I have a reinforcement learning custom env made with openAI gym. How can I improve the def _**init_plt(self) function** below? I included the code before it for reference as well. Please be brutal with your review.

scroll down for init function, generates a subplot with axes:

```
# Imports
import gym
import numpy as np
import random
from matplotlib import pyplot as plt
import matplotlib as mpl
import math
import os
class BeamEnv(gym.Env):
def __init__(self, obs_low_bounds = np.array(( 0, 0, 1.18e10, -45)),
obs_high_bounds = np.array(( 12, 12, -1.18e10, 45)),
obs_bin_sizes = np.array((0.5, 0.5, 6, 5))):
"""Environment for a ball and beam system where agent has control of tilt.
Args:
obs_low_bounds (list, optional): (target location(in), ball location(in),
ball velocity(in/s), beam angle(deg)). Defaults to ( 0, 0, "TBD", -45).
obs_high_bounds (list, optional): As above so below. Defaults to (12, 12, "TBD", 45).
"""
super(BeamEnv, self).__init__()
# Hyperparameters
self.ACC_GRAV = 386.22 # (in/s2)
self.MOTOR_SPEED = 46.875 # 1.28(sec/60deg) converted to (deg/s)
self.TIME_STEP = 0.1 # (s)
# Declare bounds of observations
self.obs_low_bounds = obs_low_bounds
self.obs_high_bounds = obs_high_bounds
self._set_velocity_bounds()
# Declare bin sizes of observations
self.obs_bin_sizes = obs_bin_sizes
# Bin observations
self.obs = ()
self.obs_sizes = ()
for i in range(4):
self.obs.append(np.sort(
np.append(
np.arange(self.obs_low_bounds(i), self.obs_high_bounds(i) + self.obs_bin_sizes(i), self.obs_bin_sizes(i)),
0)))
self.obs_sizes.append(len(self.obs(i)))
# Declare observation space
self.observation_space = gym.spaces.MultiDiscrete(self.obs_sizes)
# Action Space
# increase, decrease or keep current angle
self.action_space = gym.spaces.Discrete(3)
# Reward Range
self.reward_range = (-1, 1)
self.step_count = 0
self.sample_freq = 10
**def _init_plt(self):**
"""Initiates the animated line plot.
"""
if self.fig:
return
plt.close()
fig = plt.figure()
self.fig = fig
# fig.set_dpi(100)
# fig.set_size_inches(7, 6.5)
ax = plt.axes(xlim=(-2, 14), ylim=(0, 20))
ax.set_aspect('equal')
self.ax = ax
circle = plt.Circle((self.ball_location, 10), 1)
self.circle = circle
ax.add_patch(circle)
rect = plt.Rectangle((0, 10), 12, 0.1, linewidth=1, edgecolor='r', facecolor='r')
self.rect = rect
ax.add_patch(rect)
x = self.target_location
size = 1
target = plt.Polygon(((x, 10-0.1), (x-size/2, 10-size), (x+size/2, 10-size)), color='b')
ax.add_patch(target)
plt.show(block=False)
plt.pause(0.05)
```