def gen_img(graph: Graph,
node_num,
rm_ratio: float = 0.2,
root_folder='train',
source_folder='',
source_file='train.txt'):
"""
在graph上，以rm_ratio的概率随机删除一些链路，然后用随机选取的一对节点作为源宿点，判断其是否联通。并将生成的图像放到root_folder目录中，
对应的文件名称和标签放到source_folder目录下的train.txt文件中。
"""
# 生成原始数据
rds = rand_edges(graph, rm_ratio)
graph.remove_edges_from(rds)
src, dst = gen_src_dst(0, node_num)
label = get_label(src, dst, graph)
# 构造graphviz对象
name = str(time.time())
g = Graph(format='jpeg', engine='neato')
g.attr('node', shape='circle')
g.attr('edge')
for node in graph.nodes():
g.node(name=str(node))
g.node(name=str(src), shape='triangle')
g.node(name=str(dst), shape='triangle')
for edge in graph.edges():
g.edge(str(edge[0]), str(edge[1]))
for edge in rds:
g.edge(str(edge[0]), str(edge[1]), color='white')
g.render(filename=name, directory=root_folder, view=False, cleanup=True)
# 存储到文件中去
file = open(os.path.join(source_folder, source_file), 'a')
file.write(name + '.jpeg ' + str(label) + '\n')
file.flush()
file.close()
