hyphenationtree.java

iText是一个能够快速产生PDF文件的java类库。iText的java类对于那些要产生包含文本

/*
 * Copyright 1999-2004 The Apache Software Foundation.
 * 
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 * 
 *      http://www.apache.org/licenses/LICENSE-2.0
 * 
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

/* $Id: HyphenationTree.java 2623 2007-02-23 22:28:28Z xlv $ */
 
package com.lowagie.text.pdf.hyphenation;

import java.io.InputStream;
import java.util.ArrayList;
import java.util.HashMap;

/**
 * This tree structure stores the hyphenation patterns in an efficient
 * way for fast lookup. It provides the provides the method to
 * hyphenate a word.
 *
 * @author Carlos Villegas <[e-mail]>
 */
public class HyphenationTree extends TernaryTree 
            implements PatternConsumer {

    private static final long serialVersionUID = -7763254239309429432L;

	/**
     * value space: stores the inteletter values
     */
    protected ByteVector vspace;

    /**
     * This map stores hyphenation exceptions
     */
    protected HashMap stoplist;

    /**
     * This map stores the character classes
     */
    protected TernaryTree classmap;

    /**
     * Temporary map to store interletter values on pattern loading.
     */
    private transient TernaryTree ivalues;

    public HyphenationTree() {
        stoplist = new HashMap(23);    // usually a small table
        classmap = new TernaryTree();
        vspace = new ByteVector();
        vspace.alloc(1);    // this reserves index 0, which we don't use
    }

    /**
     * Packs the values by storing them in 4 bits, two values into a byte
     * Values range is from 0 to 9. We use zero as terminator,
     * so we'll add 1 to the value.
     * @param values a string of digits from '0' to '9' representing the
     * interletter values.
     * @return the index into the vspace array where the packed values
     * are stored.
     */
    protected int packValues(String values) {
        int i, n = values.length();
        int m = (n & 1) == 1 ? (n >> 1) + 2 : (n >> 1) + 1;
        int offset = vspace.alloc(m);
        byte[] va = vspace.getArray();
        for (i = 0; i < n; i++) {
            int j = i >> 1;
            byte v = (byte)((values.charAt(i) - '0' + 1) & 0x0f);
            if ((i & 1) == 1) {
                va[j + offset] = (byte)(va[j + offset] | v);
            } else {
                va[j + offset] = (byte)(v << 4);    // big endian
            }
        }
        va[m - 1 + offset] = 0;    // terminator
        return offset;
    }

    protected String unpackValues(int k) {
        StringBuffer buf = new StringBuffer();
        byte v = vspace.get(k++);
        while (v != 0) {
            char c = (char)((v >>> 4) - 1 + '0');
            buf.append(c);
            c = (char)(v & 0x0f);
            if (c == 0) {
                break;
            }
            c = (char)(c - 1 + '0');
            buf.append(c);
            v = vspace.get(k++);
        }
        return buf.toString();
    }

    public void loadSimplePatterns(InputStream stream) {
        SimplePatternParser pp = new SimplePatternParser();
        ivalues = new TernaryTree();

        pp.parse(stream, this);

        // patterns/values should be now in the tree
        // let's optimize a bit
        trimToSize();
        vspace.trimToSize();
        classmap.trimToSize();

        // get rid of the auxiliary map
        ivalues = null;
    }


    public String findPattern(String pat) {
        int k = super.find(pat);
        if (k >= 0) {
            return unpackValues(k);
        }
        return "";
    }

    /**
     * String compare, returns 0 if equal or
     * t is a substring of s
     */
    protected int hstrcmp(char[] s, int si, char[] t, int ti) {
        for (; s[si] == t[ti]; si++, ti++) {
            if (s[si] == 0) {
                return 0;
            }
        }
        if (t[ti] == 0) {
            return 0;
        }
        return s[si] - t[ti];
    }

    protected byte[] getValues(int k) {
        StringBuffer buf = new StringBuffer();
        byte v = vspace.get(k++);
        while (v != 0) {
            char c = (char)((v >>> 4) - 1);
            buf.append(c);
            c = (char)(v & 0x0f);
            if (c == 0) {
                break;
            }
            c = (char)(c - 1);
            buf.append(c);
            v = vspace.get(k++);
        }
        byte[] res = new byte[buf.length()];
        for (int i = 0; i < res.length; i++) {
            res[i] = (byte)buf.charAt(i);
        }
        return res;
    }

    /**
     * <p>Search for all possible partial matches of word starting
     * at index an update interletter values. In other words, it
     * does something like:</p>
     * <code>
     * for(i=0; i<patterns.length; i++) {
     * if ( word.substring(index).startsWidth(patterns[i]) )
     * update_interletter_values(patterns[i]);
     * }
     * </code>
     * <p>But it is done in an efficient way since the patterns are
     * stored in a ternary tree. In fact, this is the whole purpose
     * of having the tree: doing this search without having to test
     * every single pattern. The number of patterns for languages
     * such as English range from 4000 to 10000. Thus, doing thousands
     * of string comparisons for each word to hyphenate would be
     * really slow without the tree. The tradeoff is memory, but
     * using a ternary tree instead of a trie, almost halves the
     * the memory used by Lout or TeX. It's also faster than using
     * a hash table</p>
     * @param word null terminated word to match
     * @param index start index from word
     * @param il interletter values array to update
     */
    protected void searchPatterns(char[] word, int index, byte[] il) {
        byte[] values;
        int i = index;
        char p, q;
        char sp = word[i];
        p = root;

        while (p > 0 && p < sc.length) {
            if (sc[p] == 0xFFFF) {
                if (hstrcmp(word, i, kv.getArray(), lo[p]) == 0) {
                    values = getValues(eq[p]);    // data pointer is in eq[]
                    int j = index;
                    for (int k = 0; k < values.length; k++) {
                        if (j < il.length && values[k] > il[j]) {
                            il[j] = values[k];
                        }
                        j++;
                    }
                }
                return;
            }
            int d = sp - sc[p];
            if (d == 0) {
                if (sp == 0) {
                    break;
                }
                sp = word[++i];
                p = eq[p];
                q = p;

                // look for a pattern ending at this position by searching for
                // the null char ( splitchar == 0 )
                while (q > 0 && q < sc.length) {
                    if (sc[q] == 0xFFFF) {        // stop at compressed branch
                        break;