void harp::spec_desisim::values ( vector_double & data ) const {
data.resize ( nglobal_ );
data.clear();
fitsfile * fp;
fits::open_read ( fp, path_ );
// read the object flux
fits::img_seek ( fp, objhdu_ );
fits::img_read ( fp, data, false );
// read the sky flux and sum
vector_double skyflux ( data.size() );
fits::img_seek ( fp, skyhdu_ );
fits::img_read ( fp, skyflux, false );
fits::close ( fp );
for ( size_t i = 0; i < data.size(); ++i ) {
data[i] += skyflux[i];
}
return;
}
// The error function F(x):
void myFunction( const vector_double &x, const vector_double &y, vector_double &out_f)
{
out_f.resize(1);
// 1-cos(x+1) *cos(x*y+1)
out_f[0] = 1 - cos(x[0]+1) * cos(x[0]*x[1]+1);
}
/*---------------------------------------------------------------
getAsVector
---------------------------------------------------------------*/
void CPose2D::getAsVector(vector_double &v) const
{
v.resize(3);
v[0]=m_coords[0];
v[1]=m_coords[1];
v[2]=m_phi;
}
void harp::spec_sim::inv_variance ( vector_double & data ) const {
data.resize ( size_ );
data.clear();
return;
}
void ffff(const vector_double &x,const CQuaternionDouble &Q, vector_double &OUT)
{
OUT.resize(3);
CQuaternionDouble q(x[0],x[1],x[2],x[3]);
q.normalize();
q.rpy(OUT[2],OUT[1],OUT[0]);
}
/*---------------------------------------------------------------
getHistogramNormalized
---------------------------------------------------------------*/
void CHistogram::getHistogramNormalized( vector_double &x, vector_double &hits ) const
{
const size_t N = m_bins.size();
linspace(m_min,m_max,N, x);
hits.resize(N);
const double K=m_binSizeInv/m_count;
for (size_t i=0;i<N;i++)
hits[i]=K*m_bins[i];
}
void harp::spec_desisim::lambda ( vector_double & lambda_vals ) const {
lambda_vals.resize ( nlambda_ );
for ( size_t i = 0; i < nlambda_; ++i ) {
lambda_vals[i] = crval + cdelt * (double)i;
}
return;
}
/** Returns a 1x7 vector with [x y z qr qx qy qz] */
void CPose3DQuat::getAsVector(vector_double &v) const
{
v.resize(7);
v[0] = m_coords[0];
v[1] = m_coords[1];
v[2] = m_coords[2];
v[3] = m_quat[0];
v[4] = m_quat[1];
v[5] = m_quat[2];
v[6] = m_quat[3];
}
void harp::spec_sim::lambda ( vector_double & lambda_vals ) const {
lambda_vals.resize ( nlambda_ );
double incr = (last_lambda_ - first_lambda_) / (double)( nlambda_ - 1 );
for ( size_t j = 0; j < nlambda_; ++j ) {
lambda_vals[j] = first_lambda_ + incr * (double)j;
}
return;
}
void harp::eigen_decompose ( matrix_double const & invcov, vector_double & D, matrix_double & W, bool regularize ) {
D.resize ( invcov.size1() );
W.resize ( invcov.size1(), invcov.size2() );
matrix_double temp ( invcov );
int nfound;
boost::numeric::ublas::vector < int > support ( 2 * invcov.size1() );
boost::numeric::bindings::lapack::syevr ( 'V', 'A', boost::numeric::bindings::lower ( temp ), 0.0, 0.0, 0, 0, 0.0, nfound, D, W, support );
if ( regularize ) {
double min = 1.0e100;
double max = -1.0e100;
for ( size_t i = 0; i < D.size(); ++i ) {
if ( D[i] < min ) {
min = D[i];
}
if ( D[i] > max ) {
max = D[i];
}
}
double rcond = min / max;
// pick some delta that is bigger than machine precision, but still tiny
double epsilon = 10.0 * std::numeric_limits < double > :: epsilon();
if ( rcond < epsilon ) {
double reg = max * epsilon - min;
//cerr << "REG offset = " << reg << " for min / max = " << min << " / " << max << endl;
for ( size_t i = 0; i < D.size(); ++i ) {
D[i] += reg;
}
}
}
return;
}
void harp::column_norm ( matrix_double const & mat, vector_double & S ) {
S.resize( mat.size1() );
S.clear();
for ( size_t i = 0; i < mat.size2(); ++i ) {
for ( size_t j = 0; j < mat.size1(); ++j ) {
S[ j ] += mat( j, i );
}
}
// Invert
for ( size_t i = 0; i < S.size(); ++i ) {
S[i] = 1.0 / S[i];
}
return;
}
void harp::spec_desisim::sky ( vector_double & data ) const {
data.resize ( nglobal_ );
data.clear();
fitsfile * fp;
fits::open_read ( fp, path_ );
// read the sky flux
fits::img_seek ( fp, skyhdu_ );
fits::img_read ( fp, data, false );
fits::close ( fp );
return;
}
void harp::spec_sim::values ( vector_double & data ) const {
double PI = std::atan2 ( 0.0, -1.0 );
data.resize ( size_ );
size_t bin = 0;
size_t halfspace = (size_t)( atmspace_ / 2 );
for ( size_t i = 0; i < nspec_; ++i ) {
bool dosky = ( i % skymod_ == 0 ) ? true : false;
size_t objoff = 2 * i;
for ( size_t j = 0; j < nlambda_; ++j ) {
double val = 0.0;
val += background_ * sin ( 3.0 * (double)j / ( (double)atmspace_ * 2.0 * PI ) ) * sin ( 7.0 * (double)j / ( (double)atmspace_ * 2.0 * PI ) ) * sin ( 11.0 * (double)j / ( (double)atmspace_ * 2.0 * PI ) );
val += 2.0 * background_;
if ( ( ( j + halfspace ) % atmspace_ ) == 0 ) {
val += atmpeak_;
}
if ( ! dosky ) {
if ( ( ( j + objoff ) % objspace_ ) == 0 ) {
val += objpeak_;
}
}
data[ bin ] = val;
++bin;
}
}
return;
}
void harp::sparse_mv_trans ( matrix_double_sparse const & AT, vector_double const & in, vector_double & out ) {
// FIXME: for now, we just use the (unthreaded) boost sparse matrix-vector product. If this
// operation dominates the cost in any way, we can add a threaded implementation here.
size_t nrows = AT.size1();
size_t ncols = AT.size2();
if ( in.size() != nrows ) {
std::ostringstream o;
o << "length of input vector (" << in.size() << ") does not match number of rows in transposed matrix (" << nrows << ")";
HARP_THROW( o.str().c_str() );
}
out.resize ( ncols );
boost::numeric::ublas::axpy_prod ( in, AT, out, true );
return;
}
void harp::spec_sim::sky_truth ( vector_double & data ) const {
double PI = std::atan2 ( 0.0, -1.0 );
size_t halfspace = (size_t)( atmspace_ / 2 );
size_t nreduced = 0;
for ( size_t i = 0; i < nspec_; ++i ) {
if ( i % skymod_ != 0 ) {
++nreduced;
}
}
++nreduced;
size_t nbins = nreduced * nlambda_;
data.resize ( nbins );
size_t bin = 0;
for ( size_t i = 0; i < nspec_; ++i ) {
if ( i % skymod_ != 0 ) {
size_t objoff = 2 * i;
for ( size_t j = 0; j < nlambda_; ++j ) {
double val = 0.0;
if ( ( ( j + objoff ) % objspace_ ) == 0 ) {
val += objpeak_;
}
data[ bin ] = val;
++bin;
}
}
}
for ( size_t j = 0; j < nlambda_; ++j ) {
double val = 0.0;
val += background_ * sin ( 3.0 * (double)j / ( (double)atmspace_ * 2.0 * PI ) ) * sin ( 7.0 * (double)j / ( (double)atmspace_ * 2.0 * PI ) ) * sin ( 11.0 * (double)j / ( (double)atmspace_ * 2.0 * PI ) );
val += 2.0 * background_;
if ( ( ( j + halfspace ) % atmspace_ ) == 0 ) {
val += atmpeak_;
}
data[ bin ] = val;
++bin;
}
return;
}
/*---------------------------------------------------------------
Evaluate each gap
---------------------------------------------------------------*/
void CHolonomicND::evaluateGaps(
const vector_double &obstacles,
const double maxObsRange,
const TGapArray &gaps,
const int TargetSector,
const double TargetDist,
vector_double &out_gaps_evaluation )
{
out_gaps_evaluation.resize( gaps.size());
double targetAng = M_PI*(-1 + 2*(0.5+TargetSector)/double(obstacles.size()));
double target_x = TargetDist*cos(targetAng);
double target_y = TargetDist*sin(targetAng);
for (unsigned int i=0;i<gaps.size();i++)
{
// Para referenciarlo mas facilmente:
const TGap *gap = &gaps[i];
double d;
d = min( obstacles[ gap->representative_sector ],
min( maxObsRange, 0.95f*TargetDist) );
// Las coordenadas (en el TP-Space) representativas del gap:
double phi = M_PI*(-1 + 2*(0.5+gap->representative_sector)/double(obstacles.size()));
double x = d*cos(phi);
double y = d*sin(phi);
// Factor 1: Distancia hasta donde llego por esta GPT:
// -----------------------------------------------------
double factor1;
/* if (gap->representative_sector == TargetSector )
factor1 = min(TargetDist,obstacles[gap->representative_sector]) / TargetDist;
else
{
if (TargetDist>1)
factor1 = obstacles[gap->representative_sector] / TargetDist;
else factor1 = obstacles[gap->representative_sector];
}
*/
// Calcular la distancia media a donde llego por este gap:
double meanDist = 0;
for (int j=gap->ini;j<=gap->end;j++)
meanDist+= obstacles[j];
meanDist/= ( gap->end - gap->ini + 1);
if (abs(gap->representative_sector-TargetSector)<=1 && TargetDist<1)
factor1 = min(TargetDist,meanDist) / TargetDist;
else factor1 = meanDist;
// Factor 2: Distancia en sectores:
// -------------------------------------------
double dif = fabs(((double)( TargetSector - gap->representative_sector )));
// if (dif> (0.5f*obstacles.size()) ) dif = obstacles.size() - dif;
// Solo si NO estan el target y el gap atravesando el alfa = "-pi" o "pi"
if (dif> (0.5f*obstacles.size()) && (TargetSector-0.5f*obstacles.size())*(gap->representative_sector-0.5f*obstacles.size())<0 )
dif = obstacles.size() - dif;
double factor2= exp(-square( dif / (obstacles.size()/4))) ;
// Factor3: Para evitar cabeceos entre 2 o mas caminos que sean casi iguales:
// -------------------------------------------
double dist = (double)(abs(last_selected_sector - gap->representative_sector));
//
if (dist> (0.5f*obstacles.size()) ) dist = obstacles.size() - dist;
double factor_AntiCab;
if (last_selected_sector==-1)
factor_AntiCab = 0;
else factor_AntiCab = (dist > 0.10f*obstacles.size()) ? 0.0f:1.0f;
// Factor3: Minima distancia entre el segmento y el target:
// Se valora negativamente el alejarse del target
// -----------------------------------------------------
double closestX,closestY;
double dist_eucl = math::minimumDistanceFromPointToSegment(
target_x,
target_y,
0,0,
x,y,
closestX,closestY);
double factor3= ( maxObsRange - min(maxObsRange ,dist_eucl) ) / maxObsRange;
ASSERT_(factorWeights.size()==4);
if ( obstacles[gap->representative_sector] < TOO_CLOSE_OBSTACLE ) // Too close to obstacles
out_gaps_evaluation[i] = 0;
else out_gaps_evaluation[i] = (
factorWeights[0] * factor1 +
factorWeights[1] * factor2 +
factorWeights[2] * factor3 +
factorWeights[3] * factor_AntiCab ) / (math::sum(factorWeights)) ;
} // for each gap
}
// extracted from Particles3Dcomm.cpp
//
void Collective::read_particles_restart(
const VCtopology3D* vct,
int species_number,
vector_double& u,
vector_double& v,
vector_double& w,
vector_double& q,
vector_double& x,
vector_double& y,
vector_double& z,
vector_double& t)const
{
#ifdef NO_HDF5
eprintf("Require HDF5 to read from restart file.");
#else
if (vct->getCartesian_rank() == 0 && species_number == 0)
{
printf("LOADING PARTICLES FROM RESTART FILE in %s/restart.hdf\n",
getRestartDirName().c_str());
}
stringstream ss;
ss << vct->getCartesian_rank();
string name_file = getRestartDirName() + "/restart" + ss.str() + ".hdf";
// hdf stuff
hid_t file_id, dataspace;
hid_t datatype, dataset_id;
herr_t status;
size_t size;
hsize_t dims_out[1]; /* dataset dimensions */
int status_n;
// open the hdf file
file_id = H5Fopen(name_file.c_str(), H5F_ACC_RDWR, H5P_DEFAULT);
if (file_id < 0) {
eprintf("couldn't open file: %s\n"
"\tRESTART NOT POSSIBLE", name_file.c_str());
//cout << "couldn't open file: " << name_file << endl;
//cout << "RESTART NOT POSSIBLE" << endl;
}
//find the last cycle
int lastcycle=0;
dataset_id = H5Dopen2(file_id, "/last_cycle", H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_INT, H5S_ALL, H5S_ALL, H5P_DEFAULT, &lastcycle);
status = H5Dclose(dataset_id);
stringstream species_name;
species_name << species_number;
ss.str("");ss << "/particles/species_" << species_number << "/x/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
datatype = H5Dget_type(dataset_id);
size = H5Tget_size(datatype);
dataspace = H5Dget_space(dataset_id); /* dataspace handle */
status_n = H5Sget_simple_extent_dims(dataspace, dims_out, NULL);
// get how many particles there are on this processor for this species
status_n = H5Sget_simple_extent_dims(dataspace, dims_out, NULL);
const int nop = dims_out[0]; // number of particles in this process
//Particles3Dcomm::resize_SoA(nop);
{
//
// allocate space for particles including padding
//
const int padded_nop = roundup_to_multiple(nop,DVECWIDTH);
u.reserve(padded_nop);
v.reserve(padded_nop);
w.reserve(padded_nop);
q.reserve(padded_nop);
x.reserve(padded_nop);
y.reserve(padded_nop);
z.reserve(padded_nop);
t.reserve(padded_nop);
//
// define size of particle data
//
u.resize(nop);
v.resize(nop);
w.resize(nop);
q.resize(nop);
x.resize(nop);
y.resize(nop);
z.resize(nop);
t.resize(nop);
}
// get x
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &x[0]);
// close the data set
status = H5Dclose(dataset_id);
// get y
ss.str("");ss << "/particles/species_" << species_number << "/y/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &y[0]);
status = H5Dclose(dataset_id);
// get z
ss.str("");ss << "/particles/species_" << species_number << "/z/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &z[0]);
status = H5Dclose(dataset_id);
// get u
ss.str("");ss << "/particles/species_" << species_number << "/u/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &u[0]);
status = H5Dclose(dataset_id);
// get v
ss.str("");ss << "/particles/species_" << species_number << "/v/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &v[0]);
status = H5Dclose(dataset_id);
// get w
ss.str("");ss << "/particles/species_" << species_number << "/w/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &w[0]);
status = H5Dclose(dataset_id);
// get q
ss.str("");ss << "/particles/species_" << species_number << "/q/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &q[0]);
//if ID is not saved, read in q as ID
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &t[0]);
status = H5Dclose(dataset_id);
/* get ID
ss.str("");ss << "/particles/species_" << species_number << "/ID/cycle_" << lastcycle;
dataset_id = H5Dopen2(file_id, ss.str().c_str(), H5P_DEFAULT); // HDF 1.8.8
status = H5Dread(dataset_id, H5T_NATIVE_DOUBLE, H5S_ALL, H5S_ALL, H5P_DEFAULT, &t[0]);
status = H5Dclose(dataset_id);
*/
status = H5Fclose(file_id);
#endif
}
/*---------------------------------------------------------------
Evaluate each gap
---------------------------------------------------------------*/
void CHolonomicND::evaluateGaps(
const vector_double &obstacles,
const double maxObsRange,
const TGapArray &gaps,
const unsigned int target_sector,
const double target_dist,
vector_double &out_gaps_evaluation )
{
out_gaps_evaluation.resize( gaps.size());
double targetAng = M_PI*(-1 + 2*(0.5+target_sector)/double(obstacles.size()));
double target_x = target_dist*cos(targetAng);
double target_y = target_dist*sin(targetAng);
for (unsigned int i=0;i<gaps.size();i++)
{
// Short cut:
const TGap *gap = &gaps[i];
const double d = min3(
obstacles[ gap->representative_sector ],
maxObsRange,
0.95*target_dist );
// The TP-Space representative coordinates for this gap:
const double phi = M_PI*(-1 + 2*(0.5+gap->representative_sector)/double(obstacles.size()));
const double x = d*cos(phi);
const double y = d*sin(phi);
// Factor #1: Maximum reachable distance with this PTG:
// -----------------------------------------------------
// It computes the average free distance of the gap:
double meanDist = 0;
for (unsigned int j=gap->ini;j<=gap->end;j++)
meanDist+= obstacles[j];
meanDist/= ( gap->end - gap->ini + 1);
double factor1;
if (mrpt::utils::abs_diff(gap->representative_sector,target_sector)<=1 && target_dist<1)
factor1 = std::min(target_dist,meanDist) / target_dist;
else factor1 = meanDist;
// Factor #2: Distance to target in "sectors"
// -------------------------------------------
unsigned int dif = mrpt::utils::abs_diff(target_sector, gap->representative_sector );
// Handle the -PI,PI circular topology:
if (dif> 0.5*obstacles.size())
dif = obstacles.size() - dif;
const double factor2= exp(-square( dif / (obstacles.size()*0.25))) ;
// Factor #3: Punish paths that take us far away wrt the target: **** I don't understand it *********
// -----------------------------------------------------
double closestX,closestY;
double dist_eucl = math::minimumDistanceFromPointToSegment(
target_x, target_y, // Point
0,0, x,y, // Segment
closestX,closestY // Out
);
const double factor3 = ( maxObsRange - std::min(maxObsRange ,dist_eucl) ) / maxObsRange;
// Factor #4: Stabilizing factor (hysteresis) to avoid quick switch among very similar paths:
// ------------------------------------------------------------------------------------------
double factor_AntiCab;
if (m_last_selected_sector != std::numeric_limits<unsigned int>::max() )
{
unsigned int dist = mrpt::utils::abs_diff(m_last_selected_sector, gap->representative_sector);
if (dist > unsigned(0.1*obstacles.size()))
factor_AntiCab = 0.0;
else
factor_AntiCab = 1.0;
}
else
{
factor_AntiCab = 0;
}
ASSERT_(options.factorWeights.size()==4);
if ( obstacles[gap->representative_sector] < options.TOO_CLOSE_OBSTACLE ) // Too close to obstacles
out_gaps_evaluation[i] = 0;
else out_gaps_evaluation[i] = (
options.factorWeights[0] * factor1 +
options.factorWeights[1] * factor2 +
options.factorWeights[2] * factor3 +
options.factorWeights[3] * factor_AntiCab ) / (math::sum(options.factorWeights)) ;
} // for each gap
}
/*---------------------------------------------------------------
HornMethod
---------------------------------------------------------------*/
double scanmatching::HornMethod(
const vector_double &inVector,
vector_double &outVector, // The output vector
bool forceScaleToUnity )
{
MRPT_START
vector_double input;
input.resize( inVector.size() );
input = inVector;
outVector.resize( 7 );
// Compute the centroids
TPoint3D cL(0,0,0), cR(0,0,0);
const size_t nMatches = input.size()/6;
ASSERT_EQUAL_(input.size()%6, 0)
for( unsigned int i = 0; i < nMatches; i++ )
{
cL.x += input[i*6+3];
cL.y += input[i*6+4];
cL.z += input[i*6+5];
cR.x += input[i*6+0];
cR.y += input[i*6+1];
cR.z += input[i*6+2];
}
ASSERT_ABOVE_(nMatches,0)
const double F = 1.0/nMatches;
cL *= F;
cR *= F;
CMatrixDouble33 S; // S.zeros(); // Zeroed by default
// Substract the centroid and compute the S matrix of cross products
for( unsigned int i = 0; i < nMatches; i++ )
{
input[i*6+3] -= cL.x;
input[i*6+4] -= cL.y;
input[i*6+5] -= cL.z;
input[i*6+0] -= cR.x;
input[i*6+1] -= cR.y;
input[i*6+2] -= cR.z;
S.get_unsafe(0,0) += input[i*6+3]*input[i*6+0];
S.get_unsafe(0,1) += input[i*6+3]*input[i*6+1];
S.get_unsafe(0,2) += input[i*6+3]*input[i*6+2];
S.get_unsafe(1,0) += input[i*6+4]*input[i*6+0];
S.get_unsafe(1,1) += input[i*6+4]*input[i*6+1];
S.get_unsafe(1,2) += input[i*6+4]*input[i*6+2];
S.get_unsafe(2,0) += input[i*6+5]*input[i*6+0];
S.get_unsafe(2,1) += input[i*6+5]*input[i*6+1];
S.get_unsafe(2,2) += input[i*6+5]*input[i*6+2];
}
// Construct the N matrix
CMatrixDouble44 N; // N.zeros(); // Zeroed by default
N.set_unsafe( 0,0,S.get_unsafe(0,0) + S.get_unsafe(1,1) + S.get_unsafe(2,2) );
N.set_unsafe( 0,1,S.get_unsafe(1,2) - S.get_unsafe(2,1) );
N.set_unsafe( 0,2,S.get_unsafe(2,0) - S.get_unsafe(0,2) );
N.set_unsafe( 0,3,S.get_unsafe(0,1) - S.get_unsafe(1,0) );
N.set_unsafe( 1,0,N.get_unsafe(0,1) );
N.set_unsafe( 1,1,S.get_unsafe(0,0) - S.get_unsafe(1,1) - S.get_unsafe(2,2) );
N.set_unsafe( 1,2,S.get_unsafe(0,1) + S.get_unsafe(1,0) );
N.set_unsafe( 1,3,S.get_unsafe(2,0) + S.get_unsafe(0,2) );
N.set_unsafe( 2,0,N.get_unsafe(0,2) );
N.set_unsafe( 2,1,N.get_unsafe(1,2) );
N.set_unsafe( 2,2,-S.get_unsafe(0,0) + S.get_unsafe(1,1) - S.get_unsafe(2,2) );
N.set_unsafe( 2,3,S.get_unsafe(1,2) + S.get_unsafe(2,1) );
N.set_unsafe( 3,0,N.get_unsafe(0,3) );
N.set_unsafe( 3,1,N.get_unsafe(1,3) );
N.set_unsafe( 3,2,N.get_unsafe(2,3) );
N.set_unsafe( 3,3,-S.get_unsafe(0,0) - S.get_unsafe(1,1) + S.get_unsafe(2,2) );
// q is the quaternion correspondent to the greatest eigenvector of the N matrix (last column in Z)
CMatrixDouble44 Z, D;
vector_double v;
N.eigenVectors( Z, D );
Z.extractCol( Z.getColCount()-1, v );
ASSERTDEB_( fabs( sqrt( v[0]*v[0] + v[1]*v[1] + v[2]*v[2] + v[3]*v[3] ) - 1.0 ) < 0.1 );
// Make q_r > 0
if( v[0] < 0 ){ v[0] *= -1; v[1] *= -1; v[2] *= -1; v[3] *= -1; }
CPose3DQuat q; // Create a pose rotation with the quaternion
for(unsigned int i = 0; i < 4; i++ ) // insert the quaternion part
outVector[i+3] = q[i+3] = v[i];
// Compute scale
double num = 0.0;
double den = 0.0;
for( unsigned int i = 0; i < nMatches; i++ )
{
num += square( input[i*6+0] ) + square( input[i*6+1] ) + square( input[i*6+2] );
den += square( input[i*6+3] ) + square( input[i*6+4] ) + square( input[i*6+5] );
} // end-for
// The scale:
double s = std::sqrt( num/den );
// Enforce scale to be 1
if( forceScaleToUnity )
s = 1.0;
TPoint3D pp;
q.composePoint( cL.x, cL.y, cL.z, pp.x, pp.y, pp.z );
pp*=s;
outVector[0] = cR.x - pp.x; // X
outVector[1] = cR.y - pp.y; // Y
outVector[2] = cR.z - pp.z; // Z
return s; // return scale
MRPT_END
}
