fix: rank.

controllers/step_train.go

@@ -12,7 +12,6 @@ import (
 	"log"
 	"math"
 	"net/http"
-	"sort"
 	"strconv"
 	"strings"
 )
@@ -741,99 +740,99 @@ func (tc *StepTrainingController) GetTrainingRank(c *gin.Context) {
 		c.JSON(http.StatusInternalServerError, gin.H{"error": "获取回归结果失败：" + err.Error()})
 		return
 	}
+	// 获取指定训练的基准值
+	var baseValue float64
+	baseQuery := tc.DB.Model(&models.RegressionResult{}).
+		Select(getValueColumn(regType)).
+		Where("train_id = ?", trainId)
 
-	// 获取排名数据
-	var records []models.RegressionResult
-	query := tc.DB.Model(&models.RegressionResult{})
-	switch regType {
-	case models.LinearRegression:
-		query = query.Where("slope IS NOT NULL").
-			Select("train_id, slope, regression_type")
-	case models.QuadraticRegression:
-		query = query.Where("quadratic_a IS NOT NULL AND quadratic_a < 0").
-			Select("train_id, quadratic_a, regression_type")
-	}
-	if err := query.Find(&records).Error; err != nil {
-		c.JSON(http.StatusInternalServerError, gin.H{"error": "查询排名数据失败"})
+	if err := baseQuery.Row().Scan(&baseValue); err != nil {
+		if errors.Is(err, gorm.ErrRecordNotFound) {
+			c.JSON(http.StatusNotFound, gin.H{"error": "指定的训练数据不存在"})
+			return
+		}
+		c.JSON(http.StatusInternalServerError, gin.H{"error": "获取基准数据失败"})
 		return
 	}
 
-	if len(records) == 0 {
-		c.JSON(http.StatusNotFound, gin.H{"error": "无可用数据计算排名"})
+	// 在数据库中进行排名计算
+	var rank struct {
+		BetterCount int64
+		Total       int64
+	}
+
+	// 动态生成比较条件
+	betterCondition := fmt.Sprintf("%s %s ?",
+		getValueColumn(regType),
+		getComparisonOperator(regType))
+
+	totalQuery := tc.DB.Model(&models.RegressionResult{}).
+		Where(getTypeCondition(regType))
+
+	if err := totalQuery.Count(&rank.Total).Error; err != nil {
+		c.JSON(http.StatusInternalServerError, gin.H{"error": "统计总数失败"})
 		return
 	}
 
-	// 排序逻辑
-	sort.Slice(records, func(i, j int) bool {
-		if regType == models.LinearRegression {
-			// 线性回归：斜率越小排名越高
-			return compareFloatPtr(records[i].Slope, records[j].Slope, true)
-		} else {
-			// 二次回归：|a|越大排名越高（a为负值）
-			return compareQuadraticA(records[i].QuadraticA, records[j].QuadraticA)
-		}
-	})
-
-	// 计算排名（处理并列）
-	currentRank := 1
-	rankMap := make(map[uint]int)
-	lastValue := math.Inf(-1) // 初始极小值
-
-	for i, record := range records {
-		var currentValue float64
-		var isSet bool
-
-		switch regType {
-		case models.LinearRegression:
-			if record.Slope != nil {
-				currentValue = *record.Slope
-				isSet = true
-			}
-		case models.QuadraticRegression:
-			if record.QuadraticA != nil {
-				currentValue = math.Abs(*record.QuadraticA)
-				isSet = true
-			}
-		}
-
-		if !isSet {
-			continue // 跳过空值（理论上不应出现）
-		}
-
-		if i == 0 {
-			rankMap[record.TrainId] = currentRank
-			lastValue = currentValue
-			continue
-		}
-
-		// 值变化时更新排名（跳过重复值）
-		if math.Abs(currentValue-lastValue) > 1e-9 {
-			currentRank = i + 1
-			lastValue = currentValue
-		}
-
-		rankMap[record.TrainId] = currentRank
-	}
-
-	// 获取指定训练记录的排名
-	rank, exists := rankMap[trainId]
-	if !exists {
-		c.JSON(http.StatusInternalServerError, gin.H{"error": "训练记录未包含在排名中"})
+	if err := tc.DB.Model(&models.RegressionResult{}).
+		Where(getTypeCondition(regType)).
+		Where(betterCondition, baseValue).
+		Count(&rank.BetterCount).Error; err != nil {
+		c.JSON(http.StatusInternalServerError, gin.H{"error": "计算排名失败"})
 		return
 	}
 
+	// 计算实际排名 (并列排名)
+	currentRank := rank.BetterCount + 1
+
 	// 返回响应
 	c.JSON(http.StatusOK, gin.H{
 		"message": "排名查询成功",
 		"data": gin.H{
 			"trainId": trainId,
 			"type":    regressionType,
-			"rank":    rank,
-			"total":   len(records),
+			"rank":    currentRank,
+			"total":   rank.Total,
 		},
 	})
 }
 
+// 辅助函数：获取排序字段名
+func getValueColumn(regType models.RegressionType) string {
+	switch regType {
+	case models.LinearRegression:
+		return "slope"
+	case models.QuadraticRegression:
+		return "ABS(quadratic_a)" // 计算绝对值
+	default:
+		return ""
+	}
+}
+
+// 辅助函数：获取比较操作符
+func getComparisonOperator(regType models.RegressionType) string {
+	switch regType {
+	case models.LinearRegression:
+		return "<" // 线性回归：值越小越好
+	case models.QuadraticRegression:
+		return ">" // 二次回归：绝对值越大越好
+	default:
+		return ""
+	}
+}
+
+// 辅助函数：获取类型条件
+func getTypeCondition(regType models.RegressionType) string {
+	switch regType {
+	case models.LinearRegression:
+		return "slope IS NOT NULL"
+	case models.QuadraticRegression:
+		return "quadratic_a IS NOT NULL AND quadratic_a < 0" // 确保是负值
+	default:
+		return ""
+	}
+}
+
 // 辅助函数：比较浮点指针（用于线性回归）
 func compareFloatPtr(a, b *float64, ascending bool) bool {
 	if a == nil && b == nil {