更新根据诊断依据标准词处理症状，并在症状后添加标准词

aipt-service/src/main/java/com/diagbot/facade/ClinicalFacade.java

@@ -70,7 +70,9 @@ public class ClinicalFacade {
         SearchVo sData = searchVo;
         Map<String, List<Map<String, String>>> standWord = getStandWord();
         Response<List<Lexeme>> resp = nlpServiceClient.split(sData.getSymptom());
-        addStandWord(resp.getData(), standWord, sData);
+        if (null != resp && null != resp.getData()) {
+            addStandWord(resp.getData(), standWord, sData);
+        }
 
         sData.setLisArr(processLis(sData.getLisArr()));
 
@@ -149,7 +151,6 @@ public class ClinicalFacade {
         return list;
     }
 
-
     public List<ScaleContent> getContent(String scaleName, String pushContent) {
         List<ScaleContent> list = scaleContentService.getContentByName(scaleName);
         for (ScaleContent scaleContent : list) {
@@ -203,11 +204,7 @@ public class ClinicalFacade {
         //根据收集到的分词结果把体征指标和对应体征指标值（数字）拼接
         List<String> featureType = new ArrayList<>();
         for (int i = 0; i < feature.size(); i++) {
-            if (i < feature.size() - 1) {
-                if (feature.get(i).getProperty().contains("33") && feature.get(i + 1).getProperty().contains("28")) {
-                    featureType.add(feature.get(i).getText() + "\t" + feature.get(i + 1).getText());
-                }
-            }
+            boolean featureTypeState = true;
             if (i < feature.size() - 2) {
                 if ((feature.get(i).getProperty().contains("33") && feature.get(i + 1).getProperty().contains("28")
                         && feature.get(i + 2).getProperty().contains("2"))
@@ -215,6 +212,12 @@ public class ClinicalFacade {
                         && feature.get(i + 2).getProperty().contains("9"))) {
                     featureType.add(feature.get(i).getText() + "\t" + feature.get(i + 1).getText() + "\t"
                             + feature.get(i + 2).getText());
+                    featureTypeState = false;
+                }
+            }
+            if (i < feature.size() - 1 && featureTypeState) {
+                if (feature.get(i).getProperty().contains("33") && feature.get(i + 1).getProperty().contains("28")) {
+                    featureType.add(feature.get(i).getText() + "\t" + feature.get(i + 1).getText());
                 }
             }
         }
@@ -253,21 +256,17 @@ public class ClinicalFacade {
             if (features[1].contains("/")) {
                 if (standWordMap.get("value").contains("/")) {
                     String[] feature = features[1].split("/");
-                    Integer featuresSBP = Integer.valueOf(feature[0]); //收缩压
-                    Integer featuresDBP = Integer.valueOf(feature[1]); //舒张压
+                    Integer featuresSBP = Integer.valueOf(feature[0]); //分词特征收缩压
+                    Integer featuresDBP = Integer.valueOf(feature[1]); //分词特征舒张压
 
                     String[] values = standWordMap.get("value").split("/");
-                    Integer standWordSBP = Integer.valueOf(values[0]); //收缩压
-                    Integer standWordDBP = Integer.valueOf(values[1]); //舒张压
+                    Integer standWordSBP = Integer.valueOf(values[0]); //标准词收缩压
+                    Integer standWordDBP = Integer.valueOf(values[1]); //标准词舒张压
                     if (featuresSBP > standWordSBP && featuresDBP > standWordDBP) {
                         String standWord = standWordKey + standWordMap.get("op") + standWordMap.get("value") + standWordMap.get("unit") + "。";
                         sData.setSymptom(sData.getSymptom() + standWord);
                         System.out.println(sData.getSymptom());
-                    } else {
-                        return;
                     }
-                } else {
-                    return;
                 }
             } else {
                 String num = getNum(standWordMap.get("value"));
@@ -296,11 +295,7 @@ public class ClinicalFacade {
                         String standWord = standWordKey + standWordMap.get("op") + standWordMap.get("value") + standWordMap.get("unit") + "。";
                         sData.setSymptom(sData.getSymptom() + standWord);
                         System.out.println(sData.getSymptom());
-                    } else {
-                        return;
                     }
-                } else {
-                    return;
                 }
             } else {
                 String num = getNum(standWordMap.get("value"));
@@ -332,15 +327,15 @@ public class ClinicalFacade {
         Map<String, List<Map<String, String>>> standWordObj = new HashMap<>();
         List<List<Lexeme>> splitStandWords = new ArrayList<>();
         List<Lexeme> data = null;
-        File file = null;
         BufferedReader reader = null;
+        InputStream inputStream = null;
         String line = "";
         try {
             //file = ResourceUtils.getFile("classpath:standword.txt");
-//            Resource resource = new ClassPathResource("standword.txt");
+            //            Resource resource = new ClassPathResource("standword.txt");
             ClassPathResource classPathResource = new ClassPathResource("standword.txt");
-            InputStream inputStream =classPathResource.getInputStream();
-//            file = resource.getFile();
+            inputStream = classPathResource.getInputStream();
+            //            file = resource.getFile();
             reader = new BufferedReader(new InputStreamReader(inputStream, "UTF-8"));
             while ((line = reader.readLine()) != null) {
                 data = nlpServiceClient.split(line).getData();
@@ -354,6 +349,7 @@ public class ClinicalFacade {
         } finally {
             try {
                 reader.close();
+                inputStream.close();
             } catch (IOException e) {
                 e.printStackTrace();
             }
@@ -372,7 +368,6 @@ public class ClinicalFacade {
                 }
                 if (lexeme.getProperty().contains("1") || lexeme.getProperty().contains("5")
                         || lexeme.getProperty().contains("33")) {
-
                     if (!standWordObj.containsKey(lexeme.getText())) {
                         standWordObj.put(lexeme.getText(), standWordObjValList);
                     } else {