You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
19 lines
1.0 KiB
19 lines
1.0 KiB
2 years ago
|
import numpy as np
|
||
|
|
import scipy.sparse as sp
|
||
|
|
|
||
|
|
|
||
|
|
def load_yam_feature(dataset):
|
||
|
|
dp = np.loadtxt('../../data/RawData/Yamanishi/{}_admat_dgc.txt'.format(dataset), dtype=str, delimiter='\t')[1:, 1:].astype(np.float).T
|
||
|
|
dd = np.loadtxt('../../data/RawData/Yamanishi/{}_simmat_dc.txt'.format(dataset), dtype=str, delimiter='\t')[1:, 1:].astype(np.float)
|
||
|
|
pp = np.loadtxt('../../data/RawData/Yamanishi/{}_simmat_dg.txt'.format(dataset), dtype=str, delimiter='\t')[1:, 1:].astype(np.float)
|
||
|
|
feature = np.vstack((np.hstack((dd, dp)), np.hstack((dp.T, pp))))
|
||
|
|
return sp.lil_matrix(feature)
|
||
|
|
|
||
|
|
|
||
|
|
def load_luo_feature(dataset):
|
||
|
|
dp = np.loadtxt('../../data/RawData/luo/mat_drug_protein.txt'.format(dataset), dtype=float)
|
||
|
|
dd = np.loadtxt('../../data/RawData/luo/Similarity_Matrix_Drugs.txt'.format(dataset), dtype=float)
|
||
|
|
pp = np.loadtxt('../../data/RawData/luo/Similarity_Matrix_Proteins.txt'.format(dataset), dtype=float) / 100
|
||
|
|
feature = np.vstack((np.hstack((dd, dp)), np.hstack((dp.T, pp))))
|
||
|
|
return sp.lil_matrix(feature)
|