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/*
 *   This program is free software: you can redistribute it and/or modify
 *   it under the terms of the GNU General Public License as published by
 *   the Free Software Foundation, either version 3 of the License, or
 *   (at your option) any later version.
 *
 *   This program is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with this program.  If not, see .
 */

/*
 * Created on 15/01/2005
 *
 */
package weka.classifiers.immune.airs;

import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import weka.classifiers.immune.airs.algorithm.Utils;
import weka.core.Instances;

import java.io.FileReader;
import java.util.Random;

/**
 * Type: AIRSAlgorithmTester

 * File: AIRSAlgorithmTester.java

 * Date: 15/01/2005

 * 

 * Description:
 * 

 *
 * @author Jason Brownlee
 */
public abstract class AIRSAlgorithmTester {

  private final static int CROSSVALIDATION = 10;

  private final static int NUM_TESTS = 10;

  public static final String[] filenames = {
    "data/iris.arff",
    "data/diabetes.arff",
    "data/sonar.arff",
    "data/balance-scale.arff",
    "data/breast-w.arff",
    "data/heart-c.arff",
    "data/ionosphere.arff",
  };

  public void run()
    throws Exception {
    for (int i = 0; i < filenames.length; i++) {
      Instances dataset = new Instances(new FileReader(filenames[i]));
      dataset.setClassIndex(dataset.numAttributes() - 1);

      double[] results = new double[NUM_TESTS];
      for (int j = 0; j < NUM_TESTS; j++) {
	// prepare the algorithm
	Classifier algorithm = getAIRSAlgorithm();
	long seed = j + 1;
	setSeed(algorithm, seed);
	// evaulate
	Evaluation evaluation = new Evaluation(dataset);
	long start = System.currentTimeMillis();
	evaluation.crossValidateModel(algorithm, dataset, CROSSVALIDATION, new Random(seed));
	long end = System.currentTimeMillis();
	results[j] = evaluation.pctCorrect();

	double time = ((end - start) / 1000.0);
	System.out.println((j + 1) + " - Correct(" + Utils.format.format(results[j]) + "%), Time(" + Utils.format.format(time) + "sec).");
      }

      // mean
      double mean = mean(results);
      // standard deviation
      double stdev = stdev(results, mean);
      // print details
      StringBuffer buffer = new StringBuffer();
      buffer.append(filenames[i] + ": ");
      buffer.append("Accuracy - " + Utils.format.format(mean) + "% (" + Utils.format.format(stdev) + ")");
      System.out.println(buffer.toString());
    }
  }

  protected double mean(double[] results) {
    double mean = 0.0;
    double sum = 0.0;
    for (int i = 0; i < results.length; i++) {
      sum += results[i];
    }
    mean = (sum / results.length);
    return mean;
  }

  protected double stdev(double[] results, double mean) {
    // standard deviation -
    // square root of the average squared deviation from the mean
    double stdev = 0.0;
    double sum = 0.0;
    for (int i = 0; i < results.length; i++) {
      double diff = mean - results[i];
      sum += diff * diff;
    }
    stdev = Math.sqrt(sum / results.length);
    return stdev;
  }


  protected abstract void setSeed(Classifier aClassifier, long aSeed);

  protected abstract Classifier getAIRSAlgorithm();
}