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Dev/expose sum 2x2 to python (#238)
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Saverio requested that max_sum_2x2 exposes index information in  python 
- max_sum_2x2 returns a corner as index
- replaced eta corner with corner enum class
- max_sum_2x2 now returns index as well in python 
- added link to Documenation in README

Note: Some Tests fail in EtaCalculation due to previous PR about
updating Eta 2x2 will fix in other PR
This commit is contained in:
mazzol_a
2025-10-27 20:04:16 +01:00
committed by GitHub
parent ac83eeff9b 8989d2eb4a
commit 7fb500c44c
14 changed files with 113 additions and 47 deletions
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4
README.md
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@@ -1,6 +1,10 @@
# aare
Data analysis library for PSI hybrid detectors
## Documentation
Detailed documentation including installation can be found in [Documentation](https://slsdetectorgroup.github.io/aare/)
## Build and install

8
RELEASE.md
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@@ -1,5 +1,13 @@
# Release notes
### 2025.10.27
Features:
- max_sum_2x2 including index of subcluster with highest energy is now available from Python API
- eta stores corner as enum class cTopLeft, cTopRight, BottomLeft, cBottomRight indicating 2x2 subcluster with largest energy relative to cluster center
- max_sum_2x2 returns corner as index
### 2025.10.1
Bugfixes:

16
include/aare/CalculateEta.hpp
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@@ -3,16 +3,10 @@
#include "aare/Cluster.hpp"
#include "aare/ClusterVector.hpp"
#include "aare/NDArray.hpp"
#include "aare/defs.hpp"
namespace aare {
enum class corner : int {
cTopLeft = 0,
cTopRight = 1,
cBottomLeft = 2,
cBottomRight = 3
};
enum class pixel : int {
pBottomLeft = 0,
pBottom = 1,
@@ -28,7 +22,7 @@ enum class pixel : int {
template <typename T> struct Eta2 {
double x;
double y;
int c{0};
corner c{0};
T sum;
};
@@ -66,11 +60,11 @@ calculate_eta2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
(ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
auto max_sum = cl.max_sum_2x2();
eta.sum = max_sum.first;
int c = max_sum.second;
eta.sum = max_sum.sum;
corner c = max_sum.index;
// subcluster top right from center
switch (static_cast<corner>(c)) {
switch (c) {
case (corner::cTopLeft):
if ((cl.data[cluster_center_index - 1] +
cl.data[cluster_center_index]) != 0)

24
include/aare/Cluster.hpp
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@@ -8,6 +8,7 @@
#pragma once
#include "defs.hpp"
#include <algorithm>
#include <array>
#include <cstdint>
@@ -45,7 +46,7 @@ struct Cluster {
* @return photon energy of subcluster, 2x2 subcluster index relative to
* cluster center
*/
std::pair<T, int> max_sum_2x2() const {
Sum_index_pair<T, corner> max_sum_2x2() const {
if constexpr (cluster_size_x == 3 && cluster_size_y == 3) {
std::array<T, 4> sum_2x2_subclusters;
@@ -56,9 +57,11 @@ struct Cluster {
int index = std::max_element(sum_2x2_subclusters.begin(),
sum_2x2_subclusters.end()) -
sum_2x2_subclusters.begin();
return std::make_pair(sum_2x2_subclusters[index], index);
return Sum_index_pair<T, corner>{sum_2x2_subclusters[index],
corner{index}};
} else if constexpr (cluster_size_x == 2 && cluster_size_y == 2) {
return std::make_pair(data[0] + data[1] + data[2] + data[3], 0);
return Sum_index_pair<T, corner>{
data[0] + data[1] + data[2] + data[3], corner{0}};
} else {
constexpr size_t cluster_center_index =
(ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
@@ -97,7 +100,8 @@ struct Cluster {
int index = std::max_element(sum_2x2_subcluster.begin(),
sum_2x2_subcluster.end()) -
sum_2x2_subcluster.begin();
return std::make_pair(sum_2x2_subcluster[index], index);
return Sum_index_pair<T, corner>{sum_2x2_subcluster[index],
corner{index}};
}
}
};
@@ -125,8 +129,8 @@ reduce_to_2x2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &c) {
(ClusterSizeX / 2) + (ClusterSizeY / 2) * ClusterSizeX;
int16_t index_bottom_left_max_2x2_subcluster =
(int(index / (ClusterSizeX - 1))) * ClusterSizeX +
index % (ClusterSizeX - 1);
(int(static_cast<int>(index) / (ClusterSizeX - 1))) * ClusterSizeX +
static_cast<int>(index) % (ClusterSizeX - 1);
result.x =
c.x + (index_bottom_left_max_2x2_subcluster - cluster_center_index) %
@@ -149,22 +153,22 @@ Cluster<T, 2, 2, int16_t> reduce_to_2x2(const Cluster<T, 3, 3, int16_t> &c) {
auto [s, i] = c.max_sum_2x2();
switch (i) {
case 0:
case corner::cTopLeft:
result.x = c.x - 1;
result.y = c.y + 1;
result.data = {c.data[0], c.data[1], c.data[3], c.data[4]};
break;
case 1:
case corner::cTopRight:
result.x = c.x;
result.y = c.y + 1;
result.data = {c.data[1], c.data[2], c.data[4], c.data[5]};
break;
case 2:
case corner::cBottomLeft:
result.x = c.x - 1;
result.y = c.y;
result.data = {c.data[3], c.data[4], c.data[6], c.data[7]};
break;
case 3:
case corner::cBottomRight:
result.x = c.x;
result.y = c.y;
result.data = {c.data[4], c.data[5], c.data[7], c.data[8]};

1
include/aare/ClusterCollector.hpp
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@@ -5,6 +5,7 @@
#include "aare/ClusterFinderMT.hpp"
#include "aare/ClusterVector.hpp"
#include "aare/ProducerConsumerQueue.hpp"
#include "aare/defs.hpp"
namespace aare {

4
include/aare/ClusterFile.hpp
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@@ -453,8 +453,8 @@ bool ClusterFile<ClusterType, Enable>::is_selected(ClusterType &cl) {
if (m_noise_map) {
auto sum_1x1 = cl.data[cluster_center_index]; // central pixel
auto sum_2x2 = cl.max_sum_2x2().first; // highest sum of 2x2 subclusters
auto total_sum = cl.sum(); // sum of all pixels
auto sum_2x2 = cl.max_sum_2x2().sum; // highest sum of 2x2 subclusters
auto total_sum = cl.sum(); // sum of all pixels
auto noise =
(*m_noise_map)(cl.y, cl.x); // TODO! check if this is correct

13
include/aare/ClusterVector.hpp
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@@ -86,15 +86,14 @@ class ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>> {
/**
* @brief Sum the pixels in the 2x2 subcluster with the biggest pixel sum in
* each cluster
* @return std::vector<T> vector of sums for each cluster
* @return vector of sums index pairs for each cluster
*/
std::vector<T> sum_2x2() {
std::vector<T> sums_2x2(m_data.size());
std::vector<Sum_index_pair<T, corner>> sum_2x2() {
std::vector<Sum_index_pair<T, corner>> sums_2x2(m_data.size());
std::transform(m_data.begin(), m_data.end(), sums_2x2.begin(),
[](const ClusterType &cluster) {
return cluster.max_sum_2x2().first;
});
std::transform(
m_data.begin(), m_data.end(), sums_2x2.begin(),
[](const ClusterType &cluster) { return cluster.max_sum_2x2(); });
return sums_2x2;
}

13
include/aare/defs.hpp
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@@ -331,6 +331,19 @@ enum DACIndex {
SLOW_ADC_TEMP
};
// helper pair class to easily expose in python
template <typename T1, typename T2> struct Sum_index_pair {
T1 sum;
T2 index;
};
enum class corner : int {
cTopLeft = 0,
cTopRight = 1,
cBottomLeft = 2,
cBottomRight = 3
};
enum class TimingMode { Auto, Trigger };
enum class FrameDiscardPolicy { NoDiscard, Discard, DiscardPartial };

12
python/src/bind_Cluster.hpp
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@@ -58,7 +58,17 @@ void define_Cluster(py::module &m, const std::string &typestr) {
&Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>::x)
.def_readonly("y",
&Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>::y);
&Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>::y)
.def(
"max_sum_2x2",
[](Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType> &self) {
auto max_sum = self.max_sum_2x2();
return py::make_tuple(max_sum.sum,
static_cast<int>(max_sum.index));
},
R"(calculates sum of 2x2 subcluster with highest energy and index relative to cluster center 0: top_left, 1: top_right, 2: bottom_left, 3: bottom_right
)");
}
template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,

15
python/src/bind_ClusterVector.hpp
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@@ -44,11 +44,16 @@ void define_ClusterVector(py::module &m, const std::string &typestr) {
auto *vec = new std::vector<Type>(self.sum());
return return_vector(vec);
})
.def("sum_2x2",
[](ClusterVector<ClusterType> &self) {
auto *vec = new std::vector<Type>(self.sum_2x2());
return return_vector(vec);
})
.def(
"sum_2x2",
[](ClusterVector<ClusterType> &self) {
auto *vec = new std::vector<Sum_index_pair<Type, corner>>(
self.sum_2x2());
return return_vector(vec);
},
R"(calculates sum of 2x2 subcluster with highest energy and index relative to cluster center 0: top_left, 1: top_right, 2: bottom_left, 3: bottom_right
)")
.def_property_readonly("size", &ClusterVector<ClusterType>::size)
.def("item_size", &ClusterVector<ClusterType>::item_size)
.def_property_readonly("fmt",

7
python/src/module.cpp
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@@ -114,4 +114,11 @@ PYBIND11_MODULE(_aare, m) {
reduce_to_3x3<int, 9, 9, uint16_t>(m);
reduce_to_3x3<double, 9, 9, uint16_t>(m);
reduce_to_3x3<float, 9, 9, uint16_t>(m);
using Sum_index_pair_d = Sum_index_pair<double, corner>;
PYBIND11_NUMPY_DTYPE(Sum_index_pair_d, sum, index);
using Sum_index_pair_f = Sum_index_pair<float, corner>;
PYBIND11_NUMPY_DTYPE(Sum_index_pair_f, sum, index);
using Sum_index_pair_i = Sum_index_pair<int, corner>;
PYBIND11_NUMPY_DTYPE(Sum_index_pair_i, sum, index);
}

11
python/tests/test_Cluster.py
View File

@@ -86,6 +86,17 @@ def test_calculate_eta():
assert eta2[1,0] == 0.5
assert eta2[1,1] == 0.4 #2/5
def test_max_sum():
"""Max 2x2 Sum"""
cluster = _aare.Cluster3x3i(5,5,np.array([1, 1, 1, 2, 3, 1, 2, 2, 1], dtype=np.int32))
max_sum = cluster.max_sum_2x2()
assert max_sum[0] == 9
assert max_sum[1] == 2
def test_cluster_finder():
"""Test ClusterFinder"""

12
python/tests/test_ClusterVector.py
View File

@@ -32,6 +32,18 @@ def test_push_back_on_cluster_vector():
assert arr[0]['y'] == 22
def test_max_2x2_sum():
"""max_2x2_sum"""
cv = _aare.ClusterVector_Cluster3x3i()
cv.push_back(_aare.Cluster3x3i(19, 22, np.array([0,1,0,2,3,0,2,1,0], dtype=np.int32)))
cv.push_back(_aare.Cluster3x3i(19, 22, np.ones(9, dtype=np.int32)))
assert cv.size == 2
max_2x2 = cv.sum_2x2()
assert max_2x2.size == 2
assert max_2x2[0]["sum"] == 8
assert max_2x2[0]["index"] == 2
def test_make_a_hitmap_from_cluster_vector():
cv = _aare.ClusterVector_Cluster3x3i()

20
src/CalculateEta.test.cpp
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@@ -21,22 +21,20 @@ using ClusterTypes =
auto get_test_parameters() {
return GENERATE(
std::make_tuple(ClusterTypes{Cluster<int, 2, 2>{0, 0, {1, 2, 3, 1}}},
Eta2<int>{2. / 3, 3. / 4,
static_cast<int>(corner::cBottomLeft), 7}),
Eta2<int>{2. / 3, 3. / 4, corner::cTopLeft, 7}),
std::make_tuple(
ClusterTypes{Cluster<int, 3, 3>{0, 0, {1, 2, 3, 4, 5, 6, 1, 2, 7}}},
Eta2<int>{6. / 11, 2. / 7, static_cast<int>(corner::cTopRight),
20}),
Eta2<int>{6. / 11, 2. / 7, corner::cBottomRight, 20}),
std::make_tuple(ClusterTypes{Cluster<int, 5, 5>{
0, 0, {1, 6, 7, 6, 5, 4, 3, 2, 1, 2, 8, 9, 8,
1, 4, 5, 6, 7, 8, 4, 1, 1, 1, 1, 1}}},
Eta2<int>{8. / 17, 7. / 15, 9, 30}),
0, 0, {1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 9, 8,
1, 4, 1, 6, 7, 8, 1, 1, 1, 1, 1, 1}}},
Eta2<int>{8. / 17, 7. / 15, corner::cBottomLeft, 30}),
std::make_tuple(
ClusterTypes{Cluster<int, 4, 2>{0, 0, {1, 4, 7, 2, 5, 6, 4, 3}}},
Eta2<int>{4. / 10, 4. / 11, 1, 21}),
Eta2<int>{4. / 10, 4. / 11, corner::cTopLeft, 21}),
std::make_tuple(
ClusterTypes{Cluster<int, 2, 3>{0, 0, {1, 3, 2, 3, 4, 2}}},
Eta2<int>{3. / 5, 2. / 5, 1, 11}));
Eta2<int>{3. / 5, 2. / 5, corner::cBottomLeft, 11}));
}
TEST_CASE("compute_largest_2x2_subcluster", "[eta_calculation]") {
@@ -91,7 +89,7 @@ TEST_CASE("Calculate eta2 for a 3x3 int32 cluster with the largest 2x2 sum in "
// 30, 23, 5
auto eta = calculate_eta2(cl);
CHECK(eta.c == static_cast<int>(corner::cBottomLeft));
CHECK(eta.c == corner::cBottomLeft);
CHECK(eta.x == 50.0 / (20 + 50)); // 4/(3+4)
CHECK(eta.y == 50.0 / (23 + 50)); // 4/(1+4)
CHECK(eta.sum == 30 + 23 + 20 + 50);
@@ -120,7 +118,7 @@ TEST_CASE("Calculate eta2 for a 3x3 int32 cluster with the largest 2x2 sum in "
// 8, 12, 5
auto eta = calculate_eta2(cl);
CHECK(eta.c == static_cast<int>(corner::cTopLeft));
CHECK(eta.c == corner::cTopLeft);
CHECK(eta.x == 80. / (77 + 80)); // 4/(3+4)
CHECK(eta.y == 91.0 / (91 + 80)); // 7/(7+4)
CHECK(eta.sum == 77 + 80 + 82 + 91);