Namespace iTextSharp.text.pdf.hyphenation
Classes
- ByteVector
This class implements a simple byte vector with access to the underlying array. @author Carlos Villegas
- CharVector
This class implements a simple char vector with access to the underlying array. @author Carlos Villegas
- Hyphen
This class represents a hyphen. A 'full' hyphen is made of 3 parts: the pre-break text, post-break text and no-break. If no line-break is generated at this position, the no-break text is used, otherwise, pre-break and post-break are used. Typically, pre-break is equal to the hyphen character and the others are empty. However, this general scheme allows support for cases in some languages where words change spelling if they're split across lines, like german's 'backen' which hyphenates 'bak-ken'. BTW, this comes from TeX. @author Carlos Villegas
- Hyphenation
This class represents a hyphenated word. @author Carlos Villegas
- HyphenationException
@author Carlos Villegas
- HyphenationTree
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
- Hyphenator
This class is the main entry point to the hyphenation package. You can use only the static methods or create an instance. @author Carlos Villegas
- SimplePatternParser
Parses the xml hyphenation pattern. @author Paulo Soares (psoares@consiste.pt)
- TernaryTree
Ternary Search Tree
A ternary search tree is a hibrid between a binary tree and a digital search tree (trie). Keys are limited to strings. A data value of type char is stored in each leaf node. It can be used as an index (or pointer) to the data. Branches that only contain one key are compressed to one node by storing a pointer to the trailer substring of the key. This class is intended to serve as base class or helper class to implement Dictionary collections or the like. Ternary trees have some nice properties as the following: the tree can be traversed in sorted order, partial matches (wildcard) can be implemented, retrieval of all keys within a given distance from the target, etc. The storage requirements are higher than a binary tree but a lot less than a trie. Performance is comparable with a hash table, sometimes it outperforms a hash function (most of the time can determine a miss faster than a hash). The main purpose of this java port is to serve as a base for implementing TeX's hyphenation algorithm (see The TeXBook, appendix H). Each language requires from 5000 to 15000 hyphenation patterns which will be keys in this tree. The strings patterns are usually small (from 2 to 5 characters), but each char in the tree is stored in a node. Thus memory usage is the main concern. We will sacrify 'elegance' to keep memory requirenments to the minimum. Using java's char type as pointer (yes, I know pointer it is a forbidden word in java) we can keep the size of the node to be just 8 bytes (3 pointers and the data char). This gives room for about 65000 nodes. In my tests the english patterns took 7694 nodes and the german patterns 10055 nodes, so I think we are safe. All said, this is a map with strings as keys and char as value. Pretty limited!. It can be extended to a general map by using the string representation of an object and using the char value as an index to an array that contains the object values. @author cav@uniscope.co.jp
Interfaces
- IPatternConsumer
This interface is used to connect the XML pattern file parser to the hyphenation tree. @author Carlos Villegas