add experiment
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SobolevNS/docs/data/task2_maze/docs/data/results.csv
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лабиринт,стратегия,trial,время_мс,посещено_клеток,длина_пути,стоимость_пути
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small_10x10,BFS,1,0.0454,34,16,16
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small_10x10,BFS,2,0.0314,34,16,16
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small_10x10,BFS,3,0.0286,34,16,16
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small_10x10,BFS,4,0.0275,34,16,16
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small_10x10,BFS,5,0.0270,34,16,16
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small_10x10,BFS,6,0.0264,34,16,16
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small_10x10,BFS,7,0.0279,34,16,16
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small_10x10,DFS,1,0.0167,18,16,16
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small_10x10,DFS,2,0.0146,18,16,16
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small_10x10,DFS,3,0.0138,18,16,16
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small_10x10,DFS,4,0.0132,18,16,16
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small_10x10,DFS,5,0.0138,18,16,16
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small_10x10,DFS,6,0.0133,18,16,16
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small_10x10,DFS,7,0.0138,18,16,16
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small_10x10,A*,1,0.0585,27,16,16
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small_10x10,A*,2,0.0514,27,16,16
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small_10x10,A*,3,0.0386,27,16,16
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small_10x10,A*,4,0.0366,27,16,16
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small_10x10,A*,5,0.0367,27,16,16
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small_10x10,A*,6,0.0367,27,16,16
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small_10x10,A*,7,0.0356,27,16,16
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small_10x10,Dijkstra,1,0.0467,33,16,16
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small_10x10,Dijkstra,2,0.0409,33,16,16
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small_10x10,Dijkstra,3,0.0395,33,16,16
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small_10x10,Dijkstra,4,0.0396,33,16,16
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small_10x10,Dijkstra,5,0.0642,33,16,16
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small_10x10,Dijkstra,6,0.0404,33,16,16
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small_10x10,Dijkstra,7,0.0392,33,16,16
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medium_51x51,BFS,1,0.5159,524,353,353
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medium_51x51,BFS,2,0.5299,524,353,353
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medium_51x51,BFS,3,0.5232,524,353,353
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medium_51x51,BFS,4,0.4525,524,353,353
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medium_51x51,BFS,5,0.4667,524,353,353
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medium_51x51,BFS,6,0.4594,524,353,353
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medium_51x51,BFS,7,0.4886,524,353,353
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medium_51x51,DFS,1,0.3356,379,353,353
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medium_51x51,DFS,2,0.3270,379,353,353
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medium_51x51,DFS,3,0.3471,379,353,353
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medium_51x51,DFS,4,0.3235,379,353,353
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medium_51x51,DFS,5,0.3309,379,353,353
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medium_51x51,DFS,6,0.3856,379,353,353
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medium_51x51,DFS,7,0.3248,379,353,353
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medium_51x51,A*,1,0.8707,421,353,353
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medium_51x51,A*,2,0.6813,421,353,353
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medium_51x51,A*,3,0.6357,421,353,353
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medium_51x51,A*,4,0.6464,421,353,353
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medium_51x51,A*,5,0.6520,421,353,353
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medium_51x51,A*,6,0.6231,421,353,353
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medium_51x51,A*,7,0.6365,421,353,353
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medium_51x51,Dijkstra,1,0.7634,523,353,353
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medium_51x51,Dijkstra,2,0.6893,523,353,353
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medium_51x51,Dijkstra,3,0.6817,523,353,353
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medium_51x51,Dijkstra,4,0.6965,523,353,353
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medium_51x51,Dijkstra,5,0.6920,523,353,353
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medium_51x51,Dijkstra,6,0.6702,523,353,353
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medium_51x51,Dijkstra,7,0.7281,523,353,353
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large_101x101,BFS,1,3.2679,2143,1265,1265
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large_101x101,BFS,2,1.9302,2143,1265,1265
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large_101x101,BFS,3,1.9559,2143,1265,1265
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large_101x101,BFS,4,1.9057,2143,1265,1265
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large_101x101,BFS,5,1.8770,2143,1265,1265
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large_101x101,BFS,6,1.8828,2143,1265,1265
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large_101x101,BFS,7,1.9345,2143,1265,1265
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large_101x101,DFS,1,1.2758,1443,1265,1265
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large_101x101,DFS,2,1.3043,1443,1265,1265
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large_101x101,DFS,3,1.2613,1443,1265,1265
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large_101x101,DFS,4,1.2846,1443,1265,1265
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large_101x101,DFS,5,1.3566,1443,1265,1265
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large_101x101,DFS,6,1.3296,1443,1265,1265
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large_101x101,DFS,7,1.2501,1443,1265,1265
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large_101x101,A*,1,3.2760,1831,1265,1265
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large_101x101,A*,2,3.3353,1831,1265,1265
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large_101x101,A*,3,4.1894,1831,1265,1265
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large_101x101,A*,4,4.6809,1831,1265,1265
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large_101x101,A*,5,3.4026,1831,1265,1265
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large_101x101,A*,6,3.1036,1831,1265,1265
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large_101x101,A*,7,3.2912,1831,1265,1265
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large_101x101,Dijkstra,1,3.4403,2139,1265,1265
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large_101x101,Dijkstra,2,3.3500,2139,1265,1265
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large_101x101,Dijkstra,3,3.4201,2139,1265,1265
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large_101x101,Dijkstra,4,3.2253,2139,1265,1265
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large_101x101,Dijkstra,5,5.0122,2139,1265,1265
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large_101x101,Dijkstra,6,3.3146,2139,1265,1265
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large_101x101,Dijkstra,7,3.2323,2139,1265,1265
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empty_30x30,BFS,1,0.8417,784,55,55
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empty_30x30,BFS,2,0.8160,784,55,55
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empty_30x30,BFS,3,0.7701,784,55,55
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empty_30x30,BFS,4,0.7609,784,55,55
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empty_30x30,BFS,5,0.7931,784,55,55
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empty_30x30,BFS,6,0.7647,784,55,55
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empty_30x30,BFS,7,0.8047,784,55,55
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empty_30x30,DFS,1,0.5067,784,379,379
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empty_30x30,DFS,2,0.6133,784,379,379
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empty_30x30,DFS,3,0.8051,784,379,379
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empty_30x30,DFS,4,0.4703,784,379,379
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empty_30x30,DFS,5,0.8029,784,379,379
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empty_30x30,DFS,6,0.5463,784,379,379
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empty_30x30,DFS,7,0.4602,784,379,379
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empty_30x30,A*,1,1.5117,784,55,55
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empty_30x30,A*,2,1.4866,784,55,55
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empty_30x30,A*,3,1.5878,784,55,55
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empty_30x30,A*,4,1.8756,784,55,55
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empty_30x30,A*,5,1.4943,784,55,55
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empty_30x30,A*,6,2.0146,784,55,55
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empty_30x30,A*,7,1.5262,784,55,55
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empty_30x30,Dijkstra,1,1.2824,784,55,55
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empty_30x30,Dijkstra,2,1.2897,784,55,55
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empty_30x30,Dijkstra,3,1.3428,784,55,55
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empty_30x30,Dijkstra,4,1.3181,784,55,55
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empty_30x30,Dijkstra,5,1.2785,784,55,55
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empty_30x30,Dijkstra,6,1.3634,784,55,55
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empty_30x30,Dijkstra,7,1.2709,784,55,55
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nopath_15x15,BFS,1,0.1595,165,0,0
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nopath_15x15,BFS,2,0.1705,165,0,0
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nopath_15x15,BFS,3,0.1489,165,0,0
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nopath_15x15,BFS,4,0.1461,165,0,0
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nopath_15x15,BFS,5,0.1972,165,0,0
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nopath_15x15,BFS,6,0.1461,165,0,0
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nopath_15x15,BFS,7,0.1436,165,0,0
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nopath_15x15,DFS,1,0.2023,165,0,0
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nopath_15x15,DFS,2,0.1506,165,0,0
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nopath_15x15,DFS,3,0.1511,165,0,0
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nopath_15x15,DFS,4,0.1477,165,0,0
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nopath_15x15,DFS,5,0.1513,165,0,0
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nopath_15x15,DFS,6,0.1455,165,0,0
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nopath_15x15,DFS,7,0.1654,165,0,0
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nopath_15x15,A*,1,0.2915,165,0,0
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nopath_15x15,A*,2,0.3024,165,0,0
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nopath_15x15,A*,3,0.2743,165,0,0
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nopath_15x15,A*,4,0.2980,165,0,0
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nopath_15x15,A*,5,0.2807,165,0,0
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nopath_15x15,A*,6,0.2838,165,0,0
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nopath_15x15,A*,7,0.3015,165,0,0
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nopath_15x15,Dijkstra,1,0.2476,165,0,0
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nopath_15x15,Dijkstra,2,0.2492,165,0,0
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nopath_15x15,Dijkstra,3,0.2435,165,0,0
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nopath_15x15,Dijkstra,4,0.2869,165,0,0
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nopath_15x15,Dijkstra,5,0.2466,165,0,0
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nopath_15x15,Dijkstra,6,0.2480,165,0,0
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nopath_15x15,Dijkstra,7,0.2445,165,0,0
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weighted_31x31,BFS,1,0.4261,433,265,391
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weighted_31x31,BFS,2,0.3905,433,265,391
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weighted_31x31,BFS,3,0.3713,433,265,391
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weighted_31x31,BFS,4,0.3713,433,265,391
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weighted_31x31,BFS,5,0.3672,433,265,391
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weighted_31x31,BFS,6,0.3788,433,265,391
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weighted_31x31,BFS,7,0.4045,433,265,391
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weighted_31x31,DFS,1,0.2646,318,265,391
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weighted_31x31,DFS,2,0.2761,318,265,391
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weighted_31x31,DFS,3,0.2978,318,265,391
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weighted_31x31,DFS,4,0.2618,318,265,391
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weighted_31x31,DFS,5,0.2717,318,265,391
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weighted_31x31,DFS,6,0.2581,318,265,391
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weighted_31x31,DFS,7,0.2787,318,265,391
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weighted_31x31,A*,1,0.6283,405,265,391
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weighted_31x31,A*,2,0.6319,405,265,391
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weighted_31x31,A*,3,0.7192,405,265,391
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weighted_31x31,A*,4,0.6285,405,265,391
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weighted_31x31,A*,5,0.6179,405,265,391
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weighted_31x31,A*,6,0.6571,405,265,391
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weighted_31x31,A*,7,1.0022,405,265,391
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weighted_31x31,Dijkstra,1,0.8638,431,265,391
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weighted_31x31,Dijkstra,2,0.8008,431,265,391
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weighted_31x31,Dijkstra,3,0.6000,431,265,391
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weighted_31x31,Dijkstra,4,0.6262,431,265,391
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weighted_31x31,Dijkstra,5,0.5502,431,265,391
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weighted_31x31,Dijkstra,6,0.5523,431,265,391
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weighted_31x31,Dijkstra,7,0.5431,431,265,391
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weighted_choice,BFS,1,0.1839,189,19,29
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weighted_choice,BFS,2,0.1642,189,19,29
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weighted_choice,BFS,3,0.1718,189,19,29
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weighted_choice,BFS,4,0.2025,189,19,29
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weighted_choice,BFS,5,0.1855,189,19,29
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weighted_choice,BFS,6,0.1656,189,19,29
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weighted_choice,BFS,7,0.1674,189,19,29
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weighted_choice,DFS,1,0.0238,55,19,29
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weighted_choice,DFS,2,0.0204,55,19,29
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weighted_choice,DFS,3,0.0196,55,19,29
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weighted_choice,DFS,4,0.0201,55,19,29
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weighted_choice,DFS,5,0.0372,55,19,29
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weighted_choice,DFS,6,0.0198,55,19,29
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weighted_choice,DFS,7,0.0198,55,19,29
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weighted_choice,A*,1,0.2451,117,25,25
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weighted_choice,A*,2,0.2572,117,25,25
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weighted_choice,A*,3,0.2276,117,25,25
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weighted_choice,A*,4,0.2337,117,25,25
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weighted_choice,A*,5,0.2305,117,25,25
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weighted_choice,A*,6,0.2742,117,25,25
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weighted_choice,A*,7,0.2275,117,25,25
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weighted_choice,Dijkstra,1,0.3360,209,25,25
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weighted_choice,Dijkstra,2,0.4054,209,25,25
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weighted_choice,Dijkstra,3,0.3169,209,25,25
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weighted_choice,Dijkstra,4,0.3882,209,25,25
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weighted_choice,Dijkstra,5,0.3406,209,25,25
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weighted_choice,Dijkstra,6,0.3182,209,25,25
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weighted_choice,Dijkstra,7,0.3200,209,25,25
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--- СРЕДНИЕ ---
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лабиринт,стратегия,среднее_время_мс,посещено_клеток,длина_пути,стоимость_пути
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small_10x10,BFS,0.0306,34,16,16
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small_10x10,DFS,0.0142,18,16,16
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small_10x10,A*,0.0420,27,16,16
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small_10x10,Dijkstra,0.0444,33,16,16
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medium_51x51,BFS,0.4909,524,353,353
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medium_51x51,DFS,0.3392,379,353,353
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medium_51x51,A*,0.6780,421,353,353
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medium_51x51,Dijkstra,0.7030,523,353,353
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large_101x101,BFS,2.1077,2143,1265,1265
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large_101x101,DFS,1.2946,1443,1265,1265
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large_101x101,A*,3.6113,1831,1265,1265
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large_101x101,Dijkstra,3.5707,2139,1265,1265
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empty_30x30,BFS,0.7930,784,55,55
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empty_30x30,DFS,0.6007,784,379,379
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empty_30x30,A*,1.6424,784,55,55
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empty_30x30,Dijkstra,1.3066,784,55,55
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nopath_15x15,BFS,0.1588,165,0,0
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nopath_15x15,DFS,0.1591,165,0,0
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nopath_15x15,A*,0.2903,165,0,0
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nopath_15x15,Dijkstra,0.2523,165,0,0
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weighted_31x31,BFS,0.3871,433,265,391
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weighted_31x31,DFS,0.2727,318,265,391
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weighted_31x31,A*,0.6979,405,265,391
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weighted_31x31,Dijkstra,0.6481,431,265,391
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weighted_choice,BFS,0.1773,189,19,29
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weighted_choice,DFS,0.0230,55,19,29
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weighted_choice,A*,0.2423,117,25,25
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weighted_choice,Dijkstra,0.3465,209,25,25
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Can't render this file because it has a wrong number of fields in line 199.
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SobolevNS/docs/data/task2_maze/experiment.py
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SobolevNS/docs/data/task2_maze/experiment.py
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"""
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experiment.py - экспериментальное сравнение стратегий поиска пути.
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Для каждого лабиринта × стратегии:
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- запускаем solve() TRIALS раз
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- усредняем время в мс, фиксируем число посещённых клеток и длину пути
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- сохраняем в docs/data/results.csv
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"""
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import csv
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import os
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from maze_solver import (
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TextFileMazeBuilder, MazeSolver,
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BFSStrategy, DFSStrategy, AStarStrategy, DijkstraStrategy,
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)
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TRIALS = 7
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MAZES = [
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("small_10x10", "mazes/small_10x10.txt"),
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("medium_51x51", "mazes/medium_51x51.txt"),
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("large_101x101", "mazes/large_101x101.txt"),
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("empty_30x30", "mazes/empty_30x30.txt"),
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("nopath_15x15", "mazes/nopath_15x15.txt"),
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("weighted_31x31", "mazes/weighted_31x31.txt"),
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("weighted_choice","mazes/weighted_choice.txt"),
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]
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STRATEGY_CLASSES = [BFSStrategy, DFSStrategy, AStarStrategy, DijkstraStrategy]
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OUT_CSV = "docs/data/results.csv"
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def main():
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os.makedirs(os.path.dirname(OUT_CSV), exist_ok=True)
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builder = TextFileMazeBuilder()
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rows = [["лабиринт", "стратегия", "trial",
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"время_мс", "посещено_клеток", "длина_пути", "стоимость_пути"]]
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summary = []
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for maze_name, maze_path in MAZES:
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maze = builder.build_from_file(maze_path)
|
||||
print(f"\n## {maze_name} ({maze.width}x{maze.height})")
|
||||
|
||||
for cls in STRATEGY_CLASSES:
|
||||
times, visited_vals, path_vals, cost_vals = [], [], [], []
|
||||
for trial in range(TRIALS):
|
||||
solver = MazeSolver(maze, cls())
|
||||
stats = solver.solve()
|
||||
cost = sum(c.weight for c in stats["path"])
|
||||
times.append(stats["elapsed_ms"])
|
||||
visited_vals.append(stats["visited"])
|
||||
path_vals.append(stats["path_length"])
|
||||
cost_vals.append(cost)
|
||||
rows.append([maze_name, stats["strategy"], trial + 1,
|
||||
f"{stats['elapsed_ms']:.4f}",
|
||||
stats["visited"], stats["path_length"], cost])
|
||||
|
||||
mean_t = sum(times) / TRIALS
|
||||
print(f" {cls.name:9s} t_avg={mean_t:7.3f} ms "
|
||||
f"visited={visited_vals[0]:5d} "
|
||||
f"path={path_vals[0]:5d} cost={cost_vals[0]:5d}")
|
||||
summary.append((maze_name, cls.name, mean_t,
|
||||
visited_vals[0], path_vals[0], cost_vals[0]))
|
||||
|
||||
rows.append([])
|
||||
rows.append(["--- СРЕДНИЕ ---"])
|
||||
rows.append(["лабиринт", "стратегия", "среднее_время_мс",
|
||||
"посещено_клеток", "длина_пути", "стоимость_пути"])
|
||||
for r in summary:
|
||||
rows.append([r[0], r[1], f"{r[2]:.4f}", r[3], r[4], r[5]])
|
||||
|
||||
with open(OUT_CSV, "w", newline="", encoding="utf-8") as f:
|
||||
csv.writer(f).writerows(rows)
|
||||
print(f"\nГотово. Результаты записаны в {OUT_CSV}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
99
SobolevNS/docs/data/task2_maze/plot_results.py
Normal file
99
SobolevNS/docs/data/task2_maze/plot_results.py
Normal file
|
|
@ -0,0 +1,99 @@
|
|||
"""plot_results.py - графики для эксперимента с лабиринтами."""
|
||||
import csv
|
||||
import os
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
CSV = "docs/data/results.csv"
|
||||
PLOTS = "docs/data/plots"
|
||||
os.makedirs(PLOTS, exist_ok=True)
|
||||
|
||||
|
||||
def load_means():
|
||||
"""Возвращает dict[(maze, strategy)] = (time_ms, visited, path_len, cost)."""
|
||||
out = {}
|
||||
with open(CSV, encoding="utf-8") as f:
|
||||
rows = list(csv.reader(f))
|
||||
start = next(i for i, r in enumerate(rows) if r and r[0] == "--- СРЕДНИЕ ---") + 2
|
||||
for r in rows[start:]:
|
||||
if not r:
|
||||
continue
|
||||
maze, strat, t, vis, plen, cost = r
|
||||
out[(maze, strat)] = (float(t), int(vis), int(plen), int(cost))
|
||||
return out
|
||||
|
||||
|
||||
MAZES = ["small_10x10", "medium_51x51", "large_101x101",
|
||||
"empty_30x30", "nopath_15x15",
|
||||
"weighted_31x31", "weighted_choice"]
|
||||
STRATEGIES = ["BFS", "DFS", "A*", "Dijkstra"]
|
||||
COLORS = {"BFS": "#3498db", "DFS": "#e67e22", "A*": "#2ecc71", "Dijkstra": "#9b59b6"}
|
||||
|
||||
|
||||
def grouped_bar(means, idx, ylabel, title, fname, log=True):
|
||||
x = np.arange(len(MAZES))
|
||||
w = 0.2
|
||||
fig, ax = plt.subplots(figsize=(11, 5))
|
||||
for i, s in enumerate(STRATEGIES):
|
||||
vals = [means[(m, s)][idx] for m in MAZES]
|
||||
bars = ax.bar(x + (i - 1.5) * w, vals, w, label=s, color=COLORS[s], alpha=0.9)
|
||||
for b, v in zip(bars, vals):
|
||||
ax.text(b.get_x() + b.get_width() / 2, b.get_height(),
|
||||
f"{v:g}", ha="center", va="bottom", fontsize=7, rotation=0)
|
||||
ax.set_xticks(x)
|
||||
ax.set_xticklabels(MAZES, rotation=20, ha="right")
|
||||
ax.set_ylabel(ylabel)
|
||||
ax.set_title(title)
|
||||
if log:
|
||||
ax.set_yscale("log")
|
||||
ax.legend()
|
||||
ax.grid(axis="y", linestyle="--", alpha=0.4)
|
||||
plt.tight_layout()
|
||||
p = os.path.join(PLOTS, fname)
|
||||
plt.savefig(p, dpi=130)
|
||||
plt.close()
|
||||
print("saved:", p)
|
||||
|
||||
|
||||
def weighted_choice_chart(means):
|
||||
"""Отдельный график для weighted_choice: путь vs стоимость."""
|
||||
strategies = STRATEGIES
|
||||
lengths = [means[("weighted_choice", s)][2] for s in strategies]
|
||||
costs = [means[("weighted_choice", s)][3] for s in strategies]
|
||||
x = np.arange(len(strategies))
|
||||
w = 0.35
|
||||
fig, ax = plt.subplots(figsize=(7.5, 4.5))
|
||||
b1 = ax.bar(x - w/2, lengths, w, label="длина пути (клеток)",
|
||||
color="#3498db", alpha=0.9)
|
||||
b2 = ax.bar(x + w/2, costs, w, label="стоимость пути (сумма весов)",
|
||||
color="#e74c3c", alpha=0.9)
|
||||
for bars in (b1, b2):
|
||||
for bar in bars:
|
||||
ax.text(bar.get_x() + bar.get_width() / 2, bar.get_height(),
|
||||
f"{bar.get_height():.0f}", ha="center", va="bottom", fontsize=9)
|
||||
ax.set_xticks(x); ax.set_xticklabels(strategies)
|
||||
ax.set_title("weighted_choice: BFS/DFS режут через болото,\n"
|
||||
"Dijkstra/A* находят более дешёвый обход")
|
||||
ax.set_ylabel("значение")
|
||||
ax.legend()
|
||||
ax.grid(axis="y", linestyle="--", alpha=0.4)
|
||||
plt.tight_layout()
|
||||
p = os.path.join(PLOTS, "weighted_choice_compare.png")
|
||||
plt.savefig(p, dpi=130)
|
||||
plt.close()
|
||||
print("saved:", p)
|
||||
|
||||
|
||||
def main():
|
||||
means = load_means()
|
||||
grouped_bar(means, 0, "Время, мс (среднее по 7 запускам, лог. шкала)",
|
||||
"Время поиска пути", "time_compare.png", log=True)
|
||||
grouped_bar(means, 1, "Число посещённых клеток (лог. шкала)",
|
||||
"Сколько клеток посетил алгоритм", "visited_compare.png", log=True)
|
||||
grouped_bar(means, 2, "Длина пути (клеток)",
|
||||
"Длина найденного пути", "path_compare.png", log=False)
|
||||
weighted_choice_chart(means)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Reference in New Issue
Block a user