package experiments;

import java.io.*;
import java.text.DateFormat;
import java.text.SimpleDateFormat;
import java.util.*;

import weka.filters.Filter;
import model.Model;
import org.apache.log4j.Logger;
import weka.core.Instances;
import weka.core.OptionHandler;

/**
 * Created by hailiu on 2016/2/22.
 */
public class RunPredictionServer {
    protected Logger logger = Logger.getLogger(RunPredictionServer.class);

    final String configFile = "data/config.txt";//input file path
    String[] option = new String[50];
    String filter;
    ArrayList filterList;
    String DataFile;
    protected static DateFormat dateFormat = new SimpleDateFormat("yyyyMMdd_HHmmss");
    protected static Date date = new Date();
    protected static String resultFilename = dateFormat.format(date)+"_results";
    Map map;

    public RunPredictionServer() {
        this.filterList = new ArrayList();
        setClassName();
    }

    public static void main(String[] args)
    {
        RunPredictionServer runServer = new RunPredictionServer();
        //read config file
        runServer.loadConfigFile();
        Model tempModel = new Model();
        tempModel.loadTrainingData(runServer.DataFile);
        tempModel.addPredictor("ZEROR");
        tempModel.addPredictor("PART");
        tempModel.addPredictor("ONER");
        tempModel.addPredictor("JRIP");
        tempModel.addPredictor("IBK");
        tempModel.addPredictor("NBM");
        tempModel.addPredictor("RF");
        tempModel.addPredictor("LWL");
        tempModel.addPredictor("NBC");
        tempModel.addPredictor("BN");
        tempModel.addPredictor("REPTREE");
        tempModel.addPredictor("DT");
        tempModel.addPredictor("J48");
        tempModel.addPredictor("SMO");
        tempModel.addPredictor("MP");
        tempModel.addPredictor("SL");
        tempModel.addPredictor("LOG");
        tempModel.addPredictor("SGD");
        tempModel.addPredictor("VP");
        tempModel.addPredictor("SVM");
        tempModel.addPredictor("KSTAR");

        Instances tempInstances=tempModel.getTrainingInstances();

        Iterator ite=runServer.filterList.iterator();

        while (ite.hasNext())
        {
            ArrayList filterOption=(ArrayList) ite.next();
            Iterator tempIte = filterOption.iterator();
            String tFilter=null;
            if (tempIte.hasNext())
            {
                tFilter=(String) tempIte.next();
            }
            String[] option = new String[filterOption.size()-1];
            int i=0;
            while (tempIte.hasNext())
            {
                option[i]=(String) tempIte.next();
                i++;
            }
            tempInstances = runServer.addFilter(tempInstances,tFilter,option);
        }

        //tempInstances.setClassIndex(tempInstances.numAttributes()-2);
        tempModel.setPreprocessedInstances(tempInstances);
        tempModel.savePreprocessedInstances("preprocessed.arff");

        try {
            tempModel.benchmark(2,resultFilename);

        }catch (Exception e)
        {
            runServer.logger.warn(e.toString());
        }

        tempModel.crossValidatePredictors(10);
        try {
            tempModel.saveResults(resultFilename);
        }catch (Exception e)
        {
            runServer.logger.warn(e.toString());
        }
    }

    //read config file
    private void loadConfigFile() {
        logger.debug("Reading configure from " + configFile);
        try {
            BufferedReader in = new BufferedReader(new FileReader(configFile));
            DataFile = in.readLine();
            System.out.println(DataFile);

            String tempStr=null;
            while((tempStr=in.readLine())!=null)
            {
                String[] tempString = tempStr.split(" ");
                ArrayList<String> filterOption = new ArrayList<>();
                for(String ts:tempString)
                {
                    filterOption.add(ts);
                }
                this.filterList.add(filterOption);
            }
        } catch (Exception e) {
            logger.warn(e.toString());
        }
    }

    private Instances addFilter(Instances tempInstances,String filter, String[] option)
    {
        Class<?> tempClass=null;
        try {
            tempClass = Class.forName(this.map.get(filter).toString());
        }catch (ClassNotFoundException e)
        {
            logger.warn(e.toString());
        }

        if(tempClass==null) return null;
        Object tempFilter=null;
        try {
            tempFilter = tempClass.newInstance();
        }catch (InstantiationException e)
        {
            logger.warn(e.toString());
        }
        catch (IllegalAccessException e)
        {
            logger.warn(e.toString());
        }

        try {
            ((OptionHandler)tempFilter).setOptions(option);
            ((Filter)tempFilter).setInputFormat(tempInstances);
        }catch (Exception e)
        {
            logger.warn(e.toString());
        }

        Instances newInstances=null;
        try {
            newInstances = Filter.useFilter(tempInstances, (Filter) (tempFilter));
        }catch (Exception e)
        {
            logger.warn(e.toString());
        }
        return newInstances;
    }

    private void setClassName()
    {
        map=new HashMap();
        map.put("addexpression","weka.filters.unsupervised.attribute.AddExpression");
        map.put("remove","weka.filters.unsupervised.attribute.Remove");
        map.put("classassigner","weka.filters.unsupervised.attribute.ClassAssigner");
        map.put("numerictonominal","weka.filters.unsupervised.attribute.NumericToNominal");
        map.put("mathexpression","weka.filters.unsupervised.attribute.MathExpression");
    }
}