class_docstr: A component to compute the reward at each step of an episode.
docstr: Computes the reward for the current step of an episode.
  
  Parameters
  ----------
  env : `TradingEnv`
      The trading environment
  
  Returns
  -------
  float
      The computed reward.
docstr_tok: ["Computes","the","reward","for","the","current","step","of","an","episode",".","Parameters","--","--","--","--","--","env",":","`","TradingEnv","`","The","trading","environment","Returns","--","--","--","-","float","The","computed","reward","."]
code: def reward(self, env: "TradingEnv") -> float:
      """Computes the reward for the current step of an episode.
  
      Parameters
      ----------
      env : `TradingEnv`
          The trading environment
  
      Returns
      -------
      float
          The computed reward.
      """
      raise NotImplementedError()
  
imports: from abc import abstractmethod
  from tensortrade.core.component import Component
  from tensortrade.core.base import TimeIndexed
label_desc: Use image node_id 1 for calling the RewardScheme obj's underlying member method code with example usage: obj.reward(env) without return types