def test__init__(self):
region_name = 'London'
age_groups = ['0-10', '10-25']
contact_data_matrix = np.array([[10, 5.2], [0, 3]])
region_data_matrix = np.array([[0.5, 1.2], [0.29, 6]])
pop_size = [18, 2]
dI = 4
contacts = em.ContactMatrix(age_groups, contact_data_matrix)
regional = em.RegionMatrix(region_name, age_groups, region_data_matrix)
next_gen = em.UniNextGenMatrix(pop_size, contacts, regional, dI)
self.assertEqual(next_gen.region, 'London')
npt.assert_array_equal(next_gen.ages, np.array(['0-10', '10-25']))
npt.assert_array_equal(next_gen.susceptibles, np.array([18, 2]))
npt.assert_array_equal(next_gen.contacts, contact_data_matrix)
npt.assert_array_equal(next_gen.regional_suscep, region_data_matrix)
self.assertEqual(next_gen.infection_period, 4)
pdt.assert_frame_equal(
next_gen.get_next_gen_matrix(),
pd.DataFrame(data=np.array([[360, 449.28], [0, 144]]),
index=['0-10', '10-25'],
columns=['0-10', '10-25']))
with self.assertRaises(TypeError):
em.UniNextGenMatrix(pop_size, 0, regional, dI)
with self.assertRaises(TypeError):
em.UniNextGenMatrix(pop_size, contacts, 0, dI)
with self.assertRaises(ValueError):
new_age_groups = ['0-15', '15-25']
regional1 = em.RegionMatrix(region_name, new_age_groups,
region_data_matrix)
em.UniNextGenMatrix(pop_size, contacts, regional1, dI)
with self.assertRaises(TypeError):
em.UniNextGenMatrix(pop_size, contacts, regional, '4')
with self.assertRaises(ValueError):
em.UniNextGenMatrix(pop_size, contacts, regional, 0)
with self.assertRaises(ValueError):
em.UniNextGenMatrix([[1], [2]], contacts, regional, dI)
with self.assertRaises(ValueError):
em.UniNextGenMatrix([0, 1, 1], contacts, regional, dI)
with self.assertRaises(ValueError):
em.UniNextGenMatrix([0, -1], contacts, regional, dI)
with self.assertRaises(TypeError):
em.UniNextGenMatrix([0, '1'], contacts, regional, dI)
def test__init__(self):
region_name = 'London'
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[10, 0], [0, 3]])
region_data_matrix_0 = np.array([[0.5, 0], [0, 6]])
init_pop_size = [1, 2]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
regional_0 = em.RegionMatrix(region_name, age_groups,
region_data_matrix_0)
next_gen_0 = em.UniNextGenMatrix(init_pop_size, contacts_0, regional_0,
dI)
initial_r = 0.5
infect = em.UniInfectivityMatrix(initial_r,
initial_nextgen_matrix=next_gen_0)
self.assertEqual(infect.r0, 0.5)
self.assertEqual(infect.r0_star, 144)
with self.assertRaises(TypeError):
em.UniInfectivityMatrix('0', initial_nextgen_matrix=next_gen_0)
with self.assertRaises(TypeError):
em.UniInfectivityMatrix(initial_r, initial_nextgen_matrix=0)
def __init__(self):
# Instantiate model
super(TestPHEModel, self).__init__()
# Populate the model
regions = ['SW']
age_groups = [
'65-75', '75+']
matrices_region = []
# Initial state of the system
weeks_matrices_region = []
for r in regions:
region_data_matrix = np.array([[0.5025, 0.1977], [0.1514, 0.7383]])
regional = em.RegionMatrix(r, age_groups, region_data_matrix)
weeks_matrices_region.append(regional)
matrices_region.append(weeks_matrices_region)
contacts = em.ContactMatrix(
age_groups, np.ones((len(age_groups), len(age_groups))))
matrices_contact = [contacts]
# Matrices contact
time_changes_contact = [1]
time_changes_region = [1]
# Set the region names, age groups, contact and regional data of the
# model
self.set_regions(regions)
self.set_age_groups(age_groups)
self.read_contact_data(matrices_contact, time_changes_contact)
self.read_regional_data(matrices_region, time_changes_region)
def test_plot_heat_map(self):
with patch('plotly.graph_objs.Figure.show') as show_patch:
region_name = 'London'
age_groups = ['0-10', '10-25']
data_matrix = np.array([[10, 5.2], [0, 3]])
r = em.RegionMatrix(region_name, age_groups, data_matrix)
r.plot_heat_map()
# Assert show_figure is called once
assert show_patch.called
def test_compute_reproduction_number(self):
region_name = 'London'
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[10, 0], [0, 3]])
region_data_matrix_0 = np.array([[0.5, 0], [0, 6]])
init_pop_size = [1, 2]
dI = 4
contacts_0 = em.ContactMatrix(age_groups, contact_data_matrix_0)
regional_0 = em.RegionMatrix(region_name, age_groups,
region_data_matrix_0)
next_gen_0 = em.UniNextGenMatrix(init_pop_size, contacts_0, regional_0,
dI)
# Later time state of the system
contact_data_matrix_1 = np.array([[10, 5.2], [0, 3]])
region_data_matrix_1 = np.array([[0.5, 1.2], [0.29, 6]])
current_pop_size = [18, 2]
contacts_1 = em.ContactMatrix(age_groups, contact_data_matrix_1)
regional_1 = em.RegionMatrix(region_name, age_groups,
region_data_matrix_1)
next_gen_1 = em.UniNextGenMatrix(current_pop_size, contacts_1,
regional_1, dI)
initial_r = 0.5
temp_variation = 1
infect = em.UniInfectivityMatrix(initial_r,
initial_nextgen_matrix=next_gen_0)
self.assertEqual(
infect.compute_reproduction_number(temp_variation, next_gen_1),
5 / 4)
with self.assertRaises(TypeError):
infect.compute_reproduction_number('1', next_gen_1)
with self.assertRaises(TypeError):
infect.compute_reproduction_number(temp_variation, 0)
def test_change_region_name(self):
region_name = 'London'
age_groups = ['0-10', '10-25']
data_matrix = np.array([[10, 5.2], [0, 3]])
r = em.RegionMatrix(region_name, age_groups, data_matrix)
new_region_name = 'Oxford'
r.change_region_name(new_region_name)
self.assertEqual(r.region, 'Oxford')
with self.assertRaises(TypeError):
r.change_region_name(0)
def test_compute_dom_eigenvalue(self):
region_name = 'London'
age_groups = ['0-10', '10-25']
contact_data_matrix = np.array([[10, 0], [0, 3]])
region_data_matrix = np.array([[0.5, 0], [0, 6]])
pop_size = [1, 2]
dI = 4
contacts = em.ContactMatrix(age_groups, contact_data_matrix)
regional = em.RegionMatrix(region_name, age_groups, region_data_matrix)
next_gen = em.UniNextGenMatrix(pop_size, contacts, regional, dI)
self.assertEqual(next_gen.compute_dom_eigenvalue(), 144)
def test__init__(self):
region_name = 'London'
age_groups = ['0-10', '10-25']
data_matrix = np.array([[10, 5.2], [0, 3]])
r = em.RegionMatrix(region_name, age_groups, data_matrix)
self.assertEqual(r.region, 'London')
self.assertEqual(r.num_a_groups, 2)
npt.assert_array_equal(r.ages, np.array(['0-10', '10-25']))
pdt.assert_frame_equal(
r.region_matrix,
pd.DataFrame(data=np.array([[10, 5.2], [0, 3]]),
index=['0-10', '10-25'],
columns=['0-10', '10-25']))
with self.assertRaises(ValueError):
em.RegionMatrix(region_name, '0', data_matrix)
with self.assertRaises(TypeError):
em.RegionMatrix(region_name, [0, '1'], data_matrix)
with self.assertRaises(TypeError):
em.RegionMatrix(region_name, ['0', 1], data_matrix)
with self.assertRaises(ValueError):
em.RegionMatrix(region_name, age_groups, [1])
with self.assertRaises(ValueError):
em.RegionMatrix(region_name, age_groups,
np.array([[10, 5, 0], [0, 0, 3]]))
with self.assertRaises(ValueError):
em.RegionMatrix(region_name, age_groups,
np.array([[10, 5], [0, 3], [0, 0]]))
with self.assertRaises(TypeError):
em.RegionMatrix(region_name, age_groups,
np.array([[10, 5], [0, '3']]))
with self.assertRaises(TypeError):
em.RegionMatrix([0], age_groups, data_matrix)
def test_change_age_groups(self):
region_name = 'London'
age_groups = ['0-10', '10-25']
data_matrix = np.array([[10, 5.2], [0, 3]])
r = em.RegionMatrix(region_name, age_groups, data_matrix)
new_age_groups = ['0-15', '15-25']
r.change_age_groups(new_age_groups)
self.assertEqual(r.num_a_groups, 2)
npt.assert_array_equal(r.ages, np.asarray(['0-15', '15-25']))
pdt.assert_frame_equal(
r.region_matrix,
pd.DataFrame(data=np.array([[10, 5.2], [0, 3]]),
index=['0-15', '15-25'],
columns=['0-15', '15-25']))
with self.assertRaises(ValueError):
r.change_age_groups(['0-15', '15-25', '25+'])
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__init__(self):
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[10, 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 = [[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[0, 2], [1, 1]]]
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]
initial_r = [0.5, 1]
m = em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, dI,
susceptibles[0])
self.assertEqual(m._regions, ['London', 'Cornwall'])
npt.assert_array_equal(m.initial_r, np.array([0.5, 1]))
self.assertEqual(m.dI, 4)
npt.assert_array_equal(m.times_contact, np.array([1, 3]))
npt.assert_array_equal(m.times_region, np.array([1, 2]))
self.assertCountEqual(m.contact_matrices, matrices_contact)
self.assertCountEqual(m.region_matrices, matrices_region)
self.assertEqual(len(m.initial_infec_matrices), 2)
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(0, time_changes_contact, regions,
matrices_region, time_changes_region,
initial_r, dI, susceptibles[0])
with self.assertRaises(TypeError):
em.MultiTimesInfectivity([contacts_0, 0], time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, dI,
susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, 1, regions,
matrices_region, time_changes_region,
initial_r, dI, susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, [1], regions,
matrices_region, time_changes_region,
initial_r, dI, susceptibles[0])
with self.assertRaises(TypeError):
em.MultiTimesInfectivity(matrices_contact, [1, 1.5], regions,
matrices_region, time_changes_region,
initial_r, dI, susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, [0, 1], regions,
matrices_region, time_changes_region,
initial_r, dI, susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
'London', matrices_region,
time_changes_region, initial_r, dI,
susceptibles[0])
with self.assertRaises(TypeError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
[0, 'London'], matrices_region,
time_changes_region, initial_r, dI,
susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, [regional_1_0, regional_1_1],
time_changes_region, initial_r, dI,
susceptibles[0])
with self.assertRaises(ValueError):
matrices_region_1 = [[regional_0_0], [regional_1_0]]
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region_1,
time_changes_region, initial_r, dI,
susceptibles[0])
with self.assertRaises(TypeError):
matrices_region_1 = [[regional_0_0, 1],
[regional_1_0, regional_1_1]]
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region_1,
time_changes_region, initial_r, dI,
susceptibles[0])
with self.assertRaises(ValueError):
matrices_region_1 = [[regional_0_0, regional_0_1],
[
regional_1_0,
em.RegionMatrix(regions[0], age_groups,
region_data_matrix_1_1)
]]
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region_1,
time_changes_region, initial_r, dI,
susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region, 1, initial_r,
dI, susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region, [1, 2, 3],
initial_r, dI, susceptibles[0])
with self.assertRaises(TypeError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region, [1, '2'],
initial_r, dI, susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region, [0, 2],
initial_r, dI, susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, 0.5, dI,
susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, [0.5], dI,
susceptibles[0])
with self.assertRaises(TypeError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, [0.5, '1'], dI,
susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, [0.5, 0], dI,
susceptibles[0])
with self.assertRaises(TypeError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, '4',
susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, 0,
susceptibles[0])
with self.assertRaises(ValueError):
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, dI, [1])
with self.assertRaises(ValueError):
susceptibles_1 = [[[1], [3]], [[5], [7]], [[0], [1]]]
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, dI,
susceptibles_1[0])
with self.assertRaises(ValueError):
susceptibles_1 = [[[1, 2]], [[5, 6]], [[0, 2]]]
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, dI,
susceptibles_1[0])
with self.assertRaises(TypeError):
susceptibles_1 = [[[1, '2'], [3, 4]], [[5, 6], [7, 8]],
[[0, 2], [1, 1]]]
em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, dI,
susceptibles_1[0])
def test_compute_reproduction_number(self):
regions = ['London', 'Cornwall']
age_groups = ['0-10', '10-25']
# Initial state of the system
contact_data_matrix_0 = np.array([[10, 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 = [[[1, 2], [3, 4]], [[5, 6], [7, 8]], [[0, 2], [1, 1]]]
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]
initial_r = [0.5, 1]
m = em.MultiTimesInfectivity(matrices_contact, time_changes_contact,
regions, matrices_region,
time_changes_region, initial_r, dI,
susceptibles[0])
self.assertEqual(
m.compute_reproduction_number(1, 3, susceptibles[2][0]), 0.5)
with self.assertRaises(TypeError):
m.compute_reproduction_number('1', 3, susceptibles[2][0], 1)
with self.assertRaises(ValueError):
m.compute_reproduction_number(3, 3, susceptibles[2][0], 1)
with self.assertRaises(ValueError):
m.compute_reproduction_number(0, 3, susceptibles[2][0], 1)
with self.assertRaises(TypeError):
m.compute_reproduction_number(1, '3', susceptibles[2][0], 1)
with self.assertRaises(ValueError):
m.compute_reproduction_number(1, 0, susceptibles[2][0], 1)
with self.assertRaises(TypeError):
m.compute_reproduction_number(1, 3, susceptibles[2][0], '1')
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_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_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_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_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)
