def __init__(self, model, start, end, init_customers, growth, churn, mrr,seed):
'''
Creates the behavior/utility model objects, sets internal variables to prepare for simulation, and creates
the database connection
:param model: name of the behavior/utility model parameters
:param start: start date for simulation
:param end: end date for simulation
:param init_customers: how many customers to create at start date
:param growth: monthly customer growth rate
:param churn: monthly customer churn rate
:param mrr: customer MRR
'''
self.model_name=model
self.start_date = start
self.end_date = end
self.init_customers=init_customers
self.monthly_growth_rate = growth
self.monthly_churn_rate = churn
self.mrr=mrr
self.behave_mod=GaussianBehaviorModel(self.model_name,seed)
self.util_mod=UtilityModel(self.model_name,self.monthly_churn_rate,self.behave_mod)
self.subscription_count = 0
self.tmp_sub_file_name = os.path.join(tempfile.gettempdir(),'{}_tmp_sub.csv'.format(self.model_name))
self.tmp_event_file_name=os.path.join(tempfile.gettempdir(),'{}_tmp_event.csv'.format(self.model_name))
self.db = Postgres("postgres://%s:%s@localhost/%s" % (
os.environ['CHURN_DB_USER'], os.environ['CHURN_DB_PASS'], os.environ['CHURN_DB']))
self.con = post.connect( database= os.environ['CHURN_DB'],
user= os.environ['CHURN_DB_USER'],
password=os.environ['CHURN_DB_PASS'])
def __init__(self, model, start, end, init_customers, seed):
"""
Creates the behavior/utility model objects, sets internal variables to prepare for simulation, and creates
the database connection
:param model: name of the behavior/utility model parameters
:param start: start date for simulation
:param end: end date for simulation
:param init_customers: how many customers to create at start date
"""
self.model_name = model
self.start_date = start
self.end_date = end
self.init_customers = init_customers
self.monthly_growth_rate = 0.12
self.util_mod = UtilityModel(self.model_name)
behavior_versions = glob.glob("../conf/" + self.model_name + "_*.csv")
self.behavior_models = {}
self.model_list = []
for b in behavior_versions:
version = b[(b.find(self.model_name) + len(self.model_name) +
1):-4]
if version in ("utility", "population", "country"):
continue
behave_mod = FatTailledBehaviorModel(self.model_name, seed,
version)
self.behavior_models[behave_mod.version] = behave_mod
self.model_list.append(behave_mod)
if len(self.behavior_models) > 1:
self.population_percents = pd.read_csv(
"../conf/" + self.model_name + "_population.csv", index_col=0)
self.util_mod.setChurnScale(self.behavior_models,
self.population_percents)
self.population_picker = np.cumsum(self.population_percents)
self.country_lookup = pd.read_csv("../conf/" + self.model_name +
"_country.csv")
self.subscription_count = 0
self.tmp_sub_file_name = os.path.join(
tempfile.gettempdir(), "{}_tmp_sub.csv".format(self.model_name))
self.tmp_event_file_name = os.path.join(
tempfile.gettempdir(), "{}_tmp_event.csv".format(self.model_name))
self.db = Postgres("postgres://%s:%s@localhost/%s" % (
os.environ["CHURN_DB_USER"],
os.environ["CHURN_DB_PASS"],
os.environ["CHURN_DB"],
))
self.con = post.connect(
database=os.environ["CHURN_DB"],
user=os.environ["CHURN_DB_USER"],
password=os.environ["CHURN_DB_PASS"],
)