Revert "some benchmarks for this useless sparsemask"

This reverts commit 3b41a798a1.

benchmarks/CMakeLists.txt

@@ -19,7 +19,7 @@ add_executable(benchmarks)
 
 target_sources(
   benchmarks PRIVATE ndarray_benchmark.cpp calculateeta_benchmark.cpp
-                     reduce_benchmark.cpp sparsemask_benchmark.cpp)
+                     reduce_benchmark.cpp)
 
 # Link Google Benchmark and other necessary libraries
 target_link_libraries(benchmarks PRIVATE benchmark::benchmark aare_core

include/aare/utils/SparseMask.hpp

@@ -1,4 +1,3 @@
-#include "aare/NDArray.hpp"
 #include "aare/NDView.hpp"
 #include <cstdint>
 #include <filesystem>
@@ -42,24 +41,11 @@ class SparseMask {
     /// @brief Get number of bad channels
     size_t num_bad_channels() const;
 
-    /**
-     * Convert the sparse mask to a dense 2D array representation.
-     * @return An NDArray<bool, 2> representing the dense mask, where true
-     * indicates a bad channel
-     */
-    NDArray<bool, 2> convert_to_dense() const;
-
   private:
-    /// @brief storage format of the sparse mask, either row major or column
+    /// @brief stoarge format of the sparse mask, either row major or column
     /// major
     STORAGEFORMAT storage_format_;
 
-    /// @brief number of rows in the dense mask
-    size_t rows_;
-
-    /// @brief number of columns in the dense mask
-    size_t cols_;
-
     /// @brief for column major stores row indices of non-zero elements, for row
     /// major stores column indices of non-zero elements
     std::vector<uint32_t> innerindices_;

src/utils/SparseMask.cpp

@@ -4,17 +4,17 @@ namespace aare {
 
 SparseMask::SparseMask(const STORAGEFORMAT storage_format, const size_t rows,
                        const size_t cols)
-    : storage_format_(storage_format), rows_(rows), cols_(cols) {
+    : storage_format_(storage_format) {
     if (storage_format_ == STORAGEFORMAT::ROWMAJOR) {
-        outerindices_.resize(rows_ + 1, 0);
+        outerindices_.resize(rows + 1, 0);
     } else if (storage_format_ == STORAGEFORMAT::COLUMNMAJOR) {
-        outerindices_.resize(cols_ + 1, 0);
+        outerindices_.resize(cols + 1, 0);
     } else {
         throw std::invalid_argument(
             "Invalid storage format: must be either ROWMAJOR or COLUMNMAJOR");
     }
 
-    innerindices_.reserve(rows_ * cols_); // Reserve maximum possible size
+    innerindices_.reserve(rows * cols); // Reserve maximum possible size
 }
 
 void SparseMask::insert(const size_t row, const size_t col) {
@@ -52,33 +52,22 @@ bool SparseMask::is_masked(const size_t row, const size_t col) const {
     } else {
         auto start = outerindices_[index_outer_indices];
         auto end = outerindices_[index_outer_indices + 1];
+<<<<<<< HEAD
         // TODO: binary search does not work if not filled along cols e.g. rows
         // e.g. random row col insert
         return std::binary_search(innerindices_.begin() + start,
                                   innerindices_.begin() + end, nonzero_index);
+=======
+        for (size_t i = start; i < end; ++i) {
+            if (innerindices_[i] == nonzero_index) {
+                return true; // Found a non-zero element at (row, col)
+            }
+        }
+        return false; // No non-zero element found at (row, col)
+>>>>>>> parent of 3b41a79 (some benchmarks for this useless sparsemask)
     }
 }
 
 size_t SparseMask::num_bad_channels() const { return innerindices_.size(); }
 
-NDArray<bool, 2> SparseMask::convert_to_dense() const {
-    NDArray<bool, 2> dense_mask{
-        std::array<ssize_t, 2>{static_cast<ssize_t>(rows_),
-                               static_cast<ssize_t>(cols_)},
-        false};
-
-    for (size_t i = 0; i < outerindices_.size() - 1; ++i) {
-        size_t start = outerindices_[i];
-        size_t end = outerindices_[i + 1];
-        for (size_t j = start; j < end; ++j) {
-            if (storage_format_ == STORAGEFORMAT::ROWMAJOR) {
-                dense_mask(i, innerindices_[j]) = true;
-            } else {
-                dense_mask(innerindices_[j], i) = true;
-            }
-        }
-    }
-    return dense_mask;
-}
-
 } // namespace aare