package AEU.AVC.SUQ.engine;
import java.io.IOException;
import java.util.List;
import java.util.Map;

import AEU.OCI.AVC.SUQ.estimation.C.EmotionSample;
import AEU.OCI.AVC.SUQ.estimation.C.RatioMap;
import AEU.OEI.AVC.SUQ.SVU.EOP.E.RatioMap_E;
import AVQ.ASQ.OVQ.OSQ.VSQ.obj.WordFrequency;
import OCI.AVC.SUQ.SVQ.MPC.fhmm.C.EmotionMap;
import OCI.ME.analysis.C.A;
//import OCI.ME.analysis.C.A;
import OEI.AVC.SUQ.SVQ.MPC.fhmm.E.EmotionMap_E;
import OEI.ME.analysis.E.CogsBinaryForest_AE;
import SVQ.stable.StableString;
//作者,著作权人： 罗瑶光，浏阳
public class EnvironmentInit{
  public EmotionMap getEmotionMap() {
    return emotionMap;
  }

  public void I_EmotionMap(EmotionMap emotionMap) {
    this.emotionMap = emotionMap;
  }

  public A get_A() {
    return _A;
  }

  public void I__A(CogsBinaryForest_AE _A) {
    this._A = _A;
  }

  public Map<String, Object> getPositive() {
    return positive;
  }

  public void I_Positive(Map<String, Object> positive) {
    this.positive = positive;
  }

  public Map<String, Object> getNegative() {
    return negative;
  }

  public void I_Negative(Map<String, Object> negative) {
    this.negative = negative;
  }

  public Map<String, Object> getMotivation() {
    return motivation;
  }

  public void I_Motivation(Map<String, Object> motivation) {
    this.motivation = motivation;
  }

  public Map<String, Object> getTrending() {
    return trending;
  }

  public void I_Trending(Map<String, Object> trending) {
    this.trending = trending;
  }

  public Map<String, Object> getPrediction() {
    return prediction;
  }

  public void I_Prediction(Map<String, Object> prediction) {
    this.prediction = prediction;
  }

  public List<String> getSets() {
    return sets;
  }

  public void I_Sets(List<String> sets) {
    this.sets = sets;
  }

  public RatioMap getRationMap() {
    return rationMap;
  }

  public void I_RationMap(RatioMap rationMap) {
    this.rationMap = rationMap;
  }

  public Map<Integer, WordFrequency> getWordFrequencyMap() {
    return wordFrequencyMap;
  }

  public void I_WordFrequencyMap(Map<Integer, WordFrequency> wordFrequencyMap) {
    this.wordFrequencyMap = wordFrequencyMap;
  }

  public Map<String, EmotionSample> getEmotionSampleMap() {
    return emotionSampleMap;
  }

  public void I_EmotionSampleMap(Map<String, EmotionSample> emotionSampleMap) {
    this.emotionSampleMap = emotionSampleMap;
  }

  public double getPositiveCount() {
    return positiveCount;
  }

  public void I_PositiveCount(double positiveCount) {
    this.positiveCount = positiveCount;
  }

  public double getNegativeCount() {
    return negativeCount;
  }

  public void I_NegativeCount(double negativeCount) {
    this.negativeCount = negativeCount;
  }

  public double getTotalCount() {
    return totalCount;
  }

  public void I_TotalCount(double totalCount) {
    this.totalCount = totalCount;
  }

  public Map<String, Object> getDistinction() {
    return distinction;
  }

  public void I_Distinction(Map<String, Object> distinction) {
    this.distinction = distinction;
  }
  private EmotionMap emotionMap;
  private CogsBinaryForest_AE _A;
  private Map<String, Object> positive;
  private Map<String, Object> negative;
  private Map<String, Object> motivation;
  private Map<String, Object> trending;
  private Map<String, Object> prediction;
  private Map<String, Object> distinction;
  private List<String> sets;
  private RatioMap rationMap;
  private Map<Integer, WordFrequency> wordFrequencyMap;
  private Map<String, EmotionSample> emotionSampleMap;
  private double positiveCount;
  private double negativeCount;
  private double totalCount;
  @SuppressWarnings("unused")
  public static void main(String[] argv) throws IOException {
    EnvironmentInit environmentInit = new EnvironmentInit();
    environmentInit.IV_(StableString.text1);
    Map<String, EmotionSample> environmentSampleMap 
    = environmentInit.getEmotionSampleMap();
  }

  public void IV_(String text) throws IOException {
    emotionMap = new EmotionMap_E(); 
    emotionMap.IV_MotivationMap();
    emotionMap.IV_TrendingMap();
    emotionMap.IV_PredictionMap();
    emotionMap.IV_DistinctionMap();
    _A = new CogsBinaryForest_AE();
    //_A.IV_Mixed();
    _A.IV_Mixed();
    motivation = emotionMap.getMotivationMap();
    trending = emotionMap.getTrendingMap();
    prediction = emotionMap.getPredictionMap();
    distinction = emotionMap.getDistinctionMap();
    //sets = _A.parserMixedString(text);//稍后统一更新下接口为parserMixedString
    sets = _A.parserMixedString(text);//
    wordFrequencyMap = _A.getWordFrequencyByReturnSortMap(sets);
    rationMap = new RatioMap_E();
    emotionSampleMap = rationMap.getEnvironmentSampleMap(wordFrequencyMap);
    rationMap.IQ_Motivation(emotionSampleMap, motivation);
    rationMap.IQ_Trending(emotionSampleMap, trending);
    rationMap.IQ_Prediction(emotionSampleMap, prediction);
    rationMap.IQ_Distinction(emotionSampleMap, distinction);
  }
  
  public void IV_Exclude_A(String text
  , CogsBinaryForest_AE _AInput) throws IOException {
    emotionMap = new EmotionMap_E(); 
    emotionMap.IV_MotivationMap();
    emotionMap.IV_TrendingMap();
    emotionMap.IV_PredictionMap();
    emotionMap.IV_DistinctionMap();
    _A = _AInput;
    motivation = emotionMap.getMotivationMap();
    trending = emotionMap.getTrendingMap();
    prediction = emotionMap.getPredictionMap();
    distinction = emotionMap.getDistinctionMap();
    sets = _AInput.parserString(text);
    wordFrequencyMap = _AInput.getWordFrequencyByReturnSortMap(sets);
    rationMap = new RatioMap_E();
    emotionSampleMap = rationMap.getEnvironmentSampleMap(wordFrequencyMap);
    rationMap.IQ_Motivation(emotionSampleMap, motivation);
    rationMap.IQ_Trending(emotionSampleMap, trending);
    rationMap.IQ_Prediction(emotionSampleMap, prediction);
    rationMap.IQ_Distinction(emotionSampleMap, distinction);
  }
  
  public void IV_FromEmotion(Map<Integer
  , WordFrequency> getWordFrequencyMap) throws IOException {
    emotionMap = new EmotionMap_E(); 
    emotionMap.IV_MotivationMap();
    emotionMap.IV_TrendingMap();
    emotionMap.IV_PredictionMap();
    emotionMap.IV_DistinctionMap();
    //parser sentence
    motivation = emotionMap.getMotivationMap();
    trending = emotionMap.getTrendingMap();
    prediction = emotionMap.getPredictionMap();
    distinction = emotionMap.getDistinctionMap();
    //map
    rationMap = new RatioMap_E();
    emotionSampleMap = rationMap.getEnvironmentSampleMap(getWordFrequencyMap);
    rationMap.IQ_Motivation(emotionSampleMap, motivation);
    rationMap.IQ_Trending(emotionSampleMap, trending);
    rationMap.IQ_Prediction(emotionSampleMap, prediction);
    rationMap.IQ_Distinction(emotionSampleMap, distinction);
  }
  
  public void IV_FromEmotionExcludeEmotion(Map<Integer
  , WordFrequency> getWordFrequencyMap
  , EmotionMap emotionMapInput) throws IOException {
    emotionMap = emotionMapInput;
    motivation = emotionMap.getMotivationMap();
    trending = emotionMap.getTrendingMap();
    prediction = emotionMap.getPredictionMap();
    distinction = emotionMap.getDistinctionMap();
    rationMap = new RatioMap_E();
    emotionSampleMap = rationMap.getEnvironmentSampleMap(getWordFrequencyMap);
    rationMap.IQ_Motivation(emotionSampleMap, motivation);
    rationMap.IQ_Trending(emotionSampleMap, trending);
    rationMap.IQ_Prediction(emotionSampleMap, prediction);
    rationMap.IQ_Distinction(emotionSampleMap, distinction);
  }
  
}