Initial commit

examples/comparison_demo.py

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+"""
+Demonstration of Quicksort performance comparison.
+"""
+
+import sys
+import os
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+from src.comparison import (
+    generate_random_array,
+    generate_sorted_array,
+    generate_reverse_sorted_array,
+    generate_nearly_sorted_array,
+    generate_array_with_duplicates,
+    compare_algorithms,
+    format_results_table
+)
+from src.quicksort import quicksort, randomized_quicksort
+
+
+def demo_performance_comparison():
+    """Demonstrate performance comparison between algorithms."""
+    print("=" * 80)
+    print("QUICKSORT PERFORMANCE COMPARISON")
+    print("=" * 80)
+    
+    # Define algorithms to compare
+    algorithms = {
+        'Deterministic Quicksort': lambda arr: quicksort(arr),
+        'Randomized Quicksort': lambda arr: randomized_quicksort(arr, seed=42)
+    }
+    
+    # Define array generators
+    array_generators = {
+        'Random': generate_random_array,
+        'Sorted': generate_sorted_array,
+        'Reverse Sorted': generate_reverse_sorted_array,
+        'Nearly Sorted': lambda size: generate_nearly_sorted_array(size, swap_count=10),
+        'Many Duplicates': lambda size: generate_array_with_duplicates(size, unique_count=10)
+    }
+    
+    # Test sizes
+    sizes = [100, 500, 1000, 5000]
+    
+    print("\nRunning performance benchmarks...")
+    print("This may take a few moments...\n")
+    
+    # Run comparison
+    results = compare_algorithms(
+        algorithms=algorithms,
+        array_generators=array_generators,
+        sizes=sizes,
+        iterations=3
+    )
+    
+    # Print formatted results
+    print(format_results_table(results))
+    
+    return results
+
+
+def demo_specific_scenarios():
+    """Demonstrate performance on specific scenarios."""
+    print("\n" + "=" * 80)
+    print("SPECIFIC SCENARIO ANALYSIS")
+    print("=" * 80)
+    
+    from src.comparison import benchmark_sorting_algorithm
+    
+    scenarios = {
+        'Small Random (100)': generate_random_array(100),
+        'Medium Random (1000)': generate_random_array(1000),
+        'Large Random (10000)': generate_random_array(10000),
+        'Sorted (1000)': generate_sorted_array(1000),
+        'Reverse Sorted (1000)': generate_reverse_sorted_array(1000),
+        'Nearly Sorted (1000)': generate_nearly_sorted_array(1000, 10),
+        'Many Duplicates (1000)': generate_array_with_duplicates(1000, 10)
+    }
+    
+    algorithms = {
+        'Deterministic': quicksort,
+        'Randomized': lambda arr: randomized_quicksort(arr, seed=42)
+    }
+    
+    print(f"\n{'Scenario':<30} {'Algorithm':<20} {'Mean Time (s)':<15} {'Median Time (s)':<15}")
+    print("-" * 80)
+    
+    for scenario_name, test_array in scenarios.items():
+        for algo_name, algo_func in algorithms.items():
+            stats = benchmark_sorting_algorithm(algo_func, test_array, iterations=5)
+            print(f"{scenario_name:<30} {algo_name:<20} {stats['mean']:<15.6f} {stats['median']:<15.6f}")
+
+
+if __name__ == '__main__':
+    results = demo_performance_comparison()
+    demo_specific_scenarios()
+    
+    print("\n" + "=" * 80)
+    print("COMPARISON COMPLETE")
+    print("=" * 80)
+