/***********************************************************************//**
* @brief Evaluate PSF for a specific set of parameters
*
* @param[in] offset Offset angle (radians).
* @param[in] energy Energy (MeV).
* @param[in] index Parameter array index.
*
* Evaluates PSF as function of offset angle and energy for a specific set
* of PSF parameters. The parameter set that is used is specified by the
* index parameter. The energy parameter only serves to scale the score and
* stail parameters of the PSF.
***************************************************************************/
double GLATPsfV3::eval_psf(const double& offset, const double& energy,
const int& index)
{
// Get energy scaling
double scale = scale_factor(energy);
// Get parameters
double ncore(m_ncore[index]);
double ntail(m_ntail[index]);
double score(m_score[index] * scale);
double stail(m_stail[index] * scale);
double gcore(m_gcore[index]);
double gtail(m_gtail[index]);
// Compute argument
double rc = offset / score;
double uc = 0.5 * rc * rc;
double rt = offset / stail;
double ut = 0.5 * rt * rt;
// Evaluate PSF
double psf = ncore * (base_fct(uc, gcore) + ntail * base_fct(ut, gtail));
// Return PSF
return psf;
}
void TagViewer::mouseReleaseEvent(
QMouseEvent* e
)
{
if( !tagging_ || e->button() != Qt::LeftButton ) {
return;
}
tag_end_ = e->pos();
enforce_boundary_conditions( tag_end_ );
float scale_f = scale_factor();
// make a valid rectangle
QRect tag( tag_start_ / scale_f, tag_end_ / scale_f );
int left = tag.left();
int top = tag.top();
if( left > tag.right() ) {
tag.setLeft( tag.right() );
tag.setRight( left );
}
if( top > tag.bottom() ) {
tag.setTop( tag.bottom() );
tag.setBottom( top );
}
emit( tagged( tag ) );
tag_start_ = QPoint( 0, 0 );
tag_end_ = QPoint( 0, 0 );
}
static gboolean
parse_absolute_size (OpenTag *tag,
const char *size)
{
SizeLevel level = Medium;
double factor;
if (strcmp (size, "xx-small") == 0)
level = XXSmall;
else if (strcmp (size, "x-small") == 0)
level = XSmall;
else if (strcmp (size, "small") == 0)
level = Small;
else if (strcmp (size, "medium") == 0)
level = Medium;
else if (strcmp (size, "large") == 0)
level = Large;
else if (strcmp (size, "x-large") == 0)
level = XLarge;
else if (strcmp (size, "xx-large") == 0)
level = XXLarge;
else
return FALSE;
/* This is "absolute" in that it's relative to the base font,
* but not to sizes created by any other tags
*/
factor = scale_factor (level, 1.0);
add_attribute (tag, pango_attr_scale_new (factor));
if (tag)
open_tag_set_absolute_font_scale (tag, factor);
return TRUE;
}
static void set_intercept_vec_w(struct mvar_model *model, gsl_matrix *aug_A, gsl_vector *scale)
{
gsl_vector_view vec_view = gsl_matrix_column(aug_A, 0);
gsl_vector_memcpy(model->w, &vec_view.vector);
gsl_vector_scale(model->w, scale_factor(scale));
}
void lightcone_set_scale(float *pos) {
int64_t i;
float ds=0, dx=0, z;
for (i=0; i<3; i++) { ds = pos[i]-LIGHTCONE_ORIGIN[i]; dx+=ds*ds; }
z = comoving_distance_h_to_redshift(sqrt(dx));
SCALE_NOW = scale_factor(z);
calc_mass_definition();
}
/***********************************************************************//**
* @brief Integrates PSF for a specific set of parameters
*
* @param[in] energy Energy (MeV).
* @param[in] index Parameter array index.
*
* Integrates PSF for a specific set of parameters.
*
* Compile option G_APPROXIMATE_PSF_INTEGRAL:
* If defined, a numerical PSF integral is only performed for energies
* < 120 MeV, while for larger energies the small angle approximation is
* used. In not defined, a numerical PSF integral is performed for all
* energies.
* This option is kept for comparison with the Fermi/LAT ScienceTools who
* select the integration method based on the true photon energy. As the
* normalization is only performed once upon loading of the PSF, CPU time
* is not really an issue here, and we can afford the more precise numerical
* integration. Note that the uncertainties of the approximation at energies
* near to 120 MeV reaches 0.1%.
*
* @todo Implement gcore and gtail checking
***************************************************************************/
double GLATPsfV3::integrate_psf(const double& energy, const int& index)
{
// Initialise integral
double psf = 0.0;
// Get energy scaling
double scale = scale_factor(energy);
// Get parameters
double ncore(m_ncore[index]);
double ntail(m_ntail[index]);
double score(m_score[index] * scale);
double stail(m_stail[index] * scale);
double gcore(m_gcore[index]);
double gtail(m_gtail[index]);
// Make sure that gcore and gtail are not negative
//if (gcore < 0 || gtail < 0) {
//}
// Do we need an exact integral?
#if defined(G_APPROXIMATE_PSF_INTEGRAL)
if (energy < 120) {
#endif
// Allocate integrand
GLATPsfV3::base_integrand integrand(ncore, ntail, score, stail, gcore, gtail);
// Allocate integral
GIntegral integral(&integrand);
// Integrate radially from 0 to 90 degrees
psf = integral.romb(0.0, pihalf) * twopi;
#if defined(G_APPROXIMATE_PSF_INTEGRAL)
} // endif: exact integral was performed
// No, so we use the small angle approximation
else {
// Compute arguments
double rc = pihalf / score;
double uc = 0.5 * rc * rc;
double sc = twopi * score * score;
double rt = pihalf / stail;
double ut = 0.5 * rt * rt;
double st = twopi * stail * stail;
// Evaluate PSF integral (from 0 to 90 degrees)
psf = ncore * (base_int(uc, gcore) * sc +
base_int(ut, gtail) * st * ntail);
}
#endif
// Return PSF integral
return psf;
}
void TagViewer::paintEvent(
QPaintEvent* /*e*/
)
{
QPainter p( this );
float scale_f = scale_factor();
QRect drawing_area( 0, 0, size().width(), size().height() );
if( !pix_.isNull() && !size().isNull() ) {
p.drawPixmap( drawing_area, pix_ );
} else {
QTextOption options( Qt::AlignLeft );
options.setWrapMode( QTextOption::WordWrap );
p.setPen( QPen( Qt::red, 4 ) );
p.drawText(
QRectF( drawing_area ),
"Image cannot be displayed. Check:\n"
" - the same image is selected among the multiple selection (it's ok to select labels)\n"
" - the image file is still at the same disk location when imported\n"
" - the image format is valid and/or the file is not corrupted ",
options
);
return;
}
QFont font;
font.setPointSize( 10 );
p.setFont( font );
// draw bounding boxes
for( QList<TagDisplayElement>::iterator tag_itr = elts_.begin(); tag_itr != elts_.end(); ++tag_itr ) {
const TagDisplayElement& tag = *tag_itr;
const QList<QRect>& bbox = tag._bbox;
p.setPen( QPen( tag._color, 2 ) );
for( QList<QRect>::const_iterator bbox_itr = bbox.begin(); bbox_itr != bbox.end(); ++bbox_itr ) {
const QRect& box_rect = *bbox_itr;
QRect scaled_box( scale_f * box_rect.topLeft(), scale_f * box_rect.bottomRight() );
p.drawRect( scaled_box );
p.drawText( scaled_box.x(), scaled_box.y(), tag._label );
}
}
// draw current box being tagged
p.setPen( QPen( current_color_, 2 ) );
if( tagging_ && tag_start_ != tag_end_ ) {
QRect current_rect( tag_start_, tag_end_ );
p.drawRect( current_rect );
p.drawText( current_rect.x(), current_rect.y(), current_label_ );
}
}
/***********************************************************************//**
* @brief Normalize PSF for all parameters
*
* Makes sure that PSF is normalized for all parameters. We assure this by
* looping over all parameter nodes, integrating the PSF for each set of
* parameters, and dividing the NCORE parameter by the integral.
*
* Compile option G_CHECK_PSF_NORM:
* If defined, checks that the PSF is normalized correctly.
***************************************************************************/
void GLATPsfV3::normalize_psf(void)
{
// Loop over all energy bins
for (int ie = 0; ie < m_rpsf_bins.nenergies(); ++ie) {
// Extract energy value (in MeV)
double energy = m_rpsf_bins.energy(ie);
// Loop over all cos(theta) bins
for (int ic = 0; ic < m_rpsf_bins.ncostheta(); ++ic) {
// Get parameter index
int index = m_rpsf_bins.index(ie, ic);
// Integrate PSF
double norm = integrate_psf(energy, index);
// Normalize PSF
m_ncore[index] /= norm;
// Compile option: check PSF normalization
#if defined(G_CHECK_PSF_NORM)
double scale = scale_factor(energy);
double ncore(m_ncore[index]);
double ntail(m_ntail[index]);
double score(m_score[index] * scale);
double stail(m_stail[index] * scale);
double gcore(m_gcore[index]);
double gtail(m_gtail[index]);
GLATPsfV3::base_integrand integrand(ncore, ntail, score, stail, gcore, gtail);
GIntegral integral(&integrand);
double sum = integral.romb(0.0, pihalf) * twopi;
std::cout << "Energy=" << energy;
std::cout << " cos(theta)=" << m_rpsf_bins.costheta_lo(ic);
std::cout << " error=" << sum-1.0 << std::endl;
#endif
} // endfor: looped over cos(theta)
} // endfor: looped over energies
// Return
return;
}
void TagViewer::mousePressEvent(
QMouseEvent* e
)
{
if( e->button() != Qt::LeftButton ) {
return;
}
if( tagging_ ) {
tag_start_ = e->pos();
enforce_boundary_conditions( tag_start_ );
tag_end_ = tag_start_;
} else if( untagging_ ) {
// searches the closest rectangle to the picked point
// removes it only if point is deemed close enough
// there won't be tons of label per image, so a brute force search
// is perfectly acceptable, no need to go into quad-tree
float scale_f = scale_factor();
QRect rect_found;
QString label_found;
int distance_min = 200. / scale_f;
QPoint p = e->pos();
enforce_boundary_conditions( p );
p /= scale_f;
for( QList<TagDisplayElement>::iterator tag_itr = elts_.begin(); tag_itr != elts_.end(); ++tag_itr ) {
const TagDisplayElement& tag = *tag_itr;
const QList<QRect>& bbox = tag._bbox;
for( QList<QRect>::const_iterator bbox_itr = bbox.begin(); bbox_itr != bbox.end(); ++bbox_itr ) {
int d = shortest_distance( p, *bbox_itr );
if( d < distance_min ) {
distance_min = d;
label_found = tag._label;
rect_found = *bbox_itr;
}
}
}
if( !label_found.isEmpty() && rect_found.isValid() ) {
emit( untagged( label_found, rect_found ) );
}
}
}
void QuadDice::dice(SubPatch& sub, EdgeFactors& ef)
{
/* compute inner grid size with scale factor */
int Mu = max(ef.tu0, ef.tu1);
int Mv = max(ef.tv0, ef.tv1);
float S = scale_factor(sub, ef, Mu, Mv);
Mu = max((int)ceil(S*Mu), 2); // XXX handle 0 & 1?
Mv = max((int)ceil(S*Mv), 2); // XXX handle 0 & 1?
/* reserve space for new verts */
int offset = mesh->verts.size();
reserve(ef, Mu, Mv);
/* corners and inner grid */
add_corners(sub);
add_grid(sub, Mu, Mv, offset);
/* bottom side */
vector<int> outer, inner;
add_side_u(sub, outer, inner, Mu, Mv, ef.tu0, 0, offset);
stitch_triangles(outer, inner);
/* top side */
add_side_u(sub, outer, inner, Mu, Mv, ef.tu1, 1, offset);
stitch_triangles(inner, outer);
/* left side */
add_side_v(sub, outer, inner, Mu, Mv, ef.tv0, 0, offset);
stitch_triangles(inner, outer);
/* right side */
add_side_v(sub, outer, inner, Mu, Mv, ef.tv1, 1, offset);
stitch_triangles(outer, inner);
assert(vert_offset == mesh->verts.size());
}
static void
markup_data_close_tag (MarkupData *md)
{
OpenTag *ot;
GSList *tmp_list;
if (md->attr_list == NULL)
return;
/* pop the stack */
ot = md->tag_stack->data;
md->tag_stack = g_slist_delete_link (md->tag_stack,
md->tag_stack);
/* Adjust end indexes, and push each attr onto the front of the
* to_apply list. This means that outermost tags are on the front of
* that list; if we apply the list in order, then the innermost
* tags will "win" which is correct.
*/
tmp_list = ot->attrs;
while (tmp_list != NULL)
{
PangoAttribute *a = tmp_list->data;
a->start_index = ot->start_index;
a->end_index = md->index;
md->to_apply = g_slist_prepend (md->to_apply, a);
tmp_list = g_slist_next (tmp_list);
}
if (ot->scale_level_delta != 0)
{
/* We affected relative font size; create an appropriate
* attribute and reverse our effects on the current level
*/
PangoAttribute *a;
if (ot->has_base_font_size)
{
/* Create a font using the absolute point size
* as the base size to be scaled from
*/
a = pango_attr_size_new (scale_factor (ot->scale_level,
1.0) *
ot->base_font_size);
}
else
{
/* Create a font using the current scale factor
* as the base size to be scaled from
*/
a = pango_attr_scale_new (scale_factor (ot->scale_level,
ot->base_scale_factor));
}
a->start_index = ot->start_index;
a->end_index = md->index;
md->to_apply = g_slist_prepend (md->to_apply, a);
}
g_slist_free (ot->attrs);
g_slice_free (OpenTag, ot);
}
void read_particles(char *filename) {
int64_t i, j, gadget = 0, gadget_internal = 0;
int64_t p_start = num_p;
float dx, ds, z, a, vel_mul;
double *origin, origin_offset[3] = {0};
if (!strcasecmp(FILE_FORMAT, "ASCII")) load_particles(filename, &p, &num_p);
else if (!strncasecmp(FILE_FORMAT, "GADGET", 6)) {
if (!strcasecmp(FILE_FORMAT, "GADGET_INTERNAL") ||
!strcasecmp(FILE_FORMAT, "GADGET2_INTERNAL")) gadget_internal = 1;
load_particles_gadget2(filename, &p, &num_p);
gadget = 1;
}
else if (!strncasecmp(FILE_FORMAT, "ART", 3))
load_particles_art(filename, &p, &num_p);
else if (!strncasecmp(FILE_FORMAT, "INTERNAL", 8)) {
load_particles_internal(filename, &p, &num_p);
}
else if (!strncasecmp(FILE_FORMAT, "GENERIC", 7)) {
assert(load_particles_generic != NULL);
load_particles_generic(filename, &p, &num_p);
}
else if (!strncasecmp(FILE_FORMAT, "TIPSY", 5)) {
load_particles_internal(filename, &p, &num_p);
}
else {
fprintf(stderr, "[Error] Unknown filetype %s!\n", FILE_FORMAT);
exit(1);
}
if (LIMIT_RADIUS) {
for (i=p_start; i<num_p; i++) {
for (j=0, ds=0; j<3; j++) { dx = p[i].pos[j]-LIMIT_CENTER[j]; ds+=dx*dx; }
if (ds > LIMIT_RADIUS*LIMIT_RADIUS) {
num_p--;
p[i] = p[num_p];
i--;
}
}
}
if (LIGHTCONE) {
init_cosmology();
if (strlen(LIGHTCONE_ALT_SNAPS)) {
for (i=0; i<3; i++)
if (LIGHTCONE_ORIGIN[i] || LIGHTCONE_ALT_ORIGIN[i]) break;
if (i<3) { //Same box coordinates, different intended locations
if (LIGHTCONE == 1) {
for (i=0; i<3; i++) origin_offset[i] = LIGHTCONE_ORIGIN[i] -
LIGHTCONE_ALT_ORIGIN[i];
}
} else { //Offset everything
for (i=0; i<3; i++) origin_offset[i] = -BOX_SIZE;
}
BOX_SIZE *= 2.0;
}
origin = (LIGHTCONE == 2) ? LIGHTCONE_ALT_ORIGIN : LIGHTCONE_ORIGIN;
for (i=p_start; i<num_p; i++) {
if (LIGHTCONE == 2) p[i].id = -p[i].id; //Make ids different
for (j=0,dx=0; j<3; j++) {
ds = p[i].pos[j] - origin[j];
dx += ds*ds;
p[i].pos[j] -= origin_offset[j];
}
if (!gadget) continue;
dx = sqrt(dx);
z = comoving_distance_h_to_redshift(dx);
a = scale_factor(z);
vel_mul = (gadget_internal) ? (1.0/a) : sqrt(a);
for (j=0; j<3; j++) p[i].pos[j+3] *= vel_mul;
}
}
output_config(NULL);
}
void
pcl::Permutohedral::init (const std::vector<float> &feature, const int feature_dimension, const int N)
{
N_ = N;
d_ = feature_dimension;
// Create hash table
std::vector<std::vector<short> > keys;
keys.reserve ((d_+1) * N_);
std::multimap<size_t, int> hash_table;
// reserve class memory
if (offset_.size () > 0)
offset_.clear ();
offset_.resize ((d_ + 1) * N_);
if (barycentric_.size () > 0)
barycentric_.clear ();
barycentric_.resize ((d_ + 1) * N_);
// create vectors and matrices
Eigen::VectorXf scale_factor = Eigen::VectorXf::Zero (d_);
Eigen::VectorXf elevated = Eigen::VectorXf::Zero (d_ + 1);
Eigen::VectorXf rem0 = Eigen::VectorXf::Zero (d_+1);
Eigen::VectorXf barycentric = Eigen::VectorXf::Zero (d_+2);
Eigen::VectorXi rank = Eigen::VectorXi::Zero (d_+1);
Eigen::Matrix<int, Eigen::Dynamic, Eigen::Dynamic> canonical;
canonical = Eigen::Matrix<int, Eigen::Dynamic, Eigen::Dynamic>::Zero (d_+1, d_+1);
//short * key = new short[d_+1];
std::vector<short> key (d_+1);
// Compute the canonical simple
for (int i = 0; i <= d_; i++)
{
for (int j = 0; j <= (d_ - i); j++)
canonical (j, i) = i;
for (int j = (d_ - i + 1); j <= d_; j++)
canonical (j, i) = i - (d_ + 1);
}
// Expected standard deviation of our filter (p.6 in [Adams etal 2010])
float inv_std_dev = std::sqrt (2.0f / 3.0f) * static_cast<float> (d_ + 1);
// Compute the diagonal part of E (p.5 in [Adams etal 2010])
for (int i = 0; i < d_; i++)
scale_factor (i) = 1.0f / std::sqrt (static_cast<float> (i + 2) * static_cast<float> (i + 1)) * inv_std_dev;
// Compute the simplex each feature lies in
for (int k = 0; k < N_; k++)
//for (int k = 0; k < 5; k++)
{
// Elevate the feature (y = Ep, see p.5 in [Adams etal 2010])
int index = k * feature_dimension;
// sm contains the sum of 1..n of our faeture vector
float sm = 0;
for (int j = d_; j > 0; j--)
{
float cf = feature[index + j-1] * scale_factor (j-1);
elevated (j) = sm - static_cast<float> (j) * cf;
sm += cf;
}
elevated (0) = sm;
// Find the closest 0-colored simplex through rounding
float down_factor = 1.0f / static_cast<float>(d_+1);
float up_factor = static_cast<float>(d_+1);
int sum = 0;
for (int j = 0; j <= d_; j++){
float rd = floorf (0.5f + (down_factor * elevated (j))) ;
rem0 (j) = rd * up_factor;
sum += static_cast<int> (rd);
}
// rank differential to find the permutation between this simplex and the canonical one.
// (See pg. 3-4 in paper.)
rank.setZero ();
Eigen::VectorXf tmp = elevated - rem0;
for (int i = 0; i < d_; i++){
for (int j = i+1; j <= d_; j++)
if (tmp (i) < tmp (j))
rank (i)++;
else
rank (j)++;
}
// If the point doesn't lie on the plane (sum != 0) bring it back
for (int j = 0; j <= d_; j++){
rank (j) += sum;
if (rank (j) < 0){
rank (j) += d_+1;
rem0 (j) += static_cast<float> (d_ + 1);
}
else if (rank (j) > d_){
rank (j) -= d_+1;
rem0 (j) -= static_cast<float> (d_ + 1);
}
}
// Compute the barycentric coordinates (p.10 in [Adams etal 2010])
barycentric.setZero ();
Eigen::VectorXf v = (elevated - rem0) * down_factor;
for (int j = 0; j <= d_; j++){
barycentric (d_ - rank (j) ) += v (j);
barycentric (d_ + 1 - rank (j)) -= v (j);
}
// Wrap around
barycentric (0) += 1.0f + barycentric (d_+1);
// Compute all vertices and their offset
for (int remainder = 0; remainder <= d_; remainder++)
{
for (int j = 0; j < d_; j++)
key[j] = static_cast<short> (rem0 (j) + static_cast<float> (canonical ( rank (j), remainder)));
// insert key in hash table
size_t hash_key = generateHashKey (key);
auto it = hash_table.find (hash_key);
int key_index = -1;
if (it != hash_table.end ())
{
key_index = it->second;
// check if key is the right one
int tmp_key_index = -1;
//for (int ii = key_index; ii < keys.size (); ii++)
for (; it != hash_table.end (); ++it)
{
int ii = it->second;
bool same = true;
std::vector<short> k = keys[ii];
for (size_t i_k = 0; i_k < k.size (); i_k++)
{
if (key[i_k] != k[i_k])
{
same = false;
break;
}
}
if (same)
{
tmp_key_index = ii;
break;
}
}
if (tmp_key_index == -1)
{
key_index = static_cast<int> (keys.size ());
keys.push_back (key);
hash_table.insert (std::pair<size_t, int> (hash_key, key_index));
}
else
key_index = tmp_key_index;
}
else
{
key_index = static_cast<int> (keys.size ());
keys.push_back (key);
hash_table.insert (std::pair<size_t, int> (hash_key, key_index));
}
offset_[ k * (d_ + 1) + remainder ] = static_cast<float> (key_index);
barycentric_[ k * (d_ + 1) + remainder ] = barycentric (remainder);
}
}
// Find the Neighbors of each lattice point
// Get the number of vertices in the lattice
M_ = static_cast<int> (hash_table.size());
// Create the neighborhood structure
if (blur_neighbors_.size () > 0)
blur_neighbors_.clear ();
blur_neighbors_.resize ((d_+1)*M_);
std::vector<short> n1 (d_+1);
std::vector<short> n2 (d_+1);
// For each of d+1 axes,
for (int j = 0; j <= d_; j++)
{
for (int i = 0; i < M_; i++)
{
std::vector<short> key = keys[i];
for (int k=0; k<d_; k++){
n1[k] = static_cast<short> (key[k] - 1);
n2[k] = static_cast<short> (key[k] + 1);
}
n1[j] = static_cast<short> (key[j] + d_);
n2[j] = static_cast<short> (key[j] - d_);
std::multimap<size_t ,int>::iterator it;
size_t hash_key;
int key_index = -1;
hash_key = generateHashKey (n1);
it = hash_table.find (hash_key);
if (it != hash_table.end ())
key_index = it->second;
blur_neighbors_[j*M_+i].n1 = key_index;
key_index = -1;
hash_key = generateHashKey (n2);
it = hash_table.find (hash_key);
if (it != hash_table.end ())
key_index = it->second;
blur_neighbors_[j*M_+i].n2 = key_index;
}
}
}
// Compute the gradient of a^T K b
void Permutohedral::gradient ( float* df, const float * a, const float* b, int value_size ) const
{
// Shift all values by 1 such that -1 -> 0 (used for blurring)
float * values = new float[ (M_+2)*value_size ];
float * new_values = new float[ (M_+2)*value_size ];
// Set the results to 0
std::fill( df, df+N_*d_, 0.f );
// Initialize some constants
std::vector<float> scale_factor( d_ );
float inv_std_dev = sqrt(2.0 / 3.0)*(d_+1);
for( int i=0; i<d_; i++ )
scale_factor[i] = 1.0 / sqrt( double((i+2)*(i+1)) ) * inv_std_dev;
// Alpha is a magic scaling constant multiplied by down_factor
float alpha = 1.0f / (1+powf(2, -d_)) / (d_+1);
for( int dir=0; dir<2; dir++ ) {
for( int i=0; i<(M_+2)*value_size; i++ )
values[i] = new_values[i] = 0;
// Splatting
for( int i=0; i<N_; i++ ){
for( int j=0; j<=d_; j++ ){
int o = offset_[i*(d_+1)+j]+1;
float w = barycentric_[i*(d_+1)+j];
for( int k=0; k<value_size; k++ )
values[ o*value_size+k ] += w * (dir?b:a)[ i*value_size+k ];
}
}
// BLUR
for( int j=dir?d_:0; j<=d_ && j>=0; dir?j--:j++ ){
for( int i=0; i<M_; i++ ){
float * old_val = values + (i+1)*value_size;
float * new_val = new_values + (i+1)*value_size;
int n1 = blur_neighbors_[j*M_+i].n1+1;
int n2 = blur_neighbors_[j*M_+i].n2+1;
float * n1_val = values + n1*value_size;
float * n2_val = values + n2*value_size;
for( int k=0; k<value_size; k++ )
new_val[k] = old_val[k]+0.5*(n1_val[k] + n2_val[k]);
}
std::swap( values, new_values );
}
// Slicing gradient computation
std::vector<float> r_a( (d_+1)*value_size ), sm( value_size );
for( int i=0; i<N_; i++ ){
// Rotate a
std::fill( r_a.begin(), r_a.end(), 0.f );
for( int j=0; j<=d_; j++ ){
int r0 = d_ - rank_[i*(d_+1)+j];
int r1 = r0+1>d_?0:r0+1;
int o0 = offset_[i*(d_+1)+r0]+1;
int o1 = offset_[i*(d_+1)+r1]+1;
for( int k=0; k<value_size; k++ ) {
r_a[ j*value_size+k ] += alpha*values[ o0*value_size+k ];
r_a[ j*value_size+k ] -= alpha*values[ o1*value_size+k ];
}
}
// Multiply by the elevation matrix
std::copy( r_a.begin(), r_a.begin()+value_size, sm.begin() );
for( int j=1; j<=d_; j++ ) {
float grad = 0;
for( int k=0; k<value_size; k++ ) {
// Elevate ...
float v = scale_factor[j-1]*(sm[k]-j*r_a[j*value_size+k]);
// ... and add
grad += (dir?a:b)[ i*value_size+k ]*v;
sm[k] += r_a[j*value_size+k];
}
// Store the gradient
df[i*d_+j-1] += grad;
}
}
}
delete[] values;
delete[] new_values;
}
static void rescale_R11(gsl_matrix *R11, gsl_vector *scale)
{
gsl_vector_view vec_view = gsl_matrix_column(R11, 0);
gsl_vector_scale(&vec_view.vector, scale_factor(scale));
}
