added template for making views (#377)
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Cleaned up the helper functions by: 
- Added template for make_view (and new make_const_view) instead of the
copy paste implementation
- checks c_style and dimensions inside make_view
- test binding to be able to probe the checks in make_view

Call sites can be reviewed in a second PR since usage of const or
strictness of conversion depends...
This commit is contained in:
Erik Fröjdh
2026-09-22 09:25:42 +02:00
committed by GitHub
parent cbc4864e93
commit 752ec38596
6 changed files with 189 additions and 22 deletions
-3
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@@ -48,9 +48,6 @@ void define_ClusterVector(py::module &m, const std::string &typestr) {
"__call__",
[](ClusterVector<ClusterType> &self,
py::array_t<bool, py::array::c_style> mask) {
if (mask.ndim() != 1) {
throw py::value_error("Mask must be one-dimensional");
}
return self(make_view_1d(mask));
},
py::arg("mask").noconvert(), R"doc(
+65
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@@ -0,0 +1,65 @@
// SPDX-License-Identifier: MPL-2.0
// Probes used by the python test-suite to exercise the helpers in
// np_helper.hpp. Internal, no API guarantees.
#pragma once
#include "aare/NDArray.hpp"
#include "aare/NDView.hpp"
#include "np_helper.hpp"
#include <algorithm>
#include <cstdint>
#include <pybind11/numpy.h>
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
#include <type_traits>
namespace py = pybind11;
using namespace ::aare;
// Arrays are taken with the default flags (no c_style) so that nothing is
// made contiguous by pybind11 before it reaches make_view
template <typename T, ssize_t Ndim>
void define_make_view_probes(py::module &m, const std::string &suffix) {
// Copy what C++ sees through the view back to python
m.def(("view_roundtrip_" + suffix).c_str(),
[](py::array_t<T> arr) {
auto view = make_view<Ndim>(arr);
return return_image_data(new NDArray<T, Ndim>(view));
},
py::arg("arr").noconvert());
// Same as above but through a read only view
m.def(("const_view_roundtrip_" + suffix).c_str(),
[](py::array_t<T> arr) {
auto view = make_const_view<Ndim>(arr);
static_assert(
std::is_same_v<decltype(view), NDView<const T, Ndim>>);
auto out = new NDArray<T, Ndim>(view.shape());
std::copy(view.begin(), view.end(), out->begin());
return return_image_data(out);
},
py::arg("arr").noconvert());
// Write through the view
m.def(("view_fill_" + suffix).c_str(),
[](py::array_t<T> arr, T value) {
auto view = make_view<Ndim>(arr);
view = value;
},
py::arg("arr").noconvert(), py::arg("value"));
}
void define_testing_bindings(py::module &m) {
auto testing = m.def_submodule(
"testing", "Internal helpers for the test-suite, no API guarantees");
// noconvert + overloads gives dispatch on dtype
define_make_view_probes<double, 1>(testing, "1d");
define_make_view_probes<double, 2>(testing, "2d");
define_make_view_probes<double, 3>(testing, "3d");
define_make_view_probes<uint16_t, 1>(testing, "1d");
define_make_view_probes<uint16_t, 2>(testing, "2d");
define_make_view_probes<uint16_t, 3>(testing, "3d");
}
+2
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@@ -22,6 +22,7 @@
#include "bind_PixelMap.hpp"
#include "bind_RawFile.hpp"
#include "bind_calibration.hpp"
#include "bind_testing.hpp"
// TODO! migrate the other names
#include "ctb_raw_file.hpp"
@@ -88,6 +89,7 @@ PYBIND11_MODULE(_aare, m) {
define_jungfrau_data_file_io_bindings(m);
bind_calibration(m);
define_testing_bindings(m);
DEFINE_CLUSTER_BINDINGS(int, 3, 3, uint16_t, i);
DEFINE_CLUSTER_BINDINGS(double, 3, 3, uint16_t, d);
+47 -18
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@@ -41,31 +41,60 @@ template <typename T> py::array return_vector(std::vector<T> *vec) {
free_when_done); // numpy array references this parent
}
// todo rewrite generic
template <class T, int Flags>
auto get_shape_3d(const py::array_t<T, Flags> &arr) {
return aare::Shape<3>{arr.shape(0), arr.shape(1), arr.shape(2)};
// Create a NDView of a numpy array. NDView assumes C-order strides so we
// reject anything that is not Ndim dimensional and C-contiguous instead of
// silently reading the data in the wrong order.
template <ssize_t Ndim, class T, int Flags>
auto get_checked_shape(const py::array_t<T, Flags> &arr) {
if (arr.ndim() != Ndim) {
throw py::value_error(
fmt::format("Expected {}D array, got {}D", Ndim, arr.ndim()));
}
if (!(arr.flags() & py::array::c_style)) {
throw py::value_error(
"Array is not C-contiguous. Use np.ascontiguousarray(arr)");
}
aare::Shape<Ndim> shape{};
for (ssize_t i = 0; i < Ndim; ++i) {
shape[i] = arr.shape(i);
}
return shape;
}
template <ssize_t Ndim, class T, int Flags>
auto make_view(py::array_t<T, Flags> &arr) {
auto shape = get_checked_shape<Ndim>(arr);
return aare::NDView<T, Ndim>(arr.mutable_data(), shape);
}
// Read only view, also works for numpy arrays that are not writeable
template <ssize_t Ndim, class T, int Flags>
auto make_const_view(const py::array_t<T, Flags> &arr) {
auto shape = get_checked_shape<Ndim>(arr);
return aare::NDView<const T, Ndim>(arr.data(), shape);
}
template <class T, int Flags> auto make_view_3d(py::array_t<T, Flags> &arr) {
return aare::NDView<T, 3>(arr.mutable_data(), get_shape_3d<T, Flags>(arr));
return make_view<3>(arr);
}
template <class T, int Flags>
auto get_shape_2d(const py::array_t<T, Flags> &arr) {
return aare::Shape<2>{arr.shape(0), arr.shape(1)};
}
template <class T, int Flags>
auto get_shape_1d(const py::array_t<T, Flags> &arr) {
return aare::Shape<1>{arr.shape(0)};
}
template <class T, int Flags> auto make_view_2d(py::array_t<T, Flags> &arr) {
return aare::NDView<T, 2>(arr.mutable_data(), get_shape_2d<T, Flags>(arr));
return make_view<2>(arr);
}
template <class T, int Flags> auto make_view_1d(py::array_t<T, Flags> &arr) {
return aare::NDView<T, 1>(arr.mutable_data(), get_shape_1d<T, Flags>(arr));
return make_view<1>(arr);
}
template <class T, int Flags>
auto make_const_view_3d(const py::array_t<T, Flags> &arr) {
return make_const_view<3>(arr);
}
template <class T, int Flags>
auto make_const_view_2d(const py::array_t<T, Flags> &arr) {
return make_const_view<2>(arr);
}
template <class T, int Flags>
auto make_const_view_1d(const py::array_t<T, Flags> &arr) {
return make_const_view<1>(arr);
}
template <typename ClusterType> struct fmt_format_trait; // forward declaration