def hybrid_tech_c(coef, set, sol): #2.2
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
sol['tip_cell'] = []
for nom in range(0, n_sp): #dicek setiap element
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
dirr = movement_dir(coef, set, sol, xb, yb, nom) #2.2.1 ok
'''Making list of prob'''
list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = set_list_prob(
dirr) #2.2.(1)
'''The Movement'''
sol, tipp = movement(sol, nom, xb, yb, list_prob_0, list_prob_1,
list_prob_2, list_prob_3, list_prob_4) #2.2.(2)
'''Checking if X4 is absorbed'''
if not tipp == 'stay':
sol, abs = absorbed_f(sol, set, nom)
else:
abs = 'no'
if abs == 'no':
sol['tip_cell'].append(sol['matrix_tip'][nom][-1])
return sol
def hybrid_tech(coef, set, sol, c_o): #2.23
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n']) #to save the value of 'n' at time step k (we are calculating at time step k+1)
sol['backward_list'] = [] #backward list
for nom in range(0,n_sp): #dicek setiap tip
if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
dirr, probb = movement_dir(coef, set, sol, xb, yb, c_o) #2.2.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
if not nom in sol['sp_stop']:
sol['sp_stop'].append(nom)
sol['cause'][nom] = 'no space'
sol['n'][xb,yb] = 0
sol['stalk'][xb,yb] = 1
else:
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
'''The Movement And Tip-Tip Anastomosis Checking'''
branch = False
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(2)
return sol
def hybrid_tech(coef, set, sol, c_o): #2.23
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(
sol['n']
) #to save the value of 'n' at time step k (we are calculating at time step k+1)
sol['backward_list'] = [] #backward list
for nom in range(0, n_sp): #dicek setiap tip
if not nom in sol[
'sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
dirr, probb = movement_dir(
coef, set, sol, xb, yb,
c_o) #2.2.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[
4] == 0: #checking if there is space for tip cell to move
if not nom in sol['sp_stop']:
sol['sp_stop'].append(nom)
sol['cause'][nom] = 'no space'
sol['n'][xb, yb] = 0
sol['stalk'][xb, yb] = 1
else:
'''Making list of prob'''
list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = set_list_prob(
dirr) #2.2.(1)
'''The Movement And Tip-Tip Anastomosis Checking'''
branch = False
sol, tipp, list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = movement(
sol, set, nom, xb, yb, list_prob_0, list_prob_1,
list_prob_2, list_prob_3, list_prob_4, branch) #2.2.(2)
return sol
def hybrid_tech_c(coef, set, sol): #2.2
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
sol['tip_cell'] = []
for nom in range(0,n_sp): #dicek setiap element
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
dirr= movement_dir(coef, set, sol, xb, yb, nom) #2.2.1 ok
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
'''The Movement'''
sol,tipp = movement(sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4) #2.2.(2)
'''Checking if X4 is absorbed'''
if not tipp == 'stay':
sol, abs = absorbed_f(sol,set,nom)
else:
abs = 'no'
if abs == 'no':
sol['tip_cell'].append(sol['matrix_tip'][nom][-1])
return sol
def hybrid_tech_c(coef, set, sol): #2.2
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n'])
sol['loc_anas_tt'] = []
sol['loc_anas_tb'] = []
for nom in range(0,n_sp): #dicek setiap tip
if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
'''Proliferation
if sol['life_mit'][nom] >= coef['T_mitosis']:
sol['life_mit'][nom] = 0
if sol['list_tip_movement'] == 'left':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0] - 2
ys = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'right':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0] + 2
ys = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'down':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0]
ys = sol['matrix_tip'][nom][-1][1] -2
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'up':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0]
ys = sol['matrix_tip'][nom][-1][1] + 2
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
Proliferation'''
dirr= movement_dir(coef, set, sol, xb, yb, nom) #2.2.1 ok
'''Checking The movement if another tip meet nom'''
movi = False
if [xb,yb] in sol['PP']:
movi = True
if sol['pp'][(xb,yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb,yb)] == 'right':
dirr[1] == 0
elif sol['pp'][(xb,yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb,yb)] == 'down':
dirr[4] == 0
''' With No backward movement
if sol['list_tip_movement'][nom] == 'left':
dirr[2] == 0
if sol['pp'][(xb,yb)] == 'right':
dirr[1] == 0
elif sol['pp'][(xb,yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb,yb)] == 'down':
dirr[4] == 0
elif sol['list_tip_movement'][nom] == 'right':
dirr[1] == 0
if sol['pp'][(xb,yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb,yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb,yb)] == 'down':
dirr[4] == 0
elif sol['list_tip_movement'][nom] == 'down':
dirr[4] == 0
if sol['pp'][(xb,yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb,yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb,yb)] == 'right':
dirr[1] == 0
elif sol['list_tip_movement'][nom] == 'up':
dirr[3] == 0
if sol['pp'][(xb,yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb,yb)] == 'down':
dirr[4] == 0
elif sol['pp'][(xb,yb)] == 'right':
dirr[1] == 0
'''
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #if no space
sol['sp_stop'].append(nom)
sol['tip_cell'].remove([xb,yb])
else:
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
'''The Movement'''
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4) #2.2.(2)
'''2.1 Branching Decision'''
PP = 'test'
if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA1'
if movi == True:
sol['PP'].remove([xb,yb])
sol['pp'].pop((xb,yb))
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA2'
#print sol['life_time_tip'][nom]
if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA3'
'''Probability of Branching using life time'''
list_prob = range(1,11)#prob_by_c(sol,xb,yb) #2.2.(4)
tes = randint(1,10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #BRANCHING!
#print 'YAYAYA4'
sol['life_time_tip'][nom] = 0
sol['life_mit'][nom] += set['dt']
sol['matrix_tip'].append([(xb,yb)])
sol['life_time_tip'].append(0)
sol['life_mit'].append(0)
sol['list_tip_movement'].append('start')
tipp = 'stay'
'''The Movement from branching'''
while tipp == 'stay':
sol, tipp = movement_branch(tipp,sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4) #2.2.(5)
return sol, n_o
def system_2d(coef, set, sol, n_o): #2.3
c_o = numpy.copy(sol['c']) #to save values at time step k (we are calculating at time step k+1)
f_o = numpy.copy(sol['f']) #to save values at time step k (we are calculating at time step k+1)
'''Calculate Velocity from tip cell's Vel'''
sol['Vel_x'] = numpy.zeros((set['Nx']+1,set['Ny']+1))
sol['Vel_y'] = numpy.zeros((set['Nx']+1,set['Ny']+1))
for y in range(1,set['Ny'],2):
for x in range(1,set['Nx'],2):
if n_o[x,y] == 1:
dirr, probb = movement_dir(coef, set, sol, x, y)
sol['Vel_x'][x,y] = -probb[1]+probb[2]
sol['Vel_y'][x,y] = -probb[3]+probb[4]
'''Solve c & f at sub lattice'''
for y in range(0,set['Ny']+1,2):
for x in range(0,set['Nx']+1,2):
c_star = sol['c_o'][x,y] - c_o[x,y]
gam_f = sol['c_o'][x,y]*c_star/((1/(coef['Gama']))+c_star)
move_c = 0
move_f = 0
if y == 0:
if x == 0:
mean_n = n_o[x+1,y+1]/4
elif x == set['Nx']:
mean_n = n_o[x-1,y+1]/4
else:
mean_n = (n_o[x-1,y+1] + n_o[x+1,y+1])/4
move_c = 0#coef['Alp_c']*set['dt']*(vijx_p*(c_o[x,y]-c_o[x-2,y])-vijx_n*(c_o[x+2,y]-c_o[x,y])+vijy_p*(0)-vijy_n*(c_o[x,y+2]-c_o[x,y]))/(set['h']**2)
elif y == set['Ny']:
if x == 0:
mean_n = n_o[x+1,y-1]/4
elif x == set['Nx']:
mean_n = n_o[x-1,y-1]/4
else:
mean_n = (n_o[x-1,y-1] + n_o[x+1,y-1])/4
move_c = 0#coef['Alp_c']*set['dt']*(vijx_p*(c_o[x,y]-c_o[x-2,y]coef['Gama'])-vijx_n*(c_o[x+2,y]-c_o[x,y])+vijy_p*(c_o[x,y]-c_o[x,y-2])-vijy_n*(0))/(set['h']**2)
else:
if x == 0:
mean_n = (n_o[x+1,y-1] + n_o[x+1,y+1])/2
move_c = 0#coef['Alp_c']*set['dt']*(vijx_p*(0)-vijx_n*(c_o[x+2,y]-c_o[x,y])+vijy_p*(c_o[x,y]-c_o[x,y-2])-vijy_n*(c_o[x,y+2]-c_o[x,y]))/(set['h']**2)
elif x == set['Nx']:
mean_n = (n_o[x-1,y-1] + n_o[x-1,y+1])/4
move_c = 0#coef['Alp_c']*set['dt']*(vijx_p*(c_o[x,y]-c_o[x-2,y])-vijx_n*(0)+vijy_p*(c_o[x,y]-c_o[x,y-2])-vijy_n*(c_o[x,y+2]-c_o[x,y]))/(set['h']**2)
else:
mean_n = (n_o[x+1,y+1] + n_o[x-1,y+1] + n_o[x+1,y-1] + n_o[x-1,y-1])/4
vel_x_mean = (sol['Vel_x'][x+1,y+1] + sol['Vel_x'][x-1,y+1] + sol['Vel_x'][x+1,y-1] + sol['Vel_x'][x-1,y-1])/4
vel_y_mean = (sol['Vel_y'][x+1,y+1] + sol['Vel_y'][x-1,y+1] + sol['Vel_y'][x+1,y-1] + sol['Vel_y'][x-1,y-1])/4
vijx_p = max(0,vel_x_mean)
vijx_n = max(0,-vel_x_mean)
vijy_p = max(0,vel_y_mean)
vijy_n = max(0,-vel_y_mean)
# if vel_x_mean != 0 or vel_y_mean != 0:
# print vel_x_mean, vel_y_mean
#Method: not from P1,P2,P3,...
# vijx_p, vijx_n, vijy_p, vijy_n = velocity_max(coef,set,sol,n_o,c_o,f_o,x,y)
move_c = coef['Alp_c']*set['dt']*(vijx_p*(c_o[x,y]-c_o[x-2,y])-vijx_n*(c_o[x+2,y]-c_o[x,y])+vijy_p*(c_o[x,y]-c_o[x,y-2])-vijy_n*(c_o[x,y+2]-c_o[x,y]))/(set['h'])
move_f = coef['Alp_f']*set['dt']*(vijx_p*(f_o[x,y]-f_o[x-2,y])-vijx_n*(f_o[x+2,y]-f_o[x,y])+vijy_p*(f_o[x,y]-f_o[x,y-2])-vijy_n*(f_o[x,y+2]-f_o[x,y]))/(set['h'])
digestion_c = set['dt']*coef['Nu']*c_o[x,y]*mean_n
digestion_f = set['dt']*gam_f*f_o[x,y]*mean_n #coef['Gama']
prolifer_f = set['dt']*coef['Beta']*mean_n
sol['c'][x,y] = c_o[x,y] - digestion_c - move_c
sol['f'][x,y] = f_o[x,y] + prolifer_f - digestion_f - move_f
# if move_c != 0 or move_f != 0:
# print move_c, move_f, digestion_c, digestion_f
if sol['c'][x,y] != sol['c_o'][x, set['Ny']]:
sol['c_n'][x,y] = sol['c'][x,y]
return sol
def hybrid_tech(coef, set, sol): #2.23
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n']) #to save the value of 'n' at time step k (we are calculating at time step k+1)
sol['tip_cell'] = []
tipp = []
for nom, nom_isi in enumerate(sol['matrix_tip']): #dicek setiap tip
if isinstance(nom_isi[-1], int) == False: #cek kalau sproutnya masih hidup
# if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
df = '0'
'''Recording backward movement start'''
if len(sol['matrix_tip'][nom]) >=2:
xbm1 = sol['matrix_tip'][nom][-2][0] #get x position of 2nd last tip position (to avoid backward movement)
ybm1 = sol['matrix_tip'][nom][-2][1] #get y position of 2nd last tip position (to avoid backward movement)
tx1 = xb-xbm1
ty1 = yb-ybm1
if tx1 == 0:
if ty1 < 0:
df = '4'
else:
df = '3'
else:
if tx1 < 0:
df = '2'
else:
df = '1'
#kalau terus backward nanti dia bikin cabang baru.
'''Recording backward movement start'''
dirr, probb = movement_dir(coef, set, sol, xb, yb, df) #2.2.1 => go to direction_of_movement.py
# if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
# if not nom in sol['sp_stop']:
# sol['sp_stop'].append(nom)
# sol['cause'][nom] = 'no space'
# # if [xb,yb] in sol['tip_cell']:
# # sol['tip_cell'].remove([xb,yb])
# sol['n'][xb,yb] = 0
# sol['stalk'][xb,yb] = 1
# sol['matrix_tip'][nom][-1].append(10000) #10000 kode utk no space
# else:
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
'''The Movement'''
branch = False
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,tipp,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(2)
# '''Check Anastomosis before branching decision'''
# sol= anas_after(sol, tipp, n_sp, branchingg = False)
# '''Branching decision start'''
# for ind_i, i in enumerate(sol['matrix_tip']):
# if isinstance(i[-1], int) == False: #sprout yang masih hidup
# xbb = i[-1][0] - 1
# ybb = i[-1][1] - 1
# if sol['c_t'][xbb,ybb] > 0: #C_t nya positive
# if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #there is possibility to branch
# list_prob = prob_by_c(sol,xb,yb) #Probability of Branching using c #range(1,11) #2.2.(4)
# tes = randint(1,10)
# if not tes in list_prob: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #BRANCHING!
# sol['life_time_tip'][nom] = 0
# sol['matrix_tip'].append([[xb,yb]])
# sol['life_time_tip'].append(0)
# sol['new_ves_pair'].append([ind_i,len(sol['matrix_tip'])-1])
# '''The Movement from branching'''
# nom = len(sol['matrix_tip'])-1
# xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
# yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
#
# # dirr, probb = movement_dir(coef, set, sol, xb, yb) #2.2.1 => go to direction_of_movement.py
#
# # if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
# # if not nom in sol['sp_stop']:
# # sol['sp_stop'].append(nom)
# # sol['cause'][nom] = 'no space'
# # # if [xb,yb] in sol['tip_cell']:
# # # sol['tip_cell'].remove([xb,yb])
# # sol['n'][xb,yb] = 0
# # sol['stalk'][xb,yb] = 1
# # sol['matrix_tip'][nom][-1].append(1000) #1000 kode utk no space
# # else:
# # '''Making list of prob'''
# # list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
#
# '''The Movement'''
# branch = True
# sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,tipp,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(2)
#
# # sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,tipp,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(5)
# '''Branching decision end'''
# '''Check Anastomosis after branching decision'''
# sol= anas_after(sol, tipp, n_sp, new_ves, branchingg = True)
'''TIP CELL'''
for ind_i, i in enumerate(sol['matrix_tip']):
if len(i) > 1:
if isinstance(i[-1], int) == False: #sprout yang masih hidup
sol['tip_cell'].append(i[-1])
else:
sol['tip_cell'].append(i[-1])
# if len(sol['backward_list']) > 0:
# sol['backward_count'].append(set['k'])
return sol
def hybrid_tech_c(coef, set, sol):
##branching decision and action. Also movement
line = range(1, 11) #for Pb
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
for nom in range(0, n_sp): #dicek setiap tip
if not nom in sol[
'sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
line_1 = range(1, 10001)
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
#print 'xb,yb', xb,',',yb
dirr, space = movement_dir(coef, set, sol, xb, yb, nom, n_dir=True)
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0:
sol['sp_stop'].append(nom)
else:
if dirr[1] == 0:
list_prob_1 = []
else:
list_prob_1 = random.sample(line_1, dirr[1])
for i in list_prob_1:
line_1.remove(i)
if dirr[2] == 0:
list_prob_2 = []
else:
list_prob_2 = random.sample(line_1, dirr[2])
for i in list_prob_2:
line_1.remove(i)
if dirr[3] == 0:
list_prob_3 = []
else:
list_prob_3 = random.sample(line_1, dirr[3])
for i in list_prob_3:
line_1.remove(i)
if dirr[4] == 0:
list_prob_4 = []
else:
list_prob_4 = random.sample(line_1, dirr[4])
for i in list_prob_4:
line_1.remove(i)
list_prob_0 = line_1
#print 'corret:', len(list_prob_0), len(list_prob_1), len(list_prob_2), len(list_prob_3), len(list_prob_4)
tes = randint(
1, 10000
) #select integer number randomly between 1 and 100000
if tes in list_prob_0:
tipp = 'stay'
elif tes in list_prob_1:
tipp = 'left'
xpos_new = sol['matrix_tip'][nom][-1][0] - 2
ypos_new = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][nom] = tipp
for i in list_prob_1:
list_prob_0.append(i)
list_prob_1 = []
elif tes in list_prob_2:
tipp = 'right'
xpos_new = sol['matrix_tip'][nom][-1][0] + 2
ypos_new = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][nom] = tipp
for i in list_prob_2:
list_prob_0.append(i)
list_prob_2 = []
elif tes in list_prob_3:
tipp = 'down'
xpos_new = sol['matrix_tip'][nom][-1][0]
ypos_new = sol['matrix_tip'][nom][-1][1] - 2
sol['matrix_tip'][nom].append((xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][nom] = tipp
for i in list_prob_3:
list_prob_0.append(i)
list_prob_3 = []
elif tes in list_prob_4:
tipp = 'up'
xpos_new = sol['matrix_tip'][nom][-1][0]
ypos_new = sol['matrix_tip'][nom][-1][1] + 2
sol['matrix_tip'][nom].append((xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][nom] = tipp
for i in list_prob_4:
list_prob_0.append(i)
list_prob_4 = []
'''Checking if new position hits any existing vessel'''
if not tipp == 'stay':
if tipp == 'left' and space[0] == 'stop':
sol['sp_stop'].append(nom)
elif tipp == 'right' and space[1] == 'stop':
sol['sp_stop'].append(nom)
elif tipp == 'down' and space[2] == 'stop':
sol['sp_stop'].append(nom)
elif tipp == 'up' and space[3] == 'stop':
sol['sp_stop'].append(nom)
'''Checking m space and calculating number of EC'''
if not coef['Mic'] == 0 or not coef['Kappa'] == 0:
if not tipp == 'stay' and set['t'] > set['tm']:
#calculate number of EC
#sol['number_ec'] += 1
#Kalau di posisi n baru ada m, m nya dibuang
if sol['m'][xpos_new, ypos_new] == 1:
sol['m'][xpos_new, ypos_new] == 0
#sol['cell_m'].remove([xpos_new,ypos_new])
'''2.1 Branching Decision'''
if tipp == 'stay':
sol['life_time_tip'][nom] += sol['tp']
else:
if dirr.count(0) >= 3:
sol['life_time_tip'][nom] += sol['tp']
else:
if sol['life_time_tip'][nom] < coef['T_branch']:
sol['life_time_tip'][nom] += sol['tp']
else: #being able to branch by life time
#probabilty of branching
# print 'NILAI C', c[xb+1,yb+1]
if sol['c'][xb + 1,
yb + 1] >= 0 and sol['c'][xb + 1, yb +
1] < 0.1:
prob_weight = 7 # set the number to select here.
list_prob = random.sample(
line, prob_weight
) #list of selected numbers from line
elif sol['c'][xb + 1, yb +
1] >= 0.1 and sol['c'][xb + 1,
yb + 1] < 0.2:
prob_weight = 8 # set the number to select here.
list_prob = random.sample(line, prob_weight)
elif sol['c'][xb + 1, yb +
1] >= 0.2 and sol['c'][xb + 1,
yb + 1] < 0.3:
prob_weight = 9 # set the number to select here.
list_prob = random.sample(line, prob_weight)
elif sol['c'][xb + 1,
yb + 1] >= 0.3: #do branching
list_prob = line
#apakah branching? meaning masuk dalam probability of branching?
tes = randint(
1, 10
) #select integer number randomly between 1 and 10
#print 'check 3'
if not tes in list_prob:
sol['life_time_tip'][nom] += sol['tp']
else: #do branching
'''2.1 Branhcing'''
sol['life_time_tip'][nom] = 0
sol['matrix_tip'].append([(xb, yb)])
sol['life_time_tip'].append(0)
sol['list_tip_movement'].append('start')
tipp = 'stay'
while tipp == 'stay':
tes = randint(
1, 10000
) #select integer number randomly between 1 and 100000
if tes in list_prob_0:
tipp = 'stay'
elif tes in list_prob_1:
tipp = 'left'
xpos_new = sol['matrix_tip'][-1][-1][
0] - 2
ypos_new = sol['matrix_tip'][-1][-1][1]
sol['matrix_tip'][-1].append(
(xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][-1] = tipp
elif tes in list_prob_2:
tipp = 'right'
xpos_new = sol['matrix_tip'][-1][-1][
0] + 2
ypos_new = sol['matrix_tip'][-1][-1][1]
sol['matrix_tip'][-1].append(
(xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][-1] = tipp
elif tes in list_prob_3:
tipp = 'down'
xpos_new = sol['matrix_tip'][-1][-1][0]
ypos_new = sol['matrix_tip'][-1][-1][
1] - 2
sol['matrix_tip'][-1].append(
(xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][-1] = tipp
elif tes in list_prob_4:
tipp = 'up'
xpos_new = sol['matrix_tip'][-1][-1][0]
ypos_new = sol['matrix_tip'][-1][-1][
1] + 2
sol['matrix_tip'][-1].append(
(xpos_new, ypos_new))
sol['n'][xpos_new, ypos_new] = 1
sol['list_tip_movement'][-1] = tipp
'''Checking if new position hits any existing vessel'''
if tipp == 'left' and space[0] == 'stop':
sol['sp_stop'].append(
len(sol['matrix_tip']) - 1)
elif tipp == 'right' and space[1] == 'stop':
sol['sp_stop'].append(
len(sol['matrix_tip']) - 1)
elif tipp == 'down' and space[2] == 'stop':
sol['sp_stop'].append(
len(sol['matrix_tip']) - 1)
elif tipp == 'up' and space[3] == 'stop':
sol['sp_stop'].append(
len(sol['matrix_tip']) - 1)
'''Checking m space and calculating number of EC'''
if not coef['Mic'] == 0 or not coef[
'Kappa'] == 0:
#calculate number of EC
#sol['number_ec'] += 1
#Kalau di posisi n baru ada m, m nya dibuang
if set['t'] > set['tm']:
if sol['m'][xpos_new, ypos_new] == 1:
sol['m'][xpos_new, ypos_new] == 0
# sol['cell_m'].remove([xpos_new,ypos_new])
return sol
def hybrid_tech(coef, set, sol): #2.23
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(
sol['n']
) #to save the value of 'n' at time step k (we are calculating at time step k+1)
sol['tip_cell'] = []
tipp = []
#running movement for all active sprouts
for nom, nom_isi in enumerate(sol['matrix_tip']): #dicek setiap tip
if isinstance(nom_isi[-1],
int) == False: #cek kalau sproutnya masih hidup
# if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
dirr, probb = movement_dir(
coef, set, sol, xb,
yb) #2.2.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[
4] == 0: #checking if there is space for tip cell to move
if not nom in sol['sp_stop']:
sol['sp_stop'].append(nom)
sol['cause'][nom] = 'no space'
# if [xb,yb] in sol['tip_cell']:
# sol['tip_cell'].remove([xb,yb])
sol['n'][xb, yb] = 0
sol['stalk'][xb, yb] = 1
sol['matrix_tip'][nom][-1].append(
10000) #10000 kode utk no space
else:
'''Making list of prob'''
list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = set_list_prob(
dirr) #2.2.(1)
'''The Movement'''
branch = False
sol, tipp, list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = movement(
sol, set, tipp, nom, xb, yb, list_prob_0, list_prob_1,
list_prob_2, list_prob_3, list_prob_4, branch) #2.2.(2)
'''Check Anastomosis before branching decision'''
sol = anas_after(sol, tipp, n_sp, branchingg=False)
# '''Branching decision'''
# for ind_i, i in enumerate(sol['matrix_tip']):
# if isinstance(i[-1], int) == False: #sprout yang masih hidup
# if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #there is possibility to branch
# # Probability of Branching using c
# list_prob = prob_by_c(sol,xb,yb) #range(1,11) #2.2.(4)
# tes = randint(1,10)
# if not tes in list_prob: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #BRANCHING!
# # print 'Branchingg'
# sol['life_time_tip'][nom] = 0
# sol['matrix_tip'].append([[xb,yb]])
# sol['life_time_tip'].append(0)
# '''The Movement from branching'''
# nom = len(sol['matrix_tip'])-1
# xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
# yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
#
# dirr, probb = movement_dir(coef, set, sol, xb, yb) #2.2.1 => go to direction_of_movement.py
#
# if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
# if not nom in sol['sp_stop']:
# sol['sp_stop'].append(nom)
# sol['cause'][nom] = 'no space'
# # if [xb,yb] in sol['tip_cell']:
# # sol['tip_cell'].remove([xb,yb])
# sol['n'][xb,yb] = 0
# sol['stalk'][xb,yb] = 1
# sol['matrix_tip'][nom][-1].append(1000) #1000 kode utk no space
# else:
# '''Making list of prob'''
# list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
#
# '''The Movement'''
# branch = False
# sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,tipp,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(2)
#
# # sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,tipp,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(5)
#
# '''Check Anastomosis after branching decision'''
# sol= anas_after(sol, tipp, n_sp, branchingg = False)
'''TIP CELL'''
for ind_i, i in enumerate(sol['matrix_tip']):
if len(i) > 1:
if isinstance(i[-1], int) == False: #sprout yang masih hidup
sol['tip_cell'].append(i[-1])
else:
sol['tip_cell'].append(i[-1])
# '''2.1 Branching Decision'''
# PP = 'test'
# if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
# sol['life_time_tip'][nom] += set['dt']
# else: #there is possibility to branch
# if dirr.count(0) >= 3: #no space to move
# sol['life_time_tip'][nom] += set['dt']
# else: #there is possibility to branch
# if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #there is possibility to branch
# # Probability of Branching using c
# list_prob = prob_by_c(sol,xb,yb) #range(1,11) #2.2.(4)
# tes = randint(1,10)
# if not tes in list_prob: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #BRANCHING!
# # print 'Branchingg'
# sol['life_time_tip'][nom] = 0
# sol['matrix_tip'].append([[xb,yb]])
# sol['life_time_tip'].append(0)
# '''The Movement from branching'''
# branch = True
# nom = len(sol['matrix_tip'])-1
# sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(5)
if len(sol['backward_list']) > 0:
sol['backward_count'].append(set['k'])
# print 'nom', nom
# '''Create tip cell area'''
# for tip in sol['tip_cell']:
# sol['tip_cell_area'].append([tip[0]-2,tip[1]])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]])
# sol['tip_cell_area'].append([tip[0],tip[1]-2])
# sol['tip_cell_area'].append([tip[0],tip[1]+2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]-2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]-2])
# sol['tip_cell_area'] = []
# for i in sol['tip_cell']:
# sol['tip_cell_area'].append([i[0]+1, i[1]+1])
# sol['tip_cell_area'].append([i[0]+1, i[1]-1])
# sol['tip_cell_area'].append([i[0]-1, i[1]+1])
# sol['tip_cell_area'].append([i[0]-1, i[1]-1])
# '''Record New Tip Cell'''
# sol['tip_cell'] = []
# for nom in range(0,len(sol['matrix_tip'])): #dicek setiap tip
# if not nom in sol['sp_stop']: #record only active sprout
# sol['tip_cell'].append([sol['matrix_tip'][nom][-1][0],sol['matrix_tip'][nom][-1][1]])
# count_anas = len(i[1])
# prob_weight = 3
# line = range(1,count_anas*prob_weight+1)
# for ind_jj, j in enumerate(i[1]):
# globals()['%s' % ind_jj] = random.sample(line, prob_weight)
# for k in globals()['%s' % ind_jj]:
# line.remove(k)
# tess = randint(1,count_anas*prob_weight+1)
# kk = 0
# for ind_jj, j in enumerate(i[1]):
# if tess in
return sol
def hybrid_tech_m(coef, set, sol):
mo = sol['m'][:]
nom = 0
sol['index_mn'] = []
sol['cell_m'] = []
look = 0
for y in range(1,set['Ny'],2):
for x in range(1,set['Nx'],2):
if sol['m'][x,y] == 1:
sol['cell_m'].append([x,y])
print 'Banyaknya cell m',len(sol['cell_m'])
# print 'Banyaknya m yang 1',numpy.count_nonzero(sol['m'])
'''Identify The fartest tip from center'''
'''
distance = []
for tip in sol['tip_cell']:
r_f = numpy.sqrt((tip[0]*set['Hh']-set['O_x'])**2 + (tip[1]*set['Hh']-set['O_y'])**2)
distance.append(r_f)
far = max(distance) + 0.4
'''
far = 100
for e, cell in enumerate(sol['cell_m']):
xb = cell[0]
yb = cell[1]
if set['layout'] == 'retina':
r_f = numpy.sqrt((xb*set['Hh']-set['O_x'])**2 + (yb*set['Hh']-set['O_y'])**2)
if r_f <= far:
look = 1
else:
look = 1
if look == 1:
line_1 = range(1,10001)
dirr, space = movement_dir(coef, set, sol, xb, yb, nom, n_dir = False)
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0:
lop = 1
else:
if dirr[1] == 0:
list_prob_1 = []
else:
list_prob_1 = random.sample(line_1, dirr[1])
for i in list_prob_1:
line_1.remove(i)
if dirr[2] == 0:
list_prob_2 = []
else:
list_prob_2 = random.sample(line_1, dirr[2])
for i in list_prob_2:
line_1.remove(i)
if dirr[3] == 0:
list_prob_3 = []
else:
list_prob_3 = random.sample(line_1, dirr[3])
for i in list_prob_3:
line_1.remove(i)
if dirr[4] == 0:
list_prob_4 = []
else:
list_prob_4 = random.sample(line_1, dirr[4])
for i in list_prob_4:
line_1.remove(i)
list_prob_0 = line_1
#print 'selesai bikin line'
nx = xb
ny = yb
tes = randint(1,10000) #select integer number randomly between 1 and 100000
if tes in list_prob_1:
if [xb - 2, yb] not in sol['tip_cell']:
nx = xb - 2
ny = yb
sol['m'][xb - 2, yb] = 1
sol['m'][xb,yb] = 0
elif tes in list_prob_2:
if [xb + 2, yb] not in sol['tip_cell']:
nx = xb + 2
ny = yb
sol['m'][xb + 2, yb] = 1
sol['m'][xb,yb] = 0
elif tes in list_prob_3:
if [xb, yb - 2] not in sol['tip_cell']:
nx = xb
ny = yb - 2
sol['m'][xb, yb - 2] = 1
sol['m'][xb,yb] = 0
elif tes in list_prob_4:
if [xb, yb + 2] not in sol['tip_cell']:
nx = xb
ny = yb + 2
sol['m'][xb, yb + 2] = 1
sol['m'][xb,yb] = 0
#if sol['n'][nx,ny] == 1:
# if [xb,yb] in sol['index_mn']:
# sol['index_mn'].remove([xb,yb])
# sol['index_mn'].append([nx,ny])
#for ec_i in range(0,len(sol['matrix_tip'])):
# if (nx,ny) in sol['matrix_tip'][ec_i]:
# sol['index_mn'].append([nx,ny])
for y in range(1,set['Ny'],2):
for x in range(1,set['Nx'],2):
if sol['m'][x,y] == 1 and sol['n'][x,y] == 1:
sol['index_mn'].append([x,y])
# print 'Banyaknya MC yang di EC', len(sol['index_mn'])
return sol
def hybrid_tech(coef, set, sol): #Ref.4.1
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n']) #to save the value of 'n' at time step k (we are calculating at time step k+1)
# sol['vn_o'] = [] #to record tip cell position
# sol['bw'] = 0 #to detect backward list
sol['backward_list'] = [] #backward list
for nom in range(0,n_sp): #we check every tip cell
if not nom in sol['sp_stop']: #if the anastomosis happen, we don't need to check its movement or branching decision.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
dirr, probb = movement_dir(coef, set, sol, xb, yb) #Ref.4.1.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
if not nom in sol['sp_stop']:
sol['sp_stop'].append(nom)
sol['cause'][nom] = 'no space'
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
sol['n'][xb,yb] = 0
sol['stalk'][xb,yb] = 1
else:
'''Making list of probability for selecting the direction'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #Ref.4.1.2
'''The Movement And Tip-Tip Anastomosis Checking'''
branch = False
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #Ref.4.1.3
'''2.1 Branching Decision'''
PP = 'test'
if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
# Probability of Branching using c
list_prob = prob_by_c(sol,xb,yb) #range(1,11) ##Ref.4.1.4
tes = randint(1,10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
else: #BRANCHING!
sol['life_time_tip'][nom] = 0
sol['matrix_tip'].append([[xb,yb]])
sol['life_time_tip'].append(0)
'''The Movement from branching'''
branch = True
nom = len(sol['matrix_tip'])-1
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #Ref.4.1.3
# if len(sol['backward_list']) > 0: #to record which iteration that the backward movement occurs
# sol['backward_count'].append(set['k'])
# '''Create tip cell area'''
# for tip in sol['tip_cell']:
# sol['tip_cell_area'].append([tip[0]-2,tip[1]])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]])
# sol['tip_cell_area'].append([tip[0],tip[1]-2])
# sol['tip_cell_area'].append([tip[0],tip[1]+2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]-2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]-2])
'''Create tip cell area for solving c dan f continuously'''
sol['tip_cell_area'] = []
for i in sol['tip_cell']:
sol['tip_cell_area'].append([i[0]+1, i[1]+1])
sol['tip_cell_area'].append([i[0]+1, i[1]-1])
sol['tip_cell_area'].append([i[0]-1, i[1]+1])
sol['tip_cell_area'].append([i[0]-1, i[1]-1])
# '''Record New Tip Cell'''
# sol['tip_cell'] = []
# for nom in range(0,len(sol['matrix_tip'])): #dicek setiap tip
# if not nom in sol['sp_stop']: #record only active sprout
# sol['tip_cell'].append([sol['matrix_tip'][nom][-1][0],sol['matrix_tip'][nom][-1][1]])
return sol
def hybrid_tech_c(coef, set, sol):
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n']) #to save the value of 'n' at time step k (we are calculating at time step k+1)
for nom in range(0,n_sp): #dicek setiap tip
if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
# '''Proliferation'''
# if sol['life_mit'][nom] >= coef['T_mitosis']:
# sol['life_mit'][nom] = 0
# if sol['list_tip_movement'] == 'left':
# if [xb,yb] in sol['tip_cell']:
# sol['tip_cell'].remove([xb,yb])
# xs = sol['matrix_tip'][nom][-1][0] - 2
# ys = sol['matrix_tip'][nom][-1][1]
# sol['matrix_tip'][nom].append((xs,ys))
# sol['n'][xs,ys] = 1
# sol['tip_cell'].append([xs,ys])
# elif sol['list_tip_movement'] == 'right':
# if [xb,yb] in sol['tip_cell']:
# sol['tip_cell'].remove([xb,yb])
# xs = sol['matrix_tip'][nom][-1][0] + 2
# ys = sol['matrix_tip'][nom][-1][1]
# sol['matrix_tip'][nom].append((xs,ys))
# sol['n'][xs,ys] = 1
# sol['tip_cell'].append([xs,ys])
# elif sol['list_tip_movement'] == 'down':
# if [xb,yb] in sol['tip_cell']:
# sol['tip_cell'].remove([xb,yb])
# xs = sol['matrix_tip'][nom][-1][0]
# ys = sol['matrix_tip'][nom][-1][1] -2
# sol['matrix_tip'][nom].append((xs,ys))
# sol['n'][xs,ys] = 1
# sol['tip_cell'].append([xs,ys])
# elif sol['list_tip_movement'] == 'up':
# if [xb,yb] in sol['tip_cell']:
# sol['tip_cell'].remove([xb,yb])
# xs = sol['matrix_tip'][nom][-1][0]
# ys = sol['matrix_tip'][nom][-1][1] + 2
# sol['matrix_tip'][nom].append((xs,ys))
# sol['n'][xs,ys] = 1
# sol['tip_cell'].append([xs,ys])
# '''Proliferation'''
dirr= movement_dir(coef, set, sol, xb, yb, nom)
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0:
sol['sp_stop'].append(nom)
sol['tip_cell'].remove([xb,yb])
else:
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr)
'''Checking Space for n #if meet vessel'''
ml = 'f'
mr = 'f'
md = 'f'
mu = 'f'
tip_l = -1
tip_r = -1
tip_d = -1
tip_u = -1
'''
ml, mr, md, mu, tip_l, tip_r, tip_d, tip_u = anastomosis_tip_branch(sol,nom,xb,yb,ml,mr,md,mu,tip_l,tip_r,tip_d,tip_u)
sol['pp'] ={}
ml = 'f'
mr = 'f'
md = 'f'
mu = 'f'
tip_l = -1
tip_r = -1
tip_d = -1
tip_u = -1
'''
'''The Movement'''
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4,ml,mr,md,mu,tip_l,tip_r,tip_d,tip_u)
'''Test Anastomosis tip-tip if move'''
if not tipp == 'stay':
sol=anastomosis_tip_tip(sol,nom)
'''2.1 Branching Decision'''
if tipp == 'stay': #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
cek = str(nom)
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
if cek in sol['pp']:
sol['pp'].pop('cek')
else: #there is possibility to branch
if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
if cek in sol['pp']:
sol['pp'].pop('cek')
else: #there is possibility to branch
'''Probability of Branching using c'''
list_prob = prob_by_c(sol,xb,yb)
tes = randint(1,10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
if cek in sol['pp']:
sol['pp'].pop('cek')
else: #BRANCHING!
sol['life_time_tip'][nom] = 0
sol['life_mit'][nom] += set['dt']
sol['matrix_tip'].append([(xb,yb)])
sol['life_time_tip'].append(0)
sol['life_mit'].append(0)
sol['list_tip_movement'].append('start')
tipp = 'stay'
if cek in sol['pp']:
sol['pp'].pop('cek')
'''The Movement from branching'''
while tipp == 'stay':
sol, tipp = movement_branch(tipp,sol,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4,ml,mr,md,mu,tip_l,tip_r,tip_d,tip_u)
'''Check Anastomosis'''
if not tipp == 'stay':
sol=anastomosis_tip_tip(sol,len(sol['matrix_tip'])-1)
return sol, n_o
def hybrid_tech(coef, set, sol): #2.23
# print 'all sol', type(sol)#["stop_iter"]
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
# n_o = numpy.copy(sol['n']) #to save the value of 'n' at time step k (we are calculating at time step k+1)
# sol['vn_o'] = [] #to record tip cell position
# sol['bw'] = 0 #to detect backward list
sol['backward_list'] = [] #backward list
for nom in range(0, n_sp): #dicek setiap tip
if not nom in sol[
'sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
dirr, probb = movement_dir(
coef, set, sol, xb,
yb) #2.2.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[
4] == 0: #checking if there is space for tip cell to move
if not nom in sol['sp_stop']:
sol['sp_stop'].append(nom)
sol['cause'][nom] = 'no space'
if [xb, yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb, yb])
sol['n'][xb, yb] = 0
sol['stalk'][xb, yb] = 1
else:
'''Making list of prob'''
list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = set_list_prob(
dirr) #2.2.(1)
'''The Movement And Tip-Tip Anastomosis Checking'''
branch = False
sol, tipp, list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = movement(
sol, set, nom, xb, yb, list_prob_0, list_prob_1,
list_prob_2, list_prob_3, list_prob_4, branch) #2.2.(2)
'''2.1 Branching Decision'''
PP = 'test'
if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
if sol['life_time_tip'][nom] < coef[
'T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
# Probability of Branching using c
list_prob = prob_by_c(sol, xb,
yb) #range(1,11) #2.2.(4)
tes = randint(1, 10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
else: #BRANCHING!
sol['life_time_tip'][nom] = 0
sol['matrix_tip'].append([[xb, yb]])
sol['life_time_tip'].append(0)
'''The Movement from branching'''
branch = True
nom = len(sol['matrix_tip']) - 1
sol, tipp, list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = movement(
sol, set, nom, xb, yb, list_prob_0,
list_prob_1, list_prob_2, list_prob_3,
list_prob_4, branch) #2.2.(5)
if len(sol['backward_list']) > 0:
sol['backward_count'].append(set['k'])
# '''Create tip cell area'''
# for tip in sol['tip_cell']:
# sol['tip_cell_area'].append([tip[0]-2,tip[1]])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]])
# sol['tip_cell_area'].append([tip[0],tip[1]-2])
# sol['tip_cell_area'].append([tip[0],tip[1]+2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]-2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]-2])
'''Record New Tip Cell'''
# sol['tip_cell'] = []
# for nom in range(0,len(sol['matrix_tip'])): #dicek setiap tip
# if not nom in sol['sp_stop']: #record only active sprout
# sol['tip_cell'].append([sol['matrix_tip'][nom][-1][0],sol['matrix_tip'][nom][-1][1]])
return sol
def system_2d(coef, set, sol, n_o): #2.3
c_o = numpy.copy(
sol['c']
) #to save values at time step k (we are calculating at time step k+1)
f_o = numpy.copy(
sol['f']
) #to save values at time step k (we are calculating at time step k+1)
'''Calculate Velocity from tip cell's Vel'''
sol['Vel_x'] = numpy.zeros((set['Nx'] + 1, set['Ny'] + 1))
sol['Vel_y'] = numpy.zeros((set['Nx'] + 1, set['Ny'] + 1))
for y in range(1, set['Ny'], 2):
for x in range(1, set['Nx'], 2):
if n_o[x, y] == 1:
dirr, probb = movement_dir(coef, set, sol, x, y)
sol['Vel_x'][x, y] = -probb[1] + probb[2]
sol['Vel_y'][x, y] = -probb[3] + probb[4]
'''Solve c & f at sub lattice'''
for y in range(0, set['Ny'] + 1, 2):
for x in range(0, set['Nx'] + 1, 2):
c_star = sol['c_o'][x, y] - c_o[x, y]
gam_f = sol['c_o'][x, y] * c_star / ((1 / (coef['Gama'])) + c_star)
move_c = 0
move_f = 0
if y == 0:
if x == 0:
mean_n = n_o[x + 1, y + 1] / 4
elif x == set['Nx']:
mean_n = n_o[x - 1, y + 1] / 4
else:
mean_n = (n_o[x - 1, y + 1] + n_o[x + 1, y + 1]) / 4
move_c = 0 #coef['Alp_c']*set['dt']*(vijx_p*(c_o[x,y]-c_o[x-2,y])-vijx_n*(c_o[x+2,y]-c_o[x,y])+vijy_p*(0)-vijy_n*(c_o[x,y+2]-c_o[x,y]))/(set['h']**2)
elif y == set['Ny']:
if x == 0:
mean_n = n_o[x + 1, y - 1] / 4
elif x == set['Nx']:
mean_n = n_o[x - 1, y - 1] / 4
else:
mean_n = (n_o[x - 1, y - 1] + n_o[x + 1, y - 1]) / 4
move_c = 0 #coef['Alp_c']*set['dt']*(vijx_p*(c_o[x,y]-c_o[x-2,y]coef['Gama'])-vijx_n*(c_o[x+2,y]-c_o[x,y])+vijy_p*(c_o[x,y]-c_o[x,y-2])-vijy_n*(0))/(set['h']**2)
else:
if x == 0:
mean_n = (n_o[x + 1, y - 1] + n_o[x + 1, y + 1]) / 2
move_c = 0 #coef['Alp_c']*set['dt']*(vijx_p*(0)-vijx_n*(c_o[x+2,y]-c_o[x,y])+vijy_p*(c_o[x,y]-c_o[x,y-2])-vijy_n*(c_o[x,y+2]-c_o[x,y]))/(set['h']**2)
elif x == set['Nx']:
mean_n = (n_o[x - 1, y - 1] + n_o[x - 1, y + 1]) / 4
move_c = 0 #coef['Alp_c']*set['dt']*(vijx_p*(c_o[x,y]-c_o[x-2,y])-vijx_n*(0)+vijy_p*(c_o[x,y]-c_o[x,y-2])-vijy_n*(c_o[x,y+2]-c_o[x,y]))/(set['h']**2)
else:
mean_n = (n_o[x + 1, y + 1] + n_o[x - 1, y + 1] +
n_o[x + 1, y - 1] + n_o[x - 1, y - 1]) / 4
vel_x_mean = (sol['Vel_x'][x + 1, y + 1] +
sol['Vel_x'][x - 1, y + 1] +
sol['Vel_x'][x + 1, y - 1] +
sol['Vel_x'][x - 1, y - 1]) / 4
vel_y_mean = (sol['Vel_y'][x + 1, y + 1] +
sol['Vel_y'][x - 1, y + 1] +
sol['Vel_y'][x + 1, y - 1] +
sol['Vel_y'][x - 1, y - 1]) / 4
vijx_p = max(0, vel_x_mean)
vijx_n = max(0, -vel_x_mean)
vijy_p = max(0, vel_y_mean)
vijy_n = max(0, -vel_y_mean)
# if vel_x_mean != 0 or vel_y_mean != 0:
# print vel_x_mean, vel_y_mean
#Method: not from P1,P2,P3,...
# vijx_p, vijx_n, vijy_p, vijy_n = velocity_max(coef,set,sol,n_o,c_o,f_o,x,y)
move_c = coef['Alp_c'] * set['dt'] * (
vijx_p * (c_o[x, y] - c_o[x - 2, y]) - vijx_n *
(c_o[x + 2, y] - c_o[x, y]) + vijy_p *
(c_o[x, y] - c_o[x, y - 2]) - vijy_n *
(c_o[x, y + 2] - c_o[x, y])) / (set['h'])
move_f = coef['Alp_f'] * set['dt'] * (
vijx_p * (f_o[x, y] - f_o[x - 2, y]) - vijx_n *
(f_o[x + 2, y] - f_o[x, y]) + vijy_p *
(f_o[x, y] - f_o[x, y - 2]) - vijy_n *
(f_o[x, y + 2] - f_o[x, y])) / (set['h'])
digestion_c = set['dt'] * coef['Nu'] * c_o[x, y] * mean_n
digestion_f = set['dt'] * gam_f * f_o[x, y] * mean_n #coef['Gama']
prolifer_f = set['dt'] * coef['Beta'] * mean_n
sol['c'][x, y] = c_o[x, y] - digestion_c - move_c
sol['f'][x, y] = f_o[x, y] + prolifer_f - digestion_f - move_f
# if move_c != 0 or move_f != 0:
# print move_c, move_f, digestion_c, digestion_f
if sol['c'][x, y] != sol['c_o'][x, set['Ny']]:
sol['c_n'][x, y] = sol['c'][x, y]
return sol
def hybrid_tech_m(coef, set, sol):
mo = sol['m'][:]
nom = 0
sol['index_mn'] = []
sol['cell_m'] = []
look = 0
for y in range(1, set['Ny'], 2):
for x in range(1, set['Nx'], 2):
if sol['m'][x, y] == 1:
sol['cell_m'].append([x, y])
print 'Banyaknya cell m', len(sol['cell_m'])
# print 'Banyaknya m yang 1',numpy.count_nonzero(sol['m'])
'''Identify The fartest tip from center'''
'''
distance = []
for tip in sol['tip_cell']:
r_f = numpy.sqrt((tip[0]*set['Hh']-set['O_x'])**2 + (tip[1]*set['Hh']-set['O_y'])**2)
distance.append(r_f)
far = max(distance) + 0.4
'''
far = 100
for e, cell in enumerate(sol['cell_m']):
xb = cell[0]
yb = cell[1]
if set['layout'] == 'retina':
r_f = numpy.sqrt((xb * set['Hh'] - set['O_x'])**2 +
(yb * set['Hh'] - set['O_y'])**2)
if r_f <= far:
look = 1
else:
look = 1
if look == 1:
line_1 = range(1, 10001)
dirr, space = movement_dir(coef,
set,
sol,
xb,
yb,
nom,
n_dir=False)
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0:
lop = 1
else:
if dirr[1] == 0:
list_prob_1 = []
else:
list_prob_1 = random.sample(line_1, dirr[1])
for i in list_prob_1:
line_1.remove(i)
if dirr[2] == 0:
list_prob_2 = []
else:
list_prob_2 = random.sample(line_1, dirr[2])
for i in list_prob_2:
line_1.remove(i)
if dirr[3] == 0:
list_prob_3 = []
else:
list_prob_3 = random.sample(line_1, dirr[3])
for i in list_prob_3:
line_1.remove(i)
if dirr[4] == 0:
list_prob_4 = []
else:
list_prob_4 = random.sample(line_1, dirr[4])
for i in list_prob_4:
line_1.remove(i)
list_prob_0 = line_1
#print 'selesai bikin line'
nx = xb
ny = yb
tes = randint(
1, 10000
) #select integer number randomly between 1 and 100000
if tes in list_prob_1:
if [xb - 2, yb] not in sol['tip_cell']:
nx = xb - 2
ny = yb
sol['m'][xb - 2, yb] = 1
sol['m'][xb, yb] = 0
elif tes in list_prob_2:
if [xb + 2, yb] not in sol['tip_cell']:
nx = xb + 2
ny = yb
sol['m'][xb + 2, yb] = 1
sol['m'][xb, yb] = 0
elif tes in list_prob_3:
if [xb, yb - 2] not in sol['tip_cell']:
nx = xb
ny = yb - 2
sol['m'][xb, yb - 2] = 1
sol['m'][xb, yb] = 0
elif tes in list_prob_4:
if [xb, yb + 2] not in sol['tip_cell']:
nx = xb
ny = yb + 2
sol['m'][xb, yb + 2] = 1
sol['m'][xb, yb] = 0
#if sol['n'][nx,ny] == 1:
# if [xb,yb] in sol['index_mn']:
# sol['index_mn'].remove([xb,yb])
# sol['index_mn'].append([nx,ny])
#for ec_i in range(0,len(sol['matrix_tip'])):
# if (nx,ny) in sol['matrix_tip'][ec_i]:
# sol['index_mn'].append([nx,ny])
for y in range(1, set['Ny'], 2):
for x in range(1, set['Nx'], 2):
if sol['m'][x, y] == 1 and sol['n'][x, y] == 1:
sol['index_mn'].append([x, y])
# print 'Banyaknya MC yang di EC', len(sol['index_mn'])
return sol
def hybrid_tech(coef, set, sol): #2.23
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(
sol['n']
) #to save the value of 'n' at time step k (we are calculating at time step k+1)
sol['tip_cell'] = []
tipp = []
for nom, nom_isi in enumerate(sol['matrix_tip']): #dicek setiap tip
if isinstance(nom_isi[-1],
int) == False: #cek kalau sproutnya masih hidup
# if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
df = '0'
'''Recording backward movement start'''
if len(sol['matrix_tip'][nom]) >= 2:
xbm1 = sol['matrix_tip'][nom][-2][
0] #get x position of 2nd last tip position (to avoid backward movement)
ybm1 = sol['matrix_tip'][nom][-2][
1] #get y position of 2nd last tip position (to avoid backward movement)
tx1 = xb - xbm1
ty1 = yb - ybm1
if tx1 == 0:
if ty1 < 0:
df = '4'
else:
df = '3'
else:
if tx1 < 0:
df = '2'
else:
df = '1'
#kalau terus backward nanti dia bikin cabang baru.
'''Recording backward movement start'''
dirr, probb = movement_dir(
coef, set, sol, xb, yb,
df) #2.2.1 => go to direction_of_movement.py
# if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
# if not nom in sol['sp_stop']:
# sol['sp_stop'].append(nom)
# sol['cause'][nom] = 'no space'
# # if [xb,yb] in sol['tip_cell']:
# # sol['tip_cell'].remove([xb,yb])
# sol['n'][xb,yb] = 0
# sol['stalk'][xb,yb] = 1
# sol['matrix_tip'][nom][-1].append(10000) #10000 kode utk no space
# else:
'''Making list of prob'''
list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = set_list_prob(
dirr) #2.2.(1)
'''The Movement'''
branch = False
sol, tipp, list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = movement(
sol, set, tipp, nom, xb, yb, list_prob_0, list_prob_1,
list_prob_2, list_prob_3, list_prob_4, branch) #2.2.(2)
# '''Check Anastomosis before branching decision'''
# sol= anas_after(sol, tipp, n_sp, branchingg = False)
# '''Branching decision start'''
# for ind_i, i in enumerate(sol['matrix_tip']):
# if isinstance(i[-1], int) == False: #sprout yang masih hidup
# xbb = i[-1][0] - 1
# ybb = i[-1][1] - 1
# if sol['c_t'][xbb,ybb] > 0: #C_t nya positive
# if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #there is possibility to branch
# list_prob = prob_by_c(sol,xb,yb) #Probability of Branching using c #range(1,11) #2.2.(4)
# tes = randint(1,10)
# if not tes in list_prob: #not able to branch
# sol['life_time_tip'][nom] += set['dt']
# else: #BRANCHING!
# sol['life_time_tip'][nom] = 0
# sol['matrix_tip'].append([[xb,yb]])
# sol['life_time_tip'].append(0)
# sol['new_ves_pair'].append([ind_i,len(sol['matrix_tip'])-1])
# '''The Movement from branching'''
# nom = len(sol['matrix_tip'])-1
# xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
# yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
#
# # dirr, probb = movement_dir(coef, set, sol, xb, yb) #2.2.1 => go to direction_of_movement.py
#
# # if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
# # if not nom in sol['sp_stop']:
# # sol['sp_stop'].append(nom)
# # sol['cause'][nom] = 'no space'
# # # if [xb,yb] in sol['tip_cell']:
# # # sol['tip_cell'].remove([xb,yb])
# # sol['n'][xb,yb] = 0
# # sol['stalk'][xb,yb] = 1
# # sol['matrix_tip'][nom][-1].append(1000) #1000 kode utk no space
# # else:
# # '''Making list of prob'''
# # list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
#
# '''The Movement'''
# branch = True
# sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,tipp,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(2)
#
# # sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,tipp,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(5)
# '''Branching decision end'''
# '''Check Anastomosis after branching decision'''
# sol= anas_after(sol, tipp, n_sp, new_ves, branchingg = True)
'''TIP CELL'''
for ind_i, i in enumerate(sol['matrix_tip']):
if len(i) > 1:
if isinstance(i[-1], int) == False: #sprout yang masih hidup
sol['tip_cell'].append(i[-1])
else:
sol['tip_cell'].append(i[-1])
# if len(sol['backward_list']) > 0:
# sol['backward_count'].append(set['k'])
return sol
def hybrid_tech(coef, set, sol): #2.2
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(
sol['n']
) #to save the value of 'n' at time step k (we are calculating at time step k+1)
vn_o = [] #to record tip cell position
for nom in range(0, n_sp): #dicek setiap tip
if not nom in sol[
'sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
vn_o.append([xb, yb])
dirr = movement_dir(coef, set, sol, xb, yb,
nom) #2.2.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[
4] == 0: #checking if there is space for tip cell to move
sol['sp_stop'].append(nom)
sol['tip_cell'].remove([xb, yb])
sol['n'][xb, yb] = 0
else:
'''Making list of prob'''
list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = set_list_prob(
dirr) #2.2.(1)
'''The Movement'''
sol, tipp, list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = movement(
sol, nom, xb, yb, list_prob_0, list_prob_1, list_prob_2,
list_prob_3, list_prob_4) #2.2.(2)
'''2.1 Branching Decision
PP = 'test'
if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA1'
if movi == True:
sol['PP'].remove([xb,yb])
sol['pp'].pop((xb,yb))
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA2'
#print sol['life_time_tip'][nom]
if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA3'
# Probability of Branching using c
list_prob = range(1,11)#prob_by_c(sol,xb,yb) #2.2.(4)
tes = randint(1,10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #BRANCHING!
#print 'YAYAYA4'
sol['life_time_tip'][nom] = 0
sol['life_mit'][nom] += set['dt']
sol['matrix_tip'].append([(xb,yb)])
sol['life_time_tip'].append(0)
sol['life_mit'].append(0)
sol['list_tip_movement'].append('start')
tipp = 'stay'
# The Movement from branching
while tipp == 'stay':
sol, tipp = movement_branch(tipp,sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4) #2.2.(5)
'''
'''Vector Velocity of stalk (Vb) Method 1:all towards tip cell'''
#profile 1: \/\
for y in range(1, set['Ny'], 2):
for x in range(1, set['Nx'], 2):
vb_x = 0
vb_y = 0
for ind, vec in enumerate(vn_o):
s = m.sqrt((x - vec[0])**2 + (y - vec[1])**2)
if s <= 2:
h_s = 0
elif s <= 10:
h_s = 0.5 + coef['m1'] * (s - 10)
elif s <= 20:
h_s = 2 + coef['m2'] * (s - 20)
elif s <= 40:
h_s = 0 + coef['m3'] * (s - 40)
else:
h_s = 0
if s != 0:
vb_x += (vec[0] - x) * h_s / s #unit vector
vb_y += (vec[1] - y) * h_s / s #unit vector
sol['Vb_x'][x, y] = vb_x
sol['Vb_y'][x, y] = vb_y
#profile 2: /
for y in range(1, set['Ny'], 2):
for x in range(1, set['Nx'], 2):
vb_x = 0
vb_y = 0
for ind, vec in enumerate(vn_o):
s = m.sqrt((x - vec[0])**2 + (y - vec[1])**2)
if s <= 2:
h_s = 0
elif s <= 50:
h_s = 1 + coef['m1'] * (s - 50)
else:
h_s = 1
if s != 0:
vb_x += (vec[0] - x) * h_s / s #unit vector
vb_y += (vec[1] - y) * h_s / s #unit vector
sol['Vb_x'][x, y] = vb_x
sol['Vb_y'][x, y] = vb_y
# print 'Tip cell position:', vn_o
# print 'Velocity Vector stalk on [3,201]: [',sol['Vb_x'][3,201],',',sol['Vb_y'][3,201],']'
return sol, n_o
def hybrid_tech_c(coef, set, sol): #2.2
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
for nom in range(0,n_sp): #dicek setiap tip
if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
'''Proliferation'''
if sol['life_mit'][nom] >= coef['T_mitosis']:
sol['life_mit'][nom] = 0
if sol['list_tip_movement'] == 'left':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0] - 2
ys = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'right':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0] + 2
ys = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'down':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0]
ys = sol['matrix_tip'][nom][-1][1] -2
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'up':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0]
ys = sol['matrix_tip'][nom][-1][1] + 2
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
'''Proliferation'''
dirr= movement_dir(coef, set, sol, xb, yb, nom) #2.2.1
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0:
sol['sp_stop'].append(nom)
sol['tip_cell'].remove([xb,yb])
else:
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
'''Checking Space for n #if meet vessel'''
ml = 'f'
mr = 'f'
md = 'f'
mu = 'f'
tip_l = -1
tip_r = -1
tip_d = -1
tip_u = -1
'''
ml, mr, md, mu, tip_l, tip_r, tip_d, tip_u = anastomosis_tip_branch(sol,nom,xb,yb,ml,mr,md,mu,tip_l,tip_r,tip_d,tip_u)
sol['pp'] ={}
ml = 'f'
mr = 'f'
md = 'f'
mu = 'f'
tip_l = -1
tip_r = -1
tip_d = -1
tip_u = -1
'''
'''The Movement'''
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4,ml,mr,md,mu,tip_l,tip_r,tip_d,tip_u) #2.2.(2)
'''Test Anastomosis tip-tip if move'''
if not tipp == 'stay':
sol=anastomosis_tip_tip(sol,nom) #2.2.(3)
'''2.1 Branching Decision'''
if tipp == 'stay': #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
cek = str(nom)
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
if cek in sol['pp']:
sol['pp'].pop('cek')
else: #there is possibility to branch
if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
if cek in sol['pp']:
sol['pp'].pop('cek')
else: #there is possibility to branch
'''Probability of Branching using c'''
list_prob = prob_by_c(sol,xb,yb) #2.2.(4)
tes = randint(1,10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
if cek in sol['pp']:
sol['pp'].pop('cek')
else: #BRANCHING!
sol['life_time_tip'][nom] = 0
sol['life_mit'][nom] += set['dt']
sol['matrix_tip'].append([(xb,yb)])
sol['life_time_tip'].append(0)
sol['life_mit'].append(0)
sol['list_tip_movement'].append('start')
tipp = 'stay'
if cek in sol['pp']:
sol['pp'].pop('cek')
'''The Movement from branching'''
while tipp == 'stay':
sol, tipp = movement_branch(tipp,sol,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4,ml,mr,md,mu,tip_l,tip_r,tip_d,tip_u) #2.2.(5)
'''Check Anastomosis'''
if not tipp == 'stay':
sol=anastomosis_tip_tip(sol,len(sol['matrix_tip'])-1) #2.2.(3)
return sol
def hybrid_tech(coef, set, sol): #2.23
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n']) #to save the value of 'n' at time step k (we are calculating at time step k+1)
# sol['vn_o'] = [] #to record tip cell position
# sol['bw'] = 0 #to detect backward list
sol['backward_list'] = [] #backward list
for nom in range(0,n_sp): #dicek setiap tip
if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
dirr, probb = movement_dir(coef, set, sol, xb, yb) #2.2.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
if not nom in sol['sp_stop']:
sol['sp_stop'].append(nom)
sol['cause'][nom] = 'no space'
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
sol['n'][xb,yb] = 0
sol['stalk'][xb,yb] = 1
else:
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
'''The Movement And Tip-Tip Anastomosis Checking'''
branch = False
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(2)
'''2.1 Branching Decision'''
PP = 'test'
if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
else: #there is possibility to branch
# Probability of Branching using c
list_prob = prob_by_c(sol,xb,yb) #range(1,11) #2.2.(4)
tes = randint(1,10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
else: #BRANCHING!
sol['life_time_tip'][nom] = 0
sol['matrix_tip'].append([[xb,yb]])
sol['life_time_tip'].append(0)
'''The Movement from branching'''
branch = True
nom = len(sol['matrix_tip'])-1
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,set,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4, branch) #2.2.(5)
if len(sol['backward_list']) > 0:
sol['backward_count'].append(set['k'])
# '''Create tip cell area'''
# for tip in sol['tip_cell']:
# sol['tip_cell_area'].append([tip[0]-2,tip[1]])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]])
# sol['tip_cell_area'].append([tip[0],tip[1]-2])
# sol['tip_cell_area'].append([tip[0],tip[1]+2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]+2])
# sol['tip_cell_area'].append([tip[0]+2,tip[1]-2])
# sol['tip_cell_area'].append([tip[0]-2,tip[1]-2])
sol['tip_cell_area'] = []
for i in sol['tip_cell']:
sol['tip_cell_area'].append([i[0]+1, i[1]+1])
sol['tip_cell_area'].append([i[0]+1, i[1]-1])
sol['tip_cell_area'].append([i[0]-1, i[1]+1])
sol['tip_cell_area'].append([i[0]-1, i[1]-1])
# '''Record New Tip Cell'''
# sol['tip_cell'] = []
# for nom in range(0,len(sol['matrix_tip'])): #dicek setiap tip
# if not nom in sol['sp_stop']: #record only active sprout
# sol['tip_cell'].append([sol['matrix_tip'][nom][-1][0],sol['matrix_tip'][nom][-1][1]])
return sol
def hybrid_tech(coef, set, sol): #2.2
n_sp = len(sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n']) #to save the value of 'n' at time step k (we are calculating at time step k+1)
vn_o = [] #to record tip cell position
for nom in range(0,n_sp): #dicek setiap tip
if not nom in sol['sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][1] #get y position of last tip position
vn_o.append([xb,yb])
dirr= movement_dir(coef, set, sol, xb, yb, nom) #2.2.1 => go to direction_of_movement.py
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[4] == 0: #checking if there is space for tip cell to move
sol['sp_stop'].append(nom)
sol['tip_cell'].remove([xb,yb])
sol['n'][xb,yb] = 0
else:
'''Making list of prob'''
list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = set_list_prob(dirr) #2.2.(1)
'''The Movement'''
sol,tipp,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4 = movement(sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4) #2.2.(2)
'''2.1 Branching Decision
PP = 'test'
if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA1'
if movi == True:
sol['PP'].remove([xb,yb])
sol['pp'].pop((xb,yb))
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA2'
#print sol['life_time_tip'][nom]
if sol['life_time_tip'][nom] < coef['T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA3'
# Probability of Branching using c
list_prob = range(1,11)#prob_by_c(sol,xb,yb) #2.2.(4)
tes = randint(1,10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #BRANCHING!
#print 'YAYAYA4'
sol['life_time_tip'][nom] = 0
sol['life_mit'][nom] += set['dt']
sol['matrix_tip'].append([(xb,yb)])
sol['life_time_tip'].append(0)
sol['life_mit'].append(0)
sol['list_tip_movement'].append('start')
tipp = 'stay'
# The Movement from branching
while tipp == 'stay':
sol, tipp = movement_branch(tipp,sol,nom,xb,yb,list_prob_0,list_prob_1,list_prob_2,list_prob_3,list_prob_4) #2.2.(5)
'''
'''Vector Velocity of stalk (Vb) Method 1:all towards tip cell'''
#profile 1: \/\
for y in range(1,set['Ny'],2):
for x in range(1,set['Nx'],2):
vb_x = 0
vb_y = 0
for ind, vec in enumerate(vn_o):
s = m.sqrt((x-vec[0])**2+(y-vec[1])**2)
if s <= 2:
h_s = 0
elif s <= 10:
h_s = 0.5 + coef['m1']*(s-10)
elif s <= 20:
h_s = 2 + coef['m2']*(s-20)
elif s <= 40:
h_s = 0 + coef['m3']*(s-40)
else:
h_s = 0
if s != 0:
vb_x += (vec[0]-x)*h_s/s #unit vector
vb_y += (vec[1]-y)*h_s/s #unit vector
sol['Vb_x'][x,y] = vb_x
sol['Vb_y'][x,y] = vb_y
#profile 2: /
for y in range(1,set['Ny'],2):
for x in range(1,set['Nx'],2):
vb_x = 0
vb_y = 0
for ind, vec in enumerate(vn_o):
s = m.sqrt((x-vec[0])**2+(y-vec[1])**2)
if s <= 2:
h_s = 0
elif s <= 50:
h_s = 1 + coef['m1']*(s-50)
else:
h_s = 1
if s != 0:
vb_x += (vec[0]-x)*h_s/s #unit vector
vb_y += (vec[1]-y)*h_s/s #unit vector
sol['Vb_x'][x,y] = vb_x
sol['Vb_y'][x,y] = vb_y
# print 'Tip cell position:', vn_o
# print 'Velocity Vector stalk on [3,201]: [',sol['Vb_x'][3,201],',',sol['Vb_y'][3,201],']'
return sol, n_o
def hybrid_tech_c(coef, set, sol): #2.2
n_sp = len(
sol['matrix_tip']) #to save original number of tips before branching
n_o = numpy.copy(sol['n'])
sol['loc_anas_tt'] = []
sol['loc_anas_tb'] = []
for nom in range(0, n_sp): #dicek setiap tip
if not nom in sol[
'sp_stop']: #kalo dia sudah anastomosis, gak perlu branching dan move lg.
xb = sol['matrix_tip'][nom][-1][
0] #get x position of last tip position
yb = sol['matrix_tip'][nom][-1][
1] #get y position of last tip position
'''Proliferation
if sol['life_mit'][nom] >= coef['T_mitosis']:
sol['life_mit'][nom] = 0
if sol['list_tip_movement'] == 'left':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0] - 2
ys = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'right':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0] + 2
ys = sol['matrix_tip'][nom][-1][1]
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'down':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0]
ys = sol['matrix_tip'][nom][-1][1] -2
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
elif sol['list_tip_movement'] == 'up':
if [xb,yb] in sol['tip_cell']:
sol['tip_cell'].remove([xb,yb])
xs = sol['matrix_tip'][nom][-1][0]
ys = sol['matrix_tip'][nom][-1][1] + 2
sol['matrix_tip'][nom].append((xs,ys))
sol['n'][xs,ys] = 1
sol['tip_cell'].append([xs,ys])
Proliferation'''
dirr = movement_dir(coef, set, sol, xb, yb, nom) #2.2.1 ok
'''Checking The movement if another tip meet nom'''
movi = False
if [xb, yb] in sol['PP']:
movi = True
if sol['pp'][(xb, yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb, yb)] == 'right':
dirr[1] == 0
elif sol['pp'][(xb, yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb, yb)] == 'down':
dirr[4] == 0
''' With No backward movement
if sol['list_tip_movement'][nom] == 'left':
dirr[2] == 0
if sol['pp'][(xb,yb)] == 'right':
dirr[1] == 0
elif sol['pp'][(xb,yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb,yb)] == 'down':
dirr[4] == 0
elif sol['list_tip_movement'][nom] == 'right':
dirr[1] == 0
if sol['pp'][(xb,yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb,yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb,yb)] == 'down':
dirr[4] == 0
elif sol['list_tip_movement'][nom] == 'down':
dirr[4] == 0
if sol['pp'][(xb,yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb,yb)] == 'up':
dirr[3] == 0
elif sol['pp'][(xb,yb)] == 'right':
dirr[1] == 0
elif sol['list_tip_movement'][nom] == 'up':
dirr[3] == 0
if sol['pp'][(xb,yb)] == 'left':
dirr[2] == 0
elif sol['pp'][(xb,yb)] == 'down':
dirr[4] == 0
elif sol['pp'][(xb,yb)] == 'right':
dirr[1] == 0
'''
if dirr[1] == 0 and dirr[2] == 0 and dirr[3] == 0 and dirr[
4] == 0: #if no space
sol['sp_stop'].append(nom)
sol['tip_cell'].remove([xb, yb])
else:
'''Making list of prob'''
list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = set_list_prob(
dirr) #2.2.(1)
'''The Movement'''
sol, tipp, list_prob_0, list_prob_1, list_prob_2, list_prob_3, list_prob_4 = movement(
sol, nom, xb, yb, list_prob_0, list_prob_1, list_prob_2,
list_prob_3, list_prob_4) #2.2.(2)
'''2.1 Branching Decision'''
PP = 'test'
if tipp == 'stay' and PP == 'test': #not able to branch, PP untuk pertama kali
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA1'
if movi == True:
sol['PP'].remove([xb, yb])
sol['pp'].pop((xb, yb))
if dirr.count(0) >= 3: #no space to move
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA2'
#print sol['life_time_tip'][nom]
if sol['life_time_tip'][nom] < coef[
'T_branch']: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #there is possibility to branch
#print 'YAYAYA3'
'''Probability of Branching using life time'''
list_prob = range(
1, 11) #prob_by_c(sol,xb,yb) #2.2.(4)
tes = randint(1, 10)
if not tes in list_prob: #not able to branch
sol['life_time_tip'][nom] += set['dt']
sol['life_mit'][nom] += set['dt']
else: #BRANCHING!
#print 'YAYAYA4'
sol['life_time_tip'][nom] = 0
sol['life_mit'][nom] += set['dt']
sol['matrix_tip'].append([(xb, yb)])
sol['life_time_tip'].append(0)
sol['life_mit'].append(0)
sol['list_tip_movement'].append('start')
tipp = 'stay'
'''The Movement from branching'''
while tipp == 'stay':
sol, tipp = movement_branch(
tipp, sol, nom, xb, yb, list_prob_0,
list_prob_1, list_prob_2, list_prob_3,
list_prob_4) #2.2.(5)
return sol, n_o
