compara-deep-learning/prepare_synteny_matrix.py

import numpy as np 
import pandas as pd 
import json
import os
import sys
import pickle
from select_data import read_db_homology
from threads import Procerssrunner
from read_get_gene_seq import read_gene_sequences
from access_data_rest import update_rest,update_rest_protein
from process_negative import write_fasta

def read_data_synteny(nop,name):
    smg=[]
    sml=[]
    indexes=[]
    for i in range(nop):
        try:
            with open("temp_"+name+"/thread_"+str(i+1)+"_smg.temp","rb") as file:
                smg=smg+pickle.load(file)
            with open("temp_"+name+"/thread_"+str(i+1)+"_sml.temp","rb") as file:
                sml=sml+pickle.load(file)
            with open("temp_"+name+"/thread_"+str(i+1)+"_indexes.temp","rb") as file:
                indexes=indexes+pickle.load(file)
        except Exception as e:
            print("Problem with thread",i+1,"detected for",name,e)
            continue
    print(len(indexes))
    return smg,sml,indexes

def load_neighbor_genes():
    with open("processed/neighbor_genes.json","r") as file:
        lsy=dict(json.load(file))
    print(len(lsy))
    print("Neighbor Genes Loaded")
    return lsy

def read_data_homology(dirname):
    lf=os.listdir(dirname)
    if len(lf)==0:
        print("No Files in the Directory!!!!!!!")
        sys.exit(1)
    a_h=[]
    d_h=[]
    for x in lf:
        df,n=read_db_homology(dirname,x)
        n=n.split()[0]
        try:
            indexes=np.load("processed/"+n+"_selected_indexes.npy")
        except:
            print("Incomplete data for:",n)
        df=df.loc[indexes]
        a_h.append(df)
        d_h.append(n)
    return a_h,d_h

def main():
    arg=sys.argv
    nop=int(arg[-1])
    n=3
    a_h,d_h=read_data_homology("data_homology")
    print("Data Read")
    lsy=load_neighbor_genes()
    gene_sequences=read_gene_sequences(a_h,lsy,"geneseq","gene_seq_positive")
    gene_sequences=update_rest(gene_sequences,"gene_seq_positive")
    print("Gene Sequences Loaded.")
    if not os.path.isdir("processed/synteny_matrices"):
        os.mkdir("processed/synteny_matrices")
    ndir="processed/synteny_matrices/"
    nf1="synteny_matrices_global"
    nf2="synteny_matrices_local"
    nf3="indexes"
    for i in range(len(a_h)):
        df=a_h[i]
        part=len(df)//nop
        pr=Procerssrunner()
        pr.start_processes(nop,df,gene_sequences,lsy,part,n,d_h[i])
        smg,sml,indexes=read_data_synteny(nop,d_h[i])
        print(len(indexes))
        np.save(ndir+str(d_h[i])+"_"+nf1,smg)
        np.save(ndir+str(d_h[i])+"_"+nf2,sml)
        np.save(ndir+str(d_h[i])+"_"+nf3,indexes)
        a_h[i]=df.loc[indexes]
    print("Synteny Matrices Created Successfully :)")    
    protein_sequences=read_gene_sequences(a_h,lsy,"pro_seq","pro_seq_positive")
    protein_sequences=update_rest_protein(protein_sequences,"pro_seq_positive")    
    write_fasta(protein_sequences,"protein_seq_positive")
    print("Protein Sequences Loaded.")
if __name__=="__main__":
    main()