From 69e8a061d6fd93996d67f8b97e2c0e9d1e93f60a Mon Sep 17 00:00:00 2001
From: Carlos Santos Garcia <carlos.santos@student-cs.fr>
Date: Wed, 29 Jan 2020 09:39:45 +0100
Subject: [PATCH] =?UTF-8?q?minimiser=20distance,=20histogrammes=20et=20bri?=
=?UTF-8?q?n=20affich=C3=A9?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit
---
__pycache__/RotTable.cpython-37.pyc | Bin 2556 -> 2618 bytes
__pycache__/Traj3D.cpython-37.pyc | Bin 1910 -> 1972 bytes
__pycache__/individu.cpython-37.pyc | Bin 1915 -> 1964 bytes
algogenetique.py | 49 +++++++++++++++++++++-------
individu.py | 4 +--
population.py | 8 +++--
6 files changed, 45 insertions(+), 16 deletions(-)
diff --git a/__pycache__/RotTable.cpython-37.pyc b/__pycache__/RotTable.cpython-37.pyc
index 488d94e3495eb14f5e5656ee066c85187063795a..20d277d55079d7a6401199aa6d99042a10aacd32 100644
GIT binary patch
delta 128
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delta 66
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Ti=U%zZenpsYSCtOR$*2EelQc$
diff --git a/__pycache__/Traj3D.cpython-37.pyc b/__pycache__/Traj3D.cpython-37.pyc
index bb19acf2cb441bd950ad0bafe725b66e924b457a..3051667333c64564621cb2fe405f2b8ac037b6bd 100644
GIT binary patch
delta 128
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delta 66
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diff --git a/__pycache__/individu.cpython-37.pyc b/__pycache__/individu.cpython-37.pyc
index 421ada9911f9aceeb1a109b57518c98bb35bfd74..98e1fc46b75b89e6b1481052c1f6d4bf92a9d04c 100644
GIT binary patch
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delta 172
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diff --git a/algogenetique.py b/algogenetique.py
index a2c977b..7726e23 100644
--- a/algogenetique.py
+++ b/algogenetique.py
@@ -8,32 +8,59 @@ import croisement
from Traj3D import *
from random import random
import matplotlib.pyplot as plt
+import time
+# Debut du decompte du temps
+start_time = time.time()
-def main(N,tmax,pmutation, proportion,brin="plasmid_8k.fasta"):
- '''lineList = [line.rstrip('\n') for line in open(brin)]
- brin = ''.join(lineList[1:])'''
+
+def main(N,tmax,pmutation, proportion):
L=[]
+ lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")]
+ brin = ''.join(lineList[1:])
People=Population(N)
+ S1=[]
+ for individu in People.indiv:
+ individu.evaluate(brin)
+ S1.append(int(individu.score))
+ maximum=int(max(S1))
for i in range(tmax):
print(i)
- max=0
- best=None
+ mini=People.indiv[0].score
+ best=People.indiv[0]
People.reproduction(p = proportion, proba_mutation= pmutation)
for individu in People.indiv:
- if individu.score>max:
+ if individu.score<mini:
best=individu
- max=individu.score
- L.append(max)
+ mini=individu.score
+ L.append(mini)
+ 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')
+
+ S2=[individu.score for individu in People.indiv]
+ print("Score final: ",best.score)
+
+
+ plt.subplot(224)
+ plt.hist(S2, range = (0,maximum+10), bins = 20, color = 'blue')
plt.show()
- return(best,People)
+
+ return(best,People)
-best,People = main(100,100,0.01,50)
+lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")]
+brin = ''.join(lineList[1:])
+best,People = main(10,10,0.01,5)
test = Traj3D()
-test.compute("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA", best.table)
+test.compute(brin, best.table)
test.draw("first_plot")
+
+# Affichage du temps d execution
+print("Temps d'execution : %s secondes " % (time.time() - start_time))
diff --git a/individu.py b/individu.py
index 2419381..20958d3 100644
--- a/individu.py
+++ b/individu.py
@@ -37,9 +37,9 @@ class Individu():
list_distance += [distance_first_nuc, distance_last_nuc]
- self.score = 1/max(list_distance)
+ self.score = max(list_distance)
- return 1/max(list_distance)
+ return max(list_distance)
def mutation(self, proba = P1):
diff --git a/population.py b/population.py
index 828caac..104f66b 100644
--- a/population.py
+++ b/population.py
@@ -67,7 +67,7 @@ class Population:
p = (self.n)//2
meilleur = self.indiv[0]
for individu in self.indiv :
- if meilleur.score < individu.score:
+ if meilleur.score > individu.score:
print("meilleur, individu: ", meilleur.score, individu.score)
meilleur = individu
newself = [meilleur]
@@ -83,7 +83,7 @@ class Population:
x=self.indiv[m]
y=self.indiv[t]
- if x.score>=y.score:
+ if x.score<y.score:
newself.append(x)
else:
newself.append(y)
@@ -167,8 +167,10 @@ class Population:
y=copy.deepcopy(newself[t])
couple_enfant = enfant(x,y)
for child in couple_enfant :
+ lineList = [line.rstrip('\n') for line in open("plasmid_8k.fasta")]
+ brin = ''.join(lineList[1:])
child.mutation(proba_mutation)
- child.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
+ child.evaluate(brin)
newself.append(couple_enfant[0])
newself.append(couple_enfant[1])
self = self.modifier_population(newself)
--
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