作
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void mutate(GAIndividual& individual);
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void gaussianMutation(GAIndividual& individual);
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void polynomialMutation(GAIndividual& individual);
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// 精英保留
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void applyElitism(QVector<GAIndividual>& newPopulation);
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// 更新种群统计
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void updatePopulationStatistics();
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// 收敛检查
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bool checkConvergence();
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// 自适应参数更新
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void adaptiveParameterUpdate(int generation);
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// ==================== 智能收敛判断方法 ====================
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// 分析优化状态
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StopReasonGA analyzeOptimizationStatus();
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// 检查真收敛
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bool checkTrueConvergence() const;
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// 检查局部最优陷阱
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bool checkLocalOptimumTrap() const;
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// 计算种群多样性
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double calculatePopulationDiversity() const;
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// 计算适应度方差
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double calculateFitnessVariance(int windowSize) const;
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// 计算长期改进
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double calculateLongTermImprovement(int windowSize) const;
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// 更新收敛指标
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void updateConvergenceMetrics();
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// 最终结果验证和保护
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void validateAndProtectFinalResult();
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// ==================== 参数处理方法 ====================
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// 参数验证
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bool validateParameters(const QVector<double>& parameters) const;
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// 双对数数据验证
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bool validateLogLogData(const QVector<QVector<double>>& logLogData) const;
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// 初始值验证
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bool validateInitialValues() const;
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// 应用参数到数据管理器
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void applyParametersToDataManager(const QVector<double>& parameters);
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// 更新储层参数
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void updateReservoirParameters(const QVector<double>& parameters);
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// 更新井参数
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void updateWellParameters(const QVector<double>& parameters);
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// 更新井到数据管理器
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void updateWellToDataManager(nmDataWellBase* pWell);
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// 参数边界约束
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void clampToLimits(QVector<double>& parameters) const;
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// ==================== 求解器相关方法 ====================
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// 运行求解器
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QVector<QVector<double>> runSolver();
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// 运行EXE求解器
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QVector<QVector<double>> runSolverExe();
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// 运行Dll求解器
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QVector<QVector<double>> runSolverDll();
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// 验证求解器结果
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bool validateSolverResult(const QVector<QVector<double>>& result) const;
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// ==================== 数据处理方法 ====================
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// 插值数据
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QVector<QPointF> interpolateData(const QVector<QPointF>& source,
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const QVector<double>& targetX) const;
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// 计算双对数曲线误差
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double calculateLogLogCurveError(const QVector<QVector<double>>& target,
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const QVector<QVector<double>>& result) const;
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// 计算曲线误差
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double calculateCurveError(const QVector<QPointF>& curve1,
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const QVector<QPointF>& curve2) const;
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// ==================== 工具方法 ====================
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// 生成0-1随机数
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double random01() const;
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// 高斯随机数
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double gaussianRandom(double mean, double stddev) const;
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// 获取启用参数数量
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int getEnabledParameterCount() const;
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// 保存优化结果
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void saveOptimizationResult();
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private:
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// ==================== 常量定义 ====================
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static const double MIN_FITNESS_IMPROVEMENT;
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static const double MUTATION_STRENGTH;
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static const int CONVERGENCE_CHECK_INTERVAL;
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static const int MAX_STAGNATION_GENERATIONS;
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// ==================== 核心状态变量 ====================
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bool m_isRunning; // 是否正在运行
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bool m_shouldStop; // 是否应该停止
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bool m_isPaused; // 是否暂停
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int m_currentGeneration; // 当前代数
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// 适应度统计
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double m_bestFitness; // 最优适应度
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double m_worstFitness; // 最差适应度
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double m_averageFitness; // 平均适应度
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double m_previousBestFitness; // 上一代最优适应度
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// ==================== GA算法参数 ====================
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int m_populationSize; // 种群大小
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int m_maxGenerations; // 最大代数
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double m_targetError; // 目标误差
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double m_crossoverRate; // 交叉概率
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double m_mutationRate; // 变异概率
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double m_elitismRate; // 精英保留比例
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int m_tournamentSize; // 锦标赛选择大小
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bool m_useUniformCrossover; // 是否使用均匀交叉
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// ==================== 种群和个体 ====================
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QVector<GAIndividual> m_population; // 当前种群
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QVector<GAIndividual> m_eliteIndividuals; // 精英个体
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GAIndividual m_bestIndividual; // 全局最优个体
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// ==================== 评估统计 ====================
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int m_totalEvaluations; // 总评估次数
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int m_successfulEvaluations; // 成功评估次数
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int m_evaluationInProgress; // 正在进行的评估计数
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int m_consecutiveFailures; // 连续失败次数
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// ==================== 精英保护相关 ====================
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QVector<double> m_initialValues; // 用户初始参数值
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QVector<double> m_userInitialSolution; // 用户初始解
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double m_userInitialFitness; // 用户初始适应度
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int m_consecutiveFailedGenerations; // 连续失败代数
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int m_maxConsecutiveFailures; // 最大允许连续失败数
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bool m_hasValidUserSolution; // 是否有有效的用户解
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double m_improvementThreshold; // 改进阈值
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// ==================== 收敛判断相关 ====================
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double m_diversityThreshold; // 多样性阈值
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double m_convergenceVarianceThreshold; // 收敛方差阈值
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int m_trueConvergenceWindow; // 真收敛判断窗口
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int m_localOptimumWindow; // 局部最优判断窗口
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double m_nearTargetFactor; // 接近目标的因子
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double m_farTargetFactor; // 远离目标的因子
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// ==================== 历史记录 ====================
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QVector<double> m_convergenceHistory; // 收敛历史
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QVector<double> m_diversityHistory; // 多样性历史
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// ==================== 参数配置 ====================
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QVector<bool> m_parameterSelected; // 参数选择状态
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QVector<double> m_parameterLower; // 参数下界
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QVector<double> m_parameterUpper; // 参数上界
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QVector<int> m_enabledParamIndices; // 启用参数索引
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// ==================== 目标数据 ====================
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QVector<QVector<double>> m_targetLogLogData; // 目标双对数数据
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// ==================== 其他 ====================
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QString m_lastError; // 最后错误信息
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QTimer* m_progressTimer; // 进度更新定时器
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// DLL求解器需要的临时目录
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QString m_tempDirectory;
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QString m_targetWellName;// 目标井名称
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};
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#endif // NMCALCULATIONAUTOFITGA_H
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