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from collections import Counter
import pandas as pd
import numpy as np
def add_domains(data, path_to_domains):
DOMAINS = pd.read_csv(path_to_domains, delimiter=' ')
data = data.merge(DOMAINS, right_on='proteinID', left_on='uniprotID', how='left')
data.domStart = data.domStart.astype('Int64')
data.domEnd = data.domEnd.astype('Int64')
data = data.drop(['proteinID'], axis=1)
data['distance'] = np.NaN
zeroDistanceDomains = []
for i in data.index:
if pd.isna(data.at[i, 'domain']):
data.at[i, 'distance'] = np.NaN
else:
if int(data.at[i, 'domStart']) <= int(data.at[i, 'pos']) <= int(data.at[i, 'domEnd']):
data.at[i, 'distance'] = 0
DOMAIN_NAME = data.at[i, 'domain']
zeroDistanceDomains.append(DOMAIN_NAME)
data = data.sort_values(by=['datapoint', 'distance']).reset_index(drop=True) # Distances will be sorted.
ZeroDistance = data[data.distance == 0.0]
NotZeroDistance = data[data.distance != 0.0]
NotZeroDistance.distance = -1000
NotZeroDistance = NotZeroDistance[~NotZeroDistance.datapoint.isin(ZeroDistance.datapoint.to_list())]
data = pd.concat([ZeroDistance, NotZeroDistance], sort=False)
data.reset_index(drop=True, inplace=True)
data.fillna(-1, inplace=True)
return data
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