static real_t
aac_bits (const real_t *used_coeff, const word_t *used_states,
unsigned level, const coeff_t *coeff)
{
real_t bits = 0; /* # bits to store coefficients */
unsigned edge;
int state;
word_t *counts;
aac_model_t *model = (aac_model_t *) coeff->model;
counts = model->counts
+ (1 << (1 + coeff->dc_rpf->mantissa_bits))
+ ((level - coeff->min_level)
* (1 << (1 + coeff->rpf->mantissa_bits)));
for (edge = 0; isedge (state = used_states [edge]); edge++)
if (state)
bits -= log2 (counts [rtob (used_coeff [edge], coeff->rpf)]
/ (real_t) model->totals [level
- coeff->min_level + 1]);
else
bits -= log2 (model->counts [rtob (used_coeff [edge], coeff->dc_rpf)]
/ (real_t) model->totals [0]);
return bits;
}
static void
qac_update (const word_t *domains, const word_t *used_domains,
unsigned level, int y_state, const wfa_t *wfa, void *model)
{
int domain;
unsigned edge;
bool_t used_y_state = NO;
qac_model_t *qac_model = (qac_model_t *) model;
bool_t y_state_is_domain = NO;
if (y_state >= 0 && !usedomain (y_state, wfa)) /* don't use y-state */
y_state = -1;
for (domain = 0; domain < qac_model->n; domain++)
{
qac_model->index [domain]++; /* mark domains unused. */
if (qac_model->states [domain] == y_state) /* match */
y_state_is_domain = YES;
}
for (edge = 0; isedge (domain = used_domains [edge]); edge++)
if (domains [domain] == y_state) /* chroma coding */
{
if (y_state_is_domain)
qac_model->index [domain]--; /* undo */
qac_model->y_index >>= 1;
used_y_state = YES;
}
else /* luminance coding */
{
static void
aac_update (const real_t *used_coeff, const word_t *used_states,
unsigned level, coeff_t *coeff)
{
unsigned edge;
int state;
word_t *counts;
aac_model_t *model = (aac_model_t *) coeff->model;
counts = model->counts
+ (1 << (1 + coeff->dc_rpf->mantissa_bits))
+ ((level - coeff->min_level)
* (1 << (1 + coeff->rpf->mantissa_bits)));
for (edge = 0; isedge (state = used_states [edge]); edge++)
if (state)
{
counts [rtob (used_coeff [edge], coeff->rpf)]++;
model->totals [level - coeff->min_level + 1]++;
}
else
{
model->counts [rtob (used_coeff [edge], coeff->dc_rpf)]++;
model->totals [0]++;
}
}
real_t
compute_final_distribution (unsigned state, const wfa_t *wfa)
/*
* Compute the final distribution of the given 'state'.
* Uses the fact that the generated 'wfa' is average preserving.
*
* Return value:
* final distribution
*/
{
unsigned label;
real_t final = 0;
for (label = 0; label < MAXLABELS; label++)
{
unsigned edge;
int domain;
if (ischild (domain = wfa->tree [state][label]))
final += wfa->final_distribution [domain];
for (edge = 0; isedge (domain = wfa->into [state][label][edge]); edge++)
final += wfa->weight [state][label][edge]
* wfa->final_distribution [domain];
}
return final / MAXLABELS;
}
/*
* Move to a particular position and see if we hit a mine.
* If not, then count the number of mines adjacent to us so it can be seen.
* If we are stepping onto a location where we remembered a mine is at,
* then don't do it. Moving is only allowed to old locations, or to
* locations adjacent to old ones.
*/
static void
movetopos(POS newpos)
{
POS fixpos; /* position to fix up */
CELL cell; /* current cell */
GR_COUNT count; /* count of cells */
GR_COUNT i; /* index for neighbors */
if ((newpos < 0) || (newpos >= (FULLSIZE * FULLSIZE)) || !playing)
return;
cell = board[newpos];
if (isedge(cell) || (isseen(cell)) || isold(cell))
return;
count = isold(cell);
for (i = 0; i < 8; i++)
if (isold(board[newpos + steptable[i]]))
count++;
if (count <= 0)
return;
cell = (cell & F_FLAGS) | F_OLD;
steps++;
PRINTSTEPS;
if (ismine(cell)) { /* we hit a mine */
legs--;
board[newpos] = (F_REMEMBER | F_MINE);
cell = (F_EMPTY | F_OLD);
board[newpos] = cell;
drawbomb(newpos, redgc, GR_TRUE);
clearcell(newpos);
setcursor();
for (i = 0; i < 8; i++) {
fixpos = newpos + steptable[i];
if (isold(board[fixpos])) {
board[fixpos]--;
drawcell(fixpos);
}
}
drawstatus();
}
count = 0;
for (i = 0; i < 8; i++)
if (ismine(board[newpos + steptable[i]]))
count++;
board[newpos] = cell | (count + '0');
drawcell(newpos);
if ((legs <= 0) || (newpos == boardpos(size,size)))
gameover();
}
vector<hvec> trace(hvec stpoint)
/* Traces a contour. The start point, because of the way the iteration works,
* is the leftmost point of the bottom line, so it starts going right.
*/
{hvec dir(1), left(1,1), right(0,-1);
vector<hvec> contour;
while (isedge(stpoint) && !ismarked(stpoint))
{contour.push_back(stpoint);
mark(stpoint);
if (isedge(stpoint+dir))
;
else if (isedge(stpoint+dir*left))
dir*=left;
else
dir*=right;
stpoint+=dir;
}
return contour;
}
word_t *
compute_hits (unsigned from, unsigned to, unsigned n, const wfa_t *wfa)
/*
* Selects the 'n' most popular domain images of the given 'wfa'.
* Consider only linear combinations of state images
* {i | 'from' <= i <= 'to'}. I.e. domains are in {i | from <= i < 'to'}
* Always ensure that state 0 is among selected states even though from
* may be > 0.
*
* Return value:
* pointer to array of the most popular state images
* sorted by increasing state numbers and terminated by -1
*/
{
word_t *domains;
unsigned state, label, edge;
int domain;
pair_t *hits = Calloc (to, sizeof (pair_t));
for (domain = 0; domain < (int) to; domain++)
{
hits [domain].value = domain;
hits [domain].key = 0;
}
for (state = from; state <= to; state++)
for (label = 0; label < MAXLABELS; label++)
for (edge = 0; isedge (domain = wfa->into [state][label][edge]);
edge++)
hits [domain].key++;
qsort (hits + 1, to - 1, sizeof (pair_t), sort_desc_pair);
n = min (to, n);
domains = Calloc (n + 1, sizeof (word_t));
for (domain = 0; domain < (int) n && (!domain || hits [domain].key);
domain++)
domains [domain] = hits [domain].value;
if (n != domain)
debug_message ("Only %d domains have been used in the luminance.",
domain);
n = domain;
qsort (domains, n, sizeof (word_t), sort_asc_word);
domains [n] = -1;
Free (hits);
return domains;
}
static real_t
uniform_bits (const real_t *used_coeff, const word_t *used_states,
unsigned level, const coeff_t *coeff)
{
unsigned edge;
real_t bits = 0; /* #bits to store coefficients */
for (edge = 0; isedge (used_states [edge]); edge++)
{
rpf_t *rpf = used_states [edge] ? coeff->rpf : coeff->dc_rpf;
bits += rpf->mantissa_bits + 1;
}
return bits;
}
gchar *property_helper_get_type(ScintillaObject *current_doc_sci, CXSourceLocation code_source_location) {
gchar *type_string = NULL;
gchar current_char, previous_char;
unsigned int source_offset;
size_t type_literal_begining = 0;
size_t type_literal_ending = 0;
gboolean is_edge = FALSE;
gboolean is_in_type = FALSE;
clang_getInstantiationLocation(code_source_location,NULL,NULL,NULL,&source_offset);
while (is_edge == FALSE) {
while (isspace((current_char = sci_get_char_at(current_doc_sci,--source_offset))));
if (current_char == ',' || current_char == '=') {
while (isspace((current_char = sci_get_char_at(current_doc_sci,--source_offset))));
while (!isspace((current_char = sci_get_char_at(current_doc_sci,--source_offset))));
continue;
}
previous_char = sci_get_char_at(current_doc_sci,source_offset-1);
if (isedge(current_char,previous_char)) {
if (type_string == NULL) {
if (is_in_type == FALSE) {
type_string = malloc(4 * sizeof(gchar));
strncpy(type_string,"int",4);
} else {
gchar *untrimmed_type_string = NULL;
type_literal_begining = source_offset + 1;
untrimmed_type_string = sci_get_contents_range(current_doc_sci,type_literal_begining,type_literal_ending);
type_string = trim_left_string(untrimmed_type_string);
free (untrimmed_type_string);
}
is_edge = TRUE;
}
}
if (is_in_type == FALSE) {
type_literal_ending = source_offset + 1;
is_in_type = TRUE;
}
}
return type_string;
}
static real_t
qac_bits (const word_t *domains, const word_t *used_domains,
unsigned level, int y_state, const wfa_t *wfa, const void *model)
{
int domain; /* counter */
real_t bits = 0; /* bit rate R */
qac_model_t *qac_model = (qac_model_t *) model; /* probability model */
if (y_state >= 0 && !usedomain (y_state, wfa)) /* don't use y-state */
y_state = -1;
for (domain = 0; domain < qac_model->n; domain++)
if (qac_model->states [domain] != y_state)
bits += matrix_0 [qac_model->index [domain]];
if (y_state >= 0)
bits += matrix_0 [qac_model->y_index];
if (used_domains != NULL)
{
unsigned edge;
for (edge = 0; isedge (domain = used_domains [edge]); edge++)
if (domains [domain] == y_state)
{
bits -= matrix_0 [qac_model->y_index];
bits += matrix_1 [qac_model->y_index];
}
else
{
bits -= matrix_0 [qac_model->index [domain]];
bits += matrix_1 [qac_model->index [domain]];
}
}
return bits;
}
real_t
approximate_range (real_t max_costs, real_t price, int max_edges,
int y_state, range_t *range, domain_pool_t *domain_pool,
coeff_t *coeff, const wfa_t *wfa, const coding_t *c)
/*
* Approximate image block 'range' by matching pursuit. This functions
* calls the matching pursuit algorithm several times (with different
* parameters) in order to find the best approximation. Refer to function
* 'matching_pursuit()' for more details about parameters.
*
* Return value:
* approximation costs
*/
{
mp_t mp;
bool_t success = NO;
/*
* First approximation attempt: default matching pursuit algorithm.
*/
mp.exclude [0] = NO_EDGE;
matching_pursuit (&mp, c->options.full_search, price, max_edges,
y_state, range, domain_pool, coeff, wfa, c);
/*
* Next approximation attempt: remove domain block mp->indices [0]
* from domain pool (vector with smallest costs) and run the
* matching pursuit again.
*/
if (c->options.second_domain_block)
{
mp_t tmp_mp = mp;
tmp_mp.exclude [0] = tmp_mp.indices [0];
tmp_mp.exclude [1] = NO_EDGE;
matching_pursuit (&tmp_mp, c->options.full_search, price, max_edges,
y_state, range, domain_pool, coeff, wfa, c);
if (tmp_mp.costs < mp.costs) /* success */
{
success = YES;
mp = tmp_mp;
}
}
/*
* Next approximation attempt: check whether some coefficients have
* been quantized to zero. Vectors causing the underflow are
* removed from the domain pool and then the matching pursuit
* algorithm is run again (until underflow doesn't occur anymore).
*/
if (c->options.check_for_underflow)
{
int iteration = -1;
mp_t tmp_mp = mp;
do
{
int i;
iteration++;
tmp_mp.exclude [iteration] = NO_EDGE;
for (i = 0; isdomain (tmp_mp.indices [i]); i++)
if (tmp_mp.weight [i] == 0)
{
tmp_mp.exclude [iteration] = tmp_mp.indices [i];
break;
}
if (isdomain (tmp_mp.exclude [iteration])) /* try again */
{
tmp_mp.exclude [iteration + 1] = NO_EDGE;
matching_pursuit (&tmp_mp, c->options.full_search, price,
max_edges, y_state, range, domain_pool,
coeff, wfa, c);
if (tmp_mp.costs < mp.costs) /* success */
{
success = YES;
mp = tmp_mp;
}
}
} while (isdomain (tmp_mp.exclude [iteration])
&& iteration < MAXEDGES - 1);
}
/*
* Next approximation attempt: check whether some coefficients have
* been quantized to +/- max-value. Vectors causing the overflow are
* removed from the domain pool and then the matching pursuit
* algorithm is run again (until overflow doesn't occur anymore).
*/
if (c->options.check_for_overflow)
{
int iteration = -1;
mp_t tmp_mp = mp;
do
{
int i;
iteration++;
tmp_mp.exclude [iteration] = NO_EDGE;
for (i = 0; isdomain (tmp_mp.indices [i]); i++)
{
rpf_t *rpf = tmp_mp.indices [i] ? coeff->rpf : coeff->dc_rpf;
if (tmp_mp.weight [i] == btor (rtob (200, rpf), rpf)
|| tmp_mp.weight [i] == btor (rtob (-200, rpf), rpf))
{
tmp_mp.exclude [iteration] = tmp_mp.indices [i];
break;
}
}
if (isdomain (tmp_mp.exclude [iteration])) /* try again */
{
tmp_mp.exclude [iteration + 1] = NO_EDGE;
matching_pursuit (&tmp_mp, c->options.full_search, price,
max_edges, y_state, range, domain_pool,
coeff, wfa, c);
if (tmp_mp.costs < mp.costs) /* success */
{
success = YES;
mp = tmp_mp;
}
}
} while (isdomain (tmp_mp.exclude [iteration])
&& iteration < MAXEDGES - 1);
}
/*
* Finally, check whether the best approximation has costs
* smaller than 'max_costs'.
*/
if (mp.costs < max_costs)
{
int edge;
bool_t overflow = NO;
bool_t underflow = NO;
int new_index, old_index;
new_index = 0;
for (old_index = 0; isdomain (mp.indices [old_index]); old_index++)
if (mp.weight [old_index] != 0)
{
rpf_t *rpf = mp.indices [old_index] ? coeff->rpf : coeff->dc_rpf;
if (mp.weight [old_index] == btor (rtob (200, rpf), rpf)
|| mp.weight [old_index] == btor (rtob (-200, rpf), rpf))
overflow = YES;
mp.indices [new_index] = mp.indices [old_index];
mp.into [new_index] = mp.into [old_index];
mp.weight [new_index] = mp.weight [old_index];
new_index++;
}
else
underflow = YES;
mp.indices [new_index] = NO_EDGE;
mp.into [new_index] = NO_EDGE;
/*
* Update of probability models
*/
{
word_t *domain_blocks = domain_pool->generate (range->level, y_state,
wfa,
domain_pool->model);
domain_pool->update (domain_blocks, mp.indices,
range->level, y_state, wfa, domain_pool->model);
coeff->update (mp.weight, mp.into, range->level, coeff);
Free (domain_blocks);
}
for (edge = 0; isedge (mp.indices [edge]); edge++)
{
range->into [edge] = mp.into [edge];
range->weight [edge] = mp.weight [edge];
}
range->into [edge] = NO_EDGE;
range->matrix_bits = mp.matrix_bits;
range->weights_bits = mp.weights_bits;
range->err = mp.err;
}
else
{
range->into [0] = NO_EDGE;
mp.costs = MAXCOSTS;
}
return mp.costs;
}
int main() {
// Define Variables
std::string parameter_filename = "solver_parms.txt";
std::string input_filename = "5x5square2.bkcfd";
std::vector<double> parameters;
std::vector<double> Fiph, Fimh, Giph, Gimh;
double CFL, tmax, delta_x, delta_y, min_delta_x, min_delta_y, min_delta;
TDstate state_minus, state_plus, slope_minus, slope_plus, limiter_value;
std::vector<TDstate> F (2);
std::vector<TDstate> G (2);
// double thresh = 0.00001; // 1E-5 tolerance for riemann solver - velocity
double gamma = 1.4;
// 1 = harmonic mean for slopes, 2 = ...
int limiter_number = 1;
std::vector<cell> grid;
// Read parameters from input file defined by filename string
parameters = read_parameters(parameter_filename);
// CFL = parameters.at(0);
// tmax = parameters.at(1);
// Read initial file defined from Matlab with cell edges and connections
// Read the initial condition file from MATLAB with [rho rho*u rho*v e] defined for each cell
read_grid(input_filename, grid, gamma);
std::vector<TDstate> Uph (grid.size());
min_delta_x = gridmin(grid, 'x');
min_delta_y = gridmin(grid, 'y');
min_delta = std::min(min_delta_x,min_delta_y);
/* std::cout << "printing now..." << '\n';
for(auto input: grid) {
std::cout << input.cellnumber << '\n';
std::cout << input.cornerlocs_x[0] << ' ';
std::cout << input.cornerlocs_x[1] << ' ';
std::cout << input.cornerlocs_x[2] << ' ';
std::cout << input.cornerlocs_x[3] << '\n';
std::cout << input.cornerlocs_y[0] << ' ';
std::cout << input.cornerlocs_y[1] << ' ';
std::cout << input.cornerlocs_y[2] << ' ';
std::cout << input.cornerlocs_y[3] << '\n';
std::cout << input.adjacent_cells[0] << ' ';
std::cout << input.adjacent_cells[1] << ' ';
std::cout << input.adjacent_cells[2] << ' ';
std::cout << input.adjacent_cells[3] << '\n';
std::cout << input.state.rho << ' ';
std::cout << input.state.rhou << ' ';
std::cout << input.state.rhov << ' ';
std::cout << input.state.E << '\n' << '\n';
}
*/
// Start calculation in for loop going to final time
// for (double t = 0, t <= tmax; t++)
double max_wavespeed = 0;
// Go through each cell, calculate fluxes, update to new piecewise linear state
for (unsigned int cellnum = 0; cellnum < grid.size(); ++cellnum) { // For each cell
if (!isedge(grid,cellnum)) {
delta_x = (vectormax(grid[cellnum].cornerlocs_x) - vectormin(grid[cellnum].cornerlocs_x));
delta_y = (vectormax(grid[cellnum].cornerlocs_y) - vectormin(grid[cellnum].cornerlocs_y));
// Calculate the limited flux of each conserved quantity for initial t -> t+1/2 update
for (int direction = 0; direction < 2; ++direction) { // For the left/right direction and up/down direction
// Assign the bottom/left and the top/right states for each cell
assign_edge_state(state_minus, state_plus, grid, cellnum, direction);
// Calculate the flux of each conserved variable, in each direction, on each face, of that cell.
// Flux needs to be calculated by first finding the limiter (direction-dependent), then using that limiter to calculate the directional flux, then using the two directional fluxes to update from u_t to u_t+1/2
compute_slope(slope_minus, slope_plus, grid, cellnum, direction, state_minus, state_plus, delta_x, delta_y);
compute_limiter(limiter_value, slope_minus, slope_plus, limiter_number);
if (direction == 0) { // Compute F, x-fluxes
compute_limited_flux(F, limiter_value, min_delta, CFL, grid[cellnum].state, slope_plus, direction, gamma);
// std::cout << "rho limiter x: " << limiter_value.rho << '\n';
} else { // Compute G, y-fluxes
// std::cout << "rho limiter y: " << limiter_value.rho << '\n';
compute_limited_flux(G, limiter_value, min_delta, CFL, grid[cellnum].state, slope_plus, direction, gamma);
}
} // end of for (int direction = 0; direction < 2; ++direction)
// std::cout << "F flux: " << F[0].rho << " " << F[1].rho << ", G flux: " << G[0].rho << " " << G[1].rho << '\n';
fluxmax(max_wavespeed, F, G, grid[cellnum].state);
} // end of if (!isedge(grid,cell))
// Compute the max
// Now, use the fluxes calculated above to assign a new state, Uph
compute_halfway_state(Uph, F, G, CFL);
// -----------------------------
// Need to check values of flux to see if they are giving accurate results!
//
// Go through each edge, calculate flux, save
// for (int edge = 1, edge <= numedges, ++edge)
//
// Solve riemann problem on edge for euler flux
ODstate left;
ODstate right;
left.rho = 1.0; //rho
left.rhou = 300; //rho*u or rho*v
left.E = 100000/0.4 - pow(left.rhou,2)/(left.rho*2); //E
right.rho = 1;
right.rhou = 0;
right.E = 100000/0.4 - pow(right.rhou,2)/(right.rho*2);
/* ODstate test_state = Exact_Riemann_Solver(left, right, thresh, gamma);
std::cout << '\n' << "State on x=0 is:" << '\n';
std::cout << test_state.rho << '\n';
std::cout << test_state.rhou << '\n';
std::cout << test_state.E << '\n';
std::cout << test_state.pressure << '\n';
*/
//Use all these fluxes to define updated state on each cell
//Option to save at each timestep
} // end of for(unsigned int cell = 0; cell < grid.size(); ++cell)
return 0;
}
/** tries to find a clique, if V has only one or two nodes */
static
void reduced(
TCLIQUE_GETWEIGHTS((*getweights)), /**< user function to get the node weights */
TCLIQUE_ISEDGE ((*isedge)), /**< user function to check for existence of an edge */
TCLIQUE_GRAPH* tcliquegraph, /**< pointer to graph data structure */
int* V, /**< non-zero weighted nodes for branching */
int nV, /**< number of non-zero weighted nodes for branching */
TCLIQUE_WEIGHT* apbound, /**< apriori bound of nodes for branching */
int* tmpcliquenodes, /**< buffer for storing the temporary clique */
int* ntmpcliquenodes, /**< pointer to store number of nodes of the temporary clique */
TCLIQUE_WEIGHT* tmpcliqueweight /**< pointer to store weight of the temporary clique */
)
{
const TCLIQUE_WEIGHT* weights;
assert(getweights != NULL);
assert(isedge != NULL);
assert(tcliquegraph != NULL);
assert(V != NULL);
assert(0 <= nV && nV <= 2);
assert(apbound != NULL);
assert(tmpcliquenodes != NULL);
assert(ntmpcliquenodes != NULL);
assert(tmpcliqueweight != NULL);
weights = getweights(tcliquegraph);
assert(nV == 0 || weights[V[0]] > 0);
assert(nV <= 1 || weights[V[1]] > 0);
if( nV >= 1 )
apbound[0] = weights[V[0]];
if( nV >= 2 )
apbound[1] = weights[V[1]];
/* check if nodes are adjacent */
if( nV >= 2 && isedge(tcliquegraph, V[0], V[1]) )
{
assert(isedge(tcliquegraph, V[1], V[0]));
/* put nodes into clique */
tmpcliquenodes[0] = V[0];
tmpcliquenodes[1] = V[1];
*ntmpcliquenodes = 2;
*tmpcliqueweight = weights[V[0]] + weights[V[1]];
apbound[0] += weights[V[1]];
}
else if( nV >= 2 && weights[V[1]] > weights[V[0]] )
{
/* put V[1] into clique */
tmpcliquenodes[0] = V[1];
*ntmpcliquenodes = 1;
*tmpcliqueweight = weights[V[1]];
}
else if( nV >= 1 )
{
/* put V[0] into clique */
tmpcliquenodes[0] = V[0];
*ntmpcliquenodes = 1;
*tmpcliqueweight = weights[V[0]];
}
else
{
*tmpcliqueweight = 0;
*ntmpcliquenodes = 0;
}
}
image_t *
decode_image (unsigned orig_width, unsigned orig_height, format_e format,
unsigned *dec_timer, const wfa_t *wfa)
/*
* Compute image which is represented by the given 'wfa'.
* 'orig_width'x'orig_height' gives the resolution of the image at
* coding time. Use 4:2:0 subsampling or 4:4:4 'format' for color images.
* If 'dec_timer' is given, accumulate running time statistics.
*
* Return value:
* pointer to decoded image
*
* Side effects:
* '*dectimer' is changed if 'dectimer' != NULL.
*/
{
unsigned root_state [3]; /* root of bintree for each band */
unsigned width, height; /* computed image size */
image_t *frame; /* regenerated frame */
word_t **images; /* pointer to array of pointers
to state images */
u_word_t *offsets; /* pointer to array of state image
offsets */
unsigned max_level; /* max. level of state with approx. */
unsigned state;
clock_t ptimer;
prg_timer (&ptimer, START);
/*
* Compute root of bintree for each color band
*/
if (wfa->wfainfo->color)
{
root_state [Y] = wfa->tree [wfa->tree [wfa->root_state][0]][0];
root_state [Cb] = wfa->tree [wfa->tree [wfa->root_state][0]][1];
root_state [Cr] = wfa->tree [wfa->tree [wfa->root_state][1]][0];
}
else
root_state [GRAY] = wfa->root_state;
/*
* Compute maximum level of a linear combination
*/
for (max_level = 0, state = wfa->basis_states; state < wfa->states; state++)
if (isedge (wfa->into [state][0][0]) || isedge (wfa->into [state][1][0]))
max_level = max (max_level, wfa->level_of_state [state]);
/*
* Allocate frame buffer for decoded image
*/
compute_actual_size (format == FORMAT_4_2_0 ? root_state [Y] : MAXSTATES,
&width, &height, wfa);
width = max (width, orig_width);
height = max (height, orig_height);
frame = alloc_image (width, height, wfa->wfainfo->color, format);
/*
* Allocate buffers for intermediate state images
*/
if (wfa->wfainfo->color)
{
wfa->level_of_state [wfa->root_state] = 128;
wfa->level_of_state [wfa->tree[wfa->root_state][0]] = 128;
wfa->level_of_state [wfa->tree[wfa->root_state][1]] = 128;
}
alloc_state_images (&images, &offsets, frame, root_state, 0, max_level,
format, wfa);
if (dec_timer)
dec_timer [0] += prg_timer (&ptimer, STOP);
/*
* Decode all state images, forming the complete image.
*/
prg_timer (&ptimer, START);
compute_state_images (max_level, images, offsets, wfa);
if (dec_timer)
dec_timer [1] += prg_timer (&ptimer, STOP);
/*
* Cleanup buffers used for intermediate state images
*/
prg_timer (&ptimer, START);
free_state_images (max_level, frame->color, images, offsets, root_state, 0,
format, wfa);
/*
* Crop decoded image if the image size differs.
*/
if (orig_width != width || orig_height != height)
{
frame->height = orig_height;
frame->width = orig_width;
if (orig_width != width)
{
color_e band; /* current color band */
word_t *src, *dst; /* source and destination pointers */
unsigned y; /* current row */
for (band = first_band (frame->color);
band <= last_band (frame->color); band++)
{
src = dst = frame->pixels [band];
for (y = orig_height; y; y--)
{
memmove (dst, src, orig_width * sizeof (word_t));
dst += orig_width;
src += width;
}
if (format == FORMAT_4_2_0 && band == Y)
{
orig_width >>= 1;
orig_height >>= 1;
width >>= 1;
}
}
void
write_weights (unsigned total, const wfa_t *wfa, bitfile_t *output)
/*
* Traverse the transition matrices of the 'wfa' and write #'total'
* weights != 0 to stream 'output'.
*
* No return value.
*/
{
unsigned state, label; /* current label */
unsigned offset1, offset2; /* model offsets. */
unsigned offset3, offset4; /* model offsets. */
unsigned *weights_array; /* array of weights to encode */
unsigned *wptr; /* pointer to current weight */
unsigned *level_array; /* array of corresponding levels */
unsigned *lptr; /* pointer to current corr. level */
int min_level, max_level; /* min and max range level */
int d_min_level, d_max_level; /* min and max delta range level */
bool_t dc, d_dc; /* true if dc or delta dc are used */
bool_t delta_approx = NO; /* true if delta has been used */
unsigned delta_count = 0; /* number of delta ranges */
unsigned bits = bits_processed (output);
/*
* Check whether delta approximation has been used
*/
for (state = wfa->basis_states; state < wfa->states; state++)
if (wfa->delta_state [state])
{
delta_approx = YES;
break;
}
/*
* Generate array of corresponding levels (context of probability model)
*/
min_level = d_min_level = MAXLEVEL;
max_level = d_max_level = 0;
dc = d_dc = NO;
for (state = wfa->basis_states; state < wfa->states; state++)
for (label = 0; label < MAXLABELS; label++)
if (isrange (wfa->tree [state][label]))
{
if (delta_approx && wfa->delta_state [state]) /* delta approx. */
{
d_min_level = min (d_min_level,
wfa->level_of_state [state] - 1);
d_max_level = max (d_max_level,
wfa->level_of_state [state] - 1);
if (wfa->into [state][label][0] == 0)
d_dc = YES;
}
else
{
min_level = min (min_level, wfa->level_of_state [state] - 1);
max_level = max (max_level, wfa->level_of_state [state] - 1);
if (wfa->into [state][label][0] == 0)
dc = YES;
}
}
if (min_level > max_level) /* no lc found */
max_level = min_level - 1;
if (d_min_level > d_max_level)
d_max_level = d_min_level - 1;
/*
* Context model:
* 0 DC weight
* 1 Delta DC weight
* 2-k normal weights per level
* k+1 - m Delta weights per level
*/
offset1 = dc ? 1 : 0;
offset2 = offset1 + (d_dc ? 1 : 0);
offset3 = offset2 + (max_level - min_level + 1);
offset4 = offset3 + (d_max_level - d_min_level + 1);
/*
* Weights are encoded as follows:
* all weights of state n
* sorted by label
* sorted by domain number
*/
wptr = weights_array = Calloc (total, sizeof (unsigned));
lptr = level_array = Calloc (total, sizeof (unsigned));
for (state = wfa->basis_states; state < wfa->states; state++)
for (label = 0; label < MAXLABELS; label++)
if (isrange (wfa->tree [state][label]))
{
int edge; /* current edge */
int domain; /* current domain (context of model) */
for (edge = 0; isedge (domain = wfa->into [state][label][edge]);
edge++)
{
if (wptr - weights_array >= (int) total)
error ("Can't write more than %d weights.", total);
if (domain) /* not DC component */
{
if (delta_approx && wfa->delta_state [state]) /* delta */
{
*wptr++ = rtob (wfa->weight [state][label][edge],
wfa->wfainfo->d_rpf);
*lptr++ = offset3
+ wfa->level_of_state [state] - 1 - d_min_level;
delta_count++;
}
else
{
*wptr++ = rtob (wfa->weight [state][label][edge],
wfa->wfainfo->rpf);
*lptr++ = offset2
+ wfa->level_of_state [state] - 1 - min_level;
}
}
else /* DC component */
{
if (delta_approx && wfa->delta_state [state]) /* delta */
{
*wptr++ = rtob (wfa->weight [state][label][edge],
wfa->wfainfo->d_dc_rpf);
*lptr++ = offset1;
}
else
{
*wptr++ = rtob (wfa->weight [state][label][edge],
wfa->wfainfo->dc_rpf);
*lptr++ = 0;
}
}
}
}
{
unsigned i;
unsigned *c_symbols = Calloc (offset4, sizeof (int));
const int scale = 500; /* scaling of probability model */
c_symbols [0] = 1 << (wfa->wfainfo->dc_rpf->mantissa_bits + 1);
if (offset1 != offset2)
c_symbols [offset1] = 1 << (wfa->wfainfo->d_dc_rpf->mantissa_bits
+ 1);
for (i = offset2; i < offset3; i++)
c_symbols [i] = 1 << (wfa->wfainfo->rpf->mantissa_bits + 1);
for (; i < offset4; i++)
c_symbols [i] = 1 << (wfa->wfainfo->d_rpf->mantissa_bits + 1);
encode_array (output, weights_array, level_array, c_symbols, offset4,
total, scale);
Free (c_symbols);
}
debug_message ("%d delta weights out of %d.", delta_count, total);
debug_message ("weights: %5d bits. (%5d symbols => %5.2f bps)",
bits_processed (output) - bits, total,
(bits_processed (output) - bits) / (double) total);
Free (weights_array);
Free (level_array);
}
void
compute_ip_images_state (unsigned image, unsigned address, unsigned level,
unsigned n, unsigned from,
const wfa_t *wfa, coding_t *c)
/*
* Compute the inner products between all states
* 'from', ... , 'wfa->max_states' and the range images 'image'
* (and childs) up to given level.
*
* No return value.
*
* Side effects:
* inner product tables 'c->ip_images_states' are updated
*/
{
if (level > c->options.images_level)
{
unsigned state, label;
if (level > c->options.images_level + 1) /* recursive computation */
compute_ip_images_state (MAXLABELS * image + 1, address * MAXLABELS,
level - 1, MAXLABELS * n, from, wfa, c);
/*
* Compute inner product <f, Phi_i>
*/
for (label = 0; label < MAXLABELS; label++)
for (state = from; state < wfa->states; state++)
if (need_image (state, wfa))
{
unsigned edge, count;
int domain;
real_t *dst, *src;
if (ischild (domain = wfa->tree [state][label]))
{
if (level > c->options.images_level + 1)
{
dst = c->ip_images_state [state] + image;
src = c->ip_images_state [domain]
+ image * MAXLABELS + label + 1;
for (count = n; count; count--, src += MAXLABELS)
*dst++ += *src;
}
else
{
unsigned newadr = address * MAXLABELS + label;
dst = c->ip_images_state [state] + image;
for (count = n; count; count--, newadr += MAXLABELS)
*dst++ += standard_ip_image_state (newadr, level - 1,
domain, c);
}
}
for (edge = 0; isedge (domain = wfa->into [state][label][edge]);
edge++)
{
real_t weight = wfa->weight [state][label][edge];
if (level > c->options.images_level + 1)
{
dst = c->ip_images_state [state] + image;
src = c->ip_images_state [domain]
+ image * MAXLABELS + label + 1;
for (count = n; count; count--, src += MAXLABELS)
*dst++ += *src * weight;
}
else
{
unsigned newadr = address * MAXLABELS + label;
dst = c->ip_images_state [state] + image;
for (count = n; count; count--, newadr += MAXLABELS)
*dst++ += weight *
standard_ip_image_state (newadr, level - 1,
domain, c);
}
}
}
}
}
void
compute_ip_states_state (unsigned from, unsigned to,
const wfa_t *wfa, coding_t *c)
/*
* Computes the inner products between the current state 'state1' and the
* old states 0,...,'state1'-1
*
* No return value.
*
* Side effects:
* inner product tables 'c->ip_states_state' are computed.
*/
{
unsigned level;
unsigned state1, state2;
/*
* Compute inner product <Phi_state1, Phi_state2>
*/
for (level = c->options.images_level + 1;
level <= c->options.lc_max_level; level++)
for (state1 = from; state1 <= to; state1++)
for (state2 = 0; state2 <= state1; state2++)
if (need_image (state2, wfa))
{
unsigned label;
real_t ip = 0;
for (label = 0; label < MAXLABELS; label++)
{
int domain1, domain2;
unsigned edge1, edge2;
real_t sum, weight2;
if (ischild (domain1 = wfa->tree [state1][label]))
{
sum = 0;
if (ischild (domain2 = wfa->tree [state2][label]))
sum = get_ip_state_state (domain1, domain2,
level - 1, c);
for (edge2 = 0;
isedge (domain2 = wfa->into [state2][label][edge2]);
edge2++)
{
weight2 = wfa->weight [state2][label][edge2];
sum += weight2 * get_ip_state_state (domain1, domain2,
level - 1, c);
}
ip += sum;
}
for (edge1 = 0;
isedge (domain1 = wfa->into [state1][label][edge1]);
edge1++)
{
real_t weight1 = wfa->weight [state1][label][edge1];
sum = 0;
if (ischild (domain2 = wfa->tree [state2][label]))
sum = get_ip_state_state (domain1, domain2,
level - 1, c);
for (edge2 = 0;
isedge (domain2 = wfa->into [state2][label][edge2]);
edge2++)
{
weight2 = wfa->weight [state2][label][edge2];
sum += weight2 * get_ip_state_state (domain1, domain2,
level - 1, c);
}
ip += weight1 * sum;
}
}
c->ip_states_state [state1][level][state2] = ip;
}
}
static real_t
nd_prediction (real_t max_costs, real_t price, unsigned band, int y_state,
range_t *range, wfa_t *wfa, coding_t *c)
{
real_t costs; /* current approximation costs */
range_t lrange = *range;
/*
* Predict 'range' with DC component approximation
*/
{
real_t x = get_ip_image_state (range->image, range->address,
range->level, 0, c);
real_t y = get_ip_state_state (0, 0, range->level, c);
real_t w = btor (rtob (x / y, c->coeff->dc_rpf), c->coeff->dc_rpf);
word_t s [2] = {0, -1};
lrange.into [0] = 0;
lrange.into [1] = NO_EDGE;
lrange.weight [0] = w;
lrange.mv_coord_bits = 0;
lrange.mv_tree_bits = 0;
lrange.nd_tree_bits = tree_bits (LEAF, lrange.level, &c->p_tree);
lrange.nd_weights_bits = 0;
lrange.tree_bits = 0;
lrange.matrix_bits = 0;
lrange.weights_bits = c->coeff->bits (&w, s, range->level, c->coeff);
}
costs = price * (lrange.weights_bits + lrange.nd_tree_bits);
/*
* Recursive aproximation of difference image
*/
if (costs < max_costs)
{
unsigned state;
range_t rrange; /* range: recursive subdivision */
unsigned last_state; /* last WFA state before recursion */
real_t *ipi [MAXSTATES]; /* inner products pointers */
unsigned width = width_of_level (range->level);
unsigned height = height_of_level (range->level);
real_t *pixels;
/*
* Generate difference image original - approximation
*/
{
unsigned n;
real_t *src, *dst; /* pointers to image data */
real_t w = - lrange.weight [0] * c->images_of_state [0][0];
src = c->pixels + range->address * size_of_level (range->level);
dst = c->pixels = pixels = Calloc (width * height, sizeof (real_t));
for (n = width * height; n; n--)
*dst++ = *src++ + w;
}
/*
* Approximate difference recursively.
*/
rrange = *range;
rrange.tree_bits = 0;
rrange.matrix_bits = 0;
rrange.weights_bits = 0;
rrange.mv_coord_bits = 0;
rrange.mv_tree_bits = 0;
rrange.nd_tree_bits = 0;
rrange.nd_weights_bits = 0;
rrange.image = 0;
rrange.address = 0;
last_state = wfa->states - 1;
for (state = 0; state <= last_state; state++)
if (need_image (state, wfa))
{
ipi [state] = c->ip_images_state[state];
c->ip_images_state[state]
= Calloc (size_of_tree (c->products_level), sizeof (real_t));
}
compute_ip_images_state (rrange.image, rrange.address, rrange.level,
1, 0, wfa, c);
costs += subdivide (max_costs - costs, band, y_state, &rrange, wfa, c,
NO, YES);
Free (pixels);
if (costs < max_costs && ischild (rrange.tree)) /* use prediction */
{
unsigned img, adr;
unsigned edge;
img = range->image;
adr = range->address;
*range = rrange;
range->image = img;
range->address = adr;
range->nd_tree_bits += lrange.nd_tree_bits;
range->nd_weights_bits += lrange.weights_bits;
for (edge = 0; isedge (lrange.into [edge]); edge++)
{
range->into [edge] = lrange.into [edge];
range->weight [edge] = lrange.weight [edge];
}
range->into [edge] = NO_EDGE;
range->prediction = edge;
for (state = last_state + 1; state < wfa->states; state++)
if (need_image (state, wfa))
memset (c->ip_images_state [state], 0,
size_of_tree (c->products_level) * sizeof (real_t));
}
else
costs = MAXCOSTS;
for (state = 0; state <= last_state; state++)
if (need_image (state, wfa))
{
Free (c->ip_images_state [state]);
c->ip_images_state [state] = ipi [state];
}
}
else
costs = MAXCOSTS;
return costs;
}
void
read_weights (unsigned total, wfa_t *wfa, bitfile_t *input)
/*
* Read #'total' weights from input stream 'input' and
* update transitions of the WFA states with corresponding weights.
*
* No return value.
*
* Side effects:
* 'wfa->weights' are filled with the decoded values
*/
{
unsigned state;
unsigned label;
unsigned edge; /* current edge */
unsigned *weights_array; /* array of weights to encode */
unsigned *level_array; /* array of corresponding levels */
unsigned offset1, offset2; /* prob. model offsets. */
unsigned offset3, offset4; /* prob. model offsets. */
bool_t delta_approx = NO; /* true if delta has been used */
/*
* Check whether delta approximation has been used
*/
for (state = wfa->basis_states; state < wfa->states; state++)
if (wfa->delta_state [state])
{
delta_approx = YES;
break;
}
/*
* Generate array of corresponding levels (context of probability model)
*/
{
int min_level, max_level; /* min and max range level */
int d_min_level, d_max_level; /* min and max range level (delta) */
unsigned *lptr; /* pointer to current corresp. level */
int domain; /* current domain */
bool_t dc, d_dc; /* indicates whether DC is used */
/*
* Compute minimum and maximum level of delta and normal approximations
*/
min_level = d_min_level = MAXLEVEL;
max_level = d_max_level = 0;
dc = d_dc = NO;
for (state = wfa->basis_states; state < wfa->states; state++)
for (label = 0; label < MAXLABELS; label++)
if (isrange (wfa->tree [state][label]))
{
if (delta_approx && wfa->delta_state [state])
{
d_min_level = min (d_min_level,
wfa->level_of_state [state] - 1);
d_max_level = max (d_max_level,
wfa->level_of_state [state] - 1);
if (wfa->into [state][label][0] == 0)
d_dc = YES;
}
else
{
min_level = min (min_level, wfa->level_of_state [state] - 1);
max_level = max (max_level, wfa->level_of_state [state] - 1);
if (wfa->into [state][label][0] == 0)
dc = YES;
}
}
if (min_level > max_level) /* no lc found */
max_level = min_level - 1;
if (d_min_level > d_max_level)
d_max_level = d_min_level - 1;
offset1 = dc ? 1 : 0;
offset2 = offset1 + (d_dc ? 1 : 0);
offset3 = offset2 + (max_level - min_level + 1);
offset4 = offset3 + (d_max_level - d_min_level + 1);
lptr = level_array = Calloc (total, sizeof (int));
for (state = wfa->basis_states; state < wfa->states; state++)
for (label = 0; label < MAXLABELS; label++)
if (isrange (wfa->tree[state][label]))
for (edge = 0; isedge (domain = wfa->into[state][label][edge]);
edge++)
{
if ((unsigned) (lptr - level_array) >= total)
error ("Can't read more than %d weights.", total);
if (domain)
{
if (delta_approx && wfa->delta_state [state])
*lptr++ = offset3 + wfa->level_of_state [state]
- 1 - d_min_level;
else
*lptr++ = offset2 + wfa->level_of_state [state]
- 1 - min_level;
}
else
*lptr++ = delta_approx && wfa->delta_state [state]
? offset1 : 0;
}
}
/*
* Decode the list of weights with an arithmetic decoder
*/
{
unsigned i;
unsigned *c_symbols = Calloc (offset4, sizeof (unsigned));
const unsigned scale = 500; /* scaling of probability model */
c_symbols [0] = 1 << (wfa->wfainfo->dc_rpf->mantissa_bits + 1);
if (offset1 != offset2)
c_symbols [offset1] = 1 << (wfa->wfainfo->d_dc_rpf->mantissa_bits
+ 1);
for (i = offset2; i < offset3; i++)
c_symbols [i] = 1 << (wfa->wfainfo->rpf->mantissa_bits + 1);
for (; i < offset4; i++)
c_symbols [i] = 1 << (wfa->wfainfo->d_rpf->mantissa_bits + 1);
weights_array = decode_array (input, level_array, c_symbols,
offset4, total, scale);
Free (c_symbols);
}
Free (level_array);
/*
* Update transitions with decoded weights
*/
{
unsigned *wptr = weights_array; /* pointer to current weight */
int domain; /* current domain */
for (state = wfa->basis_states; state < wfa->states; state++)
for (label = 0; label < MAXLABELS; label++)
if (isrange (wfa->tree[state][label]))
for (edge = 0; isedge (domain = wfa->into[state][label][edge]);
edge++)
{
if (domain) /* not DC component */
{
if (delta_approx && wfa->delta_state [state])
wfa->weight [state][label][edge]
= btor (*wptr++, wfa->wfainfo->d_rpf);
else
wfa->weight [state][label][edge]
= btor (*wptr++, wfa->wfainfo->rpf);
}
else
{
if (delta_approx && wfa->delta_state [state])
wfa->weight [state][label][edge]
= btor (*wptr++, wfa->wfainfo->d_dc_rpf);
else
wfa->weight [state][label][edge]
= btor (*wptr++, wfa->wfainfo->dc_rpf);
}
wfa->int_weight [state][label][edge]
= wfa->weight [state][label][edge] * 512 + 0.5;
}
}
Free (weights_array);
}
