def buy(self, product):
# if not enough money in wallet, don't proceed
if self.wallet < product.price:
return
# purchase the product from market
Market.buy(self, product)
# add product to the owned products list
self.owned_products.add(product)
def buy(self, products):
# enable buyer to buy more than one products
amount = 0
for product in products:
amount += product.stock_price
# if not enough money in wallet, don't proceed
if self.wallet < amount: # enable buyer to buy more than one products
logging.info(
"[Customer]: (%s,%d) didn't have enough money to buy Products:[%s] from seller %s",
self.name, self.tick_count, products[0].product_name,
products[0].seller_id)
return
# if there is not enough stock, no transaction
if products[0].stock_quantity <= 0:
logging.info(
"[Customer]: (%s,%d) Seller didn't have enough stock to sell the products:[%s], "
"so the customer didn't buy", products[0].seller_id,
self.tick_count, products[0].product_name)
return
if products[0].stock_quantity < len(products):
logging.info(
"[Customer]: (%s,%d) Seller didn't have enough stock to sell the products:[%s], "
"so the customer didn't buy", products[0].seller_id,
self.tick_count, products[0].product_name)
return
products_str = ', '.join(x.product_name for x in products)
logging.info(
"[Customer]: (%s,%d) buy the Products:[%s] from seller%s with price %d",
self.name, self.tick_count, products_str, products[0].seller_id,
amount)
# purchase the product from market
Market.buy(self, products)
# add product to the owned products list
for product in products:
self.owned_products.add(product)
def consider(self, product):
# if not enough money in wallet, don't proceed
if self.wallet < product.price:
print('Out of money ' + self.name)
return
decision = self.purchase_decision(product)
if not decision:
return
# purchase the product from market
seller = Market.buy(self, product)
if seller != 0:
self.dataCenter.data_ranking(obj_data=[self, product, seller], data_type='customer')
self.owned_products.add(product)
def buy(self, product_list):
"""
Consumer decided to buy a 'product'.
:param product_list: list of products
:return: none
"""
# if not enough money in wallet, don't proceed
total_price = sum(product.price for product in product_list)
if self.wallet < total_price:
return
# purchase the product from market
if Market.buy(self, product_list):
# add product to the owned products list
for product in product_list:
self.owned_products.append(product)
purge_ratio=0.1)
market = Market(x_test, p=p)
x, y = tools.build_ar_x_y(x_train, p=p, rest=2)
x = np.array(x).reshape((-1, p, 30))
y = np.array(y).reshape((-1, 30, 1))
models = [
RidgeCV(alphas=[0.2, 0.3, 0.6], cv=6, fit_intercept=True)
for i in range(30)
]
for i in range(30):
models[i].fit(get_ith_col_x(x, i), get_ith_col_y(y, i))
# model = Lstm(time_steps=p, input_size=30, output_size=30)
# model.load_data(x, y, units=50, epochs=20, batch_size=50)
market.buy(P.items())
trades = []
y_preds = []
cash_y = []
cash_x = []
for prices in market.iterate(tick_names=False):
y_pred = [
m.predict(get_ith_col_x(np.array(prices).reshape((-1, p, 30)), i))
for i, m in enumerate(models)
]
y_pred = np.array(y_pred).flatten()
y_preds.append(y_pred)
returns = np.divide(
np.subtract(np.array(y_pred), np.array(prices[-1])),
np.array(prices[-1]))
returns = returns.flatten()
from good import Good
from market import Market
from universe import Universe
from simulation import Simulation
universe = Universe()
simulation = Simulation(universe)
simulation.run()
# Some basic market stuff
foodMarket = Market(Good.food, 100.0, 1.0, 0)
print("Current food price: " + str(foodMarket.current_price()))
print("Sold food for: " + str(foodMarket.sell_one()))
print("Sold food for: " + str(foodMarket.sell_one()))
print("Sold food for: " + str(foodMarket.sell_one()))
print("Bought 3 food for: " + str(foodMarket.buy(3)))
print("Sold 10 food for: " + str(foodMarket.sell(10)))
print("Current food price: " + str(foodMarket.current_price()))
print("Done")
