mirror of
https://github.com/slsdetectorgroup/aare.git
synced 2026-06-06 08:18:42 +02:00
Erik Fröjdh
122 lines
4.7 KiB
C++
122 lines
4.7 KiB
C++
// SPDX-License-Identifier: MPL-2.0
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#include "aare/hist/PixelHistogram.hpp"
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#include "np_helper.hpp"
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#include <cstdint>
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#include <pybind11/numpy.h>
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#include <pybind11/pybind11.h>
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#include <pybind11/stl.h>
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namespace py = pybind11;
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using namespace ::aare;
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void define_pixel_histogram_bindings(py::module &m) {
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py::class_<PixelHistogram>(m, "PixelHistogram",
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"A histogram for pixel-wise statistics")
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.def(py::init<int, int, int, double, double, int, std::size_t>(),
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R"(
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Initialize a PixelHistogram.
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Args:
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rows: Number of rows in the detector
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cols: Number of columns in the detector
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n_bins: Number of histogram bins
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xmin: Minimum value for histogram range
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xmax: Maximum value for histogram range
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n_threads: Number of threads for parallel filling (default: 1)
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max_pending: Maximum number of images that can be queued for
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asynchronous filling before fill_async() applies
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backpressure on the caller (default: 16)
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)",
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py::arg("rows"), py::arg("cols"), py::arg("n_bins"),
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py::arg("xmin"), py::arg("xmax"), py::arg("n_threads") = 1,
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py::arg("max_pending") = std::size_t{16})
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.def(
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"fill_async",
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[](PixelHistogram &self,
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py::array_t<PixelHistogram::AxisType, 0> image) {
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// Copy the numpy buffer into an owned NDArray while we
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// still hold the GIL so we don't depend on the array's
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// backing storage outliving this call.
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auto view = make_view_2d(image);
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NDArray<PixelHistogram::AxisType, 2> owned(view);
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// Release the GIL while enqueueing - fill_async can block
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// on backpressure when the queue is full.
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py::gil_scoped_release release;
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self.fill_async(std::move(owned));
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},
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R"(
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Submit an image for asynchronous filling.
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The image is copied into an internal buffer before this call
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returns, so the caller may mutate or free the numpy array
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immediately. The actual histogram update happens on a
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background thread. If the internal queue is full this call
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blocks (with the GIL released) until a slot becomes available.
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Args:
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image: A 2D numpy array of pixel values (dtype: float32)
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)",
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py::arg("image").noconvert())
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.def("flush", &PixelHistogram::flush,
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R"(
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Block until all images submitted via fill_async() have been
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merged into the accumulators. Cheap when nothing is pending.
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)",
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py::call_guard<py::gil_scoped_release>())
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.def(
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"values",
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[](const PixelHistogram &self) {
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// values() implicitly flushes - release the GIL while it
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// does so. Allocation/copy into the NDArray runs without
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// the GIL too; only the numpy wrapping needs it.
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NDArray<PixelHistogram::StorageType, 3> *ptr = nullptr;
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{
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py::gil_scoped_release release;
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ptr = new NDArray<PixelHistogram::StorageType, 3>(
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self.values());
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}
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return return_image_data(ptr);
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},
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R"(
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Get the histogram data as a numpy array.
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Implicitly flushes any pending asynchronous fills before
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returning, so the snapshot is consistent with everything
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submitted up to this call.
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Returns:
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A 3D numpy array containing the histogram bins for each pixel
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)")
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.def(
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"bin_centers",
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[](const PixelHistogram &self) {
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auto ptr = new NDArray<PixelHistogram::AxisType, 1>(
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self.bin_centers());
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return return_image_data(ptr);
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},
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R"(
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Get the bin centers along the value axis.
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Returns:
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A 1D numpy array containing the center values for each histogram bin
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)")
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.def(
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"bin_edges",
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[](const PixelHistogram &self) {
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auto ptr =
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new NDArray<PixelHistogram::AxisType, 1>(self.bin_edges());
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return return_image_data(ptr);
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},
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R"(
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Get the bin edges along the value axis.
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Returns:
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A 1D numpy array containing the edge values for the histogram bins
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)");
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}
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