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added g0 calibration, pedestal and pixel counting

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This commit is contained in:
froejdh_e
2025-07-22 16:42:09 +02:00
parent b898e1c8d0
commit 9a7713e98a
8 changed files with 379 additions and 24 deletions
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3
python/aare/__init__.py
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@@ -32,6 +32,7 @@ from .utils import random_pixels, random_pixel, flat_list, add_colorbar
from .func import *
from .calibration import *
from ._aare import apply_calibration
from ._aare import apply_calibration, count_switching_pixels
from ._aare import calculate_pedestal, calculate_pedestal_float, calculate_pedestal_g0, calculate_pedestal_g0_float
from ._aare import VarClusterFinder

71
python/src/bind_calibration.hpp
View File

@@ -17,19 +17,60 @@ py::array_t<DataType> pybind_apply_calibration(
calibration,
int n_threads = 4) {
auto data_span = make_view_3d(data);
auto ped = make_view_3d(pedestal);
auto cal = make_view_3d(calibration);
auto data_span = make_view_3d(data); // data is always 3D
/* No pointer is passed, so NumPy will allocate the buffer */
auto result = py::array_t<DataType>(data_span.shape());
auto res = make_view_3d(result);
aare::apply_calibration<DataType>(res, data_span, ped, cal, n_threads);
if (data.ndim() == 3 && pedestal.ndim() == 3 && calibration.ndim() == 3) {
auto ped = make_view_3d(pedestal);
auto cal = make_view_3d(calibration);
aare::apply_calibration<DataType, 3>(res, data_span, ped, cal,
n_threads);
} else if (data.ndim() == 3 && pedestal.ndim() == 2 &&
calibration.ndim() == 2) {
auto ped = make_view_2d(pedestal);
auto cal = make_view_2d(calibration);
aare::apply_calibration<DataType, 2>(res, data_span, ped, cal,
n_threads);
} else {
throw std::runtime_error(
"Invalid number of dimensions for data, pedestal or calibration");
}
return result;
}
py::array_t<int> pybind_count_switching_pixels(
py::array_t<uint16_t, py::array::c_style | py::array::forcecast> data,
ssize_t n_threads = 4) {
auto data_span = make_view_3d(data);
auto arr = new NDArray<int, 2>{};
*arr = aare::count_switching_pixels(data_span, n_threads);
return return_image_data(arr);
}
template <typename T>
py::array_t<T> pybind_calculate_pedestal(
py::array_t<uint16_t, py::array::c_style | py::array::forcecast> data,
ssize_t n_threads) {
auto data_span = make_view_3d(data);
auto arr = new NDArray<T, 3>{};
*arr = aare::calculate_pedestal<T>(data_span, n_threads);
return return_image_data(arr);
}
template <typename T>
py::array_t<T> pybind_calculate_pedestal_g0(
py::array_t<uint16_t, py::array::c_style | py::array::forcecast> data,
ssize_t n_threads) {
auto data_span = make_view_3d(data);
auto arr = new NDArray<T, 2>{};
*arr = aare::calculate_pedestal_g0<T>(data_span, n_threads);
return return_image_data(arr);
}
void bind_calibration(py::module &m) {
m.def("apply_calibration", &pybind_apply_calibration<float>,
py::arg("raw_data").noconvert(), py::kw_only(),
@@ -40,4 +81,20 @@ void bind_calibration(py::module &m) {
py::arg("raw_data").noconvert(), py::kw_only(),
py::arg("pd").noconvert(), py::arg("cal").noconvert(),
py::arg("n_threads") = 4);
m.def("count_switching_pixels", &pybind_count_switching_pixels,
py::arg("raw_data").noconvert(), py::kw_only(),
py::arg("n_threads") = 4);
m.def("calculate_pedestal_float", &pybind_calculate_pedestal<float>,
py::arg("raw_data").noconvert(), py::arg("n_threads") = 4);
m.def("calculate_pedestal", &pybind_calculate_pedestal<double>,
py::arg("raw_data").noconvert(), py::arg("n_threads") = 4);
m.def("calculate_pedestal_g0", &pybind_calculate_pedestal_g0<double>,
py::arg("raw_data").noconvert(), py::arg("n_threads") = 4);
m.def("calculate_pedestal_g0_float", &pybind_calculate_pedestal_g0<float>,
py::arg("raw_data").noconvert(), py::arg("n_threads") = 4);
}