class_docstr: Event topic class with logging statistics based only on rewards, therefore applicable to any valid
  reinforcement learning environment.
class_docstr_tok: ["Event","topic","class","with","logging","statistics","based","only","on","rewards",",","therefore","applicable","to","any","valid","reinforcement","learning","environment","."]
docstr: reward after being processed by reward wrappers 
docstr_tok: ["reward","after","being","processed","by","reward","wrappers"]
code: def reward_processed(
      self, step_key: str, agent_name: str, value: float
  ):
      """reward after being processed by reward wrappers"""
  
file_path: maze/maze/core/log_events/monitoring_events.py
imports: from abc import ABC
  import numpy
  from maze.core.log_events.log_create_figure_functions import create_categorical_plot, create_violin_distribution, create_binary_plot
  from maze.core.log_stats.event_decorators import define_episode_stats, define_step_stats, define_epoch_stats, define_stats_grouping, define_plot
  from maze.core.log_stats.reducer_functions import histogram
label_desc: Use image node_id 1 for calling the RewardEvents obj's underlying member method code with example usage: obj.reward_processed(step_key, agent_name, value) without return types