报告调整

src/main/java/com/rf/psychological/PsychologicalApplication.java

@@ -1,7 +1,6 @@
 package com.rf.psychological;
 
 import com.querydsl.jpa.impl.JPAQueryFactory;
-import com.rf.psychological.config.SystemExcludeFilter;
 import com.rf.psychological.utils.CPUSerial;
 import com.rf.psychological.utils.Constant;
 import lombok.extern.slf4j.Slf4j;

src/main/java/com/rf/psychological/scale/resultBusiness/scaleResult/COMMONScale.java

@@ -1,5 +1,7 @@
 package com.rf.psychological.scale.resultBusiness.scaleResult;
 
+import cn.hutool.core.util.NumberUtil;
+import cn.hutool.core.util.RandomUtil;
 import com.alibaba.fastjson.JSONArray;
 import com.alibaba.fastjson.JSONObject;
 import com.rf.psychological.dao.model.AnswerEntity;
@@ -95,8 +97,9 @@ public class COMMONScale extends BaseScale {
                                 resultJson.put("结论", scaleMarksEntity.getSymptom());
                             }
                             if (scaleMarksEntity.getImprovementSuggestions() != null && !scaleMarksEntity.getImprovementSuggestions().equals("无")) {
-                                resultMap0.put("建议", scaleMarksEntity.getImprovementSuggestions());
-                                resultJson.put("建议", scaleMarksEntity.getImprovementSuggestions());
+                                String suggest = randomSuggestion(scaleMarksEntity.getImprovementSuggestions());
+                                resultMap0.put("建议", suggest);
+                                resultJson.put("建议", suggest);
                             }
                         }
                     }
@@ -116,8 +119,9 @@ public class COMMONScale extends BaseScale {
                                     resultJson.put(dimensionEntity.getName() + "结论", scaleMarksEntity.getSymptom());
                                 }
                                 if (scaleMarksEntity.getImprovementSuggestions() != null && !scaleMarksEntity.getImprovementSuggestions().equals("无")) {
-                                    resultMap0.put(dimensionEntity.getName() + "建议", scaleMarksEntity.getImprovementSuggestions());
-                                    resultJson.put(dimensionEntity.getName() + "建议", scaleMarksEntity.getImprovementSuggestions());
+                                    String suggest = randomSuggestion(scaleMarksEntity.getImprovementSuggestions());
+                                    resultMap0.put(dimensionEntity.getName() + "建议", suggest);
+                                    resultJson.put(dimensionEntity.getName() + "建议", suggest);
                                 }
                             }
                         }
@@ -155,8 +159,9 @@ public class COMMONScale extends BaseScale {
                             resultJson.put("结论", scaleMarksEntity.getSymptom());
                         }
                         if (scaleMarksEntity.getImprovementSuggestions() != null && !scaleMarksEntity.getImprovementSuggestions().equals("无")) {
-                            resultMap0.put("建议", scaleMarksEntity.getImprovementSuggestions());
-                            resultJson.put("建议", scaleMarksEntity.getImprovementSuggestions());
+                            String suggest = randomSuggestion(scaleMarksEntity.getImprovementSuggestions());
+                            resultMap0.put("建议", suggest);
+                            resultJson.put("建议", suggest);
                         }
                     }
                 }
@@ -174,5 +179,17 @@ public class COMMONScale extends BaseScale {
         return returnJson;
     }
 
+    private String randomSuggestion(String suggestion){
+        List<String> list = Arrays.asList(suggestion.split(";"));
+        if (list.size()>1){
+            int size = list.size();
+            int num = RandomUtil.randomInt(0,size-1);
+            String text = list.get(num).substring(list.get(num).indexOf("."));
+            return text;
+        }else {
+            return suggestion;
+        }
+    }
+
 
 }

src/main/java/com/rf/psychological/scale/resultBusiness/scaleResult/NEWCOMMONScale.java

@@ -1,6 +1,7 @@
 package com.rf.psychological.scale.resultBusiness.scaleResult;
 
 import cn.hutool.core.util.NumberUtil;
+import cn.hutool.core.util.RandomUtil;
 import com.alibaba.fastjson.JSONArray;
 import com.alibaba.fastjson.JSONObject;
 import com.rf.psychological.dao.dto.scale.NewResultDto;
@@ -143,14 +144,17 @@ public class NEWCOMMONScale extends BaseScale {
                     BigDecimal scoreStart = new BigDecimal(tempTotalScore.getScoreStart());
                     BigDecimal scoreEnd = new BigDecimal(tempTotalScore.getScoreEnd());
                     if (scoreDecimal.compareTo(scoreEnd) <= 0 && scoreDecimal.compareTo(scoreStart) >= 0) {
-                        newResultDtos.add(new NewResultDto("总分", df.format(score), tempTotalScore.getSymptom(), tempTotalScore.getImprovementSuggestions(),
+
+                        String suggest = randomSuggestion(tempTotalScore.getImprovementSuggestions());
+                        newResultDtos.add(new NewResultDto("总分", df.format(score), tempTotalScore.getSymptom(), suggest,
                                 tempTotalScore.getFlag(), tempTotalScore.getReference(), tempTotalScore.getNameExplain(), tempTotalScore.getSuggestion(), tempTotalScore.getIsTotalScoreExplain()));
+
                         resultMap0.put("总分解释", tempTotalScore.getSymptom());
-                        resultMap0.put("总分说明", tempTotalScore.getImprovementSuggestions());
+                        resultMap0.put("总分说明", suggest);
                         resultMap0.put("总分解读", tempTotalScore.getNameExplain());
                         resultMap0.put("总分建议", tempTotalScore.getSuggestion());
                         resultJson.put("总分解释", tempTotalScore.getSymptom());
-                        resultJson.put("总分说明", tempTotalScore.getImprovementSuggestions());
+                        resultJson.put("总分说明", suggest);
                         resultJson.put("总分解读", tempTotalScore.getNameExplain());
                         resultJson.put("总分建议", tempTotalScore.getSuggestion());
                         break;
@@ -170,14 +174,16 @@ public class NEWCOMMONScale extends BaseScale {
                 BigDecimal scoreStart = new BigDecimal(tempTotalScore.getScoreStart());
                 BigDecimal scoreEnd = new BigDecimal(tempTotalScore.getScoreEnd());
                 if (scoreDecimal.compareTo(scoreEnd) <= 0 && scoreDecimal.compareTo(scoreStart) >= 0) {
-                    newResultDtos.add(new NewResultDto("总分", df.format(score), tempTotalScore.getSymptom(), tempTotalScore.getImprovementSuggestions(),
+                    String suggest = randomSuggestion(tempTotalScore.getImprovementSuggestions());
+                    newResultDtos.add(new NewResultDto("总分", df.format(score), tempTotalScore.getSymptom(), suggest,
                             tempTotalScore.getFlag(), tempTotalScore.getReference(), tempTotalScore.getNameExplain(), tempTotalScore.getSuggestion(), tempTotalScore.getIsTotalScoreExplain()));
+
                     resultMap0.put("总分解释", tempTotalScore.getSymptom());
-                    resultMap0.put("总分说明", tempTotalScore.getImprovementSuggestions());
+                    resultMap0.put("总分说明", suggest);
                     resultMap0.put("总分解读", tempTotalScore.getNameExplain());
                     resultMap0.put("总分建议", tempTotalScore.getSuggestion());
                     resultJson.put("总分解释", tempTotalScore.getSymptom());
-                    resultJson.put("总分说明", tempTotalScore.getImprovementSuggestions());
+                    resultJson.put("总分说明", suggest);
                     resultJson.put("总分解读", tempTotalScore.getNameExplain());
                     resultJson.put("总分建议", tempTotalScore.getSuggestion());
                     break;
@@ -389,16 +395,28 @@ public class NEWCOMMONScale extends BaseScale {
 
     private static void putDimResult(Map<String, String> resultMap0, JSONObject resultJson, String dimensionName, NewResultDto newResultDto1, ScaleMarksEntity scaleMarksEntity) {
         //resultMap0.put(dimensionName + "常模参考值", scaleMarksEntity.getReference());
+        String suggest = randomSuggestion(scaleMarksEntity.getImprovementSuggestions());
         resultMap0.put(dimensionName + "解释", scaleMarksEntity.getSymptom());
         resultJson.put(dimensionName + "解释", scaleMarksEntity.getSymptom());
         resultMap0.put(dimensionName + "解读", scaleMarksEntity.getNameExplain());
         resultJson.put(dimensionName + "解读", scaleMarksEntity.getNameExplain());
-        resultMap0.put(dimensionName + "说明", scaleMarksEntity.getImprovementSuggestions());
-        resultJson.put(dimensionName + "说明", scaleMarksEntity.getImprovementSuggestions());
+        resultMap0.put(dimensionName + "说明", suggest);
+        resultJson.put(dimensionName + "说明", suggest);
         resultMap0.put(dimensionName + "建议", scaleMarksEntity.getSuggestion());
         resultJson.put(dimensionName + "建议", scaleMarksEntity.getSuggestion());
         BeanUtils.copyProperties(scaleMarksEntity, newResultDto1);
     }
 
+    private static String randomSuggestion(String suggestion){
+        List<String> list = Arrays.asList(suggestion.split(";"));
+        if (list.size()>1){
+            int size = list.size();
+            int num = RandomUtil.randomInt(0,size-1);
+            String text = list.get(num).substring(list.get(num).indexOf("."));
+            return text;
+        }else {
+            return suggestion;
+        }
+    }
 
 }