def algoritmo_test(chain, d):
g = chain
theta = []
angles = []
radius = []
for k in range(0, len(g) - 3):
g = chain.copy()
point_a = np.array([g[k][0], g[k][1], g[k][2]])
point_b = np.array([g[k + 1][0], g[k + 1][1], g[k + 1][2]])
point_c = np.array([g[k + 2][0], g[k + 2][1], g[k + 2][2]])
point_d = np.array([g[k + 3][0], g[k + 3][1], g[k + 3][2]])
ag, bg, cg = mv.f_correction(point_c, point_d, d)
point_d[0] = ag
point_d[1] = bg
point_d[2] = cg
ah, bh, ch, dh, eh, fh = mv.b2_correction(point_c, point_b, point_a, d)
point_b[0] = ah
point_b[1] = bh
point_b[2] = ch
point_a[0] = dh
point_a[1] = eh
point_a[2] = fh
ag, bg, cg = mv.f_correction(point_b, point_a, d)
point_a[0] = ag
point_a[1] = bg
point_a[2] = cg
point_d = mv.traslation(point_d, -1 * point_c)
point_b = mv.traslation(point_b, -1 * point_c)
point_a = mv.traslation(point_a, -1 * point_c)
point_c = mv.traslation(point_c, -1 * point_c)
rot_matrix_x = mv.rotation_matrix_x(point_b, 0, center=True)
point_a = np.dot(rot_matrix_x, point_a)
point_b = np.dot(rot_matrix_x, point_b)
point_c = np.dot(rot_matrix_x, point_c)
point_d = np.dot(rot_matrix_x, point_d)
rot_matrix_y = mv.rotation_matrix_y(point_b, 0, center=True)
point_a = np.dot(rot_matrix_y, point_a)
point_b = np.dot(rot_matrix_y, point_b)
point_c = np.dot(rot_matrix_y, point_c)
point_d = np.dot(rot_matrix_y, point_d)
rot_matrix_z = mv.rotation_matrix_z(point_a, 0, center=True)
point_a = np.dot(rot_matrix_z, point_a)
point_b = np.dot(rot_matrix_z, point_b)
point_c = np.dot(rot_matrix_z, point_c)
point_d = np.dot(rot_matrix_z, point_d)
a, b, c = mv.cart2sph(point_d[0], point_d[1], point_d[2])
radius.append(a)
theta.append(b)
angles.append(c)
#angles.append(cart2sph(point_d[0], point_d[1], point_d[2])[2])
return radius, theta, angles
def algoritmo_test(chain, d):
vm = calculate_end_to_end(chain, d, 0, True)
theta = []
angles = []
radius = []
for k in range(0, len(vm) - 3):
g = vm.copy()
point_a = np.array([g[k][0], g[k][1], g[k][2]])
point_b = np.array([g[k + 1][0], g[k + 1][1], g[k + 1][2]])
point_c = np.array([g[k + 2][0], g[k + 2][1], g[k + 2][2]])
point_d = np.array([g[k + 3][0], g[k + 3][1], g[k + 3][2]])
point_d = mv.traslation(point_d, -1 * point_c)
point_b = mv.traslation(point_b, -1 * point_c)
point_a = mv.traslation(point_a, -1 * point_c)
point_c = mv.traslation(point_c, -1 * point_c)
rot_matrix_x = mv.rotation_matrix_x(point_b, 0, center=True)
point_a = np.dot(rot_matrix_x, point_a)
point_b = np.dot(rot_matrix_x, point_b)
point_c = np.dot(rot_matrix_x, point_c)
point_d = np.dot(rot_matrix_x, point_d)
rot_matrix_y = mv.rotation_matrix_y(point_b, 0, center=True)
point_a = np.dot(rot_matrix_y, point_a)
point_b = np.dot(rot_matrix_y, point_b)
point_c = np.dot(rot_matrix_y, point_c)
point_d = np.dot(rot_matrix_y, point_d)
rot_matrix_z = mv.rotation_matrix_z(point_a, 0, center=True)
point_a = np.dot(rot_matrix_z, point_a)
point_b = np.dot(rot_matrix_z, point_b)
point_c = np.dot(rot_matrix_z, point_c)
point_d = np.dot(rot_matrix_z, point_d)
a, b, c = mv.cart2sph(point_d[0], point_d[1], point_d[2])
radius.append(a)
theta.append(b)
angles.append(c)
#angles.append(cart2sph(point_d[0], point_d[1], point_d[2])[2])
return radius, theta, angles
all_data = np.zeros(
(total_data.shape[0], total_data.shape[1] + 6, 3))
all_data[k_i][3:total_data.shape[1] + 3] = copy.deepcopy(
total_data[k_i])
Th = np.random.uniform(0, 1) * np.pi
Ph = np.random.uniform(0, 2 * np.pi, 1)
all_data[k_i][2][
0] = all_data[k_i][3][0] + lo * np.sin(Th) * np.cos(Ph)
all_data[k_i][2][
1] = all_data[k_i][3][1] + lo * np.sin(Th) * np.sin(Ph)
all_data[k_i][2][2] = all_data[k_i][3][2] + lo * np.cos(Th)
temporal_0 = mv.traslation(all_data[k_i][3],
-all_data[k_i][2])
rot_matrix_x = mv.rotation_matrix_x(temporal_0,
0,
center=True)
temporal_1 = np.dot(rot_matrix_x, temporal_0)
rot_matrix_y = mv.rotation_matrix_y(temporal_1,
0,
center=True)
r_phi = np.random.uniform(0, 2 * np.pi, 1)
all_data[k_i][1][0] = lo * np.sin(Tho) * np.cos(r_phi)
all_data[k_i][1][1] = lo * np.sin(Tho) * np.sin(r_phi)
all_data[k_i][1][2] = lo * np.cos(Tho)
all_data[k_i][1] = mv.traslation(
np.dot(
np.linalg.inv(rot_matrix_x),
def same_algorithm(N,M,phi,ee,tol,name,pbc=True):
#N Numero de Cadenas
#M Numero de moleculas
Data = np.zeros((N,M,3))
label = np.ones((N,M))*-1
lo = 1.54
Tho = 1.911
ro = 0.761
Mm = 14.02658
Mol = 6.02214129*10**23
L = ((N*M*Mm/(ro*Mol))**(1/3))*1e8
print(L)
L = float('%.4f'%(L))
rcut = L/10
rcut2 = 1
ratio = math.ceil(L/rcut2)
valores = []
j = 0
#print("rcut",rcut)
print("L:",L)
while (j <= N-1):
print("Cadena: " + str(j))
### Primera Molecula ###
i=0
s = True
Data[j][0][0],Data[j][0][1],Data[j][0][2] = np.random.uniform(0,1)*L,np.random.uniform(0,1)*L,np.random.uniform(0,1)*L
while( Data[j][0][0] >=L or Data[j][0][1]>=L or Data[j][0][2]>=L or Data[j][0][0] <= 0 or Data[j][0][1]<=0 or Data[j][0][2]<=0 or s):
Data[j][0][0],Data[j][0][1],Data[j][0][2] = np.random.uniform(0,1)*L,np.random.uniform(0,1)*L,np.random.uniform(0,1)*L
s = False
x = math.floor(Data[j][0][0]/rcut2)
y = math.floor(Data[j][0][1]/rcut2)
z = math.floor(Data[j][0][2]/rcut2)
for cnt1 in range(-2,3):
for cnt2 in range(-2,3):
for cnt3 in range(-2,3):
x_a=x_b=y_a=y_b=z_a=z_b = False
tmp_x = x + cnt3
tmp_y = y + cnt2
tmp_z = z + cnt1
if tmp_x == ratio:
x_a = True
tmp_x = 0
if tmp_x == ratio+1:
x_a = True
tmp_x = 1
elif tmp_x == -2:
x_b = True
tmp_x = ratio-2
elif tmp_x == -1:
x_b = True
tmp_x = ratio-1
if tmp_y == ratio:
y_a = True
tmp_y = 0
elif tmp_y == ratio+1:
y_a = True
tmp_y = 1
elif tmp_y == -2:
y_b = True
tmp_y = ratio-2
elif tmp_y == -1:
y_b = True
tmp_y = ratio-1
if tmp_z == ratio:
z_a = True
tmp_z = 0
elif tmp_z == ratio+1:
z_a = True
tmp_z = 1
elif tmp_z == -2:
z_b = True
tmp_z = ratio-2
elif tmp_z == -1:
z_b = True
tmp_z = ratio-1
t_label = math.ceil(tmp_z*ratio**2 + tmp_y*ratio + tmp_x)
t_label = np.where(label==t_label)
points_in_space = np.array(Data[t_label])
if x_a == True:
points_in_space[:,0] = points_in_space[:,0] + L
if x_b == True:
points_in_space[:,0] = points_in_space[:,0] - L
if y_a == True:
points_in_space[:,1] = points_in_space[:,1] + L
if y_b == True:
points_in_space[:,1] = points_in_space[:,1] - L
if z_a == True:
points_in_space[:,2] = points_in_space[:,2] + L
if z_b == True:
points_in_space[:,2] = points_in_space[:,2] - L
if np.sum(np.sqrt(np.sum((points_in_space-np.array([Data[j][i][0],Data[j][i][1],Data[j][i][2]]))**2,axis=1))>rcut2) < len(points_in_space):
print(":c")
s = True
label[j,0] = get_label(Data[j][0][0],Data[j][0][1],Data[j][0][2],rcut2,L)
### Segunda Molecula ###
i=1
#print("Segunda Molecula de la cadena: " + str(j))
Th = np.random.uniform(0,1)*np.pi
#Ph = give_me_a_random_number(phi)
Ph = np.random.uniform(0,2*np.pi,1)
Data[j][1][0] = Data[j][0][0] + lo*np.sin(Th)*np.cos(Ph)
Data[j][1][1] = Data[j][0][1] + lo*np.sin(Th)*np.sin(Ph)
Data[j][1][2] = Data[j][0][2] + lo*np.cos(Th)
s = True
while( Data[j][1][0] >=L or Data[j][1][1]>=L or Data[j][1][2]>=L or Data[j][1][0] <= 0 or Data[j][1][1]<=0 or Data[j][1][2]<=0 or s):
#while(s):
Th = np.random.rand(1)[0]*np.pi
ph = give_me_a_random_number(phi)[0]
Data[j][1][0] = Data[j][0][0] + lo*np.sin(Th)*np.cos(Ph)
Data[j][1][1] = Data[j][0][1] + lo*np.sin(Th)*np.sin(Ph)
Data[j][1][2] = Data[j][0][2] + lo*np.cos(Th)
if pbc == True:
if(Data[j][1][0] > L):
Data[j][1][0] = Data[j][1][0] - L
elif(Data[j][1][0] < 0):
Data[j][1][0] = Data[j][1][0] + L
if(Data[j][1][1] > L):
Data[j][1][1] = Data[j][1][1] - L
elif(Data[j][1][1] < 0):
Data[j][1][1] = Data[j][1][1] + L
if(Data[j][1][2] > L):
Data[j][1][2] = Data[j][1][2] - L
elif(Data[j][1][2] < 0):
Data[j][1][2] = Data[j][1][2] + L
s = False
x = math.floor(Data[j][1][0]/rcut2)
y = math.floor(Data[j][1][1]/rcut2)
z = math.floor(Data[j][1][2]/rcut2)
for cnt1 in range(-2,3):
for cnt2 in range(-2,3):
for cnt3 in range(-2,3):
x_a=x_b=y_a=y_b=z_a=z_b = False
tmp_x = x + cnt3
tmp_y = y + cnt2
tmp_z = z + cnt1
if tmp_x == ratio:
x_a = True
tmp_x = 0
if tmp_x == ratio+1:
x_a = True
tmp_x = 1
elif tmp_x == -2:
x_b = True
tmp_x = ratio-2
elif tmp_x == -1:
x_b = True
tmp_x = ratio-1
if tmp_y == ratio:
y_a = True
tmp_y = 0
elif tmp_y == ratio+1:
y_a = True
tmp_y = 1
elif tmp_y == -2:
y_b = True
tmp_y = ratio-2
elif tmp_y == -1:
y_b = True
tmp_y = ratio-1
if tmp_z == ratio:
z_a = True
tmp_z = 0
elif tmp_z == ratio+1:
z_a = True
tmp_z = 1
elif tmp_z == -2:
z_b = True
tmp_z = ratio-2
elif tmp_z == -1:
z_b = True
tmp_z = ratio-1
t_label = math.ceil(tmp_z*ratio**2 + tmp_y*ratio + tmp_x)
t_label = np.where(label==t_label)
points_in_space = np.array(Data[t_label])
if x_a == True:
points_in_space[:,0] = points_in_space[:,0] + L
if x_b == True:
points_in_space[:,0] = points_in_space[:,0] - L
if y_a == True:
points_in_space[:,1] = points_in_space[:,1] + L
if y_b == True:
points_in_space[:,1] = points_in_space[:,1] - L
if z_a == True:
points_in_space[:,2] = points_in_space[:,2] + L
if z_b == True:
points_in_space[:,2] = points_in_space[:,2] - L
if np.sum(np.sqrt(np.sum((points_in_space-np.array([Data[j][i][0],Data[j][i][1],Data[j][i][2]]))**2,axis=1))>rcut2) < len(points_in_space):
print(":c")
s = True
label[j,1] = get_label(Data[j][1][0],Data[j][1][1],Data[j][1][2],rcut2,L)
### Tercera Molecula ###
i=2
#print("Tercera Molecula de la cadena: " + str(j))
temporal_0 = mv.traslation(Data[j][0],-Data[j][1])
rot_matrix_x = mv.rotation_matrix_x(temporal_0,0,center=True)
temporal_1 = np.dot(rot_matrix_x,temporal_0)
rot_matrix_y = mv.rotation_matrix_y(temporal_1,0,center=True)
#r_phi = give_me_a_random_number(phi)[0]
r_phi = np.random.uniform(0,2*np.pi,1)
Data[j][2][0] = lo*np.sin(Tho)*np.cos(r_phi)
Data[j][2][1] = lo*np.sin(Tho)*np.sin(r_phi)
Data[j][2][2] = lo*np.cos(Tho)
Data[j][2] = mv.traslation(np.dot(np.linalg.inv(rot_matrix_x),np.dot(np.linalg.inv(rot_matrix_y),Data[j][2])),Data[j][1])
s = True
while( Data[j][2][0] >=L or Data[j][2][1]>=L or Data[j][2][2]>=L or Data[j][2][0] <= 0 or Data[j][2][1]<=0 or Data[j][2][2]<=0 or s):
r_phi = np.random.uniform(0,2*np.pi,1)
Data[j][2][0] = lo*np.sin(Tho)*np.cos(r_phi)
Data[j][2][1] = lo*np.sin(Tho)*np.sin(r_phi)
Data[j][2][2] = lo*np.cos(Tho)
Data[j][2] = mv.traslation(np.dot(np.linalg.inv(rot_matrix_x),np.dot(np.linalg.inv(rot_matrix_y),Data[j][2])),Data[j][1])
if pbc == True:
if(Data[j][2][0] > L):
Data[j][2][0] = Data[j][2][0] - L
elif(Data[j][2][0] < 0):
Data[j][2][0] = Data[j][2][0] + L
if(Data[j][2][1] > L):
Data[j][2][1] = Data[j][2][1] - L
elif(Data[j][2][1] < 0):
Data[j][2][1] = Data[j][2][1] + L
if(Data[j][2][2] > L):
Data[j][2][2] = Data[j][2][2] - L
elif(Data[j][2][2] < 0):
Data[j][2][2] = Data[j][2][2] + L
s = False
x = math.floor(Data[j][2][0]/rcut2)
y = math.floor(Data[j][2][1]/rcut2)
z = math.floor(Data[j][2][2]/rcut2)
for cnt1 in range(-2,3):
for cnt2 in range(-2,3):
for cnt3 in range(-2,3):
x_a=x_b=y_a=y_b=z_a=z_b = False
tmp_x = x + cnt3
tmp_y = y + cnt2
tmp_z = z + cnt1
if tmp_x == ratio:
x_a = True
tmp_x = 0
if tmp_x == ratio+1:
x_a = True
tmp_x = 1
elif tmp_x == -2:
x_b = True
tmp_x = ratio-2
elif tmp_x == -1:
x_b = True
tmp_x = ratio-1
if tmp_y == ratio:
y_a = True
tmp_y = 0
elif tmp_y == ratio+1:
y_a = True
tmp_y = 1
elif tmp_y == -2:
y_b = True
tmp_y = ratio-2
elif tmp_y == -1:
y_b = True
tmp_y = ratio-1
if tmp_z == ratio:
z_a = True
tmp_z = 0
elif tmp_z == ratio+1:
z_a = True
tmp_z = 1
elif tmp_z == -2:
z_b = True
tmp_z = ratio-2
elif tmp_z == -1:
z_b = True
tmp_z = ratio-1
t_label = math.ceil(tmp_z*ratio**2 + tmp_y*ratio + tmp_x)
t_label = np.where(label==t_label)
points_in_space = np.array(Data[t_label])
if x_a == True:
points_in_space[:,0] = points_in_space[:,0] + L
if x_b == True:
points_in_space[:,0] = points_in_space[:,0] - L
if y_a == True:
points_in_space[:,1] = points_in_space[:,1] + L
if y_b == True:
points_in_space[:,1] = points_in_space[:,1] - L
if z_a == True:
points_in_space[:,2] = points_in_space[:,2] + L
if z_b == True:
points_in_space[:,2] = points_in_space[:,2] - L
if np.sum(np.sqrt(np.sum((points_in_space-np.array([Data[j][i][0],Data[j][i][1],Data[j][i][2]]))**2,axis=1))>rcut2) < len(points_in_space):
print(":c")
s = True
label[j,2] = get_label(Data[j][2][0],Data[j][2][1],Data[j][2][2],rcut2,L)
### Moleculas Restantes ###
i = 3
intentos = 0
angulos_test = []
cadena_coeficiente = []
true_chain = None
while(i <=M-1):
print(str(i)+" Molecula de la cadena: " + str(j))
drop = 1
emn = 1
point_a = copy.deepcopy(Data[j][i-3])
point_b = copy.deepcopy(Data[j][i-2])
point_c = copy.deepcopy(Data[j][i-1])
if point_c[0]-point_b[0] > L/2:
point_b[0] = point_b[0] + L
elif point_c[0]-point_b[0] < -L/2:
point_b[0] = point_b[0] - L
if point_c[1]-point_b[1] > L/2:
point_b[1] = point_b[1] + L
elif point_c[1]-point_b[1] < -L/2:
point_b[1] = point_b[1] - L
if point_c[2]-point_b[2] > L/2:
point_b[2] = point_b[2] + L
elif point_c[2]-point_b[2] < -L/2:
point_b[2] = point_b[2] - L
if point_b[0]-point_a[0] > L/2:
point_a[0] = point_a[0] + L
elif point_b[0]-point_a[0] < -L/2:
point_a[0] = point_a[0] - L
if point_b[1]-point_a[1] > L/2:
point_a[1] = point_a[1] + L
elif point_b[1]-point_a[1] < -L/2:
point_a[1] = point_a[1] - L
if point_b[2]-point_a[2] > L/2:
point_a[2] = point_a[2] + L
elif point_b[2]-point_a[2] < -L/2:
point_a[2] = point_a[2] - L
temporal_0 = mv.traslation(point_b,-point_c)
temporala_0 = mv.traslation(point_a,-point_c)
rot_matrix_x = mv.rotation_matrix_x(temporal_0,0,center=True)
temporal_1 = np.dot(rot_matrix_x,temporal_0)
temporala_1 = np.dot(rot_matrix_x,temporala_0)
rot_matrix_y = mv.rotation_matrix_y(temporal_1,0,center=True)
temporal_2 = np.dot(rot_matrix_y,temporal_1)
temporala_2 = np.dot(rot_matrix_y,temporala_1)
rot_matrix_z = mv.rotation_matrix_z(temporala_2,0,center=True)
r_phi = np.random.uniform(0,2*np.pi,1)[0]
Data[j][i][0] = lo*np.sin(Tho)*np.cos(r_phi)
Data[j][i][1] = lo*np.sin(Tho)*np.sin(r_phi)
Data[j][i][2] = lo*np.cos(Tho)
Data[j][i] = mv.traslation(np.dot(np.linalg.inv(rot_matrix_x),np.dot(np.linalg.inv(rot_matrix_y),np.dot(np.linalg.inv(rot_matrix_z),Data[j][i]))),Data[j][i-1])
s = True
angulos_test.append(r_phi)
while( Data[j][i][0] >=L or Data[j][i][1]>=L or Data[j][i][2]>=L or Data[j][i][0] <= 0 or Data[j][i][1]<=0 or Data[j][i][2]<=0 or s):
temp_10 = []
temp_10_index = []
temp_10_end_to_end = []
temp_angle = []
intentos = intentos + 1
flag = True
temporal_angles = []
temp_final_coord = []
counter = 0
#test_test = np.linspace(0,2*np.pi,50)
for temporal_angles in range(0,50):
r_phi = np.random.uniform(0,2*np.pi,1)[0]
tmp_molecule = [lo*np.sin(Tho)*np.cos(r_phi),
lo*np.sin(Tho)*np.sin(r_phi),
lo*np.cos(Tho)]
tmp_molecule = mv.traslation(np.dot(np.linalg.inv(rot_matrix_x),np.dot(np.linalg.inv(rot_matrix_y),np.dot(np.linalg.inv(rot_matrix_z),tmp_molecule))),Data[j][i-1])
temp_angle.append(r_phi)
if pbc == True:
if tmp_molecule[0] > L:
tmp_molecule[0] = tmp_molecule[0] - L
elif tmp_molecule[0] < 0:
tmp_molecule[0] = tmp_molecule[0] + L
if tmp_molecule[1] > L:
tmp_molecule[1] = tmp_molecule[1] - L
elif tmp_molecule[1] < 0:
tmp_molecule[1] = tmp_molecule[1] + L
if tmp_molecule[2] > L:
tmp_molecule[2] = tmp_molecule[2] - L
elif tmp_molecule[2] < 0:
tmp_molecule[2] = tmp_molecule[2] + L
temp_10.append(tmp_molecule)
Data[j][i][0] = tmp_molecule[0]
Data[j][i][1] = tmp_molecule[1]
Data[j][i][2] = tmp_molecule[2]
angulos_test[-1] = r_phi
if true_chain == None:
bb_w = ((i+1)*ee/M - calculate_end_to_end(Data[j],L,i,False))**2
else:
eec, coord = calculate_end_to_end_optimize(Data[j][i],L,i,true_chain)
bb_w = ((i+1)*ee/M - eec)**2
temp_final_coord.append(coord)
bb_w2 = (scipy.stats.ks_2samp(phi,angulos_test)[1])
temp_10_end_to_end.append(bb_w)
temp_10_index.append(bb_w2)
temp_10_end_to_end = np.array(temp_10_end_to_end)/((i+1)*ee/M)**2
cadena_coeficiente = (1+temp_10_end_to_end)/np.array(temp_10_index)
temp_10_end_to_end = np.ndarray.tolist((1-(1+temp_10_end_to_end)/np.array(temp_10_index))**2)
if true_chain == None:
check = [[x,y,z,r,p] for y,x,z,r,p in sorted(zip(temp_10_end_to_end,temp_10_index,temp_angle,temp_10,cadena_coeficiente))]
else:
check = [[x,y,z,r,p,u] for y,x,z,r,p,u in sorted(zip(temp_10_end_to_end,temp_10_index,temp_angle,temp_10,cadena_coeficiente,temp_final_coord))]
for molecule_index in check:
s = False
Data[j][i][0] = molecule_index[3][0]
Data[j][i][1] = molecule_index[3][1]
Data[j][i][2] = molecule_index[3][2]
x = math.floor(Data[j][i][0]/rcut2)
y = math.floor(Data[j][i][1]/rcut2)
z = math.floor(Data[j][i][2]/rcut2)
for cnt1 in range(-2,3):
for cnt2 in range(-2,3):
for cnt3 in range(-2,3):
x_a=x_b=y_a=y_b=z_a=z_b = False
tmp_x = x + cnt3
tmp_y = y + cnt2
tmp_z = z + cnt1
if tmp_x == ratio:
x_a = True
tmp_x = 0
if tmp_x == ratio+1:
x_a = True
tmp_x = 1
elif tmp_x == -2:
x_b = True
tmp_x = ratio-2
elif tmp_x == -1:
x_b = True
tmp_x = ratio-1
if tmp_y == ratio:
y_a = True
tmp_y = 0
elif tmp_y == ratio+1:
y_a = True
tmp_y = 1
elif tmp_y == -2:
y_b = True
tmp_y = ratio-2
elif tmp_y == -1:
y_b = True
tmp_y = ratio-1
if tmp_z == ratio:
z_a = True
tmp_z = 0
elif tmp_z == ratio+1:
z_a = True
tmp_z = 1
elif tmp_z == -2:
z_b = True
tmp_z = ratio-2
elif tmp_z == -1:
z_b = True
tmp_z = ratio-1
t_label = math.ceil(tmp_z*ratio**2 + tmp_y*ratio + tmp_x)
t_label = np.where(label==t_label)
points_in_space = np.array(Data[t_label])
if x_a == True:
points_in_space[:,0] = points_in_space[:,0] + L
if x_b == True:
points_in_space[:,0] = points_in_space[:,0] - L
if y_a == True:
points_in_space[:,1] = points_in_space[:,1] + L
if y_b == True:
points_in_space[:,1] = points_in_space[:,1] - L
if z_a == True:
points_in_space[:,2] = points_in_space[:,2] + L
if z_b == True:
points_in_space[:,2] = points_in_space[:,2] - L
v = np.sqrt(np.sum((points_in_space-np.array([Data[j][i][0],Data[j][i][1],Data[j][i][2]]))**2,axis=1))
#print(points_in_space)
#print(v)
if np.sum(np.sqrt(np.sum((points_in_space-np.array([Data[j][i][0],Data[j][i][1],Data[j][i][2]]))**2,axis=1))>rcut2) < len(points_in_space):
s = True
if s == False:
valores.append(molecule_index[4])
break
intentos = intentos + 1
if intentos > 100:
emn = 0
drop = drop + np.random.randint(1,99)
break
if emn == 1:
angulos_test[(i-3)] = molecule_index[2]
label[j,i] = get_label(Data[j][i][0],Data[j][i][1],Data[j][i][2],rcut2,L)
i = i + 1
if true_chain == None:
true_chain = calculate_end_to_end(Data[j],L,i,True)
else:
true_chain.append(molecule_index[-1])
if drop > 0:
drop = drop - 1
if emn == 0:
emn = 1
i = i - drop
angulos_test = angulos_test[0:(i-3)]
if true_chain != None:
true_chain = true_chain[0:i]
if i < 3:
break
if drop > 100:
drop = 0
break
intentos = 0
if intentos < 10:
target = calculate_end_to_end(Data[j],L)
np.save("restart_"+name+".npy",Data)
print(target)
j= j + 1
return(Data,label)