static ALIGNZONE detect_for_char(SWFFONT * f, int nr, float*row, float*column, SRECT font_bbox, SRECT char_bbox)
{
ALIGNZONE a = {0xffff,0xffff,0xffff,0xffff};
int width = font_bbox.xmax - font_bbox.xmin;
int height = font_bbox.ymax - font_bbox.ymin;
if(!width || !height)
return a;
/* find two best x values */
int x1=-1,y1=-1,x2=-1,y2=-1;
int nr_x = 0;
find_best(row, width, &x1, &x2, f->use->smallest_size,
char_bbox.xmin - font_bbox.xmin,
char_bbox.xmax - font_bbox.xmin, nr_x,
0);
if(nr_x>0 && x1>=0) a.x = floatToF16((x1+font_bbox.xmin) / 20480.0);
if(nr_x>1 && x2>=0) a.dx = floatToF16((x2-x1) / 20480.0);
find_best(column, height, &y1, &y2, f->use->smallest_size,
char_bbox.ymin - font_bbox.ymin,
char_bbox.ymax - font_bbox.ymin, 2,
0);
if(y1>=0) a.y = floatToF16((y1+font_bbox.ymin) / 20480.0);
if(y2>=0) a.dy = floatToF16((y2-y1) / 20480.0);
return a;
}
/**
* \brief Configure the filter and call the next filter's config function.
*/
static int config(struct vf_instance *vf, int width, int height, int d_width, int d_height, unsigned int flags, unsigned int outfmt)
{
if(!(vf->priv->fmt=find_best(vf)))
return 0;
else
return vf_next_config(vf,width,height,d_width,d_height,flags,vf->priv->fmt);
}
static int query_format(struct vf_instance *vf, unsigned int fmt){
int best;
if(fmt!=IMGFMT_RGB1 && fmt!=IMGFMT_BGR1) return 0;
best=find_best(vf);
if(!best) return 0; // no match
return vf->next->query_format(vf->next,best);
}
void
APG::ConstraintSolver::run()
{
if ( !m_readyToRun ) {
error() << "DANGER WILL ROBINSON! A ConstraintSolver (serial no:" << m_serialNumber << ") tried to run before its QueryMaker finished!";
m_abortRequested = true;
return;
}
if ( m_domain.empty() ) {
debug() << "The QueryMaker returned no tracks";
return;
} else {
debug() << "Domain has" << m_domain.size() << "tracks";
}
debug() << "Running ConstraintSolver" << m_serialNumber;
emit totalSteps( m_maxGenerations );
// GENETIC ALGORITHM LOOP
Population population;
quint32 generation = 0;
Meta::TrackList* best = NULL;
while ( !m_abortRequested && ( generation < m_maxGenerations ) ) {
quint32 s = m_constraintTreeRoot->suggestPlaylistSize();
m_suggestedPlaylistSize = (s > 0) ? s : m_suggestedPlaylistSize;
fill_population( population );
best = find_best( population );
if ( population.value( best ) < m_satisfactionThreshold ) {
select_population( population, best );
mutate_population( population );
generation++;
emit incrementProgress();
} else {
break;
}
}
debug() << "solution at" << (void*)(best);
m_solvedPlaylist = best->mid( 0 );
m_finalSatisfaction = m_constraintTreeRoot->satisfaction( m_solvedPlaylist );
/* clean up */
Population::iterator it = population.begin();
while ( it != population.end() ) {
delete it.key();
it = population.erase( it );
}
emit endProgressOperation( this );
}
static int config(struct vf_instance *vf,
int width, int height, int d_width, int d_height,
unsigned int flags, unsigned int outfmt){
if (!vf->priv->fmt)
vf->priv->fmt=find_best(vf);
if(!vf->priv->fmt){
// no matching fmt, so force one...
if(outfmt==IMGFMT_RGB8) vf->priv->fmt=IMGFMT_RGB32;
else if(outfmt==IMGFMT_BGR8) vf->priv->fmt=IMGFMT_BGR32;
else return 0;
}
return vf_next_config(vf,width,height,d_width,d_height,flags,vf->priv->fmt);
}
/*----------------------------------------------------------------------
* main entry point
*----------------------------------------------------------------------*/
int main(int argc, char *argv[])
{
progname = argv[0];
read_board(); /* read the board file */
dict = Dict_open(NULL); /* open the dictionary */
play.dirn = ACROSS;
board = horiz_board;
value = horiz_value;
xboard = vert_board;
xvalue = vert_value;
find_best();
play.dirn = DOWN;
board = vert_board;
value = vert_value;
xboard = horiz_board;
xvalue = horiz_value;
find_best();
if (nb_count == 0) {
printf("Cannot play\n");
}else{
int i;
nb_sort();
for (i=0; i<nb_count; i++) {
NBTYPE *p = nb_sorted[i];
if (p->dirn==ACROSS) {
printf("[%d,%d]a", p->row, p->col);
}else{
printf("[%d,%d]d", p->col, p->row);
}
printf(" %s %d\n", p->word, p->score);
}
}
Dict_close(dict);
return 0;
}
static void find_best_inorder(struct file *a, struct file *b,
int alo, int ahi, int blo, int bhi,
struct best *best, int bestlo, int besthi)
{
/* make sure the best matches we find are inorder.
* If they aren't we find a overall best, and
* recurse either side of that
*/
int i;
int bad = 0;
int bestval, bestpos = 0;
for (i = bestlo; i < besthi; i++)
best[i].val = 0;
find_best(a, b, alo, ahi, blo, bhi, best);
for (i = bestlo + 1; i < besthi; i++)
if (best[i-1].val > 0 &&
best[i].val > 0 &&
best[i-1].xhi >= best[i].xlo)
bad = 1;
if (!bad)
return;
bestval = 0;
for (i = bestlo; i < besthi; i++)
if (best[i].val > bestval) {
bestval = best[i].val;
bestpos = i;
}
if (bestpos > bestlo) {
/* move top down below chunk marker */
int y = best[bestpos].ylo;
while (b->list[y].start[0])
y--;
find_best_inorder(a, b,
alo, best[bestpos].xlo,
blo, y,
best, bestlo, bestpos);
}
if (bestpos < besthi-1) {
/* move bottom up to chunk marker */
int y = best[bestpos].yhi;
while (b->list[y].start[0])
y++;
find_best_inorder(a, b,
best[bestpos].xhi, ahi,
y, bhi,
best, bestpos+1, besthi);
}
}
static gpudata *cuda_alloc(void *c, size_t size, void *data, int flags,
int *ret) {
gpudata *res = NULL, *prev = NULL;
cuda_context *ctx = (cuda_context *)c;
size_t asize;
int err;
if ((flags & GA_BUFFER_INIT) && data == NULL) FAIL(NULL, GA_VALUE_ERROR);
if ((flags & (GA_BUFFER_READ_ONLY|GA_BUFFER_WRITE_ONLY)) ==
(GA_BUFFER_READ_ONLY|GA_BUFFER_WRITE_ONLY)) FAIL(NULL, GA_VALUE_ERROR);
/* TODO: figure out how to make this work */
if (flags & GA_BUFFER_HOST) FAIL(NULL, GA_DEVSUP_ERROR);
/* We don't want to manage really small allocations so we round up
* to a multiple of FRAG_SIZE. This also ensures that if we split a
* block, the next block starts properly aligned for any data type.
*/
if (!(ctx->flags & GA_CTX_DISABLE_ALLOCATION_CACHE)) {
asize = roundup(size, FRAG_SIZE);
find_best(ctx, &res, &prev, asize);
} else {
asize = size;
}
if (res == NULL) {
err = allocate(ctx, &res, &prev, asize);
if (err != GA_NO_ERROR)
FAIL(NULL, err);
}
err = extract(res, prev, asize);
if (err != GA_NO_ERROR)
FAIL(NULL, err);
/* It's out of the freelist, so add a ref */
res->ctx->refcnt++;
/* We consider this buffer allocated and ready to go */
res->refcnt = 1;
if (flags & GA_BUFFER_INIT) {
err = cuda_write(res, 0, data, size);
if (err != GA_NO_ERROR) {
cuda_free(res);
FAIL(NULL, err);
}
}
return res;
}
int ast_cli_command(int fd, char *s)
{
char *argv[AST_MAX_ARGS];
struct ast_cli_entry *e;
int x;
char *dup;
x = AST_MAX_ARGS;
if ((dup = parse_args(s, &x, argv))) {
/* We need at least one entry, or ignore */
if (x > 0) {
ast_mutex_lock(&clilock);
e = find_cli(argv, 0);
if (e)
e->inuse++;
ast_mutex_unlock(&clilock);
if (e) {
switch(e->handler(fd, x, argv)) {
case RESULT_SHOWUSAGE:
ast_cli(fd, e->usage);
break;
}
} else
ast_cli(fd, "No such command '%s' (type 'help' for help)\n", find_best(argv));
if (e) {
ast_mutex_lock(&clilock);
e->inuse--;
ast_mutex_unlock(&clilock);
}
}
free(dup);
} else {
ast_log(LOG_WARNING, "Out of memory\n");
return -1;
}
return 0;
}
void generate_2D_sample (FILE *output, struct speed_params2D param)
{
mpfr_t temp;
double incr_prec;
mpfr_t incr_x;
mpfr_t x, x2;
double prec;
struct speed_params s;
int i;
int test;
int nb_functions;
double *t; /* store the timing of each implementation */
/* We first determine how many implementations we have */
nb_functions = 0;
while (param.speed_funcs[nb_functions] != NULL)
nb_functions++;
t = malloc (nb_functions * sizeof (double));
if (t == NULL)
{
fprintf (stderr, "Can't allocate memory.\n");
abort ();
}
mpfr_init2 (temp, MPFR_SMALL_PRECISION);
/* The precision is sampled from min_prec to max_prec with */
/* approximately nb_points_prec points. If logarithmic_scale_prec */
/* is true, the precision is multiplied by incr_prec at each */
/* step. Otherwise, incr_prec is added at each step. */
if (param.logarithmic_scale_prec)
{
mpfr_set_ui (temp, (unsigned long int)param.max_prec, MPFR_RNDU);
mpfr_div_ui (temp, temp, (unsigned long int)param.min_prec, MPFR_RNDU);
mpfr_root (temp, temp,
(unsigned long int)param.nb_points_prec, MPFR_RNDU);
incr_prec = mpfr_get_d (temp, MPFR_RNDU);
}
else
{
incr_prec = (double)param.max_prec - (double)param.min_prec;
incr_prec = incr_prec/((double)param.nb_points_prec);
}
/* The points x are sampled according to the following rule: */
/* If logarithmic_scale_x = 0: */
/* nb_points_x points are equally distributed between min_x and max_x */
/* If logarithmic_scale_x = 1: */
/* nb_points_x points are sampled from 2^(min_x) to 2^(max_x). At */
/* each step, the current point is multiplied by incr_x. */
/* If logarithmic_scale_x = -1: */
/* nb_points_x/2 points are sampled from -2^(max_x) to -2^(min_x) */
/* (at each step, the current point is divided by incr_x); and */
/* nb_points_x/2 points are sampled from 2^(min_x) to 2^(max_x) */
/* (at each step, the current point is multiplied by incr_x). */
mpfr_init2 (incr_x, param.max_prec);
if (param.logarithmic_scale_x == 0)
{
mpfr_set_d (incr_x,
(param.max_x - param.min_x)/(double)param.nb_points_x,
MPFR_RNDU);
}
else if (param.logarithmic_scale_x == -1)
{
mpfr_set_d (incr_x,
2.*(param.max_x - param.min_x)/(double)param.nb_points_x,
MPFR_RNDU);
mpfr_exp2 (incr_x, incr_x, MPFR_RNDU);
}
else
{ /* other values of param.logarithmic_scale_x are considered as 1 */
mpfr_set_d (incr_x,
(param.max_x - param.min_x)/(double)param.nb_points_x,
MPFR_RNDU);
mpfr_exp2 (incr_x, incr_x, MPFR_RNDU);
}
/* Main loop */
mpfr_init2 (x, param.max_prec);
mpfr_init2 (x2, param.max_prec);
prec = (double)param.min_prec;
while (prec <= param.max_prec)
{
printf ("prec = %d\n", (int)prec);
if (param.logarithmic_scale_x == 0)
mpfr_set_d (temp, param.min_x, MPFR_RNDU);
else if (param.logarithmic_scale_x == -1)
{
mpfr_set_d (temp, param.max_x, MPFR_RNDD);
mpfr_exp2 (temp, temp, MPFR_RNDD);
mpfr_neg (temp, temp, MPFR_RNDU);
}
else
{
mpfr_set_d (temp, param.min_x, MPFR_RNDD);
mpfr_exp2 (temp, temp, MPFR_RNDD);
}
/* We perturb x a little bit, in order to avoid trailing zeros that */
/* might change the behavior of algorithms. */
mpfr_const_pi (x, MPFR_RNDN);
mpfr_div_2ui (x, x, 7, MPFR_RNDN);
mpfr_add_ui (x, x, 1, MPFR_RNDN);
mpfr_mul (x, x, temp, MPFR_RNDN);
test = 1;
while (test)
{
mpfr_fprintf (output, "%e\t", mpfr_get_d (x, MPFR_RNDN));
mpfr_fprintf (output, "%Pu\t", (mpfr_prec_t)prec);
s.r = (mp_limb_t)mpfr_get_exp (x);
s.size = (mpfr_prec_t)prec;
s.align_xp = (mpfr_sgn (x) > 0)?1:2;
mpfr_set_prec (x2, (mpfr_prec_t)prec);
mpfr_set (x2, x, MPFR_RNDU);
s.xp = x2->_mpfr_d;
for (i=0; i<nb_functions; i++)
{
t[i] = speed_measure (param.speed_funcs[i], &s);
mpfr_fprintf (output, "%e\t", t[i]);
}
fprintf (output, "%d\n", 1 + find_best (t, nb_functions));
if (param.logarithmic_scale_x == 0)
{
mpfr_add (x, x, incr_x, MPFR_RNDU);
if (mpfr_cmp_d (x, param.max_x) > 0)
test=0;
}
else
{
if (mpfr_sgn (x) < 0 )
{ /* if x<0, it means that logarithmic_scale_x=-1 */
mpfr_div (x, x, incr_x, MPFR_RNDU);
mpfr_abs (temp, x, MPFR_RNDD);
mpfr_log2 (temp, temp, MPFR_RNDD);
if (mpfr_cmp_d (temp, param.min_x) < 0)
mpfr_neg (x, x, MPFR_RNDN);
}
else
{
mpfr_mul (x, x, incr_x, MPFR_RNDU);
mpfr_set (temp, x, MPFR_RNDD);
mpfr_log2 (temp, temp, MPFR_RNDD);
if (mpfr_cmp_d (temp, param.max_x) > 0)
test=0;
}
}
}
prec = ( (param.logarithmic_scale_prec) ? (prec * incr_prec)
: (prec + incr_prec) );
fprintf (output, "\n");
}
free (t);
mpfr_clear (incr_x);
mpfr_clear (x);
mpfr_clear (x2);
mpfr_clear (temp);
return;
}
/**Function********************************************************************
Synopsis [Genetic algorithm for DD reordering.]
Description [Genetic algorithm for DD reordering.
The two children of a crossover will be stored in
storedd[popsize] and storedd[popsize+1] --- the last two slots in the
storedd array. (This will make comparisons and replacement easy.)
Returns 1 in case of success; 0 otherwise.]
SideEffects [None]
SeeAlso []
******************************************************************************/
int
cuddGa(
DdManager * table /* manager */,
int lower /* lowest level to be reordered */,
int upper /* highest level to be reorderded */)
{
int i,n,m; /* dummy/loop vars */
int index;
#ifdef DD_STATS
double average_fitness;
#endif
int small; /* index of smallest DD in population */
/* Do an initial sifting to produce at least one reasonable individual. */
if (!cuddSifting(table,lower,upper)) return(0);
/* Get the initial values. */
numvars = upper - lower + 1; /* number of variables to be reordered */
if (table->populationSize == 0) {
popsize = 3 * numvars; /* population size is 3 times # of vars */
if (popsize > 120) {
popsize = 120; /* Maximum population size is 120 */
}
} else {
popsize = table->populationSize; /* user specified value */
}
if (popsize < 4) popsize = 4; /* enforce minimum population size */
/* Allocate population table. */
storedd = ALLOC(int,(popsize+2)*(numvars+1));
if (storedd == NULL) {
table->errorCode = CUDD_MEMORY_OUT;
return(0);
}
/* Initialize the computed table. This table is made up of two data
** structures: A hash table with the key given by the order, which says
** if a given order is present in the population; and the repeat
** vector, which says how many copies of a given order are stored in
** the population table. If there are multiple copies of an order, only
** one has a repeat count greater than 1. This copy is the one pointed
** by the computed table.
*/
repeat = ALLOC(int,popsize);
if (repeat == NULL) {
table->errorCode = CUDD_MEMORY_OUT;
FREE(storedd);
return(0);
}
for (i = 0; i < popsize; i++) {
repeat[i] = 0;
}
computed = st_init_table(array_compare,array_hash);
if (computed == NULL) {
table->errorCode = CUDD_MEMORY_OUT;
FREE(storedd);
FREE(repeat);
return(0);
}
/* Copy the current DD and its size to the population table. */
for (i = 0; i < numvars; i++) {
STOREDD(0,i) = table->invperm[i+lower]; /* order of initial DD */
}
STOREDD(0,numvars) = table->keys - table->isolated; /* size of initial DD */
/* Store the initial order in the computed table. */
if (st_insert(computed,(char *)storedd,(char *) 0) == ST_OUT_OF_MEM) {
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
repeat[0]++;
/* Insert the reverse order as second element of the population. */
for (i = 0; i < numvars; i++) {
STOREDD(1,numvars-1-i) = table->invperm[i+lower]; /* reverse order */
}
/* Now create the random orders. make_random fills the population
** table with random permutations. The successive loop builds and sifts
** the DDs for the reverse order and each random permutation, and stores
** the results in the computed table.
*/
if (!make_random(table,lower)) {
table->errorCode = CUDD_MEMORY_OUT;
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
for (i = 1; i < popsize; i++) {
result = build_dd(table,i,lower,upper); /* build and sift order */
if (!result) {
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
if (st_lookup_int(computed,(char *)&STOREDD(i,0),&index)) {
repeat[index]++;
} else {
if (st_insert(computed,(char *)&STOREDD(i,0),(char *)(long)i) ==
ST_OUT_OF_MEM) {
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
repeat[i]++;
}
}
#if 0
#ifdef DD_STATS
/* Print the initial population. */
(void) fprintf(table->out,"Initial population after sifting\n");
for (m = 0; m < popsize; m++) {
for (i = 0; i < numvars; i++) {
(void) fprintf(table->out," %2d",STOREDD(m,i));
}
(void) fprintf(table->out," : %3d (%d)\n",
STOREDD(m,numvars),repeat[m]);
}
#endif
#endif
small = find_best();
#ifdef DD_STATS
average_fitness = find_average_fitness();
(void) fprintf(table->out,"\nInitial population: best fitness = %d, average fitness %8.3f",STOREDD(small,numvars),average_fitness);
#endif
/* Decide how many crossovers should be tried. */
if (table->numberXovers == 0) {
cross = 3*numvars;
if (cross > 60) { /* do a maximum of 50 crossovers */
cross = 60;
}
} else {
cross = table->numberXovers; /* use user specified value */
}
/* Perform the crossovers to get the best order. */
for (m = 0; m < cross; m++) {
if (!PMX(table->size)) { /* perform one crossover */
table->errorCode = CUDD_MEMORY_OUT;
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
/* The offsprings are left in the last two entries of the
** population table. These are now considered in turn.
*/
for (i = popsize; i <= popsize+1; i++) {
result = build_dd(table,i,lower,upper); /* build and sift child */
if (!result) {
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
large = largest(); /* find the largest DD in population */
/* If the new child is smaller than the largest DD in the current
** population, enter it into the population in place of the
** largest DD.
*/
if (STOREDD(i,numvars) < STOREDD(large,numvars)) {
/* Look up the largest DD in the computed table.
** Decrease its repetition count. If the repetition count
** goes to 0, remove the largest DD from the computed table.
*/
result = st_lookup_int(computed,(char *)&STOREDD(large,0),
&index);
if (!result) {
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
repeat[index]--;
if (repeat[index] == 0) {
int *pointer = &STOREDD(index,0);
result = st_delete(computed, (char **)&pointer,NULL);
if (!result) {
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
}
/* Copy the new individual to the entry of the
** population table just made available and update the
** computed table.
*/
for (n = 0; n <= numvars; n++) {
STOREDD(large,n) = STOREDD(i,n);
}
if (st_lookup_int(computed,(char *)&STOREDD(large,0),
&index)) {
repeat[index]++;
} else {
if (st_insert(computed,(char *)&STOREDD(large,0),
(char *)(long)large) == ST_OUT_OF_MEM) {
FREE(storedd);
FREE(repeat);
st_free_table(computed);
return(0);
}
repeat[large]++;
}
}
}
}
/* Find the smallest DD in the population and build it;
** that will be the result.
*/
small = find_best();
/* Print stats on the final population. */
#ifdef DD_STATS
average_fitness = find_average_fitness();
(void) fprintf(table->out,"\nFinal population: best fitness = %d, average fitness %8.3f",STOREDD(small,numvars),average_fitness);
#endif
/* Clean up, build the result DD, and return. */
st_free_table(computed);
computed = NULL;
result = build_dd(table,small,lower,upper);
FREE(storedd);
FREE(repeat);
return(result);
} /* end of cuddGa */
void add_addr(struct address *addr) {
remove_entry(addr);
add_entry(addr);
find_best();
}
