def test_faker_generator_should_delegate_to_faker_correct():
tested_name = FakerGenerator(seed=1234, method="name")
some_names = tested_name.generate(10)
assert len(some_names) == 10
tested_text = FakerGenerator(seed=1234, method="text")
some_text = tested_text.generate(20)
assert len(some_text) == 20
tested_address = FakerGenerator(seed=1234, method="address")
some_addresses = tested_address.generate(30)
assert len(some_addresses) == 30
def add_quotes(the_circus):
quote_generator = FakerGenerator(method="sentence",
nb_words=6,
variable_nb_words=True,
seed=next(the_circus.seeder))
person = the_circus.populations["person"]
quotes_rel = person.create_relationship("quotes")
for _ in range(4):
quotes_rel.add_relations(
from_ids=person.ids,
to_ids=quote_generator.generate(size=person.size)
)
def build_uganda_populations(circus):
seeder = seed_provider(12345)
cells = circus.create_population(
name="cells", ids_gen=SequencialGenerator(prefix="CELL_"), size=200)
latitude_generator = FakerGenerator(method="latitude", seed=next(seeder))
cells.create_attribute("latitude", init_gen=latitude_generator)
longitude_generator = FakerGenerator(method="longitude", seed=next(seeder))
cells.create_attribute("longitude", init_gen=longitude_generator)
# the cell "health" is its probability of accepting a call. By default
# let's says it's one expected failure every 1000 calls
healthy_level_gen = build_healthy_level_gen(next(seeder))
cells.create_attribute(name="HEALTH", init_gen=healthy_level_gen)
city_gen = FakerGenerator(method="city", seed=next(seeder))
cities_values = pd.unique(city_gen.generate(500))[:200]
cities = circus.create_population(name="cities", ids=cities_values)
cell_city_rel = cities.create_relationship("CELLS")
cell_city_df = make_random_assign(cells.ids, cities.ids, next(seeder))
cell_city_rel.add_relations(from_ids=cell_city_df["chosen_from_set2"],
to_ids=cell_city_df["set1"])
pop_gen = ParetoGenerator(xmin=10000, a=1.4, seed=next(seeder))
cities.create_attribute("population", init_gen=pop_gen)
timer_config = CyclicTimerProfile(
profile=[
1, .5, .2, .15, .2, .4, 3.8, 7.2, 8.4, 9.1, 9.0, 8.3, 8.1, 7.7,
7.4, 7.8, 8.0, 7.9, 9.7, 10.4, 10.5, 8.8, 5.7, 2.8
],
profile_time_steps="1h",
start_date=pd.Timestamp("6 June 2016 00:00:00"))
return cells, cities, timer_config
def _add_person_population(self):
id_gen = SequencialGenerator(prefix="PERSON_")
age_gen = NumpyRandomGenerator(method="normal", loc=3, scale=5,
seed=next(self.seeder))
name_gen = FakerGenerator(method="name", seed=next(self.seeder))
person = self.create_population(name="person", size=1000, ids_gen=id_gen)
person.create_attribute("NAME", init_gen=name_gen)
person.create_attribute("AGE", init_gen=age_gen)
quote_generator = FakerGenerator(method="sentence", nb_words=6, variable_nb_words=True,
seed=next(self.seeder))
quotes_rel = self.populations["person"].create_relationship("quotes")
for w in range(4):
quotes_rel.add_relations(
from_ids=person.ids,
to_ids=quote_generator.generate(size=person.size),
weights=w
)
ids_gen=id_gen)
person.create_attribute("NAME", init_gen=name_gen)
person.create_attribute("AGE", init_gen=age_gen)
# basic relationship to store people's quote
quote_generator = FakerGenerator(method="sentence",
nb_words=6,
variable_nb_words=True,
seed=next(example_circus.seeder))
quotes_rel = example_circus.populations["person"].create_relationship("quotes")
for w in range(4):
quotes_rel.add_relations(from_ids=person.ids,
to_ids=quote_generator.generate(size=person.size),
weights=w)
# message story
story_timer_gen = DefaultDailyTimerGenerator(clock=example_circus.clock,
seed=next(example_circus.seeder))
low_activity = story_timer_gen.activity(n=3, per=pd.Timedelta("1 day"))
med_activity = story_timer_gen.activity(n=10, per=pd.Timedelta("1 day"))
high_activity = story_timer_gen.activity(n=20, per=pd.Timedelta("1 day"))
activity_gen = NumpyRandomGenerator(
method="choice",
a=[low_activity, med_activity, high_activity],
p=[.2, .7, .1],