Merge branch 'master' of D:\Workspaces\push with conflicts.

bigdata-web/src/main/java/org/diagbot/bigdata/common/ApplicationCacheUtil.java

@@ -120,16 +120,20 @@ public class ApplicationCacheUtil {
                     String op = "";
                     String[] fileContentSplit = null;
                     //每一个标准词根据大于小于符号切开，不然进行分词时还是会得到原本的标准词
-                    if (fileContent.contains(">=") || fileContent.contains("≥")
-                            || fileContent.contains(">") || fileContent.contains("大于")
+                    if (fileContent.contains(">") || fileContent.contains("大于")
                             || fileContent.contains("＞") || fileContent.contains("超过")) {
                         op = ">";
                         fileContentSplit = fileContent.split(operationGreater);
-                    } else if (fileContent.contains("<=") || fileContent.contains("≤")
-                            || fileContent.contains("<") || fileContent.contains("小于")
+                    } else if (fileContent.contains("<") || fileContent.contains("小于")
                             || fileContent.contains("＜") || fileContent.contains("少于")) {
                         op = "<";
                         fileContentSplit = fileContent.split(operationSmaller);
+                    } else if (fileContent.contains(">=") || fileContent.contains("≥")){
+                        op = ">=";
+                        fileContentSplit = fileContent.split(operationGreater);
+                    } else if (fileContent.contains("<=") || fileContent.contains("≤")) {
+                        op = "<=";
+                        fileContentSplit = fileContent.split(operationGreater);
                     } else {
                         continue;
                     }
@@ -168,7 +172,7 @@ public class ApplicationCacheUtil {
                             standWordObjVal.put("value", lexeme.getText());
                         } else if (lexemeNegativeEnum == NegativeEnum.UNIT
                                 || lexemeNegativeEnum == NegativeEnum.EVENT_TIME) {
-                            standWordObjVal.put("unit", lexeme.getText());
+                            standWordObjVal.put("unit", lexeme.getText().toLowerCase());
                         }
                         if (lexemes.size() == i) {
                             standWordObjVal.put("op", op);

bigdata-web/src/main/java/org/diagbot/bigdata/work/ParamsDataProxy.java

@@ -66,16 +66,14 @@ public class ParamsDataProxy {
             }
         }
         //所有信息参与推送
-//        searchData.setSymptom(searchData.getSymptom() + searchData.getVital()
-//                + searchData.getLis() + searchData.getPacs() + searchData.getPast() + searchData.getOther() + searchData.getIndications());
-        if (StringUtils.isNotEmpty(searchData.getSymptom())) {
-            searchData.setSymptom(searchData.getSymptom().trim());
-        }
+        //        searchData.setSymptom(searchData.getSymptom() + searchData.getVital()
+        //                + searchData.getLis() + searchData.getPacs() + searchData.getPast() + searchData.getOther() + searchData.getIndications());
+        searchData.setSymptom(searchData.getSymptom().trim());
         //一次推送多个类别信息
         String[] featureTypes = searchData.getFeatureType().split(",");
         //featureType统一转换
         String[] convertFeatureTypes = new String[featureTypes.length];
-        for (int i = 0;i<featureTypes.length; i++) {
+        for (int i = 0; i < featureTypes.length; i++) {
             convertFeatureTypes[i] = convertFeatureType(searchData.getSysCode(), featureTypes[i]);
         }
         searchData.setFeatureType(StringUtils.join(convertFeatureTypes, ","));
@@ -83,45 +81,37 @@ public class ParamsDataProxy {
 
         //获取入参中的特征信息
         FeatureAnalyze fa = new FeatureAnalyze();
-        List<Map<String, Object>> featuresList = new ArrayList<>();
+
         if (!StringUtils.isEmpty(searchData.getSymptom())) {
             //提取现病史
-            featuresList = fa.start(searchData.getSymptom(), FeatureType.FEATURE);
+            List<Map<String, Object>> featuresList = fa.start(searchData.getSymptom(), FeatureType.FEATURE);
             paramFeatureInit(searchData, featuresList);
-        }
-        if (!StringUtils.isEmpty(searchData.getVital())) {
             //提取体征
             featuresList = fa.start(searchData.getVital(), FeatureType.FEATURE);
             paramFeatureInit(searchData, featuresList);
-        }
-        if (!StringUtils.isEmpty(searchData.getPast())) {
             //提取既往史
             featuresList = fa.start(searchData.getPast(), FeatureType.FEATURE);
             paramFeatureInit(searchData, featuresList);
-        }
-        if (!StringUtils.isEmpty(searchData.getOther()) || !StringUtils.isEmpty(searchData.getIndications())) {
             //提取其他史等
-            featuresList = fa.start(searchData.getOther() == null?"":searchData.getOther() + searchData.getIndications() == null?"":searchData.getIndications(), FeatureType.FEATURE);
+            featuresList = fa.start(searchData.getOther() + searchData.getIndications(), FeatureType.FEATURE);
             paramFeatureInit(searchData, featuresList);
-        }
-        if (!StringUtils.isEmpty(searchData.getPacs())) {
+
             featuresList = fa.start(searchData.getPacs(), FeatureType.PACS);
             paramFeatureInit(searchData, featuresList);
-        }
-        if (!StringUtils.isEmpty(searchData.getLis())) {
+
             featuresList = fa.start(searchData.getLis(), FeatureType.LIS);
             paramFeatureInit(searchData, featuresList);
-        }
+
             // 清洗特征词，去除词性不匹配的词
             searchData = cleanFeature(featuresList, fa, searchData);
-        if (!StringUtils.isEmpty(searchData.getOther())) {
+
             //如果既往史中诊断信息，需要提取这个特征
             featuresList = fa.start(searchData.getOther(), FeatureType.DIAG);
             paramFeatureInit(searchData, featuresList);
         }
 
         if (!StringUtils.isEmpty(searchData.getDiag()) && StringUtils.isEmpty(searchData.getSymptom())) {
-            featuresList = fa.start(searchData.getDiag(), FeatureType.DIAG);
+            List<Map<String, Object>> featuresList = fa.start(searchData.getDiag(), FeatureType.DIAG);
             paramFeatureInit(searchData, featuresList);
         }
     }
@@ -138,7 +128,7 @@ public class ParamsDataProxy {
         //下了诊断且其他信息全为空 反推标识
         boolean reverse = !StringUtils.isEmpty(searchData.getDiag()) && StringUtils.isEmpty(searchData.getSymptom());
         for (int i = 0; i < featureTypes.length; i++) {
-//            featureTypes[i] = convertFeatureType(sysCode, featureTypes[i]);
+            //            featureTypes[i] = convertFeatureType(sysCode, featureTypes[i]);
             if (featureTypes[i] != null) {
                 //模型
                 switch (FeatureType.parse(featureTypes[i])) {
@@ -326,6 +316,7 @@ public class ParamsDataProxy {
             }
         }
         //将标准词中体征指标值（数字）与分词结果中体征指标值（数字）比较
+        String newStandWord = "";
         for (String f : featureType) {
             String[] features = f.split("\t");
             if (standWords.containsKey(features[0])) {
@@ -333,25 +324,47 @@ public class ParamsDataProxy {
                 for (Map<String, String> standWordMap : standWordList) {
                     if (standWordMap.containsKey("unit") && standWordMap.containsKey("value")) {
                         if (features.length == 2) {
-                            judgment(sData, features, standWordMap);
+                            newStandWord = judgment(features, standWordMap,newStandWord);
                         } else {
-                            if (standWordMap.get("unit").equals(features[2])) {
-                                judgment(sData, features, standWordMap);
+                            if (standWordMap.get("unit").equals(features[2].toLowerCase())) {
+                                newStandWord = judgment(features, standWordMap,newStandWord);
                             }
                         }
                     } else if (standWordMap.containsKey("value")) {
                         if (features.length == 2) {
-                            judgment(sData, features, standWordMap);
+                            newStandWord = judgment(features, standWordMap,newStandWord);
                         }
                     }
                 }
             }
         }
+        String addStandWords = "";
+        String smallerStandWord = "";
+        boolean flag = true;
+        for (String standWord:newStandWord.split(",")) {
+            if (!"".equals(standWord) || standWord.length() > 0){
+                if (!standWord.contains("/")){
+                    addStandWords += "," +standWord;
+                } else {
+                    if (standWord.contains("<") || standWord.contains("<=")|| standWord.contains("小于")){
+                        smallerStandWord = "," +standWord;
+                    } else {
+                        addStandWords += "," +standWord;
+                        flag = false;
+                    }
+                }
+            }
+        }
+        if (flag){
+            addStandWords += smallerStandWord;
+        }
+        sData.setSymptom(sData.getSymptom() + "," + addStandWords);
+        System.out.println(sData.getSymptom());
         return sData;
     }
 
     //将标准词中体征指标值（数字）与分词结果中体征指标值（数字）比较
-    private void judgment(SearchData sData, String[] features, Map<String, String> standWordMap) {
+    private String judgment(String[] features, Map<String, String> standWordMap,String standWord) {
         if (hasDigit(features[1])) {
             try {
                 if (">".equals(standWordMap.get("op"))) {
@@ -365,17 +378,14 @@ public class ParamsDataProxy {
                             String[] values = standWordMap.get("value").split("/");
                             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) {
-                                sData.setSymptom(sData.getSymptom() + "," + standWordMap.get("standword"));
-                                System.out.println(sData.getSymptom());
+                            if (featuresSBP > standWordSBP || featuresDBP > standWordDBP) {
+                                standWord += "," + standWordMap.get("standword");
                             }
                         }
                     } else {
                         String num = getNum(standWordMap.get("value"));
                         if (Double.valueOf(getNum(features[1])) > Double.valueOf(num)) {
-                            sData.setSymptom(sData.getSymptom() + "," + standWordMap.get("standword"));
-                            System.out.println(sData.getSymptom());
-
+                            standWord += "," + standWordMap.get("standword");
                         }
                     }
                 } else if ("<".equals(standWordMap.get("op"))) {
@@ -389,23 +399,64 @@ public class ParamsDataProxy {
                             String[] values = standWordMap.get("value").split("/");
                             Integer standWordSBP = Integer.valueOf(values[0]); //收缩压
                             Integer standWordDBP = Integer.valueOf(values[1]); //舒张压
-                            if (featuresSBP < standWordSBP && featuresDBP < standWordDBP) {
-                                sData.setSymptom(sData.getSymptom() + "," + standWordMap.get("standword"));
-                                System.out.println(sData.getSymptom());
+                            if (featuresSBP < standWordSBP || featuresDBP < standWordDBP) {
+                                standWord += "," + standWordMap.get("standword");
                             }
                         }
                     } else {
                         String num = getNum(standWordMap.get("value"));
                         if (Double.valueOf(getNum(features[1])) < Double.valueOf(num)) {
-                            sData.setSymptom(sData.getSymptom() + "," + standWordMap.get("standword"));
-                            System.out.println(sData.getSymptom());
+                            standWord += "," + standWordMap.get("standword");
+                        }
+                    }
+                } else if (">=".equals(standWordMap.get("op"))) {
+                    //单独处理  血压小于90/60mmHg   类似情况
+                    if (standWordMap.get("value").contains("/")) {
+                        if (features[1].contains("/")) {
+                            String[] feature = features[1].split("/");
+                            Integer featuresSBP = Integer.valueOf(feature[0]); //收缩压
+                            Integer featuresDBP = Integer.valueOf(feature[1]); //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
+                            if (featuresSBP >= standWordSBP || featuresDBP >= standWordDBP) {
+                                standWord += "," + standWordMap.get("standword");
+                            }
+                        }
+                    } else {
+                        String num = getNum(standWordMap.get("value"));
+                        if (Double.valueOf(getNum(features[1])) >= Double.valueOf(num)) {
+                            standWord += "," + standWordMap.get("standword");
+                        }
+                    }
+                }else if ("<=".equals(standWordMap.get("op"))) {
+                    //单独处理  血压小于90/60mmHg   类似情况
+                    if (standWordMap.get("value").contains("/")) {
+                        if (features[1].contains("/")) {
+                            String[] feature = features[1].split("/");
+                            Integer featuresSBP = Integer.valueOf(feature[0]); //收缩压
+                            Integer featuresDBP = Integer.valueOf(feature[1]); //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
+                            if (featuresSBP <= standWordSBP || featuresDBP <= standWordDBP) {
+                                standWord += "," + standWordMap.get("standword");
+                            }
+                        }
+                    } else {
+                        String num = getNum(standWordMap.get("value"));
+                        if (Double.valueOf(getNum(features[1])) <= Double.valueOf(num)) {
+                            standWord += "," + standWordMap.get("standword");
                         }
                     }
                 }
-            }catch (NumberFormatException e){
+            } catch (NumberFormatException e) {
                 e.printStackTrace();
             }
         }
+        return standWord;
     }
 
     private boolean hasDigit(String content) {
@@ -429,20 +480,20 @@ public class ParamsDataProxy {
     private SearchData cleanFeature(List<Map<String, Object>> featuresList, FeatureAnalyze fa,
                                     SearchData searchData) {
         // 在输入的辅检文本中，只提取辅检信息
-        String[] PACS_Feature = {Constants.word_property_PACS,
-                Constants.word_property_PACS_Detail, Constants.word_property_PACS_Result};
-        searchData = removeFeature(searchData.getLis(), fa, searchData, PACS_Feature,  FeatureType.PACS);
+        String[] PACS_Feature = { Constants.word_property_PACS,
+                Constants.word_property_PACS_Detail, Constants.word_property_PACS_Result };
+        searchData = removeFeature(searchData.getLis(), fa, searchData, PACS_Feature, FeatureType.PACS);
 
         // 在输入的化验文本中，只提取化验信息
-        String[] LIS_Feature = {Constants.word_property_LIS,
-                Constants.word_property_LIS_Detail, Constants.word_property_LIS_Result};
-        searchData = removeFeature(searchData.getPacs(), fa, searchData, LIS_Feature,  FeatureType.LIS);
+        String[] LIS_Feature = { Constants.word_property_LIS,
+                Constants.word_property_LIS_Detail, Constants.word_property_LIS_Result };
+        searchData = removeFeature(searchData.getPacs(), fa, searchData, LIS_Feature, FeatureType.LIS);
 
         return searchData;
     }
 
     private SearchData removeFeature(String text, FeatureAnalyze fa,
-                                     SearchData searchData, String[] properties,  FeatureType featureType) {
+                                     SearchData searchData, String[] properties, FeatureType featureType) {
         String name = "";
         Boolean related = false;
 
@@ -454,17 +505,17 @@ public class ParamsDataProxy {
                     String[] property = item.get("property").toString().split(",");
                     for (String prop : property) {
                         if (Arrays.asList(properties).contains(prop)) {
-//                            related = true;
+                            //                            related = true;
                             searchData.getInputs().remove(name);
                             break;
                         }
                     }
 
-//                    if (!related) {
-//                        searchData.getInputs().remove(name);
-//                    }
-//9
-//                    related = false;
+                    //                    if (!related) {
+                    //                        searchData.getInputs().remove(name);
+                    //                    }
+                    //9
+                    //                    related = false;
                 }
             }
 

bigdata-web/src/main/resources/kl_result_mapping_standword.dict

@@ -70,3 +70,10 @@ Dtl+1pXSqsCdXBQ/c9gkD5Tz+I5xZDsT
 Z8+G5B4yQAJkIniXV51XYQbfxHf7qINy
 OiF4bqXkMEEAhZ46GKERaQ==
 6AdBr9ESXwxuAA4RzKQl7T8g5XqLhLp48PwpFWkMTalKYBGd+lGX+w==
+Q1zDVi3U7rI9l9Q+tlWf4Ee1cgYEdEeI/hgyPNS4IPeyXSyYJNIU/qAb9hNrEulyYTDxNHZVHIA=
+wD/+T2Rb77ANCqoCZftfGUpgEZ36UZf7
+6AdBr9ESXwx67Pnnr+kPStAxGsaAxJuz
+6AdBr9ESXwxuAA4RzKQl7Qx20j9Jd6MvshwHLo/mnJ9KYBGd+lGX+w==
+yE3028GRw4t2DqtTuKPPOg==
+SZ1VckZNWlv6YxRRpZKkEoKBWdL/M3D3
+U3FxTQC11De8fGTn0OiIddGYv9lbEEIT

bigdata-web/src/test/java/org/diagbot/AddStandWordTest.java

@@ -36,7 +36,7 @@ public class AddStandWordTest {
         long cacheTime = endCacheTime - startTime;
         System.out.println("处理标准词最终用了:" + cacheTime + "毫秒.");
         SearchData searchData = new SearchData();
-        searchData.setSymptom("关节僵硬3min");
+        searchData.setSymptom("血压120/43mmhg,收缩压180.5mmhg,");
         long splitStartTime = System.currentTimeMillis();
         LexemePath<Lexeme> data = ParticipleUtil.participle(searchData.getSymptom());
         ParamsDataProxy paramsDataProxy = new ParamsDataProxy();
@@ -46,7 +46,6 @@ public class AddStandWordTest {
         long seconds = endTime - startTime;
         System.out.println("添加标准词使用了:"+splitSeconds + "毫秒.");
         System.out.println("处理文本总共使用了:"+seconds + "毫秒.");
-        AddStandWordTest addStandWordTest = new AddStandWordTest();
     }
 
     public static void getStandWordFeatureType() throws IOException {