package PEQ.AMV.ECS.test;
import java.io.IOException;

import java.util.HashMap;
import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;

import OCI.ME.analysis.C.A;
import OEI.ME.analysis.E.CogsBinaryForest_AE;
import SVQ.stable.StableCommon;
import SVQ.stable.StableString;

//著作权人+ 作者= 罗瑶光
//作者,著作权人： 罗瑶光，浏阳
public class RNN_IDETest{
   private String text= StableString.text1;
   public static void main(String[] argv) throws IOException
   , InstantiationException, IllegalAccessException {
      RNN_IDETest rNN_IDETest= new RNN_IDETest();
      rNN_IDETest.getIDEMatrix();   
   }

   public String[][] getIDEMatrix(String text) throws IOException
   , InstantiationException, IllegalAccessException{
      this.text= text;
      return this.getIDEMatrix();
   }
   
   public String[][] getIDEMatrix() throws IOException
   , InstantiationException, IllegalAccessException{
      SensingTest sensingTest = new SensingTest();
      String[][] sensingMatrix = sensingTest.getMatrix(this.text);
      Map<String, List<Double>> map = new HashMap<>();
      for(int i = 0; i < sensingMatrix.length; i++) {
         List<Double> list = new LinkedList<>(); 
         list.add(1.0);
         map.put(sensingMatrix[i][0], list);
      }
      String[][] ideMatrix = new String [sensingMatrix.length][4];
      List<String> sets = sensingTest.getSets();
      Map<String, String> pos = sensingTest.getPosCnToCn();
      Iterator<String> setsIterator = sets.iterator();
      double count = 1;
      //map position
      while(setsIterator.hasNext()) {
         String word = setsIterator.next();
         if(map.containsKey(word)) {
            List<Double> list  = map.get(word);
            list.add(count);
            map.put(word, list);
         }   
         count++;
      }
      //RNN LOOP position
      int ideMatrixCount = 0;
      Iterator<String> mapIterator = map.keySet().iterator();
      while(mapIterator.hasNext()) {
         String word = mapIterator.next();
         List<Double> list = map.get(word);
         double dovFactor = 1;
         double popFactor = 0;
         double eopFactor = 1;
         double dovCount = 1;
         for(int i = 0; i < list.size(); i++) {
            for(int j = i + 1; j < list.size(); j++) {
               dovCount ++;
               dovFactor += list.get(j);
            }
            dovFactor += Math.abs(list.get(i) - dovFactor);
            eopFactor += (eopFactor + list.get(i)) / 2;
         }
         //pos normalization
         if(pos.containsKey(word)) {
            popFactor += pos.get(word).contains("动")? 16: 0;
            popFactor += pos.get(word).contains("名")? 4: 0;
            popFactor += pos.get(word).contains("形")? 2: 0;   
         }
         ideMatrix[ideMatrixCount][0] = word;
         ideMatrix[ideMatrixCount][1] = "" + popFactor;
         ideMatrix[ideMatrixCount][2] = "" + dovFactor/dovCount;
         ideMatrix[ideMatrixCount][3] = "" + eopFactor;
         ideMatrixCount++;
      }
      return ideMatrix;
   }

   public String[][] getIDEMatrixExclude_A(CogsBinaryForest_AE _A
   , String string) throws IOException {
      SensingTest sensingTest = new SensingTest();
      String[][] sensingMatrix = sensingTest.getMatrix(string, _A);
      Map<String, List<Double>> map = new HashMap<>();
      for(int i = 0; i < sensingMatrix.length; i++) {
         List<Double> list = new LinkedList<>(); 
         list.add(1.0);
         map.put(sensingMatrix[i][0], list);
      }
      String[][] ideMatrix = new String [sensingMatrix.length][4];
      List<String> sets = sensingTest.getSets();
      Map<String, String> pos = sensingTest.getPosCnToCn();
      Iterator<String> setsIterator = sets.iterator();
      double count = 1;
      //map position
      while(setsIterator.hasNext()) {
         String word = setsIterator.next();
         if(map.containsKey(word)) {
            List<Double> list  = map.get(word);
            list.add(count);
            map.put(word, list);
         }   
         count++;
      }
      //RNN LOOP position
      int ideMatrixCount = 0;
      Iterator<String> mapIterator = map.keySet().iterator();
      while(mapIterator.hasNext()) {
         String word = mapIterator.next();
         List<Double> list = map.get(word);
         double dovFactor = 1;
         double popFactor = 0;
         double eopFactor = 1;
         double dovCount = 1;
         for(int i = 0; i < list.size(); i++) {
            for(int j = i + 1; j < list.size(); j++) {
               dovCount ++;
               dovFactor += list.get(j);
            }
            dovFactor += Math.abs(list.get(i) - dovFactor);
            eopFactor += (eopFactor + list.get(i)) / 2;
         }
         //pos normalization
         if(pos.containsKey(word)) {
            popFactor += pos.get(word).contains("动")? 16: 0;
            popFactor += pos.get(word).contains("名")? 4: 0;
            popFactor += pos.get(word).contains("形")? 2: 0;   
         }

         ideMatrix[ideMatrixCount][0] = word;
         ideMatrix[ideMatrixCount][1] = "" + popFactor;
         ideMatrix[ideMatrixCount][2] = "" + dovFactor/dovCount;
         ideMatrix[ideMatrixCount][3] = "" + eopFactor;
         ideMatrixCount++;
      }
      return ideMatrix;
   }

   public String[][] getIDEMatrixExclude_A(SensingTest sensingTest
   , String[][] ann, A _A, String string) {
      //敏感度 意识 sensing
      String[][] sensingMatrix = ann;
      Map<String, List<Double>> map = new HashMap<>();
      for(int i = 0; i < sensingMatrix.length; i++) {
         List<Double> list = new LinkedList<>(); 
         list.add(1.0);
         map.put(sensingMatrix[i][0], list);
      }
      String[][] ideMatrix= new String [sensingMatrix.length][4];
      List<String> sets= sensingTest.getSets();
      Map<String, String> pos= sensingTest.getPosCnToCn();
      Iterator<String> setsIterator= sets.iterator();
      double count= 1;
      //map position
      //开始计算图距离
      while(setsIterator.hasNext()) {
         String word= setsIterator.next();
         if(map.containsKey(word)) {
            List<Double> list= map.get(word);
            list.add(count);
            map.put(word, list);
         }   
         count++;
      }
      //RNN LOOP position
      int ideMatrixCount= 0;
      Iterator<String> mapIterator= map.keySet().iterator();
      while(mapIterator.hasNext()) {
         String word= mapIterator.next();
         List<Double> list= map.get(word);
         double dovFactor= 1; //距离distance的距离 distance of same vebals
         double popFactor= 0; // 语义距离 part of speech
         double eopFactor= 1; // 位移距离 eclid of parts 我全部会注释 到处是猫腻
         double dovCount= 1; // 计数
         for(int i= 0; i< list.size(); i++) {
            for(int j= i + 1; j< list.size(); j++) {
               dovCount++;
               dovFactor+= list.get(j);
            }
            dovFactor+= Math.abs(list.get(i)- dovFactor); 
            //平方和距离开方
            eopFactor+= (eopFactor+ list.get(i))/ 2;
            // 欧基里德用来计算熵增
         }
         //pos normalization
         if(pos.containsKey(word)) {
            popFactor+= pos.get(word).contains("名")? 16: 0;
            popFactor+= pos.get(word).contains("动")? 5: 0;
            popFactor+= pos.get(word).contains("医")? 3: 0;
            popFactor+= pos.get(word).contains("谓")? 3: 0;
            popFactor+= pos.get(word).contains("形")? 2: 0;
         }
         ideMatrix[ideMatrixCount][0]= word;
         ideMatrix[ideMatrixCount][1]= StableCommon.STRING_EMPTY+ popFactor;
         ideMatrix[ideMatrixCount][2]
         = StableCommon.STRING_EMPTY+ dovFactor/ dovCount;// 平均distance数
         ideMatrix[ideMatrixCount][3]= StableCommon.STRING_EMPTY+ eopFactor;
         ideMatrixCount++;
      }
      //这里再2018年 最老的版本我用的是system来进行print
      , 后来包装成函数我就注释掉了,后来优化就删去了system 的打印函数,  罗瑶光20210420
      return ideMatrix;
   }
}