Update src/vis_utils.py

src/vis_utils.py

@@ -241,10 +241,10 @@ def plot_affinity_results(method_names, metric, affinity_path="/tmp/affinity_res
     sns.set_theme(style="whitegrid", color_codes=True)
 
     # Create the boxplot
-    ax = sns.boxplot(data=df_corr, whis=np.inf, orient="h")
+    ax = sns.boxplot(data=df, whis=np.inf, orient="h")
 
     # Add a swarmplot on top of the boxplot
-    sns.swarmplot(data=df_corr, orient="h", color=".1", ax=ax)
+    sns.swarmplot(data=df, orient="h", color=".1", ax=ax)
 
     # Set labels and x-axis formatting
     ax.set_xlabel("Percent Pearson Correlation")
@@ -255,9 +255,9 @@ def plot_affinity_results(method_names, metric, affinity_path="/tmp/affinity_res
     ax.grid(visible=True, which='minor', color='whitesmoke', linewidth=0.5)
 
     # Add reference lines
-    ax.plot((best_pipr, best_pipr), (-1, len(df_corr.columns) + 1), color='black', label='Best PIPR')
-    ax.plot((baseline_ac, baseline_ac), (-1, len(df_corr.columns) + 1), color='purple', linestyle='dashed', label='Baseline AC')
-    ax.plot((baseline_ctd, baseline_ctd), (-1, len(df_corr.columns) + 1), color='brown', linestyle='dashed', label='Baseline CTD')
+    ax.plot((best_pipr, best_pipr), (-1, len(df.columns) + 1), color='black', label='Best PIPR')
+    ax.plot((baseline_ac, baseline_ac), (-1, len(df.columns) + 1), color='purple', linestyle='dashed', label='Baseline AC')
+    ax.plot((baseline_ctd, baseline_ctd), (-1, len(df.columns) + 1), color='brown', linestyle='dashed', label='Baseline CTD')
 
     # Apply custom color settings to y-axis labels
     for label in ax.get_yticklabels():