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main.py
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import pandas as pd
from py2neo import Node, Graph, Relationship
graph = Graph("http://localhost:7474/", auth=("neo4j", "12345678"), name="neo4j")
featnames_file_name = "data/0.featnames"
feat_file_name = "data/0.feat"
circles_file_name = "data/0.circles"
edge_file_name = "data/0.edges"
egofeat_file_name = "data/0.egofeat"
def read_data():
feature_list = open(featnames_file_name, 'r').readlines()
feature_count = len(feature_list)
feature_data = pd.DataFrame(columns=["num", "name", "data"])
feature_name = set()
for line in feature_list:
contents = line.split(";")
if len(contents) == 2:
first = contents[0].split(" ")
second = contents[1].split(" ")
temp = pd.DataFrame({"num": [int(first[0])], "name": [first[1]], "data": [int(second[2])]})
feature_data = pd.concat([feature_data, temp], ignore_index=True)
feature_name.add(first[1])
elif len(contents) == 3:
first = contents[0].split(" ")
third = contents[2].split(" ")
name = first[1] + "_" + contents[1]
temp = pd.DataFrame({"num": [int(first[0])], "name": [name], "data": [int(third[2])]})
feature_data = pd.concat([feature_data, temp], ignore_index=True)
feature_name.add(name)
elif len(contents) == 4:
first = contents[0].split(" ")
fourth = contents[3].split(" ")
name = first[1] + "_" + contents[1] + "_" + contents[2]
temp = pd.DataFrame({"num": [int(first[0])], "name": [name], "data": [int(fourth[2])]})
feature_data = pd.concat([feature_data, temp], ignore_index=True)
feature_name.add(name)
node_feature_list = open(feat_file_name, 'r').readlines()
node_circle_list = [[] for line in node_feature_list]
circles = open(circles_file_name, 'r').readlines()
for line in circles:
contents = line.split("\t")
for i in range(1, len(contents)):
node_circle_list[int(contents[i]) - 1].append(contents[0])
node_list = list()
line_number = 0
for line in node_feature_list:
feature_dict = dict()
for name in feature_name:
feature_dict[name] = None
contents = line.split(" ")
for i in range(1, len(contents)):
if contents[i - 1] == '1':
feature_dict[feature_data.loc[i - 1, "name"]] = feature_data.loc[i - 1, "data"]
node = Node("Person",
birthday=feature_dict['birthday'],
education_classes_id=feature_dict['education_classes_id'],
education_concentration_id=feature_dict['education_concentration_id'],
education_degree_id=feature_dict['education_degree_id'],
education_school_id=feature_dict['education_school_id'],
education_type=feature_dict['education_type'],
education_with_id=feature_dict['education_with_id'],
education_year_id=feature_dict['education_year_id'],
first_name=feature_dict['first_name'],
gender=feature_dict['gender'],
hometown_id=feature_dict['hometown_id'],
languages_id=feature_dict['languages_id'],
last_name=feature_dict['last_name'],
locale=feature_dict['locale'],
location_id=feature_dict['location_id'],
work_employer_id=feature_dict['work_employer_id'],
work_end_date=feature_dict['work_end_date'],
work_location_id=feature_dict['work_location_id'],
work_position_id=feature_dict['work_position_id'],
work_start_date=feature_dict['work_start_date'],
work_with_id=feature_dict['work_with_id'],
circle=node_circle_list[line_number])
node_list.append(node)
graph.create(node)
line_number += 1
for line in open("0.edges", "r").readlines():
contents = line.split(" ")
first = int(contents[0])
second = int(contents[1])
relationship = Relationship(node_list[first - 1], "Be_Friend_With", node_list[second - 1])
relationship["undirected"] = True
graph.create(relationship)
center_data = open("0.egofeat", 'r').readline().split(" ")
for line in node_feature_list:
contents = line.split(" ")
flag = True
for i in range(1, len(contents)):
if int(contents[i]) != int(center_data[i - 1]):
flag = False
break
if flag == True:
print("Center Node Id!")
break
feature_dict = dict()
for name in feature_name:
feature_dict[name] = None
for i in range(1, len(center_data)):
if center_data[i - 1] == '1':
feature_dict[feature_data.loc[i - 1, "name"]] = feature_data.loc[i - 1, "data"]
node = Node("Person",
birthday=feature_dict['birthday'],
education_classes_id=feature_dict['education_classes_id'],
education_concentration_id=feature_dict['education_concentration_id'],
education_degree_id=feature_dict['education_degree_id'],
education_school_id=feature_dict['education_school_id'],
education_type=feature_dict['education_type'],
education_with_id=feature_dict['education_with_id'],
education_year_id=feature_dict['education_year_id'],
first_name=feature_dict['first_name'],
gender=feature_dict['gender'],
hometown_id=feature_dict['hometown_id'],
languages_id=feature_dict['languages_id'],
last_name=feature_dict['last_name'],
locale=feature_dict['locale'],
location_id=feature_dict['location_id'],
work_employer_id=feature_dict['work_employer_id'],
work_end_date=feature_dict['work_end_date'],
work_location_id=feature_dict['work_location_id'],
work_position_id=feature_dict['work_position_id'],
work_start_date=feature_dict['work_start_date'],
work_with_id=feature_dict['work_with_id'])
graph.create(node)
for i in range(len(node_feature_list)):
relationship = Relationship(node_list[i], "Be_Friend_With", node)
relationship["undirected"] = True
graph.create(relationship)
if __name__ == "__main__":
read_data()