matching_dependency/md_discovery/md_discover.py

from md_discovery import tmp_discover
from settings import *

# # 若不输出support和confidence，使用以下两块代码
# # 将列表1写入本地，路径需自己修改
# md_path = '/home/w/A-New Folder/8.14/Paper Dataset/TP_md_list.txt'
# with open(md_path, 'w') as f:
#     for _ in mds:
#         f.write(str(_) + '\n')
#
# # 将列表2写入本地，路径需自己修改
# vio_path = '/home/w/A-New Folder/8.14/Paper Dataset/TP_vio_list.txt'
# with open(vio_path, 'w') as f:
#     for _ in vio:
#         f.write(str(_) + '\n')


def md_discover():
    # 目前可以仿照这个main函数写
    t_single_tuple_path = er_output_dir + "t_single_tuple.csv"
    # 输入：csv文件路径，md左侧相似度阈值，md右侧目标字段
    # 输出：2个md列表，列表1中md无violation,列表2中md有violation但confidence满足阈值
    mds_list, vio_list = tmp_discover.pairs_inference(t_single_tuple_path, similarity_threshold, target_attr)

    # 将列表1写入本地，路径需自己修改
    mds_path = md_output_dir + "mds.txt"
    vio_path = md_output_dir + "vio.txt"
    
    with open(mds_path, 'w') as f:
        for _ in mds_list:
            f.write('Target:'+str(target_attr) + '\t')
            f.write(str(_))
            f.write('\n')

    with open(vio_path, 'w') as f:
        for _ in vio_list:
            f.write('Target:'+str(target_attr) + '\t')
            f.write(str(_))
            f.write('\n')


if __name__ == '__main__':
    md_discover()