def test_hard(self):
# the SLIARD model is considered to be hard because a state can
# go to multiple state. This is not as hard as the SEIHFR model
# below.
stateList = ['S', 'L', 'I', 'A', 'R', 'D']
paramList = [
'beta', 'p', 'kappa', 'alpha', 'f', 'delta', 'epsilon', 'N'
]
odeList = [
Transition('S', '- beta * S/N * ( I + delta * A)', 'ODE'),
Transition('L', 'beta * S/N * (I + delta * A) - kappa * L', 'ODE'),
Transition('I', 'p * kappa * L - alpha * I', 'ODE'),
Transition('A', '(1-p) * kappa * L - epsilon * A', 'ODE'),
Transition('R', 'f * alpha * I + epsilon * A', 'ODE'),
Transition('D', '(1-f) * alpha * I', 'ODE')
]
ode = SimulateOdeModel(stateList, paramList, odeList=odeList)
ode2 = ode.returnObjWithTransitionsAndBD()
diffEqZero = map(lambda x: x == 0,
sympy.simplify(ode.getOde() - ode2.getOde()))
if numpy.any(numpy.array(list(diffEqZero)) == False):
raise Exception("Hard: SLIARD Decomposition failed")
def test_simple(self):
ode1 = Transition('S','-beta*S*I', 'ode')
ode2 = Transition('I','beta*S*I - gamma * I', 'ode')
ode3 = Transition('R','gamma*I', 'ode')
stateList = ['S','I','R']
paramList = ['beta','gamma']
ode = SimulateOdeModel(stateList, paramList, odeList=[ode1,ode2,ode3])
ode2 = ode.returnObjWithTransitionsAndBD()
diffEqZero = map(lambda x: x==0, sympy.simplify(ode.getOde() - ode2.getOde()))
if numpy.any(numpy.array(diffEqZero) == False):
raise Exception("Simple: SIR Decomposition failed")
def test_simple(self):
ode1 = Transition('S', '-beta*S*I', 'ode')
ode2 = Transition('I', 'beta*S*I - gamma * I', 'ode')
ode3 = Transition('R', 'gamma*I', 'ode')
stateList = ['S', 'I', 'R']
paramList = ['beta', 'gamma']
ode = SimulateOdeModel(stateList,
paramList,
odeList=[ode1, ode2, ode3])
ode2 = ode.returnObjWithTransitionsAndBD()
diffEqZero = map(lambda x: x == 0,
sympy.simplify(ode.getOde() - ode2.getOde()))
if numpy.any(numpy.array(list(diffEqZero)) == False):
raise Exception("Simple: SIR Decomposition failed")
def test_hard(self):
# the SLIARD model is considered to be hard because a state can
# go to multiple state. This is not as hard as the SEIHFR model
# below.
stateList = ['S', 'L','I','A','R','D']
paramList = ['beta','p','kappa','alpha','f','delta','epsilon', 'N']
odeList = [
Transition('S', '- beta * S/N * ( I + delta * A)', 'ODE'),
Transition('L', 'beta * S/N * (I + delta * A) - kappa * L', 'ODE'),
Transition('I', 'p * kappa * L - alpha * I', 'ODE'),
Transition('A', '(1-p) * kappa * L - epsilon * A', 'ODE'),
Transition('R', 'f * alpha * I + epsilon * A', 'ODE'),
Transition('D', '(1-f) * alpha * I', 'ODE')
]
ode = SimulateOdeModel(stateList, paramList, odeList=odeList)
ode2 = ode.returnObjWithTransitionsAndBD()
diffEqZero = map(lambda x: x==0, sympy.simplify(ode.getOde() - ode2.getOde()))
if numpy.any(numpy.array(diffEqZero) == False):
raise Exception("Hard: SLIARD Decomposition failed")
def test_bd(self):
stateList = ['S', 'I', 'R']
paramList = ['beta', 'gamma', 'B', 'mu']
odeList = [
Transition(origState='S',
equation='-beta * S * I + B - mu * S',
transitionType=TransitionType.ODE),
Transition(origState='I',
equation='beta * S * I - gamma * I - mu * I',
transitionType=TransitionType.ODE),
Transition(origState='R',
destState='R',
equation='gamma * I',
transitionType=TransitionType.ODE)
]
ode = SimulateOdeModel(stateList, paramList, odeList=odeList)
ode2 = ode.returnObjWithTransitionsAndBD()
diffEqZero = map(lambda x: x==0, sympy.simplify(ode.getOde() - ode2.getOde()))
if numpy.any(numpy.array(diffEqZero) == False):
raise Exception("Birth Death: SIR+BD Decomposition failed")
def test_bd(self):
stateList = ['S', 'I', 'R']
paramList = ['beta', 'gamma', 'B', 'mu']
odeList = [
Transition(origState='S',
equation='-beta * S * I + B - mu * S',
transitionType=TransitionType.ODE),
Transition(origState='I',
equation='beta * S * I - gamma * I - mu * I',
transitionType=TransitionType.ODE),
Transition(origState='R',
destState='R',
equation='gamma * I',
transitionType=TransitionType.ODE)
]
ode = SimulateOdeModel(stateList, paramList, odeList=odeList)
ode2 = ode.returnObjWithTransitionsAndBD()
diffEqZero = map(lambda x: x == 0,
sympy.simplify(ode.getOde() - ode2.getOde()))
if numpy.any(numpy.array(list(diffEqZero)) == False):
raise Exception("Birth Death: SIR+BD Decomposition failed")
