这本是课程的一个作业研究搜索算法，当时研究了一下Tkinter，然后写了个很简单的机器人走迷宫的界面，并且使用了各种搜索算法来进行搜索，如下图：
使用A*寻找最优路径：
由于时间关系，不分析了，我自己贴代码吧。希望对一些也要用Tkinter的人有帮助。
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
|
from Tkinter import *from random import *import timeimport numpy as npimport utilclass Directions: NORTH = 'North' SOUTH = 'South' EAST = 'East' WEST = 'West'# Detect elements in the mapwindow = Tk()window.title('CityBusPlanner')window.resizable(0,0)width = 25(x, y) = (22, 22)totalsteps = 0buidings = [(0, 0), (1, 0), (2, 0), (3, 0), (7, 0), (8, 0), (11, 0), (12, 0), (13, 0), (17, 0), (18, 0), (21, 0), (21, 1), (2, 2), (5, 2), (8, 2), (9, 2), (12, 2), (14, 2), (15, 2), (16, 2), (17, 2), (21, 2), (2, 3), (4, 3), (5, 3), (7, 3), (8, 3), (11, 3), (17, 3), (18, 3), (19, 3), (2, 4), (4, 4), (5, 4), (8, 4), (9, 4), (14, 4), (15, 4),(17, 4), (18, 4), (19, 4), (0, 6), (2, 6), (4, 6), (7, 6), (8, 6), (11, 6), (12, 6), (14, 6), (15, 6),(16, 6), (18, 6), (19, 6), (2, 7), (5, 7), (21, 7), (0, 8), (2, 8), (11, 8), (14, 8), (15, 8), (17, 8), (18, 8), (21, 8), (4, 9), (5, 9), (7, 9), (9, 9), (11, 9), (14, 9), (21, 9), (2, 10), (7, 10), (14, 10), (17, 10), (19, 10), (0, 11), (2, 11), (4, 11), (5, 11), (7, 11), (8, 11), (9, 11), (11, 11), (12, 11), (14, 11), (15, 11), (16, 11), (17, 11), (18, 11), (19, 11), (0, 13), (2, 13), (3, 13), (5, 13), (7, 13), (8, 13), (9, 13), (14, 13), (17, 13), (18, 13), (21, 13), (2, 14), (3, 14), (5, 14), (7, 14),(9, 14), (12, 14), (14, 14), (15, 14), (17, 14), (18, 14), (21, 14), (2, 15), (3, 15), (5, 15), (7, 15), (9, 15), (12, 15), (15, 15), (19, 15), (21, 15), (0, 16), (21, 16), (0, 17), (3, 17), (5, 17), (7, 17),(9, 17), (11, 17), (14, 17), (15, 17), (17, 17), (18, 17), (21, 17), (2, 18), (3, 18), (5, 18), (7, 18),(9, 18), (11, 18), (14, 18), (17, 18), (18, 18), (3, 19), (5, 19), (7, 19), (9, 19), (11, 19), (12, 19), (14, 19), (17, 19), (18, 19), (0, 21), (1, 21), (2, 21), (5, 21), (6, 21), (9, 21), (10, 21), (11, 21), (12, 21), (15, 21), (16, 21), (18, 21), (19, 21), (21, 21)]walls = [(10, 0), (0, 12), (21, 12), (14, 21)]park = [(14, 0), (15, 0), (16, 0)]robotPos = (21, 12)view = Canvas(window, width=x * width, height=y * width)view.grid(row=0, column=0)searchMapButton = Button(window,text = 'search')searchMapButton.grid(row = 0,column = 1)robotView = Canvas(window,width=x * width, height=y * width)robotView.grid(row = 0,column = 2)def formatColor(r, g, b): return '#%02x%02x%02x' % (int(r * 255), int(g * 255), int(b * 255))def cityMap(): global width, x, y, buidings,walls,park,robot for i in range(x): for j in range(y): view.create_rectangle( i * width, j * width, (i + 1) * width, (j + 1) * width, fill='white', outline='gray', width=1) for (i, j) in buidings: view.create_rectangle( i * width, j * width, (i + 1) * width, (j + 1) * width, fill='black', outline='gray', width=1) for (i,j) in walls: view.create_rectangle( i * width, j * width, (i + 1) * width, (j + 1) * width, fill='blue', outline='gray', width=1) for (i,j) in park: view.create_rectangle( i * width, j * width, (i + 1) * width, (j + 1) * width, fill='red', outline='gray', width=1)def robotCityMap(): global width, x, y, buidings,walls,park,robot,robotPos for i in range(x): for j in range(y): robotView.create_rectangle( i * width, j * width, (i + 1) * width, (j + 1) * width, fill='black', width=1) robotView.create_rectangle( robotPos[0] * width, robotPos[1] * width, (robotPos[0] + 1) * width, (robotPos[1] + 1) * width, fill='white', outline='gray', width=1)# Create City MapcityMap()# Create Robot ViewrobotCityMap()# Create a robotrobot = view.create_rectangle(robotPos[0] * width + width * 2 / 10, robotPos[1] * width + width * 2 / 10, robotPos[0] * width + width * 8 / 10, robotPos[1] * width + width * 8 / 10, fill="orange", width=1, tag="robot")robotSelf = robotView.create_rectangle(robotPos[0] * width + width * 2 / 10, robotPos[1] * width + width * 2 / 10, robotPos[0] * width + width * 8 / 10, robotPos[1] * width + width * 8 / 10, fill="orange", width=1, tag="robot")visited = [robotPos]def move(dx,dy): global robot,x,y,robotPos,robotSelf,view global totalsteps totalsteps = totalsteps + 1 newX = robotPos[0] + dx newY = robotPos[1] + dy if (not isEdge(newX, newY)) and (not isBlock(newX, newY)): #print "move %d" % totalsteps view.coords(robot, (newX) * width + width * 2 / 10, (newY) * width + width * 2 / 10, (newX) * width + width * 8 / 10, (newY) * width + width * 8 / 10) robotView.coords(robotSelf, (newX) * width + width * 2 / 10, (newY) * width + width * 2 / 10, (newX) * width + width * 8 / 10, (newY) * width + width * 8 / 10) robotPos = (newX, newY) if robotPos not in visited: visited.append(robotPos) visitedPanel = robotView.create_rectangle( robotPos[0] * width, robotPos[1] * width, (robotPos[0] + 1) * width, (robotPos[1] + 1) * width, fill='white', outline='gray', width=1) robotView.tag_lower(visitedPanel,robotSelf) else: print "move error"def callUp(event): move(0,-1)def callDown(event): move(0, 1)def callLeft(event): move(-1, 0)def callRight(event): move(1, 0)def isBlock(newX,newY): global buidings,x,y for (i,j) in buidings: if (i == newX) and (j == newY): return True return Falsedef isEdge(newX,newY): global x,y if newX >= x or newY >= y or newX < 0 or newY < 0 : return True return Falsedef getSuccessors(robotPos): n = Directions.NORTH w = Directions.WEST s = Directions.SOUTH e = Directions.EAST successors = [] posX = robotPos[0] posY = robotPos[1] if not isBlock(posX - 1, posY) and not isEdge(posX - 1,posY): successors.append(w) if not isBlock(posX, posY + 1) and not isEdge(posX,posY + 1): successors.append(s) if not isBlock(posX + 1, posY) and not isEdge(posX + 1,posY): successors.append(e) if not isBlock(posX, posY -1) and not isEdge(posX,posY - 1): successors.append(n) return successorsdef getNewPostion(position,action): posX = position[0] posY = position[1] n = Directions.NORTH w = Directions.WEST s = Directions.SOUTH e = Directions.EAST if action == n: return (posX,posY - 1) elif action == w: return (posX - 1,posY) elif action == s: return (posX,posY + 1) elif action == e: return (posX + 1,posY)delay = Falsedef runAction(actions): global delay n = Directions.NORTH w = Directions.WEST s = Directions.SOUTH e = Directions.EAST for i in actions: if delay: time.sleep(0.05) if i == n: #print "North" move(0, -1) elif i == w: #print "West" move(-1, 0) elif i == s: #print "South" move(0, 1) elif i == e: #sprint "East" move(1, 0) view.update()def searchMapTest(event): global robotPos actions = [] position = robotPos for i in range(100): successors = getSuccessors(position) successor = successors[randint(0, len(successors) - 1)] actions.append(successor) position = getNewPostion(position, successor) print actions runAction(actions)def reverseSuccessor(successor): n = Directions.NORTH w = Directions.WEST s = Directions.SOUTH e = Directions.EAST if successor == n: return s elif successor == w: return e elif successor == s: return n elif successor == e: return wroads = set()detectedBuildings = {}blockColors = {}blockIndex = 0def updateBuildings(detectedBuildings): global robotView,width for block,buildings in detectedBuildings.items(): color = blockColors[block] for building in buildings: robotView.create_rectangle( building[0] * width, building[1] * width, (building[0] + 1) * width, (building[1] + 1) * width, fill=color, outline=color, width=1)def addBuilding(position): global blockIndex,detectedBuildings isAdd = False addBlock = '' for block,buildings in detectedBuildings.items(): for building in buildings: if building == position: return if util.manhattanDistance(position, building) == 1: if not isAdd: buildings.add(position) isAdd = True addBlock = block break else: #merge two block for building in detectedBuildings[block]: detectedBuildings[addBlock].add(building) detectedBuildings.pop(block) if not isAdd: newBlock = set([position]) blockIndex = blockIndex + 1 detectedBuildings['Block %d' % blockIndex] = newBlock color = formatColor(random(), random(), random()) blockColors['Block %d' % blockIndex] = color updateBuildings(detectedBuildings)def addRoad(position): global robotView,width,robotSelf visitedPanel = robotView.create_rectangle( position[0] * width, position[1] * width, (position[0] + 1) * width, (position[1] + 1) * width, fill='white', outline='gray', width=1) robotView.tag_lower(visitedPanel,robotSelf)def showPath(positionA,positionB,path): global robotView,width,view view.create_oval(positionA[0] * width + width * 3 / 10, positionA[1] * width + width * 3 / 10, positionA[0] * width + width * 7 / 10, positionA[1] * width + width * 7 / 10, fill='yellow', width=1) nextPosition = positionA for action in path: nextPosition = getNewPostion(nextPosition, action) view.create_oval(nextPosition[0] * width + width * 4 / 10, nextPosition[1] * width + width * 4 / 10, nextPosition[0] * width + width * 6 / 10, nextPosition[1] * width + width * 6 / 10, fill='yellow', width=1) view.create_oval(positionB[0] * width + width * 3 / 10, positionB[1] * width + width * 3 / 10, positionB[0] * width + width * 7 / 10, positionB[1] * width + width * 7 / 10, fill='yellow', width=1)hasDetected = set()def detectLocation(position): if position not in hasDetected: hasDetected.add(position) if isBlock(position[0],position[1]): addBuilding(position) elif not isEdge(position[0],position[1]): addRoad(position)def detect(position): posX = position[0] posY = position[1] detectLocation((posX,posY + 1)) detectLocation((posX,posY - 1)) detectLocation((posX + 1,posY)) detectLocation((posX - 1,posY))def heuristic(positionA,positionB): return util.manhattanDistance(positionA,positionB)def AstarSearch(positionA,positionB): "Step 1: define closed: a set" closed = set() "Step 2: define fringe: a PriorityQueue " fringe = util.PriorityQueue() "Step 3: insert initial node to fringe" "Construct node to be a tuple (location,actions)" initialNode = (positionA,[]) initCost = 0 + heuristic(initialNode[0],positionB) fringe.push(initialNode,initCost) "Step 4: Loop to do search" while not fringe.isEmpty(): node = fringe.pop() if node[0] == positionB: return node[1] if node[0] not in closed: closed.add(node[0]) for successor in getSuccessors(node[0]): actions = list(node[1]) actions.append(successor) newPosition = getNewPostion(node[0], successor) childNode = (newPosition,actions) cost = len(actions) + heuristic(childNode[0],positionB) fringe.push(childNode,cost) return []def AstarSearchBetweenbuildings(building1,building2): "Step 1: define closed: a set" closed = set() "Step 2: define fringe: a PriorityQueue " fringe = util.PriorityQueue() "Step 3: insert initial node to fringe" "Construct node to be a tuple (location,actions)" initialNode = (building1,[]) initCost = 0 + heuristic(initialNode[0],building2) fringe.push(initialNode,initCost) "Step 4: Loop to do search" while not fringe.isEmpty(): node = fringe.pop() if util.manhattanDistance(node[0],building2) == 1: return node[1] if node[0] not in closed: closed.add(node[0]) for successor in getSuccessors(node[0]): actions = list(node[1]) actions.append(successor) newPosition = getNewPostion(node[0], successor) childNode = (newPosition,actions) cost = len(actions) + heuristic(childNode[0],building2) fringe.push(childNode,cost) return []def calculatePositions(buildingA,path): positions = set() positions.add(buildingA) nextPosition = buildingA for action in path: nextPosition = getNewPostion(nextPosition, action) positions.add(nextPosition) return positionsdef showRoad(fullRoad): global view,width for road in fullRoad: view.create_oval(road[0] * width + width * 4 / 10, road[1] * width + width * 4 / 10, road[0] * width + width * 6 / 10, road[1] * width + width * 6 / 10, fill='yellow', width=1) view.update()def search(node): successors = getSuccessors(node[0]) detect(node[0]) for successor in successors: nextPosition = getNewPostion(node[0], successor) if nextPosition not in roads: runAction([successor]) # to the next node roads.add(nextPosition) search((nextPosition,[successor],[reverseSuccessor(successor)])) runAction(node[2]) #back to top nodedef searchConsiderTopVisit(node,topWillVisit): successors = getSuccessors(node[0]) detect(node[0]) newTopWillVisit = set(topWillVisit) for successor in successors: nextPosition = getNewPostion(node[0], successor) newTopWillVisit.add(nextPosition) for successor in successors: nextPosition = getNewPostion(node[0], successor) if nextPosition not in roads and nextPosition not in topWillVisit: runAction([successor]) # to the next node roads.add(nextPosition) newTopWillVisit.remove(nextPosition) searchConsiderTopVisit((nextPosition,[successor],[reverseSuccessor(successor)]),newTopWillVisit) runAction(node[2]) #back to top nodedef searchShortestPathBetweenBlocks(block1,block2): shortestPath = [] buildingA = (0,0) buildingB = (0,0) for building1 in block1: for building2 in block2: path = AstarSearchBetweenbuildings(building1, building2) if len(shortestPath) == 0: shortestPath = path buildingA = building1 buildingB = building2 elif len(path) < len(shortestPath): shortestPath = path buildingA = building1 buildingB = building2 return (buildingA,buildingB,shortestPath)def addBuildingToBlocks(linkedBlock,buildingA): global detectedBuildings newLinkedBlock = linkedBlock.copy() for block,buildings in detectedBuildings.items(): for building in buildings: if util.manhattanDistance(buildingA, building) == 1: newLinkedBlock[block] = buildings break return newLinkedBlockdef bfsSearchNextBlock(initBuilding,linkedBlock): global detectedBuildings closed = set() fringe = util.Queue() initNode = (initBuilding,[]) fringe.push(initNode) while not fringe.isEmpty(): node = fringe.pop() newLinkedBlock = addBuildingToBlocks(linkedBlock,node[0]) if len(newLinkedBlock) == len(detectedBuildings): return node[1] if len(newLinkedBlock) > len(linkedBlock): # find a new block actions = list(node[1]) ''' if len(node[1]) > 0: lastAction = node[1][len(node[1]) - 1] for successor in getSuccessors(node[0]): if successor == lastAction: nextPosition = getNewPostion(node[0], successor) actions.append(successor) return actions + bfsSearchNextBlock(nextPosition, newLinkedBlock) ''' return node[1] + bfsSearchNextBlock(node[0], newLinkedBlock) if node[0] not in closed: closed.add(node[0]) for successor in getSuccessors(node[0]): actions = list(node[1]) actions.append(successor) nextPosition = getNewPostion(node[0], successor) childNode = (nextPosition,actions) fringe.push(childNode) return []def isGoal(node): global detectedBuildings,robotPos linkedBlock = {} positions = calculatePositions(robotPos, node[1]) for position in positions: for block,buildings in detectedBuildings.items(): for building in buildings: if util.manhattanDistance(position, building) == 1: linkedBlock[block] = buildings print len(linkedBlock) if len(linkedBlock) == 17: return True else: return Falsedef roadHeuristic(road): return 0def AstarSearchRoad(): global robotPos,detectedBuildings "Step 1: define closed: a set" closed = set() "Step 2: define fringe: a PriorityQueue " fringe = util.PriorityQueue() "Step 3: insert initial node to fringe" "Construct node to be a tuple (location,actions)" initRoad = (robotPos,[]) initCost = 0 + roadHeuristic(initRoad) fringe.push(initRoad,initCost) "Step 4: Loop to do search" while not fringe.isEmpty(): node = fringe.pop() if isGoal(node): print len(closed) return node[1] if node[0] not in closed: closed.add(node[0]) for successor in getSuccessors(node[0]): actions = list(node[1]) actions.append(successor) newPosition = getNewPostion(node[0], successor) childNode = (newPosition,actions) cost = len(actions) + roadHeuristic(childNode) fringe.push(childNode,cost) return []def searchRoad(building): global detectedBuildings,robotPos linkedBlock = {} initBuilding = building return bfsSearchNextBlock(initBuilding,linkedBlock)def searchShortestRoad(): shortestRoad = [] shortestPositions = set() for block,buildings in detectedBuildings.items(): for building in buildings: road = searchRoad(building) positions = calculatePositions(building, road) if len(shortestPositions) == 0 or len(positions) < len(shortestPositions): shortestRoad = road shortestPositions = positions print len(shortestPositions) showRoad(shortestPositions)def searchMap(event): print "Search Map" global robotPos,roads,detectedBuildings,delay actions = [] #roads = set()s #roads.add(robotPos) #fringe = util.Stack() initNode = (robotPos,[],[]) # (position,forwardActions,backwarsdActions) #fringe.push(initNode) roads.add(robotPos) search(initNode) #searchConsiderTopVisit(initNode, set()) print detectedBuildings print len(detectedBuildings) #path = AstarSearchBetweenbuildings((6,21), (2, 18)) #showPath((6,21),(2,18), path) ''' shortestRoad = set() for block1 in detectedBuildings.values(): roads = set() for block2 in detectedBuildings.values(): if not block1 == block2: (buildingA,buildingB,path) = searchShortestPathBetweenBlocks(block1, block2) #showPath(buildingA,buildingB,path) positions = calculatePositions(buildingA,buildingB,path) roads = roads | positions if len(shortestRoad) == 0 or len(roads) < len(shortestRoad): shortestRoad = roads print len(shortestRoad) showRoad(shortestRoad) ''' ''' block1 = detectedBuildings.values()[3] print block1 block2 = detectedBuildings.values()[5] print block2 (buildingA,buildingB,path) = searchShortestPathBetweenBlocks(block1, block2) print buildingA,buildingB,path showPath(buildingA,buildingB,path) block1 = detectedBuildings.values()[10] print block1 block2 = detectedBuildings.values()[20] print block2 (buildingA,buildingB,path) = searchShortestPathBetweenBlocks(block1, block2) print buildingA,buildingB,path showPath(buildingA,buildingB,path) ''' searchShortestRoad() ''' path = searchRoad() #path = AstarSearchRoad() positions = calculatePositions(robotPos, path) print len(positions) showRoad(positions) delay = True #runAction(path) '''window.bind("<Up>", callUp)window.bind("<Down>", callDown)window.bind("<Right>", callRight)window.bind("<Left>", callLeft)window.bind("s", searchMap)searchMapButton.bind("<Button-1>",searchMap)window.mainloop() |
下面的util.py使用的是加州伯克利的代码：
|
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
|
# util.py# -------# Licensing Information: You are free to use or extend these projects for# educational purposes provided that (1) you do not distribute or publish# solutions, (2) you retain this notice, and (3) you provide clear# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.## Attribution Information: The Pacman AI projects were developed at UC Berkeley.# The core projects and autograders were primarily created by John DeNero# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).# Student side autograding was added by Brad Miller, Nick Hay, and# Pieter Abbeel (pabbeel@cs.berkeley.edu).import sysimport inspectimport heapq, random""" Data structures useful for implementing SearchAgents"""class Stack: "A container with a last-in-first-out (LIFO) queuing policy." def __init__(self): self.list = [] def push(self,item): "Push 'item' onto the stack" self.list.append(item) def pop(self): "Pop the most recently pushed item from the stack" return self.list.pop() def isEmpty(self): "Returns true if the stack is empty" return len(self.list) == 0class Queue: "A container with a first-in-first-out (FIFO) queuing policy." def __init__(self): self.list = [] def push(self,item): "Enqueue the 'item' into the queue" self.list.insert(0,item) def pop(self): """ Dequeue the earliest enqueued item still in the queue. This operation removes the item from the queue. """ return self.list.pop() def isEmpty(self): "Returns true if the queue is empty" return len(self.list) == 0class PriorityQueue: """ Implements a priority queue data structure. Each inserted item has a priority associated with it and the client is usually interested in quick retrieval of the lowest-priority item in the queue. This data structure allows O(1) access to the lowest-priority item. Note that this PriorityQueue does not allow you to change the priority of an item. However, you may insert the same item multiple times with different priorities. """ def __init__(self): self.heap = [] self.count = 0 def push(self, item, priority): # FIXME: restored old behaviour to check against old results better # FIXED: restored to stable behaviour entry = (priority, self.count, item) # entry = (priority, item) heapq.heappush(self.heap, entry) self.count += 1 def pop(self): (_, _, item) = heapq.heappop(self.heap) # (_, item) = heapq.heappop(self.heap) return item def isEmpty(self): return len(self.heap) == 0class PriorityQueueWithFunction(PriorityQueue): """ Implements a priority queue with the same push/pop signature of the Queue and the Stack classes. This is designed for drop-in replacement for those two classes. The caller has to provide a priority function, which extracts each item's priority. """ def __init__(self, priorityFunction): "priorityFunction (item) -> priority" self.priorityFunction = priorityFunction # store the priority function PriorityQueue.__init__(self) # super-class initializer def push(self, item): "Adds an item to the queue with priority from the priority function" PriorityQueue.push(self, item, self.priorityFunction(item))def manhattanDistance( xy1, xy2 ): "Returns the Manhattan distance between points xy1 and xy2" return abs( xy1[0] - xy2[0] ) + abs( xy1[1] - xy2[1] ) |
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持服务器之家。
原文链接：http://blog.csdn.net/songrotek/article/details/48023301
