Esempio n. 1
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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
Esempio n. 2
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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
Esempio n. 3
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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
Esempio n. 4
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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
Esempio n. 5
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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
Esempio n. 6
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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)
Esempio n. 7
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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)
Esempio n. 8
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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)
Esempio n. 9
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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