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65 lines
1.9 KiB
65 lines
1.9 KiB
import pickle
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import gym
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import numpy as np
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from matplotlib import pyplot as plt
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# numpy precision for printing
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np.set_printoptions(precision=3, suppress=True)
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plt.ion() # interactive plotting
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fig, ax = plt.subplots()
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colors = ["xkcd:orange", "xkcd:forest green", "xkcd:gray", "xkcd:light blue"]
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plots = [None] * 4
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env = gym.make("CartPole-v1")
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observation, info = env.reset(seed=42, return_info=True)
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max_steps = 100
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num_samples = 500
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samples = np.random.randn(num_samples, 4)
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data = []
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for lam in samples:
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breakpoints = []
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score = 0
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obs = []
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for n in range(max_steps):
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ax.cla()
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# action = env.action_space.sample()
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action = 1 if lam.T @ observation < 0 else 0
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# action = 1 if observation[0] - observation[3] < 0 else 0
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observation, reward, done, info = env.step(action)
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score += reward
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obs.append(observation.tolist())
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o = np.array(obs)
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var = np.var(o[-int(score) :, :], axis=0)
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for q in range(4):
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lines = np.hstack([o[:, q], np.zeros(max_steps - n)])
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ax.plot(range(max_steps + 1), lines, c=colors[q])
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ax.set_title(f"Reward: {int(score)}, Variance: {var}")
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ax.set_ylim([-3, 3])
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if done or n == max_steps:
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breakpoints.append(n)
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observation, info = env.reset(return_info=True)
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# print(score, observation)
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score = 0 # reset score
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# draw break-point lines when game is lost
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for b in breakpoints:
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ax.vlines(
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b, np.min(o, axis=0).min(), np.max(o, axis=0).max(), color="black", lw=2
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)
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fig.canvas.draw()
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fig.show()
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fig.canvas.flush_events()
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env.render()
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data.append({"lam": lam, "obs": obs, "break": breakpoints})
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pickle.dump(data, open("data.pkl", "wb")) # dump data frequently
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stop = input("Press any key to close.")
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plt.close()
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env.close()
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