class_docstr: A linear dynamical system characterized by A, B, Q, and R.
  
  Suppose x_t is current state, u_t is current action, then:
  
  x_t+1 = A x_t + B u_t
  Reward_t = x_t' Q x_t + u_t' R u_t
code: def reset(self):
      self.state = np.random.randint(
          low=-1, high=2, size=(self.state_dim,)
      ).astype(float)
      self.step_cnt = 0
      return self.state
  
file_path: ReAgent/reagent/gym/envs/dynamics/linear_dynamics.py
imports: import logging
  import numpy
  from gym import Env
  from gym.spaces import Box
label_desc: Use image node_id 3 for calling the LinDynaEnv obj's underlying member method code with example usage: obj.reset() and returns: self