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`prepare_negative_dataset.py` selects a gene from the homology database and another one from the gtf files which is not present in the any of the homology databases.
71 lines
1.7 KiB
Python
71 lines
1.7 KiB
Python
import sys
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import numpy as np
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import pandas as pd
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import os
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import gc
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import progressbar
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import random
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from read_data import read_data_homology,read_data_genome
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arg=sys.argv
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arg=arg[1:]
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nos=int(arg[0])
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seed=int(arg[1])
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random.seed(seed)
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a_h,d_h=read_data_homology("data_homology")
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a=[]
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d={}
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a,d=read_data_genome("data",a,d)
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assert(len(a)==len(d))
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indexes_gd=[list(df.index.values) for df in a]
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d=list(d.keys())
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gmap={}
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indexes_hd=[]
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for df in progressbar.progressbar(a_h):
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indexes_hd.append(list(df.index.values))
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hgids=df.homology_gene_stable_id.unique()
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for h in hgids:
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gmap[h]=1
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col_names=["gid","species","hgid","h_species"]
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nohd=len(a_h)
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nogd=len(a)
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rows=[]
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for i in progressbar.progressbar(range(nos)):
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while(1):
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try:
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slh=random.randrange(nohd)
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slg=random.randrange(nogd)
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slgd=a[slg]
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n1=d[slg]
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indexes=indexes_gd[slg]
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ind=random.randrange(len(indexes))
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try:
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_=gmap[slgd.loc[indexes[ind]].gene_id]
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continue
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except:
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slhd=a_h[slh]
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lid=indexes_hd[slh]
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ind_1=random.randrange(len(slhd))
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row=slhd.loc[lid[ind_1]]
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r={}
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r["gene_stable_id"]=row.gene_stable_id
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r["species"]=row.species
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r["homology_gene_stable_id"]=slgd.loc[indexes[ind]].gene_id
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r["homology_species"]=n1
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rows.append(r)
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break
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except:
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continue
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a_h=[]
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gc.collect()
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ndf=pd.DataFrame(rows)
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print(ndf[0:10])
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ndf.to_hdf("negative_dataset.h5",key="ndf",mode="w")
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