reduction tests for python

include/aare/CalculateEta.hpp

@@ -28,7 +28,7 @@ enum class pixel : int {
 template <typename T> struct Eta2 {
     double x;
     double y;
-    int c;
+    int c{0};
     T sum;
 };
 
@@ -70,6 +70,8 @@ calculate_eta2(const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
     size_t index_bottom_left_max_2x2_subcluster =
         (int(c / (ClusterSizeX - 1))) * ClusterSizeX + c % (ClusterSizeX - 1);
 
+    // calculate direction of gradient
+
     // check that cluster center is in max subcluster
     if (cluster_center_index != index_bottom_left_max_2x2_subcluster &&
         cluster_center_index != index_bottom_left_max_2x2_subcluster + 1 &&
@@ -128,12 +130,15 @@ Eta2<T> calculate_eta2(const Cluster<T, 2, 2, int16_t> &cl) {
     Eta2<T> eta{};
 
     if ((cl.data[0] + cl.data[1]) != 0)
-        eta.x = static_cast<double>(cl.data[1]) / (cl.data[0] + cl.data[1]);
+        eta.x = static_cast<double>(cl.data[1]) /
+                (cl.data[0] + cl.data[1]); // between (0,1) the closer to zero
+                                           // left value probably larger
     if ((cl.data[0] + cl.data[2]) != 0)
-        eta.y = static_cast<double>(cl.data[2]) / (cl.data[0] + cl.data[2]);
+        eta.y = static_cast<double>(cl.data[2]) /
+                (cl.data[0] + cl.data[2]); // between (0,1) the closer to zero
+                                           // bottom value probably larger
     eta.sum = cl.sum();
-    eta.c = static_cast<int>(corner::cBottomLeft); // TODO! This is not correct,
+
-                                                   // but need to put something
     return eta;
 }
 
@@ -150,13 +155,11 @@ template <typename T> Eta2<T> calculate_eta3(const Cluster<T, 3, 3> &cl) {
 
     eta.sum = sum;
 
-    eta.c = corner::cBottomLeft;
-
     if ((cl.data[3] + cl.data[4] + cl.data[5]) != 0)
 
         eta.x = static_cast<double>(-cl.data[3] + cl.data[3 + 2]) /
 
-                (cl.data[3] + cl.data[4] + cl.data[5]);
+                (cl.data[3] + cl.data[4] + cl.data[5]); // (-1,1)
 
     if ((cl.data[1] + cl.data[4] + cl.data[7]) != 0)
 

python/aare/__init__.py

@@ -17,7 +17,7 @@ from .ClusterVector import ClusterVector
 from ._aare import fit_gaus, fit_pol1, fit_scurve, fit_scurve2
 from ._aare import Interpolator
 from ._aare import calculate_eta2
-
+from ._aare import reduce_to_2x2, reduce_to_3x3
 
 from ._aare import apply_custom_weights
 

python/src/bind_Cluster.hpp

@@ -34,31 +34,54 @@ void define_Cluster(py::module &m, const std::string &typestr) {
                 cluster.data[i] = r(i);
             }
             return cluster;
-        }));
+        }))
 
-    /*
+        // TODO! Review if to keep or not
-    //TODO! Review if to keep or not
+        .def_property_readonly(
-    .def_property(
+            "data",
-        "data",
+            [](Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType> &c)
-        [](ClusterType &c) -> py::array {
+                -> py::array {
-            return py::array(py::buffer_info(
+                return py::array(py::buffer_info(
-                c.data, sizeof(Type),
+                    c.data.data(), sizeof(Type),
-                py::format_descriptor<Type>::format(), // Type
+                    py::format_descriptor<Type>::format(), // Type
-                                                       // format
+                                                           // format
-                1, // Number of dimensions
+                    2, // Number of dimensions
-                {static_cast<ssize_t>(ClusterSizeX *
+                    {static_cast<ssize_t>(ClusterSizeX),
-                                      ClusterSizeY)}, // Shape (flattened)
+                     static_cast<ssize_t>(ClusterSizeY)}, // Shape (flattened)
-                {sizeof(Type)} // Stride (step size between elements)
+                    {sizeof(Type) * ClusterSizeY, sizeof(Type)}
-                ));
+                    // Stride (step size between elements)
+                    ));
+            })
+
+        .def_readonly("x",
+                      &Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>::x)
+
+        .def_readonly("y",
+                      &Cluster<Type, ClusterSizeX, ClusterSizeY, CoordType>::y);
+}
+
+template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
+          typename CoordType = int16_t>
+void reduce_to_3x3(py::module &m) {
+
+    m.def(
+        "reduce_to_3x3",
+        [](const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
+            return reduce_to_3x3(cl);
         },
-        [](ClusterType &c, py::array_t<Type> arr) {
+        py::return_value_policy::move);
-            py::buffer_info buf_info = arr.request();
+}
-            Type *ptr = static_cast<Type *>(buf_info.ptr);
-            std::copy(ptr, ptr + ClusterSizeX * ClusterSizeY,
-                      c.data); // TODO dont iterate over centers!!!
 
-        });
+template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
-    */
+          typename CoordType = int16_t>
+void reduce_to_2x2(py::module &m) {
+
+    m.def(
+        "reduce_to_2x2",
+        [](const Cluster<T, ClusterSizeX, ClusterSizeY, CoordType> &cl) {
+            return reduce_to_2x2(cl);
+        },
+        py::return_value_policy::move);
 }
 
 #pragma GCC diagnostic pop

python/src/module.cpp

@@ -48,7 +48,8 @@ double, 'f' for float)
     define_ClusterCollector<T, N, M, U>(m, "Cluster" #N "x" #M #TYPE_CODE);    \
     define_Cluster<T, N, M, U>(m, #N "x" #M #TYPE_CODE);                       \
     register_calculate_eta<T, N, M, U>(m);                                     \
-    define_2x2_reduction<T, N, M, U>(m);
+    define_2x2_reduction<T, N, M, U>(m);                                       \
+    reduce_to_2x2<T, N, M, U>(m);
 
 PYBIND11_MODULE(_aare, m) {
     define_file_io_bindings(m);
@@ -86,16 +87,29 @@ PYBIND11_MODULE(_aare, m) {
     DEFINE_CLUSTER_BINDINGS(double, 9, 9, uint16_t, d);
     DEFINE_CLUSTER_BINDINGS(float, 9, 9, uint16_t, f);
 
-    define_3x3_reduction<int, 3, 3>(m);
+    define_3x3_reduction<int, 3, 3, uint16_t>(m);
-    define_3x3_reduction<double, 3, 3>(m);
+    define_3x3_reduction<double, 3, 3, uint16_t>(m);
-    define_3x3_reduction<float, 3, 3>(m);
+    define_3x3_reduction<float, 3, 3, uint16_t>(m);
-    define_3x3_reduction<int, 5, 5>(m);
+    define_3x3_reduction<int, 5, 5, uint16_t>(m);
-    define_3x3_reduction<double, 5, 5>(m);
+    define_3x3_reduction<double, 5, 5, uint16_t>(m);
-    define_3x3_reduction<float, 5, 5>(m);
+    define_3x3_reduction<float, 5, 5, uint16_t>(m);
-    define_3x3_reduction<int, 7, 7>(m);
+    define_3x3_reduction<int, 7, 7, uint16_t>(m);
-    define_3x3_reduction<double, 7, 7>(m);
+    define_3x3_reduction<double, 7, 7, uint16_t>(m);
-    define_3x3_reduction<float, 7, 7>(m);
+    define_3x3_reduction<float, 7, 7, uint16_t>(m);
-    define_3x3_reduction<int, 9, 9>(m);
+    define_3x3_reduction<int, 9, 9, uint16_t>(m);
-    define_3x3_reduction<double, 9, 9>(m);
+    define_3x3_reduction<double, 9, 9, uint16_t>(m);
-    define_3x3_reduction<float, 9, 9>(m);
+    define_3x3_reduction<float, 9, 9, uint16_t>(m);
+
+    reduce_to_3x3<int, 3, 3, uint16_t>(m);
+    reduce_to_3x3<double, 3, 3, uint16_t>(m);
+    reduce_to_3x3<float, 3, 3, uint16_t>(m);
+    reduce_to_3x3<int, 5, 5, uint16_t>(m);
+    reduce_to_3x3<double, 5, 5, uint16_t>(m);
+    reduce_to_3x3<float, 5, 5, uint16_t>(m);
+    reduce_to_3x3<int, 7, 7, uint16_t>(m);
+    reduce_to_3x3<double, 7, 7, uint16_t>(m);
+    reduce_to_3x3<float, 7, 7, uint16_t>(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);
 }

python/tests/test_Cluster.py

@@ -101,6 +101,27 @@ def test_cluster_finder():
     assert clusters.size == 0
 
 
+def test_2x2_reduction(): 
+    """Test 2x2 Reduction"""
+    cluster = _aare.Cluster3x3i(5,5,np.array([1, 1, 1, 2, 3, 1, 2, 2, 1], dtype=np.int32))
+
+    reduced_cluster = _aare.reduce_to_2x2(cluster) 
+
+    assert reduced_cluster.x == 4
+    assert reduced_cluster.y == 5
+    assert (reduced_cluster.data == np.array([[2, 3], [2, 2]], dtype=np.int32)).all()
+    
+    
+def test_3x3_reduction(): 
+    """Test 3x3 Reduction"""
+    cluster = _aare.Cluster5x5d(5,5,np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0,
+                                   1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], dtype=np.double))
+
+    reduced_cluster = _aare.reduce_to_3x3(cluster) 
+
+    assert reduced_cluster.x == 4
+    assert reduced_cluster.y == 5
+    assert (reduced_cluster.data == np.array([[1.0, 2.0, 1.0], [2.0, 2.0, 3.0], [1.0, 2.0, 1.0]], dtype=np.double)).all()
 
 
 

python/tests/test_ClusterVector.py

@@ -5,7 +5,7 @@ import time
 from pathlib import Path
 import pickle
 
-from aare import ClusterFile
+from aare import ClusterFile, ClusterVector
 from aare import _aare
 from conftest import test_data_path
 
@@ -51,4 +51,36 @@ def test_make_a_hitmap_from_cluster_vector():
     # print(img)
     # print(ref)
     assert (img == ref).all()
-    
+
+
+def test_2x2_reduction(): 
+    cv = ClusterVector((3,3))
+
+    cv.push_back(_aare.Cluster3x3i(5, 5, np.array([1, 1, 1, 2, 3, 1, 2, 2, 1], dtype=np.int32)))
+    cv.push_back(_aare.Cluster3x3i(5, 5, np.array([2, 2, 1, 2, 3, 1, 1, 1, 1], dtype=np.int32)))
+
+    reduced_cv = np.array(_aare.reduce_to_2x2(cv), copy=False) 
+
+    assert reduced_cv.size == 2
+    assert reduced_cv[0]["x"] == 4
+    assert reduced_cv[0]["y"] == 5
+    assert (reduced_cv[0]["data"] == np.array([[2, 3], [2, 2]], dtype=np.int32)).all()
+    assert reduced_cv[1]["x"] == 4
+    assert reduced_cv[1]["y"] == 6
+    assert (reduced_cv[1]["data"] == np.array([[2, 2], [2, 3]], dtype=np.int32)).all()
+    
+    
+def test_3x3_reduction(): 
+    cv = _aare.ClusterVector_Cluster5x5d()
+    
+    cv.push_back(_aare.Cluster5x5d(5,5,np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0,
+                                   1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], dtype=np.double)))
+    cv.push_back(_aare.Cluster5x5d(5,5,np.array([1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0,
+                                   1.0, 1.0, 1.0, 2.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], dtype=np.double)))
+    
+    reduced_cv = np.array(_aare.reduce_to_3x3(cv), copy=False)  
+
+    assert reduced_cv.size == 2
+    assert reduced_cv[0]["x"] == 4
+    assert reduced_cv[0]["y"] == 5
+    assert (reduced_cv[0]["data"] == np.array([[1.0, 2.0, 1.0], [2.0, 2.0, 3.0], [1.0, 2.0, 1.0]], dtype=np.double)).all()

src/Cluster.test.cpp

@@ -65,7 +65,7 @@ TEST_CASE("Test reduce to 2x2 Cluster", "[.cluster]") {
                      expected_reduced_cluster.data.begin()));
 }
 
-TEST_CASE("Test reduce to 3x3 Clsuter", "[.cluster]") {
+TEST_CASE("Test reduce to 3x3 Cluster", "[.cluster]") {
     auto [cluster, expected_reduced_cluster] = GENERATE(
         std::make_tuple(ClusterTypesLargerThan2x2{Cluster<int, 3, 3>{
                             5, 5, {1, 1, 1, 1, 3, 1, 1, 1, 1}}},