def __init__(self, params_names: list):
super(StochasticSEIRModel, self).__init__()
self._parameters = se.SEIRParameters(params_names)
# sets up n compartments, returns names of output variables
# Define the names of the compartments to record - default all
self._output_collector = se.StochasticOutputCollector(
['S', 'E', 'I', 'R'])
def __init__(self):
super(DeterministicSEIRModel, self).__init__()
# Assign default values
self._output_collector = seirmo.SEIROutputCollector(
['S', 'E', 'I', 'R', 'Incidence'])
self._parameters = seirmo.SEIRParameters(
['S0', 'E0', 'I0', 'R0', 'alpha', 'beta', 'gamma'])
def test_parameter_names(self):
testSubject = se.SEIRParameters(['a', 'b'])
self.assertEqual(['a', 'b'], testSubject.parameter_names())
def test_n_parameters(self):
testSubject = se.SEIRParameters(['a', 'b'])
self.assertEqual(2, testSubject.n_parameters())
def test__getitem__(self):
testSubject = se.SEIRParameters(['a', 'b'])
params = np.array([1, 2])
testSubject.configure_parameters(params)
for i in range(params.shape[0]):
self.assertEqual(params[i], testSubject[i])
def test_configureParametersError(self):
testSubject = se.SEIRParameters(['a', 'b'])
with self.assertRaises(AssertionError):
testSubject.configure_parameters(np.array([1, 2, 3]))
def test_configureParameters(self):
testSubject = se.SEIRParameters(['a', 'b'])
testSubject.configure_parameters(np.zeros((2, )))
def test__init__(self):
se.SEIRParameters([])