Add test for reduce and fix type error in sparse matrix local

Author: Mikolaj Komar

include/dr/mp/containers/matrix_formats/csr_eq_segment.hpp

@@ -240,7 +240,7 @@ template <typename DSM> class csr_eq_segment_iterator {
     const auto my_process_segment_index = dsm_->rows_backend_.getrank();
     assert(my_process_segment_index == segment_index_);
     if (dsm_->local_view == nullptr) {
-      return nullptr;
+      throw std::runtime_error("Requesting not existing local segment");
     }
     return dsm_->local_view->begin();
   }

include/dr/mp/containers/matrix_formats/csr_row_segment.hpp

@@ -228,7 +228,7 @@ template <typename DSM> class csr_row_segment_iterator {
     const auto my_process_segment_index = dsm_->vals_backend_.getrank();
     assert(my_process_segment_index == segment_index_);
     if (dsm_->local_view == nullptr) {
-      return nullptr;
+      throw std::runtime_error("Requesting not existing local segment");
     }
     return dsm_->local_view->begin();
   }

test/gtest/mp/sparse_matrix.cpp

@@ -14,6 +14,23 @@ auto testMatrixIter(auto &src, auto &matrix) {
   }
 }
 
+auto testMatrixReduce(auto &src, auto &matrix) {
+  EXPECT_TRUE(src.size() == matrix.size());
+  long sum = 0;
+  for (auto [index, val] : src) {
+    auto [x, y] = index;
+    sum += (long)(val + x + y);
+  }
+  auto transformer = [](auto entry) {
+    auto [index, val] = entry;
+    auto [x, y] = index;
+    return (long)(val + x + y);
+  };
+  auto transformed = dr::transform_view(matrix, transformer);
+  long reduced = dr::mp::reduce(transformed, 0, std::plus<long>{});
+  EXPECT_TRUE((sum == reduced));
+}
+
 TEST(SparseMatrix, staticAssertEq) {
   std::size_t m = 100;
   std::size_t k = 100;
@@ -73,3 +90,25 @@ TEST(SparseMatrix, IterEq) {
       a(csr, 0);
   testMatrixIter(csr, a);
 }
+
+TEST(SparseMatrix, ReduceRow) {
+  std::size_t m = 100;
+  std::size_t k = 100;
+  auto csr = dr::generate_random_csr({m, k}, 0.1f);
+  dr::mp::distributed_sparse_matrix<
+      float, unsigned long, dr::mp::MpiBackend,
+      dr::mp::csr_row_distribution<float, unsigned long, dr::mp::MpiBackend>>
+      a(csr, 0);
+  testMatrixReduce(csr, a);
+}
+
+TEST(SparseMatrix, ReduceEq) {
+  std::size_t m = 100;
+  std::size_t k = 100;
+  auto csr = dr::generate_random_csr({m, k}, 0.1f);
+  dr::mp::distributed_sparse_matrix<
+      float, unsigned long, dr::mp::MpiBackend,
+      dr::mp::csr_eq_distribution<float, unsigned long, dr::mp::MpiBackend>>
+      a(csr, 0);
+  testMatrixReduce(csr, a);
+}