def test_controlling_age_of_head(self):
""" Controls for one marginal characteristics, namely age_of_head.
"""
annual_household_control_totals_data = {
"year": array([2000, 2000, 2000, 2001, 2001, 2001, 2002, 2002, 2002]),
"age_of_head": array([0,1,2,0,1,2, 0,1,2]),
"total_number_of_households": array([25013, 21513, 18227, # 2000
10055, 15003, 17999, # 2001
15678, 14001, 20432]) # 2002
}
household_characteristics_for_ht_data = {
"characteristic": array(3*['age_of_head']),
"min": array([0, 35, 65]),
"max": array([34, 64, -1])
}
households_data = {
"household_id":arange(15000)+1,
"building_id": array(15000*[1]),
"age_of_head": array(1000*[25] + 1000*[28] + 2000*[32] + 1000*[34] +
2000*[35] + 1000*[40] + 1000*[54]+ 1000*[62] +
1000*[65] + 1000*[68] + 2000*[71] + 1000*[98]),
"persons": array(1000*[2] + 2000*[3] + 1000*[1] + 1000*[6] + 1000*[1] + 1000*[4] +
3000*[1]+ 5000*[5], dtype=int8)
}
storage = StorageFactory().get_storage('dict_storage')
storage.write_table(table_name='hh_set', table_data=households_data)
hh_set = HouseholdDataset(in_storage=storage, in_table_name='hh_set')
storage.write_table(table_name='hct_set', table_data=annual_household_control_totals_data)
hct_set = ControlTotalDataset(in_storage=storage, in_table_name='hct_set', what='household',
id_name=['year' ,'age_of_head'])
storage.write_table(table_name='hc_set', table_data=household_characteristics_for_ht_data)
hc_set = HouseholdCharacteristicDataset(in_storage=storage, in_table_name='hc_set')
storage.write_table(table_name='prs_set', table_data=self.person_data)
prs_set = PersonDataset(in_storage=storage, in_table_name='prs_set')
model = HouseholdTransitionModel(debuglevel=3)
# this run should add households in all four categories
model.run(year=2000, person_set=prs_set, household_set=hh_set, control_totals=hct_set, characteristics=hc_set)
results = hh_set.size()
should_be = [(hct_set.get_attribute("total_number_of_households")[0:3]).sum()]
self.assertEqual(ma.allclose(should_be, results, rtol=1e-1),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
results = zeros(hc_set.size(), dtype=int32)
results[0] = where(hh_set.get_attribute('age_of_head') <= hc_set.get_attribute("max")[0], 1,0).sum()
for i in range(1, hc_set.size()-1):
results[i] = logical_and(where(hh_set.get_attribute('age_of_head') >= hc_set.get_attribute("min")[i], 1,0),
where(hh_set.get_attribute('age_of_head') <= hc_set.get_attribute("max")[i], 1,0)).sum()
results[hc_set.size()-1] = where(hh_set.get_attribute('age_of_head') >= hc_set.get_attribute("min")[hc_set.size()-1], 1,0).sum()
should_be = hct_set.get_attribute("total_number_of_households")[0:3]
self.assertEqual(ma.allclose(results, should_be, rtol=1e-6),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
# this run should remove households in all four categories
model.run(year=2001, person_set=prs_set, household_set=hh_set, control_totals=hct_set, characteristics=hc_set)
results = hh_set.size()
should_be = [(hct_set.get_attribute("total_number_of_households")[3:6]).sum()]
self.assertEqual(ma.allclose(should_be, results, rtol=1e-1),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
results = zeros(hc_set.size(), dtype=int32)
results[0] = where(hh_set.get_attribute('age_of_head') <= hc_set.get_attribute("max")[0], 1,0).sum()
for i in range(1, hc_set.size()-1):
results[i] = logical_and(where(hh_set.get_attribute('age_of_head') >= hc_set.get_attribute("min")[i], 1,0),
where(hh_set.get_attribute('age_of_head') <= hc_set.get_attribute("max")[i], 1,0)).sum()
results[hc_set.size()-1] = where(hh_set.get_attribute('age_of_head') >= hc_set.get_attribute("min")[hc_set.size()-1], 1,0).sum()
should_be = hct_set.get_attribute("total_number_of_households")[3:6]
self.assertEqual(ma.allclose(results, should_be, rtol=1e-6),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
# this run should add and remove households
model.run(year=2002, person_set=prs_set, household_set=hh_set, control_totals=hct_set, characteristics=hc_set)
results = hh_set.size()
should_be = [(hct_set.get_attribute("total_number_of_households")[6:9]).sum()]
self.assertEqual(ma.allclose(should_be, results, rtol=1e-1),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
results = zeros(hc_set.size(), dtype=int32)
results[0] = where(hh_set.get_attribute('age_of_head') <= hc_set.get_attribute("max")[0], 1,0).sum()
for i in range(1, hc_set.size()-1):
results[i] = logical_and(where(hh_set.get_attribute('age_of_head') >= hc_set.get_attribute("min")[i], 1,0),
where(hh_set.get_attribute('age_of_head') <= hc_set.get_attribute("max")[i], 1,0)).sum()
results[hc_set.size()-1] = where(hh_set.get_attribute('age_of_head') >= hc_set.get_attribute("min")[hc_set.size()-1], 1,0).sum()
should_be = hct_set.get_attribute("total_number_of_households")[6:9]
self.assertEqual(ma.allclose(results, should_be, rtol=1e-6),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
def test_controlling_income(self):
""" Controls for one marginal characteristics, namely income.
"""
annual_household_control_totals_data = {
"year": array([2000, 2000, 2000, 2000, 2001, 2001, 2001, 2001, 2002, 2002, 2002, 2002]),
"income": array([0,1,2,3,0,1,2,3, 0,1,2,3]),
"total_number_of_households": array([25013, 21513, 18227, 18493, # 2000
10055, 15003, 17999, 17654, # 2001
15678, 14001, 20432, 14500]) # 2002
}
household_characteristics_for_ht_data = {
"characteristic": array(4*['income']),
"min": array([0, 40000, 120000, 70000]), # category 120000 has index 3 and category 70000 has index 2
"max": array([39999, 69999, -1, 119999]) # (testing row invariance)
}
hc_sorted_index = array([0,1,3,2])
households_data = {
"household_id":arange(20000)+1,
"building_id": array(19950*[1] + 50*[0]),
"income": array(1000*[1000] + 1000*[10000] + 2000*[20000] + 1000*[35000] + 2000*[45000] +
1000*[50000] + 2000*[67000]+ 2000*[90000] + 1000*[100005] + 2000*[110003] +
1000*[120000] + 1000*[200000] + 2000*[500000] + 1000*[630000]),
"persons": array(3000*[2] + 2000*[3] + 1000*[1] + 1000*[6] + 1000*[1] + 1000*[4] +
3000*[1]+ 8000*[5], dtype=int8)
}
storage = StorageFactory().get_storage('dict_storage')
storage.write_table(table_name='hh_set', table_data=households_data)
hh_set = HouseholdDataset(in_storage=storage, in_table_name='hh_set')
storage.write_table(table_name='hct_set', table_data=annual_household_control_totals_data)
hct_set = ControlTotalDataset(in_storage=storage, in_table_name='hct_set', what='household', id_name=['year' ,'income'])
storage.write_table(table_name='hc_set', table_data=household_characteristics_for_ht_data)
hc_set = HouseholdCharacteristicDataset(in_storage=storage, in_table_name='hc_set')
storage.write_table(table_name='prs_set', table_data=self.person_data)
prs_set = PersonDataset(in_storage=storage, in_table_name='prs_set')
model = HouseholdTransitionModel(debuglevel=3)
# this run should add households in all four categories
model.run(year=2000, person_set=prs_set, household_set=hh_set, control_totals=hct_set, characteristics=hc_set)
results = hh_set.size()
should_be = [83246]
self.assertEqual(ma.allclose(should_be, results, rtol=1e-1),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
results = zeros(hc_set.size(), dtype=int32)
results[0] = where(hh_set.get_attribute('income') <=
hc_set.get_attribute("max")[hc_sorted_index[0]], 1,0).sum()
for i in range(1, hc_set.size()-1):
results[i] = logical_and(where(hh_set.get_attribute('income') >=
hc_set.get_attribute("min")[hc_sorted_index[i]], 1,0),
where(hh_set.get_attribute('income') <=
hc_set.get_attribute("max")[hc_sorted_index[i]], 1,0)).sum()
results[-1] = where(hh_set.get_attribute('income') >= hc_set.get_attribute("min")[hc_sorted_index[-1]], 1,0).sum()
should_be = hct_set.get_attribute("total_number_of_households")[0:4]
self.assertEqual(ma.allclose(results, should_be, rtol=1e-6),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
# this run should remove households in all four categories
model.run(year=2001, person_set=prs_set, household_set=hh_set, control_totals=hct_set, characteristics=hc_set)
results = hh_set.size()
should_be = [(hct_set.get_attribute("total_number_of_households")[4:8]).sum()]
self.assertEqual(ma.allclose(should_be, results, rtol=1e-1),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
results = zeros(hc_set.size(), dtype=int32)
results[0] = where(hh_set.get_attribute('income') <=
hc_set.get_attribute("max")[hc_sorted_index[0]], 1,0).sum()
for i in range(1, hc_set.size()-1):
results[i] = logical_and(where(hh_set.get_attribute('income') >=
hc_set.get_attribute("min")[hc_sorted_index[i]], 1,0),
where(hh_set.get_attribute('income') <=
hc_set.get_attribute("max")[hc_sorted_index[i]], 1,0)).sum()
results[-1] = where(hh_set.get_attribute('income') >= hc_set.get_attribute("min")[hc_sorted_index[-1]], 1,0).sum()
should_be = hct_set.get_attribute("total_number_of_households")[4:8]
self.assertEqual(ma.allclose(results, should_be, rtol=1e-6),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
# this run should add and remove households
model.run(year=2002, person_set=prs_set, household_set=hh_set, control_totals=hct_set, characteristics=hc_set)
results = hh_set.size()
should_be = [(hct_set.get_attribute("total_number_of_households")[8:13]).sum()]
self.assertEqual(ma.allclose(should_be, results, rtol=1e-1),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
results = zeros(hc_set.size(), dtype=int32)
results[0] = where(hh_set.get_attribute('income') <= hc_set.get_attribute("max")[hc_sorted_index[0]], 1,0).sum()
for i in range(1, hc_set.size()-1):
results[i] = logical_and(where(hh_set.get_attribute('income') >=
hc_set.get_attribute("min")[hc_sorted_index[i]], 1,0),
where(hh_set.get_attribute('income') <=
hc_set.get_attribute("max")[hc_sorted_index[i]], 1,0)).sum()
results[-1] = where(hh_set.get_attribute('income') >= hc_set.get_attribute("min")[hc_sorted_index[-1]], 1,0).sum()
should_be = hct_set.get_attribute("total_number_of_households")[8:13]
self.assertEqual(ma.allclose(results, should_be, rtol=1e-6),
True, "Error, should_be: %s, but result: %s" % (should_be, results))
