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): lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")] brin = ''.join(lineList[1:]) 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 def evaluate(self): ''' Evalue le score d'un individu sur un nombre numb_ajout de points''' traj = Traj3D() numb_ajout = 100 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) #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]/15) 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)