mirror of
https://github.com/Priyatham-sai-chand/compara-deep-learning.git
synced 2026-10-05 08:11:34 -07:00
Delete process_data.py
This commit is contained in:
parent
525b433cc8
commit
580050f3d0
1 changed files with 0 additions and 83 deletions
|
|
@ -1,83 +0,0 @@
|
||||||
import pandas
|
|
||||||
import gc
|
|
||||||
import numpy as np
|
|
||||||
|
|
||||||
def get_nearest_neighbors(g,gs,n,a,d,ld,ldg):
|
|
||||||
ne=[]
|
|
||||||
nr=[]
|
|
||||||
gi=d[gs.capitalize()]
|
|
||||||
sldf=a[gi]
|
|
||||||
sld=ld[gi]
|
|
||||||
sldg=ldg[gi]
|
|
||||||
if g not in sldg:
|
|
||||||
return ne
|
|
||||||
i=sldg[g]
|
|
||||||
#get the -n neighbors
|
|
||||||
start=int(sldf.iloc[i,[3]])
|
|
||||||
for j in range(n):
|
|
||||||
#select the column
|
|
||||||
itemp=0
|
|
||||||
end=sldf.iloc[:,4]
|
|
||||||
end=np.array(end)
|
|
||||||
assert(len(end)==len(sld))
|
|
||||||
end=end-start
|
|
||||||
end_s=np.argsort(end)
|
|
||||||
for k in end_s:
|
|
||||||
if end[k]<0 and end[k+1]>=0:
|
|
||||||
itemp=k
|
|
||||||
break
|
|
||||||
ne.append(sld[itemp])
|
|
||||||
start=int(sldf.iloc[itemp,[3]])
|
|
||||||
#print(start)
|
|
||||||
#get the +n neighbors
|
|
||||||
end=int(sldf.iloc[i,[4]])
|
|
||||||
for j in range(n):
|
|
||||||
itemp=0
|
|
||||||
start=sldf.iloc[:,3]
|
|
||||||
start=np.array(start)
|
|
||||||
start=start-end
|
|
||||||
start_s=np.argsort(start)
|
|
||||||
for k in start_s:
|
|
||||||
if start[k]>0:
|
|
||||||
itemp=k
|
|
||||||
break
|
|
||||||
nr.append(sld[itemp])
|
|
||||||
end=int(sldf.iloc[itemp,[4]])
|
|
||||||
|
|
||||||
return ne,nr
|
|
||||||
|
|
||||||
ls=[]
|
|
||||||
ld=[]
|
|
||||||
def list_dict_genomes(a,n):
|
|
||||||
for x in a:
|
|
||||||
ldg={}
|
|
||||||
uc=list(x["gene_id"])
|
|
||||||
for i in range(len(uc)):
|
|
||||||
ldg[uc[i]]=i
|
|
||||||
ls.append(uc)
|
|
||||||
ld.append(ldg)
|
|
||||||
return ls,ld
|
|
||||||
|
|
||||||
def create_data_homology_ls(a_h,d_h,n,a,d,ld,ldg):
|
|
||||||
lsy={} #dictionary which stores +/- n genes of the given gene by id. Each key is a gene id which corresponds to the one in center.
|
|
||||||
lcmap={} #dictionary which stores the gene pairs already considered
|
|
||||||
t=0
|
|
||||||
for df in a_h:
|
|
||||||
for index,row in df.iterrows():
|
|
||||||
x=row["gene_stable_id"]
|
|
||||||
y=row["homology_gene_stable_id"]
|
|
||||||
xs=row["species"]
|
|
||||||
ys=row["homology_species"]
|
|
||||||
if x+y in lcmap or y+x in lcmap:
|
|
||||||
continue
|
|
||||||
if x not in lsy:
|
|
||||||
xl,xr=get_nearest_neighbors(x,xs,n,a,d,ld,ldg)
|
|
||||||
lsy[x]=dict(b=xl,f=xr)
|
|
||||||
if y not in lsy:
|
|
||||||
yarr=[]
|
|
||||||
yl,yr=get_nearest_neighbors(y,ys,n,a,d,ld,ldg)
|
|
||||||
lsy[y]=dict(b=yl,f=yr)
|
|
||||||
lcmap[x+y]=1
|
|
||||||
|
|
||||||
|
|
||||||
return lsy,lcmap
|
|
||||||
Loading…
Reference in a new issue