2 * CompactSersicModel.icpp
4 * Created on: Jul 25, 2019
10 namespace ModelFitting {
12 template<typename ImageType>
13 CompactSersicModel<ImageType>::CompactSersicModel(double sharp_radius,
14 std::shared_ptr<BasicParameter> i0, std::shared_ptr<BasicParameter> k, std::shared_ptr<BasicParameter> n,
15 std::shared_ptr<BasicParameter> x_scale, std::shared_ptr<BasicParameter> y_scale,
16 std::shared_ptr<BasicParameter> rotation, double width, double height,
17 std::shared_ptr<BasicParameter> x, std::shared_ptr<BasicParameter> y,
18 std::tuple<double, double, double, double> transform)
19 : CompactModelBase<ImageType>(x_scale, y_scale, rotation, width, height, x, y, transform),
20 m_sharp_radius_squared(float(sharp_radius * sharp_radius)),
21 m_i0(i0), m_k(k), m_n(n)
24 template<typename ImageType>
25 double CompactSersicModel<ImageType>::getValue(double x, double y) const {
26 SersicModelEvaluator model_eval;
27 model_eval.transform = getCombinedTransform(1.0);
28 model_eval.i0 = m_i0->getValue();
29 model_eval.k = m_k->getValue();
30 model_eval.n = m_n->getValue();
32 auto area_correction = (1.0 / fabs(m_jacobian[0] * m_jacobian[3] - m_jacobian[1] * m_jacobian[2]));
33 return model_eval.evaluateModel(x, y) * area_correction;
36 template<typename ImageType>
37 ImageType CompactSersicModel<ImageType>::getRasterizedImage(double pixel_scale, std::size_t size_x, std::size_t size_y) const {
38 //std::cout << "]] " << getX() << " " << getY() << "\n";
39 using Traits = ImageTraits<ImageType>;
41 if (size_x % 2 == 0 || size_y % 2 == 0) {
42 throw Elements::Exception() << "Rasterized image dimensions must be odd numbers "
43 << "but got (" << size_x << ',' << size_y << ")";
46 ImageType image = Traits::factory(size_x, size_y);
48 SersicModelEvaluator model_eval;
49 model_eval.transform = getCombinedTransform(pixel_scale);
50 model_eval.i0 = m_i0->getValue();
51 model_eval.k = m_k->getValue();
52 model_eval.n = m_n->getValue();
54 float area_correction = (1.0 / fabs(m_jacobian[0] * m_jacobian[3] - m_jacobian[1] * m_jacobian[2])) * pixel_scale * pixel_scale;
56 for (int x=0; x<(int)size_x; ++x) {
57 int dx = x - size_x / 2;
58 for (int y=0; y<(int)size_y; ++y) {
59 int dy = y - size_y / 2;
60 if (dx*dx + dy*dy < m_sharp_radius_squared) {
61 Traits::at(image, x, y) = adaptiveSamplePixel(model_eval, dx, dy, 8, 1.01) * area_correction;
63 Traits::at(image, x, y) = model_eval.evaluateModel(dx, dy) * area_correction;