diff --git a/__pycache__/RotTable.cpython-37.pyc b/__pycache__/RotTable.cpython-37.pyc
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diff --git a/__pycache__/Traj3D.cpython-37.pyc b/__pycache__/Traj3D.cpython-37.pyc
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diff --git a/__pycache__/croisement.cpython-37.pyc b/__pycache__/croisement.cpython-37.pyc
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diff --git a/__pycache__/individu.cpython-37.pyc b/__pycache__/individu.cpython-37.pyc
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diff --git a/__pycache__/population.cpython-37.pyc b/__pycache__/population.cpython-37.pyc
index 037163fdebd2a013e0b24fa10c0ea6f91cff2c10..a2d00a0f413706a094887ce7f0dfe4f1e70ccd5f 100644
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diff --git a/algogenetique.py b/algogenetique.py
index ad4ca277301d88d9a51f433b100f054a692e382e..29f0985ce8bcda14b45a1f1a1adc40ccffaa3c52 100644
--- a/algogenetique.py
+++ b/algogenetique.py
@@ -4,79 +4,67 @@ import numpy
import RotTable
from individu import Individu
from population import Population, afficher
-from croisement import *
+import croisement
from Traj3D import *
from random import random
import matplotlib.pyplot as plt
import time
-from copy import deepcopy
-def main(N,tmax,pmutation, proportion, indice_selection, population_initiale, enfant = croisement_un_point):
+# Debut du decompte du temps
+start_time = time.time()
-
+
+def main(N,tmax,pmutation, proportion):
+
+ L=[]
lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")]
brin = ''.join(lineList[1:])
- People=deepcopy(population_initiale)
- # S1=[]
+ People=Population(N)
+ S1=[]
for individu in People.indiv:
individu.evaluate()
- # S1.append(int(individu.score))
- # maximum=int(max(S1))
- mini=People.indiv[0].score
- for individu in People.indiv:
- if individu.score<mini:
- mini=individu.score
- # L=[mini]
+ S1.append(int(individu.score))
+ maximum=int(max(S1))
for i in range(tmax):
- print(i)
- People.reproduction(p = proportion, proba_mutation= pmutation, selection = indice_selection, enfant = enfant)
mini=People.indiv[0].score
best=People.indiv[0]
+ People.reproduction(p = proportion, proba_mutation= pmutation)
for individu in People.indiv:
if individu.score<mini:
best=individu
mini=individu.score
- # S2=[individu.score for individu in People.indiv]
- # avg = sum(S2)/len(S2)
- # L.append(mini)
+ S2=[individu.score for individu in People.indiv]
+ avg = sum(S2)/len(S2)
+ L.append(mini)
+ print(i,"avg:",avg,"best score:", mini)
- # plt.subplot(221)
- # liste_selections = ["selection_p_best", "selection_duel_pondere", "selection_duel", "selection_par_rang", "selection_proportionnelle"]
- # plt.plot([j for j in range(len(L))], L, label = liste_selections[indice_selection])
+ plt.subplot(221)
+ plt.plot([i for i in range(tmax)], L)
- # plt.subplot(223)
- # plt.hist(S1, range = (0, maximum+10), bins = 20, color = 'red')
+ plt.subplot(223)
+ plt.hist(S1, range = (0, maximum+10), bins = 20, color = 'red')
S2=[individu.score for individu in People.indiv]
print("Score final: ",best.score)
+ print("Distance finale: ", best.distance)
print("Avg:", sum(S2)/len(S2))
- print("Distance final: ",best.distance)
-
- # plt.subplot(224)
- # plt.hist(S2, range = (0,maximum+10), bins = 20, color = 'blue')
- # plt.show()
+ plt.subplot(224)
+ plt.hist(S2, range = (0,maximum+10), bins = 20, color = 'blue')
+ plt.show()
return(best,People)
lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")]
brin = ''.join(lineList[1:])
-best,People = main(100,10,0.05,10)
+best,People = main(60,60,0.05,30)
test = Traj3D()
test.compute(brin, best.table)
test.draw("first_plot")
-# [['selection_p_best' '22.637820959091187' '116.30569654472626']
-# ['selection_duel_pondere' '22.636890172958374' '46.6242321955727']
-# ['selection_duel' '22.21168804168701' '234.7640748029787']
-# ['selection_par_rang' '22.180259227752686' '190.0163752068961']
-# ['selection_proportionnelle' '22.329176902770996' '315.7030719673908']]
-# [['selection_p_best' '22.775274991989136' '106.89365704155766']
-# ['selection_duel_pondere' '22.716803073883057' '284.11538487097084']
-# ['selection_duel' '23.19036889076233' '155.83887357033393']
-# ['selection_par_rang' '22.752396821975708' '118.6068497149259']
-# ['selection_proportionnelle' '22.71982979774475' '151.80114914793427']]
\ No newline at end of file
+# Affichage du temps d execution
+print("Temps d'execution : %s secondes " % (time.time() - start_time))
diff --git a/first_plot.png b/first_plot.png
index 0e536fb530ea40bc82a9395940755ad27a030609..f9294f16e9e6dc29674f763436bc6927a5b6bbb7 100644
Binary files a/first_plot.png and b/first_plot.png differ
diff --git a/individu.py b/individu.py
index 253b874252ed3088a57d76fc87a96fa992a3f178..00766d2f75786c3f5416aab70898d8307b5ead4d 100644
--- a/individu.py
+++ b/individu.py
@@ -9,8 +9,6 @@ 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:])
@@ -24,7 +22,7 @@ class Individu():
traj = Traj3D()
- numb_ajout = 100
+ numb_ajout = 10
fisrt_seq = self.brin[0:numb_ajout]
last_seq = self.brin[-numb_ajout:]
@@ -99,7 +97,7 @@ class Individu():
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)
+ 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]: