Add graphs

graphs_plot.py

@@ -1,10 +1,11 @@
 import os
+import numpy as np
 import pandas as pd
 import seaborn as sns
 import matplotlib.pyplot as plt
 from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
 
-
+"""
 def tabulate_events(dpath):
     files = os.listdir(dpath)[0]
     summary_iterators = [EventAccumulator(os.path.join(dpath, files)).Reload()]
@@ -43,7 +44,43 @@ for tag, values in events.items():
 
 df = pd.DataFrame(data)
 print(df.head())
+exit()
 
 plt.figure(figsize=(10,6))
 sns.lineplot(data=df, x='step', y='value', hue='tag', ci='sd')
 plt.show()
+"""
+
+
+from tensorboard.backend.event_processing import event_accumulator
+
+
+
+def data_from_tb(files):
+    all_steps, all_rewards = [], []
+    for file in files:
+        ea = event_accumulator.EventAccumulator(file, size_guidance={'scalars': 0})
+        ea.Reload()
+
+        episode_rewards = ea.Scalars('train/episode_reward')
+        steps = [event.step for event in episode_rewards][:990000]
+        rewards = [event.value for event in episode_rewards][:990000]
+        all_steps.append(steps)
+        all_rewards.append(rewards)
+    return all_steps, all_rewards
+
+
+files = ['/home/vedant/pytorch_sac_ae/log/runs/tb_21_05_2023-13_19_36/events.out.tfevents.1684667976.cpswkstn6-nvidia4090.1749060.0',
+         '/home/vedant/pytorch_sac_ae/log/runs/tb_22_05_2023-09_56_30/events.out.tfevents.1684742190.cpswkstn6-nvidia4090.1976229.0']
+
+all_steps, all_rewards = data_from_tb(files)
+mean_rewards = np.mean(all_rewards, axis=0)
+std_rewards = np.std(all_rewards, axis=0)
+mean_steps = np.mean(all_steps, axis=0) 
+
+df = pd.DataFrame({'Steps': mean_steps,'Rewards': mean_rewards,'Standard Deviation': std_rewards})
+
+sns.relplot(x='Steps', y='Rewards', kind='line', data=df, ci="sd")
+plt.fill_between(df['Steps'], df['Rewards'] - df['Standard Deviation'], df['Rewards'] + df['Standard Deviation'], color='b', alpha=.1)
+plt.title("Mean Rewards vs Steps with Standard Deviation")
+plt.show()