LSST Applications g00d0e8bbd7+8c5ae1fdc5,g013ef56533+603670b062,g083dd6704c+2e189452a7,g199a45376c+0ba108daf9,g1c5cce2383+bc9f6103a4,g1fd858c14a+cd69ed4fc1,g210f2d0738+c4742f2e9e,g262e1987ae+612fa42d85,g29ae962dfc+83d129e820,g2cef7863aa+aef1011c0b,g35bb328faa+8c5ae1fdc5,g3fd5ace14f+5eaa884f2a,g47891489e3+e32160a944,g53246c7159+8c5ae1fdc5,g5b326b94bb+dcc56af22d,g64539dfbff+c4742f2e9e,g67b6fd64d1+e32160a944,g74acd417e5+c122e1277d,g786e29fd12+668abc6043,g87389fa792+8856018cbb,g88cb488625+47d24e4084,g89139ef638+e32160a944,g8d7436a09f+d14b4ff40a,g8ea07a8fe4+b212507b11,g90f42f885a+e1755607f3,g97be763408+34be90ab8c,g98df359435+ec1fa61bf1,ga2180abaac+8c5ae1fdc5,ga9e74d7ce9+43ac651df0,gbf99507273+8c5ae1fdc5,gc2a301910b+c4742f2e9e,gca7fc764a6+e32160a944,gd7ef33dd92+e32160a944,gdab6d2f7ff+c122e1277d,gdb1e2cdc75+1b18322db8,ge410e46f29+e32160a944,ge41e95a9f2+c4742f2e9e,geaed405ab2+0d91c11c6d,w.2025.44
LSST Data Management Base Package
Loading...
Searching...
No Matches
observation.cc File Reference
#include <memory>
#include <string>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#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}
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::classh<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 Python image using numpy arrrays for storage.
Definition image.h:72
std::vector< ParamBaseRef > ParamRefs
Definition param_defs.h:13
g2d::python::Image< double > Image
Definition test_image.cc:14
g2d::python::Image< bool > Mask
Definition test_image.cc:16