package jalview.gui.structurechooser;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.BitSet;
import java.util.Collection;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;

import jalview.datamodel.SequenceI;
import jalview.fts.api.FTSData;
import jalview.fts.core.FTSRestRequest;

public class TDBResultAnalyser
{

  /**
   * model categories - update as needed. warnings output if unknown types
   * encountered.
   * 
   * Order denotes 'trust'
   */
  private static List<String> EXP_CATEGORIES = Arrays
          .asList(new String[]
          { "EXPERIMENTALLY DETERMINED", "DEEP-LEARNING",
              "TEMPLATE-BASED" });

  private SequenceI seq;

  private Collection<FTSData> collectedResults;

  private FTSRestRequest lastTdbRequest;

  private int idx_ups;

  private int idx_upe;

  private int idx_mcat;

  private int idx_mqual;

  private int idx_resol;

  public TDBResultAnalyser(SequenceI seq,
          Collection<FTSData> collectedResults,
          FTSRestRequest lastTdbRequest)
  {
    this.seq = seq;
    this.collectedResults = collectedResults;
    this.lastTdbRequest = lastTdbRequest;
    idx_ups = lastTdbRequest.getFieldIndex("Uniprot Start");
    idx_upe = lastTdbRequest.getFieldIndex("Uniprot End");
    idx_mcat = lastTdbRequest.getFieldIndex("Model Category");
    idx_mqual = lastTdbRequest.getFieldIndex("Confidence");
    idx_resol = lastTdbRequest.getFieldIndex("Resolution");
  }
  private final int scoreCategory(String cat)
  {
    // TODO: make quicker
    int idx = EXP_CATEGORIES.indexOf(cat.toUpperCase());
    if (idx == -1)
    {
      System.out.println("Unknown category: '" + cat + "'");
    }
    return -EXP_CATEGORIES.size() - idx;
  }

  /**
   * sorts records discovered by 3D beacons and excludes any that don't
   * intersect with the sequence's start/end rage
   * 
   * @return
   */
  public List<FTSData> getFilteredResponse()
  {
    List<FTSData> filteredResponse = new ArrayList<FTSData>();

    // ignore anything outside the sequence region
    for (FTSData row : collectedResults)
    {
      int up_s = (Integer) row.getSummaryData()[idx_ups];
      int up_e = (Integer) row.getSummaryData()[idx_upe];

      if (seq == row.getSummaryData()[0] && up_e > seq.getStart()
              && up_s < seq.getEnd())
      {
        filteredResponse.add(row);
      }
    }
    // sort according to decreasing length,
    // increasing start
    Collections.sort(filteredResponse, new Comparator<FTSData>()
    {


      @Override
      public int compare(FTSData o1, FTSData o2)
      {
        Object[] o1data = o1.getSummaryData();
        Object[] o2data = o2.getSummaryData();
        int o1_s = (Integer) o1data[idx_ups];
        int o1_e = (Integer) o1data[idx_upe];
        int o1_cat = scoreCategory((String) o1data[idx_mcat]);
        int o2_s = (Integer) o2data[idx_ups];
        int o2_e = (Integer) o2data[idx_upe];
        int o2_cat = scoreCategory((String) o2data[idx_mcat]);

        if (o1_cat == o2_cat)
        {
          if (o1_s == o2_s)
          {
            int o1_xtent = o1_e - o1_s;
            int o2_xtent = o2_e - o2_s;
            if (o1_xtent == o2_xtent)
            {
              if (o1_cat == scoreCategory(EXP_CATEGORIES.get(0)))
              {
                // experimental structures, so rank on quality
                double o1_res = (Double) o1data[idx_resol];
                double o2_res = (Double) o2data[idx_resol];
                return (o2_res < o1_res) ? 1 : (o2_res == o1_res) ? 0 : -1;
              }
              else
              {
                // models, so rank on qmean
                float o1_mq = (Float) o1data[idx_mqual];
                float o2_mq = (Float) o2data[idx_mqual];
                return (o2_mq < o1_mq) ? 1 : (o2_mq == o1_mq) ? 0 : -1;
              }
            }
            else
            {
              return o1_xtent - o2_xtent;
            }
          }
          else
          {
            return o1_s - o2_s;
          }
        }
        else
        {
          return o2_cat - o1_cat;
        }
      }

      @Override
      public boolean equals(Object obj)
      {
        return super.equals(obj);
      }
    });
    return filteredResponse;
  }

  /**
   * return list of structures to be marked as selected for this sequence according to given criteria
   * @param filteredStructures - sorted, filtered structures from getFilteredResponse
   * 
   */
  public List<FTSData> selectStructures(List<FTSData> filteredStructures)
  {
    List<FTSData> selected = new ArrayList<FTSData>();
    BitSet cover = new BitSet();
    cover.set(seq.getStart(),seq.getEnd());
    // walk down the list of structures, selecting some to add to selected
    for (FTSData structure:filteredStructures)
    {
      Object[] odata=structure.getSummaryData();
      int o1_s = (Integer) odata[idx_ups];
      int o1_e = (Integer) odata[idx_upe];
      int o1_cat = scoreCategory((String) odata[idx_mcat]);
      BitSet scover = new BitSet();
      // measure intersection
      scover.set(o1_s,o1_e);
      scover.and(cover);
      if (scover.cardinality()>4)
      {
        selected.add(structure);
        // clear the range covered by this structure
        cover.andNot(scover); 
      }
    }
    // final step is to sort on length - this might help the superposition process
    Collections.sort(selected,new Comparator<FTSData>()
    {
      @Override
      public int compare(FTSData o1, FTSData o2)
      {
        Object[] o1data = o1.getSummaryData();
        Object[] o2data = o2.getSummaryData();
        int o1_xt = ((Integer) o1data[idx_upe]) - ((Integer) o1data[idx_ups]);
        int o1_cat = scoreCategory((String) o1data[idx_mcat]);
        int o2_xt = ((Integer) o2data[idx_upe]-(Integer) o2data[idx_ups]);
        int o2_cat = scoreCategory((String) o2data[idx_mcat]);
        return o2_xt-o1_xt;
      }
    });
    return selected;
  }

}