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1
.gitignore
vendored
1
.gitignore
vendored
@ -1,3 +1,4 @@
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.idea
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hr_receiver.iml
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main.go.bak
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config.yaml
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895
controllers/step_train.go
Normal file
895
controllers/step_train.go
Normal file
@ -0,0 +1,895 @@
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package controllers
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import (
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"errors"
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"fmt"
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"github.com/gin-gonic/gin"
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"github.com/sajari/regression"
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"gorm.io/gorm"
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"gorm.io/gorm/clause"
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"hr_receiver/config"
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"hr_receiver/models"
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"log"
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"math"
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"net/http"
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"strconv"
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"strings"
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)
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type StepTrainingController struct {
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DB *gorm.DB
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}
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func NewStepTrainingController() *StepTrainingController {
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return &StepTrainingController{DB: config.DB}
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}
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// 接收训练记录
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func (tc *StepTrainingController) CreateTrainingRecord(c *gin.Context) {
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var record models.StepTrainRecord
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// 绑定并验证JSON数据
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if err := c.ShouldBindJSON(&record); err != nil {
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c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
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return
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}
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// 使用事务保存数据[4](@ref)
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err := tc.DB.Transaction(func(tx *gorm.DB) error {
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// 保存主记录
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if err := tx.Clauses(clause.OnConflict{
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Columns: []clause.Column{{Name: "train_id"}}, // 指定冲突的列
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DoUpdates: clause.Assignments(map[string]interface{}{
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"max_heart_rate": record.MaxHeartRate,
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"start_time": record.StartTime,
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"end_time": record.EndTime,
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"duration": record.Duration,
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"dead_zone": record.DeadZone,
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"name": record.Name,
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"evaluation": record.Evaluation,
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}),
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}).Omit("HeartRates", "StrideFreqs").Create(&record).Error; err != nil {
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return err
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}
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// 保存关联的心率数据
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for i := range record.HeartRates {
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if err := tx.Clauses(
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clause.OnConflict{
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Columns: []clause.Column{{Name: "identifier"}}, // 指定冲突的列
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DoUpdates: clause.Assignments(map[string]interface{}{"heart_rate_type": record.HeartRates[i].HeartRateType, "value": record.HeartRates[i].Value, "time": record.HeartRates[i].Time}),
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},
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).Create(&record.HeartRates[i]).Error; err != nil {
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return err
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}
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}
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for i := range record.StrideFreqs {
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if err := tx.Clauses(
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clause.OnConflict{
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Columns: []clause.Column{{Name: "identifier"}}, // 指定冲突的列
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DoUpdates: clause.Assignments(map[string]interface{}{"value": record.StrideFreqs[i].Value, "time": record.StrideFreqs[i].Time}),
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},
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).Create(&record.StrideFreqs[i]).Error; err != nil {
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return err
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}
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}
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return nil
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})
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// ====== 新增部分：启动异步回归计算 ======
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go func() {
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// 查询完整数据（需要关联的心率和步频数据）
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var fullRecord models.StepTrainRecord
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if err := tc.DB.
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Where("train_id = ?", record.TrainId).
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Preload("HeartRates", "heart_rate_type = ?", 1). // 只要有效心率
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Preload("StrideFreqs", "predict_value = ?", 1). // 只要有效步频
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First(&fullRecord).Error; err != nil {
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log.Printf("训练记录%d查询失败，无法计算回归: %v", record.TrainId, err)
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return
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}
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// 检查数据是否满足计算条件
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if len(fullRecord.HeartRates) == 0 || len(fullRecord.StrideFreqs) == 0 {
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log.Printf("训练记录%d缺少心率或步频数据，跳过回归计算", record.TrainId)
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return
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}
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// 计算并保存回归结果
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if _, err := tc.GetOrCalculateRegression(fullRecord.TrainId); err != nil {
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log.Printf("训练记录%d回归计算失败: %v", fullRecord.TrainId, err)
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} else {
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log.Printf("训练记录%d回归结果已保存", fullRecord.TrainId)
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}
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}()
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if err != nil {
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c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
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return
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}
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c.JSON(http.StatusCreated, gin.H{
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"message": "数据保存成功",
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"id": record.TrainId,
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})
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}
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func (tc *StepTrainingController) GetTrainingRecords(c *gin.Context) {
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// 定义分页参数结构
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type PaginationParams struct {
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PageNum int `form:"pageNum,default=1"` // 页码，默认第一页
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PageSize int `form:"pageSize,default=10"` // 每页数量，默认10条
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}
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var params PaginationParams
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if err := c.ShouldBindQuery(¶ms); err != nil {
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c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
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return
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}
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// 验证分页参数有效性
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if params.PageNum < 1 {
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params.PageNum = 1
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}
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if params.PageSize < 1 || params.PageSize > 100 {
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params.PageSize = 10
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}
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// 计算偏移量
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offset := (params.PageNum - 1) * params.PageSize
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var (
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records []models.StepTrainRecord
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totalRows int64
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)
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// 获取总记录数
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if err := tc.DB.Model(&models.StepTrainRecord{}).Count(&totalRows).Error; err != nil {
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c.JSON(http.StatusInternalServerError, gin.H{"error": "获取记录总数失败"})
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return
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}
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// 查询分页数据（按开始时间倒序排列）
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result := tc.DB.
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Order("start_time DESC"). // 按开始时间倒序
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Offset(offset).
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Limit(params.PageSize).
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Find(&records)
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if result.Error != nil {
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c.JSON(http.StatusInternalServerError, gin.H{"error": result.Error.Error()})
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return
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}
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// 计算总页数
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totalPages := int(math.Ceil(float64(totalRows) / float64(params.PageSize)))
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c.JSON(http.StatusOK, gin.H{
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"message": "查询成功",
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"data": gin.H{
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"list": records,
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"pagination": gin.H{
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"currentPage": params.PageNum,
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"pageSize": params.PageSize,
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"totalPage": totalPages,
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"totalList": totalRows,
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},
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},
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})
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}
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func (tc *StepTrainingController) GetTrainingRecordByTrainId(c *gin.Context) {
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// 从URL路径参数获取trainId
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trainId := c.Param("trainId")
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if trainId == "" {
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c.JSON(http.StatusBadRequest, gin.H{"error": "训练ID不能为空"})
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return
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}
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// 将字符串trainId转换为uint类型
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tid, err := strconv.ParseInt(trainId, 10, 64)
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if err != nil {
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c.JSON(http.StatusBadRequest, gin.H{"error": "无效的训练ID格式"})
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return
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}
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var record models.StepTrainRecord
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// 查询主记录并预加载关联的心率和步频数据
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result := tc.DB.Where("train_id = ?", uint(tid)).
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Preload("HeartRates").
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Preload("StrideFreqs").
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First(&record)
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if result.Error != nil {
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if errors.Is(result.Error, gorm.ErrRecordNotFound) {
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c.JSON(http.StatusNotFound, gin.H{"error": "训练记录不存在"})
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} else {
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c.JSON(http.StatusInternalServerError, gin.H{"error": result.Error.Error()})
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}
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return
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}
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// 成功返回数据
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c.JSON(http.StatusOK, gin.H{
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"message": "查询成功",
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"data": record,
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})
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}
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// 定义结构体
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type SpeedSegment struct {
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Duration float64
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Speed float64
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}
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// 实现线性回归算法
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func performLinearRegression(averages []map[float64]float64) models.RegressionResult {
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if len(averages) == 0 {
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return models.RegressionResult{
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Equation: "无数据",
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||||
}
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||||
}
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// 收集数据点
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var points []struct{ x, y float64 }
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for _, m := range averages {
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for x, y := range m {
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points = append(points, struct{ x, y float64 }{x, y})
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||||
}
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||||
}
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// 使用回归库计算
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r := new(regression.Regression)
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r.SetObserved("y")
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r.SetVar(0, "x")
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for _, p := range points {
|
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r.Train(regression.DataPoint(p.y, []float64{p.x}))
|
||||
}
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||||
|
||||
if err := r.Run(); err != nil {
|
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log.Printf("线性回归计算失败: %v", err)
|
||||
return models.RegressionResult{
|
||||
Equation: "计算失败",
|
||||
}
|
||||
}
|
||||
|
||||
// 创建结果
|
||||
slope := r.Coeff(1)
|
||||
intercept := r.Coeff(0)
|
||||
r2 := r.R2
|
||||
return models.RegressionResult{
|
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RegressionType: models.LinearRegression,
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Slope: &slope,
|
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Intercept: &intercept,
|
||||
RSquared: &r2,
|
||||
Equation: r.Formula,
|
||||
}
|
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}
|
||||
|
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// 实现对数和二次回归算法
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// 对数回归算法
|
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func performLogarithmicRegression(averages []map[float64]float64) models.RegressionResult {
|
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if len(averages) == 0 {
|
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return models.RegressionResult{
|
||||
Equation: "无数据",
|
||||
}
|
||||
}
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||||
|
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// 收集数据点
|
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r := new(regression.Regression)
|
||||
r.SetObserved("y")
|
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r.SetVar(0, "log(x+1)")
|
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|
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for _, m := range averages {
|
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for speed, hr := range m {
|
||||
logSpeed := math.Log(speed + 1)
|
||||
r.Train(regression.DataPoint(hr, []float64{logSpeed}))
|
||||
}
|
||||
}
|
||||
|
||||
if err := r.Run(); err != nil {
|
||||
log.Printf("对数回归计算失败: %v", err)
|
||||
return models.RegressionResult{
|
||||
Equation: "计算失败",
|
||||
}
|
||||
}
|
||||
|
||||
// 创建结果
|
||||
logA := r.Coeff(1)
|
||||
logB := r.Coeff(0)
|
||||
r2 := r.R2
|
||||
return models.RegressionResult{
|
||||
RegressionType: models.LogarithmicRegression,
|
||||
LogA: &logA,
|
||||
LogB: &logB,
|
||||
RSquared: &r2,
|
||||
Equation: r.Formula,
|
||||
}
|
||||
}
|
||||
|
||||
// 二次回归算法
|
||||
//func performQuadraticRegression(averages []map[float64]float64) models.RegressionResult {
|
||||
// if len(averages) == 0 {
|
||||
// return models.RegressionResult{
|
||||
// Equation: "无数据",
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// // 收集数据点
|
||||
// r := new(regression.Regression)
|
||||
// r.SetObserved("y")
|
||||
// r.SetVar(0, "x")
|
||||
// r.SetVar(1, "x²")
|
||||
//
|
||||
// for _, m := range averages {
|
||||
// for speed, hr := range m {
|
||||
// speedSq := math.Pow(speed, 2)
|
||||
// r.Train(regression.DataPoint(hr, []float64{speed, speedSq}))
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// if err := r.Run(); err != nil {
|
||||
// log.Printf("二次回归计算失败: %v", err)
|
||||
// return models.RegressionResult{
|
||||
// Equation: "计算失败",
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// // 创建结果
|
||||
// a := r.Coeff(2)
|
||||
// b := r.Coeff(1)
|
||||
// c := r.Coeff(0)
|
||||
// r2 := r.R2
|
||||
// return models.RegressionResult{
|
||||
// RegressionType: models.QuadraticRegression,
|
||||
// QuadraticA: &a,
|
||||
// QuadraticB: &b,
|
||||
// QuadraticC: &c,
|
||||
// RSquared: &r2,
|
||||
// Equation: r.Formula,
|
||||
// }
|
||||
//}
|
||||
|
||||
func performQuadraticRegression(averages []map[float64]float64) models.RegressionResult {
|
||||
if len(averages) == 0 {
|
||||
return models.RegressionResult{
|
||||
Equation: "无数据",
|
||||
}
|
||||
}
|
||||
|
||||
// 步骤1：收集所有数据点（与Flutter一致）
|
||||
var xValues []float64
|
||||
var yValues []float64
|
||||
for _, m := range averages {
|
||||
for speed, hr := range m {
|
||||
xValues = append(xValues, speed)
|
||||
yValues = append(yValues, hr)
|
||||
}
|
||||
}
|
||||
n := float64(len(xValues))
|
||||
|
||||
// 步骤2：计算各项和（完全匹配Flutter的计算）
|
||||
var sumX, sumY, sumX2, sumX3, sumX4, sumXY, sumX2Y float64
|
||||
for i := 0; i < len(xValues); i++ {
|
||||
x := xValues[i]
|
||||
y := yValues[i]
|
||||
x2 := x * x
|
||||
x3 := x2 * x
|
||||
x4 := x3 * x
|
||||
|
||||
sumX += x
|
||||
sumY += y
|
||||
sumX2 += x2
|
||||
sumX3 += x3
|
||||
sumX4 += x4
|
||||
sumXY += x * y
|
||||
sumX2Y += x2 * y
|
||||
}
|
||||
|
||||
// 步骤3：构建正规方程矩阵（与Flutter完全一致）
|
||||
matrix := [3][3]float64{
|
||||
{n, sumX, sumX2},
|
||||
{sumX, sumX2, sumX3},
|
||||
{sumX2, sumX3, sumX4},
|
||||
}
|
||||
vector := []float64{sumY, sumXY, sumX2Y}
|
||||
|
||||
// 步骤4：计算矩阵行列式（复制Flutter的determinant3x3逻辑）
|
||||
det := matrix[0][0]*(matrix[1][1]*matrix[2][2]-matrix[1][2]*matrix[2][1]) -
|
||||
matrix[0][1]*(matrix[1][0]*matrix[2][2]-matrix[1][2]*matrix[2][0]) +
|
||||
matrix[0][2]*(matrix[1][0]*matrix[2][1]-matrix[1][1]*matrix[2][0])
|
||||
|
||||
if det == 0 {
|
||||
return models.RegressionResult{
|
||||
Equation: "无法拟合",
|
||||
}
|
||||
}
|
||||
|
||||
// 步骤5：克莱姆法则求解系数（顺序与Flutter一致）
|
||||
// 注意：最终系数顺序 a=二次项, b=一次项, c=常数项
|
||||
c := det3x3([3][3]float64{
|
||||
{vector[0], matrix[0][1], matrix[0][2]},
|
||||
{vector[1], matrix[1][1], matrix[1][2]},
|
||||
{vector[2], matrix[2][1], matrix[2][2]},
|
||||
}) / det
|
||||
|
||||
b := det3x3([3][3]float64{
|
||||
{matrix[0][0], vector[0], matrix[0][2]},
|
||||
{matrix[1][0], vector[1], matrix[1][2]},
|
||||
{matrix[2][0], vector[2], matrix[2][2]},
|
||||
}) / det
|
||||
|
||||
a := det3x3([3][3]float64{
|
||||
{matrix[0][0], matrix[0][1], vector[0]},
|
||||
{matrix[1][0], matrix[1][1], vector[1]},
|
||||
{matrix[2][0], matrix[2][1], vector[2]},
|
||||
}) / det
|
||||
|
||||
// 步骤6：计算R平方（完全复制Flutter的计算逻辑）
|
||||
var ssRes, ssTot float64
|
||||
meanY := sumY / n
|
||||
for i := 0; i < len(xValues); i++ {
|
||||
x := xValues[i]
|
||||
y := yValues[i]
|
||||
yPred := a*x*x + b*x + c
|
||||
ssRes += math.Pow(y-yPred, 2)
|
||||
ssTot += math.Pow(y-meanY, 2)
|
||||
}
|
||||
rSquared := 0.0
|
||||
if ssTot != 0 {
|
||||
rSquared = 1 - ssRes/ssTot
|
||||
}
|
||||
|
||||
// 步骤7：格式化公式字符串（与Flutter格式完全一致）
|
||||
equation := formatEquation(a, b, c, rSquared)
|
||||
|
||||
return models.RegressionResult{
|
||||
RegressionType: models.QuadraticRegression,
|
||||
QuadraticA: &a,
|
||||
QuadraticB: &b,
|
||||
QuadraticC: &c,
|
||||
RSquared: &rSquared,
|
||||
Equation: equation,
|
||||
}
|
||||
}
|
||||
|
||||
// 3x3行列式计算（与Flutter实现相同）
|
||||
func det3x3(m [3][3]float64) float64 {
|
||||
return m[0][0]*(m[1][1]*m[2][2]-m[1][2]*m[2][1]) -
|
||||
m[0][1]*(m[1][0]*m[2][2]-m[1][2]*m[2][0]) +
|
||||
m[0][2]*(m[1][0]*m[2][1]-m[1][1]*m[2][0])
|
||||
}
|
||||
|
||||
// 公式格式化（完全匹配Flutter格式）
|
||||
func formatEquation(a, b, c, r2 float64) string {
|
||||
// 保留4位小数
|
||||
aStr := fmt.Sprintf("%.4f", a)
|
||||
bStr := fmt.Sprintf("%.4f", b)
|
||||
cStr := fmt.Sprintf("%.4f", c)
|
||||
r2Str := fmt.Sprintf("%.4f", r2)
|
||||
|
||||
builder := strings.Builder{}
|
||||
builder.WriteString("y = ")
|
||||
|
||||
// 处理二次项
|
||||
if a >= 0 {
|
||||
builder.WriteString(aStr + " x²")
|
||||
} else {
|
||||
builder.WriteString("-" + strings.TrimPrefix(aStr, "-") + " x²")
|
||||
}
|
||||
|
||||
// 处理一次项
|
||||
if b >= 0 {
|
||||
builder.WriteString(" + " + bStr + " x")
|
||||
} else {
|
||||
builder.WriteString(" - " + strings.TrimPrefix(bStr, "-") + " x")
|
||||
}
|
||||
|
||||
// 处理常数项
|
||||
if c >= 0 {
|
||||
builder.WriteString(" + " + cStr)
|
||||
} else {
|
||||
builder.WriteString(" - " + strings.TrimPrefix(cStr, "-"))
|
||||
}
|
||||
|
||||
builder.WriteString(" (R² = " + r2Str + ")")
|
||||
return builder.String()
|
||||
}
|
||||
|
||||
// 步频数据转换为速度段
|
||||
func convertStrideFrequencyToSegments(steps []models.StepStrideFreq) []SpeedSegment {
|
||||
if len(steps) == 0 {
|
||||
return []SpeedSegment{}
|
||||
}
|
||||
|
||||
// 过滤零值并排序
|
||||
validSteps := make([]models.StepStrideFreq, 0, len(steps))
|
||||
for _, s := range steps {
|
||||
if s.Value > 0 {
|
||||
validSteps = append(validSteps, s)
|
||||
}
|
||||
}
|
||||
|
||||
if len(validSteps) == 0 {
|
||||
return []SpeedSegment{}
|
||||
}
|
||||
|
||||
// 按时间排序
|
||||
for i := 0; i < len(validSteps)-1; i++ {
|
||||
for j := i + 1; j < len(validSteps); j++ {
|
||||
if validSteps[i].Time > validSteps[j].Time {
|
||||
validSteps[i], validSteps[j] = validSteps[j], validSteps[i]
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 创建速度段
|
||||
segments := make([]SpeedSegment, 0)
|
||||
startTime := validSteps[0].Time
|
||||
currentValue := validSteps[0].Value
|
||||
|
||||
for i := 1; i < len(validSteps); i++ {
|
||||
if validSteps[i].Value != currentValue {
|
||||
duration := float64(validSteps[i].Time-startTime) / 1000.0
|
||||
if duration > 0 {
|
||||
segments = append(segments, SpeedSegment{
|
||||
Duration: duration,
|
||||
Speed: float64(currentValue),
|
||||
})
|
||||
}
|
||||
startTime = validSteps[i].Time
|
||||
currentValue = validSteps[i].Value
|
||||
}
|
||||
}
|
||||
|
||||
// 添加最后一个段
|
||||
if len(validSteps) > 0 {
|
||||
duration := float64(validSteps[len(validSteps)-1].Time-startTime) / 1000.0
|
||||
if duration > 0 {
|
||||
segments = append(segments, SpeedSegment{
|
||||
Duration: duration,
|
||||
Speed: float64(currentValue),
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
return segments
|
||||
}
|
||||
|
||||
// 计算区段平均值
|
||||
func calculateSegmentAverages(heartRates []models.StepHeartRate, segments []SpeedSegment, errorThreshold int) []map[float64]float64 {
|
||||
currentTime := 0.0
|
||||
results := make([]map[float64]float64, 0)
|
||||
|
||||
for _, seg := range segments {
|
||||
minRequired := 60 + (60 - float64(errorThreshold))
|
||||
|
||||
// 跳过不满足条件的区段
|
||||
if seg.Duration < minRequired {
|
||||
currentTime += seg.Duration
|
||||
continue
|
||||
}
|
||||
|
||||
// 计算时间窗口
|
||||
startSec := currentTime + 60
|
||||
endSec := currentTime
|
||||
if seg.Duration >= 120 {
|
||||
endSec = currentTime + 120
|
||||
} else {
|
||||
endSec = currentTime + 120 - float64(errorThreshold)
|
||||
}
|
||||
|
||||
// 收集该区段的心率数据
|
||||
sum, count := 0, 0
|
||||
for _, hr := range heartRates {
|
||||
sec := float64(hr.Time) / 1000.0
|
||||
if sec >= startSec && sec <= endSec {
|
||||
sum += hr.Value
|
||||
count++
|
||||
}
|
||||
}
|
||||
|
||||
// 计算平均值
|
||||
if count > 0 {
|
||||
avg := float64(sum) / float64(count)
|
||||
results = append(results, map[float64]float64{seg.Speed: avg})
|
||||
}
|
||||
|
||||
currentTime += seg.Duration
|
||||
}
|
||||
|
||||
return results
|
||||
}
|
||||
|
||||
// 计算步频区段的心率平均值
|
||||
func CalculateSegmentAveragesByRealStep(heartRates []models.StepHeartRate, steps []models.StepStrideFreq) []map[float64]float64 {
|
||||
segments := convertStrideFrequencyToSegments(steps)
|
||||
return calculateSegmentAverages(heartRates, segments, 15) // 默认5秒误差阈值
|
||||
}
|
||||
|
||||
// 存储回归结果到数据库（支持多种回归类型）
|
||||
func (tc *StepTrainingController) SaveRegressionResults(trainId uint, results []models.RegressionResult) error {
|
||||
return tc.DB.Transaction(func(tx *gorm.DB) error {
|
||||
for i := range results {
|
||||
results[i].TrainId = trainId
|
||||
// 使用复合唯一约束确保每种回归类型只存储一条记录
|
||||
err := tx.Clauses(clause.OnConflict{
|
||||
Columns: []clause.Column{
|
||||
{Name: "id"},
|
||||
},
|
||||
DoUpdates: clause.Assignments(map[string]interface{}{
|
||||
"equation": results[i].Equation,
|
||||
"slope": results[i].Slope,
|
||||
"intercept": results[i].Intercept,
|
||||
"log_a": results[i].LogA,
|
||||
"log_b": results[i].LogB,
|
||||
"quadratic_a": results[i].QuadraticA,
|
||||
"quadratic_b": results[i].QuadraticB,
|
||||
"quadratic_c": results[i].QuadraticC,
|
||||
"r_squared": results[i].RSquared,
|
||||
"updated_at": gorm.Expr("CURRENT_TIMESTAMP"),
|
||||
}),
|
||||
}).Create(&results[i]).Error
|
||||
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
return nil
|
||||
})
|
||||
}
|
||||
|
||||
// 获取或计算回归结果（返回多种回归类型列表）
|
||||
func (tc *StepTrainingController) GetOrCalculateRegression(trainId uint) ([]models.RegressionResult, error) {
|
||||
// 尝试从数据库获取所有类型的回归结果
|
||||
var results []models.RegressionResult
|
||||
err := tc.DB.Where("train_id = ?", trainId).Find(&results).Error
|
||||
|
||||
// 如果已存在三种类型的结果，直接返回
|
||||
if err == nil && len(results) >= 3 {
|
||||
return results, nil
|
||||
}
|
||||
|
||||
// 查询训练记录及相关数据
|
||||
var record models.StepTrainRecord
|
||||
if err := tc.DB.
|
||||
Where("train_id = ?", uint(trainId)).
|
||||
Preload("HeartRates", "heart_rate_type = ?", 1).
|
||||
Preload("StrideFreqs", "predict_value = ?", 1).
|
||||
First(&record).Error; err != nil {
|
||||
return nil, err
|
||||
}
|
||||
|
||||
// 计算心率平均值
|
||||
averages := CalculateSegmentAveragesByRealStep(record.HeartRates, record.StrideFreqs)
|
||||
if len(averages) == 0 {
|
||||
return nil, errors.New("无足够数据进行回归计算")
|
||||
}
|
||||
|
||||
// 创建三种回归类型的结果
|
||||
results = make([]models.RegressionResult, 3)
|
||||
|
||||
// 线性回归
|
||||
linearRes := performLinearRegression(averages)
|
||||
results[0] = models.RegressionResult{
|
||||
RegressionType: models.LinearRegression,
|
||||
TrainId: trainId,
|
||||
Equation: linearRes.Equation,
|
||||
Slope: linearRes.Slope,
|
||||
Intercept: linearRes.Intercept,
|
||||
RSquared: linearRes.RSquared,
|
||||
}
|
||||
|
||||
// 对数回归
|
||||
logRes := performLogarithmicRegression(averages)
|
||||
results[1] = models.RegressionResult{
|
||||
RegressionType: models.LogarithmicRegression,
|
||||
TrainId: trainId,
|
||||
Equation: logRes.Equation,
|
||||
LogA: logRes.LogA,
|
||||
LogB: logRes.LogB,
|
||||
RSquared: logRes.RSquared,
|
||||
}
|
||||
|
||||
// 二次回归
|
||||
quadRes := performQuadraticRegression(averages)
|
||||
results[2] = models.RegressionResult{
|
||||
RegressionType: models.QuadraticRegression,
|
||||
TrainId: trainId,
|
||||
Equation: quadRes.Equation,
|
||||
QuadraticA: quadRes.QuadraticA,
|
||||
QuadraticB: quadRes.QuadraticB,
|
||||
QuadraticC: quadRes.QuadraticC,
|
||||
RSquared: quadRes.RSquared,
|
||||
}
|
||||
|
||||
// 批量保存结果到数据库
|
||||
if err := tc.SaveRegressionResults(trainId, results); err != nil {
|
||||
log.Printf("保存回归结果失败: %v", err)
|
||||
return nil, err
|
||||
}
|
||||
|
||||
return results, nil
|
||||
}
|
||||
|
||||
// 新增接口：获取回归结果
|
||||
func (tc *StepTrainingController) GetRegressionResult(c *gin.Context) {
|
||||
trainIdStr := c.Param("trainId")
|
||||
tid, err := strconv.ParseUint(trainIdStr, 10, 32)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"error": "无效的训练ID"})
|
||||
return
|
||||
}
|
||||
|
||||
result, err := tc.GetOrCalculateRegression(uint(tid))
|
||||
if err != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
|
||||
return
|
||||
}
|
||||
|
||||
c.JSON(http.StatusOK, gin.H{
|
||||
"message": "获取成功",
|
||||
"data": result,
|
||||
})
|
||||
}
|
||||
|
||||
func (tc *StepTrainingController) GetTrainingRank(c *gin.Context) {
|
||||
// 参数解析
|
||||
trainIdStr := c.Param("trainId")
|
||||
regressionTypeStr := c.Query("type")
|
||||
regressionType, err := strconv.Atoi(regressionTypeStr)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"error": "参数type必须为整数"})
|
||||
return
|
||||
}
|
||||
|
||||
// 验证回归类型
|
||||
regType := models.RegressionType(regressionType)
|
||||
if regType != models.LinearRegression && regType != models.QuadraticRegression {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"error": "无效的回归类型，必须是'linear'或'quadratic'"})
|
||||
return
|
||||
}
|
||||
|
||||
// 转换训练ID
|
||||
tid, err := strconv.ParseUint(trainIdStr, 10, 64)
|
||||
if err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{"error": "无效的训练ID"})
|
||||
return
|
||||
}
|
||||
trainId := uint(tid)
|
||||
|
||||
// 确保回归结果存在
|
||||
if _, err := tc.GetOrCalculateRegression(trainId); err != nil {
|
||||
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)
|
||||
|
||||
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
|
||||
}
|
||||
|
||||
// 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
|
||||
}
|
||||
|
||||
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": 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 {
|
||||
return false
|
||||
}
|
||||
if a == nil {
|
||||
return false // 空值排最后
|
||||
}
|
||||
if b == nil {
|
||||
return true // 非空值排前
|
||||
}
|
||||
|
||||
if ascending {
|
||||
return *a < *b
|
||||
}
|
||||
return *a > *b
|
||||
}
|
||||
|
||||
// 辅助函数：比较二次项系数（用于二次回归）
|
||||
func compareQuadraticA(a, b *float64) bool {
|
||||
if a == nil && b == nil {
|
||||
return false
|
||||
}
|
||||
if a == nil {
|
||||
return false
|
||||
}
|
||||
if b == nil {
|
||||
return true
|
||||
}
|
||||
|
||||
// 比较绝对值（a和b都是负值，所以取绝对值后大的排前面）
|
||||
return math.Abs(*a) > math.Abs(*b)
|
||||
}
|
||||
@ -1,14 +1,33 @@
|
||||
package controllers
|
||||
|
||||
import (
|
||||
"gonum.org/v1/gonum/floats"
|
||||
"gonum.org/v1/gonum/stat"
|
||||
"gonum.org/v1/gonum/stat/distuv"
|
||||
)
|
||||
|
||||
import (
|
||||
"errors"
|
||||
"github.com/gin-gonic/gin"
|
||||
"gorm.io/gorm"
|
||||
"gorm.io/gorm/clause"
|
||||
"hr_receiver/config"
|
||||
"hr_receiver/models"
|
||||
"math"
|
||||
"net/http"
|
||||
)
|
||||
|
||||
var analyzeRunTypes = []string{"6.5开始", "7开始", "8开始"} // 替换为你的具体值
|
||||
|
||||
func contains(s string) bool {
|
||||
for _, item := range analyzeRunTypes {
|
||||
if item == s {
|
||||
return true
|
||||
}
|
||||
}
|
||||
return false
|
||||
}
|
||||
|
||||
type TrainingController struct {
|
||||
DB *gorm.DB
|
||||
}
|
||||
@ -57,13 +76,12 @@ func (tc *TrainingController) CreateTrainingRecord(c *gin.Context) {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
//// 保存腰带关联关系
|
||||
//if len(record.Belts) > 0 {
|
||||
// if err := tx.Model(&record).Association("Belts").Replace(record.Belts); err != nil {
|
||||
// return err
|
||||
// }
|
||||
//}
|
||||
if contains(record.RunType) {
|
||||
err := tc.heartRateAnalyze(tx, record)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
|
||||
return nil
|
||||
})
|
||||
@ -79,25 +97,270 @@ func (tc *TrainingController) CreateTrainingRecord(c *gin.Context) {
|
||||
})
|
||||
}
|
||||
|
||||
func ReceiveTrainingData(c *gin.Context) {
|
||||
var data models.TrainingData
|
||||
|
||||
if err := c.ShouldBindJSON(&data); err != nil {
|
||||
c.JSON(http.StatusBadRequest, gin.H{
|
||||
"error": "Invalid request body: " + err.Error(),
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
if result := config.DB.Create(&data); result.Error != nil {
|
||||
c.JSON(http.StatusInternalServerError, gin.H{
|
||||
"error": "Failed to save data: " + result.Error.Error(),
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
c.JSON(http.StatusCreated, gin.H{
|
||||
"message": "Data saved successfully",
|
||||
"id": data.ID,
|
||||
})
|
||||
// analysis_response.go
|
||||
type AnalysisResponse struct {
|
||||
Status string `json:"status"` // 状态码
|
||||
Message string `json:"message"` // 附加信息
|
||||
Data struct {
|
||||
Mean float64 `json:"mean"` // 均值
|
||||
StdDev float64 `json:"stdDev"` // 标准差
|
||||
Histogram []HistoBin `json:"histogram"` // 直方图数据
|
||||
Curve []CurvePoint `json:"curve"` // 正态曲线数据
|
||||
} `json:"data"`
|
||||
}
|
||||
|
||||
type HistoBin struct {
|
||||
BinStart float64 `json:"binStart"` // 区间起始值
|
||||
BinEnd float64 `json:"binEnd"` // 区间结束值
|
||||
Count int `json:"count"` // 该区间计数
|
||||
}
|
||||
|
||||
type CurvePoint struct {
|
||||
X float64 `json:"x"` // X坐标
|
||||
Y float64 `json:"y"` // Y坐标
|
||||
}
|
||||
|
||||
// analysis_handler.go
|
||||
func (tc *TrainingController) HandleCurveAnalysis(c *gin.Context) {
|
||||
// 获取数据库连接（根据实际项目配置调整）
|
||||
|
||||
// 1. 获取历史数据
|
||||
aValues, err := collectCurveParams(tc.DB)
|
||||
if err != nil {
|
||||
c.JSON(500, gin.H{
|
||||
"status": "error",
|
||||
"message": "数据查询失败: " + err.Error(),
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
// 2. 检查数据有效性
|
||||
if len(aValues) < 10 { // 至少需要10个样本
|
||||
c.JSON(400, gin.H{
|
||||
"status": "fail",
|
||||
"message": "数据量不足，至少需要10个样本",
|
||||
})
|
||||
return
|
||||
}
|
||||
|
||||
// 3. 计算统计量
|
||||
mean, stddev := calculateStats(aValues)
|
||||
|
||||
// 4. 生成直方图数据
|
||||
histogram := calculateHistogram(aValues, 20) // 20个分箱
|
||||
|
||||
// 5. 生成正态曲线
|
||||
x, y := generateNormalCurve(mean, stddev, 100)
|
||||
|
||||
// 6. 构造响应
|
||||
response := AnalysisResponse{
|
||||
Status: "success",
|
||||
Message: "分析完成",
|
||||
Data: struct {
|
||||
Mean float64 `json:"mean"`
|
||||
StdDev float64 `json:"stdDev"`
|
||||
Histogram []HistoBin `json:"histogram"`
|
||||
Curve []CurvePoint `json:"curve"`
|
||||
}{
|
||||
Mean: mean,
|
||||
StdDev: stddev,
|
||||
Histogram: histogram,
|
||||
Curve: convertToCurvePoints(x, y),
|
||||
},
|
||||
}
|
||||
|
||||
c.JSON(200, response)
|
||||
}
|
||||
|
||||
// 直方图计算函数
|
||||
func calculateHistogram(data []float64, bins int) []HistoBin {
|
||||
minV, maxV := floats.Min(data), floats.Max(data)
|
||||
binWidth := (maxV - minV) / float64(bins)
|
||||
|
||||
counts := make([]int, bins)
|
||||
for _, v := range data {
|
||||
idx := int((v - minV) / binWidth)
|
||||
if idx == bins { // 处理最大值刚好等于maxV的情况
|
||||
idx--
|
||||
}
|
||||
counts[idx]++
|
||||
}
|
||||
|
||||
histogram := make([]HistoBin, bins)
|
||||
for i := 0; i < bins; i++ {
|
||||
start := minV + float64(i)*binWidth
|
||||
end := minV + float64(i+1)*binWidth
|
||||
histogram[i] = HistoBin{
|
||||
BinStart: start,
|
||||
BinEnd: end,
|
||||
Count: counts[i],
|
||||
}
|
||||
}
|
||||
return histogram
|
||||
}
|
||||
|
||||
// 转换曲线数据格式
|
||||
func convertToCurvePoints(x, y []float64) []CurvePoint {
|
||||
points := make([]CurvePoint, len(x))
|
||||
for i := range x {
|
||||
points[i] = CurvePoint{
|
||||
X: x[i],
|
||||
Y: y[i],
|
||||
}
|
||||
}
|
||||
return points
|
||||
}
|
||||
|
||||
func (tc *TrainingController) heartRateAnalyze(tx *gorm.DB, record models.TrainRecord) error {
|
||||
var startTime int64
|
||||
if record.TestTime > 0 {
|
||||
startTime = record.TestTime
|
||||
} else {
|
||||
startTime = record.StartTime
|
||||
}
|
||||
|
||||
// 获取所有唯一的beltID
|
||||
var beltIDs []uint
|
||||
tx.Model(&models.HeartRate{}).Where("train_id = ?", record.TrainId).
|
||||
Select("DISTINCT belt_id").Pluck("belt_id", &beltIDs)
|
||||
|
||||
// 对每个belt计算
|
||||
for _, bid := range beltIDs {
|
||||
// 计算平均心率
|
||||
ranges := getTimeRanges(startTime)
|
||||
averages, err := calculateAverages(tx, record.TrainId, bid, ranges)
|
||||
if err != nil {
|
||||
return err
|
||||
}
|
||||
|
||||
// 曲线拟合
|
||||
x := []float64{2, 4, 6}
|
||||
y := []float64{averages["2min"], averages["4min"], averages["6min"]}
|
||||
a, b, _ := quadraticFit(x, y)
|
||||
|
||||
// 存储结果
|
||||
analysis := models.BeltAnalysis{
|
||||
TrainID: record.TrainId,
|
||||
RunType: record.RunType,
|
||||
BeltID: bid,
|
||||
Avg2min: averages["2min"],
|
||||
Avg4min: averages["4min"],
|
||||
Avg6min: averages["6min"],
|
||||
CurveParamA: a,
|
||||
CurveParamB: b,
|
||||
}
|
||||
if err := tx.Create(&analysis).Error; err != nil {
|
||||
return err
|
||||
}
|
||||
}
|
||||
return nil
|
||||
}
|
||||
|
||||
func collectCurveParams(tx *gorm.DB) ([]float64, error) {
|
||||
var aValues []float64
|
||||
// 查询所有记录的 CurveParamA 字段
|
||||
err := tx.Model(&models.BeltAnalysis{}).Pluck("curve_param_a", &aValues).Error
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
return aValues, nil
|
||||
}
|
||||
func calculateStats(data []float64) (mean, stddev float64) {
|
||||
mean = stat.Mean(data, nil)
|
||||
variance := stat.Variance(data, nil)
|
||||
stddev = math.Sqrt(variance)
|
||||
return
|
||||
}
|
||||
|
||||
func generateNormalCurve(mean, stddev float64, numPoints int) (x, y []float64) {
|
||||
normal := distuv.Normal{
|
||||
Mu: mean,
|
||||
Sigma: stddev,
|
||||
}
|
||||
|
||||
minV := mean - 3*stddev // 从均值-3σ开始
|
||||
maxV := mean + 3*stddev // 到均值+3σ结束
|
||||
step := (maxV - minV) / float64(numPoints-1)
|
||||
|
||||
for i := 0; i < numPoints; i++ {
|
||||
xi := minV + float64(i)*step
|
||||
yi := normal.Prob(xi)
|
||||
x = append(x, xi)
|
||||
y = append(y, yi)
|
||||
}
|
||||
return
|
||||
}
|
||||
func calculateAverages(tx *gorm.DB, trainID uint, beltID uint, ranges map[string]TimeRange) (map[string]float64, error) {
|
||||
averages := make(map[string]float64)
|
||||
for key, tr := range ranges {
|
||||
var avg float64
|
||||
// 使用GORM Raw SQL提高效率[6,10](@ref)
|
||||
err := tx.Raw(`
|
||||
SELECT COALESCE(AVG(value), 0) AS avg -- 关键修复
|
||||
FROM heart_rates
|
||||
WHERE train_id = ?
|
||||
AND belt_id = ?
|
||||
AND time BETWEEN ? AND ?`,
|
||||
trainID, beltID, tr.Start, tr.End,
|
||||
).Scan(&avg).Error
|
||||
if err != nil {
|
||||
return nil, err
|
||||
}
|
||||
averages[key] = avg
|
||||
}
|
||||
return averages, nil
|
||||
}
|
||||
|
||||
//func quadraticFit(x []float64, y []float64) (float64, error) {
|
||||
// // 使用三点计算y=ax²+b的a值（x=[2,4,6]对应分钟）
|
||||
// if len(x) != 3 || len(y) != 3 {
|
||||
// return 0, errors.New("需要三个点")
|
||||
// }
|
||||
// // 构造方程组矩阵（简化计算）
|
||||
// a := (y[2] - 2*y[1] + y[0]) / (x[2]*x[2] - 2*x[1]*x[1] + x[0]*x[0])
|
||||
// return a, nil
|
||||
//}
|
||||
|
||||
func quadraticFit(x []float64, y []float64) (float64, float64, error) {
|
||||
// 校验输入长度
|
||||
if len(x) != 3 || len(y) != 3 {
|
||||
return 0, 0, errors.New("需要三个点")
|
||||
}
|
||||
|
||||
// 计算各项累加值
|
||||
var sumX4, sumX2, sumY, sumX2Y float64
|
||||
for i := 0; i < 3; i++ {
|
||||
xi := x[i]
|
||||
xi2 := xi * xi
|
||||
sumX4 += xi2 * xi2 // x^4累加
|
||||
sumX2 += xi2 // x^2累加
|
||||
sumY += y[i] // y累加
|
||||
sumX2Y += xi2 * y[i] // x²y累加
|
||||
}
|
||||
|
||||
// 计算行列式
|
||||
determinant := sumX4*3 - sumX2*sumX2
|
||||
if determinant == 0 {
|
||||
return 0, 0, errors.New("无解，行列式为零")
|
||||
}
|
||||
|
||||
// 计算系数 a 和 b
|
||||
a := (sumX2Y*3 - sumY*sumX2) / determinant
|
||||
b := (sumX4*sumY - sumX2*sumX2Y) / determinant
|
||||
|
||||
return a, b, nil
|
||||
}
|
||||
|
||||
type TimeRange struct {
|
||||
Start int64 // 毫秒时间戳起点
|
||||
End int64 // 毫秒时间戳终点
|
||||
}
|
||||
|
||||
func getTimeRanges(startTime int64) map[string]TimeRange {
|
||||
// 计算相对于训练开始时间的窗口
|
||||
return map[string]TimeRange{
|
||||
"2min": {Start: startTime + 120000, End: startTime + 240000}, // 第2分钟（120-240秒）
|
||||
"4min": {Start: startTime + 240000, End: startTime + 360000},
|
||||
"6min": {Start: startTime + 360000, End: startTime + 480000},
|
||||
}
|
||||
}
|
||||
|
||||
@ -4,7 +4,7 @@ services:
|
||||
app:
|
||||
build: .
|
||||
ports:
|
||||
- "8080:8180"
|
||||
- "8180:8080"
|
||||
depends_on:
|
||||
db:
|
||||
condition: service_healthy
|
||||
|
||||
7
go.mod
7
go.mod
@ -4,9 +4,10 @@ go 1.23.3
|
||||
|
||||
require (
|
||||
github.com/gin-gonic/gin v1.10.0
|
||||
github.com/golang-jwt/jwt/v4 v4.5.1
|
||||
github.com/golang-jwt/jwt/v5 v5.2.1
|
||||
github.com/sajari/regression v1.0.1
|
||||
github.com/spf13/viper v1.20.0
|
||||
gonum.org/v1/gonum v0.16.0
|
||||
gorm.io/driver/postgres v1.5.11
|
||||
gorm.io/gorm v1.25.12
|
||||
)
|
||||
@ -51,9 +52,9 @@ require (
|
||||
golang.org/x/arch v0.8.0 // indirect
|
||||
golang.org/x/crypto v0.32.0 // indirect
|
||||
golang.org/x/net v0.33.0 // indirect
|
||||
golang.org/x/sync v0.10.0 // indirect
|
||||
golang.org/x/sync v0.12.0 // indirect
|
||||
golang.org/x/sys v0.29.0 // indirect
|
||||
golang.org/x/text v0.21.0 // indirect
|
||||
golang.org/x/text v0.23.0 // indirect
|
||||
google.golang.org/protobuf v1.36.1 // indirect
|
||||
gopkg.in/yaml.v3 v3.0.1 // indirect
|
||||
)
|
||||
|
||||
14
go.sum
14
go.sum
@ -31,8 +31,6 @@ github.com/go-viper/mapstructure/v2 v2.2.1 h1:ZAaOCxANMuZx5RCeg0mBdEZk7DZasvvZIx
|
||||
github.com/go-viper/mapstructure/v2 v2.2.1/go.mod h1:oJDH3BJKyqBA2TXFhDsKDGDTlndYOZ6rGS0BRZIxGhM=
|
||||
github.com/goccy/go-json v0.10.2 h1:CrxCmQqYDkv1z7lO7Wbh2HN93uovUHgrECaO5ZrCXAU=
|
||||
github.com/goccy/go-json v0.10.2/go.mod h1:6MelG93GURQebXPDq3khkgXZkazVtN9CRI+MGFi0w8I=
|
||||
github.com/golang-jwt/jwt/v4 v4.5.1 h1:JdqV9zKUdtaa9gdPlywC3aeoEsR681PlKC+4F5gQgeo=
|
||||
github.com/golang-jwt/jwt/v4 v4.5.1/go.mod h1:m21LjoU+eqJr34lmDMbreY2eSTRJ1cv77w39/MY0Ch0=
|
||||
github.com/golang-jwt/jwt/v5 v5.2.1 h1:OuVbFODueb089Lh128TAcimifWaLhJwVflnrgM17wHk=
|
||||
github.com/golang-jwt/jwt/v5 v5.2.1/go.mod h1:pqrtFR0X4osieyHYxtmOUWsAWrfe1Q5UVIyoH402zdk=
|
||||
github.com/google/go-cmp v0.6.0 h1:ofyhxvXcZhMsU5ulbFiLKl/XBFqE1GSq7atu8tAmTRI=
|
||||
@ -77,6 +75,8 @@ github.com/rogpeppe/go-internal v1.13.1 h1:KvO1DLK/DRN07sQ1LQKScxyZJuNnedQ5/wKSR
|
||||
github.com/rogpeppe/go-internal v1.13.1/go.mod h1:uMEvuHeurkdAXX61udpOXGD/AzZDWNMNyH2VO9fmH0o=
|
||||
github.com/sagikazarmark/locafero v0.7.0 h1:5MqpDsTGNDhY8sGp0Aowyf0qKsPrhewaLSsFaodPcyo=
|
||||
github.com/sagikazarmark/locafero v0.7.0/go.mod h1:2za3Cg5rMaTMoG/2Ulr9AwtFaIppKXTRYnozin4aB5k=
|
||||
github.com/sajari/regression v1.0.1 h1:iTVc6ZACGCkoXC+8NdqH5tIreslDTT/bXxT6OmHR5PE=
|
||||
github.com/sajari/regression v1.0.1/go.mod h1:NeG/XTW1lYfGY7YV/Z0nYDV/RGh3wxwd1yW46835flM=
|
||||
github.com/sourcegraph/conc v0.3.0 h1:OQTbbt6P72L20UqAkXXuLOj79LfEanQ+YQFNpLA9ySo=
|
||||
github.com/sourcegraph/conc v0.3.0/go.mod h1:Sdozi7LEKbFPqYX2/J+iBAM6HpqSLTASQIKqDmF7Mt0=
|
||||
github.com/spf13/afero v1.12.0 h1:UcOPyRBYczmFn6yvphxkn9ZEOY65cpwGKb5mL36mrqs=
|
||||
@ -114,14 +114,16 @@ golang.org/x/crypto v0.32.0 h1:euUpcYgM8WcP71gNpTqQCn6rC2t6ULUPiOzfWaXVVfc=
|
||||
golang.org/x/crypto v0.32.0/go.mod h1:ZnnJkOaASj8g0AjIduWNlq2NRxL0PlBrbKVyZ6V/Ugc=
|
||||
golang.org/x/net v0.33.0 h1:74SYHlV8BIgHIFC/LrYkOGIwL19eTYXQ5wc6TBuO36I=
|
||||
golang.org/x/net v0.33.0/go.mod h1:HXLR5J+9DxmrqMwG9qjGCxZ+zKXxBru04zlTvWlWuN4=
|
||||
golang.org/x/sync v0.10.0 h1:3NQrjDixjgGwUOCaF8w2+VYHv0Ve/vGYSbdkTa98gmQ=
|
||||
golang.org/x/sync v0.10.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
|
||||
golang.org/x/sync v0.12.0 h1:MHc5BpPuC30uJk597Ri8TV3CNZcTLu6B6z4lJy+g6Jw=
|
||||
golang.org/x/sync v0.12.0/go.mod h1:1dzgHSNfp02xaA81J2MS99Qcpr2w7fw1gpm99rleRqA=
|
||||
golang.org/x/sys v0.5.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
|
||||
golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
|
||||
golang.org/x/sys v0.29.0 h1:TPYlXGxvx1MGTn2GiZDhnjPA9wZzZeGKHHmKhHYvgaU=
|
||||
golang.org/x/sys v0.29.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
|
||||
golang.org/x/text v0.21.0 h1:zyQAAkrwaneQ066sspRyJaG9VNi/YJ1NfzcGB3hZ/qo=
|
||||
golang.org/x/text v0.21.0/go.mod h1:4IBbMaMmOPCJ8SecivzSH54+73PCFmPWxNTLm+vZkEQ=
|
||||
golang.org/x/text v0.23.0 h1:D71I7dUrlY+VX0gQShAThNGHFxZ13dGLBHQLVl1mJlY=
|
||||
golang.org/x/text v0.23.0/go.mod h1:/BLNzu4aZCJ1+kcD0DNRotWKage4q2rGVAg4o22unh4=
|
||||
gonum.org/v1/gonum v0.16.0 h1:5+ul4Swaf3ESvrOnidPp4GZbzf0mxVQpDCYUQE7OJfk=
|
||||
gonum.org/v1/gonum v0.16.0/go.mod h1:fef3am4MQ93R2HHpKnLk4/Tbh/s0+wqD5nfa6Pnwy4E=
|
||||
google.golang.org/protobuf v1.36.1 h1:yBPeRvTftaleIgM3PZ/WBIZ7XM/eEYAaEyCwvyjq/gk=
|
||||
google.golang.org/protobuf v1.36.1/go.mod h1:9fA7Ob0pmnwhb644+1+CVWFRbNajQ6iRojtC/QF5bRE=
|
||||
gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=
|
||||
|
||||
11
main.go
11
main.go
@ -15,7 +15,16 @@ func main() {
|
||||
|
||||
config.DB.Debug()
|
||||
// 自动迁移模型
|
||||
config.DB.AutoMigrate(&models.TrainRecord{}, &models.TrainingData{}, &models.Belt{}, &models.HeartRate{})
|
||||
config.DB.AutoMigrate(&models.TrainRecord{},
|
||||
&models.TrainingData{},
|
||||
&models.Belt{},
|
||||
&models.HeartRate{},
|
||||
&models.BeltAnalysis{},
|
||||
&models.StepTrainRecord{},
|
||||
&models.StepHeartRate{},
|
||||
&models.StepStrideFreq{},
|
||||
&models.RegressionResult{},
|
||||
)
|
||||
|
||||
// 启动服务
|
||||
r := routes.SetupRouter()
|
||||
|
||||
@ -4,10 +4,12 @@ import (
|
||||
"compress/gzip"
|
||||
"github.com/gin-gonic/gin"
|
||||
"net/http"
|
||||
"strings"
|
||||
)
|
||||
|
||||
func GzipMiddleware() gin.HandlerFunc {
|
||||
return func(c *gin.Context) {
|
||||
// 1. 处理请求解压
|
||||
if c.Request.Header.Get("Content-Encoding") == "gzip" {
|
||||
gzReader, err := gzip.NewReader(c.Request.Body)
|
||||
if err != nil {
|
||||
@ -17,6 +19,39 @@ func GzipMiddleware() gin.HandlerFunc {
|
||||
defer gzReader.Close()
|
||||
c.Request.Body = gzReader
|
||||
}
|
||||
|
||||
// 2. 设置响应压缩支持
|
||||
if strings.Contains(c.Request.Header.Get("Accept-Encoding"), "gzip") {
|
||||
// 创建gzip writer
|
||||
gzWriter := gzip.NewWriter(c.Writer)
|
||||
defer gzWriter.Close()
|
||||
|
||||
// 替换原始writer为压缩writer
|
||||
originalWriter := c.Writer
|
||||
c.Writer = &gzipResponseWriter{
|
||||
ResponseWriter: originalWriter,
|
||||
gzWriter: gzWriter,
|
||||
}
|
||||
|
||||
// 设置响应头
|
||||
c.Header("Content-Encoding", "gzip")
|
||||
c.Header("Vary", "Accept-Encoding")
|
||||
}
|
||||
|
||||
c.Next()
|
||||
}
|
||||
}
|
||||
|
||||
// 自定义ResponseWriter实现gzip压缩
|
||||
type gzipResponseWriter struct {
|
||||
gin.ResponseWriter
|
||||
gzWriter *gzip.Writer
|
||||
}
|
||||
|
||||
func (w *gzipResponseWriter) Write(data []byte) (int, error) {
|
||||
return w.gzWriter.Write(data)
|
||||
}
|
||||
|
||||
func (w *gzipResponseWriter) WriteString(s string) (int, error) {
|
||||
return w.gzWriter.Write([]byte(s))
|
||||
}
|
||||
|
||||
1
models/pageination.go
Normal file
1
models/pageination.go
Normal file
@ -0,0 +1 @@
|
||||
package models
|
||||
69
models/step_train.go
Normal file
69
models/step_train.go
Normal file
@ -0,0 +1,69 @@
|
||||
package models
|
||||
|
||||
import "gorm.io/gorm"
|
||||
|
||||
type StepStrideFreq struct {
|
||||
gorm.Model
|
||||
TrainId uint `gorm:"column:train_id; index" json:"trainId"` // 外键关联训练记录[4](@ref)
|
||||
Time int64 `gorm:"type:bigint" json:"time"` // 保持与前端一致的毫秒时间戳[3](@ref)
|
||||
Value int `gorm:"type:int" json:"value"`
|
||||
Count int `gorm:"type:int" json:"count"`
|
||||
PredictValue int `gorm:"type:int" json:"predictValue"`
|
||||
Identifier string `gorm:"uniqueIndex;type:varchar(255)" json:"identifier"`
|
||||
}
|
||||
|
||||
// 对应Flutter的HeartRate结构
|
||||
type StepHeartRate struct {
|
||||
gorm.Model
|
||||
TrainId uint `gorm:"column:train_id; index" json:"trainId"` // 外键关联训练记录[4](@ref)
|
||||
Time int64 `gorm:"type:bigint" json:"time"` // 保持与前端一致的毫秒时间戳[3](@ref)
|
||||
Value int `gorm:"type:int" json:"value"`
|
||||
HeartRateType int `gorm:"type:int" json:"predictValue"`
|
||||
Identifier string `gorm:"uniqueIndex;type:varchar(255)" json:"identifier"`
|
||||
}
|
||||
|
||||
// 对应Flutter的TrainRecord结构
|
||||
type StepTrainRecord struct {
|
||||
gorm.Model
|
||||
TrainId uint `gorm:"uniqueIndex" json:"tid"` // 对应Dart的tid字段
|
||||
StartTime int64 `gorm:"type:bigint" json:"time"` // 开始时间戳
|
||||
EndTime int64 `gorm:"type:bigint" json:"endTime"` // 结束时间戳[3](@ref)
|
||||
Name string `gorm:"size:100" json:"name"`
|
||||
RunType string `gorm:"size:100" json:"runType"`
|
||||
MaxHeartRate int `gorm:"type:int" json:"maxHeartRate"`
|
||||
Duration int `gorm:"type:int" json:"duration"` // 持续时间(秒)
|
||||
DeadZone int `gorm:"type:int" json:"deadZone"`
|
||||
Evaluation string `gorm:"size:50" json:"evaluation"`
|
||||
HeartRates []StepHeartRate `gorm:"foreignKey:TrainId;references:TrainId" json:"heartRates"`
|
||||
StrideFreqs []StepStrideFreq `gorm:"foreignKey:TrainId;references:TrainId" json:"strideFreqs"`
|
||||
}
|
||||
|
||||
type RegressionType int
|
||||
|
||||
const (
|
||||
LinearRegression RegressionType = iota + 1
|
||||
LogarithmicRegression
|
||||
QuadraticRegression
|
||||
)
|
||||
|
||||
type RegressionResult struct {
|
||||
gorm.Model
|
||||
RegressionType RegressionType `gorm:"column:regression_type;index" json:"regressionType"` // 训练记录ID
|
||||
TrainId uint `gorm:"column:train_id;index" json:"trainId"` // 训练记录ID
|
||||
Equation string `gorm:"type:text" json:"equation"` // 回归方程
|
||||
|
||||
// 线性回归系数
|
||||
Slope *float64 `gorm:"column:slope" json:"slope"`
|
||||
Intercept *float64 `gorm:"column:intercept" json:"intercept"`
|
||||
|
||||
// 对数回归系数
|
||||
LogA *float64 `gorm:"column:log_a" json:"logA"`
|
||||
LogB *float64 `gorm:"column:log_b" json:"logB"`
|
||||
|
||||
// 二次回归系数
|
||||
QuadraticA *float64 `gorm:"column:quadratic_a" json:"quadraticA"`
|
||||
QuadraticB *float64 `gorm:"column:quadratic_b" json:"quadraticB"`
|
||||
QuadraticC *float64 `gorm:"column:quadratic_c" json:"quadraticC"`
|
||||
|
||||
RSquared *float64 `gorm:"column:r_squared" json:"rSquared"` // R平方值
|
||||
}
|
||||
@ -18,6 +18,21 @@ type Belt struct {
|
||||
Name string `gorm:"size:100" json:"name"`
|
||||
}
|
||||
|
||||
// 分析结果存储实体
|
||||
type BeltAnalysis struct {
|
||||
gorm.Model
|
||||
TrainID uint `gorm:"index;not null"` // 关联训练记录
|
||||
BeltID uint `gorm:"index;not null"` // 腰带唯一标识
|
||||
RunType string `gorm:"size:100" json:"RunType"`
|
||||
Avg2min float64 `gorm:"type:double precision"` // 第2分钟平均心率
|
||||
Avg4min float64 `gorm:"type:double precision"` // 第4分钟平均心率
|
||||
Avg6min float64 `gorm:"type:double precision"` // 第6分钟平均心率
|
||||
CurveParamA float64 `gorm:"type:double precision"` // 拟合参数a值
|
||||
CurveParamB float64 `gorm:"type:double precision"` // 拟合参数a值
|
||||
}
|
||||
|
||||
// 中间计算结构（无需持久化）
|
||||
|
||||
// 对应Flutter的HeartRate结构
|
||||
type HeartRate struct {
|
||||
gorm.Model
|
||||
@ -35,8 +50,10 @@ type TrainRecord struct {
|
||||
gorm.Model
|
||||
TrainId uint `gorm:"uniqueIndex" json:"tid"` // 对应Dart的tid字段
|
||||
StartTime int64 `gorm:"type:bigint" json:"time"` // 开始时间戳
|
||||
TestTime int64 `gorm:"type:bigint" json:"testTime"` // 开始时间戳
|
||||
EndTime int64 `gorm:"type:bigint" json:"endTime"` // 结束时间戳[3](@ref)
|
||||
Name string `gorm:"size:100" json:"name"`
|
||||
RunType string `gorm:"size:100" json:"RunType"`
|
||||
MaxHeartRate int `gorm:"type:int" json:"maxHeartRate"`
|
||||
Duration int `gorm:"type:int" json:"duration"` // 持续时间(秒)
|
||||
PeopleNum int `gorm:"type:int" json:"peopleNum"`
|
||||
|
||||
@ -12,12 +12,22 @@ func SetupRouter() *gin.Engine {
|
||||
r := gin.Default()
|
||||
r.Use(middleware.GzipMiddleware())
|
||||
trainingController := controllers.NewTrainingController()
|
||||
stepTrainController := controllers.NewStepTrainingController()
|
||||
|
||||
v1 := r.Group("/api/v1")
|
||||
{
|
||||
records := v1.Group("/train-records").Use(middleware.AuthMiddleware())
|
||||
records := v1.Group("/train-records") //.Use(middleware.AuthMiddleware())
|
||||
{
|
||||
records.POST("", trainingController.CreateTrainingRecord)
|
||||
records.GET("/analysis", trainingController.HandleCurveAnalysis)
|
||||
// 可扩展其他路由：GET, PUT, DELETE等
|
||||
}
|
||||
steps := v1.Group("/step") //.Use(middleware.AuthMiddleware())
|
||||
{
|
||||
steps.POST("", stepTrainController.CreateTrainingRecord)
|
||||
steps.GET("train-records", stepTrainController.GetTrainingRecords)
|
||||
steps.GET("train-data/:trainId", stepTrainController.GetTrainingRecordByTrainId)
|
||||
steps.GET("train-rank/:trainId", stepTrainController.GetTrainingRank)
|
||||
// 可扩展其他路由：GET, PUT, DELETE等
|
||||
}
|
||||
auth := v1.Group("/auth")
|
||||
|
||||
Reference in New Issue
Block a user