LSST Applications 28.0.0,g1653933729+a8ce1bb630,g1a997c3884+a8ce1bb630,g28da252d5a+5bd70b7e6d,g2bbee38e9b+638fca75ac,g2bc492864f+638fca75ac,g3156d2b45e+07302053f8,g347aa1857d+638fca75ac,g35bb328faa+a8ce1bb630,g3a166c0a6a+638fca75ac,g3e281a1b8c+7bbb0b2507,g4005a62e65+17cd334064,g414038480c+5b5cd4fff3,g41af890bb2+4ffae9de63,g4e1a3235cc+0f1912dca3,g6249c6f860+3c3976f90c,g80478fca09+46aba80bd6,g82479be7b0+77990446f6,g858d7b2824+78ba4d1ce1,g89c8672015+f667a5183b,g9125e01d80+a8ce1bb630,ga5288a1d22+2a6264e9ca,gae0086650b+a8ce1bb630,gb58c049af0+d64f4d3760,gc22bb204ba+78ba4d1ce1,gc28159a63d+638fca75ac,gcf0d15dbbd+32ddb6096f,gd6b7c0dfd1+3e339405e9,gda3e153d99+78ba4d1ce1,gda6a2b7d83+32ddb6096f,gdaeeff99f8+1711a396fd,gdd5a9049c5+b18c39e5e3,ge2409df99d+a5e4577cdc,ge33fd446bb+78ba4d1ce1,ge79ae78c31+638fca75ac,gf0baf85859+64e8883e75,gf5289d68f6+e1b046a8d7,gfa443fc69c+91d9ed1ecf,gfda6b12a05+8419469a56
LSST Data Management Base Package
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observation.cc File Reference
#include <pybind11/attr.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <memory>
#include <string>
#include "lsst/gauss2d/fit/observation.h"
#include "lsst/gauss2d/fit/parametric.h"
#include "lsst/gauss2d/python/image.h"
#include "pybind11.h"

Go to the source code of this file.

Functions

template<typename T >
void declare_observation (py::module &m, std::string str_type)
 
void bind_observation (py::module &m)
 

Function Documentation

◆ bind_observation()

void bind_observation ( py::module & m)

Definition at line 64 of file observation.cc.

64 {
67}
int m
Definition SpanSet.cc:48
void declare_observation(py::module &m, std::string str_type)

◆ declare_observation()

template<typename T >
void declare_observation ( py::module & m,
std::string str_type )

Definition at line 43 of file observation.cc.

43 {
44 typedef g2p::Image<T> Image;
45 typedef g2p::Image<bool> Mask;
46 typedef g2f::Observation<T, Image, Mask> Observation;
47 std::string pyclass_name = std::string("Observation") + str_type;
48 py::class_<Observation, std::shared_ptr<Observation>, g2f::Parametric>(m, pyclass_name.c_str())
50 const g2f::Channel &>(),
51 "image"_a, "sigma_inv"_a, "mask_inv"_a, "channel"_a)
52 .def_property_readonly("channel", &Observation::get_channel)
53 .def_property_readonly("image", &Observation::get_image)
54 .def_property_readonly("mask_inv", &Observation::get_mask_inverse)
55 .def_property_readonly("sigma_inv", &Observation::get_sigma_inverse)
56 .def_property_readonly("n_cols", &Observation::get_n_cols)
57 .def_property_readonly("n_rows", &Observation::get_n_rows)
58 .def("parameters", &Observation::get_parameters, "parameters"_a = g2f::ParamRefs(),
59 "paramfilter"_a = nullptr)
60 .def("__repr__", [](const Observation &self) { return self.repr(true); })
61 .def("__str__", &Observation::str);
62}
T c_str(T... args)
An observational channel, usually representing some range of wavelengths of light.
Definition channel.h:29
An observed single-channel image with an associated variance and mask.
Definition observation.h:35
A parametric object that can return and filter its Parameter instances.
Definition parametric.h:13
A Python image using numpy arrrays for storage.
Definition image.h:72
g2d::python::Image< double > Image
Definition test_image.cc:14
g2d::python::Image< bool > Mask
Definition test_image.cc:16