Merge pull request 'develop' (#11) from develop into main

Reviewed-on: #11

result.py

@@ -1,138 +0,0 @@
-import timeit
-import random
-import statistics
-import matplotlib.pyplot as plt
-import numpy as np
-from fabelous_math import is_even, is_odd
-
-def generate_test_numbers(count: int, min_val: int, max_val: int):
-    return random.sample(range(min_val, max_val), count)
-
-def run_benchmark(numbers, func, iterations=100):
-    times = []
-    for _ in range(iterations):
-        start_time = timeit.default_timer()
-        for num in numbers:
-            func(num)
-        end_time = timeit.default_timer()
-        times.append(end_time - start_time)
-    return times
-
-def create_visualization(results, title):
-    # Prepare data
-    methods = list(results.keys())
-    means = [statistics.mean(times) * 1000 for times in results.values()]  # Convert to milliseconds
-    stds = [statistics.stdev(times) * 1000 for times in results.values()]  # Convert to milliseconds
-
-    # Create figure with two subplots
-    fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 10), height_ratios=[2, 1])
-    fig.suptitle(title, fontsize=14)
-    plt.subplots_adjust(top=0.9)  # Adjust spacing for title
-
-    # Bar plot
-    x = np.arange(len(methods))
-    width = 0.35
-    bars = ax1.bar(x, means, width, yerr=stds, capsize=5)
-    
-    # Customize bar plot
-    ax1.set_ylabel('Time (milliseconds)')
-    ax1.set_xticks(x)
-    ax1.set_xticklabels(methods, rotation=0)
-    ax1.grid(True, axis='y', linestyle='--', alpha=0.7)
-    
-    # Add value labels on bars
-    for bar in bars:
-        height = bar.get_height()
-        ax1.text(bar.get_x() + bar.get_width()/2., height,
-                f'{height:.3f}ms',
-                ha='center', va='bottom')
-
-    # Create table
-    cell_text = []
-    for method, times in results.items():
-        mean_time = statistics.mean(times) * 1000
-        std_dev = statistics.stdev(times) * 1000
-        min_time = min(times) * 1000
-        max_time = max(times) * 1000
-        
-        cell_text.append([
-            method,
-            f"{mean_time:.3f}",
-            f"{std_dev:.3f}",
-            f"{min_time:.3f}",
-            f"{max_time:.3f}"
-        ])
-
-    # Add table
-    ax2.axis('tight')
-    ax2.axis('off')
-    columns = ['Method', 'Mean (ms)', 'Std Dev (ms)', 'Min (ms)', 'Max (ms)']
-    table = ax2.table(cellText=cell_text,
-                     colLabels=columns,
-                     loc='center',
-                     cellLoc='center')
-    
-    # Adjust table appearance
-    table.auto_set_font_size(False)
-    table.set_fontsize(9)
-    table.scale(1.2, 1.5)
-
-    plt.tight_layout()
-    return plt
-
-def main():
-    # Test parameters
-    SAMPLE_SIZE = 5000
-    LOW_RANGE = (1, 10000000)
-    HIGH_RANGE = (1000000000000, 1000000010000000)
-    ITERATIONS = 100
-
-    print(f"Running benchmarks with {SAMPLE_SIZE} numbers, {ITERATIONS} iterations each...")
-    
-    # Generate test numbers
-    low_numbers = generate_test_numbers(SAMPLE_SIZE, *LOW_RANGE)
-    high_numbers = generate_test_numbers(SAMPLE_SIZE, *HIGH_RANGE)
-
-    # Run benchmarks for low numbers
-    print("\nTesting low numbers...")
-    low_results = {
-        'Fabelous Even': run_benchmark(low_numbers, is_even, ITERATIONS),
-        'Fabelous Odd': run_benchmark(low_numbers, is_odd, ITERATIONS),
-        'Modulo Even': run_benchmark(low_numbers, lambda x: x % 2 == 0, ITERATIONS),
-        'Modulo Odd': run_benchmark(low_numbers, lambda x: x % 2 == 1, ITERATIONS)
-    }
-
-    # Run benchmarks for high numbers
-    print("Testing high numbers...")
-    high_results = {
-        'Fabelous Even': run_benchmark(high_numbers, is_even, ITERATIONS),
-        'Fabelous Odd': run_benchmark(high_numbers, is_odd, ITERATIONS),
-        'Modulo Even': run_benchmark(high_numbers, lambda x: x % 2 == 0, ITERATIONS),
-        'Modulo Odd': run_benchmark(high_numbers, lambda x: x % 2 == 1, ITERATIONS)
-    }
-
-    # Create and save visualizations
-    print("\nGenerating visualizations...")
-    plt_low = create_visualization(low_results, 'Performance Comparison - Low Numbers')
-    plt_low.savefig('low_numbers_comparison.png')
-    plt_low.show()
-
-    plt_high = create_visualization(high_results, 'Performance Comparison - High Numbers')
-    plt_high.savefig('high_numbers_comparison.png')
-    plt_high.show()
-
-    # Print summary
-    print("\nSummary of Findings:")
-    print("-------------------")
-    print("1. Low Numbers Performance:")
-    for method, times in low_results.items():
-        mean_time = statistics.mean(times) * 1000
-        print(f"   - {method}: {mean_time:.3f}ms average")
-    
-    print("\n2. High Numbers Performance:")
-    for method, times in high_results.items():
-        mean_time = statistics.mean(times) * 1000
-        print(f"   - {method}: {mean_time:.3f}ms average")
-
-if __name__ == "__main__":
-    main()