诊断的过滤，归一和排序

common-push/pom.xml

@@ -23,6 +23,7 @@
             <version>1.0.0</version>
             <scope>compile</scope>
         </dependency>
+
     </dependencies>
 
     <build>

common-push/src/main/java/org/diagbot/common/push/filter/ClassifyDiag.java

@@ -1,21 +1,51 @@
 package org.diagbot.common.push.filter;
 
 import com.alibaba.fastjson.JSONObject;
+import org.apache.commons.lang3.StringUtils;
 import org.diagbot.common.work.FeatureRate;
 import org.diagbot.common.work.ResponseData;
 import org.diagbot.graph.util.CacheUtil;
 
+import java.text.DecimalFormat;
 import java.util.*;
+import java.util.stream.Stream;
 
 /**
  * Created by kwz on 2019/8/5.
  */
 public class ClassifyDiag {
+    Map<String, String>  diagDepartCache     = CacheUtil.getDiagDepartCache();
+    //get diagClassifyCache
+    Map<String, String>  diagClassifyCache   = CacheUtil.getDiagClassifyCache();
+    //每个诊断所在的级别缓存
+    Map<String, Integer> diagClassifyJiCache = CacheUtil.getDiagClassifyJiCache();
+
     public static void main(String[] args) {
-        Map<String, String> diagClassifyCache = CacheUtil.getDiagClassifyCache();
-        for(Map.Entry<String,String>d:diagClassifyCache.entrySet()){
-            System.out.println(d.getKey()+"\t"+d.getValue());
+
+        List<String> disList = new LinkedList<>();
+        String[] disArray = {"急性胰腺炎","冠心病","急性冠状动脉综合征","急性非ST段抬高型心肌梗死","急性ST段抬高型心肌梗死"
+        ,"三度房室传导阻滞","心力衰竭","急性心力衰竭"};
+         disList = Arrays.asList(disArray);
+        System.out.println("输入的诊断"+disList);
+        List<FeatureRate> inintFeature = new ArrayList<>();
+        Double inintNumber = 0.95;
+        String rate = "";
+        for (String dis:disList) {
+            FeatureRate featureRate = new FeatureRate();
+            featureRate.setFeatureName(dis);
+            inintNumber = inintNumber - 0.1;
+            rate = String.valueOf(inintNumber);
+            featureRate.setRate(rate);
+            inintFeature.add(featureRate);
+        }
+
+        ClassifyDiag classifyDiag = new ClassifyDiag();
+        List<FeatureRate> classify = classifyDiag.diagClassify(inintFeature);
+        System.out.println("hao hai you");
+        for (FeatureRate d:classify) {
+            System.out.println(d.getFeatureName()+"\t"+d.getRate()+"\t"+d.getExtraProperty());
         }
+
     }
 
     /**
@@ -37,9 +67,6 @@ public class ClassifyDiag {
         return updateFeatures;
     }
 
-    //get diagClassifyCache
-    Map<String, String> diagClassifyCache = CacheUtil.getDiagClassifyCache();
-
     /**
      * 诊断归一
      * @param updateFeatures 归一前的诊断
@@ -71,15 +98,391 @@ public class ClassifyDiag {
         //先把警惕的加进去
         if(highDiagList.size()>0){
             for(int j =0;j<updateFeatures.size();j++){
-                if(highDiagList.indexOf(updateFeatures.get(j).getFeatureName()) == 1){
-                    finalDiagList.add(updateFeatures.get(j));
+                FeatureRate featureRate = updateFeatures.get(j);
+                String featureName = featureRate.getFeatureName();
+                int i = highDiagList.indexOf(featureName);
+                if(i >= 0){
+                    finalDiagList.add(featureRate);
+                }
+            }
+        }
+        /**
+         * 这里处理一下可能诊断剔除的功能
+         * 如果图谱推出的诊断和可能诊断有层级关系，就把对应的可能诊断剔除
+         */
+        List<String> newBIgDiagList = this.removeKeng(queDiagList, bigDiagList);
+
+        if(queDiagList != null && queDiagList.size()>0){
+            //图谱归一
+            Set<String> queSet = this.diagProcess(queDiagList);
+            if(queSet != null && queSet.size()>0){
+                for (String queDis:queSet) {
+                    if(queDiagList.indexOf(queDis)>=0){ //可以找到，就取出来，用原来的
+                        FeatureRate feature = this.getFeature(updateFeatures, queDis);
+                        finalDiagList.add(feature);
+                    }else {
+                        FeatureRate featureRate = new FeatureRate();
+                        featureRate.setFeatureName(queDis);
+                        featureRate.setDesc("{\\\"确诊\\\":\\\"\\\"}");
+                        featureRate.setExtraProperty(diagDepartCache.get(queDis));
+                        featureRate.setSource("neo4j");
+                        finalDiagList.add(featureRate);
+                    }
                 }
             }
         }
-        //归一确诊
 
 
+        if(newBIgDiagList!= null && newBIgDiagList.size()>0){
+            //大数据的可能诊断归一和排序
+            List<FeatureRate> featureRates = this.sortFeatureList(newBIgDiagList, updateFeatures);
+            finalDiagList.addAll(featureRates);
+        }
+
         return finalDiagList;
 
     }
+
+    /**
+     * 诊断排序（诊断分为I类和II类，I类在前，II类在后，没有分类的诊断认为是I类）
+     * @param updateFeatureRates  //入参（通过过滤条件过滤后）
+     * @return
+     */
+    public List<FeatureRate> sortDiag(List<FeatureRate> updateFeatureRates){
+        Map<String, String> diagSortCache = CacheUtil.getDiagSortCache();
+        List<String> finalDiagList = new LinkedList<>();
+        List<String> neoDiagList = new LinkedList<>();
+        List<String> bigDataIDiagList = new LinkedList<>();
+        List<String> bigDataIIDiagList = new LinkedList<>();
+        List<FeatureRate> finalDiagFeature = new LinkedList<>();
+        if(updateFeatureRates != null || updateFeatureRates.size()>0){
+            for (FeatureRate feature:updateFeatureRates) {
+                String featureName = feature.getFeatureName();
+                String source = feature.getSource();
+                if("neo4j".equals(source)){
+                    neoDiagList.add(featureName);
+                }else {
+                    String s = diagSortCache.get(featureName);
+                    if(StringUtils.isNotEmpty(s)){
+                        if("Ⅰ".equals(s)){
+                            bigDataIDiagList.add(featureName);
+                        }else if("Ⅱ".equals(s)){
+                            bigDataIIDiagList.add(featureName);
+                        }
+                    }else {
+                        bigDataIDiagList.add(featureName);
+                    }
+                }
+            }
+        }
+        finalDiagList.addAll(neoDiagList);
+        finalDiagList.addAll(bigDataIDiagList);
+        finalDiagList.addAll(bigDataIIDiagList);
+        if(finalDiagList != null && finalDiagList.size()>0){
+            for (String diag:finalDiagList){
+                for (FeatureRate f:updateFeatureRates) {
+                    if(diag.equals(f.getFeatureName())){
+                        finalDiagFeature.add(f);
+                        break;
+                    }
+                }
+            }
+        }
+        return finalDiagFeature;
+    }
+
+    /**
+     * 去除可能诊断和确诊有关系的诊断
+     * @param queDiagList
+     * @param bigDiagList
+     * @return
+     */
+    public List<String> removeKeng(List<String> queDiagList,List<String> bigDiagList){
+        List<String> bigList = new ArrayList<>();
+        Set<String> queAll = new HashSet<>();
+        if(queDiagList.size()>0 && bigDiagList.size()>0){
+            for (String dis:queDiagList) {
+                String s = diagClassifyCache.get(dis);
+                if(s != null){
+                    queAll.add(s);
+                }
+                queAll.add(dis);
+                List<Object> key = this.getKey(diagClassifyCache, dis);
+                if(key != null && key.size()>0){
+                    for (Object o:key) {
+                        queAll.add(o.toString());
+                        List<Object> key1 = this.getKey(diagClassifyCache, o.toString());
+                        if(key1 !=null && key1.size()>0){
+                            for (Object o1:key1
+                                 ) {
+                                queAll.add(o1.toString());
+                            }
+                        }
+                    }
+
+                }
+
+            }
+        }
+        System.out.println(queAll);
+        String[] strings = queAll.stream().toArray(String[]::new);
+        if(bigDiagList != null && bigDiagList.size()>0){
+            for (String dis:bigDiagList) {
+                if(Arrays.asList(strings).indexOf(dis) == -1){
+                    bigList.add(dis);
+                }
+            }
+        }
+        return bigList;
+    }
+
+
+
+
+
+    /**
+     * 诊断归一和排序
+     * @param disList
+     * @return
+     */
+    public Set<String> diagProcess(List<String> disList){
+        Set<String> first = new HashSet<>();
+        Set<String> second= new HashSet<>();
+        Set<String> third= new HashSet<>();
+        Set<String> other= new HashSet<>();
+
+        /**
+         * 分级
+         * 初始化每个病出现的次数为0
+         */
+        Map<String, Integer> children_cnt = new HashMap<>();
+        for (String dis:disList) {
+            Integer ji = diagClassifyJiCache.get(dis);
+            if(ji != null){
+                if(1 == ji){
+                    first.add(dis);
+                    children_cnt.put(dis,0);
+                }else if(2 == ji){
+                    second.add(dis);
+                    children_cnt.put(dis,0);
+                }else if(3 == ji){
+                    third.add(dis);
+                    children_cnt.put(dis,0);
+                }
+            }else {
+                other.add(dis);
+            }
+        }
+        /**
+         * 从孙子找父亲，根据父亲找爷爷
+         */
+        if(third != null && third.size()>0){
+            for (String dis:third) {
+                String s = diagClassifyCache.get(dis);
+                Integer count = children_cnt.get(s);
+                if(s != null){
+                    children_cnt.put(s,(count == null)?1:count+1);
+                    second.add(s);
+                }
+
+            }
+        }
+
+        if(second != null && second.size()>0){
+            for (String dis:second) {
+                String s = diagClassifyCache.get(dis);
+                Integer count = children_cnt.get(s);
+                if(s != null){
+                    children_cnt.put(s,(count == null)?1:count+1);
+                    first.add(s);
+                }
+            }
+        }
+        List<String> pushDiag = new ArrayList<>();
+        //从顶级往下级依次看
+        for (String dis:first) {
+            Integer count = children_cnt.get(dis);
+            if(count == 0){
+                pushDiag.add(dis);
+            }else if(count == 1){
+                List<Object> key = this.getKey(diagClassifyCache, dis);
+                for (String diss:second) {
+                    Integer c2 = children_cnt.get(diss);
+                    if(key.contains(diss)){
+                        if(c2 == 0){
+                            pushDiag.add(diss);
+                        }else if(c2 == 1){
+                            List<Object> key1 = this.getKey(diagClassifyCache, diss);
+                            for (String disss:third) {
+                                if(key1.contains(disss)){
+                                    pushDiag.add(disss);
+                                }
+                            }
+                        }else if(c2 >1){
+                            pushDiag.add(diss);
+                        }
+                    }
+
+                }
+            }else if(count >1){
+                pushDiag.add(dis);
+            }
+
+        }
+        pushDiag.addAll(other); //归一后的
+
+        Set<String> finalList = new LinkedHashSet<>();
+        Map<String,String> disRate = new HashMap<>();//诊断-->百分比
+        for (String dis:disList) {
+            int i = pushDiag.indexOf(dis);
+            if(i >= 0){
+                finalList.add(dis);
+
+            }else {
+                List<Object> testList= new ArrayList<>();
+                String s = diagClassifyCache.get(dis);
+                if(StringUtils.isNotEmpty(s)){
+                    testList.add(s);
+                }
+                List<Object> key = this.getKey(diagClassifyCache, dis);
+                boolean b = testList.addAll(key);
+                for (Object dis1:testList) {
+                    if(pushDiag.indexOf(dis1)>=0){
+                        finalList.add(dis1.toString());
+
+                    }
+                }
+            }
+        }
+        return finalList;
+
+    }
+
+    /**
+     * 根据rate排序
+     * @param diss 大数据可能诊断列表
+     * @param updates 所有推送的诊断
+     * @return 排好序并且归一的可能诊断列表
+     */
+    public List<FeatureRate> sortFeatureList(List<String> diss,List<FeatureRate> updates){
+        DecimalFormat df = new DecimalFormat("0.####");
+       List<FeatureRate> sortFeatures = new LinkedList<>();
+        Set<String> strings = this.diagProcess(diss);
+
+        Map<String,Double> disRate = new HashMap<>();
+        //归一确诊
+        if(diss!= null &&diss.size()>0){
+            //归一后的确诊（图谱出来的）
+
+            if(strings != null && strings.size()>0){
+                for (String queDis:strings) {
+                    List<Object> testCollect = new ArrayList<>();
+//                    FeatureRate feature = classifyDiag.getFeature(inintFeature, queDis);
+                    //如果能找到就把相关联的rate加起来
+                    testCollect.add(queDis);
+
+                    String s = diagClassifyCache.get(queDis);
+                    if(s != null){
+                        testCollect.add(s);
+                    }
+                    List<Object> key = this.getKey(diagClassifyCache, queDis);
+                    testCollect.addAll(key);
+                    Double count = 0.0;
+                    for (String dis:diss) {
+                        if(testCollect.indexOf(dis) >= 0){
+                            FeatureRate feature1 = this.getFeature(updates, dis);
+                            String rate1 = feature1.getRate();
+                            count = count+Double.parseDouble(rate1);
+                        }
+                    }
+                    disRate.put(queDis,count);
+                }
+            }
+
+        }
+        //根据rate排序
+        List<Map.Entry<String,Double>> list = new ArrayList<>(disRate.entrySet());
+        Collections.sort(list, new Comparator<Map.Entry<String, Double>>() {
+            @Override
+            public int compare(Map.Entry<String, Double> o1, Map.Entry<String, Double> o2) {
+                return o2.getValue().compareTo(o1.getValue());
+            }
+        });
+        for (Map.Entry<String,Double> s:list) {
+            System.out.println(s.getKey()+"\t"+s.getValue());
+            FeatureRate featureRate = new FeatureRate();
+            featureRate.setRate(df.format(s.getValue()));
+            featureRate.setFeatureName(s.getKey());
+            featureRate.setExtraProperty(diagDepartCache.get(s.getKey()));
+            sortFeatures.add(featureRate);
+        }
+
+        return sortFeatures;
+    }
+
+    /**
+     * 根据诊断名找到这个feature
+     * @param updateFeatures
+     * @param disName
+     * @return
+     */
+    public FeatureRate getFeature(List<FeatureRate> updateFeatures,String disName){
+        FeatureRate f = new FeatureRate();
+        for (FeatureRate fe:updateFeatures){
+            if(disName.equals(fe.getFeatureName())){
+                f = fe;
+            }
+        }
+        return f;
+    }
+
+    /**
+     * dis找大类
+     * @param inputs
+     * @return
+     */
+    public List<String> getDisList(List<String> inputs){
+        List<String> newDiagList = new ArrayList<>();
+        if(inputs!= null && inputs.size()>0){
+            for (String dis:inputs) {
+                String s = diagClassifyCache.get(dis);
+                if(StringUtils.isNotEmpty(s)){
+                    newDiagList.add(s);
+                }else {
+                    newDiagList.add(dis);
+                }
+
+            }
+        }
+        return newDiagList;
+    }
+
+    /**
+     * 统计列表中每个字符出现的次数
+     * @param inputs 输入列表
+     * @return
+     */
+    public Map<String,Integer> fildCount(List<String> inputs){
+        Map<String,Integer> map = new HashMap<>();
+        for (String dis:inputs) {
+            Integer count = map.get(dis);
+            map.put(dis,(count == null)?1:count+1);
+        }
+        return map;
+    }
+
+    public List<Object>  getKey(Map map, Object value){
+        Set set = map.entrySet(); //通过entrySet()方法把map中的每个键值对变成对应成Set集合中的一个对象
+        Iterator<Map.Entry<Object, Object>> iterator = set.iterator();
+        List<Object> arrayList = new ArrayList();
+        while(iterator.hasNext()){
+            //Map.Entry是一种类型，指向map中的一个键值对组成的对象
+            Map.Entry<Object, Object> entry = iterator.next();
+            if(entry.getValue().equals(value)){
+                arrayList.add(entry.getKey());
+            }
+        }
+        return arrayList;
+    }
+
 }

graph-web/src/main/java/org/diagbot/graphWeb/work/FilterSortDiag.java

@@ -15,6 +15,7 @@ import java.util.*;
  */
 public class FilterSortDiag {
     Logger logger = LoggerFactory.getLogger(FilterSortDiag.class);
+
     /**
      * 过滤诊断
      */

graph-web/src/main/java/org/diagbot/graphWeb/work/GraphCalculate.java

@@ -65,8 +65,7 @@ public class GraphCalculate {
         logger.info("从分词系统接收到的词 :" + ss);
         System.out.println("Participle takes: " + (System.currentTimeMillis()-starttime)/1000d + 's');
 
-        String[] featureTypes = searchData.getFeatureType().split(",");
-        List<String> featureTypeList = Arrays.asList(featureTypes);
+        List<String> featureTypeList = Arrays.asList(searchData.getFeatureTypes());
         logger.info("featureTypeList : " + featureTypeList);
         inputList.addAll(ss);
         if(neo4jAPI == null){

graph/src/main/java/org/diagbot/graph/util/CacheUtil.java

@@ -3,7 +3,6 @@ package org.diagbot.graph.util;
 import org.apache.commons.lang3.StringUtils;
 import org.diagbot.nlp.participle.cfg.Configuration;
 import org.diagbot.nlp.participle.cfg.DefaultConfig;
-import org.neo4j.cypher.internal.frontend.v2_3.ast.Foreach;
 
 import java.util.HashMap;
 import java.util.List;
@@ -15,6 +14,54 @@ public class CacheUtil {
     public static Map<String,String> vitalMap=null;
     public static Map<String,String> disgSortMap=null;
     public static Map<String,String> diagClassifyMap = null;
+    public static Map<String,Integer> diagClassifyJiMap = null;
+    //诊断科室衍射
+    public static Map<String, String> doc_result_mapping_diag_map = null;
+
+    //疾病科室，获取缓存
+    public static Map<String,String> getDiagDepartCache(){
+        String path = "doc_result_mapping_diag.dict";
+        Configuration configuration = new DefaultConfig();
+        if(doc_result_mapping_diag_map == null){
+            doc_result_mapping_diag_map = new HashMap<>();
+            List<String> contentList = configuration.readFileContents(path);
+            for (String s:contentList) {
+                String[] splits = s.split("\\|");
+                doc_result_mapping_diag_map.put(splits[0],splits[1]);
+            }
+        }
+        return doc_result_mapping_diag_map;
+    }
+
+    //疾病分级解析，获取缓存
+    public static Map<String,Integer> getDiagClassifyJiCache(){
+        String path = "diagClassify.dict";
+        Configuration configuration = new DefaultConfig();
+        if(diagClassifyJiMap == null){
+            diagClassifyJiMap = new HashMap<>();
+            List<String> contentList = configuration.readFileContents(path);
+            String diagName =null,bigdiagName=null;
+            String[] diagSort =null;
+            for (String s:contentList) {
+                String[] splits = s.split("\\|");
+                if (splits.length >= 2) {
+                    diagName = splits[0].trim();//疾病本体
+                    bigdiagName = splits[1].trim();//疾病大类
+                    diagClassifyJiMap.put(bigdiagName, 2);
+                    diagClassifyJiMap.put(diagName,1);
+                    if (splits.length == 3) {
+                        diagSort = splits[2].split("\\、");
+                        for (String dis : diagSort) {
+                            if (StringUtils.isNotEmpty(dis.trim())) {
+                                diagClassifyJiMap.put(dis.trim(), 3);
+                            }
+                        }
+                    }
+                }
+            }
+        }
+        return diagClassifyJiMap;
+    }
     //疾病归一解析，获取缓存
     public static Map<String,String> getDiagClassifyCache(){
         String path = "diagClassify.dict";
@@ -26,20 +73,18 @@ public class CacheUtil {
             String[] diagSort =null;
             for (String s:contentList) {
                 String[] splits = s.split("\\|");
-                if(splits.length >= 2){
+                if (splits.length >= 2) {
                     diagName = splits[0].trim();//疾病本体
                     bigdiagName = splits[1].trim();//疾病大类
-                    if(splits.length == 2){
-                        diagClassifyMap.put(bigdiagName,diagName);
-                    }else if(splits.length == 3){
+                    diagClassifyMap.put(bigdiagName, diagName);
+                    if (splits.length == 3) {
                         diagSort = splits[2].split("\\、");
-                        for (String dis:diagSort) {
-                            if(StringUtils.isNotEmpty(dis.trim())){
-                                diagClassifyMap.put(dis.trim(),bigdiagName);
+                        for (String dis : diagSort) {
+                            if (StringUtils.isNotEmpty(dis.trim())) {
+                                diagClassifyMap.put(dis.trim(), bigdiagName);
                             }
                         }
                     }
-
                 }
             }
         }

graph/src/main/resources/diagClassify.dict

@@ -18,3 +18,64 @@ QY8HRySr7Iwnp75iBJ/Vj+3XaTjV4VFOlsI/pFsgIb0u2WJVxeidQQ==
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graph/src/test/java/org/diagbot/graph/CacheFile.java

@@ -6,18 +6,47 @@ import org.diagbot.pub.utils.security.EncrypDES;
 import java.io.FileWriter;
 import java.sql.Connection;
 import java.sql.ResultSet;
+import java.sql.SQLException;
 import java.sql.Statement;
+import java.util.*;
 
 public class CacheFile {
     public static void main(String[] args) {
         CacheFile cacheFile = new CacheFile();
-        cacheFile.diagClassifyMaping();
+        cacheFile.diagSort();
 
     }
-
+    //疾病 -- 科室
+    public void diagDepartMaping(){
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
+        Connection conn = nlpJdbc.connect();
+        Statement st = null;
+        ResultSet rs = null;
+        try {
+            EncrypDES encrypDES = new EncrypDES();//加密对象
+            String path = this.getClass().getClassLoader().getResource("").getPath();
+            path = path.substring(0, path.indexOf("target"));
+            String sql = "SELECT k1.lib_name diag_name, k2.lib_name dept_name FROM kl_concept_common kcc, kl_concept k1, kl_concept k2 " +
+                    "where kcc.concept_id = k1.id and kcc.dept_id = k2.id " +
+                    "and k1.lib_type = 18 and kcc.dept_id  is not null";
+            st = conn.createStatement();
+            rs = st.executeQuery(sql);
+            List<Map.Entry<String, String>> libaryList = rsToMap(rs, true);
+            FileWriter fw = new FileWriter(path + "src/main/resources/doc_result_mapping_diag.dict");
+            for (Map.Entry<String, String> entry : libaryList) {
+                fw.write(encrypDES.encrytor(entry.getKey() + "|" + entry.getValue()));
+                fw.write("\n");
+            }
+            fw.close();
+        } catch (Exception e) {
+            e.printStackTrace();
+        } finally {
+            nlpJdbc.close(rs, st, conn);
+        }
+    }
     //疾病分类归一
     public void diagClassifyMaping(){
-        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/bigdata-web?useUnicode=true&characterEncoding=UTF-8");
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
         Connection conn = nlpJdbc.connect();
         Statement st = null;
         ResultSet rs = null;
@@ -46,7 +75,7 @@ public class CacheFile {
     }
     //诊断大小类对应
     public void diagSort(){
-        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/bigdata-web?useUnicode=true&characterEncoding=UTF-8");
+        MysqlJdbc nlpJdbc = new MysqlJdbc("root", "diagbot@20180822", "jdbc:mysql://192.168.2.235:3306/med-s?useUnicode=true&characterEncoding=UTF-8");
         Connection conn = nlpJdbc.connect();
         Statement st = null;
         ResultSet rs = null;
@@ -169,4 +198,28 @@ public class CacheFile {
             nlpJdbc.close(rs, st, conn);
         }
     }
+
+    private List<Map.Entry<String, String>> rsToMap(ResultSet rs, boolean isJoin) throws SQLException {
+        String r1 = "";
+        String r2 = "";
+        Map<String, String> libraryMap = new HashMap<>(10);
+        while (rs.next()) {
+            r1 = rs.getString(1);
+            r2 = rs.getString(2);
+            if (libraryMap.get(r1) == null) {
+                libraryMap.put(r1, r2);
+            } else if (isJoin && libraryMap.get(r1) != null) {
+                libraryMap.put(r1, libraryMap.get(r1) + "," + r2);
+            }
+        }
+
+        List<Map.Entry<String, String>> libraryList = new ArrayList<Map.Entry<String, String>>(libraryMap.entrySet());
+        Collections.sort(libraryList, new Comparator<Map.Entry<String, String>>() {
+            public int compare(Map.Entry<String, String> o1, Map.Entry<String, String> o2) {
+                return o1.getKey().compareTo(o2.getKey());
+            }
+        });
+
+        return libraryList;
+    }
 }

push-web/src/main/java/org/diagbot/push/controller/AlgorithmController.java

@@ -147,11 +147,13 @@ public class AlgorithmController extends BaseController {
             //把所有的诊断拿出来经过过滤层过滤
             ClassifyDiag classifyDiag = new ClassifyDiag();
             List<FeatureRate> upfes = classifyDiag.filterDiag(graphResponseData, graphFeatureRates);
-            List<FeatureRate> classifyFeature = classifyDiag.diagClassify(upfes);
-            FilterSortDiag filterSortDiag = new FilterSortDiag();
-            List<FeatureRate> filterDiagList = filterSortDiag.filterDiag(graphResponseData, graphFeatureRates);
-            List<FeatureRate> filterSortDiagList = filterSortDiag.sortDiag(filterDiagList);
-            bigDataResponseData.setDis(filterSortDiagList);
+            List<FeatureRate> classify = classifyDiag.diagClassify(upfes);
+            List<FeatureRate> featureRates = classifyDiag.sortDiag(classify);
+//            List<FeatureRate> classifyFeature = classifyDiag.diagClassify(upfes);
+//            FilterSortDiag filterSortDiag = new FilterSortDiag();
+//            List<FeatureRate> filterDiagList = filterSortDiag.filterDiag(graphResponseData, graphFeatureRates);
+//            List<FeatureRate> filterSortDiagList = filterSortDiag.sortDiag(filterDiagList);
+            bigDataResponseData.setDis(featureRates);
         }
         //推送出的诊断信息作为参数传入知识图谱
         List<FeatureRate> pushDiags = new ArrayList<>();