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C/C++ Users Group Library 1996 July
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C-C++ Users Group Library July 1996.iso
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vol_400
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425_01
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lzpipe
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trees.c
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1994-03-13
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/*
The following sorce code is derived from Info-Zip 'zip' 2.01
distribution copyrighted by Mark Adler, Richard B. Wales,
Jean-loup Gailly, Kai Uwe Rommel, Igor Mandrichenko and John Bush.
*/
/*
* trees.c by Jean-loup Gailly
*
* This is a new version of im_ctree.c originally written by Richard B. Wales
* for the defunct implosion method.
*
* PURPOSE
*
* Encode various sets of source values using variable-length
* binary code trees.
*
* DISCUSSION
*
* The PKZIP "deflation" process uses several Huffman trees. The more
* common source values are represented by shorter bit sequences.
*
* Each code tree is stored in the ZIP file in a compressed form
* which is itself a Huffman encoding of the lengths of
* all the code strings (in ascending order by source values).
* The actual code strings are reconstructed from the lengths in
* the UNZIP process, as described in the "application note"
* (APPNOTE.TXT) distributed as part of PKWARE's PKZIP program.
*
* REFERENCES
*
* Lynch, Thomas J.
* Data Compression: Techniques and Applications, pp. 53-55.
* Lifetime Learning Publications, 1985. ISBN 0-534-03418-7.
*
* Storer, James A.
* Data Compression: Methods and Theory, pp. 49-50.
* Computer Science Press, 1988. ISBN 0-7167-8156-5.
*
* Sedgewick, R.
* Algorithms, p290.
* Addison-Wesley, 1983. ISBN 0-201-06672-6.
*
* INTERFACE
*
* int ct_init (void)
* Allocate the match buffer and initialize the various tables.
*
* int ct_tally(int dist, int lc);
* Save the match info and tally the frequency counts.
* Return true if the current block must be flushed.
*
* long flush_block (char *buf, ulg stored_len, int eof)
* Determine the best encoding for the current block: dynamic trees,
* static trees or store, and output the encoded block to the zip
* file. Returns the total compressed length for the file so far.
*/
#include "modern.h"
#include "zalloc.h"
#include "zipdefs.h"
#include "zipguts.h"
#include "lzpipe.h"
#define MAX_BITS 15
/* All codes must not exceed MAX_BITS bits */
#define MAX_BL_BITS 7
/* Bit length codes must not exceed MAX_BL_BITS bits */
#define LENGTH_CODES 29
/* number of length codes, not counting the special END_BLOCK code */
#define LITERALS 256
/* number of literal bytes 0..255 */
#define END_BLOCK 256
/* end of block literal code */
#define L_CODES (LITERALS+1+LENGTH_CODES)
/* number of Literal or Length codes, including the END_BLOCK code */
#define D_CODES 30
/* number of distance codes */
#define BL_CODES 19
/* number of codes used to transfer the bit lengths */
static int near extra_lbits[LENGTH_CODES] /* extra bits for each length code */
= {0,0,0,0,0,0,0,0,1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,0};
static int near extra_dbits[D_CODES] /* extra bits for each distance code */
= {0,0,0,0,1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,11,11,12,12,13,13};
static int near extra_blbits[BL_CODES]/* extra bits for each bit length code */
= {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,3,7};
#define STORED_BLOCK 0
#define STATIC_TREES 1
#define DYN_TREES 2
/* The three kinds of block type */
#ifndef LIT_BUFSIZE
# ifdef SMALL_MEM
# define LIT_BUFSIZE 0x2000
# else
# ifdef MEDIUM_MEM
# define LIT_BUFSIZE 0x4000
# else
# define LIT_BUFSIZE 0x8000
# endif
# endif
#endif
#define DIST_BUFSIZE LIT_BUFSIZE
/* Sizes of match buffers for literals/lengths and distances. There are
* 4 reasons for limiting LIT_BUFSIZE to 64K:
* - frequencies can be kept in 16 bit counters
* - if compression is not successful for the first block, all input data is
* still in the window so we can still emit a stored block even when input
* comes from standard input. (This can also be done for all blocks if
* LIT_BUFSIZE is not greater than 32K.)
* - if compression is not successful for a file smaller than 64K, we can
* even emit a stored file instead of a stored block (saving 5 bytes).
* - creating new Huffman trees less frequently may not provide fast
* adaptation to changes in the input data statistics. (Take for
* example a binary file with poorly compressible code followed by
* a highly compressible string table.) Smaller buffer sizes give
* fast adaptation but have of course the overhead of transmitting trees
* more frequently.
* - I can't count above 4
* The current code is general and allows DIST_BUFSIZE < LIT_BUFSIZE (to save
* memory at the expense of compression). Some optimizations would be possible
* if we rely on DIST_BUFSIZE == LIT_BUFSIZE.
*/
#define REP_3_6 16
/* repeat previous bit length 3-6 times (2 bits of repeat count) */
#define REPZ_3_10 17
/* repeat a zero length 3-10 times (3 bits of repeat count) */
#define REPZ_11_138 18
/* repeat a zero length 11-138 times (7 bits of repeat count) */
/* Data structure describing a single value and its code string. */
typedef struct ct_data {
union {
ush freq; /* frequency count */
ush code; /* bit string */
} fc;
union {
ush dad; /* father node in Huffman tree */
ush len; /* length of bit string */
} dl;
} ct_data;
#define Freq fc.freq
#define Code fc.code
#define Dad dl.dad
#define Len dl.len
#define HEAP_SIZE (2*L_CODES+1)
/* maximum heap size */
static ct_data near dyn_ltree[HEAP_SIZE]; /* literal and length tree */
static ct_data near dyn_dtree[2*D_CODES+1]; /* distance tree */
static ct_data near static_ltree[L_CODES+2];
/* The static literal tree. Since the bit lengths are imposed, there is no
* need for the L_CODES extra codes used during heap construction. However
* The codes 286 and 287 are needed to build a canonical tree (see ct_init
* below).
*/
static ct_data near static_dtree[D_CODES];
/* The static distance tree. (Actually a trivial tree since all codes use
* 5 bits.)
*/
static ct_data near bl_tree[2*BL_CODES+1];
/* Huffman tree for the bit lengths */
typedef struct tree_desc {
ct_data near *dyn_tree; /* the dynamic tree */
ct_data near *static_tree; /* corresponding static tree or NULL */
int near *extra_bits; /* extra bits for each code or NULL */
int extra_base; /* base index for extra_bits */
int elems; /* max number of elements in the tree */
int max_length; /* max bit length for the codes */
int max_code; /* largest code with non zero frequency */
} tree_desc;
static tree_desc near l_desc =
{dyn_ltree, static_ltree, extra_lbits, LITERALS+1, L_CODES, MAX_BITS, 0};
static tree_desc near d_desc =
{dyn_dtree, static_dtree, extra_dbits, 0, D_CODES, MAX_BITS, 0};
static tree_desc near bl_desc =
{bl_tree, (ct_data near *)0, extra_blbits, 0, BL_CODES, MAX_BL_BITS, 0};
static ush near bl_count[MAX_BITS+1];
/* number of codes at each bit length for an optimal tree */
static uch near bl_order[BL_CODES]
= {16,17,18,0,8,7,9,6,10,5,11,4,12,3,13,2,14,1,15};
/* The lengths of the bit length codes are sent in order of decreasing
* probability, to avoid transmitting the lengths for unused bit length codes.
*/
static int near heap[2*L_CODES+1]; /* heap used to build the Huffman trees */
static int heap_len; /* number of elements in the heap */
static int heap_max; /* element of largest frequency */
/* The sons of heap[n] are heap[2*n] and heap[2*n+1]. heap[0] is not used.
* The same heap array is used to build all trees.
*/
static uch near depth[2*L_CODES+1];
/* Depth of each subtree used as tie breaker for trees of equal frequency */
static uch length_code[MAX_MATCH-MIN_MATCH+1];
/* length code for each normalized match length (0 == MIN_MATCH) */
static uch dist_code[512];
/* dis