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update 优化算法

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develop
hhb@hotmail.com 2 months ago
parent 8ec3179cbb
commit 2b56f1b454
3 changed files with 62 additions and 28 deletions
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3
src/main/java/cn/teammodel/controller/admin/service/impl/AdminAppraiseServiceImpl.java
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@ -165,7 +165,8 @@ public class AdminAppraiseServiceImpl implements AdminAppraiseService {
academicYearId,
startTime,
endTime,
classIds
classIds,
"德育"
);
if (res != null) {

78
src/main/java/cn/teammodel/controller/admin/service/impl/LaborEducationServiceImpl.java
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@ -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);
// 如果题目没有知识点或得分为空，跳过
if (knowledgePoints.isEmpty() || score < 0) continue;
// 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, score, Double::sum);
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);
}

5
src/main/java/cn/teammodel/repository/AppraiseRecordRepository.java
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@ -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);
/**

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