f4cbb28
joyvan 6 years ago
4 changed file(s) with 1190 addition(s) and 402 deletion(s). Raw diff Collapse all Expand all
5656 },
5757 {
5858 "cell_type": "code",
59 "execution_count": null,
59 "execution_count": 2,
6060 "metadata": {},
6161 "outputs": [],
6262 "source": [
7373 },
7474 {
7575 "cell_type": "code",
76 "execution_count": null,
77 "metadata": {},
78 "outputs": [],
76 "execution_count": 3,
77 "metadata": {},
78 "outputs": [
79 {
80 "data": {
81 "image/png": 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\n",
82 "text/plain": [
83 "<Figure size 432x576 with 1 Axes>"
84 ]
85 },
86 "metadata": {},
87 "output_type": "display_data"
88 }
89 ],
7990 "source": [
8091 "# 定义节点列表\n",
8192 "node_list = ['A', 'B', 'C', 'D', 'E', 'F', 'G']\n",
132143 },
133144 {
134145 "cell_type": "code",
135 "execution_count": null,
136 "metadata": {},
137 "outputs": [],
146 "execution_count": 4,
147 "metadata": {},
148 "outputs": [
149 {
150 "data": {
151 "image/png": 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\n",
152 "text/plain": [
153 "<Figure size 432x576 with 1 Axes>"
154 ]
155 },
156 "metadata": {},
157 "output_type": "display_data"
158 }
159 ],
138160 "source": [
139161 "g.show_graph(this_path=\"ABDG\")"
140162 ]
182204 },
183205 {
184206 "cell_type": "code",
185 "execution_count": null,
186 "metadata": {},
187 "outputs": [],
207 "execution_count": 5,
208 "metadata": {},
209 "outputs": [
210 {
211 "data": {
212 "image/png": 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\n",
213 "text/plain": [
214 "<Figure size 1080x324 with 1 Axes>"
215 ]
216 },
217 "metadata": {
218 "needs_background": "light"
219 },
220 "output_type": "display_data"
221 }
222 ],
188223 "source": [
189224 "# 查看搜索树\n",
190225 "g.show_search_tree()"
341376 },
342377 {
343378 "cell_type": "code",
344 "execution_count": null,
345 "metadata": {},
346 "outputs": [],
379 "execution_count": 6,
380 "metadata": {},
381 "outputs": [
382 {
383 "data": {
384 "image/png": 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\n",
385 "text/plain": [
386 "<Figure size 1080x324 with 1 Axes>"
387 ]
388 },
389 "metadata": {
390 "needs_background": "light"
391 },
392 "output_type": "display_data"
393 }
394 ],
347395 "source": [
348396 "# 为搜索算法提供辅助信息\n",
349397 "g.help_info = {'A': 30, 'B': 20, 'C': 19, 'D':10, 'E':5, 'F':25, 'G': 0}\n",
388436 },
389437 {
390438 "cell_type": "code",
391 "execution_count": null,
392 "metadata": {},
393 "outputs": [],
439 "execution_count": 10,
440 "metadata": {},
441 "outputs": [
442 {
443 "data": {
444 "image/png": 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\n",
445 "text/plain": [
446 "<Figure size 1080x324 with 1 Axes>"
447 ]
448 },
449 "metadata": {
450 "needs_background": "light"
451 },
452 "output_type": "display_data"
453 }
454 ],
394455 "source": [
395456 "# 为搜索算法提供辅助信息\n",
396457 "g.help_info = {'A': 30, 'B': 20, 'C': 19, 'D':10, 'E':5, 'F':25, 'G': 0}\n",
400461 },
401462 {
402463 "cell_type": "code",
403 "execution_count": null,
404 "metadata": {},
405 "outputs": [],
464 "execution_count": 9,
465 "metadata": {},
466 "outputs": [
467 {
468 "data": {
469 "image/png": 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\n",
470 "text/plain": [
471 "<Figure size 1080x324 with 1 Axes>"
472 ]
473 },
474 "metadata": {
475 "needs_background": "light"
476 },
477 "output_type": "display_data"
478 }
479 ],
406480 "source": [
407481 "# 可以调整辅助信息的比重\n",
408482 "# 当只考虑额外信息时,即 origin_info_weight 设置为 0 的时候,A* 算法退化为贪婪算法。\n",
439513 },
440514 {
441515 "cell_type": "code",
442 "execution_count": null,
443 "metadata": {},
444 "outputs": [],
516 "execution_count": 12,
517 "metadata": {},
518 "outputs": [
519 {
520 "data": {
521 "image/png": 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\n",
522 "text/plain": [
523 "<Figure size 432x576 with 1 Axes>"
524 ]
525 },
526 "metadata": {},
527 "output_type": "display_data"
528 }
529 ],
445530 "source": [
446531 "node_list = [\"0\",\"1\",\"2\",\"3\",\"4\"]\n",
447532 "weighted_edges_list = [(\"0\",\"1\",10), (\"0\",\"2\",10),\n",
7777 },
7878 {
7979 "cell_type": "code",
80 "execution_count": null,
80 "execution_count": 1,
8181 "metadata": {},
8282 "outputs": [],
8383 "source": [
8484 "# 首先导入必要的包\n",
85 "from search import SearchGraph\n",
85 "from search import Graph\n",
8686 "import collections\n",
8787 "import matplotlib.pyplot as plt\n",
8888 "import collections\n",
9494 },
9595 {
9696 "cell_type": "code",
97 "execution_count": null,
98 "metadata": {},
99 "outputs": [],
97 "execution_count": 5,
98 "metadata": {},
99 "outputs": [
100 {
101 "data": {
102 "image/png": 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\n",
103 "text/plain": [
104 "<Figure size 432x576 with 1 Axes>"
105 ]
106 },
107 "metadata": {},
108 "output_type": "display_data"
109 }
110 ],
100111 "source": [
101112 "# 定义节点列表\n",
102113 "node_list = ['A', 'B', 'C', 'D', 'E', 'F', 'G']\n",
111122 "nodes_pos = {\"A\": (1, 1), \"B\": (3, 3), \"C\": (5, 0), \"D\": (9, 2),\n",
112123 " \"E\": (7, 4), \"F\": (6,6),\"G\": (11,5)}\n",
113124 "\n",
114 "# 绘制无向图\n",
115 "g = SearchGraph(node_list, weighted_edges_list, 'A', 'G', max_depth=3, nodes_pos = nodes_pos)\n",
125 "# 实例化图\n",
126 "g = Graph()\n",
127 "g.add_nodes_from(node_list)\n",
128 "g.add_weighted_edges_from(weighted_edges_list)\n",
129 "g.set_nodes_pos(nodes_pos)\n",
130 "\n",
131 "# 设置起点\n",
132 "g.set_start_node('A')\n",
133 "# 设置目标点\n",
134 "g.set_target_node(\"G\")\n",
135 "# 设置最大搜索深度\n",
136 "g.set_max_depth(3)\n",
137 "\n",
116138 "g.show_graph()"
117139 ]
118140 },
175197 },
176198 {
177199 "cell_type": "code",
178 "execution_count": null,
179 "metadata": {},
180 "outputs": [],
200 "execution_count": 6,
201 "metadata": {},
202 "outputs": [
203 {
204 "data": {
205 "image/png": 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\n",
206 "text/plain": [
207 "<Figure size 432x576 with 1 Axes>"
208 ]
209 },
210 "metadata": {},
211 "output_type": "display_data"
212 }
213 ],
181214 "source": [
182215 "g.show_graph(this_path=\"ABDG\")"
183216 ]
222255 },
223256 {
224257 "cell_type": "code",
225 "execution_count": null,
226 "metadata": {},
227 "outputs": [],
258 "execution_count": 7,
259 "metadata": {},
260 "outputs": [
261 {
262 "data": {
263 "image/png": 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\n",
264 "text/plain": [
265 "<Figure size 1080x324 with 1 Axes>"
266 ]
267 },
268 "metadata": {
269 "needs_background": "light"
270 },
271 "output_type": "display_data"
272 }
273 ],
228274 "source": [
229275 "g.show_search_tree()"
230276 ]
300346 },
301347 {
302348 "cell_type": "code",
303 "execution_count": null,
304 "metadata": {},
305 "outputs": [],
306 "source": [
307 "g.animation_search_tree('dfs')"
349 "execution_count": 9,
350 "metadata": {},
351 "outputs": [
352 {
353 "data": {
354 "image/png": 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\n",
355 "text/plain": [
356 "<Figure size 1080x324 with 1 Axes>"
357 ]
358 },
359 "metadata": {
360 "needs_background": "light"
361 },
362 "output_type": "display_data"
363 }
364 ],
365 "source": [
366 "g.animate_search_tree('dfs')"
308367 ]
309368 },
310369 {
323382 },
324383 {
325384 "cell_type": "code",
326 "execution_count": null,
327 "metadata": {},
328 "outputs": [],
329 "source": [
330 "g.animation_search_tree('bfs')"
385 "execution_count": 10,
386 "metadata": {},
387 "outputs": [
388 {
389 "data": {
390 "image/png": 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\n",
391 "text/plain": [
392 "<Figure size 1080x324 with 1 Axes>"
393 ]
394 },
395 "metadata": {
396 "needs_background": "light"
397 },
398 "output_type": "display_data"
399 }
400 ],
401 "source": [
402 "g.animate_search_tree('bfs')"
331403 ]
332404 },
333405 {
0 import matplotlib.pyplot as plt
1 import collections
2 from IPython import display
3 import networkx as nx
4 import numpy as np
5 import time
6
7
8 class SearchGraph():
9 def __init__(self,
10 node_list,
11 weighted_edges_list,
12 start_node,
13 target_node,
14 max_depth=1000,
15 nodes_pos=None,
16 help_info=None,):
17 self.node_list = node_list
18 self.weighted_edges_list = weighted_edges_list
19 self.start_node = start_node
20 self.target_node = target_node
21 self.nodes_pos = nodes_pos
22 self.max_depth = min(max_depth, len(node_list))
23 self.temp_best_path = None
24
25 self.weighted_edges_dic = {frozenset([e[0],e[1]]):e[2] for e in weighted_edges_list}
26 self.help_info = help_info
27 self.path_score={self.start_node:0}
28
29 self.animation_type = 'dfs'
30
31 self.basic_node_color = '#6CB6FF'
32 self.start_node_color = 'y'
33 self.target_node_color = 'r'
34 self.visited_node_color = 'g'
35
36 self.basic_edge_color = 'b'
37 self.visited_edge_color = 'g'
38
39 self.success_color = 'r'
40
41 self.correct_paths={}
42 self.show_correct_path = []
43 self.build_graph()
44 self.get_search_tree_node_position()
45 self.bfs_search()
46
47
48
49 def build_graph(self):
50 self.G = nx.Graph()
51 self.G.add_nodes_from(self.node_list)
52 self.G.add_weighted_edges_from(self.weighted_edges_list)
53
54 def get_search_tree_node_position(self):
55 """得到绘图的点的坐标
56 """
57 self.dfs_search()
58 # 得到 dfs 的搜索路径图
59 paths = self.dfs_path
60 # 得到每条路径的子路径
61 path_childern = {}
62 for path in paths:
63 father = path[:-1]
64 if father in paths:
65 if father in path_childern:
66 path_childern[father].append(path)
67 else:
68 path_childern[father] = [path]
69 # 对每条子路径排序
70 o_path_childern = collections.OrderedDict(sorted(path_childern.items()))
71 # 计算每个树图中每个节点的位置
72 tree_node_position = {self.start_node:(1, 0, 2)}
73 for path, sub_paths in o_path_childern.items():
74 y_pos = -1.0/self.max_depth * len(path)
75 dx = tree_node_position[path][2]/len(sub_paths)
76 sub_paths.sort()
77 for index, e_s in enumerate(sub_paths):
78 x_pos = tree_node_position[path][0] - tree_node_position[path][2]/2 + dx/2 + dx*index
79 tree_node_position[e_s]=(x_pos,y_pos, dx)
80 self.tree_node_position = tree_node_position
81
82 def show_edge_labels(self, ax, pos1, pos2, label):
83 (x1, y1) = pos1
84 (x2, y2) = pos2
85 (x, y) = (x1*0.5 + x2*0.5, y1*0.5 + y2*0.5)
86
87 angle = np.arctan2(y2 - y1, x2 - x1) / (2.0 * np.pi) * 360
88 if angle > 90:
89 angle -= 180
90 if angle < - 90:
91 angle += 180
92 xy = np.array((x, y))
93 trans_angle = ax.transData.transform_angles(np.array((angle,)),
94 xy.reshape((1, 2)))[0]
95 bbox = dict(boxstyle='round',
96 ec=(1.0, 1.0, 1.0),
97 fc=(1.0, 1.0, 1.0),
98 )
99 label = str(label)
100 ax.text(x, y,
101 label,
102 size=16,
103 color='k',
104 alpha=1,
105 horizontalalignment='center',
106 verticalalignment='center',
107 rotation=trans_angle,
108 transform=ax.transData,
109 bbox=bbox,
110 zorder=1,
111 clip_on=True,
112 )
113
114 def show_search_tree(self,
115 this_path=None,
116 show_success_color=False,
117 best_path=None
118 ):
119 """展示搜索树
120 """
121 # 画出树图
122 fig, ax = plt.subplots()
123 fig.set_figwidth(15)
124 fig.set_figheight(self.max_depth*1.5)
125 plt.axis('off')
126
127 for path, pos in self.tree_node_position.items():
128 if path[-1] == self.start_node:
129 node_color = self.start_node_color
130 edge_color = self.basic_edge_color
131 elif this_path and path in this_path:
132 if show_success_color:
133 node_color = self.success_color
134 edge_color = self.success_color
135 else:
136 node_color = self.visited_node_color
137 edge_color = self.visited_edge_color
138 elif path[-1] == self.target_node:
139 node_color = self.target_node_color
140 edge_color = self.basic_edge_color
141 else:
142 node_color = self.basic_node_color
143 edge_color = self.basic_edge_color
144 ax.scatter(pos[0], pos[1], c=node_color, s=1000,zorder=1)
145 plt.annotate(
146 path[-1],
147 xy=(pos[0], pos[1]),
148 xytext=(0, 0),
149 textcoords='offset points',
150 ha='center',
151 va='center',
152 size=15,)
153 if len(path)>1:
154 plt.plot([self.tree_node_position[path[:-1]][0],pos[0]],
155 [self.tree_node_position[path[:-1]][1],pos[1]],
156 color=edge_color,
157 zorder=0)
158 if len(path)>1:
159 label = self.weighted_edges_dic[frozenset([path[-2],path[-1]])]
160 if self.animation_type in ['greedy','a_star']:
161 label = self.help_info_weight*self.help_info[path[-1]] + self.origin_info_weight*label
162 self.show_edge_labels(ax, self.tree_node_position[path[:-1]][0:2], pos[0:2], label)
163 display.clear_output(wait=True)
164
165 show_res_text = ""
166 for e_c in self.show_correct_path:
167 show_res_text += '找到一条路径: %-7s' % e_c + '。距离为:' +str(self.correct_paths[e_c]) + '\n'
168 plt.text(0, -1.1, show_res_text, fontsize=18,horizontalalignment='left', verticalalignment='top',)
169
170 if best_path:
171 top_text = '最终最短路径为: %-7s' % this_path + '。距离为:' +str(self.correct_paths[this_path]) + '\n'
172 elif this_path and self.animation_type in ['dfs','bfs']:
173 top_text = '当前路径: %-7s' % this_path + '。距离为:' +str(self.path_score[this_path]) + '\n'
174 if self.temp_best_path:
175 top_text += '当前最短路径为: %-7s' % self.temp_best_path + '。距离为:' +str(self.correct_paths[self.temp_best_path]) + '\n'
176 else:
177 top_text = ''
178
179 plt.text(0, 0,
180 top_text,
181 fontsize=18,
182 horizontalalignment='left',
183 verticalalignment='top',)
184
185 if self.animation_type in ['greedy','a_star']:
186 show_greedy_text = self.generate_greedy_help_text(this_path)
187 plt.text(0, 0, show_greedy_text, fontsize=18, horizontalalignment='left', verticalalignment='top',)
188 plt.show()
189
190 def animation_search_tree(self,search_method='dfs', help_info_weight=1, origin_info_weight=1):
191 """动画展示搜索过程
192 """
193 self.animation_type = search_method
194 self.show_correct_path = []
195 self.temp_best_path = None
196 if search_method == 'bfs':
197 paths = self.bfs_path
198 elif search_method == 'dfs':
199 paths = self.dfs_path
200 elif search_method == 'greedy':
201 self.greedy_search()
202 paths = self.greedy_search_path
203 elif search_method == 'a_star':
204 self.a_star_search(help_info_weight=help_info_weight, origin_info_weight=origin_info_weight)
205 paths = self.greedy_search_path
206 else:
207 paths = []
208 for e_path in paths:
209 self.show_search_tree(e_path)
210 if e_path in self.correct_paths:
211 if not self.temp_best_path:
212 self.temp_best_path = e_path
213 elif self.path_score[e_path] < self.path_score[self.temp_best_path]:
214 self.temp_best_path = e_path
215 self.show_correct_path.append(e_path)
216 self.show_search_tree(e_path, True)
217 if search_method in ['greedy', 'a_star']:
218 time.sleep(5)
219 if search_method in ['bfs', 'dfs']:
220 if self.correct_paths:
221 best_path = min(self.correct_paths, key=self.correct_paths.get)
222 self.show_search_tree(best_path, True, True)
223
224 def animation_graph(self, search_method='bfs', help_info_weight=1, origin_info_weight=1):
225
226 """
227 """
228 self.animation_type = search_method
229 self.show_correct_path = []
230 if search_method == 'bfs':
231 paths = self.bfs_path
232 elif search_method == 'dfs':
233 paths = self.dfs_path
234 elif search_method == 'greedy':
235 self.greedy_search()
236 paths = self.greedy_search_path
237 elif search_method == 'a_star':
238 self.a_star_search(help_info_weight=help_info_weight, origin_info_weight=origin_info_weight)
239 paths = self.greedy_search_path
240 else:
241 paths = []
242 for e_path in paths:
243 self.show_graph(e_path)
244 if e_path in self.correct_paths:
245 self.show_correct_path.append(e_path)
246 self.show_graph(e_path, True)
247 time.sleep(5)
248 if search_method in ['bfs', 'dfs']:
249 best_path = min(self.correct_paths, key=self.correct_paths.get)
250 self.show_graph(best_path, True, True)
251
252 def show_graph(self, this_path='',
253 show_success_color=False,
254 best_path=None):
255 """
256 绘制图
257 :return:
258 """
259 fig, ax = plt.subplots()
260 fig.set_figwidth(6)
261 fig.set_figheight(8)
262 plt.axis('off')
263
264 # 绘制节点与边颜色
265 visited_edges = []
266 if not this_path:
267 this_path = self.start_node
268 path_node_list = list(this_path)
269 for i in range(1,len(path_node_list)):
270 visited_edges.append(frozenset([path_node_list[i],path_node_list[i-1]]))
271
272 # 节点与标识
273 nlabels = dict(zip(self.node_list, self.node_list))
274 edge_labels = dict([((u, v,), d['weight']) for u, v, d in self.G.edges(data=True)])
275
276 # 节点颜色变化
277 val_map = {self.target_node: self.target_node_color}
278 if path_node_list:
279 for i in path_node_list:
280 if show_success_color:
281 val_map[i] = self.success_color
282 else:
283 val_map[i] = self.visited_node_color
284 val_map[self.start_node] = self.start_node_color
285 values = [val_map.get(node, self.basic_node_color) for node in self.G.nodes()]
286
287 # 处理边的颜色
288 edge_colors = []
289 for edge in self.G.edges():
290 # 如果边在result_red_edges,分2种情况:
291 # 如果this_path[0]/this_path[-1] 对应起始点和终点,颜色为绿色,否则颜色为红色
292 # 如果边不在result_red_edges,则初始化边的颜色为黑色
293 if frozenset(edge) in visited_edges:
294 if show_success_color:
295 edge_colors.append(self.success_color)
296 else:
297 edge_colors.append(self.visited_edge_color)
298 else:
299 edge_colors.append(self.basic_edge_color)
300
301 # 绘制节点及其标签
302 nx.draw_networkx_nodes(self.G, self.nodes_pos, node_size=800, node_color=values, width=6.0)
303 nx.draw_networkx_labels(self.G, self.nodes_pos, nlabels, font_size=20)
304 # 绘制边及其标签
305 nx.draw_networkx_edges(self.G, self.nodes_pos, edge_color=edge_colors, width=2.0, alpha=1.0)
306 nx.draw_networkx_edge_labels(self.G, self.nodes_pos, edge_labels=edge_labels, font_size=18)
307
308 display.clear_output(wait=True)
309 # show_text = ""
310 # for e_c in self.show_correct_path:
311 # show_text += '找到一条路径: %-7s' % e_c + '。距离为:' +str(self.correct_paths[e_c]) + '\n'
312 # plt.text(0, -2.6, show_text, fontsize=18, horizontalalignment='left', verticalalignment='top', )
313
314 # if best_path:
315 # top_text = '最佳路径为: %-7s' % this_path + '。 距离为:' +str(self.correct_paths[this_path]) + '\n'
316 # elif this_path and self.animation_type in ['dfs','bfs']:
317 # top_text = '当前路径: %-7s' % this_path + '。 距离为:' +str(self.cal_dis(this_path)) + '\n'
318 # else:
319 # top_text = ''
320 # plt.text(0, 0,
321 # top_text,
322 # fontsize=18,
323 # horizontalalignment='left',
324 # verticalalignment='top',)
325 plt.show()
326
327 def _dfs_helper(self, G, node, father, target_node,level, res, path):
328 path+=str(node)
329 if len(path)>1:
330 self.path_score[path] = self.path_score[path[:-1]] + self.weighted_edges_dic[frozenset([path[-2],path[-1]])]
331 res.append(path)
332 # 找到目标,停止搜索
333 if node==target_node:
334 return
335 if level< self.max_depth:
336 for neighbor in sorted(G[node]):
337 if str(neighbor) not in path:
338 self._dfs_helper(G, neighbor, node, target_node, level+1, res, path)
339
340 def dfs_search(self):
341 dfs_path=[]
342 this_path=''
343 if self.start_node:
344 self._dfs_helper(self.G, self.start_node, None, self.target_node, 0, dfs_path, this_path)
345 self.dfs_path = dfs_path
346 for p in dfs_path:
347 if p[-1]==self.target_node and p not in self.correct_paths:
348 self.correct_paths[p] = self.cal_dis(p)
349
350 def bfs_search(self):
351 to_search=[self.start_node]
352 bfs_path = []
353 bfs_correct_path = []
354 depth = 0
355 while to_search:
356 this_search = to_search.pop(0)
357 if len(this_search)>self.max_depth+1 :
358 break
359 bfs_path.append(this_search)
360 if this_search[-1]==self.target_node:
361 bfs_correct_path.append(this_search)
362 continue
363 for ne in sorted(self.G[this_search[-1]]):
364 if ne not in this_search:
365 to_search.append(this_search+ne)
366 self.bfs_path = bfs_path
367 for p in bfs_path:
368 if p[-1]==self.target_node and p not in self.correct_paths:
369 self.correct_paths[p] = self.cal_dis(p)
370
371 def greedy_search(self, help_info_weight=1, origin_info_weight=0):
372 self.help_info_weight = help_info_weight
373 self.origin_info_weight = origin_info_weight
374 search_path = self.start_node
375 # 存储每一步的可选项及其分数,用来在动态演示时显示出来
376 search_scores = {}
377 while len(search_path) <= self.max_depth:
378 this_node = search_path[-1]
379 neighbour_nodes = [e_n for e_n in sorted(self.G[this_node]) if e_n not in search_path]
380 if len(neighbour_nodes) == 0:
381 search_scores[search_path]={}
382 break
383 if self.help_info:
384 scores = {e_n:help_info_weight*self.help_info[e_n]+origin_info_weight*self.weighted_edges_dic[frozenset([this_node,e_n])] for e_n in neighbour_nodes }
385 else:
386 scores = {e_n:self.weighted_edges_dic[frozenset([this_node,e_n])]
387 for e_n in neighbour_nodes }
388 search_scores[search_path]=scores
389 nearest_node = min(scores, key=scores.get)
390 search_path += nearest_node
391 if nearest_node == self.target_node:
392 break
393 self.greedy_search_path = [search_path[0:index+1] for index in range(len(search_path))]
394 self.search_scores = search_scores
395
396 def a_star_search(self, help_info_weight=1, origin_info_weight=1):
397 self.greedy_search(help_info_weight, origin_info_weight)
398
399
400 def generate_greedy_help_text(self,path):
401 if path[-1] == self.target_node:
402 return '抵达目标节点' + str(self.target_node)
403 elif path not in self.search_scores:
404 return '抵达最大搜索深度,未找到目标节点'
405
406 base_text = '当前可选的子节点及其信息值为 \n'+ \
407 str(self.search_scores[path]) + '\n'
408 if self.target_node in self.search_scores[path]:
409 return base_text + '当前可选的子节点包含了目标节点,\n所以选择目标节点'
410 elif len(self.search_scores[path]) == 1:
411 return base_text + '因为只有一个子节点,所以选择此节点'
412 else:
413 return base_text + '因为'+ \
414 str(min(self.search_scores[path], key=self.search_scores[path].get)) + \
415 '的值最小,所以选择此节点'
416
417 def cal_dis(self,path):
418 dis = 0
419 if len(path) > 1:
420 for i in range(len(path)-1):
421 dis += self.weighted_edges_dic[frozenset([path[i],path[i+1]])]
422 return dis
423
55 import time
66
77
8 class SearchGraph():
8 class Color:
9 # 绘图配色
10 # 基本的节点配色
11 basic_node_color = '#6CB6FF'
12 # 初始节点配色
13 start_node_color = 'y'
14 # 目标节点配色
15 target_node_color = 'r'
16 # 已访问的节点配色
17 visited_node_color = 'g'
18 # 基本边的配色
19 basic_edge_color = 'b'
20 # 已访问的边的配色
21 visited_edge_color = 'g'
22 # 抵达目标节点时的配色
23 success_color = 'r'
24
25
26 class Graph(nx.Graph):
927 def __init__(self,
10 node_list,
11 weighted_edges_list,
12 start_node,
13 target_node,
14 max_depth=1000,
15 nodes_pos=None,
16 help_info=None,):
17 self.node_list = node_list
18 self.weighted_edges_list = weighted_edges_list
28 start_node=None,
29 target_node=None):
30
31 # 初始化父类
32 nx.Graph.__init__(self)
33 # 绘制 graph 时各个节点的坐标值
34 self.nodes_pos = {}
35 # 搜索起点
1936 self.start_node = start_node
37 # 搜搜目标点
2038 self.target_node = target_node
39 # 搜索的最大深度
40 self.max_depth = None
41 # bfs 的历史查找路径,例如 ['A','AB', 'AD', 'ABC']
42 self.bfs_paths = []
43 # dfs 的历史查找路径,例如 ['A','AB', 'ABC', 'AD']
44 self.dfs_paths = []
45 # 每条历史路径的分数(历史距离)
46 self.path_score = {}
47 # 绘制搜索数时每个节点的坐标值
48 self.tree_node_position = {}
49 # 额外的辅助信息值,用于进行启发式搜索(贪婪或 A-star 搜索)
50 self.help_info = {}
51 # 额外辅助信息的权重
52 self.help_info_weight = 1
53 # 原始信息的权重
54 self.origin_info_weight = 1
55 # a_star 算法的历史查找路径
56 self.a_star_search_paths = []
57 # a_star 算法的中路径的得分
58 self.a_star_search_scores = {}
59 #
60 self.changed = True
61
62 def set_start_node(self, start_node):
63 """
64 设置起点
65 :param start_node: 起点
66 :return:
67 """
68 self.start_node = start_node
69 self.path_score = {self.start_node: 0}
70 self.changed = True
71
72 def set_target_node(self, target_node):
73 """
74 设置目标点
75 :param target_node: 目标点
76 :return:
77 """
78 self.target_node = target_node
79 self.path_score = {self.start_node: 0}
80 self.changed = True
81
82 def set_nodes_pos(self, nodes_pos):
83 """
84 设置 graph 内各个节点的坐标,绘图用,与搜索无关
85 :param nodes_pos: 字典,节点的坐标,
86 例如 {"A": (1, 1), "B": (3, 3), "C": (5, 0)}
87 :return:
88 """
2189 self.nodes_pos = nodes_pos
22 self.max_depth = min(max_depth, len(node_list))
23 self.temp_best_path = None
24
25 self.weighted_edges_dic = {frozenset([e[0],e[1]]):e[2] for e in weighted_edges_list}
90
91 def set_max_depth(self, max_depth):
92 """
93 设置最大搜索深度
94 :param max_depth: 整数,大于 0
95 :return:
96 """
97 max_depth = min(max_depth, len(self.nodes))
98 self.max_depth = max_depth
99 self.changed = True
100
101 def set_help_info(self, help_info):
102 """
103 设置辅助信息,用于进行启发式搜索(贪婪或 A-star 搜索)
104 :param help_info: 字典,
105 例如 {'A': 30, 'B': 20, 'C': 19 },为各个点到目标点的距离
106 :return:
107 """
26108 self.help_info = help_info
27 self.path_score={self.start_node:0}
28
29 self.animation_type = 'dfs'
30
31 self.basic_node_color = '#6CB6FF'
32 self.start_node_color = 'y'
33 self.target_node_color = 'r'
34 self.visited_node_color = 'g'
35
36 self.basic_edge_color = 'b'
37 self.visited_edge_color = 'g'
38
39 self.success_color = 'r'
40
41 self.correct_paths={}
42 self.show_correct_path = []
43 self.build_graph()
109
110 def show_graph(self, this_path=''):
111 """
112 绘制 graph
113 :param this_path: 设置一条图中的路径
114 :return:
115 """
116 # 当不传入路径时,默认在初始节点
117 this_path = this_path or self.start_node
118 # 根据当前你路径,处理节点和边的颜色
119 # 根据路径得到已访问的边,例如 'ABC' 得到 ['AB', 'BC']
120 visited_edges = []
121 for i in range(1, len(this_path)):
122 visited_edges.append(
123 frozenset([this_path[i], this_path[i - 1]]))
124 # 节点和边以及其显示的标签
125 node_labels = dict(zip(self.nodes(), self.nodes()))
126 edge_labels = dict(
127 [((u, v,), d['weight']) for u, v, d in self.edges(data=True)])
128
129 # 处理节点的颜色
130 node_color_map = {e_node: Color.visited_node_color for e_node in
131 this_path}
132 node_color_map[self.start_node] = Color.start_node_color
133 node_color_map[self.target_node] = Color.target_node_color
134 node_color = [node_color_map.get(node, Color.basic_node_color)
135 for node in self.nodes()]
136
137 # 处理每条边的颜色
138 edge_color = []
139 for edge in self.edges():
140 if frozenset(edge) in visited_edges:
141 edge_color.append(Color.visited_edge_color)
142 else:
143 edge_color.append(Color.basic_edge_color)
144
145 # 创建绘图
146 fig, ax = plt.subplots()
147 # 定义绘图的宽和高,并关闭坐标轴的显示
148 fig.set_figwidth(6)
149 fig.set_figheight(8)
150 plt.axis('off')
151
152 # 绘制节点及其标签
153 nx.draw_networkx_nodes(self, self.nodes_pos, node_size=800,
154 node_color=node_color, width=6.0)
155 nx.draw_networkx_labels(self, self.nodes_pos, node_labels,
156 font_size=20)
157 # 绘制边及其标签
158 nx.draw_networkx_edges(self, self.nodes_pos, edge_color=edge_color,
159 width=2.0, alpha=1.0)
160 nx.draw_networkx_edge_labels(self, self.nodes_pos,
161 edge_labels=edge_labels, font_size=18)
162 # 清除绘图区,显示新绘图
163 display.clear_output(wait=True)
164 plt.show()
165
166 def bfs_search(self):
167 """
168 使用迭代法进行广度优先搜索
169 :return:
170 """
171 # 待访问的路径
172 to_search = [self.start_node]
173 # 存储所有的已访问的路径
174 bfs_paths = []
175 # 当还有待访问的路径时
176 while to_search:
177 # 从待访问的路径中取第一个待访问路径
178 this_search = to_search.pop(0)
179 # 如果待访问的路径超过最大搜索深度,跳出循环
180 if len(this_search) > self.max_depth + 1:
181 break
182 # 把刚取出的路径存入已访问的路径中
183 bfs_paths.append(this_search)
184 # 如果路径的最后一个节点是目标节点,路径 AC 的最后一个节点是 C
185 if this_search[-1] == self.target_node:
186 # 其为一条正确的路径,将存入正确的路径列表中,
187 # 并不再继续往其子节点进行探索
188 continue
189 # 找到路径最后一个节点的相邻节点
190 else:
191 for ne in sorted(self.neighbors(this_search[-1])):
192 # 如果相邻节点不在路径中,即不存在回路
193 if ne not in this_search:
194 # 则加入到待访问的路径中
195 to_search.append(this_search + ne)
196 self.bfs_paths = bfs_paths
197
198 def _dfs_helper(self, node, target_node, level, dfs_paths, path):
199 """
200 深度优先搜索的辅助函数
201 :param node: 当前节点
202 :param target_node: 目标点
203 :param level: 搜索深度
204 :param dfs_paths: dfs 的历史搜索路径
205 :param path: 从哪一个路径来到当前节点
206 :return:
207 """
208 path += str(node)
209 # 更新路径的分数(距离)
210 if len(path) > 1:
211 self.path_score[path] = self.path_score[path[:-1]] + \
212 self.edges[path[-2], path[-1]]['weight']
213 # 存储 dfs 的历史搜索路径
214 dfs_paths.append(path)
215 # 找到目标,停止搜索
216 if node == target_node:
217 return
218 # 未达到最大搜索深度时,继续下一层搜索
219 if level < self.max_depth:
220 # 对当前节点的每一个相邻节点
221 for neighbor in sorted(self.neighbors(node)):
222 # 如果该相邻节点不在路径中,即没有出现回环,则递归调用,继续往下搜索
223 if str(neighbor) not in path:
224 self._dfs_helper(neighbor, target_node, level + 1,
225 dfs_paths, path)
226
227 def dfs_search(self):
228 """
229 使用递归法进行深度优先搜索
230 :return:
231 """
232 # dfs 的历史搜索路径
233 dfs_paths = []
234 this_path = ''
235 if self.start_node and self.target_node:
236 self._dfs_helper(self.start_node, self.target_node,
237 0, dfs_paths, this_path)
238 else:
239 print('请设置起点和目标点')
240 self.dfs_paths = dfs_paths
241 # 完成搜索后,可得到搜索树中各个节点的坐标
44242 self.get_search_tree_node_position()
45 self.bfs_search()
46
47
48
49 def build_graph(self):
50 self.G = nx.Graph()
51 self.G.add_nodes_from(self.node_list)
52 self.G.add_weighted_edges_from(self.weighted_edges_list)
53
243
54244 def get_search_tree_node_position(self):
55 """得到绘图的点的坐标
56 """
57 self.dfs_search()
245 """得到绘图时各个节点的坐标
246 """
58247 # 得到 dfs 的搜索路径图
59 paths = self.dfs_path
248 paths = self.dfs_paths
60249 # 得到每条路径的子路径
61 path_childern = {}
250 path_children = {}
62251 for path in paths:
63252 father = path[:-1]
64253 if father in paths:
65 if father in path_childern:
66 path_childern[father].append(path)
254 if father in path_children:
255 path_children[father].append(path)
67256 else:
68 path_childern[father] = [path]
257 path_children[father] = [path]
69258 # 对每条子路径排序
70 o_path_childern = collections.OrderedDict(sorted(path_childern.items()))
259 o_path_children = collections.OrderedDict(
260 sorted(path_children.items()))
71261 # 计算每个树图中每个节点的位置
72 tree_node_position = {self.start_node:(1, 0, 2)}
73 for path, sub_paths in o_path_childern.items():
74 y_pos = -1.0/self.max_depth * len(path)
75 dx = tree_node_position[path][2]/len(sub_paths)
262 tree_node_position = {self.start_node: (1, 0, 2)}
263 for path, sub_paths in o_path_children.items():
264 y_pos = -1.0 / self.max_depth * len(path)
265 dx = tree_node_position[path][2] / len(sub_paths)
76266 sub_paths.sort()
77267 for index, e_s in enumerate(sub_paths):
78 x_pos = tree_node_position[path][0] - tree_node_position[path][2]/2 + dx/2 + dx*index
79 tree_node_position[e_s]=(x_pos,y_pos, dx)
268 x_pos = tree_node_position[path][0] - tree_node_position[path][
269 2] / 2 + dx / 2 + dx * index
270 tree_node_position[e_s] = (x_pos, y_pos, dx)
80271 self.tree_node_position = tree_node_position
81
82 def show_edge_labels(self, ax, pos1, pos2, label):
272
273 def a_star_search(self, help_info_weight=1, origin_info_weight=0):
274 """
275 a-star 搜索, 当 origin_info_weight 为 0 时,则退化为贪婪搜索
276 :param help_info_weight: 辅助信息的比重
277 :param origin_info_weight: 原始信息的比重
278 :return:
279 """
280 # 存到类属性中,便于绘图时使用
281 self.help_info_weight = help_info_weight
282 self.origin_info_weight = origin_info_weight
283 # 初始路径为起点
284 search_path = self.start_node
285 # 存储每一步的可选项及其分数,用来在动态演示时显示出来
286 search_scores = {}
287 # 当搜索路径未超过最大搜索深度
288 while len(search_path) <= self.max_depth:
289 # 当前的节点
290 this_node = search_path[-1]
291 # 当前节点的子节点
292 neighbour_nodes = [e_n for e_n in sorted(self.neighbors(this_node))
293 if e_n not in search_path]
294 # 如果没有子节点,则跳出循环,结束搜索
295 if len(neighbour_nodes) == 0:
296 search_scores[search_path] = {}
297 break
298 # 计算每个子节点的得分并存储
299 scores = {e_n: help_info_weight * self.help_info[
300 e_n] + origin_info_weight * self.edges[this_node, e_n][
301 'weight'] for e_n in
302 neighbour_nodes}
303 search_scores[search_path] = scores
304 # 挑选最佳的子节点,并添加到路径中
305 nearest_node = min(scores, key=scores.get)
306 search_path += nearest_node
307 # 如果最佳的子节点是目标节点,跳出循环,结束搜索
308 if nearest_node == self.target_node:
309 break
310 # 把最终路径切分为每一步,便于动态展示,例如 ABCD 变为 [A, AB, ABC, ABCD ]
311 self.a_star_search_paths = [search_path[0:index + 1] for index in
312 range(len(search_path))]
313 self.a_star_search_scores = search_scores
314
315 def greedy_search(self):
316 """
317 贪婪搜索,就是 origin_info_weight权重为 0 时的 a-star 搜索
318 :return:
319 """
320 self.a_star_search(help_info_weight=1, origin_info_weight=0)
321
322 @staticmethod
323 def show_edge_labels(ax, pos1, pos2, label):
324 """
325 绘制搜索树的边
326 :param ax: 子图
327 :param pos1: 点 1 的坐标
328 :param pos2: 点 2 的坐标
329 :param label: 连接点 1 和点 2 的边上的文字
330 :return:
331 """
332 # 点1
83333 (x1, y1) = pos1
334 # 点2
84335 (x2, y2) = pos2
85 (x, y) = (x1*0.5 + x2*0.5, y1*0.5 + y2*0.5)
86
336 # 文字的位置
337 (x, y) = (x1 * 0.5 + x2 * 0.5, y1 * 0.5 + y2 * 0.5)
338 # 文字的角度
87339 angle = np.arctan2(y2 - y1, x2 - x1) / (2.0 * np.pi) * 360
88340 if angle > 90:
89341 angle -= 180
92344 xy = np.array((x, y))
93345 trans_angle = ax.transData.transform_angles(np.array((angle,)),
94346 xy.reshape((1, 2)))[0]
347 # 绘制文字框和文字
95348 bbox = dict(boxstyle='round',
96349 ec=(1.0, 1.0, 1.0),
97350 fc=(1.0, 1.0, 1.0),
98351 )
99 label = str(label)
352 label = str(label)
100353 ax.text(x, y,
101 label,
102 size=16,
103 color='k',
104 alpha=1,
105 horizontalalignment='center',
106 verticalalignment='center',
107 rotation=trans_angle,
108 transform=ax.transData,
109 bbox=bbox,
110 zorder=1,
111 clip_on=True,
112 )
113
114 def show_search_tree(self,
115 this_path=None,
354 label,
355 size=16,
356 color='k',
357 alpha=1,
358 horizontalalignment='center',
359 verticalalignment='center',
360 rotation=trans_angle,
361 transform=ax.transData,
362 bbox=bbox,
363 zorder=1,
364 clip_on=True,
365 )
366
367 def show_search_tree(self,
368 animation_type='bfs',
369 top_text='',
370 bottom_text='',
371 this_path=None,
116372 show_success_color=False,
117 best_path=None
118 ):
119 """展示搜索树
120 """
121 # 画出树图
373 ):
374 """
375 展示搜索树,动态展示搜索过程时,会调用此方法
376 :param animation_type: 动态演示的类型,如果是启发式搜索,边的权重需要变化
377 :param top_text: 上方的文字展示
378 :param bottom_text: 下方的文字展示
379 :param this_path: 当前路径
380 :param show_success_color: 成功找到目标点后,路径颜色的变换
381 :return:
382 """
383 # 如果对起始点,目标点或搜索深度进行了设置,需要重新绘制搜索树
384 if self.changed is True:
385 self.bfs_search()
386 self.dfs_search()
387 self.changed = False
388
389 # 创建子图
122390 fig, ax = plt.subplots()
391 # 定义绘图的宽度
123392 fig.set_figwidth(15)
124 fig.set_figheight(self.max_depth*1.5)
393 # 定义绘图的高度
394 fig.set_figheight(self.max_depth * 1.5)
395 # 关闭绘图中坐标轴的显示
125396 plt.axis('off')
126
397
398 # 对每条路径
127399 for path, pos in self.tree_node_position.items():
400 # 如果是初始点
128401 if path[-1] == self.start_node:
129 node_color = self.start_node_color
130 edge_color = self.basic_edge_color
402 node_color = Color.start_node_color
403 edge_color = Color.basic_edge_color
404 # 把当前路径的节点和边的颜色变为已访问的颜色
131405 elif this_path and path in this_path:
406 # 是否显示成功找到目标点
132407 if show_success_color:
133 node_color = self.success_color
134 edge_color = self.success_color
408 node_color = Color.success_color
409 edge_color = Color.success_color
135410 else:
136 node_color = self.visited_node_color
137 edge_color = self.visited_edge_color
411 node_color = Color.visited_node_color
412 edge_color = Color.visited_edge_color
413 # 如果路径的终点是目标点,改变目标点的颜色
138414 elif path[-1] == self.target_node:
139 node_color = self.target_node_color
140 edge_color = self.basic_edge_color
415 node_color = Color.target_node_color
416 edge_color = Color.basic_edge_color
417 # 其他的情况下,节点和边的颜色是正常色
141418 else:
142 node_color = self.basic_node_color
143 edge_color = self.basic_edge_color
144 ax.scatter(pos[0], pos[1], c=node_color, s=1000,zorder=1)
419 node_color = Color.basic_node_color
420 edge_color = Color.basic_edge_color
421 # 绘制节点
422 ax.scatter(pos[0], pos[1], c=node_color, s=1000, zorder=1)
423 # 绘制节点的标注
145424 plt.annotate(
146425 path[-1],
147426 xy=(pos[0], pos[1]),
149428 textcoords='offset points',
150429 ha='center',
151430 va='center',
152 size=15,)
153 if len(path)>1:
154 plt.plot([self.tree_node_position[path[:-1]][0],pos[0]],
155 [self.tree_node_position[path[:-1]][1],pos[1]],
431 size=15, )
432 if len(path) > 1:
433 # 绘制边
434 plt.plot([self.tree_node_position[path[:-1]][0], pos[0]],
435 [self.tree_node_position[path[:-1]][1], pos[1]],
156436 color=edge_color,
157437 zorder=0)
158 if len(path)>1:
159 label = self.weighted_edges_dic[frozenset([path[-2],path[-1]])]
160 if self.animation_type in ['greedy','a_star']:
161 label = self.help_info_weight*self.help_info[path[-1]] + self.origin_info_weight*label
162 self.show_edge_labels(ax, self.tree_node_position[path[:-1]][0:2], pos[0:2], label)
438 # 绘制边的标注
439 label = self.edges[path[-2], path[-1]]['weight']
440
441 if animation_type in ['greedy', 'a_star']:
442 label = self.help_info_weight * self.help_info[
443 path[-1]] + self.origin_info_weight * label
444 self.show_edge_labels(ax,
445 self.tree_node_position[path[:-1]][
446 0:2], pos[0:2], label)
447
448 # 绘制上方文字
449 plt.text(0,
450 0,
451 top_text,
452 fontsize=18,
453 horizontalalignment='left',
454 verticalalignment='top', )
455 # 绘制下方文字
456 plt.text(0,
457 -1.1,
458 bottom_text,
459 fontsize=18,
460 horizontalalignment='left',
461 verticalalignment='top', )
462
463 # 刷新绘图
163464 display.clear_output(wait=True)
164
165 show_res_text = ""
166 for e_c in self.show_correct_path:
167 show_res_text += '找到一条路径: %-7s' % e_c + '。距离为:' +str(self.correct_paths[e_c]) + '\n'
168 plt.text(0, -1.1, show_res_text, fontsize=18,horizontalalignment='left', verticalalignment='top',)
169
170 if best_path:
171 top_text = '最终最短路径为: %-7s' % this_path + '。距离为:' +str(self.correct_paths[this_path]) + '\n'
172 elif this_path and self.animation_type in ['dfs','bfs']:
173 top_text = '当前路径: %-7s' % this_path + '。距离为:' +str(self.path_score[this_path]) + '\n'
174 if self.temp_best_path:
175 top_text += '当前最短路径为: %-7s' % self.temp_best_path + '。距离为:' +str(self.correct_paths[self.temp_best_path]) + '\n'
465 plt.show()
466
467 def _generate_bottom_text(self, show_correct_path):
468 """
469 生成目前找到的最佳路径的信息的文字
470 :param show_correct_path: 当前找到的正确的路径
471 :return:
472 """
473 # 默认不展示文字
474 bottom_text = ""
475 # 对每一条找到的正确路径,增加一条展示文本s
476 for path in show_correct_path:
477 bottom_text += '找到一条路径: %-7s' % path + '。距离为:' + str(
478 self.path_score[path]) + '\n'
479 return bottom_text
480
481 def _generate_a_star_help_text(self, path):
482 """
483 生成贪婪搜索和 a-star 动态展示时的文字
484 :param path: 当前路径
485 :return:
486 """
487 # 如果到达目标节点
488 if path[-1] == self.target_node:
489 return '抵达目标节点' + str(self.target_node)
490 # 如果未抵达目标节点并且抵达了最大搜索深度
491 elif path not in self.a_star_search_scores:
492 return '未找到目标节点, 结束搜索'
493 # 其他情况,展示当前节点可选节点的信息,以及挑选的原因
494 else:
495 base_text = '当前可选的子节点及其信息值为 \n' + \
496 str(self.a_star_search_scores[path]) + '\n'
497 if self.target_node in self.a_star_search_scores[path]:
498 return base_text + '当前可选的子节点包含了目标节点,\n所以选择目标节点'
499 elif len(self.a_star_search_scores[path]) == 1:
500 return base_text + '因为只有一个子节点,所以选择此节点'
501 else:
502 return base_text + '因为' + \
503 str(min(self.a_star_search_scores[path],
504 key=self.a_star_search_scores[path].get)) + \
505 '的值最小,所以选择此节点'
506
507 def _generate_top_text(self,
508 animation_type,
509 this_path,
510 best_path=None,
511 finish=False):
512 """
513 生成展示当前路径的信息文字
514 :param animation_type:
515 :param this_path:
516 :param best_path:
517 :param finish:
518 :return:
519 """
520 # 如果结束搜索,展示最终的最短路径
521 if finish:
522 top_text = '最终最短路径为: %-7s' % this_path + '。距离为:' + str(
523 self.path_score[this_path]) + '\n'
524 # 如果是其他路径,并且是展示 dfs 或 bfs 的搜索过程,展示当前路径的信息
525 elif this_path and animation_type in ['dfs', 'bfs']:
526 top_text = '当前路径: %-7s' % this_path + '。距离为:' + str(
527 self.path_score[this_path]) + '\n'
528 if best_path:
529 top_text += '当前最短路径为: %-7s' % best_path + '。距离为:' + \
530 str(self.path_score[best_path]) + '\n'
531 # 如果是其他路径,并且是展示 贪婪搜索 或 A-star 算法的搜索过程,展示当前路径的信息
532 elif this_path and animation_type in ['greedy', 'a_star']:
533 top_text = self._generate_a_star_help_text(this_path)
534 # 其他情况,不展示文字
176535 else:
177536 top_text = ''
178
179 plt.text(0, 0,
180 top_text,
181 fontsize=18,
182 horizontalalignment='left',
183 verticalalignment='top',)
184
185 if self.animation_type in ['greedy','a_star']:
186 show_greedy_text = self.generate_greedy_help_text(this_path)
187 plt.text(0, 0, show_greedy_text, fontsize=18, horizontalalignment='left', verticalalignment='top',)
188 plt.show()
189
190 def animation_search_tree(self,search_method='dfs', help_info_weight=1, origin_info_weight=1):
191 """动画展示搜索过程
192 """
193 self.animation_type = search_method
194 self.show_correct_path = []
195 self.temp_best_path = None
196 if search_method == 'bfs':
197 paths = self.bfs_path
198 elif search_method == 'dfs':
199 paths = self.dfs_path
200 elif search_method == 'greedy':
537 return top_text
538
539 def animate_search_tree(self,
540 animation_type='dfs',
541 help_info_weight=1,
542 origin_info_weight=1,
543 sleep_time=0):
544 """
545 动态演示搜索过程
546 :param animation_type: 可选项为 ['bfs', 'dfs', 'greedy', 'a_star']
547 :param help_info_weight: 附加信息的权重值
548 :param origin_info_weight: 原始信息的权重值
549 :param sleep_time: 设置每一步的等待时间
550 :return:
551 """
552 # 根据展示的搜索方式,获取展示的路径列表
553 if animation_type == 'bfs':
554 paths = self.bfs_paths
555 elif animation_type == 'dfs':
556 paths = self.dfs_paths
557 elif animation_type == 'greedy':
201558 self.greedy_search()
202 paths = self.greedy_search_path
203 elif search_method == 'a_star':
204 self.a_star_search(help_info_weight=help_info_weight, origin_info_weight=origin_info_weight)
205 paths = self.greedy_search_path
559 paths = self.a_star_search_paths
560 elif animation_type == 'a_star':
561 self.a_star_search(help_info_weight=help_info_weight,
562 origin_info_weight=origin_info_weight)
563 paths = self.a_star_search_paths
206564 else:
207 paths = []
208 for e_path in paths:
209 self.show_search_tree(e_path)
210 if e_path in self.correct_paths:
211 if not self.temp_best_path:
212 self.temp_best_path = e_path
213 elif self.path_score[e_path] < self.path_score[self.temp_best_path]:
214 self.temp_best_path = e_path
215 self.show_correct_path.append(e_path)
216 self.show_search_tree(e_path, True)
217 if search_method in ['greedy', 'a_star']:
218 time.sleep(5)
219 if search_method in ['bfs', 'dfs']:
220 if self.correct_paths:
221 best_path = min(self.correct_paths, key=self.correct_paths.get)
222 self.show_search_tree(best_path, True, True)
223
224 def animation_graph(self, search_method='bfs', help_info_weight=1, origin_info_weight=1):
225
226 """
227 """
228 self.animation_type = search_method
229 self.show_correct_path = []
230 if search_method == 'bfs':
231 paths = self.bfs_path
232 elif search_method == 'dfs':
233 paths = self.dfs_path
234 elif search_method == 'greedy':
235 self.greedy_search()
236 paths = self.greedy_search_path
237 elif search_method == 'a_star':
238 self.a_star_search(help_info_weight=help_info_weight, origin_info_weight=origin_info_weight)
239 paths = self.greedy_search_path
565 print('animation_type 参数错误,请从 dfs、bfs、 greedy 或 a_star 中挑选一个')
566 return
567
568 if animation_type in ['bfs', 'dfs']:
569 show_correct_path = []
570 # 动态演示过程中找到的最佳路径
571 best_path = None
572 # 对路径列表中的每一个路径,绘图
573 for e_path in paths:
574 top_text = self._generate_top_text(animation_type,
575 e_path,
576 best_path=best_path,
577 finish=False)
578 bottom_text = self._generate_bottom_text(show_correct_path)
579 self.show_search_tree(top_text=top_text,
580 bottom_text=bottom_text,
581 this_path=e_path)
582 # 设置等待时间,避免切换过快
583 time.sleep(sleep_time)
584 # 如果该路径是正确路径
585 if e_path[-1] == self.target_node:
586 # 如果是第一个正确路径,则其为当前最佳路径
587 if not best_path:
588 best_path = e_path
589 # 如果不是,与当前最佳路径比较,
590 elif self.path_score[e_path] < self.path_score[best_path]:
591 best_path = e_path
592 # 增加一条最佳路径的展示
593 show_correct_path.append(e_path)
594 bottom_text = self._generate_bottom_text(show_correct_path)
595 self.show_search_tree(top_text=top_text,
596 bottom_text=bottom_text,
597 this_path=e_path,
598 show_success_color=True)
599 # 设置等待时间,避免切换过快
600 time.sleep(sleep_time)
601 # 搜索结束后,展示最佳路径
602 top_text = self._generate_top_text(animation_type,
603 best_path,
604 best_path=best_path,
605 finish=True
606 )
607 bottom_text = self._generate_bottom_text(show_correct_path)
608 self.show_search_tree(top_text=top_text,
609 bottom_text=bottom_text,
610 this_path=best_path,
611 show_success_color=True)
612
240613 else:
241 paths = []
242 for e_path in paths:
243 self.show_graph(e_path)
244 if e_path in self.correct_paths:
245 self.show_correct_path.append(e_path)
246 self.show_graph(e_path, True)
247 time.sleep(5)
248 if search_method in ['bfs', 'dfs']:
249 best_path = min(self.correct_paths, key=self.correct_paths.get)
250 self.show_graph(best_path, True, True)
251
252 def show_graph(self, this_path='',
253 show_success_color=False,
254 best_path=None):
255 """
256 绘制图
257 :return:
258 """
259 fig, ax = plt.subplots()
260 fig.set_figwidth(6)
261 fig.set_figheight(8)
262 plt.axis('off')
263
264 # 绘制节点与边颜色
265 visited_edges = []
266 if not this_path:
267 this_path = self.start_node
268 path_node_list = list(this_path)
269 for i in range(1,len(path_node_list)):
270 visited_edges.append(frozenset([path_node_list[i],path_node_list[i-1]]))
271
272 # 节点与标识
273 nlabels = dict(zip(self.node_list, self.node_list))
274 edge_labels = dict([((u, v,), d['weight']) for u, v, d in self.G.edges(data=True)])
275
276 # 节点颜色变化
277 val_map = {self.target_node: self.target_node_color}
278 if path_node_list:
279 for i in path_node_list:
280 if show_success_color:
281 val_map[i] = self.success_color
282 else:
283 val_map[i] = self.visited_node_color
284 val_map[self.start_node] = self.start_node_color
285 values = [val_map.get(node, self.basic_node_color) for node in self.G.nodes()]
286
287 # 处理边的颜色
288 edge_colors = []
289 for edge in self.G.edges():
290 # 如果边在result_red_edges,分2种情况:
291 # 如果this_path[0]/this_path[-1] 对应起始点和终点,颜色为绿色,否则颜色为红色
292 # 如果边不在result_red_edges,则初始化边的颜色为黑色
293 if frozenset(edge) in visited_edges:
294 if show_success_color:
295 edge_colors.append(self.success_color)
296 else:
297 edge_colors.append(self.visited_edge_color)
298 else:
299 edge_colors.append(self.basic_edge_color)
300
301 # 绘制节点及其标签
302 nx.draw_networkx_nodes(self.G, self.nodes_pos, node_size=800, node_color=values, width=6.0)
303 nx.draw_networkx_labels(self.G, self.nodes_pos, nlabels, font_size=20)
304 # 绘制边及其标签
305 nx.draw_networkx_edges(self.G, self.nodes_pos, edge_color=edge_colors, width=2.0, alpha=1.0)
306 nx.draw_networkx_edge_labels(self.G, self.nodes_pos, edge_labels=edge_labels, font_size=18)
307
308 display.clear_output(wait=True)
309 # show_text = ""
310 # for e_c in self.show_correct_path:
311 # show_text += '找到一条路径: %-7s' % e_c + '。距离为:' +str(self.correct_paths[e_c]) + '\n'
312 # plt.text(0, -2.6, show_text, fontsize=18, horizontalalignment='left', verticalalignment='top', )
313
314 # if best_path:
315 # top_text = '最佳路径为: %-7s' % this_path + '。 距离为:' +str(self.correct_paths[this_path]) + '\n'
316 # elif this_path and self.animation_type in ['dfs','bfs']:
317 # top_text = '当前路径: %-7s' % this_path + '。 距离为:' +str(self.cal_dis(this_path)) + '\n'
318 # else:
319 # top_text = ''
320 # plt.text(0, 0,
321 # top_text,
322 # fontsize=18,
323 # horizontalalignment='left',
324 # verticalalignment='top',)
325 plt.show()
326
327 def _dfs_helper(self, G, node, father, target_node,level, res, path):
328 path+=str(node)
329 if len(path)>1:
330 self.path_score[path] = self.path_score[path[:-1]] + self.weighted_edges_dic[frozenset([path[-2],path[-1]])]
331 res.append(path)
332 # 找到目标,停止搜索
333 if node==target_node:
334 return
335 if level< self.max_depth:
336 for neighbor in sorted(G[node]):
337 if str(neighbor) not in path:
338 self._dfs_helper(G, neighbor, node, target_node, level+1, res, path)
339
340 def dfs_search(self):
341 dfs_path=[]
342 this_path=''
343 if self.start_node:
344 self._dfs_helper(self.G, self.start_node, None, self.target_node, 0, dfs_path, this_path)
345 self.dfs_path = dfs_path
346 for p in dfs_path:
347 if p[-1]==self.target_node and p not in self.correct_paths:
348 self.correct_paths[p] = self.cal_dis(p)
349
350 def bfs_search(self):
351 to_search=[self.start_node]
352 bfs_path = []
353 bfs_correct_path = []
354 depth = 0
355 while to_search:
356 this_search = to_search.pop(0)
357 if len(this_search)>self.max_depth+1 :
358 break
359 bfs_path.append(this_search)
360 if this_search[-1]==self.target_node:
361 bfs_correct_path.append(this_search)
362 continue
363 for ne in sorted(self.G[this_search[-1]]):
364 if ne not in this_search:
365 to_search.append(this_search+ne)
366 self.bfs_path = bfs_path
367 for p in bfs_path:
368 if p[-1]==self.target_node and p not in self.correct_paths:
369 self.correct_paths[p] = self.cal_dis(p)
370
371 def greedy_search(self, help_info_weight=1, origin_info_weight=0):
372 self.help_info_weight = help_info_weight
373 self.origin_info_weight = origin_info_weight
374 search_path = self.start_node
375 # 存储每一步的可选项及其分数,用来在动态演示时显示出来
376 search_scores = {}
377 while len(search_path) <= self.max_depth:
378 this_node = search_path[-1]
379 neighbour_nodes = [e_n for e_n in sorted(self.G[this_node]) if e_n not in search_path]
380 if len(neighbour_nodes) == 0:
381 search_scores[search_path]={}
382 break
383 if self.help_info:
384 scores = {e_n:help_info_weight*self.help_info[e_n]+origin_info_weight*self.weighted_edges_dic[frozenset([this_node,e_n])] for e_n in neighbour_nodes }
385 else:
386 scores = {e_n:self.weighted_edges_dic[frozenset([this_node,e_n])]
387 for e_n in neighbour_nodes }
388 search_scores[search_path]=scores
389 nearest_node = min(scores, key=scores.get)
390 search_path += nearest_node
391 if nearest_node == self.target_node:
392 break
393 self.greedy_search_path = [search_path[0:index+1] for index in range(len(search_path))]
394 self.search_scores = search_scores
395
396 def a_star_search(self, help_info_weight=1, origin_info_weight=1):
397 self.greedy_search(help_info_weight, origin_info_weight)
398
399
400 def generate_greedy_help_text(self,path):
401 if path[-1] == self.target_node:
402 return '抵达目标节点' + str(self.target_node)
403 elif path not in self.search_scores:
404 return '抵达最大搜索深度,未找到目标节点'
405
406 base_text = '当前可选的子节点及其信息值为 \n'+ \
407 str(self.search_scores[path]) + '\n'
408 if self.target_node in self.search_scores[path]:
409 return base_text + '当前可选的子节点包含了目标节点,\n所以选择目标节点'
410 elif len(self.search_scores[path]) == 1:
411 return base_text + '因为只有一个子节点,所以选择此节点'
412 else:
413 return base_text + '因为'+ \
414 str(min(self.search_scores[path], key=self.search_scores[path].get)) + \
415 '的值最小,所以选择此节点'
416
417 def cal_dis(self,path):
418 dis = 0
419 if len(path) > 1:
420 for i in range(len(path)-1):
421 dis += self.weighted_edges_dic[frozenset([path[i],path[i+1]])]
422 return dis
423
614 # 对路径列表中的每一个路径,绘图
615 for e_path in paths:
616 top_text = self._generate_top_text(animation_type,
617 e_path,
618 best_path=False)
619 self.show_search_tree(top_text=top_text,
620 this_path=e_path)
621 # 设置等待时间,避免切换过快
622 time.sleep(sleep_time)
623 # 如果抵达目标点
624 if e_path[-1] == self.target_node:
625 top_text = self._generate_top_text(animation_type,
626 e_path,
627 best_path=True)
628 self.show_search_tree(top_text=top_text,
629 this_path=e_path,
630 show_success_color=True)