void gk_find_frequent_itemsets(int ntrans, int *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;
mat->rowptr = gk_zmalloc(ntrans+1, "gk_find_frequent_itemsets: mat.rowptr");
for (i=0; i<ntrans+1; i++)
mat->rowptr[i] = tranptr[i];
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(¶ms, mat, -1);
gk_csr_Free(&mat);
pattern = gk_imalloc(pmat->ncols, "gk_find_frequent_itemsets: pattern");
itemsets_find_frequent_itemsets(¶ms, pmat, 0, pattern);
gk_csr_Free(&pmat);
gk_free((void **)&pattern, ¶ms.rmarker, ¶ms.cand, LTERM);
}
int main(int argc, char** argv)
{
int rank, p;
int n;
int nb;
int prow;
char ** a;
float *b;
float * pb;
gk_csr_t *mat;
int * nEachData;
int ndata;
int i, j;
if (argc != 3)
{
printf("error: invalid arguments\n");
exit(-1);
}
mat = (gk_csr_t *) malloc(sizeof(gk_csr_t));
n = numberOfLines(argv[1]);
nb = numberOfLines(argv[2]);
mat->nrows = nb;
mat->ncols = nb;
a = getDataA(argv[1], n);
b = getDataB(argv[2], nb);
mat->rowptr = (int *) calloc(nb + 1, sizeof(int));
mat->rowval = (float *) malloc(sizeof(float) * n);
mat->rowind = (int *) malloc(sizeof(int) * n);
if (parseInput(a, mat, n, nb) == -1)
{
printf("ERROR: Failed to parse data.\n");
exit(-1);
}
gk_csr_CreateIndex(mat, GK_CSR_COL);
float * result = (float *) calloc(nb, sizeof(float));
for (i = 0; i < nb; i++)
{
float output = 0.0;
int total = mat->colptr[i+1] - mat->colptr[i];
int * startind = mat->colind + mat->colptr[i];
float * startval = mat->colval + mat->colptr[i];
for (j = 0; j < total; j++)
{
result[startind[j]] += b[i] * startval[j];
// printf("%f : val %f\n", b[startind[j]] ,startval[j]);
}
}
/*
float * result = (float *) malloc(sizeof(float) * nb);
for (i = 0; i < nb; i++)
{
float output = 0.0;
int total = mat->rowptr[i+1] - mat->rowptr[i];
int * startind = mat->rowind + mat->rowptr[i];
float * startval = mat->rowval + mat->rowptr[i];
for (j = 0; j < total; j++)
{
output += b[startind[j]] * startval[j];
printf("%f : val %f\n", b[startind[j]] ,startval[j]);
}
result[i] = output;
}
*/
for (i = 0; i < nb; i++)
{
printf("%f\n", result[i]);
}
/*
for (i = 0; i < nb; i++)
{
int total = mat->rowptr[i+1] - mat->rowptr[i];
int * startind = mat->rowind + mat->rowptr[i];
float * startval = mat->rowval + mat->rowptr[i];
for (j = 0; j < total; j++)
{
printf("row %d col %d : val %f\n",i, startind[j] ,startval[j]);
}
}
printf("cols\n\n");
for (i = 0; i < nb; i++)
{
int total = mat->colptr[i+1] - mat->colptr[i];
int * startind = mat->colind + mat->colptr[i];
float * startval = mat->colval + mat->colptr[i];
for (j = 0; j < total; j++)
{
printf("col %d row %d : val %f\n",i, startind[j] ,startval[j]);
}
}
*/
return 0;
}
void ComputeNeighbors(params_t *params)
{
int i, j, nhits;
gk_csr_t *mat;
int32_t *marker;
gk_fkv_t *hits, *cand;
FILE *fpout;
printf("Reading data for %s...\n", params->infstem);
mat = gk_csr_Read(params->infstem, GK_CSR_FMT_CSR, 1, 0);
printf("#docs: %d, #nnz: %d.\n", mat->nrows, mat->rowptr[mat->nrows]);
/* compact the column-space of the matrices */
gk_csr_CompactColumns(mat);
/* perform auxiliary normalizations/pre-computations based on similarity */
gk_csr_Normalize(mat, GK_CSR_ROW, 2);
/* create the inverted index */
gk_csr_CreateIndex(mat, GK_CSR_COL);
/* create the output file */
fpout = (params->outfile ? gk_fopen(params->outfile, "w", "ComputeNeighbors: fpout") : NULL);
/* allocate memory for the necessary working arrays */
hits = gk_fkvmalloc(mat->nrows, "ComputeNeighbors: hits");
marker = gk_i32smalloc(mat->nrows, -1, "ComputeNeighbors: marker");
cand = gk_fkvmalloc(mat->nrows, "ComputeNeighbors: cand");
/* find the best neighbors for each query document */
gk_startwctimer(params->timer_1);
for (i=0; i<mat->nrows; i++) {
if (params->verbosity > 0)
printf("Working on query %7d\n", i);
/* find the neighbors of the ith document */
nhits = gk_csr_GetSimilarRows(mat,
mat->rowptr[i+1]-mat->rowptr[i],
mat->rowind+mat->rowptr[i],
mat->rowval+mat->rowptr[i],
GK_CSR_COS, params->nnbrs, params->minsim, hits,
marker, cand);
/* write the results in the file */
if (fpout) {
for (j=0; j<nhits; j++)
fprintf(fpout, "%8d %8d %.3f\n", i, hits[j].val, hits[j].key);
}
}
gk_stopwctimer(params->timer_1);
/* cleanup and exit */
if (fpout) gk_fclose(fpout);
gk_free((void **)&hits, &marker, &cand, LTERM);
gk_csr_Free(&mat);
return;
}
