def test_no_mixing_matrix():
"""
Test that we are using the default 'null-op' mixing matrix when
we have a no user-specified mixing matrix
"""
model = StratifiedModel(**MODEL_KWARGS)
default_matrix = np.array([[2, 3], [5, 7]])
model.stratify(
stratification_name="agegroup",
strata_request=["child", "adult"],
compartments_to_stratify=["S", "I", "R"],
mixing_matrix=default_matrix,
)
# We should get the default mixing matrix
actual_mixing = model.get_mixing_matrix(0)
assert_array_equal(actual_mixing, default_matrix)
# Static matrices shouldn't change over time
actual_mixing = model.get_mixing_matrix(123)
assert_array_equal(actual_mixing, default_matrix)
model.stratify(
stratification_name="location",
strata_request=["work", "home"], # These kids have jobs.
compartments_to_stratify=["S", "I", "R"],
mixing_matrix=None,
)
# We should get the default mixing matrix
actual_mixing = model.get_mixing_matrix(0)
assert_array_equal(actual_mixing, default_matrix)
# Static matrices shouldn't change over time
actual_mixing = model.get_mixing_matrix(123)
assert_array_equal(actual_mixing, default_matrix)
def test_multiple_dynamic_mixing_matrices():
"""
Test that we are using the correct mixing matrix when
we have multiple dynamic mixing matrices
"""
model = StratifiedModel(**MODEL_KWARGS)
agegroup_matrix = lambda t: t * np.array([[2, 3], [5, 7]])
model.stratify(
stratification_name="agegroup",
strata_request=["child", "adult"],
compartments_to_stratify=["S", "I", "R"],
mixing_matrix=agegroup_matrix,
)
location_matrix = lambda t: t * np.array([[11, 13], [17, 19]])
model.stratify(
stratification_name="location",
strata_request=["work", "home"], # These kids have jobs.
compartments_to_stratify=["S", "I", "R"],
mixing_matrix=location_matrix,
)
expected_mixing = np.array([
[2 * 11, 2 * 13, 3 * 11, 3 * 13],
[2 * 17, 2 * 19, 3 * 17, 3 * 19],
[5 * 11, 5 * 13, 7 * 11, 7 * 13],
[5 * 17, 5 * 19, 7 * 17, 7 * 19],
])
# We should get the Kronecker product of the two matrices
actual_mixing = model.get_mixing_matrix(1)
assert_array_equal(actual_mixing, expected_mixing)
# Double check that we calculated the Kronecker product correctly
kron_mixing = np.kron(agegroup_matrix(1), location_matrix(1))
assert_array_equal(expected_mixing, kron_mixing)
# Dynamic matrices should change over time
actual_mixing = model.get_mixing_matrix(5)
assert_array_equal(actual_mixing, 25 * expected_mixing)
def test_single_dynamic_mixing_matrix():
"""
Test that we are using the correct mixing matrix when
we have a single dynamic mixing matrix
"""
model = StratifiedModel(**MODEL_KWARGS)
agegroup_matrix = lambda t: t * np.array([[2, 3], [5, 7]])
model.stratify(
stratification_name="agegroup",
strata_request=["child", "adult"],
compartments_to_stratify=["S", "I", "R"],
mixing_matrix=agegroup_matrix,
)
# We should get the age mixing matrix
actual_mixing = model.get_mixing_matrix(1)
assert_array_equal(actual_mixing, agegroup_matrix(1))
# Dynamic matrices should change over time
actual_mixing = model.get_mixing_matrix(123)
assert_array_equal(actual_mixing, agegroup_matrix(123))