def test_01_setup():
"""
sample init init attr, state, action space
:return:
"""
names = ['gender', 'age']
vals = {'gender': ['M', 'F', 'U'],
'age': ['0-19', '20-29', '30-39', '40-49', '50-59', '60-69', '70-*']}
attr_set = AttrSet(names, vals)
state_set = StateSet(['date', 'how'], ['discrete', 'discrete'],
[['2018-01-01', '2018-01-02'], list(range(168))])
act_set = ActionSet(attr_set, max_bid=9.99, min_bid=0.01, max_mod=9.0, min_mod=0.1)
return attr_set, state_set, act_set
def _load_settings(self):
file_data_handler = FileDataHandler()
settings_spec = file_data_handler.load_spec(os.path.join(""),
self.settings_spec_name)
if settings_spec is None:
sys.exit("Can't load experiment spec")
self.save_history = settings_spec["save_history"]
self.print_simulator_output = settings_spec["print_simulator_output"]
self.processing = settings_spec["processing"]
self.num_cores = settings_spec["num_cores"]
self.master_seed = settings_spec["master_seed"]
self.n_experiment_reps = settings_spec["n_experiment_reps"]
# Initialize state set
self.date_from = settings_spec.get("date_from", None)
self.date_to = settings_spec.get("date_to", None)
self.time_steps_df, self.dates_list = \
self._get_time_steps_data(self.date_from, self.date_to)
self.state_set = StateSet(
["date", "how"], ["discrete", "discrete"],
[self.dates_list, list(range(168))])
# Initialize attribute set
names = settings_spec["attributes"]["names"]
vals = settings_spec["attributes"]["vals"]
self.attr_set = AttrSet(names, vals)
# Initialize action set
self.action_set = ActionSet(self.attr_set,
max_bid=9.99,
min_bid=0.01,
max_mod=9.0,
min_mod=0.1)
return settings_spec
def setUp(self):
from ssa_sim_v2.simulator.modules.auctions.auctions_base_module import AuctionsPoissonModule
from ssa_sim_v2.simulator.modules.auction_attributes.auction_attributes_base_module import AuctionAttributesModule
from ssa_sim_v2.simulator.modules.vickrey_auction.vickrey_auction_module import VickreyAuctionModule
from ssa_sim_v2.simulator.modules.competitive_click_probability.competitive_click_probability_base_module import CompetitiveClickProbabilityTwoClassGeometricModule
from ssa_sim_v2.simulator.modules.competitive_clicks.competitive_clicks_base_module import CompetitiveClicksBinomialModule
from ssa_sim_v2.simulator.modules.conversion_rate.conversion_rate_base_module import ConversionRateFlatModule
from ssa_sim_v2.simulator.modules.conversions.conversions_base_module import ConversionsBinomialModule
from ssa_sim_v2.simulator.modules.revenue.revenue_base_module import RevenueGammaNoiseModule
from ssa_sim_v2.simulator.modules.competitive_cpc.competitive_cpc_base_module import CompetitiveCPCVickreyModule
from ssa_sim_v2.simulator.modules.auctions.auctions_date_how_module import AuctionsDateHoWModule
from ssa_sim_v2.simulator.modules.auction_attributes.auction_attributes_date_how_module import AuctionAttributesDateHoWModule
from ssa_sim_v2.simulator.modules.vickrey_auction.vickrey_auction_date_how_module import VickreyAuctionDateHoWModule
from ssa_sim_v2.simulator.modules.competitive_click_probability.competitive_click_probability_date_how_module import CompetitiveClickProbabilityDateHoWModule
from ssa_sim_v2.simulator.modules.competitive_clicks.competitive_clicks_date_how_module import CompetitiveClicksDateHoWModule
from ssa_sim_v2.simulator.modules.conversion_rate.conversion_rate_date_how_module import ConversionRateDateHoWModule
from ssa_sim_v2.simulator.modules.conversions.conversions_date_how_module import ConversionsDateHoWModule
from ssa_sim_v2.simulator.modules.revenue.revenue_date_how_module import RevenueDateHoWModule
from ssa_sim_v2.simulator.modules.competitive_cpc.competitive_cpc_date_how_module import CompetitiveCpcDateHoWModule
self.seed = 1111
self.date_from = "2018-01-01"
self.date_to = "2018-01-02"
self.tmp_df = pd.DataFrame(np.array(range(24)),
columns=["hour_of_day"])
self.tmp_df["key"] = 1
self.dates = pd.DataFrame(pd.date_range(self.date_from,
self.date_to),
columns=["date"])
dates_list = self.dates["date"].tolist()
self.dates["key"] = 1
self.dates = pd.merge(
self.dates, self.tmp_df, on=["key"],
how="left") # columns: ['date', 'hour_of_day']
self.dates["hour_of_week"] = pd.to_datetime(self.dates[
"date"]).dt.dayofweek * 24 + self.dates["hour_of_day"]
self.dates["date"] = self.dates["date"].dt.strftime("%Y-%m-%d")
self.dates = self.dates[["date", "hour_of_week"]]
# Initialize state set
self.state_set = StateSet(
["date", "how"], ["discrete", "discrete"],
[dates_list, list(range(168))])
# Initialize attribute set
names = ['gender', 'age']
vals = {
'gender': ['M', 'F', 'U'],
'age':
['0-19', '20-29', '30-39', '40-49', '50-59', '60-69', '70-*']
}
self.attr_set = AttrSet(names, vals)
attr_combinations = self.attr_set.get_all_attr_tuples()
# Initialize action set
self.action_set = ActionSet(self.attr_set,
max_bid=9.99,
min_bid=0.01,
max_mod=9.0,
min_mod=0.1)
def initialize_priors(params, base_class):
attr_combinations = list(self.attr_set.get_all_attr_tuples())
priors = self.dates.copy()
priors.loc[:, "prior"] = pd.Series(
[dict.fromkeys(attr_combinations, params)] * len(priors))
base_classes = self.dates.copy()
base_classes.loc[:, "base_class"] = base_class
return priors, base_classes
# Initialize auctions priors
module_class = AuctionsPoissonModule
Params = module_class.Params
params = Params(auctions=100)
priors = self.dates.copy()
priors.loc[:, "prior"] = [{(): params}] * len(priors)
base_classes = self.dates.copy()
base_classes.loc[:, "base_class"] = module_class
self.auctions_priors = priors
self.auctions_base_classes = base_classes
# Initialize auction_attributes priors
module_class = AuctionAttributesModule
Params = module_class.Params
params = Params(p=1.0) # Probabilities are normalized
self.auction_attributes_priors, self.auction_attributes_base_classes \
= initialize_priors(params, module_class)
# Initialize vickrey_auction priors
module_class = VickreyAuctionModule
Params = module_class.Params
params = Params()
self.vickrey_auction_priors, self.vickrey_auction_base_classes \
= initialize_priors(params, module_class)
# Initialize competitive_click_probability priors
module_class = CompetitiveClickProbabilityTwoClassGeometricModule
Params = module_class.Params
params = Params(n_pos=8, p=0.5, q=0.5, r_11=0.6, r_12=0.4, r_2=0.5)
self.competitive_click_probability_priors, self.competitive_click_probability_base_classes \
= initialize_priors(params, module_class)
# Initialize competitive_clicks priors
module_class = CompetitiveClicksBinomialModule
Params = module_class.Params
params = Params(noise_level=0.0, noise_type="multiplicative")
self.competitive_clicks_priors, self.competitive_clicks_base_classes \
= initialize_priors(params, module_class)
# Initialize conversion_rate priors
module_class = ConversionRateFlatModule
Params = module_class.Params
params = Params(cvr=0.02,
noise_level=0.0,
noise_type="multiplicative")
self.conversion_rate_priors, self.conversion_rate_base_classes \
= initialize_priors(params, module_class)
# Initialize conversions priors
module_class = ConversionsBinomialModule
Params = module_class.Params
params = Params(noise_level=0.0, noise_type="multiplicative")
self.conversions_priors, self.conversions_base_classes \
= initialize_priors(params, module_class)
# Initialize revenue priors
module_class = RevenueGammaNoiseModule
Params = module_class.Params
params = Params(avg_rpv=300.0, noise_level=100.0)
self.revenue_priors, self.revenue_base_classes = initialize_priors(
params, module_class)
# Initialize competitive_cpc priors
module_class = CompetitiveCPCVickreyModule
Params = module_class.Params
params = Params(n_pos=8, fee=0.01)
self.competitive_cpc_priors, self.competitive_cpc_base_classes = \
initialize_priors(params, module_class)
# Module setup for the simulator
self.mods = \
{"auctions": AuctionsDateHoWModule(self.auctions_priors,
self.auctions_base_classes,
self.seed),
"auction_attributes": AuctionAttributesDateHoWModule(self.auction_attributes_priors,
self.auction_attributes_base_classes,
self.seed),
"vickrey_auction": VickreyAuctionDateHoWModule(self.vickrey_auction_priors,
self.vickrey_auction_base_classes,
self.seed),
"competitive_click_probability": CompetitiveClickProbabilityDateHoWModule(self.competitive_click_probability_priors,
self.competitive_click_probability_base_classes,
self.seed),
"competitive_clicks": CompetitiveClicksDateHoWModule(self.competitive_clicks_priors,
self.competitive_clicks_base_classes,
self.seed),
"conversion_rate": ConversionRateDateHoWModule(self.conversion_rate_priors,
self.conversion_rate_base_classes,
self.seed),
"conversions": ConversionsDateHoWModule(self.conversions_priors,
self.conversions_base_classes,
self.seed),
"revenue": RevenueDateHoWModule(self.revenue_priors,
self.revenue_base_classes,
self.seed),
"competitive_cpc": CompetitiveCpcDateHoWModule(self.competitive_cpc_priors,
self.competitive_cpc_base_classes,
self.seed)
}
self.simulator = CompetitiveDateHowSimulator(self.state_set,
self.action_set,
self.attr_set,
self.mods,
self.date_from,
self.date_to,
income_share=1.0)