package ca.pfv.spmf.algorithms.sequentialpatterns.BIDE_and_prefixspan;
import java.io.BufferedWriter;
import java.io.FileWriter;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import ca.pfv.spmf.input.sequence_database_list_integers.Sequence;
import ca.pfv.spmf.input.sequence_database_list_integers.SequenceDatabase;
import ca.pfv.spmf.patterns.itemset_list_integers_without_support.Itemset;
import ca.pfv.spmf.tools.MemoryLogger;
/***
* This is an implementation of the PrefixSpan algorithm.
* PrefixSpan was proposed by Pei et al. 2001.
*
* NOTE: This implementation saves the pattern to a file as soon
* as they are found or can keep the pattern into memory, depending
* on what the user choose.
*
* Copyright (c) 2008-2012 Philippe Fournier-Viger
*
* 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 <http://www.gnu.org/licenses/>.
*/
public class AlgoPrefixSpan{
// for statistics
long startTime;
long endTime;
// the number of pattern found
int patternCount;
// absolute minimum support
private int minsuppAbsolute;
// writer to write output file
BufferedWriter writer = null;
// The sequential patterns that are found
// (if the user want to keep them into memory)
private SequentialPatterns patterns = null;
// maximum pattern length in terms of item count
private int maximumPatternLength = Integer.MAX_VALUE;
/** if true, sequence identifiers of each pattern will be shown*/
boolean showSequenceIdentifiers = false;
/**
* Default constructor
*/
public AlgoPrefixSpan(){
}
/**
* Run the algorithm
* @param database : a sequence database
* @param minsupRelative : the minimum support as a percentage (e.g. 50%) as a value in [0,1]
* @param outputFilePath : the path of the output file to save the result
* or null if you want the result to be saved into memory
* @return return the result, if saved into memory, otherwise null
* @throws IOException exception if error while writing the file
*/
public SequentialPatterns runAlgorithm(SequenceDatabase database, double minsupRelative, String outputFilePath) throws IOException {
// convert to a absolute minimum support
this.minsuppAbsolute = (int) Math.ceil(minsupRelative * database.size());
if(this.minsuppAbsolute == 0){ // protection
this.minsuppAbsolute = 1;
}
// record start time
startTime = System.currentTimeMillis();
// run the algorithm
prefixSpan(database, outputFilePath);
// record end time
endTime = System.currentTimeMillis();
// close the output file if the result was saved to a file
if(writer != null){
writer.close();
}
return patterns;
}
/**
* Run the algorithm
* @param database : a sequence database
* @param minsupPercent : the minimum support as an integer
* @param outputFilePath : the path of the output file to save the result
* or null if you want the result to be saved into memory
* @return return the result, if saved into memory, otherwise null
* @throws IOException exception if error while writing the file
*/
public SequentialPatterns runAlgorithm(SequenceDatabase database, String outputFilePath, int minsup) throws IOException {
// initialize variables for statistics
patternCount =0;
MemoryLogger.getInstance().reset();
// save the minsup chosen by the user
this.minsuppAbsolute = minsup;
// save the start time
startTime = System.currentTimeMillis();
// run the algorithm
prefixSpan(database, outputFilePath);
// save the end time
endTime = System.currentTimeMillis();
// close the output file if the result was saved to a file
if(writer != null){
writer.close();
}
return patterns;
}
/**
* This is the main method for the PrefixSpan algorithm that is called
* to start the algorithm
* @param outputFilePath an output file path if the result should be saved to a file
* or null if the result should be saved to memory.
* @param database a sequence database
* @throws IOException exception if an error while writing the output file
*/
private void prefixSpan(SequenceDatabase database, String outputFilePath) throws IOException{
// if the user want to keep the result into memory
if(outputFilePath == null){
writer = null;
patterns = new SequentialPatterns("FREQUENT SEQUENTIAL PATTERNS");
}else{ // if the user want to save the result to a file
patterns = null;
writer = new BufferedWriter(new FileWriter(outputFilePath));
}
// We have to scan the database to find all frequent sequential patterns of size 1.
// We note the sequences in which the items appear.
Map<Integer, Set<Integer>> mapSequenceID = findSequencesContainingItems(database);
// WE CONVERT THE DATABASE ITON A PSEUDO-DATABASE, AND REMOVE
// THE ITEMS OF SIZE 1 THAT ARE NOT FREQUENT, SO THAT THE ALGORITHM
// WILL NOT CONSIDER THEM ANYMORE.
// Create a list of pseudosequence
List<PseudoSequence> initialDatabase = new ArrayList<PseudoSequence>();
// for each sequence in the database
for(Sequence sequence : database.getSequences()){
// remove infrequent items
Sequence optimizedSequence = sequence.cloneSequenceMinusItems(mapSequenceID, minsuppAbsolute);
if(optimizedSequence.size() != 0){
// if the size is > 0, create a pseudo sequence with this sequence
initialDatabase.add(new PseudoSequence(optimizedSequence, 0, 0));
}
}
// For each item
for(Entry<Integer, Set<Integer>> entry : mapSequenceID.entrySet()){
// if the item is frequent (has a support >= minsup)
if(entry.getValue().size() >= minsuppAbsolute){
Integer item = entry.getKey();
// Create the prefix for this projected database
SequentialPattern prefix = new SequentialPattern();
prefix.addItemset(new Itemset(item));
prefix.setSequenceIDs(entry.getValue());
// The prefix is a frequent sequential pattern.
// We save it in the result.
savePattern(prefix);
// build the projected database for that item
List<PseudoSequence> projectedContext
= buildProjectedDatabaseForSingleItem(item, initialDatabase, entry.getValue());
// We make a recursive call to try to find larger sequential
// patterns starting with this prefix
if(maximumPatternLength >1){
recursion(prefix, projectedContext, 2);
}
}
}
}
/**
* This method saves a sequential pattern to the output file or
* in memory, depending on if the user provided an output file path or not
* when he launched the algorithm
* @param prefix the pattern to be saved.
* @throws IOException exception if error while writing the output file.
*/
private void savePattern(SequentialPattern prefix) throws IOException {
// increase the number of pattern found for statistics purposes
patternCount++;
// if the result should be saved to a file
if(writer != null){
// create a StringBuilder
StringBuilder r = new StringBuilder("");
// for each itemset in this sequential pattern
for(Itemset itemset : prefix.getItemsets()){
// for each item
for(Integer item : itemset.getItems()){
r.append(item.toString()); // add the item
r.append(' ');
}
r.append("-1 "); // add the itemset separator
}
// add the support
r.append("#SUP: ");
r.append(prefix.getAbsoluteSupport());
if(showSequenceIdentifiers) {
r.append(" #SID: ");
for (Integer sid: prefix.getSequenceIDs()) {
r.append(sid);
r.append(" ");
}
}
// write the string to the file
writer.write(r.toString());
// start a new line
writer.newLine();
}
// otherwise the result is kept into memory
else{
patterns.addSequence(prefix, prefix.size());
}
}
/**
* For each item, calculate the sequence id of sequences containing that item
* @param database the current sequence database
* @return Map of items to sequence IDs that contains each item
*/
private Map<Integer, Set<Integer>> findSequencesContainingItems(SequenceDatabase database) {
// We use a map to store the sequence IDs where an item appear
// Key : item Value : a set of sequence IDs
Map<Integer, Set<Integer>> mapSequenceID = new HashMap<Integer, Set<Integer>>();
// for each sequence in the current database
for(Sequence sequence : database.getSequences()){
// for each itemset in this sequence
for(List<Integer> itemset : sequence.getItemsets()){
// for each item
for(Integer item : itemset){
// get the set of sequence IDs for this item until now
Set<Integer> sequenceIDs = mapSequenceID.get(item);
if(sequenceIDs == null){
// if the set does not exist, create one
sequenceIDs = new HashSet<Integer>();
mapSequenceID.put(item, sequenceIDs);
}
// add the sequence ID of the current sequence to the
// set of sequences IDs of this item
sequenceIDs.add(sequence.getId());
}
}
}
return mapSequenceID;
}
/**
* Create a projected database by pseudo-projection with the initial database and a given item.
* @param item The item to use to make the pseudo-projection
* @param initialDatabase The current database.
* @param sidSet The set of sequence ids containing the item
* @return the projected database.
*/
private List<PseudoSequence> buildProjectedDatabaseForSingleItem(Integer item, List<PseudoSequence> initialDatabase,Set<Integer> sidSet) {
// We create a new projected database
List<PseudoSequence> sequenceDatabase = new ArrayList<PseudoSequence>();
// for each sequence in the database received as parameter
loopSeq:for(PseudoSequence sequence : initialDatabase){
// if this sequence do not contain the current prefix, then skip it.
if(!sidSet.contains(sequence.getId())){
continue;
}
// for each itemset of the sequence
for(int i = 0; i< sequence.size(); i++){
// check if the itemset contains the item that is used for the projection
int index = sequence.indexOfBis(i, item);
// if it does not, and the current item is part of a suffix if inSuffix is true
// and vice-versa
if(index == -1 ){
continue;
}
// if the item is the last item of this itemset
if(index == sequence.getSizeOfItemsetAt(i)-1){
// if it is not the last itemset
if ((i != sequence.size()-1)){
// create new pseudo sequence
// add it to the projected database.
sequenceDatabase.add(new PseudoSequence( sequence, i+1, 0));
}
}else{
// create a new pseudo sequence and
// add it to the projected database.
sequenceDatabase.add(new PseudoSequence(sequence, i, index+1));
}
}
}
//
// for(PseudoSequence seq : sequenceDatabase){
// System.out.println(seq);
// System.out.println("original seq: " + seq.sequence);
// }
//
return sequenceDatabase; // return the projected database
}
/**
* Create a projected database by pseudo-projection
* @param item The item to use to make the pseudo-projection
* @param database The current sequence database.
* @param inPostFix This boolean indicates if the item "item" is part of a suffix or not.
* @param sidset the set of sequence IDs of sequence containing this item
* @return the projected database.
*/
private List<PseudoSequence> buildProjectedDatabase(Integer item, List<PseudoSequence> database, Set<Integer> sidset, boolean inPostFix) {
// We create a new projected database
List<PseudoSequence> sequenceDatabase = new ArrayList<PseudoSequence>();
// for each sequence in the database received as parameter
for(PseudoSequence sequence : database){
if(sidset.contains(sequence.getId()) == false){
continue;
}
// for each itemset of the sequence
for(int i = 0; i< sequence.size(); i++){
if (sequence.isPostfix(i) != inPostFix){
// if the item is not in a postfix, but this itemset
// is a postfix, then we can continue scanning from the next itemset
continue;
}
// check if the itemset contains the item that we use for the projection
int index = sequence.indexOfBis(i, item);
// if it does not, move to next itemset
if(index == -1 ){
continue;
}
// if the item is the last item of this itemset
if(index == sequence.getSizeOfItemsetAt(i)-1){
// if it is not the last itemset
if ((i != sequence.size()-1)){
// create new pseudo sequence
// add it to the projected database.
sequenceDatabase.add(new PseudoSequence( sequence, i+1, 0));
//System.out.println(sequence.getId() + "--> "+ newSequence.toString());
// break itemsetLoop;
}
}else{
// create a new pseudo sequence and
// add it to the projected database.
sequenceDatabase.add(new PseudoSequence(sequence, i, index+1));
//System.out.println(sequence.getId() + "--> "+ newSequence.toString());
// break itemsetLoop;
}
}
}
return sequenceDatabase; // return the projected database
}
/**
* Method to recursively grow a given sequential pattern.
* @param prefix the current sequential pattern that we want to try to grow
* @param database the current projected sequence database
* @param k the prefix length in terms of items
* @throws IOException exception if there is an error writing to the output file
*/
private void recursion(SequentialPattern prefix, List<PseudoSequence> database, int k) throws IOException {
// find frequent items of size 1 in the current projected database.
Set<Pair> pairs = findAllFrequentPairs(database);
// For each pair found (a pair is an item with a boolean indicating if it
// appears in an itemset that is cut (a postfix) or not, and the sequence IDs
// where it appears in the projected database).
for(Pair pair : pairs){
// if the item is frequent in the current projected database
if(pair.getCount() >= minsuppAbsolute){
// create the new postfix by appending this item to the prefix
SequentialPattern newPrefix;
// if the item is part of a postfix
if(pair.isPostfix()){
// we append it to the last itemset of the prefix
newPrefix = appendItemToPrefixOfSequence(prefix, pair.getItem());
}else{ // else, we append it as a new itemset to the sequence
newPrefix = appendItemToSequence(prefix, pair.getItem());
}
newPrefix.setSequenceIDs(pair.getSequenceIDs());
// build the projected database with this item
List<PseudoSequence> projectedDatabase = buildProjectedDatabase(pair.getItem(), database, pair.getSequenceIDs(), pair.isPostfix());
// save the pattern
savePattern(newPrefix);
// make a recursive call
if( k < maximumPatternLength){
recursion(newPrefix, projectedDatabase, k+1);
}
}
}
// check the current memory usage
MemoryLogger.getInstance().checkMemory();
}
/**
* Method to find all frequent items in a projected sequence database
* @param sequences the set of sequences
* @return A list of pairs, where a pair is an item with (1) a boolean indicating if it
* is in an itemset that is "cut" and (2) the sequence IDs where it occurs.
*/
protected Set<Pair> findAllFrequentPairs(List<PseudoSequence> sequences){
// We use a Map the store the pairs.
Map<Pair, Pair> mapPairs = new HashMap<Pair, Pair>();
// for each sequence
for(PseudoSequence sequence : sequences){
// for each itemset
for(int i=0; i< sequence.size(); i++){
// for each item
for(int j=0; j < sequence.getSizeOfItemsetAt(i); j++){
Integer item = sequence.getItemAtInItemsetAt(j, i);
// create the pair corresponding to this item
Pair pair = new Pair(sequence.isPostfix(i), item);
// get the pair object store in the map if there is one already
Pair oldPair = mapPairs.get(pair);
// if there is no pair object yet
if(oldPair == null){
// store the pair object that we created
mapPairs.put(pair, pair);
}else{
// otherwise use the old one
pair = oldPair;
}
// record the current sequence id for that pair
pair.getSequenceIDs().add(sequence.getId());
}
}
}
MemoryLogger.getInstance().checkMemory(); // check the memory for statistics.
// return the map of pairs
return mapPairs.keySet();
}
/**
* This method creates a copy of the sequence and add a given item
* as a new itemset to the sequence.
* It sets the support of the sequence as the support of the item.
* @param prefix the sequence
* @param item the item
* @return the new sequence
*/
private SequentialPattern appendItemToSequence(SequentialPattern prefix, Integer item) {
SequentialPattern newPrefix = prefix.cloneSequence(); // isSuffix
newPrefix.addItemset(new Itemset(item)); // cr�� un nouvel itemset + decalage
return newPrefix;
}
/**
* This method creates a copy of the sequence and add a given item
* to the last itemset of the sequence.
* It sets the support of the sequence as the support of the item.
* @param prefix the sequence
* @param item the item
* @return the new sequence
*/
private SequentialPattern appendItemToPrefixOfSequence(SequentialPattern prefix, Integer item) {
SequentialPattern newPrefix = prefix.cloneSequence();
Itemset itemset = newPrefix.get(newPrefix.size()-1); // ajoute au dernier itemset
itemset.addItem(item);
return newPrefix;
}
/**
* Print statistics about the algorithm execution to System.out.
* @param size the size of the database
*/
public void printStatistics(int size) {
StringBuilder r = new StringBuilder(200);
r.append("============= PREFIXSPAN - STATISTICS =============\n Total time ~ ");
r.append(endTime - startTime);
r.append(" ms\n");
r.append(" Frequent sequences count : " + patternCount);
r.append('\n');
r.append(" Max memory (mb) : " );
r.append(MemoryLogger.getInstance().getMaxMemory());
r.append(patternCount);
r.append('\n');
r.append("===================================================\n");
// if the result was save into memory, print it
if(patterns !=null){
patterns.printFrequentPatterns(size, showSequenceIdentifiers);
}
System.out.println(r.toString());
}
/**
* Get the maximum length of patterns to be found (in terms of item count)
* @return the maximumPatternLength
*/
public int getMaximumPatternLength() {
return maximumPatternLength;
}
/**
* Set the maximum length of patterns to be found (in terms of item count)
* @param maximumPatternLength the maximumPatternLength to set
*/
public void setMaximumPatternLength(int maximumPatternLength) {
this.maximumPatternLength = maximumPatternLength;
}
/**
* Set that the sequence identifiers should be shown (true) or not (false) for each
* pattern found
* @param showSequenceIdentifiers true or false
*/
public void setShowSequenceIdentifiers(boolean showSequenceIdentifiers) {
this.showSequenceIdentifiers = showSequenceIdentifiers;
}
}