def step(self, action):
# 0: Sit
# 1: But
# 2: Sell
assert (action in (0, 1, 2))
# State transition
next_state = getState(self.data, self.t + 1, self.window_size + 1)
# Reward
if action == 0:
reward = 0
elif action == 1:
reward = 0
self.agent.inventory.append(self.data[self.t])
print("Buy: " + formatPrice(self.data[self.t]))
else:
if len(self.agent.inventory) > 0:
bought_price = self.agent.inventory.pop(0)
profit = self.data[self.t] - bought_price
reward = max(profit, 0)
self.total_profit += profit
print("Sell: " + formatPrice(self.data[self.t]) +
" | Profit: " + formatPrice(profit))
else:
reward = 0 # try to sell, but con't do
done = True if self.t == len(self.data) - 2 else False
self.t += 1
return next_state, reward, done, {}
def reset(self):
self.t = 0
self.total_profit = 0
return getState(self.data, self.t, self.window_size + 1)
print(
colored(
'To {} ~~> {} {:.7f}\n\n'.format(l, currency.upper(),
data[-1]).center(width), 'magenta'))
for e in range(episode_count + 1):
print(
colored(" {}/BTC".format(asset_name).center(width),
'yellow',
attrs=['bold']))
print(
colored("> Episode {}/{}\n".format(str(e),
str(episode_count)).center(width),
'yellow',
attrs=['bold']))
state = getState(data, 0, window_size + 1)
total_profit = 0
agent.inventory = []
for t in range(l):
action = agent.act(state)
next_state = getState(data, t + 1, window_size + 1)
reward = 0
print("> {} BTC {:.7f}".format(t, data[t]), end='\r') #hold
if action == 1: # buy
agent.inventory.append(data[t])
print(colored("> {} BTC {:.7f} |".format(t, data[t]), 'cyan'),
end='\r')
elif action == 2 and len(agent.inventory) > 0: # sell
bought_price = agent.inventory.pop(0)
reward = max(data[t] - bought_price, 0)
total_profit += data[t] - bought_price
import sys
# parameters: python testing.py {stock} {model_name} (python 3.6)
stock_name, model_name = sys.argv[1], sys.argv[2]
model = load_model("models/" + model_name)
state_size = model.layers[0].input.shape.as_list()[1]
broker = Broker(state_size, True, model_name)
data = getStockDataVector(stock_name)
data_size = len(data) - 1
batch_size = 100
gain = 0
broker.trades_list = []
reward = 0
state = getState(data, 0, state_size + 1)
for t in range(data_size):
action = broker.act(state)
if action == 1 and broker.portfolio >= data[t]: # buy
broker.trades_list.append(data[t])
broker.portfolio = broker.portfolio - data[t]
print("Bought: " + formatPrice(data[t]) + "| Portfolio Value: " + formatPrice(broker.portfolio))
reward = 0
elif action == 2 and len(broker.trades_list) > 0: # sell
buying_price = broker.trades_list.pop(0)
def getPinState():
"""Returns devices' state as JSON"""
devices = getState()
return json.dumps(devices)
def index():
"""Index page"""
devices = getState()
return render_template('index.html', devices=devices, polling=app.config['GPIO_POLLING_DELAY'], display=app.config['DISPLAY_PIN_ID'])