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cleanup

feature/notebook
Michael Pilosov 3 years ago
parent
commit
177c1ff006
  1. 12
      sample.py

12
sample.py

@ -1,10 +1,7 @@
import sys
import pickle
import gym
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.animation import FuncAnimation
from time import sleep
# numpy precision for printing
np.set_printoptions(precision=3, suppress=True)
@ -25,7 +22,7 @@ data = []
for lam in samples:
breakpoints = []
score = 0
O = []
obs = []
for n in range(max_steps):
ax.cla()
# action = env.action_space.sample()
@ -33,8 +30,8 @@ for lam in samples:
# action = 1 if observation[0] - observation[3] < 0 else 0
observation, reward, done, info = env.step(action)
score += reward
O.append(observation.tolist())
o = np.array(O)
obs.append(observation.tolist())
o = np.array(obs)
var = np.var(o[-int(score) :, :], axis=0)
for q in range(4):
lines = np.hstack([o[:, q], np.zeros(max_steps - n)])
@ -59,9 +56,8 @@ for lam in samples:
fig.show()
fig.canvas.flush_events()
env.render()
# sleep(0.01)
data.append({"lam": lam, "obs": O, "break": breakpoints})
data.append({"lam": lam, "obs": obs, "break": breakpoints})
pickle.dump(data, open("data.pkl", "wb")) # dump data frequently
stop = input("Press any key to close.")

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