code: def render(self, mode="human", close=False):
      if self.simple_render:
          observation = np.zeros((20, 20 * self.chain_length))
          observation[:, self.state * 20 : (self.state + 1) * 20] = 255
          return observation
      else:
          # lazy loading of networkx and matplotlib to allow using the environment without installing them if
          # necessary
          import networkx as nx
          from networkx.drawing.nx_agraph import graphviz_layout
          import matplotlib.pyplot as plt
  
          if not hasattr(self, "G"):
              self.states = list(range(self.chain_length))
              self.G = nx.DiGraph(directed=True)
              for i, origin_state in enumerate(self.states):
                  if i < self.chain_length - 1:
                      self.G.add_edge(
                          origin_state, origin_state + 1, weight=0.5
                      )
                  if i > 0:
                      self.G.add_edge(
                          origin_state,
                          origin_state - 1,
                          weight=0.5,
                      )
                  if i == 0 or i < self.chain_length - 1:
                      self.G.add_edge(
                          origin_state,
                          origin_state,
                          weight=0.5,
                      )
  
          fig = plt.gcf()
          if np.all(fig.get_size_inches() != [10, 2]):
              fig.set_size_inches(5, 1)
          color = ["y"] * (len(self.G))
          color[self.state] = "r"
          options = {
              "node_color": color,
              "node_size": 50,
              "width": 1,
              "arrowstyle": "-|>",
              "arrowsize": 5,
              "font_size": 6,
          }
          pos = graphviz_layout(self.G, prog="dot", args="-Grankdir=LR")
          nx.draw_networkx(self.G, pos, arrows=True, **options)
          fig.canvas.draw()
          data = np.fromstring(
              fig.canvas.tostring_rgb(), dtype=np.uint8, sep=""
          )
          data = data.reshape(
              fig.canvas.get_width_height()[::-1] + (3,)
          )
          return data
  
file_path: coach/rl_coach/environments/toy_problems/exploration_chain.py
imports: from enum import Enum
  import gym
  import numpy
  from gym import spaces
label_desc: Use image node_id 7 for calling the ExplorationChain obj's underlying member method code with example usage: obj.render(mode, close) and returns: observation, data