/*
 * Jalview - A Sequence Alignment Editor and Viewer ($$Version-Rel$$)
 * Copyright (C) $$Year-Rel$$ The Jalview Authors
 * 
 * This file is part of Jalview.
 * 
 * Jalview 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.
 *  
 * Jalview 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 Jalview.  If not, see <http://www.gnu.org/licenses/>.
 * The Jalview Authors are detailed in the 'AUTHORS' file.
 */
package jalview.analysis.scoremodels;

import jalview.api.analysis.ScoreModelI;
import jalview.api.analysis.ViewBasedAnalysisI;
import jalview.datamodel.AlignmentView;
import jalview.datamodel.SeqCigar;
import jalview.datamodel.SequenceFeature;
import jalview.util.SetUtils;

import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;

public class FeatureScoreModel implements ScoreModelI, ViewBasedAnalysisI
{
  jalview.api.FeatureRenderer fr;

  @Override
  public boolean configureFromAlignmentView(
          jalview.api.AlignmentViewPanel view)
  {
    fr = view.cloneFeatureRenderer();
    return true;
  }

  /**
   * Calculates a distance measure [i][j] between each pair of sequences as the
   * average number of features they have but do not share. That is, find the
   * features each sequence pair has at each column, ignore feature types they
   * have in common, and count the rest. The totals are normalised by the number
   * of columns processed.
   */
  @Override
  public float[][] findDistances(AlignmentView seqData)
  {
    List<String> dft = fr.getDisplayedFeatureTypes();
    SeqCigar[] seqs = seqData.getSequences();
    int noseqs = seqs.length;
    int cpwidth = 0;// = seqData.getWidth();
    float[][] distance = new float[noseqs][noseqs];
    if (dft.isEmpty())
    {
      return distance;
    }

    // need to get real position for view position
    int[] viscont = seqData.getVisibleContigs();

    /*
     * scan each column, compute and add to each distance[i, j]
     * the number of feature types that seqi and seqj do not share
     */
    for (int vc = 0; vc < viscont.length; vc += 2)
    {
      for (int cpos = viscont[vc]; cpos <= viscont[vc + 1]; cpos++)
      {
        cpwidth++;

        /*
         * first pass: record features types in column for each sequence
         */
        Map<SeqCigar, Set<String>> sfap = findFeatureTypesAtColumn(
                seqs, cpos);

        /*
         * count feature types on either i'th or j'th sequence but not both
         * and add this 'distance' measure to the total for [i, j] for j > i
         */
        for (int i = 0; i < (noseqs - 1); i++)
        {
          for (int j = i + 1; j < noseqs; j++)
          {
            int seqDistance = SetUtils.countDisjunction(sfap.get(seqs[i]),
                    sfap.get(seqs[j]));
            distance[i][j] += seqDistance;
          }
        }
      }
    }

    /*
     * normalise the distance scores (summed over columns) by the
     * number of visible columns used in the calculation
     */
    for (int i = 0; i < noseqs; i++)
    {
      for (int j = i + 1; j < noseqs; j++)
      {
        distance[i][j] /= cpwidth;
        distance[j][i] = distance[i][j];
      }
    }
    return distance;
  }

  /**
   * Builds and returns a list (one per SeqCigar) of visible feature types at
   * the given column position
   * 
   * @param seqs
   * @param columnPosition
   * @return
   */
  protected Map<SeqCigar, Set<String>> findFeatureTypesAtColumn(
          SeqCigar[] seqs, int columnPosition)
  {
    Map<SeqCigar, Set<String>> sfap = new HashMap<SeqCigar, Set<String>>();
    for (SeqCigar seq : seqs)
    {
      Set<String> types = new HashSet<String>();
      int spos = seq.findPosition(columnPosition);
      if (spos != -1)
      {
        List<SequenceFeature> sfs = fr.findFeaturesAtRes(seq.getRefSeq(),
                spos);
        for (SequenceFeature sf : sfs)
        {
          types.add(sf.getType());
        }
      }
      sfap.put(seq, types);
    }
    return sfap;
  }

  @Override
  public String getName()
  {
    return "Sequence Feature Similarity";
  }

  @Override
  public boolean isDNA()
  {
    return true;
  }

  @Override
  public boolean isProtein()
  {
    return true;
  }

  @Override
  public String toString()
  {
    return "Score between sequences based on hamming distance between binary vectors marking features displayed at each column";
  }
}