From 7ef86a5484ed6f87172feabf98c0ef48ef8017ba Mon Sep 17 00:00:00 2001
From: Gauthier Roy <gauthierroy83@gmail.com>
Date: Tue, 28 Jan 2020 16:54:49 +0100
Subject: [PATCH] new fitness function
---
__pycache__/RotTable.cpython-36.pyc | Bin 2085 -> 2132 bytes
__pycache__/Traj3D.cpython-36.pyc | Bin 1976 -> 1976 bytes
individu.py | 32 ++++++++++++++++++----------
3 files changed, 21 insertions(+), 11 deletions(-)
diff --git a/__pycache__/RotTable.cpython-36.pyc b/__pycache__/RotTable.cpython-36.pyc
index 7a6158dd6374a43aa0874b27bdbf65bcfb4208a1..a8064bb45dbaad46db289f9e730b7dd816423ae4 100644
GIT binary patch
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diff --git a/__pycache__/Traj3D.cpython-36.pyc b/__pycache__/Traj3D.cpython-36.pyc
index 31651032f232ae34320d1f923ad5b5548331aa50..b5c1da4e7f16d56be5828446b2f8423d03027c1c 100644
GIT binary patch
delta 54
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delta 54
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diff --git a/individu.py b/individu.py
index 0b14b4c..3c652c8 100644
--- a/individu.py
+++ b/individu.py
@@ -1,7 +1,7 @@
from RotTable import RotTable
from Traj3D import *
import numpy as np
-from math import sqrt
+from math import sqrt, inf
class Individu():
@@ -12,20 +12,30 @@ class Individu():
def evaluate(self, brin):
traj = Traj3D()
- fisrt_nuc = brin[0]
- last_nu = brin[-1]
+ numb_ajout = 3
- traj.compute(brin + fisrt_nuc, self.table)
+ fisrt_seq = brin[0:numb_ajout]
+ last_seq = brin[-numb_ajout:]
+
+ traj.compute(last_seq + brin + fisrt_seq, self.table)
traj_array = np.array(traj.getTraj())
- first_nuc_coordonate = traj_array[0, 0:3]
- last_nuc_coordonate = traj_array[-2, 0:3]
+ list_distance = []
+
+ for i in range(numb_ajout):
+ first_nuc_coordonate = traj_array[numb_ajout+i, 0:3]
+ first_nuc_coordonate_compute = traj_array[-(numb_ajout-i), 0:3]
+
+ last_nuc_coordonate = traj_array[-(2*numb_ajout-i), 0:3]
+ last_nuc_coordonate_compute = traj_array[i, 0:3]
+
+ distance_first_nuc = np.linalg.norm(first_nuc_coordonate - first_nuc_coordonate_compute, ord=2)
+ distance_last_nuc = np.linalg.norm(last_nuc_coordonate - last_nuc_coordonate_compute, ord=2)
+
+ list_distance += [distance_first_nuc, distance_last_nuc]
+
- test = np.linalg.norm(first_nuc_coordonate - last_nuc_coordonate, ord=2)
- distance = sqrt(sum((first_nuc_coordonate - last_nuc_coordonate) ** 2))
- diff_ideal_distance = abs(3.38 - distance)
- diff_ideal_distance_2 = abs(3.38 - test)
- self.score = (1/(diff_ideal_distance ), 1/diff_ideal_distance_2)
+ self.score = 1/max(list_distance)
def mutation(self):
--
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