init

stats.py

@@ -104,6 +104,7 @@ if __name__ == '__main__':
     print(df_size.to_markdown())
 
     # plot predicate distribution
+    fig = plt.figure()
     df_p = pd.DataFrame([dict(enumerate(sorted(p.values(), reverse=True))) for p in p_dist_full]).T
     df_p.columns = [f"min entity: {mef}, max predicate: {mpf}" for mef, mpf in candidates]
     _df_p = df_p[[f"min entity: {mef}, max predicate: 100" for mef in [1, 2, 3, 4]]]
@@ -116,7 +117,6 @@ if __name__ == '__main__':
     # plot entity distribution
     df_e = pd.DataFrame([dict(enumerate(sorted(e.values(), reverse=True))) for e in e_dist_full]).T
     df_e.columns = [f"min entity: {mef}, max predicate: {mpf}" for mef, mpf in candidates]
-
     fig, axes = plt.subplots(2, 2, constrained_layout=True)
     fig.suptitle('Entity Distribution over Different Configurations')
     for (x, y), mpf in zip([(0, 0), (0, 1), (1, 0), (1, 1)], [100, 50, 25, 10]):