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File: visualization.py
Role: Auxiliary data
Content type: text/plain
Description: Auxiliary data
Class: PHP Breadth First Search
Find the shortest path to visit warehouse bins
Author: By
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Date: 5 months ago
Size: 3,560 bytes
 

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import matplotlib.pyplot as plt import networkx as nx graph = nx.Graph() # pos = {(0, 0): (0, 0)} pos = {} s, e = 1, 0 start = [0, 13, 26, 39] end = [12, 25, 38, 51] for i in range(51): graph.add_node(i) graph.add_node(i + 1) pos[i] = (s, e) if i > 1 and i % 13 == 0: s += 3 e = (e + 1) % 13 if i > 1 and i in end: continue graph.add_edge(i, i + 1) # pos[(i, i + 1)] = (i + 1, -1 * i) k = 0 s = 2 for i in range(52, 58, 2): graph.add_node(i) graph.add_node(i + 1) graph.add_edge(start[k], i) pos[i] = (s, 0) pos[i + 1] = (s + 1, 0) # pos[(start[k], i)] = (i, -1 * start[k]) graph.add_edge(i, i + 1) # pos[(i, i + 1)] = (i + 1, -1 * i) graph.add_edge(i + 1, start[k + 1]) # pos[(i + 1, start[k + 1])] = (start[k + 1], -1 * (i + 1)) s += 3 k += 1 k = 0 e = 12 s = 2 for i in range(58, 64, 2): graph.add_node(i) graph.add_node(i + 1) graph.add_edge(end[k], i) pos[i] = (s, e) pos[i + 1] = (s + 1, e) # pos[(end[k], i)] = (i, -1 * end[k]) graph.add_edge(i, i + 1) # pos[(i, i + 1)] = (i + 1, -1 * i) graph.add_edge(i + 1, end[k + 1]) # pos[(i + 1, end[k + 1])] = (end[k + 1], -1 * (i + 1)) s += 3 k += 1 s = 1 for u in start: pos[u] = (s, 0) s += 3 s = 1 for u in end: pos[u] = (s, 12) s += 3 pos[51] = (10, 12) bins = [] s = 0 for i in range(1, 12): label = 'A' + str(i) graph.add_node(label) pos[label] = (s, i) bins.append(label) s = 2 for i in range(1, 12): label1 = 'B' + str(i) label2 = 'C' + str(i) graph.add_node(label1) graph.add_node(label2) pos[label1] = (s, i) pos[label2] = (s + 1, i) bins.append(label1) bins.append(label2) s = 5 for i in range(1, 12): label1 = 'D' + str(i) label2 = 'E' + str(i) graph.add_node(label1) graph.add_node(label2) pos[label1] = (s, i) pos[label2] = (s + 1, i) bins.append(label1) bins.append(label2) s = 8 for i in range(1, 12): label1 = 'F' + str(i) label2 = 'G' + str(i) graph.add_node(label1) graph.add_node(label2) pos[label1] = (s, i) pos[label2] = (s + 1, i) bins.append(label1) bins.append(label2) color_map = [] for i in range(64): color_map.append('#e0ecd4') for i in range(77): color_map.append('#FFF') print(pos) # graph.add_node(0) # graph.add_node(1) # graph.add_node(2) # graph.add_node(3) # graph.add_edge(0, 1) # graph.add_edge(1, 2) # graph.add_edge(2, 3) # graph.add_edge(3, 0) print(graph.nodes()) # pos = {(x, y):(y, -x) for x,y in graph.nodes()} options = { "edgecolors": "#333", "node_size": 800, # "node_color": "#FC5647", "node_color": color_map, "linewidths": 2, "width": 2, "edge_color": "#333", "font_color": "#212a35", "font_size": "11", "node_shape": "s" } nx.draw(graph, with_labels=True, pos=pos, **options)#nx.random_layout(graph)) #pos=pos) # nx.spring_layout(graph)) plt.show() adj_matrix = nx.adjacency_matrix(graph).todense().tolist() # adj_matrix = adj_matrix.reshape(len(adj_matrix), len(adj_matrix)) edges = [] # print(adj_matrix) for i in range(len(adj_matrix)): for j in range(len(adj_matrix)): if adj_matrix[i][j] == 1: edges.append((i, j)) # print(adj_matrix[i]) print(edges) # edges = [] # for edge in : # eg = str(edge) # array = eg[:eg.find(')') + 1].strip() # print(array) # # edges.append(tuple(array)) # print(edges) # print(nx.adjacency_matrix(graph).toarray())