def act(self, state, data=None):
"""
Returns an action given state.
:return: An action chosen by the policy.
"""
# This example method returns a random bid in the range of [min_bid, max_bid]
b_max = self.action_set.max_bid
b_min = self.action_set.min_bid
mod_max = self.action_set.max_mod # maximum valid value of a modifier
mod_min = self.action_set.min_mod # minimum valid value of a modifier
bid = self.rng.uniform(low=b_min, high=b_max) # note: use self.rng instead of numpy.random
action_inc = Action(bid) # note: underspecified action (modifiers not defined at all)
# action_inc = Action(bid, {'gender': {'M': 1.1, 'F': 1.2}}) # underspecified modifiers
action = self.action_set.validify_action(action_inc) # this function fills in unspecified modifiers
# Example how you can access provided default values
if hasattr(self.stp, "cvr_default"):
print(self.stp.cvr_default)
if hasattr(self.stp, "rpv_default"):
print(self.stp.rpv_default)
# The following way you can make the simulator save your policy
# variable values into the output csv file.
# Save is made after both learn and act methods are invoked.
self.history.update({"bid": action.bid})
return action
def test_run_simulation_method(self):
print("----------------------------------------")
print(
"CompetitiveDateHowSimulator sample run_simulation method run")
N = 48
for n in range(N):
print("Round={}".format(n))
actions = [
Action(
2.0, {
attr_name: {
attr_value: np.random.uniform(0.5, 1.5)
for attr_value in
self.attr_set.attr_sets[attr_name]
}
for attr_name in self.attr_set.attr_names
}) for _ in range(3)
]
for action in actions:
print(action)
print("state={}".format(self.simulator.state))
results = self.simulator.step(actions)
# print(results)
self.assertTrue(True)
print("")
def test_sanity(self):
print("VickreyAuctionDateHoWModule class sample run -------------")
from ssa_sim_v2.simulator.modules.vickrey_auction.vickrey_auction_module import VickreyAuctionModule
date_range = pd.DataFrame(pd.date_range("2017-01-05",
"2017-01-06"),
columns=["date"])
date_range["key"] = 1
hours = pd.DataFrame(np.array(range(24)), columns=["hour_of_day"])
hours["key"] = 1
priors = pd.merge(date_range, hours, how="left", on="key")
priors["hour_of_week"] = priors["date"].dt.dayofweek * 24 + priors[
"hour_of_day"]
priors.loc[:, "date"] = priors["date"].dt.strftime("%Y-%m-%d")
priors = priors[["date", "hour_of_week"]]
base_classes = priors.copy()
priors.loc[:, "prior"] = None
base_classes.loc[:, "base_class"] = None
i = 0
for index, row in priors.iterrows():
Params = VickreyAuctionModule.Params
priors.loc[index, "prior"] = [{
(0, 0): Params(),
(0, 1): Params(),
(1, 0): Params(),
(1, 1): Params()
}]
base_classes.loc[index, "base_class"] = VickreyAuctionModule
i = (i + 1) % 24
vickrey_model = VickreyAuctionDateHoWModule(priors,
base_classes,
seed=9)
actions = [
Action(2.0, [[np.random.uniform(0.5, 1.5) for _ in range(2)]
for _ in range(2)]) for _ in range(3)
]
t = 0
while t < len(priors):
results = vickrey_model.get_auction_results(
actions=actions,
date=priors["date"][t],
how=priors["hour_of_week"][t])
print("date={} how={} result={}".format(
priors["date"][t], priors["hour_of_week"][t], results))
t = t + 1
self.assertTrue(True)
print("")
def act(self, state, data=None):
"""
Returns an action given state.
:param State state: The current state.
:param Union[pd.DataFrame, dict] data: Input data.
:return: An action chosen by the policy.
:rtype: Action
"""
if self.online:
action_index = dhl.randargmax(
self.ip.mu + self.udp.discount_factor /
(1 - self.udp.discount_factor) * self.ip.kg_nu,
rng=self.rng)
else:
action_index = dhl.randargmax(self.ip.kg_nu, rng=self.rng)
base_bid_amount = self.index_to_bid_amount(action_index)
action_inc = Action(
base_bid_amount
) # note: underspecified action (modifiers not defined at all)
# action_inc = Action(bid, {'gender': {'M': 1.1, 'F': 1.2}}) # underspecified modifiers
action = self.action_set.validify_action(
action_inc) # this function fills in unspecified modifiers
self.history.update({"bid": action.bid})
#self.history.update({"bid": self.action_set[action_index].bid})
return action
def _prepare_numerical_action(self, action):
"""
Prepares a numerical action (with numerical modifiers in the form
of a list of lists of floats) abusing the Action class definition.
Must be removed in future versions.
:param Action action: Action.
:return: Action with a list of lists of float modifiers instead of dicts.
:rtype: Action
"""
modifiers = [[action.modifiers[attr_name][attr_value]
for attr_value in self.attr_set.attr_sets[attr_name]]
for attr_name in self.attr_set.attr_names]
numerical_action = Action(action.bid, modifiers)
return numerical_action
def act(self, state, data=None):
"""
Returns an action given state.
:param StateSet.State state state: The current state.
:param Union[pd.DataFrame, dict] data: Input data.
:return: An action chosen by the policy.
:rtype: Action
"""
del state, data # Used to suppress PyCharm warning
action = self.action_set.validify_action(Action(bid=1.0))
# An example of how to store data in the history.
# It will get saved in the csv file from the simulation.
self.history.update({"bid": action.bid})
return action
def act(self, state, data=None):
"""
Returns an action given state.
:param State state: The current state.
:param Union[pd.DataFrame, dict] data: Input data.
:return: An action chosen by the policy.
:rtype: Action
"""
Policy.act(self, state, data)
try:
randomized_mu = np.array([
self.rng.normal(self.ip.mu[idx], self.ip.sigma[idx])
for idx in range(round(self.action_set.max_bid))
])
except:
print('error !!!!!')
print(self.action_set.max_bid)
print(len(self.ip.mu))
print(len(self.ip.sigma))
print('length of mu = {}, length of sigma = {}').format(
len(self.ip.mu), len(self.ip.sigma))
action_index = dhl.randargmax(randomized_mu, rng=self.rng)
base_bid_amount = self.index_to_bid_amount(action_index)
action_inc = Action(
base_bid_amount
) # note: underspecified action (modifiers not defined at all)
# action_inc = Action(base_bid_amount, {'gender': {'M': 1.1, 'F': 1.2}}) # underspecified modifiers
action = self.action_set.validify_action(
action_inc) # this function fills in unspecified modifiers
self.history.update(
{"bid": action.bid}
) # TODO: we should keep not just the base bid, but the entire bid for all attrs
return action
def test_sanity(self):
print("VickreyAuctionModule class sample run -------------")
from ssa_sim_v2.simulator.action import Action
print("Example 1")
actions = [
Action(2.0, [[np.random.uniform(0.5, 1.5) for _ in range(2)]
for _ in range(2)]) for _ in range(3)
]
for action in actions:
print(action)
print("")
vickrey_auction = VickreyAuctionModule(
prior={
(0, 0): VickreyAuctionModule.Params(),
(0, 1): VickreyAuctionModule.Params(),
(1, 0): VickreyAuctionModule.Params(),
(1, 1): VickreyAuctionModule.Params()
})
# vickrey_auction.determine_effective_modifiers(actions,segment=(0, 1, 2))
results = vickrey_auction.get_auction_results(actions=actions)
for key, value in results.items():
print("{}: {}".format(key, value))
print("")
print("Example 2")
actions = [
Action(2.0, [[np.random.uniform(0.5, 1.5) for _ in range(5)]
for _ in range(7)]) for _ in range(10)
]
for action in actions:
print(action)
print("")
vickrey_auction = VickreyAuctionModule(
prior={
(0, 0, 0): VickreyAuctionModule.Params(),
(0, 0, 1): VickreyAuctionModule.Params(),
(0, 0, 2): VickreyAuctionModule.Params(),
(0, 1, 0): VickreyAuctionModule.Params(),
(0, 1, 1): VickreyAuctionModule.Params(),
(0, 1, 2): VickreyAuctionModule.Params(),
(0, 2, 0): VickreyAuctionModule.Params(),
(0, 2, 1): VickreyAuctionModule.Params(),
(0, 2, 2): VickreyAuctionModule.Params(),
(1, 0, 0): VickreyAuctionModule.Params(),
(1, 0, 1): VickreyAuctionModule.Params(),
(1, 0, 2): VickreyAuctionModule.Params(),
(1, 1, 0): VickreyAuctionModule.Params(),
(1, 1, 1): VickreyAuctionModule.Params(),
(1, 1, 2): VickreyAuctionModule.Params(),
(1, 2, 0): VickreyAuctionModule.Params(),
(1, 2, 1): VickreyAuctionModule.Params(),
(1, 2, 2): VickreyAuctionModule.Params(),
(2, 0, 0): VickreyAuctionModule.Params(),
(2, 0, 1): VickreyAuctionModule.Params(),
(2, 0, 2): VickreyAuctionModule.Params(),
(2, 1, 0): VickreyAuctionModule.Params(),
(2, 1, 1): VickreyAuctionModule.Params(),
(2, 1, 2): VickreyAuctionModule.Params(),
(2, 2, 0): VickreyAuctionModule.Params(),
(2, 2, 1): VickreyAuctionModule.Params(),
(2, 2, 2): VickreyAuctionModule.Params(),
})
# vickrey_auction.determine_effective_modifiers(actions,segment=(0, 1, 2))
results = vickrey_auction.get_auction_results(actions=actions)
for key, value in results.items():
print("{}: {}".format(key, value))
print("")
self.assertTrue(True)