init

stats.py

@@ -104,13 +104,13 @@ 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]]]
+    fig = plt.figure()
+    _df_p = df_p[[f"min entity: {mef}, max predicate: 10" for mef in [1, 2, 3, 4]]]
     _df_p.columns = [f"min entity: {mef}" for mef in [1, 2, 3, 4]]
     ax = sns.lineplot(data=_df_p, linewidth=2.5)
-    ax.set(xlabel='unique predicates sorted by frequency', ylabel='number of triples', title='Predicate Distribution (max predicate: 100)')
+    ax.set(xlabel='unique predicates sorted by frequency', ylabel='number of triples', title='Predicate Distribution (max predicate: 10)')
     ax.get_figure().savefig("data/stats.predicate_distribution.png", bbox_inches='tight')
     ax.get_figure().clf()