###### import ######
import pickle
import numpy as np
from rdkit import Chem
from rdkit.Chem import AllChem
from rdkit import RDLogger
RDLogger.DisableLog('rdApp.info')
RDLogger.DisableLog('rdApp.*')
###### import ######
def plot_hist(prefix_name, prediction, label):
import seaborn as sns
import matplotlib.pyplot as plt
figure_name = prefix_name + "_histogram.png"
positive_prediction = [prediction[i] for i in range(len(label)) if label[i]==1]
negative_prediction = [prediction[i] for i in range(len(label)) if label[i]==0]
save_file_name = "results/" + prefix_name.split('/')[-1] + "_positive_negative.pkl"
pickle.dump((positive_prediction, negative_prediction), open(save_file_name, 'wb'))
sns.distplot(positive_prediction, hist=True, kde=False, bins=20, color = 'blue', label = 'success') #### bins = 50 -> 20
sns.distplot(negative_prediction, hist=True, kde=False, bins=20, color = 'red', label = 'fail')
plt.xlabel("predicted success probability", fontsize=24)
plt.ylabel("frequencies", fontsize = 25)
plt.legend(fontsize = 21)
plt.tight_layout()
# plt.show()
plt.savefig(figure_name)
return
def replace_strange_symbol(text):
for i in "[]'\n/":
text = text.replace(i,'_')
return text
# xml read blog: https://blog.csdn.net/yiluochenwu/article/details/23515923
def walkData(root_node, prefix, result_list):
temp_list =[prefix + '/' + root_node.tag, root_node.text]
result_list.append(temp_list)
children_node = root_node.getchildren()
if len(children_node) == 0:
return
for child in children_node:
walkData(child, prefix = prefix + '/' + root_node.tag, result_list = result_list)
def dynamic_programming(s1, s2):
arr2d = [[0 for i in s2] for j in s1]
if s1[0] == s2[0]:
arr2d[0][0] = 1
for i in range(1, len(s1)):
if s1[i]==s2[0]:
arr2d[i][0] = 1
else:
arr2d[i][0] = arr2d[i-1][0]
for i in range(1,len(s2)):
if s2[i]==s1[0]:
arr2d[0][i] = 1
else:
arr2d[0][i] = arr2d[0][i-1]
for i in range(1,len(s1)):
for j in range(1,len(s2)):
if s1[i] == s2[j]:
arr2d[i][j] = arr2d[i-1][j-1] + 1
else:
arr2d[i][j] = max(arr2d[i-1][j], arr2d[i][j-1])
return arr2d[len(s1)-1][len(s2)-1]
def get_path_of_all_xml_file():
input_file = "./data/all_xml"
with open(input_file, 'r') as fin:
lines = fin.readlines()
input_file_lst = [i.strip() for i in lines]
return input_file_lst
def remove_multiple_space(text):
text = ' '.join(text.split())
return text
def nctid_2_xml_file_path(nctid):
assert len(nctid)==11
prefix = nctid[:7] + "xxxx"
datafolder = os.path.join("./ClinicalTrialGov/", prefix, nctid+".xml")
return datafolder
def fingerprints_from_mol(mol):
fp = AllChem.GetMorganFingerprint(mol, 3, useCounts=True, useFeatures=True)
size = 2048
nfp = np.zeros((1, size), np.int32)
for idx,v in fp.GetNonzeroElements().items():
nidx = idx%size
nfp[0, nidx] += int(v)
return nfp
def smiles2fp(smiles):
try:
mol = Chem.MolFromSmiles(smile)
fp = fingerprints_from_mol(mol)
return fp
except:
return np.zeros((1, 2048), np.int32)
def smiles_lst2fp(smiles_lst):
fp_lst = [smiles2fp(smiles) for smiles in smiles_lst]
fp_mat = np.concatenate(fp_lst, 0)
fp = np.mean(fp_mat,0)
return fp
if __name__ == "__main__":
text = "interpret_result/NCT00329602__completed____1__1.7650960683822632__phase 4__['restless legs syndrome']__['placebo', 'ropinirole'].png"
print(replace_strange_symbol(text))
# if __name__ == "__main__":
# input_file_lst = get_path_of_all_xml_file()
# print(input_file_lst[:5])
# '''
# input_file_lst = [
# 'ClinicalTrialGov/NCT0000xxxx/NCT00000102.xml',
# 'ClinicalTrialGov/NCT0000xxxx/NCT00000104.xml',
# 'ClinicalTrialGov/NCT0000xxxx/NCT00000105.xml',
# ... ]
# '''
# if __name__ == "__main__":
# s1 = "328943"
# s2 = "13785"
# assert dynamic_programming(s1, s2)==2
