lsst::meas::extensions::trailedSources Namespace Reference

Namespaces
	NaivePlugin
	VeresPlugin
	version

Classes
class	VeresModel
	Implementation of an axisymmetric 2D Gaussian convolved with a line – a model for a fast-moving, trailed-source (Veres et al. More...

Typedefs
using	ImageF = afw::image::Image< float >
using	ExposureF = afw::image::Exposure< float >

Functions
void	wrapVeresModel (lsst::utils::python::WrapperCollection &wrappers)
	PYBIND11_MODULE (_trailedSources, mod)
void	wrapVeresModel (utils::python::WrapperCollection &wrappers)

Typedef Documentation

ExposureF

using lsst::meas::extensions::trailedSources::ExposureF = typedef afw::image::Exposure<float>

Definition at line 36 of file VeresModel.cc.

ImageF

using lsst::meas::extensions::trailedSources::ImageF = typedef afw::image::Image<float>

Examples

imageStatistics.cc.

Definition at line 35 of file VeresModel.cc.

Function Documentation

PYBIND11_MODULE()

lsst::meas::extensions::trailedSources::PYBIND11_MODULE	(	_trailedSources	,
		mod
	)

Definition at line 36 of file _trailedSources.cc.

                                      {
    lsst::utils::python::WrapperCollection wrappers(mod, "lsst.meas.extensions.trailedSources");
    wrapVeresModel(wrappers);
    wrappers.finish();
}

wrapVeresModel() [1/2]

void lsst::meas::extensions::trailedSources::wrapVeresModel

(

lsst::utils::python::WrapperCollection &

wrappers

)

wrapVeresModel() [2/2]

void lsst::meas::extensions::trailedSources::wrapVeresModel

(

utils::python::WrapperCollection &

wrappers

)

Definition at line 41 of file _VeresModel.cc.

                                                            {
 
    wrappers.addSignatureDependency("lsst.geom");
    wrappers.addSignatureDependency("lsst.afw.image");
 
    wrappers.wrapType(
        py::class_<VeresModel, std::shared_ptr<VeresModel>>(wrappers.module, "VeresModel"),
        [](auto & mod, auto & cls) {
            cls.def(py::init<afw::image::Exposure<float> const&>(), "data"_a);
            cls.def("__call__", &VeresModel::operator(), py::is_operator(), "params"_a);
            cls.def("gradient", &VeresModel::gradient, "params"_a);
            cls.def_property_readonly("sigma", &VeresModel::getSigma);
    });
}