Cloned library GKlib with extra build files for internal package management.
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/*!
* \file
* \brief Frequent/Closed itemset discovery routines
*
* This file contains the code for finding frequent/closed itemests. These routines
* are implemented using a call-back mechanism to deal with the discovered itemsets.
*
* \date 6/13/2008
* \author George Karypis
* \version\verbatim $Id: itemsets.c 19240 2015-10-22 12:41:19Z karypis $ \endverbatim
*/
#include <GKlib.h>
/*-------------------------------------------------------------*/
/*! Data structures for use within this module */
/*-------------------------------------------------------------*/
typedef struct {
int minfreq; /* the minimum frequency of a pattern */
int maxfreq; /* the maximum frequency of a pattern */
int minlen; /* the minimum length of the requested pattern */
int maxlen; /* the maximum length of the requested pattern */
int tnitems; /* the initial range of the item space */
/* the call-back function */
void (*callback)(void *stateptr, int nitems, int *itemids, int ntrans, int *transids);
void *stateptr; /* the user-supplied pointer to pass to the callback */
/* workspace variables */
int *rmarker;
gk_ikv_t *cand;
} isparams_t;
/*-------------------------------------------------------------*/
/*! Prototypes for this module */
/*-------------------------------------------------------------*/
void itemsets_find_frequent_itemsets(isparams_t *params, gk_csr_t *mat,
int preflen, int *prefix);
gk_csr_t *itemsets_project_matrix(isparams_t *param, gk_csr_t *mat, int cid);
/*************************************************************************/
/*! The entry point of the frequent itemset discovery code */
/*************************************************************************/
void gk_find_frequent_itemsets(int ntrans, ssize_t *tranptr, int *tranind,
int minfreq, int maxfreq, int minlen, int maxlen,
void (*process_itemset)(void *stateptr, int nitems, int *itemids,
int ntrans, int *transids),
void *stateptr)
{
ssize_t i;
gk_csr_t *mat, *pmat;
isparams_t params;
int *pattern;
/* Create the matrix */
mat = gk_csr_Create();
mat->nrows = ntrans;
mat->ncols = tranind[gk_iargmax(tranptr[ntrans], tranind, 1)]+1;
mat->rowptr = gk_zcopy(ntrans+1, tranptr, gk_zmalloc(ntrans+1, "gk_find_frequent_itemsets: mat.rowptr"));
mat->rowind = gk_icopy(tranptr[ntrans], tranind, gk_imalloc(tranptr[ntrans], "gk_find_frequent_itemsets: mat.rowind"));
mat->colids = gk_iincset(mat->ncols, 0, gk_imalloc(mat->ncols, "gk_find_frequent_itemsets: mat.colids"));
/* Setup the parameters */
params.minfreq = minfreq;
params.maxfreq = (maxfreq == -1 ? mat->nrows : maxfreq);
params.minlen = minlen;
params.maxlen = (maxlen == -1 ? mat->ncols : maxlen);
params.tnitems = mat->ncols;
params.callback = process_itemset;
params.stateptr = stateptr;
params.rmarker = gk_ismalloc(mat->nrows, 0, "gk_find_frequent_itemsets: rmarker");
params.cand = gk_ikvmalloc(mat->ncols, "gk_find_frequent_itemsets: cand");
/* Perform the initial projection */
gk_csr_CreateIndex(mat, GK_CSR_COL);
pmat = itemsets_project_matrix(&params, mat, -1);
gk_csr_Free(&mat);
pattern = gk_imalloc(pmat->ncols, "gk_find_frequent_itemsets: pattern");
itemsets_find_frequent_itemsets(&params, pmat, 0, pattern);
gk_csr_Free(&pmat);
gk_free((void **)&pattern, &params.rmarker, &params.cand, LTERM);
}
/*************************************************************************/
/*! The recursive routine for DFS-based frequent pattern discovery */
/*************************************************************************/
void itemsets_find_frequent_itemsets(isparams_t *params, gk_csr_t *mat,
int preflen, int *prefix)
{
ssize_t i;
gk_csr_t *cmat;
/* Project each frequent column */
for (i=0; i<mat->ncols; i++) {
prefix[preflen] = mat->colids[i];
if (preflen+1 >= params->minlen)
(*params->callback)(params->stateptr, preflen+1, prefix,
mat->colptr[i+1]-mat->colptr[i], mat->colind+mat->colptr[i]);
if (preflen+1 < params->maxlen) {
cmat = itemsets_project_matrix(params, mat, i);
itemsets_find_frequent_itemsets(params, cmat, preflen+1, prefix);
gk_csr_Free(&cmat);
}
}
}
/******************************************************************************/
/*! This function projects a matrix w.r.t. to a particular column.
It performs the following steps:
- Determines the length of each column that is remaining.
- Sorts the columns in increasing length.
- Creates a column-based version of the matrix with the proper
column ordering.
*/
/*******************************************************************************/
gk_csr_t *itemsets_project_matrix(isparams_t *params, gk_csr_t *mat, int cid)
{
ssize_t i, j, k, ii, pnnz;
int nrows, ncols, pnrows, pncols;
ssize_t *colptr, *pcolptr;
int *colind, *colids, *pcolind, *pcolids, *rmarker;
gk_csr_t *pmat;
gk_ikv_t *cand;
nrows = mat->nrows;
ncols = mat->ncols;
colptr = mat->colptr;
colind = mat->colind;
colids = mat->colids;
rmarker = params->rmarker;
cand = params->cand;
/* Allocate space for the projected matrix based on what you know thus far */
pmat = gk_csr_Create();
pmat->nrows = pnrows = (cid == -1 ? nrows : colptr[cid+1]-colptr[cid]);
/* Mark the rows that will be kept and determine the prowids */
if (cid == -1) { /* Initial projection */
gk_iset(nrows, 1, rmarker);
}
else { /* The other projections */
for (i=colptr[cid]; i<colptr[cid+1]; i++)
rmarker[colind[i]] = 1;
}
/* Determine the length of each column that will be left in the projected matrix */
for (pncols=0, pnnz=0, i=cid+1; i<ncols; i++) {
for (k=0, j=colptr[i]; j<colptr[i+1]; j++) {
k += rmarker[colind[j]];
}
if (k >= params->minfreq && k <= params->maxfreq) {
cand[pncols].val = i;
cand[pncols++].key = k;
pnnz += k;
}
}
/* Sort the columns in increasing order */
gk_ikvsorti(pncols, cand);
/* Allocate space for the remaining fields of the projected matrix */
pmat->ncols = pncols;
pmat->colids = pcolids = gk_imalloc(pncols, "itemsets_project_matrix: pcolids");
pmat->colptr = pcolptr = gk_zmalloc(pncols+1, "itemsets_project_matrix: pcolptr");
pmat->colind = pcolind = gk_imalloc(pnnz, "itemsets_project_matrix: pcolind");
/* Populate the projected matrix */
pcolptr[0] = 0;
for (pnnz=0, ii=0; ii<pncols; ii++) {
i = cand[ii].val;
for (j=colptr[i]; j<colptr[i+1]; j++) {
if (rmarker[colind[j]])
pcolind[pnnz++] = colind[j];
}
pcolids[ii] = colids[i];
pcolptr[ii+1] = pnnz;
}
/* Reset the rmarker array */
if (cid == -1) { /* Initial projection */
gk_iset(nrows, 0, rmarker);
}
else { /* The other projections */
for (i=colptr[cid]; i<colptr[cid+1]; i++)
rmarker[colind[i]] = 0;
}
return pmat;
}