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Kappes Marques Rodrigo authoredKappes Marques Rodrigo authored
individu.py 6.15 KiB
from RotTable import RotTable
from Traj3D import Traj3D
import numpy as np
from math import sqrt, inf
from random import random, choice
P1 = 0.015
class Individu():
''' Un individu est caractérisé par sa table de rotations (individu.table)'''
def __init__(self, table):
self.table = table
lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")]
self.brin = ''.join(lineList[1:])
#self.brin = "AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA"
self.score = None
self.distance = None
def evaluate(self):
''' Evalue le score d'un individu sur un nombre numb_ajout de points'''
traj = Traj3D()
numb_ajout = 10
fisrt_seq = self.brin[0:numb_ajout]
last_seq = self.brin[-numb_ajout:]
traj.compute(last_seq + self.brin + fisrt_seq, self.table)
traj_array = traj.getTraj()
list_distance = []
begining = traj_array[0:2*numb_ajout]
end = traj_array[-2*numb_ajout:]
for i in range(numb_ajout):
nuc_coordonate_beg = begining[i]
nuc_coordonate_end = end[i]
distance_nuc = np.linalg.norm(nuc_coordonate_beg - nuc_coordonate_end, ord=2)
list_distance += [distance_nuc]
self.score = max(list_distance)
self.distance = np.linalg.norm(traj_array[numb_ajout] - traj_array[-(numb_ajout+1)], ord=2)
#return max(list_distance)
def mutation(self, proba = P1):
table_rotations = self.table.rot_table
for doublet in sorted(table_rotations.keys()) :
for coord in range(3):
tir = random()
if tir < proba :
table_rotations[doublet][coord] =np.random.uniform(low = self.table.orta()[doublet][coord] - self.table.orta()[doublet][coord + 3], high = self.table.orta()[doublet][coord] + self.table.orta()[doublet][coord + 3])
doublet2 = self.table.corr()[doublet]
if coord == 0 or coord == 1 :
table_rotations[doublet2][coord] = table_rotations[doublet][coord]
else :
#sur l'axe z il y a un moins
table_rotations[doublet2][coord] = - table_rotations[doublet][coord]
def mutation_with_numbers(self, proba = P1, number_of_mutations = 1):
table_rotations = self.table.rot_table
table_rotation_not_seen = [i for i in sorted(table_rotations.keys())]
table_rotation_not_seen = table_rotation_not_seen[:8]
tir = random()
if tir < proba :
for i in range(0,number_of_mutations):
doublet = choice(table_rotation_not_seen)
table_rotation_not_seen.remove(doublet)
for coord in range(3):
table_rotations[doublet][coord] =np.random.uniform(low = self.table.orta()[doublet][coord] - self.table.orta()[doublet][coord + 3], high = self.table.orta()[doublet][coord] + self.table.orta()[doublet][coord + 3])
doublet2 = self.table.corr()[doublet]
if coord == 0 or coord == 1 :
table_rotations[doublet2][coord] = table_rotations[doublet][coord]
else :
#sur l'axe z il y a un moins
table_rotations[doublet2][coord] = - table_rotations[doublet][coord]
def mutation_close_values(self, proba = P1, number_of_mutations = 1):
table_rotations = self.table.rot_table
table_rotation_not_seen = [i for i in sorted(table_rotations.keys())]
table_rotation_not_seen = table_rotation_not_seen[:8]
tir = random()
if tir < proba :
for i in range(0,number_of_mutations):
doublet = choice(table_rotation_not_seen)
table_rotation_not_seen.remove(doublet)
for coord in range(3):
value = table_rotations[doublet][coord] + np.random.normal(0, self.table.orta()[doublet][coord + 3]/10)
if value > self.table.orta()[doublet][coord] + self.table.orta()[doublet][coord + 3]:
value = self.table.orta()[doublet][coord] + self.table.orta()[doublet][coord + 3]
elif value < self.table.orta()[doublet][coord] - self.table.orta()[doublet][coord + 3]:
value = self.table.orta()[doublet][coord] - self.table.orta()[doublet][coord + 3]
table_rotations[doublet][coord] = value
doublet2 = self.table.corr()[doublet]
if coord == 0 or coord == 1 :
table_rotations[doublet2][coord] = table_rotations[doublet][coord]
else :
#sur l'axe z il y a un moins
table_rotations[doublet2][coord] = - table_rotations[doublet][coord]
# individu1 = Individu(RotTable())
# print(individu1.table.rot_table)
# individu1.mutation()
# table = RotTable()
# test = Individu(table)
# test.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
# print(test.score)
# qqun=Individu(RotTable())
# qqun.table.rot_table={'AA': [35.576558502141, 7.433901511509349, -154], 'AC': [33.22048222654215, 5.25191751302917, 143], 'AG': [26.446029097301288, 6.052240462237622, -2], 'AT': [30.47045254036881, 1.333716025628036, 0], 'CA': [34.00734209585039, 33.70710613604862, -64], 'CC': [33.61019622767888, 3.713127032109607, -57], 'CG': [29.664061041382677, 6.725155507162601, 0], 'CT': [26.446029097301288, 6.052240462237622, 2], 'GA': [36.655773481637176, 10.45337581740701, 120], 'GC': [42.26984493493484, 3.5310453395352823, 180], 'GG': [33.61019622767888, 3.713127032109607, -57], 'GT': [33.22048222654215, 5.25191751302917, 143], 'TA': [36.951508786388914, -2.5174751178033303, 0], 'TC': [36.655773481637176, 10.45337581740701, -120], 'TG': [34.00734209585039, 33.70710613604862, -64], 'TT': [35.576558502141, 7.433901511509349, -154]}
# qqun.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
# print(qqun.score)