def test_set_outputs(self):
model = em.PheSEIRModel()
outputs = ['S', 'I1', 'I2', 'Incidence']
model.set_outputs(outputs)
with self.assertRaises(ValueError):
outputs1 = ['S', 'E', 'I1', 'I2', 'Incidence']
model.set_outputs(outputs1)
def test__init__(self):
model = em.PheSEIRModel()
self.assertEqual(model._output_names,
['S', 'E1', 'E2', 'I1', 'I2', 'R', 'Incidence'])
self.assertEqual(
model._parameter_names,
['S0', 'E10', 'E20', 'I10', 'I20', 'R0', 'beta', 'kappa', 'gamma'])
self.assertEqual(model._n_outputs, 7)
self.assertEqual(model._n_parameters, 9)
def test_samples_positive_tests(self):
model = em.PheSEIRModel()
# Populate the model
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[1, 0], [0, 3]])
contact_data_matrix_1 = np.array([[10, 5.2], [0, 3]])
region_data_matrix_0_0 = np.array([[0.5, 0], [0, 6]])
region_data_matrix_0_1 = np.array([[1, 10], [1, 0]])
region_data_matrix_1_0 = np.array([[0.5, 1.2], [0.29, 6]])
region_data_matrix_1_1 = np.array([[0.85, 1], [0.9, 6]])
susceptibles = [[5, 6], [7, 8]]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
contacts_1 = em.ContactMatrix(age_groups, contact_data_matrix_1)
regional_0_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_0_0)
regional_0_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_0_1)
regional_1_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_1_0)
regional_1_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_1_1)
# Matrices contact
matrices_contact = [contacts_0, contacts_1]
time_changes_contact = [1, 3]
matrices_region = [[regional_0_0, regional_0_1],
[regional_1_0, regional_1_1]]
time_changes_region = [1, 2]
model.set_regions(regions)
model.read_contact_data(matrices_contact, time_changes_contact)
model.read_regional_data(matrices_region, time_changes_region)
initial_r = [0.5, 1]
parameters = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0.1, 0.2], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.5, 'my-solver'
]
times = [1, 2]
output = model.simulate(list(deepflatten(parameters, ignore=str)),
times)
tests = [[20, 30], [10, 0]]
sens = 0.9
spec = 0.1
self.assertEqual(
model.samples_positive_tests(output, tests[0], sens, spec,
0).shape, (len(age_groups), ))
with self.assertRaises(TypeError):
model.samples_positive_tests(output, tests[0], sens, spec, '1')
with self.assertRaises(ValueError):
model.samples_positive_tests(output, tests[0], sens, spec, -1)
with self.assertRaises(ValueError):
model.samples_positive_tests(output, tests[0], sens, spec, 3)
def test_check_positives_format(self):
model = em.PheSEIRModel()
# Populate the model
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[1, 0], [0, 3]])
contact_data_matrix_1 = np.array([[10, 5.2], [0, 3]])
region_data_matrix_0_0 = np.array([[0.5, 0], [0, 6]])
region_data_matrix_0_1 = np.array([[1, 10], [1, 0]])
region_data_matrix_1_0 = np.array([[0.5, 1.2], [0.29, 6]])
region_data_matrix_1_1 = np.array([[0.85, 1], [0.9, 6]])
susceptibles = [[5, 6], [7, 8]]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
contacts_1 = em.ContactMatrix(age_groups, contact_data_matrix_1)
regional_0_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_0_0)
regional_0_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_0_1)
regional_1_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_1_0)
regional_1_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_1_1)
# Matrices contact
matrices_contact = [contacts_0, contacts_1]
time_changes_contact = [1, 3]
matrices_region = [[regional_0_0, regional_0_1],
[regional_1_0, regional_1_1]]
time_changes_region = [1, 2]
model.set_regions(regions)
model.read_contact_data(matrices_contact, time_changes_contact)
model.read_regional_data(matrices_region, time_changes_region)
initial_r = [0.5, 1]
parameters = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0.1, 0.2], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.5, 'my-solver'
]
times = [1, 2]
output = model.simulate(list(deepflatten(parameters, ignore=str)),
times)
tests = [[20, 30], [10, 0]]
sens = 0.9
spec = 0.1
with self.assertRaises(ValueError):
output1 = np.array([5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
model.check_positives_format(output1, tests, sens, spec)
with self.assertRaises(ValueError):
output1 = np.array([[5, 6, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, 0, 0, 0, 0, 0, 0, 0, 0]])
model.check_positives_format(output1, tests, sens, spec)
with self.assertRaises(ValueError):
output1 = np.array([[5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
model.check_positives_format(output1, tests, sens, spec)
with self.assertRaises(TypeError):
output1 = np.array([['5', 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, '0', 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
model.check_positives_format(output1, tests, sens, spec)
with self.assertRaises(ValueError):
tests1 = 100
model.check_positives_format(output, tests1, sens, spec)
with self.assertRaises(ValueError):
tests1 = np.array([2, 50])
model.check_positives_format(output, tests1, sens, spec)
with self.assertRaises(ValueError):
tests1 = np.array([[20, 30, 1], [10, 0, 0]])
model.check_positives_format(output, tests1, sens, spec)
with self.assertRaises(TypeError):
tests1 = np.array([[20, '30'], [10, 0]])
model.check_positives_format(output, tests1, sens, spec)
with self.assertRaises(ValueError):
tests1 = np.array([[-1, 50], [10, 0]])
model.check_positives_format(output, tests1, sens, spec)
with self.assertRaises(TypeError):
model.check_positives_format(output, tests, '0.9', spec)
with self.assertRaises(ValueError):
model.check_positives_format(output, tests, -0.2, spec)
with self.assertRaises(ValueError):
model.check_positives_format(output, tests, 1.2, spec)
with self.assertRaises(TypeError):
model.check_positives_format(output, tests, sens, '0.1')
with self.assertRaises(ValueError):
model.check_positives_format(output, tests, sens, -0.1)
with self.assertRaises(ValueError):
model.check_positives_format(output, tests, sens, 1.2)
def test_simulate(self):
model = em.PheSEIRModel()
# Populate the model
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[1, 0], [0, 3]])
contact_data_matrix_1 = np.array([[10, 5.2], [0, 3]])
region_data_matrix_0_0 = np.array([[0.5, 0], [0, 6]])
region_data_matrix_0_1 = np.array([[1, 10], [1, 0]])
region_data_matrix_1_0 = np.array([[0.5, 1.2], [0.29, 6]])
region_data_matrix_1_1 = np.array([[0.85, 1], [0.9, 6]])
susceptibles = [[5, 6], [7, 8]]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
contacts_1 = em.ContactMatrix(age_groups, contact_data_matrix_1)
regional_0_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_0_0)
regional_0_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_0_1)
regional_1_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_1_0)
regional_1_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_1_1)
# Matrices contact
matrices_contact = [contacts_0, contacts_1]
time_changes_contact = [1, 3]
matrices_region = [[regional_0_0, regional_0_1],
[regional_1_0, regional_1_1]]
time_changes_region = [1, 2]
model.set_regions(regions)
model.read_contact_data(matrices_contact, time_changes_contact)
model.read_regional_data(matrices_region, time_changes_region)
initial_r = [0.5, 1]
parameters = [
initial_r, 2, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.5, 'RK45'
]
times = [1, 2]
output_my_solver = model.simulate(
list(deepflatten(parameters, ignore=str)), times)
npt.assert_almost_equal(
output_my_solver,
np.array([[7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]),
decimal=3)
parameters[-1] = 'my-solver'
output_scipy_solver = model.simulate(
list(deepflatten(parameters, ignore=str)), times)
npt.assert_almost_equal(
output_scipy_solver,
np.array([[7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[7, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]),
decimal=3)
parameters[-1] = 'my-solver'
with self.assertRaises(TypeError):
model.simulate(list(deepflatten(parameters, ignore=str)), '0')
with self.assertRaises(TypeError):
model.simulate(list(deepflatten(parameters, ignore=str)), ['1', 2])
with self.assertRaises(ValueError):
model.simulate(list(deepflatten(parameters, ignore=str)), [0, 1])
with self.assertRaises(TypeError):
model.simulate('parameters', times)
with self.assertRaises(ValueError):
model.simulate([0], times)
with self.assertRaises(TypeError):
parameters1 = [
initial_r, 0.5, susceptibles, [[0, 0], [0, 0]], [[0, 0],
[0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=(str, float))),
times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 0, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 3, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
susceptibles1 = [5, 6]
parameters1 = [
initial_r, 1, susceptibles1, [[0, 0], [0, 0]], [[0, 0], [0,
0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]],
[[0, 0], [0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[1] * 2, [1] * 2], 4, dI, 0.5, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0, 0], [0, 0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[[1] * 2, [1] * 2], [[1] * 2, [1] * 2]], 4, dI, 0.005,
'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2, [1] * 2], 4, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 4, [1] * 4], 4, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(TypeError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], '4', dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], -1, dI, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(TypeError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, '4', 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, 0, 0.005, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(TypeError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, '0.005', 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0, 'my-solver'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(TypeError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.5, 3
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
with self.assertRaises(ValueError):
parameters1 = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.5, 'my-solver2'
]
model.simulate(list(deepflatten(parameters1, ignore=str)), times)
def test_samples_deaths(self):
model = em.PheSEIRModel()
# Populate the model
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[1, 0], [0, 3]])
contact_data_matrix_1 = np.array([[10, 5.2], [0, 3]])
region_data_matrix_0_0 = np.array([[0.5, 0], [0, 6]])
region_data_matrix_0_1 = np.array([[1, 10], [1, 0]])
region_data_matrix_1_0 = np.array([[0.5, 1.2], [0.29, 6]])
region_data_matrix_1_1 = np.array([[0.85, 1], [0.9, 6]])
susceptibles = [[5, 6], [7, 8]]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
contacts_1 = em.ContactMatrix(age_groups, contact_data_matrix_1)
regional_0_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_0_0)
regional_0_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_0_1)
regional_1_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_1_0)
regional_1_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_1_1)
# Matrices contact
matrices_contact = [contacts_0, contacts_1]
time_changes_contact = [1, 3]
matrices_region = [[regional_0_0, regional_0_1],
[regional_1_0, regional_1_1]]
time_changes_region = [1, 2]
model.set_regions(regions)
model.read_contact_data(matrices_contact, time_changes_contact)
model.read_regional_data(matrices_region, time_changes_region)
initial_r = [0.5, 1]
parameters = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0.1, 0.2], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 60, [1] * 60], 4, dI, 0.5, 'my-solver'
]
times = np.arange(1, 61).tolist()
output = model.simulate(list(deepflatten(parameters, ignore=str)),
times)
new_infections = model.new_infections(output)
fatality_ratio = [0.1, 0.5]
td_mean = 15.0
td_var = 12.1**2
theta = td_var / td_mean
k = td_mean / theta
time_to_death = gamma(k, scale=theta).pdf(np.arange(1, 60)).tolist()
self.assertEqual(
model.samples_deaths(new_infections, fatality_ratio, time_to_death,
0.5, 41).shape, (len(age_groups), ))
self.assertEqual(
model.samples_deaths(new_infections, fatality_ratio, time_to_death,
0.5, 1).shape, (len(age_groups), ))
with self.assertRaises(ValueError):
model.samples_deaths(new_infections, fatality_ratio, time_to_death,
0.5, -1)
with self.assertRaises(TypeError):
model.samples_deaths(new_infections, fatality_ratio, time_to_death,
0.5, '1')
with self.assertRaises(ValueError):
model.samples_deaths(new_infections, fatality_ratio, time_to_death,
0.5, 62)
def test_set_age_groups(self):
model = em.PheSEIRModel()
age_groups = ['0-10', '10-20']
model.set_age_groups(age_groups)
self.assertEqual(model.age_groups_names(), ['0-10', '10-20'])
def test_set_regions(self):
model = em.PheSEIRModel()
regions = ['London', 'Cornwall']
model.set_regions(regions)
self.assertEqual(model.region_names(), ['London', 'Cornwall'])
def test_check_death_format(self):
model = em.PheSEIRModel()
# Populate the model
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[1, 0], [0, 3]])
contact_data_matrix_1 = np.array([[10, 5.2], [0, 3]])
region_data_matrix_0_0 = np.array([[0.5, 0], [0, 6]])
region_data_matrix_0_1 = np.array([[1, 10], [1, 0]])
region_data_matrix_1_0 = np.array([[0.5, 1.2], [0.29, 6]])
region_data_matrix_1_1 = np.array([[0.85, 1], [0.9, 6]])
susceptibles = [[5, 6], [7, 8]]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
contacts_1 = em.ContactMatrix(age_groups, contact_data_matrix_1)
regional_0_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_0_0)
regional_0_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_0_1)
regional_1_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_1_0)
regional_1_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_1_1)
# Matrices contact
matrices_contact = [contacts_0, contacts_1]
time_changes_contact = [1, 3]
matrices_region = [[regional_0_0, regional_0_1],
[regional_1_0, regional_1_1]]
time_changes_region = [1, 2]
model.set_regions(regions)
model.read_contact_data(matrices_contact, time_changes_contact)
model.read_regional_data(matrices_region, time_changes_region)
initial_r = [0.5, 1]
parameters = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0.1, 0.2], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.5, 'my-solver'
]
times = [1, 2]
output = model.simulate(list(deepflatten(parameters, ignore=str)),
times)
new_infections = model.new_infections(output)
fatality_ratio = [0.1, 0.5]
time_to_death = [0.5, 0.5]
with self.assertRaises(TypeError):
model.check_death_format(new_infections, fatality_ratio,
time_to_death, '0.5')
with self.assertRaises(ValueError):
model.check_death_format(new_infections, fatality_ratio,
time_to_death, -2)
with self.assertRaises(ValueError):
new_infections1 = \
np.array([5, 6])
model.check_death_format(new_infections1, fatality_ratio,
time_to_death, 0.5)
with self.assertRaises(ValueError):
new_infections1 = np.array([[5, 6, 0, 0], [5, 6, 0, 0]])
model.check_death_format(new_infections1, fatality_ratio,
time_to_death, 0.5)
with self.assertRaises(ValueError):
new_infections1 = np.array([[5, 6], [5, 6], [5, 6]])
model.check_death_format(new_infections1, fatality_ratio,
time_to_death, 0.5)
with self.assertRaises(TypeError):
new_infections1 = np.array([['5', 6], [5, '0']])
model.check_death_format(new_infections1, fatality_ratio,
time_to_death, 0.5)
with self.assertRaises(ValueError):
fatality_ratio1 = 0
model.check_death_format(new_infections, fatality_ratio1,
time_to_death, 0.5)
with self.assertRaises(ValueError):
fatality_ratio1 = np.array([0.1, 0.5, 0.1])
model.check_death_format(new_infections, fatality_ratio1,
time_to_death, 0.5)
with self.assertRaises(TypeError):
fatality_ratio1 = np.array([0.1, '0.5'])
model.check_death_format(new_infections, fatality_ratio1,
time_to_death, 0.5)
with self.assertRaises(ValueError):
fatality_ratio1 = np.array([-0.1, 0.5])
model.check_death_format(new_infections, fatality_ratio1,
time_to_death, 0.5)
with self.assertRaises(ValueError):
fatality_ratio1 = np.array([0.1, 1.5])
model.check_death_format(new_infections, fatality_ratio1,
time_to_death, 0.5)
with self.assertRaises(ValueError):
time_to_death1 = np.array([[0.5], [0.5]])
model.check_death_format(new_infections, fatality_ratio,
time_to_death1, 0.5)
with self.assertRaises(ValueError):
time_to_death1 = np.array([0.5, 0.5, 0.15])
model.check_death_format(new_infections, fatality_ratio,
time_to_death1, 0.5)
with self.assertRaises(TypeError):
time_to_death1 = np.array(['0.1', 0.5])
model.check_death_format(new_infections, fatality_ratio,
time_to_death1, 0.5)
with self.assertRaises(ValueError):
time_to_death1 = np.array([-0.1, 0.5])
model.check_death_format(new_infections, fatality_ratio,
time_to_death1, 0.5)
with self.assertRaises(ValueError):
time_to_death1 = np.array([0.5, 1.1])
model.check_death_format(new_infections, fatality_ratio,
time_to_death1, 0.5)
def test_parameter_names(self):
model = em.PheSEIRModel()
self.assertEqual(
model.parameter_names(),
['S0', 'E10', 'E20', 'I10', 'I20', 'R0', 'beta', 'kappa', 'gamma'])
def test_output_names(self):
model = em.PheSEIRModel()
self.assertEqual(model.output_names(),
['S', 'E1', 'E2', 'I1', 'I2', 'R', 'Incidence'])
def test_n_parameters(self):
model = em.PheSEIRModel()
self.assertEqual(model.n_parameters(), 9)
def test_new_infections(self):
model = em.PheSEIRModel()
# Populate the model
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[1, 0], [0, 3]])
contact_data_matrix_1 = np.array([[10, 5.2], [0, 3]])
region_data_matrix_0_0 = np.array([[0.5, 0], [0, 6]])
region_data_matrix_0_1 = np.array([[1, 10], [1, 0]])
region_data_matrix_1_0 = np.array([[0.5, 1.2], [0.29, 6]])
region_data_matrix_1_1 = np.array([[0.85, 1], [0.9, 6]])
susceptibles = [[5, 6], [7, 8]]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
contacts_1 = em.ContactMatrix(age_groups, contact_data_matrix_1)
regional_0_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_0_0)
regional_0_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_0_1)
regional_1_0 = em.RegionMatrix(regions[0], age_groups,
region_data_matrix_1_0)
regional_1_1 = em.RegionMatrix(regions[1], age_groups,
region_data_matrix_1_1)
# Matrices contact
matrices_contact = [contacts_0, contacts_1]
time_changes_contact = [1, 3]
matrices_region = [[regional_0_0, regional_0_1],
[regional_1_0, regional_1_1]]
time_changes_region = [1, 2]
model.set_regions(regions)
model.read_contact_data(matrices_contact, time_changes_contact)
model.read_regional_data(matrices_region, time_changes_region)
initial_r = [0.5, 1]
parameters = [
initial_r, 1, susceptibles, [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[0, 0], [0, 0]], [[0, 0], [0, 0]], [[0, 0], [0, 0]],
[[1] * 2, [1] * 2], 4, dI, 0.5, 'my-solver'
]
times = [1, 2]
output = model.simulate(list(deepflatten(parameters, ignore=str)),
times)
npt.assert_array_equal(model.new_infections(output),
np.array([[0, 0], [0, 0]]))
with self.assertRaises(ValueError):
output1 = np.array([5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
model.new_infections(output1)
with self.assertRaises(ValueError):
output1 = np.array([[5, 6, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, 0, 0, 0, 0, 0, 0, 0, 0]])
model.new_infections(output1)
with self.assertRaises(ValueError):
output1 = np.array([[5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
model.new_infections(output1)
with self.assertRaises(TypeError):
output1 = np.array([['5', 6, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[5, 6, '0', 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
model.new_infections(output1)
def test_n_outputs(self):
model = em.PheSEIRModel()
self.assertEqual(model.n_outputs(), 7)