def test_present_value():
"""
Testing all the methods to generate a present value of net transfers
"""
size_generation = 3
cohort = create_neutral_profiles_cohort(population=1)
cohort2 = create_neutral_profiles_cohort(population=size_generation)
res = cohort.aggregate_generation_present_value('tax')
# defining a function which creates the theoretical result of the present value for the following test
def control_value(x):
control_value = (50 - abs(x - 50))
return control_value
age = 0
while age <= 100:
assert res.get_value((age, 1, 2002),
'tax') == control_value(age), res.get_value(
(age, 1, 2060), 'tax') == control_value(age)
age += 1
cohort3 = cohort2.per_capita_generation_present_value('tax')
res_control = cohort2.aggregate_generation_present_value('tax',
discount_rate=0)
count = 0
while count <= 100:
# print cohort3.get_value((count, 1, 2001), 'tax'), res_control.get_value((count, 0, 2001), 'tax')
assert cohort3.get_value(
(count, 1, 2001),
'tax') * size_generation == res_control.get_value((count, 0, 2001),
'tax')
count += 1
def test_present_value():
"""
Testing all the methods to generate a present value of net transfers
"""
size_generation = 3
cohort = create_neutral_profiles_cohort(population = 1)
cohort2 = create_neutral_profiles_cohort(population = size_generation)
res = cohort.aggregate_generation_present_value('tax')
# defining a function which creates the theoretical result of the present value for the following test
def control_value(x):
control_value = (50 - abs(x-50))
return control_value
age = 0
while age <= 100:
assert res.get_value((age, 1, 2002), 'tax') == control_value(age), res.get_value((age, 1, 2060), 'tax') == control_value(age)
age +=1
cohort3 = cohort2.per_capita_generation_present_value('tax')
res_control = cohort2.aggregate_generation_present_value('tax', discount_rate=0)
count = 0
while count <= 100:
# print cohort3.get_value((count, 1, 2001), 'tax'), res_control.get_value((count, 0, 2001), 'tax')
assert cohort3.get_value((count, 1, 2001), 'tax')*size_generation == res_control.get_value((count, 0, 2001), 'tax')
count +=1
def test_compute_ipl():
size_generation = 3
cohort2 = create_neutral_profiles_cohort(population=size_generation)
cohort3 = cohort2.aggregate_generation_present_value('tax')
ipl = cohort3.compute_ipl(typ='tax', net_gov_wealth=10)
assert ipl == 10.0
def test_compute_ipl():
size_generation = 3
cohort2 = create_neutral_profiles_cohort(population=size_generation)
cohort3 = cohort2.aggregate_generation_present_value("tax")
ipl = cohort3.compute_ipl(typ="tax", net_gov_wealth=10)
assert ipl == 10.0
def test_compute_ipl():
size_generation = 3
cohort2 = create_neutral_profiles_cohort(population = size_generation)
cohort3 = cohort2.aggregate_generation_present_value('tax')
ipl = cohort3.compute_ipl(typ = 'tax', net_gov_wealth = 10)
precision = cohort3.compute_ipl(typ = 'tax', net_gov_wealth = 10, precision=True)
assert precision == size_generation/ipl
assert ipl == -10.0
def test_compute_gen_imbalance():
size_generation = 1
cohort = create_neutral_profiles_cohort(population=size_generation)
simulation = Simulation()
simulation.discount_rate = 0
simulation.growth_rate = 0
simulation.cohorts = cohort
simulation.create_present_values('tax')
gen_imbalance = simulation.compute_gen_imbalance(typ='tax')
# print gen_imbalance
assert gen_imbalance == -5000.0 / (2 * 199.0)
def test_compute_gen_imbalance():
size_generation = 1
cohort = create_neutral_profiles_cohort(population = size_generation)
simulation = Simulation()
simulation.discount_rate = 0
simulation.growth_rate = 0
simulation.cohorts = cohort
simulation.create_present_values('tax')
gen_imbalance = simulation.compute_gen_imbalance(typ = 'tax')
# print gen_imbalance
assert gen_imbalance[0] == -5000.0/(2*199.0), gen_imbalance[1] == -5000.0/(2*199.0)
def test_compute_gen_imbalance():
size_generation = 1
cohort = create_neutral_profiles_cohort(population = size_generation)
simulation = Simulation()
simulation.discount_rate = 0
simulation.growth_rate = 0
simulation.cohorts = cohort
simulation.create_present_values('tax')
print simulation.aggregate_pv.tail(20).to_string()
print simulation.cohorts.head(20).to_string()
gen_imbalance = simulation.compute_gen_imbalance(typ = 'tax', to_return='difference')
# print gen_imbalance, -5000.0/(2*199.0)
assert gen_imbalance == -5000.0/(2*199.0)
def test_save_simulation():
size_generation = 1
cohort = create_neutral_profiles_cohort(population = size_generation)
simulation = Simulation()
simulation.country = 'france'
simulation.discount_rate = 0
simulation.growth_rate = 0
simulation.cohorts = cohort
simulation.create_present_values('tax')
simulation.save_simulation(filename='test_save')
store = HDFStore(os.path.join(SRC_PATH,'countries','france','sources', 'Output_folder','test_save.h5'))
assert store['aggregate_pv'] is not None
