def test_side_effects():
class DoneState(State):
@uses_columns(['count'])
def _transition_side_effect(self, index, population_view):
pop = population_view.get(index)
population_view.update(pop['count'] + 1)
done_state = DoneState('done')
start_state = State('start')
done_transition = Transition(done_state,
lambda agents: np.full(len(agents), 1.0))
start_state.transition_set.append(done_transition)
done_state.transition_set.append(done_transition)
machine = Machine('state')
machine.states.extend([start_state, done_state])
simulation = setup_simulation([
machine,
_population_fixture('state', 'start'),
_population_fixture('count', 0)
])
machine.transition(simulation.population.population.index)
assert np.all(simulation.population.population['count'] == 1)
machine.transition(simulation.population.population.index)
assert np.all(simulation.population.population['count'] == 2)
def test_interpolated_tables__exact_values_at_input_points():
years = build_table(lambda age, sex, year: year)
input_years = years.year.unique()
simulation = setup_simulation([generate_test_population], 10000)
manager = simulation.tables
years = manager.build_table(years)
for year in input_years:
simulation.current_time = datetime(year=year, month=1, day=1)
assert np.allclose(years(simulation.population.population.index),
simulation.current_time.year + 1/365, rtol=1.e-5)
def test_transition():
done_state = State('done')
start_state = State('start')
done_transition = Transition(done_state,
lambda agents: np.full(len(agents), 1.0))
start_state.transition_set.append(done_transition)
machine = Machine('state')
machine.states.extend([start_state, done_state])
simulation = setup_simulation(
[machine, _population_fixture('state', 'start')])
machine.transition(simulation.population.population.index)
assert np.all(simulation.population.population.state == 'done')
def test_null_transition():
a_state = State('a')
start_state = State('start')
start_state.add_transition(
a_state, probability_func=lambda agents: np.full(len(agents), 0.5))
start_state.allow_self_transitions()
machine = Machine('state', states=[start_state, a_state])
simulation = setup_simulation(
[machine, _population_fixture('state', 'start')],
population_size=10000)
machine.transition(simulation.population.population.index)
a_count = (simulation.population.population.state == 'a').sum()
assert round(a_count / len(simulation.population.population), 1) == 0.5
def test_no_null_transition():
a_state = State('a')
b_state = State('b')
start_state = State('start')
a_transition = Transition(a_state)
b_transition = Transition(b_state)
start_state.transition_set.allow_null_transition = False
start_state.transition_set.extend((a_transition, b_transition))
machine = Machine('state')
machine.states.extend([start_state, a_state, b_state])
simulation = setup_simulation(
[machine, _population_fixture('state', 'start')],
population_size=10000)
machine.transition(simulation.population.population.index)
a_count = (simulation.population.population.state == 'a').sum()
assert round(a_count / len(simulation.population.population), 1) == 0.5
def test_choice():
a_state = State('a')
b_state = State('b')
start_state = State('start')
a_transition = Transition(a_state,
lambda agents: np.full(len(agents), 0.5))
b_transition = Transition(b_state,
lambda agents: np.full(len(agents), 0.5))
start_state.transition_set.extend((a_transition, b_transition))
machine = Machine('state')
machine.states.extend([start_state, a_state, b_state])
simulation = setup_simulation(
[machine, _population_fixture('state', 'start')],
population_size=10000)
machine.transition(simulation.population.population.index)
a_count = (simulation.population.population.state == 'a').sum()
assert round(a_count / len(simulation.population.population), 1) == 0.5
def test_interpolated_tables():
years = build_table(lambda age, sex, year: year)
ages = build_table(lambda age, sex, year: age)
one_d_age = ages.copy()
del one_d_age['year']
one_d_age = one_d_age.drop_duplicates()
simulation = setup_simulation([generate_test_population], 10000)
manager = simulation.tables
years = manager.build_table(years)
ages = manager.build_table(ages)
one_d_age = manager.build_table(one_d_age, parameter_columns=('age',))
result_years = years(simulation.population.population.index)
result_ages = ages(simulation.population.population.index)
result_ages_1d = one_d_age(simulation.population.population.index)
fractional_year = simulation.current_time.year
fractional_year += simulation.current_time.timetuple().tm_yday / 365.25
assert np.allclose(result_years, fractional_year)
assert np.allclose(result_ages, simulation.population.population.age)
assert np.allclose(result_ages_1d, simulation.population.population.age)
simulation.current_time += timedelta(days=30.5 * 125)
simulation.population._population.age += 125/12
result_years = years(simulation.population.population.index)
result_ages = ages(simulation.population.population.index)
result_ages_1d = one_d_age(simulation.population.population.index)
fractional_year = simulation.current_time.year
fractional_year += simulation.current_time.timetuple().tm_yday / 365.25
assert np.allclose(result_years, fractional_year)
assert np.allclose(result_ages, simulation.population.population.age)
assert np.allclose(result_ages_1d, simulation.population.population.age)
def test_interpolated_tables_without_uniterpolated_columns():
years = build_table(lambda age, sex, year: year)
del years['sex']
years = years.drop_duplicates()
simulation = setup_simulation([generate_test_population], 10000)
manager = simulation.tables
years = manager.build_table(years, key_columns=(), parameter_columns=('year', 'age',))
result_years = years(simulation.population.population.index)
fractional_year = simulation.current_time.year
fractional_year += simulation.current_time.timetuple().tm_yday / 365.25
assert np.allclose(result_years, fractional_year)
simulation.current_time += timedelta(days=30.5 * 125)
result_years = years(simulation.population.population.index)
fractional_year = simulation.current_time.year
fractional_year += simulation.current_time.timetuple().tm_yday / 365.25
assert np.allclose(result_years, fractional_year)