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Fix/clusterfinder test (#359)
- fixed test in ClusterFinderMT (use minimum one pedestal to accumulate dummy pedestal) - added minimum_pedestal_samples as additional constructor argument in ClusterFinder and ClusterFinderMT - bugfix: race conditions for empty queues in collect() - check directly when needed
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@@ -18,24 +18,55 @@ def _get_class(name, cluster_size, dtype):
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def ClusterFinder(image_size, cluster_size=(3,3), n_sigma=5, dtype = np.int32, capacity = 1024):
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def ClusterFinder(image_size, *, cluster_size=(3,3), n_sigma=5, dtype = np.int32, capacity = 1024, min_pedestal_samples = 1000):
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"""
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Factory function to create a ClusterFinder object. Provides a cleaner syntax for
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the templated ClusterFinder in C++.
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Parameters
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----------
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image_size : tuple
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The size of the image as a tuple (height, width).
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cluster_size : tuple, optional
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The size of the cluster to find as a tuple (height, width). Default is (3,3).
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n_sigma : int, optional
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Multiplier of the standard deviation used as a threshold to identify potential photon pixels. Default is 5.
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dtype : data-type, optional
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The data type of the image. Default is np.int32.
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capacity : int, optional
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The maximum number of clusters than can be stored before reallocating. Default is 1024.
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min_pedestal_samples : int, optional
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The minimum number of pedestal samples to accumulate before using the pedestal. Default is 1000.
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"""
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cls = _get_class("ClusterFinder", cluster_size, dtype)
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return cls(image_size, n_sigma=n_sigma, capacity=capacity)
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return cls(image_size, n_sigma=n_sigma, capacity=capacity, min_pedestal_samples=min_pedestal_samples)
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def ClusterFinderMT(image_size, cluster_size = (3,3), dtype=np.int32, n_sigma=5, capacity = 1024, n_threads = 3):
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def ClusterFinderMT(image_size, *, cluster_size = (3,3), dtype=np.int32, n_sigma=5, capacity = 1024, n_threads = 3, min_pedestal_samples = 1000):
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"""
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Factory function to create a ClusterFinderMT object. Provides a cleaner syntax for
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the templated ClusterFinderMT in C++.
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Parameters
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----------
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image_size : tuple
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The size of the image as a tuple (height, width).
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cluster_size : tuple, optional
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The size of the cluster to find as a tuple (height, width). Default is (3,3).
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n_sigma : int, optional
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Multiplier of the standard deviation used as a threshold to identify potential photon pixels. Default is 5.
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dtype : data-type, optional
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The data type of the image. Default is np.int32.
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capacity : int, optional
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The maximum number of clusters than can be stored before reallocating. Default is 1024.
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n_threads : int, optional
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The number of threads to use for processing. Default is 3.
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min_pedestal_samples : int, optional
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The minimum number of pedestal samples to accumulate before using the pedestal. Default is 1000.
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"""
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cls = _get_class("ClusterFinderMT", cluster_size, dtype)
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return cls(image_size, n_sigma=n_sigma, capacity=capacity, n_threads=n_threads)
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return cls(image_size, n_sigma=n_sigma, capacity=capacity, min_pedestal_samples=min_pedestal_samples, n_threads=n_threads)
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def ClusterCollector(clusterfindermt, dtype=np.int32):
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@@ -32,8 +32,10 @@ void define_ClusterFinder(py::module &m, const std::string &typestr) {
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py::class_<ClusterFinder<ClusterType, uint16_t, pd_type>>(
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m, class_name.c_str())
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.def(py::init<Shape<2>, pd_type, size_t>(), py::arg("image_size"),
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py::arg("n_sigma") = 5.0, py::arg("capacity") = 1'000'000)
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.def(py::init<Shape<2>, pd_type, size_t, size_t>(),
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py::arg("image_size"), py::arg("n_sigma") = 5.0,
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py::arg("capacity") = 1'000'000,
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py::arg("min_pedestal_samples") = 1000)
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.def_property(
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"nSigma",
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@@ -32,10 +32,11 @@ void define_ClusterFinderMT(py::module &m, const std::string &typestr) {
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py::class_<ClusterFinderMT<ClusterType, uint16_t, pd_type>>(
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m, class_name.c_str())
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.def(py::init<Shape<2>, pd_type, size_t, size_t, size_t>(),
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.def(py::init<Shape<2>, pd_type, size_t, size_t, size_t, size_t>(),
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py::arg("image_size"), py::arg("n_sigma") = 5.0,
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py::arg("capacity") = 2048, py::arg("n_threads") = 3,
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py::arg("queue_depth") = 16)
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py::arg("queue_depth") = 16,
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py::arg("min_pedestal_samples") = 1000)
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.def("push_pedestal_frame",
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[](ClusterFinderMT<ClusterType, uint16_t, pd_type> &self,
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py::array_t<uint16_t> frame) {
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