Merge branch 'Chloe2'

RotTable.py

@@ -63,3 +63,4 @@ class RotTable:
 table1 = RotTable()
 print(table1.orta())
 
+print(table1.rot_table["AA"])

individu.py

@@ -2,6 +2,9 @@ from RotTable import RotTable
 from Traj3D import *
 import numpy as np
 from math import sqrt
+from random import random
+
+P1 = 0.015
 
 class Individu():
 
@@ -28,13 +31,24 @@ class Individu():
         diff_angle = sum(abs(rot_computed - rot_traj))
 
         self.score = 1/(distance + diff_angle)
-        
-    
-    def mutation(self):
-        mutation = 0
-        return mutation
-
-table = RotTable()
-test = Individu(table)
-test.evaluate("AAAGGATCTTCTTGAGATCCTTTTTTTCTGCGCGTAATCTGCTGCCAGTAAACGAAAAAACCGCCTGGGGAGGCGGTTTAGTCGAA")
-print(test.score)
+
+
+    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 :
+                    print("mutation", doublet, coord)
+                    print("table", table_rotations[doublet][coord])
+                    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])
+                    print("table", 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)

selection_par_rang.py

+from random import random
+
+def creer_population(self, liste_individus):
+    self.n = len(liste_individus)
+    self.indiv = set(liste_individus)
+    return self
+
+def selection_par_rang(self, p = n//2):
+    set_individus = self.indiv
+    n = self.n
+
+    def partitionner(tableau,debut,fin):
+        echanger(tableau,debut,random.randint(debut,fin-1)) 
+        partition=debut
+        for i in range(debut+1,fin):
+            if tableau[i].score<tableau[debut].score: 
+                partition+=1 
+                echanger(tableau,i,partition) 
+        echanger(tableau,debut,partition) 
+        return partition
+
+    def tri_rapide_aux(tableau,debut,fin):
+        if debut < fin-1:
+            positionPivot=partitionner(tableau,debut,fin)
+          tri_rapide_aux(tableau,debut,positionPivot)
+          tri_rapide_aux(tableau,positionPivot+1,fin)
+    
+    def tri_rapide(tableau):
+        tri_rapide_aux(tableau,0,len(tableau))
+
+    liste = list(set_individus)
+    tri_rapide(liste)
+    individus_selectionnes = []
+
+    for _ in range(p):
+        curseur = random()*n*(n+1)/2
+        j = 1
+        while j*(j+1)/2 < curseur :
+            j+=1 
+        #on doit prendre l'individu avec le jème score 
+        individus_selectionnes.append(liste[j])
+    self = creer_population(self, liste_individus)
+
+
+    
\ No newline at end of file