Move LivePlot under examples for now

examples/utilities/live_plot.py

@@ -0,0 +1,68 @@
+import gym
+
+import matplotlib
+import matplotlib.pyplot as plt
+
+class LivePlot(object):
+    def __init__(self, outdir, data_key='episode_rewards', line_color='blue'):
+        """
+        Liveplot renders a graph of either episode_rewards or episode_lengths
+
+        Args:
+            outdir (outdir): Monitor output file location used to populate the graph
+            data_key (Optional[str]): The key in the json to graph (episode_rewards or episode_lengths).
+            line_color (Optional[dict]): Color of the plot.
+        """
+        self.outdir = outdir
+        self._last_data = None
+        self.data_key = data_key
+        self.line_color = line_color
+
+        #styling options
+        matplotlib.rcParams['toolbar'] = 'None'
+        plt.style.use('ggplot')
+        plt.xlabel("")
+        plt.ylabel(data_key)
+        fig = plt.gcf().canvas.set_window_title('')
+
+    def plot(self):
+        results = gym.monitoring.monitor.load_results(self.outdir)
+        data =  results[self.data_key]
+
+        #only update plot if data is different (plot calls are expensive)
+        if data !=  self._last_data:
+            self._last_data = data
+            plt.plot(data, color=self.line_color)
+
+            # pause so matplotlib will display
+            # may want to figure out matplotlib animation or use a different library in the future
+            plt.pause(0.000001)
+
+if __name__ == '__main__':
+    env = gym.make('CartPole-v0')
+    outdir = '/tmp/random-agent-results'
+    env.monitor.start(outdir, force=True, seed=0)
+
+    # You may optionally include a LivePlot so that you can see
+    # how your agent is performing.  Use plotter.plot() to update
+    # the graph.
+    plotter = LivePlot(outdir)
+
+    episode_count = 100
+    max_steps = 200
+    reward = 0
+    done = False
+
+    for i in range(episode_count):
+        ob = env.reset()
+
+        for j in range(max_steps):
+            ob, reward, done, _ = env.step(env.action_space.sample())
+            if done:
+                break
+
+            plotter.plot()
+            env.render()
+
+    # Dump result info to disk
+    env.monitor.close()