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plateau-1.1.py
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#!/usr/python
#
# Copyright (c) 2018 AG Freund, Freie Universitaet Berlin (GER)
#
# This program is distributed as a free scientific tool,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
#
# For questions about running the script or for reporting bugs, please contact either:
# Christian Freund ([email protected])
# or
# Eliot Morrison ([email protected])
#
import sys
import re
import csv
import os
import numpy as np
from scipy import stats
import math
import itertools
from pyteomics import fasta, parser, mass, achrom, electrochem, auxiliary
from scipy import stats
from os import listdir
from os.path import isfile, join
from scipy.stats import ttest_ind
import statistics
def openfile(filename, cols):
raw = list(csv.reader(open(filename, 'rU'), delimiter='\t'))
headers = raw[0]
raw = raw[1:]
count = 0
inds = []
for a in headers:
for b in cols:
if a == b:
inds.append(count)
count += 1
return raw, headers, inds
def savefile(filename, out, headers_out):
if headers_out != []:
out.insert(0,headers_out)
with open(filename, 'w') as a_file:
for result in out:
result = '\t'.join(result)
a_file.write(result + '\n')
def add_areas_to_evidence(evidence_file):
cols = ['Raw file', 'm/z', 'Retention time', 'Intensity']
raw, headers, inds = openfile(evidence_file, cols)
unique_exps = []
# headers_out = ['Run', 'Total intensity',
#'Total area under curve', 'Area/Intens']
headers_out = ['Run', 'Total intensity']
out = []
for a in raw:
if a[inds[0]] not in unique_exps:
unique_exps.append(a[inds[0]])
unique_exps.sort()
for a in unique_exps:
entry = ['']*len(headers_out)
entry[0] = a
intens_sum = 0.0
for b in raw:
if b[inds[0]] == entry[0] and b[inds[3]] != '':
intens_sum += float(b[inds[3]])
entry[1] = str(intens_sum)
out.append(entry)
print entry
out_file = 'ms_exps_total_intens_areas_for_norm.txt'
savefile(out_file, out, headers_out)
exp_tots = out[1:]
headers_out = headers
headers_out.append('Intensity')
headers_out.append('Intensity (normalized)')
out = []
for a in raw:
entry = ['']*len(headers_out)
for x in range(0,len(a)):
entry[x] = a[x]
last_ind = x + 1
intens = a[inds[3]]
exp = a[inds[0]]
for b in exp_tots:
if b[0] == exp:
intens_tot = float(b[1])
# area_tot = float(b[2])
intens_norm = ''
if intens != '':
intens_norm = float(intens)/intens_tot
entry[last_ind] = str(intens)
entry[last_ind+1] = str(intens_norm)
print entry[0], entry[-2], entry[-1]
out.append(entry)
out_file = evidence_file.split('.txt')[0] + '_intens_norm.txt'
savefile(out_file, out, headers_out)
def get_cond_peps(file_in, fasta_file):
cols = ['Sequence', 'Proteins', 'Experiment', 'Intensity (normalized)']
raw, headers, inds = openfile(file_in, cols)
unique_prots = []
unique_conds = []
unique_bio_reps = ['']
count = 0
prot_seqs = []
no_fasta = []
for a in raw:
prots = a[inds[1]].split(';')
count += 1
for b in prots:
prot = b.split('CON__')[-1]
prot_seq = ''
if prot not in unique_prots and [prot] not in no_fasta:
fasta_test = False
# print prot
for description, sequence in fasta.read(fasta_file):
if '|'+prot+'|' in description:
fasta_test = True
print 'Fasta match found:', prot, count, '/', len(raw)
prot_seq = sequence
if fasta_test == True:
unique_prots.append(prot)
prot_seqs.append([prot, prot_seq])
else:
print 'No FASTA match:', prot
no_fasta.append([prot])
if a[inds[2]] not in unique_conds:
unique_conds.append(a[inds[2]])
#if a[inds[4]] not in unique_bio_reps:
# unique_bio_reps.append(a[inds[4]])
headers_out = ['Protein', 'Experiment', 'Passing Peptides', 'FASTA seq', 'Intensities (normalized)']
out = []
for prot in unique_prots:
for cond in unique_conds:
for bio_rep in unique_bio_reps:
pep_list = []
intens_list = []
for a in raw:
if prot in a[inds[1]]:
if cond == a[inds[2]]:
if 1==1:
pep_list.append(a[inds[0]])
intens_list.append(a[inds[3]])
pep_str = ''
for i in pep_list:
pep_str += i + ';'
pep_str = pep_str[:-1]
intens_str = ''
for i in intens_list:
intens_str += i + ';'
intens_str = intens_str[:-1]
for b in prot_seqs:
if b[0] == prot:
prot_seq = b[1]
entry = [prot, cond, pep_str, prot_seq, intens_str]
out.append(entry)
print entry
file_out = file_in.split('.txt')[0] + '_passpeps.txt'
savefile(file_out, out, headers_out)
def gen_epitopes(file_in, fasta_file, min_epi_len, min_step_size, min_epi_overlap):
cols = ['Protein', 'Passing Peptides', 'FASTA seq', 'Intensities (normalized)']
raw, headers, inds = openfile(file_in, cols)
headers_out = headers[:-1]
headers_out.append('Core epitopes')
headers_out.append('Whole epitopes')
# headers_out.append('PLAtEAU Spec. Counts')
headers_out.append('PLAtEAU Intens. (norm)')
headers_out.append('Peptides contributing to core epitopes')
out = []
prot_seqs = []
for a in raw:
prot = a[inds[0]]
prot_seq = a[inds[2]]
prot_seqs.append([prot, prot_seq])
jump_count = 0
total_count = 0
for j in raw:
total_count += 1
entry = ['']*len(headers_out)
for i in range(0,len(j)-1):
entry[i] = j[i]
core_epis = []
whole_epis = []
founds_for_entry = []
pep_matches = []
prot = j[inds[0]]
prot_seq = ''
for b in prot_seqs:
if prot == b[0]:
prot_seq = b[1]
if j[inds[1]] != '':
pep_list = j[inds[1]].split(';')
intens_list = j[inds[3]].split(';')
# 0 = AA, 1 = position
seq_pos = []
count = 1
for a in prot_seq:
seq_pos.append([a, count])
count += 1
# pep_pos: 0 = peptide, 1 = start_index
pep_pos = []
# 0 = AA, 1 = position
tot_found = []
for y in range(0,len(pep_list)):
pep = pep_list[y]
intens = intens_list[y]
if intens == '':
intens = '0.0'
before_pep = prot_seq.split(pep)[0]
if len(prot_seq.split(pep)) > 1:
after_pep = prot_seq.split(pep)[1]
else:
after_pep = ''
pep_start_ind = len(before_pep)
pep_pos.append([pep, pep_start_ind])
for i in range(0,len(pep)):
tot_found.append([pep[i], pep_start_ind + i + 1, float(intens)])
#print prot, tot_found[-1]
pep_pos.sort(key=lambda x: int(x[-1]))
# this gives a total protein primary sequence w/ spec. count at each position
seq_list = []
for a in seq_pos:
tot_count = 0
intens_count = 0.0
for b in tot_found:
if b[0] == a[0] and b[1] == a[1]:
tot_count += 1
intens_count += b[2]
#seq_list.append([a[0], a[1], tot_count])
seq_list.append([a[0], a[1], intens_count])
#print seq_list[-1]
epis = []
start_pos = []
end_pos = []
for i in range(1,len(seq_list)-1):
prev_num = float(seq_list[i-1][2])
current_num = float(seq_list[i][2])
next_num = float(seq_list[i+1][2])
#if current_num != 0 or next_num != 0:
#print i, prev_num, current_num, next_num
if current_num == 0.0 and next_num != 0.0:
#start_pos.append(i-3) # ******
start_pos.append(i) # ******
#print 'Start pos:', i+1
if i == 1 and current_num != 0.0:
start_pos.append(i-1)
#print 'Start pos:', i+1
if current_num != 0.0 and next_num == 0.0:
end_pos.append(i+2)
#print 'End pos:', i
#print ''
if i == len(seq_list)-2 and current_num != 0.0:
end_pos.append(i+2)
#print '**'
#print start_pos, end_pos
# Problem:
# MACARPLISVYSEKGESSGKNVTLPAVFKAPIRPDIVNFVHTNLRKNNRQPYAVSELAGHQTSAESWGTGRA whole
# contains two cores (AVSELAGHQTSAESWGTGR), (ACARPLISVYSEKGESSGK)
# need to split whole epitopes that have two local maxima
new_start_pos = []
new_end_pos = []
for i in range(0,len(start_pos)):
epi = seq_list[start_pos[i]:end_pos[i]]
found_str = ''
founds = []
for x in epi:
if float(x[2]) not in founds:
if float(x[2]) != 0.0:
founds.append(float(x[2]))
found_str += str(x[2]) + '--'
found_str = found_str[:-2]
# a normal epitope should go low > high > low
# two local maxima will go low > high > low > high > low
# Create a string: 0 = less than or equal, 1 = greater than
found_strs = []
founds.sort()
for y in founds:
bin_str = ''
for z in epi:
if float(z[2]) <= y:
bin_str += '0'
else:
bin_str += '1'
#print y, bin_str
split_1 = bin_str.split('0')
split_2 = []
for z in split_1:
if z != '':
split_2.append(z)
#print y, split_1, split_2
if len(split_2) > 1:
if len(split_2[0]) >= min_epi_len and len(split_2[-1]) >= min_epi_len:
found_strs.append([y, len(split_2[0]), len(split_2[-1]), bin_str])
#print y, bin_str
#print found_str
#print found_strs[-1]
if len(found_strs) > 0:
print found_strs
new_min = found_strs[0][0]
bin_str = found_strs[0][-1]
zero_list = []
for k in bin_str.split('1'):
if k != '':
zero_list.append(k)
gap_size = len(zero_list[1])
gap_pos_bin = len(zero_list[0]) + found_strs[0][1]
gap_pos = epi[gap_pos_bin][1]
print 'Gap size:', gap_size, 'starting:', gap_pos_bin, gap_pos
# gap_pos = first '0' of gap
# if gap size = 1, add new end = gap_pos - 1, new start = gap_pos
# if gap size > 1:
# new end = len(first 1s) + gap_size
# new start = len(first 1s)
new_starts = []
new_ends = []
if gap_size == 1:
new_ends.append(gap_pos-1)
new_end_pos.append(gap_pos-1)
new_starts.append(gap_pos)
new_start_pos.append(gap_pos)
elif gap_size > 1:
new_ends.append(gap_pos+gap_size)
new_end_pos.append(gap_pos+gap_size)
new_starts.append(gap_pos)
new_start_pos.append(gap_pos)
#print bin_str
#print found_strs, prot
#print ''
#new_min = found_strs[-1][0]
#new_min = found_strs[0][0]
#print ''
#print 'Old start pos:', start_pos
#print 'Old end pos:', end_pos
#print 'new_min', new_min
#bin_str = found_strs[0][-1]
#print bin_str
#start_ind = 0
#for h in bin_str:
# if h == '1':
# break
# start_ind += 1
#new_starts = []
#new_ends = []
#epi_starts = [0]
#epi_ends = []
#for i in range(start_ind,len(epi)-found_strs[0][2]-1):
# prev_num = int(bin_str[i-1])
# current_num = int(bin_str[i])
# next_num = int(bin_str[i+1])
# pos = epi[i][1]
# #print pos, current_num
# if current_num == 0 and next_num == 1:
# new_ends.append(pos)
# new_end_pos.append(pos)
# #print 'new_end:', pos
# if current_num == 1 and next_num == 0:
# new_starts.append(pos)
# new_start_pos.append(pos)
# #print 'new_start:', pos
# if len(new_end_pos) == 0 and i == len(epi)-found_strs[0][2]-2:
# new_end_pos.append(pos)
#new_start_pos.append(epi[0][1])
#new_end_pos.append(new_ends[0])
#new_start_pos.append(new_starts[0])
#new_end_pos.append(epi[-1][1])
if len(new_start_pos) > 0:
#print '**', new_start_pos
#print new_end_pos
for f in range(0,len(new_start_pos)):
start_pos.append(new_start_pos[f])
end_pos.append(new_end_pos[f])
start_pos.sort()
end_pos.sort()
#if 'P04233' in prot:
# print start_pos
# print end_pos
# Look for overlapping epitopes
# A standard nested peptide distribution should change by 1-2 residues
# A large jump (> 5 residues) likely means a different epitope distribution
# pep_pos: 0 = peptide, 1 = start_index
pep_pos_unique = []
for x in pep_pos:
if x not in pep_pos_unique:
pep_pos_unique.append(x)
new_start_pos = []
new_end_pos = []
jump_test = False
for i in range(0,len(start_pos)):
epi = seq_list[start_pos[i]:end_pos[i]]
start_ind = start_pos[i]
epi_str = ''
for y in epi:
epi_str += str(y[0])
match_pep_pos = []
for x in pep_pos_unique:
#print epi_str, x[0]
# if epi_str in x[0]:
if x[0] in epi_str:
match_pep_pos.append(x)
#print x
found_str = ''
founds = []
for x in epi:
if float(x[2]) not in founds:
if float(x[2]) != 0.0:
founds.append(float(x[2]))
found_str += str(x[2]) + '--'
found_str = found_str[:-2]
#jump_test = False
for i in range(0,len(match_pep_pos)-1):
this_pep = match_pep_pos[i]
next_pep = match_pep_pos[i+1]
#print '**', this_pep, next_pep
#if next_pep[1] - this_pep[1] > min_step_size and 'P04233' in prot:
step_size = next_pep[1] - this_pep[1]
#print '&&', this_pep, next_pep, step_size, len(this_pep[0]), step_size + min_epi_overlap
if next_pep[1] - this_pep[1] > min_step_size and len(this_pep[0]) <= step_size + min_epi_overlap:
print ''
print 'Jump:', this_pep, next_pep
jump_test = True
if next_pep[1]-1 not in start_pos:
new_start_pos.append(next_pep[1]) ####
if this_pep[1]+len(this_pep[0])-1 not in end_pos:
new_end_pos.append(this_pep[1]+len(this_pep[0])) ####
print 'Step size:', step_size, 'pep length:', len(this_pep[0])
#print 'Start added:', new_start_pos[-1]
#print 'End added:', new_end_pos[-1]
# pep_list_1 will be peptides with start index <= this_pep[1]
# pep_list_2 will be peptides with start index > this_pep[1]
pep_list_1_ind_end = this_pep[1]
pep_list_1_ind_start = start_ind
pep_list_2_ind_start = next_pep[1]
pep_list_2_ind_end = match_pep_pos[-1][1] + len(match_pep_pos[-1][0])
#pep_list_2_ind = next_pep[1]
pep_list_1 = []
pep_list_2 = []
#print '..', match_pep_pos
if jump_test == True:
for j in match_pep_pos:
if pep_list_1_ind_start <= j[1] <= pep_list_1_ind_end:
pep_list_1.append(j[0])
elif pep_list_2_ind_start <= j[1] <= pep_list_2_ind_end:
pep_list_2.append(j[0])
#print pep_list_1
#print pep_list_2
if jump_test == True:
jump_count += 1
print 'Jumps:', jump_count, '/', total_count, ' (' + str(float(jump_count)/float(total_count)*100.0)+'%)'
if len(new_start_pos) > 0:
#print '**', new_start_pos
#print new_end_pos
for f in range(0,len(new_start_pos)):
start_pos.append(new_start_pos[f])
end_pos.append(new_end_pos[f])
start_pos.sort()
end_pos.sort()
#if 'P04233' in prot and jump_test == True:
# print start_pos
# print end_pos
#print new_start_pos, new_end_pos
#print start_pos, end_pos
for i in range(0,len(start_pos)):
epi = seq_list[start_pos[i]:end_pos[i]]
core_start = start_pos[i]
core_end = end_pos[i]
#found_str = ''
founds = []
for x in epi:
if float(x[2]) not in founds:
founds.append(float(x[2]))
# found_str += str(x[2]) + '--'
#found_str = found_str[:-2]
#print prot, j[1], j[2], '(',start_pos[i],')', found_str, '(',end_pos[i],')'
#founds_for_entry.append(found_str)
whole_epi = ''
for l in epi:
whole_epi += l[0]
if jump_test == True:
print 'whole epi:', whole_epi
#if prot == 'P36578':
#if whole_epi == 'MACARPLISVYSEKGESSGKNVTLPAVFKAPIRPDIVNFVHTNLRKNNRQPYAVSELAGHQTSAESWGTGRA':
# print prot, j[1], j[2], '(',start_pos[i],')', found_str, '(',end_pos[i],')'
list_1_jump_test = False
list_2_jump_test = False
if jump_test == True:
if pep_list_1_ind_start <= start_pos[i] <= pep_list_1_ind_end:
list_1_jump_test = True
if pep_list_2_ind_start <= start_pos[i] <= pep_list_2_ind_end:
list_2_jump_test = True
pep_match = []
intens_match = []
if jump_test == False:
for y in range(0,len(pep_list)):
pep = pep_list[y]
intens = intens_list[y]
if pep in whole_epi:
pep_match.append(pep)
intens_match.append(intens)
else:
#print start_pos[i], pep_list_1_ind
#print 'List 1', pep_list_1_ind_start, start_pos[i], pep_list_1_ind_end
#print 'List 2', pep_list_2_ind_start, start_pos[i], pep_list_2_ind_end
if list_1_jump_test == True:
for y in range(0,len(pep_list)):
pep = pep_list[y]
intens = intens_list[y]
if pep in whole_epi and pep in pep_list_1:
pep_match.append(pep)
intens_match.append(intens)
#print 'List 1 pep', pep
elif list_2_jump_test == True:
for y in range(0,len(pep_list)):
pep = pep_list[y]
intens = intens_list[y]
if pep in whole_epi and pep in pep_list_2:
pep_match.append(pep)
intens_match.append(intens)
else:
for y in range(0,len(pep_list)):
pep = pep_list[y]
intens = intens_list[y]
if pep in whole_epi:
pep_match.append(pep)
intens_match.append(intens)
if list_1_jump_test == True or list_2_jump_test == True:
tot_found_1 = []
for y in range(0,len(pep_match)):
pep = pep_match[y]
intens = intens_match[y]
if intens == '':
intens = 0.0
before_pep = prot_seq.split(pep)[0]
if len(prot_seq.split(pep)) > 1:
after_pep = prot_seq.split(pep)[1]
else:
after_pep = ''
pep_start_ind = len(before_pep)
#pep_pos.append([pep, pep_start_ind])
for n in range(0,len(pep)):
tot_found_1.append([pep[n], pep_start_ind + n + 1, intens])
#print prot, tot_found[-1]
#pep_pos.sort(key=lambda x: int(x[-1]))
# this gives a total protein primary sequence w/ spec. count at each position
seq_list_1 = []
for f in seq_pos:
tot_count = 0
intens_count = 0.0
for d in tot_found_1:
if d[0] == f[0] and d[1] == f[1]:
tot_count += 1
if d[2] != '':
intens_count += float(d[2])
#seq_list_1.append([f[0], f[1], tot_count])
seq_list_1.append([f[0], f[1], intens_count])
#print seq_list_1[-1]
epi_1 = seq_list_1[start_pos[i]:end_pos[i]]
founds_1 = []
for x in epi_1:
if float(x[2]) not in founds_1:
if float(x[2]) != 0.0:
founds_1.append(float(x[2]))
pep_match_str = ''
for g in pep_match:
pep_match_str += g + ','
pep_match_str = pep_match_str[:-1]
core_str = ''
if list_1_jump_test == True or list_2_jump_test == True:
found_str = ''
for x in epi_1:
found_str += str(x[2]) + '--'
found_str = found_str[:-2]
founds_for_entry.append(found_str)
founds_1.sort(reverse=True)
passing_core = False
for num in founds_1:
core = []
for k in epi_1:
#print k
if float(k[2]) >= num:
core.append(k)
#core_str = ''
#core_start = core[0][1]
#core_end = core[-1][1]
#for l in core:
# core_str += l[0]
if len(core) >= min_epi_len and passing_core == False:
passing_core = True
core_str = ''
core_start = core[0][1]
core_end = core[-1][1]
for l in core:
core_str += l[0]
if 'P04233' in prot and jump_test == True:
print 'Chosen core:', core_str
print founds_for_entry[-1]
#print whole_epi, core_str
core_str = ''
core = seq_list[core_start-1:core_end]
#print 'jj', core_start, core_end, seq_list[core_start:core_end]
for l in core:
core_str += l[0]
# epitope, start pos, end pos
if list_1_jump_test == True:
core_str = core_str + '*'
if list_2_jump_test == True:
core_str = '*' + core_str
core_epis.append([core_str, core_start, core_end])
if list_1_jump_test == True:
whole_epi = whole_epi + '*'
if list_2_jump_test == True:
whole_epi = '*' + whole_epi
whole_epis.append([whole_epi, start_pos[i], end_pos[i]])
pep_matches.append(pep_match_str)
else:
found_str = ''
for x in epi:
found_str += str(x[2]) + '--'
found_str = found_str[:-2]
founds_for_entry.append(found_str)
founds.sort(reverse=True)
passing_core = False
for num in founds:
core = []
for k in epi:
#print k
if float(k[2]) >= num:
core.append(k)
#core_str = ''
#core_start = core[0][1]
#core_end = core[-1][1]
#for l in core:
# core_str += l[0]
if len(core) >= min_epi_len and passing_core == False:
passing_core = True
core_str = ''
core_start = core[0][1]
core_end = core[-1][1]
for l in core:
core_str += l[0]
if 'P04233' in prot and jump_test == True:
print 'Chosen core:', core_str
print founds_for_entry[-1]
#print whole_epi, core_str
core_str = ''
core = seq_list[core_start-1:core_end]
#print 'jj', core_start, core_end, seq_list[core_start:core_end]
for l in core:
core_str += l[0]
# epitope, start pos, end pos
if list_1_jump_test == True:
core_str = core_str + '*'
if list_2_jump_test == True:
core_str = '*' + core_str
core_epis.append([core_str, core_start, core_end])
if list_1_jump_test == True:
whole_epi = whole_epi + '*'
if list_2_jump_test == True:
whole_epi = '*' + whole_epi
whole_epis.append([whole_epi, start_pos[i], end_pos[i]])
pep_matches.append(pep_match_str)
core_str = ''
for t in core_epis:
epi_temp = str(t[1]) + '-' + t[0] + '-' + str(t[2])
core_str += epi_temp + ';'
core_str = core_str[:-1]
whole_str = ''
for t in whole_epis:
epi_temp = str(t[1]) + '-' + t[0] + '-' + str(t[2])
whole_str += epi_temp + ';'
whole_str = whole_str[:-1]
pep_match_str = ''
for o in pep_matches:
pep_match_str += o + ';'
pep_match_str = pep_match_str[:-1]
founds_for_entry_str = ''
for o in founds_for_entry:
founds_for_entry_str += o + ';'
founds_for_entry_str = founds_for_entry_str [:-1]
entry[-4] = core_str
entry[-3] = whole_str
entry[-2] = founds_for_entry_str
entry[-1] = pep_match_str
out.append(entry)
#if 'P04233' in prot:
# #print entry
# print ''
# print core_str
# print whole_str
file_out = file_in.split('.txt')[0] + '_epitopes.txt'
savefile(file_out, out, headers_out)
def comb_epis(evidence_file, epitope_file, exp_name):
cols = ['Protein', 'Experiment', 'Core epitopes', 'Whole epitopes',
'PLAtEAU Intens. (norm)', 'Peptides contributing to core epitopes'
]
epis, epi_headers, epi_inds = openfile(epitope_file, cols)
cols = ['Sequence', 'Proteins', 'Experiment', 'Intensity (normalized)'
]
raw, headers, inds = openfile(evidence_file, cols)
# find all unique wholes
unique_wholes = []
for a in epis:
wholes = a[epi_inds[3]].split(';')
print wholes
if wholes[0] != '':
for i in wholes:
whole = i.split('-')[1]
if whole not in unique_wholes and whole != '':
unique_wholes.append(whole)
#print whole
#print len(unique_wholes)
# match unique cores to wholes; choose longest match
unique_cores = []
for a in epis:
cores = a[epi_inds[2]].split(';')
if cores[0] != '':
for i in cores:
core = i.split('-')[1]
if core not in unique_cores and '--' not in i:
unique_cores.append(core)
#print core
#print len(unique_cores)
# 0 = unique core
# 1 = longest whole match
unique_longest_wholes = []
for a in unique_cores:
whole_matches = []
whole_lens = []
for b in unique_wholes:
if '*' not in a and '*' not in b:
if a in b:
whole_matches.append(b)
whole_lens.append(len(b))
elif '*' in a:
if a[-1] == '*' and b[-1] == '*':
if a[:-1] in b[:-1]:
whole_matches.append(b)
whole_lens.append(len(b))
elif a[0] == '*' and b[0] == '*':
if a[1:] in b[1:]:
whole_matches.append(b)
whole_lens.append(len(b))
print 'core:', a, 'whole:', b
if len(whole_lens) > 0:
longest_len = max(whole_lens)
for i in range(0,len(whole_matches)):
if whole_lens[i] == longest_len:
longest_whole = whole_matches[i]
if longest_whole not in unique_longest_wholes:
unique_longest_wholes.append(longest_whole)
#print longest_whole
#print len(unique_wholes), len(unique_longest_wholes)
# 0 = core, 1 = whole
unique_longest_cores = []
seen = []
for a in unique_longest_wholes:
core_matches = []
core_lens = []
for b in unique_cores:
if '*' not in a and '*' not in b:
if b in a:
core_matches.append(b)
core_lens.append(len(b))
elif '*' in a:
#print a, b
if a[-1] == '*' and b[-1] == '*':
if b[:-1] in a[:-1]:
core_matches.append(b)
core_lens.append(len(b))
elif a[0] == '*' and b[0] == '*':
if b[1:] in a[1:]:
core_matches.append(b)
core_lens.append(len(b))
#print a, core_matches
if len(core_lens) > 0:
longest_len = max(core_lens)
longest_cores = []
for i in range(0,len(core_matches)):
if core_lens[i] == longest_len:
longest_cores.append(core_matches[i])
if len(core_lens) > 0:
longest_len = max(core_lens)
longest_cores = []
finals = []
for i in range(0,len(core_matches)):
if core_lens[i] == longest_len:
longest_cores.append(core_matches[i])
if len(longest_cores) == 1:
longest_core = longest_cores[0]
finals.append(longest_core)
else:
core1 = longest_cores[0]
core2 = longest_cores[1]
#print core1, core2
if core1[0] == '*':
core1 = core1[1:]
if core2[0] == '*':
core2 = core2[1:]
if core1[-1] == '*':
core1 = core1[:-1]
if core2[-1] == '*':
core2 = core2[:-1]
n_dist_1 = a.split(core1)[0]
n_dist_2 = a.split(core2)[0]
if n_dist_1 > n_dist_2:
first_core = core2
second_core = core1
elif n_dist_1 < n_dist_2:
first_core = core1
second_core = core2
new_core = first_core + second_core[-1]
print ''
print '******'
print first_core, second_core, new_core
if first_core in new_core and second_core in new_core:
longest_core = new_core
if longest_cores[0][0] == '*' and longest_cores[1][0] == '*':
longest_core = '*' + longest_core
finals.append(longest_core)
#print '*********'
#print ''
#print ''
#print '**', first_core, second_core, new_core
else:
# two different cores of same length
for x in longest_cores: