Merge remote-tracking branch 'origin/development' into development

Author: gjbex

hands-on/.virtual_documents/Untitled.ipynb

@@ -0,0 +1,7 @@
+
+
+
+%cat data/measurement.txt
+
+
+

hands-on/data/measurement.txt

@@ -0,0 +1,10 @@
+case condition temperature
+1 1 -0.5
+2 1 0.0
+3 1 0.5
+4 2 -0.5
+5 2 0.0
+6 2 0.5
+7 3 -0.5
+8 3 0.0
+9 3 0.5

hands-on/fundamentals.ipynb

@@ -0,0 +1,68 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "6ff74021-98f7-4ddb-9896-cccefeb153bd",
+   "metadata": {},
+   "source": [
+    "Consider the following data file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "d00ca0af-79b9-4dff-8e75-fcd5c813ce95",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "case condition temperature\n",
+      "1 1 -0.5\n",
+      "2 1 0.0\n",
+      "3 1 0.5\n",
+      "4 2 -0.5\n",
+      "5 2 0.0\n",
+      "6 2 0.5\n",
+      "7 3 -0.5\n",
+      "8 3 0.0\n",
+      "9 3 0.5\n"
+     ]
+    }
+   ],
+   "source": [
+    "%cat data/measurement.txt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "03a674c5-6b8a-4fb8-9c7f-37e6cc1b9cd5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

source_code/intersection_trees/README.md

@@ -17,6 +17,8 @@ on intervals.
 1. `array_intersection_tree.py`: alternative array-based implementation of an intersection tree.
 1. `test_comparison.py`: comprehensive test suite comparing both implementations.
 1. `performance_analysis.py`: detailed performance analysis and benchmarking tools.
+1. `build_time_analysis.py`: comprehensive build time performance analysis.
+1. `build_time_focused_analysis.py`: focused analysis answering build vs query performance questions.
 
 ## Implementation Comparison
 
@@ -33,7 +35,23 @@ on intervals.
 - Slightly slower execution (~20% overhead) due to array indexing
 
 ### Performance Characteristics
-- **Memory Usage**: Array-based implementation uses ~70% less memory
-- **Execution Speed**: Traditional implementation is ~20% faster
-- **Cache Locality**: Array-based shows potential for better cache performance with sequential access patterns
-- **Scalability**: Both implementations scale similarly with increasing dataset size
+
+#### Query Performance
+- **Traditional (Node-based)**: ~20% faster query execution
+- **Array-based**: ~20% slower query execution
+- Both scale similarly with increasing dataset size
+
+#### Build/Insertion Performance  
+- **Traditional (Node-based)**: ~12% faster build time
+- **Array-based**: ~12% slower build time
+- Node-based achieves ~310k insertions/sec vs ~250k insertions/sec for array-based
+
+#### Memory Usage
+- **Traditional (Node-based)**: Higher memory usage (~3x more)
+- **Array-based**: ~70% less memory usage
+- Better cache locality potential for sequential access patterns
+
+#### Trade-off Summary
+- **Array-based**: Slower build (~12%) and query (~20%) but major memory savings (~70%)
+- **Node-based**: Faster in all operations but uses significantly more memory
+- **Recommendation**: Use node-based for performance-critical, use array-based for memory-constrained environments