def test_Vector_State1(self):
# state is a vector
state_list = ['y1:4']
param_list = []
# transitions call from the vector
transition_list = [
Transition(origin='y[0]',
destination='y[1]',
equation='0.04*y[0]',
transition_type=TransitionType.T),
Transition(origin='y[1]',
destination='y[0]',
equation='1e4*y[1]*y[2]',
transition_type=TransitionType.T),
Transition(origin='y[1]',
destination='y[2]',
equation='3e7*y[1]*y[1]',
transition_type=TransitionType.T)
]
# initialize the model
ode = DeterministicOde(state_list, param_list,
transition=transition_list)
ode.get_ode_eqn()
t = numpy.append(0, 4*numpy.logspace(-6, 6, 1000))
ode.initial_values = ([1.0, 0.0, 0.0], t[0])
# try to integrate to see if there is any problem
_solution, _output = ode.integrate(t[1::], full_output=True)
def test_Vector_State3(self):
# state is a vector
state_list = [ODEVariable('y1', 'y1'),
ODEVariable('y2', 's'),
ODEVariable('y3', 'x')]
param_list = []
# transitions are explicit names
transition_list = [
Transition(origin='y1',
destination='y2',
equation='0.04*y1',
transition_type=TransitionType.T),
Transition(origin='y2',
destination='y1',
equation='1e4*y2*y3',
transition_type=TransitionType.T),
Transition(origin='y2',
destination='y3',
equation='3e7*y2*y2',
transition_type=TransitionType.T)
]
ode = DeterministicOde(state_list, param_list,
transition=transition_list)
ode.get_ode_eqn()
t = numpy.append(0, 4*numpy.logspace(-6, 6, 1000))
ode.initial_values = ([1.0, 0.0, 0.0], t[0])
# try to integrate to see if there is any problem
solution, output = ode.integrate(t[1::], full_output=True)
def test_deterministic(self):
ode = DeterministicOde(self.states,
self.params,
birth_death=self.birth_deaths,
transition=self.transitions)
ode.parameters = self.param_eval
ode.initial_values = (self.x0, self.t[0])
_solution = ode.integrate(self.t[1::])
def test_deterministic(self):
ode = DeterministicOde(self.states,
self.params,
birth_death=self.birth_deaths,
transition=self.transitions)
ode.parameters = self.param_eval
ode.initial_values = (self.x0, self.t[0])
_solution = ode.integrate(self.t[1::])
)
]
# Build the model system
model_system = DeterministicOde(states,
parameters,
transition=transitions,
birth_death=births_deaths,
derived_param=derived_parameters)
model_system.print_ode()
# Create the timeline
t = numpy.linspace(0, 200, 200)
# Set the inital values for the states
model_system.initial_values = ([1000000, 20000, 15, 10, 0, 0], t[0])
liberia_parameters = {
'phi_H': 1.6,
'sigma_I': 0.1,
'sigma_H': 0.5,
'theta_I': 0.1,
'theta_H': 0.2,
'alpha': 0.1,
'tau': 0.16,
'Rec_rate': 1.7,
'p': 0.2,
'beta': 0.371,
'mu': (1 / 63) / 365,
'eta': 0.7,
}