mirror of
https://github.com/Priyatham-sai-chand/compara-deep-learning.git
synced 2026-10-05 08:11:34 -07:00
57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
import pandas as pd
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import numpy as np
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import os
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import sys
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import progressbar
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import json
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from read_data import read_data_homology
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from read_get_gene_seq import read_gene_sequences
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from create_synteny_matrix import synteny_matrix
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if not os.path.exists("processed/synteny_matrcies"):
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os.mkdir("processed/synteny_matrices")
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arg=sys.argv
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arg=arg[1:]
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enable_break=0
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if arg[-1]=="-test":
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enable_break=1
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lsy={}
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a_h,d_h=read_data_homology("data_homology")
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print("Homology Data Read")
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with open("processed/neighbor_genes.json","r") as file:
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lsy=dict(json.load(file))
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print(len(lsy))
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print("Neighbor Genes Loaded")
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if enable_break==1:
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gene_sequences=read_gene_sequences(a_h,lsy,"geneseq","gene_sequences")
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else:
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gene_sequences=read_gene_sequences(a_h,lsy,"geneseq","gene_sequences")
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print("Gene Sequences Loaded")
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if enable_break==1:
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save_after=10
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else:
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save_after=500000
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n=3
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c=0
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j=0
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ndir="processed/synteny_matrices/"
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nf1="synteny_matrices_global"
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nf2="synteny_matrices_local"
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nf3="indexes"
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for df in a_h:
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j+=1
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for i in progressbar.progressbar(range(0,len(df)//save_after)):
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synteny_matrices_global,synteny_matrices_local,indexes=synteny_matrix(gene_sequences,df[i*save_after:(i+1)*save_after],lsy,n,enable_break)
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np.save(ndir+nf1+"_"+str(j)+str(c+1),synteny_matrices_global)
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np.save(ndir+nf2+"_"+str(j)+str(c+1),synteny_matrices_local)
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np.save(ndir+nf3+"_"+str(j)+str(c+1),indexes)
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c+=1
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if enable_break==1:
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break
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print("Synteny Matrices Created Successfully :)")
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