def show_train_result(result, val_position, initial_offset):
""" Displays training results. """
if val_position == initial_offset or val_position == 0.0:
logging.info('Episode {}/{} - Train Position: {} Val Position: USELESS Train Loss: {:.4f} (~{:.4f} secs)'
.format(result[0], result[1], format_position(result[2]), result[3], result[4]))
else:
logging.info('Episode {}/{} - Train Position: {} Val Position: {} Train Loss: {:.4f} (~{:.4f} secs)'
.format(result[0], result[1], format_position(result[2]), format_position(val_position), result[3], result[4]))
def show_train_result(result, val_position, initial_offset):
if val_position == initial_offset or val_position == 0.0:
print(
'Episode {}/{} - Train Position: {} Val Position: USELESS Train Loss: {:.4f} (~{:.4f} secs)'
.format(result[0], result[1], format_position(result[2]),
result[3], result[4]))
else:
print(
'Episode {}/{} - Train Position: {} Val Position: {} Train Loss: {:.4f} (~{:.4f} secs)'
.format(result[0], result[1], format_position(result[2]),
format_position(val_position), result[3], result[4]))
def evaluate_model(agent, data, window_size, debug):
data_length = len(data) - 1
state = get_state(data, 0, window_size + 1)
total_profit = 0
agent.inventory = []
for t in range(data_length):
action = agent.act(state, is_eval=True)
# SIT
next_state = get_state(data, t + 1, window_size + 1)
reward = 0
# BUY
if action == 1:
agent.inventory.append(data[t])
if debug:
logging.debug('Buy at: {}'.format(format_currency(data[t])))
# SELL
elif action == 2 and len(agent.inventory) > 0:
bought_price = agent.inventory.pop(0)
reward = max(data[t] - bought_price, 0)
total_profit += data[t] - bought_price
if debug:
logging.debug('Sell at: {} | Position: {}'.format(
format_currency(data[t]),
format_position(data[t] - bought_price)))
done = True if t == data_length - 1 else False
agent.memory.append((state, action, reward, next_state, done))
state = next_state
if done:
return total_profit
def show_eval_result(model_name, profit, initial_offset):
if profit == initial_offset or profit == 0.0:
logging.info('{}: USELESS\n'.format(model_name))
else:
logging.info('{}: {}\n'.format(model_name, format_position(profit)))
