###### 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