def test_interpolated_tables(base_config):
year_start = base_config.time.start.year
year_end = base_config.time.end.year
years = build_table(lambda age, sex, year: year, year_start, year_end)
ages = build_table(lambda age, sex, year: age, year_start, year_end)
one_d_age = ages.copy()
del one_d_age['year']
one_d_age = one_d_age.drop_duplicates()
base_config.population.update({'population_size': 10000})
simulation = setup_simulation([TestPopulation()], input_config=base_config)
manager = simulation.tables
years = manager.build_table(years,
key_columns=('sex', ),
parameter_columns=(
'age',
'year',
))
ages = manager.build_table(ages,
key_columns=('sex', ),
parameter_columns=(
'age',
'year',
))
one_d_age = manager.build_table(one_d_age,
key_columns=('sex', ),
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.clock.time.year
fractional_year += simulation.clock.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.clock._time += pd.Timedelta(30.5 * 125, unit='D')
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.clock.time.year
fractional_year += simulation.clock.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_uninterpolated_columns(base_config):
year_start = base_config.time.start.year
year_end = base_config.time.end.year
years = build_table(lambda age, sex, year: year, year_start, year_end)
del years['sex']
years = years.drop_duplicates()
base_config.population.update({'population_size': 10000})
simulation = setup_simulation([TestPopulation()], input_config=base_config)
manager = simulation.tables
years = manager.build_table(years,
key_columns=(),
parameter_columns=(
'year',
'age',
))
result_years = years(simulation.population.population.index)
fractional_year = simulation.clock.time.year
fractional_year += simulation.clock.time.timetuple().tm_yday / 365.25
assert np.allclose(result_years, fractional_year)
simulation.clock._time += pd.Timedelta(30.5 * 125, unit='D')
result_years = years(simulation.population.population.index)
fractional_year = simulation.clock.time.year
fractional_year += simulation.clock.time.timetuple().tm_yday / 365.25
assert np.allclose(result_years, fractional_year)
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_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__exact_values_at_input_points(base_config):
year_start = base_config.time.start.year
year_end = base_config.time.end.year
years = build_table(lambda age, sex, year: year, year_start, year_end)
input_years = years.year.unique()
base_config.population.update({'population_size': 10000})
simulation = setup_simulation([TestPopulation()], input_config=base_config)
manager = simulation.tables
years = manager.build_table(years,
key_columns=('sex', ),
parameter_columns=(
'age',
'year',
))
for year in input_years:
simulation.clock._time = pd.Timestamp(year, 1, 1)
assert np.allclose(years(simulation.population.population.index),
simulation.clock.time.year + 1 / 365)
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)