Predicting-DTIs/create_dataset.py at master · fa-fa97/Predicting-DTIs · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Aug 18 12:49:34 2019

@author: fatemehf
"""

import pandas as pd


pcols = ['Source ID', 'Target ID', 'Edge Type','Edge ID']
ncols = ['Source ID', 'Target ID', 'Edge Type']

neg_data = pd.read_csv('~/Desktop/final_project/DTINet/data/generated_data/neg_data.csv', sep=' ',names=ncols)
pos_data = pd.read_csv('~/Desktop/final_project/DTINet/data/generated_data/main_db.csv', sep=' ',names=pcols)

neg_data['Label'] = 0
pos_data['Label'] = 1

column = ['F'+str(i) for i in range(1,129)]

column.insert(0,'Node ID')

embedding=pd.read_csv('~/Desktop/final_project/edge2vec/vector_db.txt',sep=' ', names=column)

for i in range(1,129):
    embedding['F'+str(i)] = embedding['F'+str(i)].apply(lambda x : float(x))

embedding['Node ID'] = embedding['Node ID'].apply(lambda x : float(x))

cols = ['F'+str(i) for i in range(1,129)]
cols.insert(0,'Source ID')
cols.insert(1,'Target ID')
cols.insert(2,'Label')

dataset = pd.DataFrame(columns=cols,data=None)

for i,row in neg_data.iterrows():
    label=row['Label']
    dataset_full = []
    target_vector = embedding.loc[embedding['Node ID'] == row['Target ID']]
    target_vector = target_vector.reset_index(drop=True)
    source_vector = embedding.loc[embedding['Node ID'] == row['Source ID']]
    source_vector = source_vector.reset_index(drop=True)

    dataset_vector = source_vector.subtract(target_vector)

    dataset_vector= dataset_vector.drop(columns = ['Node ID'])
    dataset_vector['Label'] = label
    dataset_vector['Source ID'] = source_vector['Node ID']
    dataset_vector['Target ID'] = target_vector['Node ID']

    dataset_full.append(list(dataset_vector))
    print(i)


dataset.to_csv('~/Desktop/DTINet/data/generated_data/dataset_neg.csv', sep=' ',index=False)