try_pl.py 文件源码

def execute(symbol, begin, end, days, plot, model_path,random):
    print model_path
    model = load_model(model_path)
    env = gym.make('trading-v0').env
    env.initialise(symbol=symbol, start=begin, end=end, days=days, random = random)
    state_size = env.observation_space.shape[0]
    state = env.reset()
    done = False
    while not done:
        state = state.reshape(1, state_size)
        # state = state.reshape(1, 1, state_size)
        qval = model.predict(state, batch_size=1)
        action = (np.argmax(qval))
        state, _, done, info = env.step(action)

        # log.info("%s,%s,%s,%s",state, _, done, info)
        # log.info("\n%s", env.sim.to_df())
        if plot:
           env.render()