[2] generate performance plots from experimental data

BoriskovaDV/docs/data/2-nd-exercise/main.py

@@ -3,6 +3,9 @@ import os
 from collections import deque
 import heapq
 import time
+import csv
+import matplotlib.pyplot as plt
+import numpy as np
 
 class GridPoint:
     def __init__(self, x, y):
@@ -289,7 +292,101 @@ def run_experiment(maze_file, algo, runs=5):
             total_len += plen
     return total_ms / runs, total_visited / runs, total_len / runs
 
+def generate_plots(results):
+    mazes = list(set([r['maze'] for r in results]))
+    strategies = ['BFS', 'DFS', 'AStar']
+    
+    fig, axes = plt.subplots(1, 3, figsize=(15, 5))
+    x = np.arange(len(mazes))
+    width = 0.25
+
+    for i, strat in enumerate(strategies):
+        times = []
+        for maze in mazes:
+            val = next((r['time_ms'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
+            times.append(val)
+        axes[0].bar(x + i*width, times, width, label=strat)
+    axes[0].set_xlabel('Maze')
+    axes[0].set_ylabel('Time (ms)')
+    axes[0].set_title('Execution Time')
+    axes[0].set_xticks(x + width)
+    axes[0].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[0].legend()
+    axes[0].grid(True, alpha=0.3)
+
+    for i, strat in enumerate(strategies):
+        visited = []
+        for maze in mazes:
+            val = next((r['visited_cells'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
+            visited.append(val)
+        axes[1].bar(x + i*width, visited, width, label=strat)
+    axes[1].set_xlabel('Maze')
+    axes[1].set_ylabel('Visited Cells')
+    axes[1].set_title('Visited Cells')
+    axes[1].set_xticks(x + width)
+    axes[1].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[1].legend()
+    axes[1].grid(True, alpha=0.3)
+
+    for i, strat in enumerate(strategies):
+        lengths = []
+        for maze in mazes:
+            val = next((r['path_length'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
+            lengths.append(val)
+        axes[2].bar(x + i*width, lengths, width, label=strat)
+    axes[2].set_xlabel('Maze')
+    axes[2].set_ylabel('Path Length')
+    axes[2].set_title('Path Length')
+    axes[2].set_xticks(x + width)
+    axes[2].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[2].legend()
+    axes[2].grid(True, alpha=0.3)
+
+    plt.tight_layout()
+    plt.savefig('performance_comparison.png', dpi=150, bbox_inches='tight')
+    plt.show()
+
 if __name__ == "__main__":
+    if len(sys.argv) > 1 and sys.argv[1] == 'experiment':
+        print("Running experiments on all mazes...")
+        maze_files = [
+            ("maze/maze1.txt", "Small 10x6"),
+            ("maze/maze10x10.txt", "Medium 10x10"),
+            ("maze/maze20x20.txt", "Large 20x20"),
+            ("maze/maze_empty.txt", "Empty 15x15"),
+            ("maze/maze_no_exit.txt", "No exit 10x10")
+        ]
+        algorithms = [
+            ("BFS", BreadthFirst()),
+            ("DFS", DepthFirst()),
+            ("AStar", AStar())
+        ]
+        results = []
+        for fname, label in maze_files:
+            print(f"Testing {label}...")
+            for aname, algo in algorithms:
+                try:
+                    avg_t, avg_v, avg_l = run_experiment(fname, algo, runs=3)
+                    results.append({
+                        'maze': label,
+                        'strategy': aname,
+                        'time_ms': avg_t,
+                        'visited_cells': avg_v,
+                        'path_length': avg_l
+                    })
+                    print(f"  {aname}: time={avg_t:.3f}ms visited={avg_v:.0f} length={avg_l:.0f}")
+                except Exception as e:
+                    print(f"  {aname}: ERROR {e}")
+        # save csv
+        with open('experiment_results.csv', 'w', newline='', encoding='utf-8') as f:
+            writer = csv.DictWriter(f, fieldnames=['maze', 'strategy', 'time_ms', 'visited_cells', 'path_length'])
+            writer.writeheader()
+            writer.writerows(results)
+        generate_plots(results)
+        print("Done. Results saved to experiment_results.csv and performance_comparison.png")
+        sys.exit(0)
+
+    # else interactive mode
     loader = TextMazeLoader()
     lab = loader.load("maze/maze1.txt")
     player = Player(lab.start_point, lab)