def generate_molecules(self):
"""Generates the number of molecules prescribed by
self.verlhurst()
"""
for i in range(self.myosin_add):
self.mol_all.append(myosin(random()*self.width,random()*self.height))
for i in range(self.actin_add):
where = random()
if (where <= simulation_values.near_okt3_odds):
# Generates actin near OKT3 by choosing points near
# the first ok_count molecules which are the OKT3s
which = int(random()*float(simulation_values.ok_count))
okt3 = self.mol_all[which]
p = point_near(okt3.pos,5.)
self.mol_all.append(actin(p[0],p[1]))
else:
# Generates actin randomly on field
if simulation_values.ok_count == 1:
angle = random()*2.*np.pi
self.mol_all.append( \
actin((simulation_values.cortex_rad+3.)*random()*np.cos(angle)+50., \
(simulation_values.cortex_rad+3.)*random()*np.sin(angle)+50.) \
)
else:
self.mol_all.append(actin(random()*self.width,random()*self.height))
self.molecule_count()
def initialize(self):
"""Initializes the molecules for the start of the synapse
simulation. All myosin and actin are randomly places to
simulate t=0 where the T-cell has not been introduced to OKT3.
"""
if simulation_values.ok_count == 3:
# Generates 3 OKT3
a = okt3(25.,25.)
b = okt3(75.,25.)
c = okt3(50.,75.)
self.mol_all.append(a)
self.mol_all.append(b)
self.mol_all.append(c)
elif simulation_values.ok_count == 2:
# Generates 2 OKT3
for i in range(2):
mol = okt3(self.width/4.*(2.*(i+.5)),self.height/2.)
self.mol_all.append(mol)
elif simulation_values.ok_count == 1:
# Generates 1 OKT3
a = okt3(50.,50.)
self.mol_all.append(a)
if simulation_values.ok_count == 1:
# Generates actin radially for cortex
for i in range(simulation_values.num_act):
angle = random()*2.*np.pi
mol = actin( \
((simulation_values.cortex_rad+(random()-random())*4.+1.5))*np.cos(angle)+50., \
((simulation_values.cortex_rad+(random()-random())*4.+1.5))*np.sin(angle)+50.)
self.mol_all.append(mol)
else:
# Generates appropriate amount of myosin and actin for new
# population dynamics
for i in range(simulation_values.num_act):
mol = actin(random()*self.width,random()*self.height)
self.mol_all.append(mol)
#for i in range(int(simulation_values.carrying_capacity_myo*(5./8.))):
for i in range(simulation_values.num_myo):
mol = myosin(random()*self.width,random()*self.height)
self.mol_all.append(mol)
self.molecule_count()
