diff --git a/__pycache__/RotTable.cpython-36.pyc b/__pycache__/RotTable.cpython-36.pyc index 7a6158dd6374a43aa0874b27bdbf65bcfb4208a1..a8064bb45dbaad46db289f9e730b7dd816423ae4 100644 Binary files a/__pycache__/RotTable.cpython-36.pyc and b/__pycache__/RotTable.cpython-36.pyc differ diff --git a/__pycache__/Traj3D.cpython-36.pyc b/__pycache__/Traj3D.cpython-36.pyc index 31651032f232ae34320d1f923ad5b5548331aa50..b5c1da4e7f16d56be5828446b2f8423d03027c1c 100644 Binary files a/__pycache__/Traj3D.cpython-36.pyc and b/__pycache__/Traj3D.cpython-36.pyc differ diff --git a/individu.py b/individu.py index 0b14b4cf7baf06b66c3374a6bae2f16c6fc795ff..3c652c85b782d491cabfc214baefcdef6f3d34eb 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):