def processLines(lines, best_sequences, find_params, verbose=False):
if len(best_sequences) > 0:
print("len of best_sequences={}".format(len(best_sequences[0][0])))
for i in range(1, len(best_sequences)):
assert len(best_sequences[i][0]) == len(best_sequences[0][0])
if len(lines) > 0:
print("len of new lines={}".format(len(lines[0])))
for i in range(1, len(lines)):
assert len(lines[i]) == len(lines[0])
if len(lines) == 0:
return best_sequences
if len(best_sequences) > 0:
if len(best_sequences[0][0]) < len(lines[0]):
return best_sequences
if len(best_sequences[0][0]) > len(lines[0]):
best_sequences = []
space = lines if verbose==False else tqdm.tqdm(lines)
for seq in space:
seq_coefs = parsers.analyze_string(seq, find_params)
good = True
for _, other_coefs in best_sequences:
if is_less(seq_coefs, other_coefs):
good = False
break
if good == True:
best_sequences.append((seq, seq_coefs))
best_sequences = list(filter(
lambda x: not is_less(x[1], seq_coefs), best_sequences))
return best_sequences
def create_table(kParam, resultStringSize):
result = []
excludedStrings = set()
counter = 0
for patternSize in tqdm.trange(1, kParam+1):
assert resultStringSize % patternSize == 0
for patternString in itertools.product(*(['acgt'] * patternSize)):
fullString = "".join(patternString) * (resultStringSize // patternSize)
good = True
for s in excludedStrings:
if fullString == s or fullString == s[::-1]:
good = False
if good == False:
continue
excludedStrings.add(fullString)
if patternSize == kParam:
#print("{}: {}".format(str(counter), fullString))
result.append(("".join(patternString), fullString))
#counter += 1
find_GQD = False
find_IMT = False
find_TRP = False
find_HRP = False
result_lines = []
for pattern, fullString in result:
seq_coefs = parsers.analyze_string(s, [find_GQD, find_IMT, find_TRP, find_HRP])
#print(seq_coefs)
result_lines.append((kParam, pattern, fullString) + seq_coefs)
return result_lines
from itertools import *
from modules import parsers
from timeit import default_timer as timer
length = 14
start = timer()
with open('result.txt', 'w') as f:
for s in product('acgt', repeat=length):
s = ''.join(s)
result_tuple = parsers.analyze_string(s, [True, True, True, 1])
if result_tuple >= (1, 1, 1, 1):
f.write('{0} {1}\n'.format(s, result_tuple))
end = timer()
f.write('total seconds:{0}'.format(end - start))
# -*- coding: utf-8 -*-
import sys, os
sys.path.append('../')
from modules import parsers
if __name__ == "__main__":
seq = "tgactgactgactgactgactgac"
find_GQD = True
find_IMT = True
find_TRP = True
find_HRP = True
result = parsers.analyze_string(seq,
[find_GQD, find_IMT, find_TRP, find_HRP])
print("GQD strength = {}".format(result[0]))
print("IMT strength = {}".format(result[1]))
print("HRP strength = {}".format(result[2]))
print("TRP strength = {}".format(result[3]))
parser.add_argument('--find-GQD', type=int, default=0)
parser.add_argument('--find-IMT', type=int, default=1)
parser.add_argument('--find-HRP', type=int, default=0)
parser.add_argument('--find-TRP', type=int, default=0)
args = parser.parse_args()
input_path = args.input_path
output_path = args.output_path
if output_path == None:
output_path = input_path + ".processed.csv"
find_GQD = bool(args.find_GQD)
find_IMT = bool(args.find_IMT)
find_HRP = bool(args.find_HRP)
find_TRP = bool(args.find_TRP)
with open(output_path, "w") as output:
output.write(",".join(["{}"] *
5).format("string", "GQD", "IMT", "TRP", "HRP") +
"\n")
with open(input_path, "r") as input:
lines = input.readlines()
lines = list(map(lambda x: re.sub('[\n\r]', '', x), lines))
for line in tqdm.tqdm(lines):
sequence = line.split(",")[0]
seq_coefs = parsers.analyze_string(
sequence, [find_GQD, find_IMT, find_TRP, find_HRP])
output.write(",".join(["{}"] * 5).format(*(
(sequence, ) + seq_coefs)) + "\n")