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h_fgm.py
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# -*- coding: utf-8 -*-
# import cProfile, pstats, StringIO
# pr = cProfile.Profile()
# pr.enable()
import os
import re
import time
from newer_rules import cl, closedd
start_time = time.time()
a = open('E:\F DRIVE\M.Tech\patterns for gmk_down.txt','r').readlines()
a1 = open('E:\F DRIVE\M.Tech\patterns for gmk_up.txt','r').readlines()
allgmk=a+a1
for i in range(len(allgmk)):
allgmk[i] = allgmk[i].rstrip() #to remove the lagging \n in many GMKs
allgmk[i] = allgmk[i].lower()
allgmk=filter(None, allgmk)
print (allgmk)
keyword1 = open('E:\F DRIVE\M.Tech\mouse_gs_small_simple_reduced.txt','r').readlines() # this has the new small GS
keyword2 = open('E:\F DRIVE\M.Tech\mouse_gs_number_large.txt','r').readlines() # this has the large GS
keywords = keyword1+keyword2
keystripped = [k.rstrip().lower() for k in keywords]
c=0
def find_matches(s, gmk, file):
if gmk in s: # checking if gmk is in the line
gs_list = [k for k in keystripped if k in s]
l = re.split('\s|(?<!\d)[,.]|[,.](?!\d)|;|[()]|-', s) # split the line by comma, semicolon and space to check for gmks and gs. Also http://goo.gl/RPQNbT
filter(None, l) # remove empty elements in the list
for gs in gs_list: # gene symbols
if gs in s: # search for GS in line. using 'gs in s' led to a lot of partial word matches <-----------------
gs1 = re.split('\s|(?<!\d)[,.]|[,.](?!\d)|;|-', gs)
gs1=list(filter(None, gs1))
gmk1 = re.split('\s|(?<!\d)[,.]|[,.](?!\d)|;|-', gmk)
gmk1=list(filter(None, gmk1))
if any(l[i:i+len(gs1)]==gs1 for i in range(len(l)-len(gs1)+1)) and (any(l[i:i+len(gmk1)]==gmk1 for i in range(len(l)-len(gmk1)+1))): # this ensures that both gs and gmk are in l, as a unit(i.e. and in order) otherwise it was detecting things like 'beta c' from beta cells
# UPTO THIS POINT WE HAVE ESTABLISHED THAT THE GMK AND GS ARE INDEED IN THE LINE
k1 = '_MKKEYWORD_1_'
k2 = '_SKEYWORD_2_'
#print gmk
text = re.sub(re.escape(gmk), k1, s, flags=re.I) # because of this replacement, we dont have the problem of counting r from behind etc.
# also, I cannot use the regex based replacement used below for gmk replacement because we do want
# cases where gmk's like -/- or + are just after or before a word, without the word boundary
text = re.sub(r'(\b%s\b)' % (re.escape(gs)), k2, text, flags=re.I)
lt = text.split()
d_idx = {k1:[], k2:[]}
for k,v in enumerate(lt): # store all instances of both gs and gmk separately
if k1 in v:
d_idx[k1].append(k)
if k2 in v:
d_idx[k2].append(k)
distance = 8
data = []
for idx1 in d_idx[k1]:
for idx2 in d_idx[k2]:
d = abs(idx1 - idx2) # find distance between gs and gmk
if d<=distance:
data.append((d,idx1,idx2))
data.sort(key=lambda x: x[0])
for i in range (0, len(data)):
aq = data[i]
loq = min(aq[1], aq[2])
hiq = max(aq[1], aq[2])
brrq = lt[max(0, loq-6):hiq+6]
brq = " ".join(brrq)
if data:
cll=cl(s, gmk, gs, gs_list, data, file)
# if cll: #those cases where there is no CL returned because of no rule match, are filtered here
# cll=float(cll)
# gs_cl.append((cll, gs))
c=0
for path, dirs, files in os.walk(r'E:\F DRIVE\M.Tech\for assigning cl\selected\mouse in random 500_l'):
for file in files:
sentences = open(os.path.join(path,file)).readlines();
c = c+1
r=0
rr=0
rt=0
gs_cl=[]
hg=''
for s in sentences:
if s.startswith('!Sample_organism_ch1\t"Mus musculus"'):
r=1
if s.startswith('!Series_type'):
if s.startswith('!Series_type\t"Expression profiling by array"'):
# print 'OUR TYPE'
# print s, file
rr=1
# hg=s
# else:
# print 'OTHER TYPES'
# print s
# rt=1
if (rr==1):
# if rt==1:
# print 'else type in mouse'
# if rr==1:
# print 'good'
for s in sentences:
#print 1
s = s.rstrip()
if s.startswith('!Series_title') or s.startswith('!Series_summary') or s.startswith('!Series_overall_design'):
s = s.lower()
#gs_list = [kk for kk in keystripped if kk in s]
# print(45)
for gmk in allgmk:
find_matches(s, gmk, file)
# gs_cl=sorted(gs_cl, key=lambda x: abs(x[0]), reverse=True) #sorted sorts them in ascending order, reverse makes it descending,
# #key is the rule telling it to sort based on the first element of the tuples and in absolute manner
# #print gs_cl
# gc = [list(t) for t in gs_cl]
# for k in range(len(gc)):
# for i in range(k+1,len(gc)):
# if gc[k][1]==gc[i][1]:
# gc[k][0]=gc[k][0]+gc[i][0]
# gc[i][0]=0
# if gc:
# None
# # print (gc)
# # print (file)
## print ('File is %s, the GS modified is \'%s\' with confidence %f' %(file, gc[0][1], gc[0][0]))
# # print('\n')
# else:
# # None
# print (file)
# print ('match not found yet for these rules')
# print('\n')
#
# #else:
# #print 'GENOME BINDING'
# #print hg
# else:
# # None
# print (file)
# print ('NOT Microarray')
# print('\n')
closedd()
print("--- %s seconds ---" % (time.time() - start_time))
#pr.disable()
#s = StringIO.StringIO()
#sortby = 'cumulative'
#ps = pstats.Stats(pr, stream=s).sort_stats(sortby)
#ps.print_stats()
#print s.getvalue()