added first working MAPPO implementation

studies/playground_file.py

@@ -1,32 +1,22 @@
-import numpy as np
 import pandas as pd
 from pathlib import Path
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-study_root = Path(__file__).parent / 'entropy_study'
-names_all = ['basic_gru', 'layernorm_gru', 'spectralnorm_gru', 'nonorm_gru']
-names_only_1 = ['L2OnlyAh_gru', 'L2OnlyChAh_gru', 'L2OnlyMix_gru', 'basic_gru']
-names_only_2 = ['L2NoCh_gru', 'L2NoAh_gru', 'nomix_gru', 'basic_gru']
 
-names = names_only_2
-#names = ['nonorm_gru']
-# /Users/romue/PycharmProjects/EDYS/studies/normalization_study/basic_gru#3
-csvs = []
-for name in ['basic_gru', 'nonorm_gru', 'spectralnorm_gru']:
-    for run in range(0, 1):
+dfs = []
+for name in ['l2snac', 'iac', 'snac', 'seac']:
+    for c in range(5):
         try:
-            df = pd.read_csv(study_root / f'{name}#{run}' / 'results.csv')
-            df = df[df.agent == 'sum']
-            df = df.groupby(['checkpoint', 'run']).mean().reset_index()
-            df['method'] = name
-            df['run_'] = run
-
-            df.reward = df.reward.rolling(15).mean()
-            csvs.append(df)
+            study_root = Path(__file__).parent / name / f'{name}#{c}'
+            df = pd.read_csv(study_root / 'results.csv', index_col=False)
+            df.reward = df.reward.rolling(100).mean()
+            df['method'] = name.upper()
+            dfs.append(df)
         except Exception as e:
-            print(f'skipped {run}\t {name}')
+            pass
 
-csvs = pd.concat(csvs).rename(columns={"checkpoint": "steps*2e3", "B": "c"})
-sns.lineplot(data=csvs, x='steps*2e3', y='reward', hue='method', palette='husl', ci='sd', linewidth=1.8)
-plt.savefig('entropy.png')
+df = pd.concat(dfs).reset_index()
+sns.lineplot(data=df, x='episode', y='reward', hue='method', palette='husl', ci='sd', linewidth=1.5)
+plt.savefig('study.png')
+print('saved image')