BrdfSlice(const arguments& args,
int width, int height, int slice,
double* content)
: data(brdf_slice_parameters(args),
width * height * slice),
_width(width), _height(height), _slice(slice),
_data(content)
{
// Allocate data
if (args.is_defined("param") && parametrization().dimX() == 3)
_phi = (M_PI / 180.0) * args.get_float("phi", 90);
else
_phi = 0.5*M_PI;
// Is the position of the slice componnent (third coordinate)
// reversed? This ensure that some params can be displayed.
auto in_param = parametrization().input_parametrization();
_reverse = in_param == params::ISOTROPIC_TL_TV_PROJ_DPHI ||
in_param == params::SCHLICK_TL_TK_PROJ_DPHI ||
in_param == params::RETRO_TL_TVL_PROJ_DPHI;
// Update the domain
_max = max();
_min = min();
}
// Allow for a different parametrization depending on the arguments provided.
static const alta::parameters
brdf_slice_parameters(const arguments& args)
{
auto result = alta::parameters(2, 3,
params::STARK_2D, params::RGB_COLOR);
if(args.is_defined("param")) {
params::input param = params::parse_input(args["param"]);
// The param is a 2D param
if(params::dimension(param) == 2) {
std::cout << "<<INFO>> Specified param \"" << args["param"] << "\"" << std::endl;
result = alta::parameters(result.dimX(), result.dimY(),
param, result.output_parametrization());
// The oaram is a 3D param
} else if(params::dimension(param) == 3) {
std::cout << "<<INFO>> Specified param \"" << args["param"] << "\"" << std::endl;
result = alta::parameters(3, result.dimY(),
param, result.output_parametrization());
} else {
std::cout << "<<ERROR>> Invalid specified param \"" << args["param"] << "\"" << std::endl;
std::cout << "<<ERROR>> Must have 2D input dimension" << std::endl;
}
}
return result;
}
bool rational_fitter_parallel::fit_data(const ptr<data>& dat, ptr<function>& fit, const arguments &args)
{
ptr<rational_function> r = dynamic_pointer_cast<rational_function>(fit) ;
if(!r)
{
std::cerr << "<<ERROR>> not passing the correct function class to the fitter: must be a rational_function" << std::endl ;
return false ;
}
ptr<vertical_segment> d = dynamic_pointer_cast<vertical_segment>(dat) ;
if(!d
|| d->confidence_interval_kind() != vertical_segment::ASYMMETRICAL_CONFIDENCE_INTERVAL)
{
std::cerr << "<<WARNING>> automatic convertion of the data object to vertical_segment," << std::endl;
std::cerr << "<<WARNING>> we advise you to perform convertion with a separate command." << std::endl;
size_t elem_size =
dat->parametrization().dimX() + 3*dat->parametrization().dimY();
double* content = new double[dat->size() * elem_size];
for(int i=0; i<dat->size(); ++i)
{
const vec x = dat->get(i);
for(int k=0; k<x.size(); ++k) {
content[i + k] = x[k];
}
for(int k=0; k<dat->parametrization().dimY(); ++k) {
content[i + k + dat->parametrization().dimX() + dat->parametrization().dimY()] =
(1.0 - args.get_float("dt", 0.1)) * x[k + dat->parametrization().dimX()];
}
for(int k=0; k<dat->parametrization().dimY(); ++k) {
content[i + k + dat->parametrization().dimX() + 2*dat->parametrization().dimY()] =
(1.0 + args.get_float("dt", 0.1)) * x[k + dat->parametrization().dimX()];
}
}
ptr<vertical_segment> vs(new vertical_segment(dat->parametrization(),
dat->size(),
std::shared_ptr<double>(content)));
d = vs;
}
// XXX: FIT and D may have different values of dimX() and dimY(), but
// this is fine: we convert values as needed in operator().
r->setMin(d->min());
r->setMax(d->max());
const int _min_np = args.get_int("min-np", 10);
const int _max_np = args.get_int("np", _min_np);
std::cout << "<<INFO>> N in [" << _min_np << ", " << _max_np << "]" << std::endl ;
const int nb_starting_points = args.get_int("nb-starting-points", 100);
std::cout << "<<INFO>> number of data point used in start: " << nb_starting_points << std::endl;
const int step = args.get_int("np-step", 1);
const bool use_delta = args.is_defined("use_delta");
for(int i=_min_np; i<=_max_np; i+=step)
{
std::cout << "<<INFO>> fit using np+nq = " << i << std::endl ;
std::cout.flush() ;
timer time ;
time.start() ;
#ifdef _OPENMP
const int nb_cores = args.get_int("nb-cores", omp_get_num_procs());
#ifdef DEBUG
std::cout << "<<DEBUG>> will use " << nb_cores << " threads to compute the quadratic programs" << std::endl ;
#endif
omp_set_num_threads(nb_cores) ;
#endif
double min_delta = std::numeric_limits<double>::max();
double min_l2_dist = std::numeric_limits<double>::max();
double mean_delta = 0.0;
int nb_sol_found = 0;
int nb_sol_tested = 0;
#pragma omp parallel for shared(r, args, nb_sol_found, nb_sol_tested, min_delta, mean_delta), schedule(dynamic,1)
for(int j=1; j<i; ++j)
{
// Compute the number of coefficients in the numerator and in the denominator
// from the current number of coefficients i and the current index in the
// loop j.
int temp_np = i - j;
int temp_nq = j;
//vec p(temp_np*r->dimY()), q(temp_nq*r->dimY());
// Allocate a rational function and set it to the correct size, dimensions
// and parametrizations.
ptr<rational_function> rk(NULL);
#pragma omp critical (args)
{
rk = dynamic_pointer_cast<rational_function>(
ptr<function>(plugins_manager::get_function(args,
r->parametrization())));
}
if(!rk)
{
std::cerr << "<<ERROR>> unable to obtain a rational function from the plugins manager" << std::endl;
throw;
}
rk->setMin(r->min()) ;
rk->setMax(r->max()) ;
// Set the rational function size
rk->setSize(temp_np, temp_nq);
double delta = 1.0;
double linf_dist, l2_dist;
bool is_fitted = fit_data(d, temp_np, temp_nq, rk, args, delta, linf_dist, l2_dist);
if(is_fitted)
{
#pragma omp critical (r)
{
++nb_sol_found ;
mean_delta += delta ;
std::cout << "<<INFO>> found a solution with np=" << temp_np
<< ", nq = " << temp_nq << std::endl;
std::cout << "<<INFO>> Linf error = " << linf_dist << std::endl;
std::cout << "<<INFO>> L2 error = " << l2_dist << std::endl;
std::cout << "<<INFO>> delta = " << delta << std::endl;
std::cout << std::endl;
// Get the solution with the minimum delta or the minimum L2 distance,
// and update the main rational function r.
if((use_delta && delta < min_delta) || (!use_delta && l2_dist < min_l2_dist))
{
min_delta = delta ;
min_l2_dist = l2_dist ;
r->setSize(temp_np, temp_nq);
r->update(rk);
}
}
}
#pragma omp critical (nb_sol_tested)
{
// Update the solution
nb_sol_tested++;
std::cout << "<<DEBUG>> nb solutions tested: " << nb_sol_tested << " / " << i << "\r";
std::cout.flush();
}
}
if(min_delta < std::numeric_limits<double>::max())
{
std::cout << "<<INFO>> mean delta = " << mean_delta/nb_sol_found << std::endl;
std::cout << "<<INFO>> min delta = " << min_delta << std::endl;
std::cout << *(r.get()) << std::endl;
time.stop();
std::cout << "<<INFO>> got a fit using N = " << i << std::endl ;
std::cout << "<<INFO>> it took " << time << std::endl ;
std::cout << "<<INFO>> I got " << nb_sol_found << " solutions to the QP" << std::endl ;
return true ;
}
}
return false ;
}
// dat is the data object, it contains all the points to fit
// np and nq are the degree of the RP to fit to the data
// y is the dimension to fit on the y-data (e.g. R, G or B for RGB signals)
// the function returns a rational BRDF function and a boolean
bool rational_fitter_parallel::fit_data(const ptr<vertical_segment>& d, int np, int nq, int ny,
rational_function_1d* r, const arguments& args,
vec& p, vec& q, double& delta)
{
const int m = d->size(); // 2*m = number of constraints
const int n = np+nq; // n = np+nq
quadratic_program qp(np, nq, args.is_defined("use_delta"));
// Starting with only a nb_starting_points vertical segments
std::list<unsigned int> training_set;
const int di = std::max((m-1) / (nb_starting_points-1), 1);
for(int i=0; i<m; ++i)
{
if(i % di == 0)
{
// Create two vector of constraints
vec c1(n), c2(n);
get_constraint(i, np, nq, ny, d, r, c1, c2);
qp.add_constraints(c1);
qp.add_constraints(c2);
}
else
{
training_set.push_back(i);
}
}
qp.set_training_set(training_set);
do
{
#ifdef _OPENMP
#ifdef DEBUG
std::cout << "<<DEBUG>> thread " << omp_get_thread_num() << ", number of intervals tested = " << qp.nb_constraints()/2 << std::endl ;
#endif
#endif
Eigen::VectorXd x(n);
bool solves_qp = qp.solve_program(x, delta, p, q);
r->update(p, q);
if(solves_qp)
{
if(qp.test_constraints(ny, r, d))
{
#ifdef DEBUG
std::cout << "<<INFO>> got solution " << *r << std::endl ;
#endif
return true;
}
}
else
{
#ifdef DEBUG
std::cout << "<<DEBUG>> not enough coefficients" << std::endl;
#endif
return false;
}
} while(qp.nb_constraints() < 2*m);
return false;
}
