def self_test():
'''自己构造测试数据，检查算法运行是否正确'''
# v1 v2 v3 v4 v5 v6 v7 v8 v9 v10v11v12v13v14
matrix = [
[0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0], # v1
[0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0], # v2
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0], # v3
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0], # v4
[0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0], # v5
[0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0], # v6
[1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0], # v7
[0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0], # v8
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0, 0], # v9
[1, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0], # v10
[0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0], # v11
[0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1], # v12
[0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1], # v13
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0] # v14
]
graph = apiGraph(matrix)
# category数据写在了文件中
categories = []
with open('../dataset/test_category.txt', 'r', encoding='utf-8') as f:
for line in f:
line = line[:-1] # 去除换行符
fields = line.split('\t')
categories.append(fields[1:])
keywords = ['k1', 'k2']
algorithm = GreedyMethod(graph, categories)
weight, nodes = algorithm.run(keywords)
print(weight)
print(nodes)
def __init__(self):
self.graph = apiGraph(json.load(open('../dataset/graph.json')))
self.categories = json.load(open('../dataset/api_categories.json'))
self.api_dict = json.load(open('../dataset/connected_api_dict.json'))
self.reverseApiDict()
self.combineCategoryList()
print('total vertexes:', self.graph.dimension)
def prepare_data():
'''
加载关键词图结构，返回关键字图和类别列表
:return:
'''
#加载预先生成的图结构
graph = apiGraph(json.load(open('../dataset/graph.json')))
categories = json.load(open('../dataset/api_categories.json'))
category_list = json.load(open('../dataset/category_list.json'))
return graph, categories, category_list
def test():
graph = apiGraph(json.load(open('../dataset/graph.json')))
categories = json.load(open('../dataset/api_categories.json'))
category_list = json.load(open('../dataset/category_list.json'))
minimal_steiner = MinimalSteinerTree(graph, categories)
count_options = [2, 3, 4, 5, 6]
num_of_options = len(count_options)
keywords = ['England', 'Home Automation', 'Barcodes', 'Web Site Management', 'Metadata', 'Classifieds']
begin = time.time()
min_tree = minimal_steiner.run(keywords);
if min_tree is None:
print('weight:%d, time:%fs' % (0, time.time() - begin))
print('weight:%d, time:%fs' % (min_tree.weight, time.time() - begin))
# test()