mirror of
https://github.com/Priyatham-sai-chand/compara-deep-learning.git
synced 2026-10-05 08:11:34 -07:00
51 lines
1.5 KiB
Python
51 lines
1.5 KiB
Python
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import pandas as pd
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import gc
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import numpy as np
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import json
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import os
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import progressbar
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import sys
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from selector import select,create_map_reverse
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def read_db_homology(dir_name,filename):
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df=pd.read_csv(dir_name+"/"+filename,compression='gzip',sep='\t')
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n=filename.split(".")[0]
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n=n.split(" ")[0]
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return df,n
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def get_selection_data():
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with open("dist_matrix","r") as file:
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matrix=file.readlines()
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matrix=[x.split("\t") for x in matrix]
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matrix=[[float(y) for y in x] for x in matrix]
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matrix=np.array(matrix)
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with open("sp_names","r") as file:
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dname=file.readlines()
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dname=[x.split("\n")[0] for x in dname]
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spnmap,nspmap=create_map_reverse(dname)
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return matrix,spnmap,nspmap
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def read_select_data(dirname,matrix,spnmap,nspmap,nos):
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lf=os.listdir(dirname)
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if len(lf)==0:
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print("No Files in the Directory!!!!!!!")
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sys.exit(1)
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if not os.path.isdir("processed"):
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os.mkdir("processed")
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for x in lf:
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df,n=read_db_homology(dirname,x)
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n=n.split(" ")[0]
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df=select(df,nos,matrix,spnmap,nspmap,n)
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(len(df)==nos)
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indexes=np.array(list(df.index.values))
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np.save("processed/"+n+"_selected_indexes",indexes)
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def main():
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arg=sys.argv
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nos=int(arg[-1])
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matrix,spnmap,nspmap=get_selection_data()
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read_select_data("data_homology",matrix,spnmap,nspmap,nos)
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if __name__=="__main__":
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main()
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