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package utils;

import biodiscml.BestModelSelectionAndReport;

import java.io.BufferedReader;

import java.io.FileReader;

import java.io.FileWriter;

import java.io.PrintWriter;

import java.util.ArrayList;

import java.util.HashMap;

/**

 *

 * @author mickael

 */

public class UpSetR {

    public void creatUpSetRDataset(String featureSelectionFile, String predictionsResultsFile) {

        System.out.println("# create UpSetR file");

        String outfile = predictionsResultsFile.replace(".csv", ".UpSetR.csv");

        //create header

        ArrayList<String> featuresHeader = new ArrayList<>();

        try {

            BufferedReader br = new BufferedReader(new FileReader(featureSelectionFile.replace(".csv", ".arff")));

            String line = br.readLine(); //relation

            br.readLine(); //empty line

            line = br.readLine(); // @attribute

            while (line.startsWith("@attribute")) {

                featuresHeader.add(line.replace("@attribute ", "").replaceAll(" \\w+$", ""));

                line = br.readLine();

            }

        } catch (Exception e) {

            e.printStackTrace();

        }

        featuresHeader.remove(featuresHeader.size() - 1);

        featuresHeader.remove(0);

        //output

        try {

            BufferedReader br = new BufferedReader(new FileReader(predictionsResultsFile));

            PrintWriter pw = new PrintWriter(new FileWriter(outfile));

            pw.println("ID,"

                    + "TRAIN_10CV_MCC"

                    + ",TRAIN_LOOCV_MCC"

                    + ",TRAIN_BS_MCC"

                    + ",TEST_MCC"

                    + ",TRAIN_TEST_BS_MCC"

                    + ",AVG_MCC,"

                    + featuresHeader.toString().replace("[", "").replace("]", "").trim() + "");

            pw.flush();

            String line = br.readLine();

            while (br.ready()) {

                line = br.readLine();

                BestModelSelectionAndReport.classificationObject co = new BestModelSelectionAndReport.classificationObject(line);

                //get ID

                ArrayList<String> featureList = co.featureList;

                featureList.remove(featureList.size() - 1);

                featureList.remove(0);

                int[] tab = new int[featuresHeader.size()];

                try {

                    for (String index : featureList) {

                        tab[Integer.valueOf(index) - 2] = 1;

                    }

                } catch (Exception e) {

                    e.printStackTrace();

                }

                String features = "";

                for (int i : tab) {

                    features += "," + i;

                }

                String out = "" + co.identifier + ""

                        + "," + co.hmValues.get("TRAIN_10CV_MCC")

                        + "," + co.hmValues.get("TRAIN_LOOCV_MCC")

                        + "," + co.hmValues.get("TRAIN_BS_MCC")

                        + "," + co.hmValues.get("TEST_MCC")

                        + "," + co.hmValues.get("TRAIN_TEST_BS_MCC")

                        + "," + co.hmValues.get("AVG_MCC") + features + "";

                pw.println(out);

            }

            pw.close();

        } catch (Exception e) {

            e.printStackTrace();

        }

        System.out.println("UpSetR file: " + outfile);

    }

    public void creatUpSetRDatasetFromSignature(BestModelSelectionAndReport.classificationObject co_model,

            String featureSelectionFile, String predictionsResultsFile) {

        System.out.println("# create UpSetR file");

        String outfile = predictionsResultsFile.replace(".csv", ".UpSetR.csv");

        //create header

        ArrayList<String> alFeaturesOrder = new ArrayList<>();

        try {

            BufferedReader br = new BufferedReader(new FileReader(featureSelectionFile.replace(".csv", ".arff")));

            String line = br.readLine(); //relation

            br.readLine(); //empty line

            line = br.readLine(); // @attribute            

            while (line.startsWith("@attribute")) {

                alFeaturesOrder.add(line.replace("@attribute ", "").replaceAll(" \\w+$", ""));

                line = br.readLine();

            }

        } catch (Exception e) {

            e.printStackTrace();

        }

        alFeaturesOrder.remove(alFeaturesOrder.size() - 1);

        //retreive signature

        String featuresHeader = "";

        for (int i = 1; i < co_model.featureList.size() - 1; i++) {

            featuresHeader += "," + alFeaturesOrder.get(Integer.valueOf(co_model.featureList.get(i)) - 1);

        }

        //output

        try {

            //header

            BufferedReader br = new BufferedReader(new FileReader(predictionsResultsFile));

            PrintWriter pw = new PrintWriter(new FileWriter(outfile));

            pw.println("ID,"

                    + "TRAIN_10CV_MCC"

                    + ",TRAIN_LOOCV_MCC"

                    + ",TRAIN_BS_MCC"

                    + ",TEST_MCC"

                    + ",TRAIN_TEST_BS_MCC"

                    + ",AVG_MCC"

                    + featuresHeader);

            pw.flush();

            String line = br.readLine();

            //content

            while (br.ready()) {

                line = br.readLine();

                BestModelSelectionAndReport.classificationObject co_line = new BestModelSelectionAndReport.classificationObject(line);

                ArrayList<String> featureList = co_line.featureList;

                if (co_line.identifier.equals("trees.RandomForest_AUC_FB_19_0.9571_877")){

                    System.out.println("");

                }

                HashMap<String, String> hmFeaturesLine = new HashMap<>();

                for (int i = 1; i < co_line.featureList.size() - 1; i++) {

                    hmFeaturesLine.put(co_line.featureList.get(i),"");

                }

                String presence = "";

                for (int i = 1; i < co_model.featureList.size() - 1; i++) {                   

                    if (hmFeaturesLine.containsKey(co_model.featureList.get(i) + "")) {

                        presence += ",1";

                    } else {

                        presence += ",0";

                    }

                }

                String out = "" + co_line.identifier + ""

                        + "," + co_line.hmValues.get("TRAIN_10CV_MCC")

                        + "," + co_line.hmValues.get("TRAIN_LOOCV_MCC")

                        + "," + co_line.hmValues.get("TRAIN_BS_MCC")

                        + "," + co_line.hmValues.get("TEST_MCC")

                        + "," + co_line.hmValues.get("TRAIN_TEST_BS_MCC")

                        + "," + co_line.hmValues.get("AVG_MCC") + presence + "";

                pw.println(out);

            }

            pw.close();

        } catch (Exception e) {

            e.printStackTrace();

        }

        System.out.println("UpSetR file: " + outfile);

    }

}