/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */

package org.apache.samoa.evaluation.measures;

import java.util.ArrayList;
import java.util.List;

import org.apache.samoa.instances.DenseInstance;
import org.apache.samoa.instances.Instance;
import org.apache.samoa.moa.cluster.Cluster;
import org.apache.samoa.moa.cluster.Clustering;
import org.apache.samoa.moa.cluster.SphereCluster;
import org.apache.samoa.moa.core.DataPoint;
import org.apache.samoa.moa.evaluation.MeasureCollection;

public class Separation extends MeasureCollection {

  public Separation() {
    super();
  }

  @Override
  protected String[] getNames() {
    return new String[] { "BSS", "BSS-GT", "BSS-Ratio" };
  }

  // @Override
  public void evaluateClusteringSamoa(Clustering clustering,
      Clustering trueClustering, ArrayList<Instance> points)
      throws Exception {

    double BSS_GT = 1.0;
    double BSS;
    int dimension = points.get(0).numAttributes() - 1;
    SphereCluster sc = new SphereCluster(points, dimension);

    // DO INTERNAL EVALUATION
    // clustering.getClustering().get(0).getCenter();

    BSS = getBSS(clustering, sc.getCenter());

    if (trueClustering != null) {
      List<Instance> listInstances = new ArrayList<>();
      for (Cluster c : trueClustering.getClustering()) {
        DenseInstance inst = new DenseInstance(c.getWeight(), c.getCenter());
        listInstances.add(inst);
      }
      SphereCluster gt = new SphereCluster(listInstances, dimension);
      BSS_GT = getBSS(trueClustering, gt.getCenter());
    }

    addValue("BSS", BSS);
    addValue("BSS-GT", BSS_GT);
    addValue("BSS-Ratio", BSS / BSS_GT);

  }

  private double getBSS(Clustering clustering, double[] mean) {
    double bss = 0.0;
    for (int i = 0; i < clustering.size(); i++) {
      double weight = clustering.get(i).getWeight();
      double sum = 0.0;
      for (int j = 0; j < mean.length; j++) {
        sum += Math.pow((mean[j] - clustering.get(i).getCenter()[j]), 2);
      }
      bss += weight * sum;
    }

    return bss;
  }

  @Override
  protected void evaluateClustering(Clustering clustering,
      Clustering trueClustering, ArrayList<DataPoint> points)
      throws Exception {
    double BSS_GT = 1.0;
    double BSS;
    int dimension = points.get(0).numAttributes() - 1;
    SphereCluster sc = new SphereCluster(points, dimension);

    // DO INTERNAL EVALUATION
    // clustering.getClustering().get(0).getCenter();

    BSS = getBSS(clustering, sc.getCenter());

    if (trueClustering != null) {
      String s = "";
      List<Instance> listInstances = new ArrayList<>();
      for (Cluster c : trueClustering.getClustering()) {
        DenseInstance inst = new DenseInstance(c.getWeight(), c.getCenter());
        listInstances.add(inst);
        s += " " + c.getWeight();
      }
      SphereCluster gt = new SphereCluster(listInstances, dimension);
      BSS_GT = getBSS(trueClustering, gt.getCenter());
    }

    addValue("BSS", BSS);
    addValue("BSS-GT", BSS_GT);
    addValue("BSS-Ratio", BSS / BSS_GT);
  }
}