update 优化算法

src/main/java/cn/teammodel/controller/admin/service/impl/AdminAppraiseServiceImpl.java

@@ -165,7 +165,8 @@ public class AdminAppraiseServiceImpl implements AdminAppraiseService {
                 academicYearId,
                 startTime,
                 endTime,
-                classIds
+                classIds,
+                "德育"
         );
 
         if (res != null) {

src/main/java/cn/teammodel/controller/admin/service/impl/LaborEducationServiceImpl.java

@@ -126,7 +126,8 @@ public class LaborEducationServiceImpl implements LaborEducationService {
                 academicYearId,
                 startTime,
                 endTime,
-                classIds
+                classIds,
+                "德育"
         );
         //表扬的次数
         int rightCount = (int) res.stream().filter(RecordVo::isPraise).count();
@@ -138,6 +139,11 @@ public class LaborEducationServiceImpl implements LaborEducationService {
                 .filter(Objects::nonNull) // 过滤掉 null 值
                 .distinct()
                 .count();
+        List<String> targetId = res.stream()
+                .map(RecordVo::getTargetId)
+                .filter(Objects::nonNull) // 过滤掉 null 值
+                .distinct()
+                .collect(Collectors.toList());
 
         List<String> recordIds = new ArrayList<>();
         for (LessonRecord record : records) {
@@ -298,6 +304,7 @@ public class LaborEducationServiceImpl implements LaborEducationService {
                     convertedScore = 100.0; // 如果次数超过最大次数，设置为满分
                 } else {
                     convertedScore = (count / maxCount) * 100;
+                    convertedScore = Double.parseDouble(String.format("%.2f", convertedScore));
                 }
                 subjectiveTotal += convertedScore;
 
@@ -310,7 +317,7 @@ public class LaborEducationServiceImpl implements LaborEducationService {
                 String combinedScore = count + "/" + objectiveScore;
                 */
                 double finalCount = convertedScore;
-                double finalScore = score / knowledgeBlockCount;
+                double finalScore = score;
                 finalScore = Double.parseDouble(String.format("%.2f", finalScore));
                 double finalScore1 = finalScore;
                 combinedScores.put(knowledgeBlock, new HashMap<String, Object>() {{
@@ -324,15 +331,19 @@ public class LaborEducationServiceImpl implements LaborEducationService {
             }
 
             // 计算客观平均分
-            double objectiveAverage = (knowledgeBlockCount > 0) ? objectiveTotal : 0.0;
+            double objectiveAverage = (knowledgeBlockCount > 0) ? objectiveTotal / knowledgeBlockCount : 0.0;
+            objectiveAverage = Double.parseDouble(String.format("%.2f", objectiveAverage));
+            //计算主观平均分
+            double subjectiveAverage = (subjectiveTotal > 0) ? subjectiveTotal / knowledgeBlockCount : 0.0;
+            subjectiveAverage = Double.parseDouble(String.format("%.2f", subjectiveAverage));
 
             // 计算综合得分（主观占 60%，客观占 40%）
-            double compositeScore = (subjectiveTotal * 0.6) + (objectiveAverage * 0.4);
+            double compositeScore = (subjectiveAverage * 0.6) + (objectiveAverage * 0.4);
             compositeScore = Double.parseDouble(String.format("%.2f", compositeScore));
 
             // 更新返回数据
             studentResult.put("scores", combinedScores);
-            studentResult.put("subjectiveTotal", subjectiveTotal);
+            studentResult.put("subjectiveTotal", subjectiveAverage);
             studentResult.put("objectiveTotal", objectiveAverage);
             studentResult.put("compositeScore", compositeScore);
         }
@@ -639,7 +650,13 @@ public class LaborEducationServiceImpl implements LaborEducationService {
                 String block = entry.getKey();
                 int count = entry.getValue();
                 double maxCount = 50.0;
-                double convertedScore = (count / maxCount) * 100;
+                double convertedScore;
+                if (count > maxCount) {
+                    convertedScore = 100.0; // 如果次数超过最大次数，设置为满分
+                } else {
+                    convertedScore = (count / maxCount) * 100;
+                    convertedScore = Double.parseDouble(String.format("%.2f", convertedScore));
+                }
                 convertedScores.put(block, convertedScore);
             }
 
@@ -743,65 +760,68 @@ public class LaborEducationServiceImpl implements LaborEducationService {
             Map<String, List<Double>> points,
             Map<String, Double> knowledgeTotalScore) {
 
-        // 记录每个知识点在所有考试中的平均分总和及考试次数
         Map<String, Double> knowledgeTotalAverage = new HashMap<>();
         Map<String, Integer> knowledgeExamCount = new HashMap<>();
 
-        // 过滤出当前学生的考试结果
         for (ExamClassResult examResult : examResults) {
             int studentIndex = examResult.getStudentIds().indexOf(studentId);
             if (studentIndex == -1) continue;
             int status = examResult.getStatus().get(studentIndex);
-            if (status == 1) continue; // 跳过无效考试
+            if (status == 1) continue;
 
-            // 获取当前考试的知识点和题目分数
             List<List<String>> knowledgeList = knowledgeMap.get(examResult.getExamId());
             List<Double> pointList = points.get(examResult.getExamId());
             if (knowledgeList == null || pointList == null) continue;
 
-            // 获取学生的得分列表
             List<List<Double>> studentScores = examResult.getStudentScores();
             if (studentIndex >= studentScores.size() || studentScores.get(studentIndex) == null) continue;
             List<Double> studentScoreList = studentScores.get(studentIndex);
 
-            // 确保数据一致性
             if (knowledgeList.size() != studentScoreList.size()) continue;
 
-            // 记录当前考试中每个知识点的总得分和题目数量
             Map<String, Double> currentExamKnowledgeTotal = new HashMap<>();
             Map<String, Integer> currentExamKnowledgeCount = new HashMap<>();
 
             // 遍历每道题
             for (int i = 0; i < studentScoreList.size(); i++) {
-                String knowledge = knowledgeList.get(i).get(0); // 取第一个知识点
+                List<String> knowledgePoints = knowledgeList.get(i); // 题目对应的知识点列表
                 double score = studentScoreList.get(i);
 
-                // 累加当前考试中该知识点的总得分和题目数量
+                // 如果题目没有知识点或得分为空，跳过
-                currentExamKnowledgeTotal.merge(knowledge, score, Double::sum);
+                if (knowledgePoints.isEmpty() || score < 0) continue;
-                currentExamKnowledgeCount.merge(knowledge, 1, Integer::sum);
+
+                // 将题目得分分摊到每个知识点
+                double scorePerKnowledge = score / knowledgePoints.size();
+
+                // 遍历该题的所有知识点
+                for (String knowledge : knowledgePoints) {
+                    // 累加当前考试中该知识点的总得分和题目数量
+                    currentExamKnowledgeTotal.merge(knowledge, scorePerKnowledge, Double::sum);
+                    currentExamKnowledgeCount.merge(knowledge, 1, Integer::sum);
+                }
             }
 
-            // 计算当前考试中每个知识点的平均分，并累加到总平均分
+            // 计算当前考试中每个知识点的平均分（总得分/题目数量）
             for (String knowledge : currentExamKnowledgeTotal.keySet()) {
                 double total = currentExamKnowledgeTotal.get(knowledge);
                 int count = currentExamKnowledgeCount.get(knowledge);
-                double average = total / count; // 当前考试内该知识点的平均分
+                double average = total / count;
 
-                // 将该考试的平均分累加到总平均分中，并增加考试次数
+                // 累加跨考试的总平均分和考试次数
                 knowledgeTotalAverage.merge(knowledge, average, Double::sum);
                 knowledgeExamCount.merge(knowledge, 1, Integer::sum);
             }
         }
 
-        // 计算每个知识点的最终平均分（所有考试平均分的平均）
+        // 计算最终平均分（所有考试平均分的平均）
         for (String knowledge : knowledgeTotalAverage.keySet()) {
             double totalAverage = knowledgeTotalAverage.get(knowledge);
-            int examCount = knowledgeExamCount.getOrDefault(knowledge, 1);
+            int examCount = knowledgeExamCount.get(knowledge);
             double finalAverage = totalAverage / examCount;
+            finalAverage = Double.parseDouble(String.format("%.2f", finalAverage));
             knowledgeTotalScore.put(knowledge, finalAverage);
         }
 
-        // 返回知识点平均分对象列表
         return knowledgeTotalScore.entrySet().stream()
                 .map(entry -> new KnowledgeScoreRate(entry.getKey(), entry.getValue()))
                 .collect(Collectors.toList());
@@ -873,7 +893,13 @@ public class LaborEducationServiceImpl implements LaborEducationService {
                 String block = entry.getKey();
                 int count = entry.getValue();
                 double maxCount = 50.0;
-                double convertedScore = (count / maxCount) * 100;
+                double convertedScore;
+                if (count > maxCount) {
+                    convertedScore = 100.0; // 如果次数超过最大次数，设置为满分
+                } else {
+                    convertedScore = (count / maxCount) * 100;
+                    convertedScore = Double.parseDouble(String.format("%.2f", convertedScore));
+                }
                 convertedScores.put(block, convertedScore);
             }
 
@@ -1054,7 +1080,13 @@ public class LaborEducationServiceImpl implements LaborEducationService {
                 String block = entry.getKey();
                 int count = entry.getValue();
                 double maxCount = 50.0;
-                double convertedScore = (count / maxCount) * 100;
+                double convertedScore;
+                if (count > maxCount) {
+                    convertedScore = 100.0; // 如果次数超过最大次数，设置为满分
+                } else {
+                    convertedScore = (count / maxCount) * 100;
+                    convertedScore = Double.parseDouble(String.format("%.2f", convertedScore));
+                }
                 convertedScores.put(block, convertedScore);
             }
 

src/main/java/cn/teammodel/repository/AppraiseRecordRepository.java

@@ -77,9 +77,10 @@ public interface AppraiseRecordRepository extends CosmosRepository<AppraiseRecor
             "c.academicYearId =  @academicYearId and " +
             "(IS_NULL(@startTime) or n.createTime >= @startTime) and " +
             "(IS_NULL(@endTime) or n.createTime <= @endTime) and " +
-            "c.classId in (@ids)"
+            "c.classId in (@ids) and " +
+            "array_contains(n.appraiseNode.path ,@typeName)"
     )
-    List<RecordVo> latestRecords(String code, String academicYearId, Long startTime, Long endTime, Collection<String> ids);
+    List<RecordVo> latestRecords(String code, String academicYearId, Long startTime, Long endTime, Collection<String> ids,String typeName);
 
 
     /**