minor fix and reordering

uxlfoundation · Dec 3, 2024 · 8d103c1 · 8d103c1
1 parent 1bef482
commit 8d103c1
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Showing 2 changed files with 144 additions and 85 deletions.
diff --git a/...gorithms/k_nearest_neighbors/kdtree_knn_classification_predict_dense_default_batch_impl.i b/...gorithms/k_nearest_neighbors/kdtree_knn_classification_predict_dense_default_batch_impl.i
@@ -39,6 +39,7 @@
 #include "src/algorithms/k_nearest_neighbors/kdtree_knn_classification_model_impl.h"
 #include "src/algorithms/k_nearest_neighbors/kdtree_knn_impl.i"
 #include "src/algorithms/k_nearest_neighbors/knn_heap.h"
+#include <iostream>
 
 namespace daal
 {
@@ -145,11 +146,27 @@ Status KNNClassificationPredictKernel<algorithmFpType, defaultDense, cpu>::compu
 
     if (par3 == NULL) return Status(ErrorNullParameterNotSupported);
 
-    const Model * const model    = static_cast<const Model *>(m);
-    const auto & kdTreeTable     = *(model->impl()->getKDTreeTable());
+    const Model * const model       = static_cast<const Model *>(m);
+    const KDTreeTable & kdTreeTable = *(model->impl()->getKDTreeTable());
+    const KDTreeNode * const nodes  = static_cast<const KDTreeNode *>(kdTreeTable.getArray());
+    const size_t xRowCount          = x->getNumberOfRows();
+
+    const algorithmFpType base        = 2.0;
+    const algorithmFpType baseInPower = Math::sPowx(base, Math::sCeil(Math::sLog(base * xRowCount - 1) / Math::sLog(base)));
+    DAAL_ASSERT(baseInPower > 0)
+    const size_t maxKDTreeNodeCount = ((size_t)baseInPower * __KDTREE_MAX_NODE_COUNT_MULTIPLICATION_FACTOR) / __KDTREE_LEAF_BUCKET_SIZE + 1;
+    for (int index = 0; index < maxKDTreeNodeCount; index++)
+    {
+        const KDTreeNode & node = nodes[index];
+
+        std::cout << "Node Index: " << index << ", Dimension: " << node.dimension << ", Cut Point: " << node.cutPoint
+                  << ", Left Index: " << node.leftIndex << ", Right Index: " << node.rightIndex << std::endl;
+    }
+
     const auto rootTreeNodeIndex = model->impl()->getRootNodeIndex();
     const NumericTable & data    = *(model->impl()->getData());
     const NumericTable * labels  = nullptr;
+
     if (resultsToEvaluate != 0)
     {
         labels = model->impl()->getLabels().get();
@@ -164,8 +181,6 @@ Status KNNClassificationPredictKernel<algorithmFpType, defaultDense, cpu>::compu
     }
     const size_t heapSize = (iSize / 16 + 1) * 16;
 
-    const size_t xRowCount        = x->getNumberOfRows();
-    const algorithmFpType base    = 2.0;
     const size_t expectedMaxDepth = (Math::sLog(xRowCount) / Math::sLog(base) + 1) * __KDTREE_DEPTH_MULTIPLICATION_FACTOR;
     const size_t stackSize        = Math::sPowx(base, Math::sCeil(Math::sLog(expectedMaxDepth) / Math::sLog(base)));
     struct Local