fix(nmNum): 补齐 LM 拟合翻译并移除时间分段日志

Bin/Config/Lang/cn/nmNum_cn.ts

@@ -1056,6 +1056,38 @@ Reason: %1</source>
         <source>Unknown reason</source>
         <translation>未知原因</translation>
     </message>
+    <message>
+        <source>Failed to load configuration from data manager</source>
+        <translation>从数据管理器加载配置失败</translation>
+    </message>
+    <message>
+        <source>Auto fitting is already running</source>
+        <translation>自动拟合正在运行</translation>
+    </message>
+    <message>
+        <source>No parameters enabled for optimization</source>
+        <translation>未启用任何优化参数</translation>
+    </message>
+    <message>
+        <source>Target LogLog data is empty or insufficient</source>
+        <translation>目标双对数数据为空或不足</translation>
+    </message>
+    <message>
+        <source>Target LogLog data arrays have inconsistent sizes</source>
+        <translation>目标双对数数据数组长度不一致</translation>
+    </message>
+    <message>
+        <source>Failed to apply final parameters: %1</source>
+        <translation>应用最终参数失败：%1</translation>
+    </message>
+    <message>
+        <source>Failed to apply final parameters due to unknown error</source>
+        <translation>应用最终参数时发生未知错误</translation>
+    </message>
+    <message>
+        <source>Target well name is empty</source>
+        <translation>目标井名称为空</translation>
+    </message>
 </context>
 <context>
     <name>nmCalculationSolver</name>
@@ -4017,6 +4049,14 @@ Supported types: Vertical, Vertical Fractured, and Horizontal Multi-Fractured We
         <source>The minimum value of %1 must be greater than zero for automatic fitting.</source>
         <translation>自动拟合时，%1 的最小值和初始值必须大于零。</translation>
     </message>
+    <message>
+        <source>Data manager is unavailable!</source>
+        <translation>数据管理器不可用！</translation>
+    </message>
+    <message>
+        <source>Gas pseudo-pressure data is unavailable or invalid.</source>
+        <translation>气体拟压力数据不可用或无效。</translation>
+    </message>
 </context>
 <context>
     <name>nmWxAutomaticfitting</name>

Include/nmNum/nmCalculation/nmCalculationAutoFitLM.h

@@ -155,7 +155,6 @@ private:
 		const AutoFitObjectiveBreakdownLM* objectiveBreakdown = nullptr);
 	QVector<double> buildTraceParameterVector(const QVector<double>& selectedParameters) const;
 	void emitRunSummary(bool success, StopReasonLM finalReason);
-	void emitTimeWindowDiagnostics(const AutoFitObjectiveBreakdownLM& breakdown);
 
 	bool validateParameters(const QVector<double>& parameters) const;
 	bool validateLogLogData(const QVector<QVector<double> >& logLogData) const;

Src/nmNum/nmCalculation/nmCalculationAutoFitLM.cpp

@@ -981,7 +981,6 @@ void nmCalculationAutoFitLM::emitRunSummary(bool success, StopReasonLM finalReas
         .arg(m_totalEvaluations)
         .arg(m_successfulEvaluations)
         .arg(m_totalEvaluations - m_successfulEvaluations));
-    emitTimeWindowDiagnostics(m_globalBestObjectiveBreakdown);
 
     if(!m_traceFilePath.isEmpty()) {
         emit logMessageGenerated(tr("Artifacts: trace=%1").arg(m_traceFilePath));
@@ -991,26 +990,6 @@ void nmCalculationAutoFitLM::emitRunSummary(bool success, StopReasonLM finalReas
     }
 }
 
-void nmCalculationAutoFitLM::emitTimeWindowDiagnostics(
-        const AutoFitObjectiveBreakdownLM& breakdown)
-{
-    // 只汇报有效工作点；能量占比说明各时间段对全局误差的贡献。
-    if(!breakdown.valid) {
-        return;
-    }
-    const double totalEnergy = breakdown.total * breakdown.total;
-    for(int k = 0; k < breakdown.timeWindows.size(); ++k) {
-        const AutoFitTimeWindowLM& window = breakdown.timeWindows[k];
-        const double percentage = totalEnergy > 0.0
-                ? 100.0 * window.energy / totalEnergy : 0.0;
-        emit logMessageGenerated(
-                    tr("Time window %1 [%2, %3]: RMS=%4, energy=%5 (%6%)")
-                    .arg(k + 1).arg(window.timeMin, 0, 'g', 6)
-                    .arg(window.timeMax, 0, 'g', 6).arg(window.rmsError, 0, 'e', 4)
-                    .arg(window.energy, 0, 'e', 4).arg(percentage, 0, 'f', 1));
-    }
-}
-
 QVector<double> nmCalculationAutoFitLM::buildTraceParameterVector(const QVector<double>& selectedParameters) const
 {
     // 将 LM 内部使用的“启用参数向量”还原成完整 7 维参数向量。
@@ -1077,7 +1056,7 @@ bool nmCalculationAutoFitLM::loadAllConfigFromDataManager()
         extractUserInitialValues(); // 直接提取初始值，无需条件判断
         return true;
     } catch(...) {
-        m_lastError = "Failed to load configuration from data manager";
+        m_lastError = tr("Failed to load configuration from data manager");
         return false;
     }
 }
@@ -1160,7 +1139,7 @@ bool nmCalculationAutoFitLM::startAutoFitting()
     StopReasonLM finalReason = LM_CONTINUE_OPTIMIZATION;
 
     if(m_isRunning) {
-        m_lastError = "Auto fitting is already running";
+        m_lastError = tr("Auto fitting is already running");
         return false;
     }
 
@@ -1175,26 +1154,26 @@ bool nmCalculationAutoFitLM::startAutoFitting()
         emit logMessageGenerated(tr("Enabled parameters count: %1").arg(enabledParams));
 
         if(enabledParams == 0) {
-            m_lastError = "No parameters enabled for optimization";
+            m_lastError = tr("No parameters enabled for optimization");
             emit logMessageGenerated(tr("ERROR: No parameters enabled for optimization"));
             return false;
         }
 
         if(m_targetLogLogData.size() < 3) {
-            m_lastError = "Target LogLog data is empty or insufficient";
+            m_lastError = tr("Target LogLog data is empty or insufficient");
             emit logMessageGenerated(tr("ERROR: Target LogLog data is empty or insufficient"));
             return false;
         }
 
         if(m_targetLogLogData[0].size() != m_targetLogLogData[1].size() ||
                 m_targetLogLogData[0].size() != m_targetLogLogData[2].size()) {
-            m_lastError = "Target LogLog data arrays have inconsistent sizes";
+            m_lastError = tr("Target LogLog data arrays have inconsistent sizes");
             emit logMessageGenerated(tr("ERROR: Target LogLog data arrays have inconsistent sizes"));
             return false;
         }
 
         if(m_targetWellName.isEmpty()) {
-            m_lastError = "Target well name is empty";
+            m_lastError = tr("Target well name is empty");
             emit logMessageGenerated(tr("ERROR: Target well name is empty"));
             return false;
         }
@@ -1258,7 +1237,6 @@ bool nmCalculationAutoFitLM::startAutoFitting()
                                           m_globalBestLogLogData,
                                           0,
                                           m_globalBestFitness);
-                    emitTimeWindowDiagnostics(m_globalBestObjectiveBreakdown);
                 } else {
                     m_hasValidUserSolution = false;
                     emit logMessageGenerated(tr("Initial solution evaluation failed"));
@@ -1388,12 +1366,12 @@ bool nmCalculationAutoFitLM::startAutoFitting()
             }
         } catch(const std::exception& e) {
             finalFullSolverSucceeded = false;
-            m_lastError = QString("Failed to apply final parameters: %1").arg(e.what());
+            m_lastError = tr("Failed to apply final parameters: %1").arg(e.what());
             emit logMessageGenerated(
                 tr("ERROR: Failed to apply final parameters: %1").arg(e.what()));
         } catch(...) {
             finalFullSolverSucceeded = false;
-            m_lastError = "Failed to apply final parameters due to unknown error";
+            m_lastError = tr("Failed to apply final parameters due to unknown error");
             emit logMessageGenerated(
                 tr("ERROR: Unknown error applying final parameters"));
         }
@@ -1683,7 +1661,6 @@ StopReasonLM nmCalculationAutoFitLM::runTrustRegionFitting()
         m_globalBestFitness = evaluation.fitness;
         m_globalBestObjectiveBreakdown = evaluation.breakdown;
         m_globalBestLogLogData = evaluation.curve;
-        emitTimeWindowDiagnostics(evaluation.breakdown);
         emit bestCurveUpdated(m_targetLogLogData,
                               m_globalBestLogLogData,
                               m_currentIteration + 1,
@@ -3960,11 +3937,6 @@ double nmCalculationAutoFitLM::calculateLogLogCurveError(
                 m_comparisonTimeMin = overlapMinX;
                 m_comparisonTimeMax = overlapMaxX;
                 writeTraceMetaFile();
-                emit logMessageGenerated(
-                            tr("Fixed LM comparison time range: [%1, %2]; %3 windows, %4% overlap")
-                            .arg(overlapMinX, 0, 'g', 8).arg(overlapMaxX, 0, 'g', 8)
-                            .arg(kAutoFitTimeWindowCount)
-                            .arg(kAutoFitTimeWindowOverlapRatio * 100.0, 0, 'f', 0));
             }
         }
         m_lastObjectiveBreakdown = breakdown;