package ca.pfv.spmf.algorithms.sequentialpatterns.gsp_AGP.items;


import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;

import ca.pfv.spmf.algorithms.sequentialpatterns.gsp_AGP.items.creators.AbstractionCreator;
import ca.pfv.spmf.algorithms.sequentialpatterns.gsp_AGP.items.creators.ItemAbstractionPairCreator;
import ca.pfv.spmf.algorithms.sequentialpatterns.gsp_AGP.items.patterns.Pattern;
import ca.pfv.spmf.algorithms.sequentialpatterns.gsp_AGP.items.patterns.PatternCreator;

/**
 * Inspired in SPMF
 * Implementation of a sequence database, where each sequence is implemented
 * as an array of integers and should have a unique id.
 * See examples in /test/ directory for the format of input files.
 *
 * Copyright (c) 2013 Antonio Gomariz Peñalver
 * 
 * This file is part of the SPMF DATA MINING SOFTWARE
 * (http://www.philippe-fournier-viger.com/spmf).
 *
 * SPMF 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.
 *
 * SPMF 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 SPMF.  If not, see .
 * 
 * @author agomariz
 */
public class SequenceDatabase {
    
    private AbstractionCreator abstractionCreator;
    
    /**
     * Map to associate the frequent items with the 1-patterns composed by themselves
     */
    private Map frequentItems = new HashMap();
    
    /**
     * List of sequences that compose the database
     */
    private List sequences = new ArrayList();
    
    /**
     * Instance of ItemFactory
     */
    private ItemFactory itemFactory = new ItemFactory();
    
    /**
     * Instance of PatternCreator
     */
    private PatternCreator patternCreator = PatternCreator.getInstance();
    
    public SequenceDatabase(AbstractionCreator abstractionCreator) {
        this.abstractionCreator = abstractionCreator;
    }

    /**
     * It loads the database contained in the file path given as parameter.
     * Besides, all the frequent 1-patterns are identified and the original database
     * is updated by removing the non-frequent items
     * @param path File path of the original database
     * @param minSupportAbsolute Minimum absolute support
     * @throws IOException 
     */
    public void loadFile(String path, double minSupportAbsolute) throws IOException {
        String thisLine;
        BufferedReader myInput = null;
        try {
            FileInputStream fis = new FileInputStream(new File(path));
            myInput = new BufferedReader(new InputStreamReader(fis));
            while ((thisLine = myInput.readLine()) != null) {
                // si la linea no es un comentario
                if (thisLine.charAt(0) != '#') {
                    // añade una secuencia
                    addSequence(thisLine.split(" "));
                }
            }
            double minSupRelative = (int) Math.ceil(minSupportAbsolute * sequences.size());
           // double support = (int) (minSupport * sequences.size());
            Set items = frequentItems.keySet();
            Set itemsToRemove = new HashSet();
            for (Item item : items) {
                Pattern pattern = frequentItems.get(item);
                if (pattern.getSupport() < minSupRelative) {
                    itemsToRemove.add(item);
                }
            }
            for (Item nonFrequent : itemsToRemove) {
                frequentItems.remove(nonFrequent);
            }

            shrinkDatabase(frequentItems.keySet());
        } catch (Exception e) {
        } finally {
            if (myInput != null) {
                myInput.close();
            }
        }
    }
    
    /**
     * It creates and addes the sequence found in the array of Strings
     * @param integers 
     */
    public void addSequence(String[] integers) {
        ItemAbstractionPairCreator creadorPares = ItemAbstractionPairCreator.getInstance();
        long timestamp;
        Sequence sequence = new Sequence(sequences.size());
        Itemset itemset = new Itemset();
        int start = 0;

        for (int i = start; i < integers.length; i++) {
            if (integers[i].codePointAt(0) == '<') {  // Timestamp
                String value = integers[i].substring(1, integers[i].length() - 1);
                timestamp = Long.parseLong(value);
                itemset.setTimestamp(timestamp);
            } else if (integers[i].equals("-1")) { // indica el final de un itemset
                long time = itemset.getTimestamp() + 1;
                sequence.addItemset(itemset);
                itemset = new Itemset();
                itemset.setTimestamp(time);
            } else if (integers[i].equals("-2")) { // indica el final de la secuencia
                sequences.add(sequence);
            } else {
                // extract the value for an item
                Item item = itemFactory.getItem(Integer.parseInt(integers[i]));
                Pattern pattern = frequentItems.get(item);
                if (pattern == null) {
                    pattern = patternCreator.createPattern(creadorPares.getItemAbstractionPair(item, abstractionCreator.CreateDefaultAbstraction()));
                    frequentItems.put(item, pattern);
                }
                pattern.addAppearance(sequence.getId());
                itemset.addItem(item);

            }
        }
    }

    public void addSequence(Sequence sequence) {
        sequences.add(sequence);
    }

    @Override
    public String toString() {
        StringBuilder r = new StringBuilder();
        for (Sequence sequence : sequences) {
            r.append(sequence.getId());
            r.append(":  ");
            r.append(sequence.toString());
            r.append('\n');
        }
        return r.toString();
    }

    public int size() {
        return sequences.size();
    }

    public List getSequences() {
        return sequences;
    }

    /**
     * It returns the frequent 1-patterns
     * @return the list of frequent items.
     */
    public List frequentItems() {
        List celdasDeItemsFrecuentes = new ArrayList(frequentItems.values());
        Collections.sort(celdasDeItemsFrecuentes);
        return celdasDeItemsFrecuentes;
    }

    /**
     * It return a map where are associated each frequent item with the 
     * 1-pattern composed by itself
     * @return the map
     */
    public Map getFrequentItems() {
        return frequentItems;
    }

    public void clear() {
        if (sequences != null) {
            sequences.clear();
        }
        sequences = null;
        if (frequentItems != null) {
            frequentItems.clear();
        }
        frequentItems = null;
        itemFactory = null;
    }

    /**
     * Reduce the original database, removing the items given in the 
     * parameter set
     * @param keySet 
     */
    private void shrinkDatabase(Set keySet) {
        for (Sequence sequence : sequences) {
            for (int i = 0; i < sequence.size(); i++) {
                Itemset itemset = sequence.get(i);
                for (int j = 0; j < itemset.size(); j++) {
                    Item item = itemset.get(j);
                    if (!keySet.contains(item)) {
                        sequence.remove(i, j);
                        j--;
                    }
                }
                if (itemset.size() == 0) {
                    sequence.remove(i);
                    i--;
                }
            }
        }
    }
}