Update src/vis_utils.py

src/vis_utils.py

@@ -30,7 +30,7 @@ def benchmark_plot(benchmark_type, methods_selected, x_metric, y_metric, aspect,
     elif benchmark_type == 'function':
         return plot_function_results(methods_selected, aspect, single_metric)
     elif benchmark_type == 'family':
-        return plot_family_results(methods_selected, dataset, single_metric)
+        return plot_family_results(methods_selected, dataset)
     elif benchmark_type == "affinity":
         return plot_affinity_results(methods_selected, single_metric)
     else:
@@ -170,7 +170,7 @@ def plot_function_results(method_names, aspect, metric, function_path="/tmp/func
 
     return filename
 
-def plot_family_results(method_names, dataset, metric, family_path="/tmp/family_results.csv"):
+def plot_family_results(method_names, dataset, family_path="/tmp/family_results.csv"):
     if not os.path.exists(family_path):
         benchmark_types = ["similarity", "function", "family", "affinity"] #download all files for faster results later
         download_from_hub(benchmark_types)
@@ -180,14 +180,14 @@ def plot_family_results(method_names, dataset, metric, family_path="/tmp/family_
     # Filter by method names and selected dataset columns
     df = df[df['Method'].isin(method_names)]
 
-    # Filter columns based on the aspect and metrics
+    # Filter columns based on the dataset and metrics
     value_vars = [col for col in df.columns if col.startswith(f"{dataset}_") and "_" in col]
 
     # Reshape the DataFrame to long format
-    df_long = pd.melt(df, id_vars=["Method"], value_vars=value_vars, var_name="Aspect_Metric_Fold", value_name="Value")
+    df_long = pd.melt(df, id_vars=["Method"], value_vars=value_vars, var_name="Dataset_Metric_Fold", value_name="Value")
 
-    # Split the "Aspect_Metric_Fold" column into "Metric" and "Fold"
-    df_long[["Metric", "Fold"]] = df_long["Aspect_Metric_Fold"].str[len(aspect) + 1:].str.split("_", expand=True)
+    # Split the "Dataset_Metric_Fold" column into "Metric" and "Fold"
+    df_long[["Metric", "Fold"]] = df_long["Dataset_Metric_Fold"].str[len(dataset) + 1:].str.split("_", expand=True)
     df_long["Fold"] = df_long["Fold"].astype(int)
 
     # Set up the plot