frame nr and checks on mask

RELEASE.md

@@ -19,6 +19,9 @@
 ### Bugfixes:
 - Fixed ``ClusterVector`` move operations to transfer storage instead of
   copying every cluster.
+- Validate that ``ClusterVector`` masks are one-dimensional, C-contiguous
+  Boolean arrays.
+- Preserve ``ClusterVector`` frame numbers when reducing cluster dimensions.
 - Fixed broken reading of old (pre reordering) Moench03
 
 ## 2026.7.2
@@ -168,5 +171,3 @@ dhanya.thattil@psi.ch
 
 
 
-
-

include/aare/ClusterVector.hpp

@@ -194,7 +194,8 @@ template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
 ClusterVector<Cluster<T, 2, 2, CoordType>> reduce_to_2x2(
     const ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>
         &cv) {
-    ClusterVector<Cluster<T, 2, 2, CoordType>> result;
+    ClusterVector<Cluster<T, 2, 2, CoordType>> result(cv.size(),
+                                                      cv.frame_number());
     for (const auto &c : cv) {
         result.push_back(reduce_to_2x2(c));
     }
@@ -211,7 +212,8 @@ template <typename T, uint8_t ClusterSizeX, uint8_t ClusterSizeY,
 ClusterVector<Cluster<T, 3, 3, CoordType>> reduce_to_3x3(
     const ClusterVector<Cluster<T, ClusterSizeX, ClusterSizeY, CoordType>>
         &cv) {
-    ClusterVector<Cluster<T, 3, 3, CoordType>> result;
+    ClusterVector<Cluster<T, 3, 3, CoordType>> result(cv.size(),
+                                                      cv.frame_number());
     for (const auto &c : cv) {
         result.push_back(reduce_to_3x3(c));
     }

python/src/bind_ClusterVector.hpp

@@ -37,10 +37,14 @@ void define_ClusterVector(py::module &m, const std::string &typestr) {
 
         .def(
             "__call__",
-            [](ClusterVector<ClusterType> &self, py::array_t<bool> mask) {
+            [](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"), R"(
+            py::arg("mask").noconvert(), R"(
             Create a copy of the clustervector and apply a boolean mask to the ClusterVector.
 
             Parameters

python/tests/test_ClusterVector.py

@@ -83,12 +83,15 @@ def test_make_a_hitmap_from_cluster_vector():
 
 def test_2x2_reduction(): 
     cv = ClusterVector((3,3))
+    cv.frame_number = 135
 
     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) 
+    reduced = _aare.reduce_to_2x2(cv)
+    reduced_cv = np.array(reduced, copy=False)
 
+    assert reduced.frame_number == cv.frame_number
     assert reduced_cv.size == 2
     assert reduced_cv[0]["x"] == 5
     assert reduced_cv[0]["y"] == 5
@@ -100,14 +103,17 @@ def test_2x2_reduction():
     
 def test_3x3_reduction(): 
     cv = _aare.ClusterVector_Cluster5x5d()
+    cv.frame_number = 246
     
     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)  
+    reduced = _aare.reduce_to_3x3(cv)
+    reduced_cv = np.array(reduced, copy=False)
 
+    assert reduced.frame_number == cv.frame_number
     assert reduced_cv.size == 2
     assert reduced_cv[0]["x"] == 5
     assert reduced_cv[0]["y"] == 5
@@ -130,3 +136,26 @@ def test_masking():
     assert cv_masked_array[0]["x"] == 1
     assert cv_masked_array[0]["y"] == 2
     assert (cv_masked_array[0]["data"] == np.ones((3,3),dtype=np.int32)).all()
+
+
+def test_masking_requires_c_contiguous_array():
+    cv = _aare.ClusterVector_Cluster3x3i()
+    cv.push_back(_aare.Cluster3x3i(1, 2, np.ones(9, dtype=np.int32)))
+    cv.push_back(_aare.Cluster3x3i(3, 4, np.ones(9, dtype=np.int32)))
+
+    mask = np.array([True, False, True, False], dtype=bool)[::2]
+    assert not mask.flags.c_contiguous
+
+    with pytest.raises(TypeError):
+        cv(mask)
+
+
+def test_masking_requires_one_dimension():
+    cv = _aare.ClusterVector_Cluster3x3i()
+    cv.push_back(_aare.Cluster3x3i(1, 2, np.ones(9, dtype=np.int32)))
+    cv.push_back(_aare.Cluster3x3i(3, 4, np.ones(9, dtype=np.int32)))
+
+    mask = np.array([[True, False]], dtype=bool)
+
+    with pytest.raises(ValueError, match="one-dimensional"):
+        cv(mask)

src/ClusterVector.test.cpp

@@ -271,6 +271,28 @@ TEST_CASE("Concatenate two cluster vectors where we need to allocate") {
     REQUIRE(ptr[3].y == 17);
 }
 
+TEST_CASE("Reducing a ClusterVector preserves its frame number") {
+    SECTION("Reduce to 2x2") {
+        ClusterVector<Cluster<int32_t, 3, 3>> source(1, 135);
+        source.push_back(Cluster<int32_t, 3, 3>{});
+
+        auto reduced = aare::reduce_to_2x2(source);
+
+        CHECK(reduced.size() == source.size());
+        CHECK(reduced.frame_number() == source.frame_number());
+    }
+
+    SECTION("Reduce to 3x3") {
+        ClusterVector<Cluster<int32_t, 5, 5>> source(1, 246);
+        source.push_back(Cluster<int32_t, 5, 5>{});
+
+        auto reduced = aare::reduce_to_3x3(source);
+
+        CHECK(reduced.size() == source.size());
+        CHECK(reduced.frame_number() == source.frame_number());
+    }
+}
+
 struct ClusterTestData {
     uint8_t ClusterSizeX;
     uint8_t ClusterSizeY;