Class TernaryTree
- Namespace
- iText.Layout.Hyphenation
- Assembly
- itext.layout.dll
Ternary Search Tree.
public class TernaryTree
- Inheritance
-
TernaryTree
- Derived
- Inherited Members
Remarks
Ternary Search Tree.
A ternary search tree is a hybrid 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 requirements 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. This work was authored by Carlos Villegas (cav@uniscope.co.jp).Fields
BLOCK_SIZE
allocation size for arrays
protected const int BLOCK_SIZE = 2048
Field Value
eq
Pointer to equal branch and to data when this node is a string terminator.
protected char[] eq
Field Value
- char[]
freenode
free node
protected char freenode
Field Value
hi
Pointer to high branch.
protected char[] hi
Field Value
- char[]
kv
This vector holds the trailing of the keys when the branch is compressed.
protected CharVector kv
Field Value
length
number of items in tree
protected int length
Field Value
lo
Pointer to low branch and to rest of the key when it is stored directly in this node, we don't have unions in java!
protected char[] lo
Field Value
- char[]
root
root
protected char root
Field Value
sc
The character stored in this node: splitchar.
protected char[] sc
Field Value
- char[]
Remarks
The character stored in this node: splitchar. Two special values are reserved:
- 0x0000 as string terminator
- 0xFFFF to indicate that the branch starting at this node is compressed
Methods
Balance()
Balance the tree for best search performance
public virtual void Balance()
Find(char[], int)
Find key.
public virtual int Find(char[] key, int start)
Parameters
Returns
- int
result
Find(string)
Find key.
public virtual int Find(string key)
Parameters
key
stringthe key
Returns
- int
result
Init()
initialize
protected virtual void Init()
Insert(char[], int, char)
Insert key.
public virtual void Insert(char[] key, int start, char val)
Parameters
Insert(string, char)
Branches are initially compressed, needing one node per key plus the size of the string key.
public virtual void Insert(string key, char val)
Parameters
Remarks
Branches are initially compressed, needing one node per key plus the size of the string key. They are decompressed as needed when another key with same prefix is inserted. This saves a lot of space, specially for long keys.
InsertBalanced(string[], char[], int, int)
Recursively insert the median first and then the median of the lower and upper halves, and so on in order to get a balanced tree.
protected virtual void InsertBalanced(string[] k, char[] v, int offset, int n)
Parameters
Remarks
Recursively insert the median first and then the median of the lower and upper halves, and so on in order to get a balanced tree. The array of keys is assumed to be sorted in ascending order.
Keys()
public virtual IEnumerator Keys()
Returns
- IEnumerator
the keys
Knows(string)
public virtual bool Knows(string key)
Parameters
key
stringa key
Returns
- bool
trye if key present
Size()
public virtual int Size()
Returns
- int
length
Strcmp(char[], int, char[], int)
Compares 2 null terminated char arrays
public static int Strcmp(char[] a, int startA, char[] b, int startB)
Parameters
a
char[]a character array
startA
intan index into character array
b
char[]a character array
startB
intan index into character array
Returns
- int
an integer
Strcmp(string, char[], int)
Compares a string with null terminated char array
public static int Strcmp(string str, char[] a, int start)
Parameters
Returns
- int
an integer
Strcpy(char[], int, char[], int)
public static void Strcpy(char[] dst, int di, char[] src, int si)
Parameters
dst
char[]a character array
di
intan index into character array
src
char[]a character array
si
intan index into character array
Strlen(char[])
public static int Strlen(char[] a)
Parameters
a
char[]a character array
Returns
- int
an integer
Strlen(char[], int)
public static int Strlen(char[] a, int start)
Parameters
Returns
- int
an integer
TrimToSize()
Each node stores a character (splitchar) which is part of some key(s).
public virtual void TrimToSize()
Remarks
Each node stores a character (splitchar) which is part of some key(s). In a compressed branch (one that only contain a single string key) the trailer of the key which is not already in nodes is stored externally in the kv array. As items are inserted, key substrings decrease. Some substrings may completely disappear when the whole branch is totally decompressed. The tree is traversed to find the key substrings actually used. In addition, duplicate substrings are removed using a map (implemented with a TernaryTree!).