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Joseph Gordon
joseph-gordon/
Uncertainty-Quantificatio
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[bc9e98]: / benchmark / utils.py

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###### import ######





import numpy as np 

try:

	from rdkit import Chem 

	from rdkit.Chem import AllChem

except:

	pass 

###### 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]

	sns.distplot(positive_prediction, hist=True,  kde=False, bins=50, color = 'blue', label = 'positive')

	sns.distplot(negative_prediction, hist=True,  kde=False, bins=50, color = 'red', label = 'negative')

	plt.legend()

	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