From 59c403af85e61e58fa930613f9e76ab077e7e31e Mon Sep 17 00:00:00 2001
From: Kappes Marques Rodrigo <rodrigo.kappes@student-cs.fr>
Date: Wed, 29 Jan 2020 09:23:14 +0100
Subject: [PATCH] added everything
---
__pycache__/RotTable.cpython-37.pyc | Bin 2571 -> 2576 bytes
__pycache__/Traj3D.cpython-37.pyc | Bin 1925 -> 1930 bytes
algogenetique.py | 13 ++++++------
individu.py | 30 ++++++++++++++++++----------
population.py | 9 ++++-----
5 files changed, 31 insertions(+), 21 deletions(-)
diff --git a/__pycache__/RotTable.cpython-37.pyc b/__pycache__/RotTable.cpython-37.pyc
index eda825aff2fc67047d02eda36807123f6b5899fc..6611c6bdf67c60524cc9c963f7a2261ce632ed52 100644
GIT binary patch
delta 60
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QWifgAW%-*QuxPUa03~=6{{R30
delta 55
zcmbOr(k;T}#LLUYz`(#TbJ|9(9V~K=$yPC;#i>QbG2V#<1*yd`E~&-YCHVz0Azr$v
LWt*R}XtM$UwH^_O
diff --git a/__pycache__/Traj3D.cpython-37.pyc b/__pycache__/Traj3D.cpython-37.pyc
index 27f1de9630c467c4d2341a5f33c68535c5d6a139..82a390bdf94f09f504f253f023b0405e31d60754 100644
GIT binary patch
delta 35
rcmZqW@8aij;^pOHU|?W)K4&9WH6x?T<Tge*mc0D3{LPCQAF%=emN5z0
delta 30
lcmeC;Z{_E5;^pOHU|?X_nYodxnvv0davP)E=9P>OSpj8c2eJSF
diff --git a/algogenetique.py b/algogenetique.py
index 8a1874e..1be4716 100644
--- a/algogenetique.py
+++ b/algogenetique.py
@@ -12,12 +12,10 @@ import matplotlib.pyplot as plt
def main(N,tmax,pmutation, proportion,brin="plasmid_8k.fasta"):
- '''lineList = [line.rstrip('\n') for line in open(brin)]
- brin = ''.join(lineList[1:])'''
L=[]
People=Population(N)
for i in range(tmax):
- print(i)
+ #print(i)
max=0
best=None
People.reproduction(p = proportion, proba_mutation= pmutation)
@@ -26,13 +24,16 @@ def main(N,tmax,pmutation, proportion,brin="plasmid_8k.fasta"):
best=individu
max=individu.score
L.append(max)
+ print(i,":",max)
plt.plot([i for i in range(tmax)], L)
plt.show()
- return(best)
+ return(best, People)
-main(100,100,0,50)
-
+best, People = main(60,100,0.01,20)
+traj = Traj3D()
+traj.compute(best.brin,best.table)
+traj.draw("plot")
diff --git a/individu.py b/individu.py
index 2419381..6457428 100644
--- a/individu.py
+++ b/individu.py
@@ -2,7 +2,7 @@ from RotTable import RotTable
from Traj3D import Traj3D
import numpy as np
from math import sqrt, inf
-from random import random
+from random import random, randrange
P1 = 0.015
@@ -10,17 +10,20 @@ class Individu():
def __init__(self, table):
self.table = table
- self.score = self.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
+ lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")]
+ self.brin = ''.join(lineList[1:])
+ #self.brin = "AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA"
+ self.score = self.evaluate()
- def evaluate(self, brin):
+ def evaluate(self):
traj = Traj3D()
numb_ajout = 3
- fisrt_seq = brin[0:numb_ajout]
- last_seq = brin[-numb_ajout:]
+ fisrt_seq = self.brin[0:numb_ajout]
+ last_seq = self.brin[-numb_ajout:]
- traj.compute(last_seq + brin + fisrt_seq, self.table)
+ traj.compute(last_seq + self.brin + fisrt_seq, self.table)
traj_array = np.array(traj.getTraj())
list_distance = []
@@ -44,10 +47,17 @@ class Individu():
def mutation(self, proba = P1):
table_rotations = self.table.rot_table
- for doublet in table_rotations :
- for coord in range(3):
- tir = random()
- if tir < proba :
+ number_of_mutations = 5
+ for i in range(0,number_of_mutations):
+ tir = random()
+ if tir < proba :
+ doubletNumber = randrange(0,8)
+ counter = 0
+ for doublet in table_rotations:
+ if counter==doubletNumber:
+ break
+ counter+=1
+ 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 :
diff --git a/population.py b/population.py
index 828caac..6e2657b 100644
--- a/population.py
+++ b/population.py
@@ -15,8 +15,7 @@ class Population:
self.n = len(liste_individus)
self.indiv = liste_individus
for i in range(0,self.n):
- self.indiv[i].evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
-
+ self.indiv[i].evaluate()
return self
def selection_p_best(self,p=None):
@@ -68,7 +67,7 @@ class Population:
meilleur = self.indiv[0]
for individu in self.indiv :
if meilleur.score < individu.score:
- print("meilleur, individu: ", meilleur.score, individu.score)
+ #print("meilleur, individu: ", meilleur.score, individu.score)
meilleur = individu
newself = [meilleur]
vu=set()
@@ -168,7 +167,7 @@ class Population:
couple_enfant = enfant(x,y)
for child in couple_enfant :
child.mutation(proba_mutation)
- child.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
+ child.evaluate()
newself.append(couple_enfant[0])
newself.append(couple_enfant[1])
self = self.modifier_population(newself)
@@ -184,7 +183,7 @@ def test():
popu = Population(4)
print("\n POPULATION INITIALE \n")
for individu in popu.indiv :
- individu.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
+ individu.evaluate()
afficher(popu)
popu.reproduction(selection = popu.selection_duel)
print("\n REPRODUCTION \n")
--
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