def test_population_size():
population = Population()
population.add(Household('1'))
population['1'].add(Person('0', freq=1))
population['1'].add(Person('1', freq=3))
population.add(Household('2'))
assert population.size == 4
def population():
population = Population()
for hid in range(1, 11):
household = HouseHold(hid)
for pid in range(2):
pid = f"{hid}-{pid}"
person = Person(pid)
person.add(Activity(1, 'home', 'a'))
person.add(Leg(1, 'car', 'a', 'b'))
person.add(Activity(2, 'work', 'b'))
person.add(Leg(2, 'car', 'b', 'a'))
person.add(Activity(3, 'home', 'a'))
household.add(person)
population.add(household)
for hid in range(10, 21):
household = HouseHold(hid)
for pid in range(2):
pid = f"{hid}-{pid}"
person = Person(pid)
person.add(Activity(1, 'home', 'a'))
person.add(Leg(1, 'bus', 'a', 'b'))
person.add(Activity(2, 'education', 'b'))
person.add(Leg(2, 'bus', 'b', 'a'))
person.add(Activity(3, 'home', 'a'))
household.add(person)
population.add(household)
return population
def test_extract_population_mode_classes():
population = Population()
for hid, (_act, _mode) in enumerate(zip(['work', 'shop'], ['pt', 'walk'])):
household = Household(hid=str(hid))
population.add(household)
for i, (act, mode) in enumerate(zip(['work', _act], ['car', _mode])):
person = Person(pid=str(i))
person.add(
Activity(seq=1,
act='home',
area='A',
start_time=mtdt(0),
end_time=mtdt(600)))
person.add(
Leg(seq=2,
mode=mode,
start_area='A',
end_area='B',
start_time=mtdt(600),
end_time=mtdt(620)))
person.add(
Activity(seq=3,
act=act,
area='B',
start_time=mtdt(620),
end_time=mtdt(1200)))
household.add(person)
assert population.mode_classes == set(['car', 'pt', 'walk'])
def test_population_print(capfd, person_heh):
population = Population()
population.add(Household('1'))
population['1'].add(person_heh)
population.print()
out, _ = capfd.readouterr()
assert (out)
def test_population_num_households():
population = Population()
population.add(Household('1'))
population['1'].add(Person('0', freq=1))
population['1'].add(Person('1', freq=3))
population.add(Household('2'))
assert population.num_households == 2
def test_population_stats():
population = Population()
population.add(Household('1'))
population['1'].add(Person('0', freq=1))
population['1'].add(Person('1', freq=3))
population.add(Household('2'))
population['2'].add(Person('2', freq=3))
assert isinstance(population.stats, dict)
def test_pickle_population(person_crop_last_act, tmpdir):
population = Population()
hh = Household('1')
hh.add(person_crop_last_act)
population.add(hh)
path = os.path.join(tmpdir, 'test.pkl')
population.pickle(path)
assert os.path.exists(path)
def test_count_population():
population = Population()
for i in range(1, 5):
hh = Household(str(i))
for ii in range(i):
hh.add(Person(f"{i}_{ii}"))
population.add(hh)
assert population.population == 10
def test_populations_equal_given_same_population():
pop1 = Population()
hh1 = Household('1', attributes={1: 1})
p1 = Person('1', attributes={1: 1})
hh1.add(p1)
pop1.add(hh1)
assert pop1 == pop1
def test_plot_act_time_bins(Steve, Hilda):
population = Population()
for i, person in enumerate([Steve, Hilda]):
hh = Household(i)
hh.add(person)
population.add(hh)
fig = plot_activity_times(population)
assert isinstance(fig, Figure)
def test_populations_not_equal_given_diff_type():
pop1 = Population()
hh1 = Household('1', attributes={1: 1})
p1 = Person('1', attributes={1: 1})
hh1.add(p1)
pop1.add(hh1)
assert not pop1 == None
def test_reindex_population_duplicate_key():
pop = Population()
for i in ['1', 'test_1']:
hh = Household(i)
pop.add(hh)
for j in ['1', 'test_1']:
hh.add(Person(j))
with pytest.raises(KeyError):
pop.reindex("test_")
def test_build_leg_log(person_heh):
population = Population()
for i in range(5):
hh = Household(i)
hh.add(person_heh)
population.add(hh)
log = extract_leg_log(population)
assert len(log) == 10
assert list(log.columns) == ['mode', 'start', 'end', 'duration']
def population():
population = Population()
hh = Household('A', attributes={1: 1})
pa = Person('person_A', attributes={1: 1})
hh.add(pa)
pb = Person('Person_B', attributes={1: 3})
hh.add(pb)
population.add(hh)
population.add(Household('B'))
return population
def test_load_pickle_population(person_crop_last_act, tmpdir):
population = Population()
hh = Household('1')
hh.add(person_crop_last_act)
population.add(hh)
path = os.path.join(tmpdir, 'test.pkl')
population.pickle(path)
loaded = load_pickle(path)
assert loaded.households
assert list(loaded.households['1'].people) == list(
population.households['1'].people)
def test_population_combine_person_duplicate_key():
pop1 = Population()
hh1 = Household('1')
p1 = Person('1')
hh1.add(p1)
pop1.add(hh1)
p2 = Person('1')
with pytest.raises(KeyError):
pop1.combine(p2, '')
def test_time_binner(person_heh):
population = Population()
for i in range(5):
hh = Household(i)
hh.add(person_heh)
population.add(hh)
log = extract_activity_log(population)
binned = time_binner(log)
assert len(binned) == 96
for h in ['start', 'end', 'duration']:
assert binned[h].sum() == 3
def test_population_sample_locs(person_heh):
population = Population()
population.add(Household('1'))
population['1'].add(person_heh)
class DummySampler:
def sample(self, loc, act):
return None
population.sample_locs(DummySampler())
assert population['1']['1'].plan[2].location.loc is None
def test_assign_same_locs_to_household_activity_in_same_area(SmithHousehold):
population = Population()
population.add(SmithHousehold)
class FakeSampler:
def sample(self, location_idx, activity):
return random()
population.sample_locs(FakeSampler())
SmithHousehold['3'].plan[2].location == SmithHousehold['4'].plan[
2].location
def test_populations_not_equal_given_missing_person():
pop1 = Population()
hh1 = Household('1', attributes={1: 1})
p1 = Person('1', attributes={1: 1})
hh1.add(p1)
pop1.add(hh1)
pop4 = Population()
hh4 = Household('2', attributes={1: 2})
pop4.add(hh4)
assert not pop1 == pop4
def test_write_plans_xml_v12_assert_contents(tmp_path):
population = Population()
hh = Household('a')
p = Person('a', attributes={'1':'1'})
p.add(Activity(
act="home",
loc=Point((0,0)),
start_time=datetime(1900,1,1,0,0,0),
end_time=datetime(1900,1,1,8,0,0)
))
p.add(Leg(
mode='car',
start_loc=Point((0,0)),
end_loc=Point((0,1000)),
start_time=datetime(1900,1,1,8,0,0),
end_time=datetime(1900,1,1,9,0,0)
))
p.add(Activity(
act="work",
loc=Point((0,1000)),
start_time=datetime(1900,1,1,9,0,0),
end_time=datetime(1900,1,1,18,0,0)
))
p.add(Leg(
mode='car',
start_loc=Point((0,1000)),
end_loc=Point((0,0)),
start_time=datetime(1900,1,1,18,0,0),
end_time=datetime(1900,1,1,19,0,0)
))
p.add(Activity(
act="home",
loc=Point((0,0)),
start_time=datetime(1900,1,1,19,0,0),
end_time=END_OF_DAY
))
hh.add(p)
population.add(hh)
plans_location = str(tmp_path / "test_plans.xml")
write_matsim(
population,
plans_path=plans_location,
comment="test",
version=12,
household_key=None
)
new = read_matsim(
plans_location,
version=12
)
assert new == population
assert new['a']['a'].attributes == {'1':'1'}
assert new['a']['a'].plan.day[1].distance == 1000
def test_assign_same_locs_to_household(SmithHousehold):
population = Population()
population.add(SmithHousehold)
class FakeSampler:
def sample(self, location_idx, activity):
return random()
population.sample_locs(FakeSampler())
home_location = population['1'].location
for pid, person in SmithHousehold:
assert person.home == home_location
def test_population_iadd_person():
pop1 = Population()
hh1 = Household('1')
p1 = Person('1')
hh1.add(p1)
pop1.add(hh1)
p2 = Person('2')
pop1 += p2
assert set(pop1.households) == {'1', '2'}
assert set(pop1.households['2'].people) == {'2'}
assert isinstance(pop1.households['2'], Household)
assert isinstance(pop1.households['2'].people['2'], Person)
def test_population_combine_person():
pop1 = Population()
hh1 = Household('1')
p1 = Person('1')
hh1.add(p1)
pop1.add(hh1)
p2 = Person('1')
pop1.combine(p2, 'test_')
assert set(pop1.households) == {'1', 'test_1'}
assert set(pop1.households['test_1'].people) == {'test_1'}
assert isinstance(pop1.households['test_1'], Household)
assert isinstance(pop1.households['test_1'].people['test_1'], Person)
def test_populations_equal_with_same_hh_and_person_attributes():
pop1 = Population()
hh1 = Household('1', attributes={1: 1})
p1 = Person('1', attributes={1: 1})
hh1.add(p1)
pop1.add(hh1)
pop2 = Population()
hh2 = Household('1', attributes={1: 1})
p2 = Person('1', attributes={1: 1})
hh2.add(p2)
pop2.add(hh2)
assert pop1 == pop2
def test_populations_equal_given_same_hh_and_persons_with_diff_ids():
pop1 = Population()
hh1 = Household('1', attributes={1: 1})
p1 = Person('1', attributes={1: 1})
hh1.add(p1)
pop1.add(hh1)
pop3 = Population()
hh3 = Household('2', attributes={1: 1})
p3 = Person('2', attributes={1: 1})
hh3.add(p3)
pop3.add(hh3)
assert pop1 == pop3
def test_populations_not_equal_given_wrong_person_attributes():
pop1 = Population()
hh1 = Household('1', attributes={1: 1})
p1 = Person('1', attributes={1: 1})
hh1.add(p1)
pop1.add(hh1)
pop5 = Population()
hh5 = Household('2', attributes={1: 1})
p5 = Person('1', attributes={1: 2})
hh5.add(p5)
pop5.add(hh5)
assert not pop1 == pop5
def test_reindex_population():
pop = Population()
for i in ['1', '2']:
hh = Household(i)
pop.add(hh)
for j in ['1', '2']:
hh.add(Person(j))
pop.reindex("test_")
assert set(pop.households) == {'test_1', 'test_2'}
assert {hh.hid for hh in pop.households.values()} == {'test_1', 'test_2'}
assert set(pop.households['test_1'].people) == {'test_1', 'test_2'}
assert {p.pid
for p in pop.households['test_1'].people.values()
} == {'test_1', 'test_2'}
def add_hhs_from_persons_attributes(
population: core.Population,
persons_attributes: Optional[pd.DataFrame] = None):
logger = logging.getLogger(__name__)
if persons_attributes is None or 'hid' not in persons_attributes.columns:
return None
logger.info("Adding hhs from persons_attributes")
for hid, hh_data in persons_attributes.groupby('hid'):
if hid not in population.households:
hzone = hh_data.iloc[0].to_dict().get("hzone")
household = core.Household(hid, area=hzone)
population.add(household)
def add_hhs_from_hhs_attributes(population: core.Population,
hhs_attributes: Optional[pd.DataFrame] = None):
logger = logging.getLogger(__name__)
if hhs_attributes is None:
return None
logger.info("Adding hhs from hhs_attributes")
for hid, hh in hhs_attributes.groupby('hid'):
if hid not in population.households:
hh_attributes = hhs_attributes.loc[hid].to_dict()
household = core.Household(hid,
attributes=hh_attributes,
freq=hh_attributes.pop("freq", None),
area=hh_attributes.pop("hzone", None))
population.add(household)
