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// sersic: small program which samples an elliptic Sérsic profile and computes
// IMT's for a number of interpolated marching squares thresholds
// using the preliminary Papaya2 library.
// 2018 Sebastian Kapfer <sebastian.kapfer@fau.de>
#include "sersic.hpp"
#include "common.hpp"
using namespace papaya2;
int main(int, const char **argv)
{
if (!argv[1])
die("give mode");
double aspect = 3. / 8;
void (Photo::*method)(const Sersic &) = &Photo::sample_function;
Photo ds;
bool interpolated_marching_squares = false;
double threshold = 1.2;
int resolution = 200;
string mode = argv[1];
for (argv += 2; *argv; ++argv) {
if (string(*argv) == "integrate") {
method = &Photo::integrate_function;
} else if (string(*argv) == "threshold") {
threshold = read_arg<double>(argv++);
} else if (string(*argv) == "aspect") {
aspect = read_arg<double>(argv++);
} else if (string(*argv) == "interpolated_marching_squares") {
interpolated_marching_squares = true;
} else if (string(*argv) == "resolution") {
resolution = read_arg<unsigned long>(argv++);
} else {
std::cerr << "illegal argument: " << *argv << "\n";
return 1;
}
}
ds.set_coordinates(-1, -1, 1, 1, resolution, resolution);
MinkowskiAccumulator imt;
if (mode == "scan_threshold") {
(ds.*method)(Sersic(1., aspect, deg2rad(10)));
Datafile df(std::cout << "#threshold area perimeter q2 q3 q4\n");
for (auto threshold : logspace(1.1, 2.71828, 30, true)) {
if (!interpolated_marching_squares)
imt = imt_regular_marching_squares(ds, threshold);
else
imt = imt_interpolated_marching_squares(ds, threshold);
df << threshold << imt.area() << imt.perimeter() << imt.msm(2)
<< imt.msm(3) << imt.msm(4) << imt.msm(5) << imt.msm(6)
<< imt.msm(7) << imt.msm(8) << std::arg(imt.imt(2)) << NAN
<< std::endl;
}
} else if (mode == "scan_angle") {
const double ellip = std::sqrt(1 - fsq(aspect));
Datafile df(std::cout << "# aspect ratio " << aspect << " ellipticity "
<< ellip << "\n"
<< "#angle area perimeter q2 q3 q4\n");
for (auto angle : linspace(0, .5 * TWO_PI, 50, false)) {
(ds.*method)(Sersic(1., aspect, angle));
if (!interpolated_marching_squares)
imt = imt_regular_marching_squares(ds, threshold);
else
imt = imt_interpolated_marching_squares(ds, threshold);
df << angle << imt.area() << imt.perimeter() << imt.msm(2)
<< imt.msm(3) << imt.msm(4) << imt.msm(5) << imt.msm(6)
<< imt.msm(7) << imt.msm(8) << std::arg(imt.imt(2)) << NAN
<< std::endl;
}
}
return 0;
}