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More uniform binding of Numpy arrays (#381)
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- Introduce a standard way to bind numpy arrays: py::array_t<T> and
.noconvert() on the argument
- Take py::array_t by value since it's just a small wrapper
- Update bindings
This commit is contained in:
Erik Fröjdh authored and GitHub committed 2026-09-25 14:40:33 +02:00
1 parent 8579a140f7
commit 941325ea15
26 files changed
+597 -280
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python/src/bind_calibration.hpp
+13 -19
View File
@@ -11,38 +11,34 @@
namespace py = pybind11;
template <typename DataType>
py::array_t<DataType> pybind_apply_calibration(
py::array_t<uint16_t, py::array::c_style | py::array::forcecast> data,
py::array_t<DataType, py::array::c_style | py::array::forcecast> pedestal,
py::array_t<DataType, py::array::c_style | py::array::forcecast>
calibration,
int n_threads = 4) {
py::array_t<DataType>
pybind_apply_calibration(py::array_t<uint16_t> data,
py::array_t<DataType> pedestal,
py::array_t<DataType> calibration, int n_threads = 4) {
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);
if (data.ndim() == 3 && pedestal.ndim() == 3 && calibration.ndim() == 3) {
if (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) {
} else if (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");
"Invalid number of dimensions for 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) {
py::array_t<int> pybind_count_switching_pixels(py::array_t<uint16_t> data,
ssize_t n_threads = 4) {
auto data_span = make_view_3d(data);
auto arr = new NDArray<int, 2>{};
@@ -51,9 +47,8 @@ py::array_t<int> pybind_count_switching_pixels(
}
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) {
py::array_t<T> pybind_calculate_pedestal(py::array_t<uint16_t> data,
ssize_t n_threads) {
auto data_span = make_view_3d(data);
auto arr = new NDArray<T, 3>{};
@@ -62,9 +57,8 @@ py::array_t<T> pybind_calculate_pedestal(
}
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) {
py::array_t<T> pybind_calculate_pedestal_g0(py::array_t<uint16_t> data,
ssize_t n_threads) {
auto data_span = make_view_3d(data);
auto arr = new NDArray<T, 2>{};