Add files to create negative dataset

`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.

prepare_negative_dataset.py

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+import sys
+import numpy as np
+import pandas as pd
+import os
+import gc
+import progressbar
+import random
+from read_data import read_data_homology,read_data_genome
+
+arg=sys.argv
+arg=arg[1:]
+
+nos=int(arg[0])
+seed=int(arg[1])
+random.seed(seed)
+
+a_h,d_h=read_data_homology("data_homology")
+a=[]
+d={}
+a,d=read_data_genome("data",a,d)
+assert(len(a)==len(d))
+indexes_gd=[list(df.index.values) for df in a]
+d=list(d.keys())
+
+gmap={}
+indexes_hd=[]
+for df in progressbar.progressbar(a_h):
+    indexes_hd.append(list(df.index.values))
+    hgids=df.homology_gene_stable_id.unique()
+    for h in hgids:
+        gmap[h]=1
+
+
+
+col_names=["gid","species","hgid","h_species"]
+nohd=len(a_h)
+nogd=len(a)
+rows=[]
+for i in progressbar.progressbar(range(nos)):
+    while(1):
+        try:
+            slh=random.randrange(nohd)
+            slg=random.randrange(nogd)
+            slgd=a[slg]
+            n1=d[slg]
+            indexes=indexes_gd[slg]
+            ind=random.randrange(len(indexes))
+            try:
+                _=gmap[slgd.loc[indexes[ind]].gene_id]
+                continue
+            except:
+                slhd=a_h[slh]
+                lid=indexes_hd[slh]
+                ind_1=random.randrange(len(slhd))
+                row=slhd.loc[lid[ind_1]]
+                r={}
+                r["gene_stable_id"]=row.gene_stable_id 
+                r["species"]=row.species
+                r["homology_gene_stable_id"]=slgd.loc[indexes[ind]].gene_id
+                r["homology_species"]=n1  
+                rows.append(r) 
+                break 
+        except:
+            continue  
+
+a_h=[]
+gc.collect()
+
+ndf=pd.DataFrame(rows)
+print(ndf[0:10])
+ndf.to_hdf("negative_dataset.h5",key="ndf",mode="w")

read_negative_dataset.py

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+import pandas as pd 
+
+df=pd.read_hdf("negative_dataset.h5",key="ndf")
+
+print(df.info())
+print(df.loc[33333:33433])