コード例 #1
0
ファイル: Utility.java プロジェクト: pichitpr/Trimmed_SPMF
 public static SequenceDatabase load(List<List<Integer>>[] aryListDB) {
   SequenceDatabase db = new SequenceDatabase();
   Sequence seq;
   for (int i = 0; i < aryListDB.length; i++) {
     if (aryListDB[i] != null) {
       seq = new Sequence(i);
       for (List<Integer> itemset : aryListDB[i]) {
         seq.addItemset(itemset);
       }
       db.addSequence(seq);
     }
   }
   return db;
 }
コード例 #2
0
ファイル: Utility.java プロジェクト: pichitpr/Trimmed_SPMF
 public static SequenceDatabase load(String strDB) {
   SequenceDatabase db = new SequenceDatabase();
   Sequence seq;
   List<Integer> iset;
   String[] sequences = strDB.split("\\n");
   String[] itemsets;
   String[] items;
   for (String seqStr : sequences) {
     itemsets = seqStr.trim().split("\\s*\\|\\s*");
     seq = new Sequence(Integer.valueOf(itemsets[0]));
     for (int i = 1; i < itemsets.length; i++) {
       items = itemsets[i].split("\\s+");
       iset = new ArrayList<Integer>();
       for (String itemStr : items) {
         iset.add(Integer.valueOf(itemStr));
       }
       seq.addItemset(iset);
     }
     db.addSequence(seq);
   }
   return db;
 }
コード例 #3
0
  /**
   * This method generates statistics for a sequence database (a file)
   *
   * @param path the path to the file
   * @throws IOException exception if there is a problem while reading the file.
   */
  public void getStats(String path) throws IOException {

    /////////////////////////////////////
    //  (1) First we will read the sequence database into memory.
    // (actually, we don't really need to read it into memory because it
    //  just require a single pass, but the code is more simple like that
    //  - it could be optimized, if necessary).
    ///////////////////////////////////

    List<Sequence> sequences =
        new ArrayList<Sequence>(); //  A sequence database is stored as a list of sequences
    int maxItem = 0; // the largest id for items in the database

    String thisLine; // a temporary variable to read each line from the file

    BufferedReader myInput = null;
    try {
      // we read the file line by line
      FileInputStream fin = new FileInputStream(new File(path));
      myInput = new BufferedReader(new InputStreamReader(fin));
      int i = 0; // used to count the lines.

      // for each line until the end of the file
      while ((thisLine = myInput.readLine()) != null) {
        // we split the line according to spaces into tokens
        String tokens[] = thisLine.split(" ");
        // we create a new sequence object to store the sequence that correspond to this line.
        Sequence sequence = new Sequence(i++);
        // we create a list of integer to store the current itemset from the sequence
        // that correspond to this line.
        List<Integer> itemset = new ArrayList<Integer>();
        // For each token
        for (String token : tokens) {
          // if the token starts with "<" it means that it is a timestamp
          if (token.codePointAt(0) == '<') {
            // we just ignore it for statistics..
          }
          // if the token is "-1" it means that it is the end of an itemset
          else if (token.equals("-1")) {
            // we add the itemset to the sequence
            sequence.addItemset(itemset);
            // we reset the variable itemset to read the next itemset
            itemset = new ArrayList<Integer>();
          }
          // if the token is "-2", it indicates the end of this sequence and the
          // end of the line
          else if (token.equals("-2")) {
            // we add the sequence to the list of sequences
            sequences.add(sequence);
          }
          // otherwise, it means that the token is an item
          else {
            // we convert to an integer
            Integer item = Integer.parseInt(token);
            // we check if it has the largest value because we
            // want to keep this information
            if (item >= maxItem) {
              maxItem = item;
            }
            // we add the item to the current itemset.
            itemset.add(item);
          }
        }
      }
    } catch (Exception e) {
      e.printStackTrace();
    } finally {
      if (myInput != null) {
        myInput.close();
      }
    }

    /////////////////////////////////////
    //  We finished reading the database into memory.
    //  We will calculate statistics on this sequence database.
    ///////////////////////////////////

    System.out.println("============  SEQUENCE DATABASE STATS ==========");
    System.out.println("Number of sequences : " + sequences.size());

    // we initialize some variables that we will use to generate the statistics
    java.util.Set<Integer> items = new java.util.HashSet<Integer>(); // the set of all items
    List<Integer> sizes = new ArrayList<Integer>(); // the lengths of each sequence
    List<Integer> itemsetsizes = new ArrayList<Integer>(); // the lengths of each itemset
    List<Integer> differentitems =
        new ArrayList<Integer>(); // the number of different item for each sequence
    List<Integer> appearXtimesbySequence =
        new ArrayList<
            Integer>(); // the average number of times that items appearing in a sequence, appears
                        // in this sequence.
    // Loop on sequences from the database
    for (Sequence sequence : sequences) {
      // we add the size of this sequence to the list of sizes
      sizes.add(sequence.size());

      // this map is used to calculate the number of times that each item
      // appear in this sequence.
      // the key is an item
      // the value is the number of occurences of the item until now for this sequence
      HashMap<Integer, Integer> mapIntegers = new HashMap<Integer, Integer>();

      // Loop on itemsets from this sequence
      for (List<Integer> itemset : sequence.getItemsets()) {
        // we add the size of this itemset to the list of itemset sizes
        itemsetsizes.add(itemset.size());
        // Loop on items from this itemset
        for (Integer item : itemset) {
          // If the item is not in the map already, we set count to 0
          Integer count = mapIntegers.get(item);
          if (count == null) {
            count = 0;
          }
          // otherwise we set the count to count +1
          count = count + 1;
          mapIntegers.put(item, count);
          // finally, we add the item to the set of items
          items.add(item);
        }
      }
      // we add all items found in this sequence to the global list
      // of different items for the database
      differentitems.add(mapIntegers.entrySet().size());

      // for each item appearing in this sequence,
      // we put  the number of times in a global list "appearXtimesbySequence"
      // previously described.
      for (Entry<Integer, Integer> entry : mapIntegers.entrySet()) {
        appearXtimesbySequence.add(entry.getValue());
      }
    }

    // we print the statistics
    System.out.println("File " + path);
    System.out.println("Number of distinct items: " + items.size());
    System.out.println("Largest item id: " + maxItem);
    System.out.println(
        "Average number of itemsets per sequence : "
            + calculateMean(sizes)
            + " standard deviation: "
            + calculateStdDeviation(sizes)
            + " variance: "
            + calculateVariance(sizes));
    System.out.println(
        "Average number of distinct item per sequence : "
            + calculateMean(differentitems)
            + " standard deviation: "
            + calculateStdDeviation(differentitems)
            + " variance: "
            + calculateVariance(differentitems));
    System.out.println(
        "Average number of occurences in a sequence for each item appearing in a sequence : "
            + calculateMean(appearXtimesbySequence)
            + " standard deviation: "
            + calculateStdDeviation(appearXtimesbySequence)
            + " variance: "
            + calculateVariance(appearXtimesbySequence));
    System.out.println(
        "Average number of items per itemset : "
            + calculateMean(itemsetsizes)
            + " standard deviation: "
            + calculateStdDeviation(itemsetsizes)
            + " variance: "
            + calculateVariance(itemsetsizes));
  }