Update src/vis_utils.py

src/vis_utils.py

@@ -301,7 +301,7 @@ def plot_affinity_results(method_names, metric, affinity_path="/tmp/affinity_res
     return filename
 
 def update_metric_choices(benchmark_type):
-    if benchmark_type == 'similarity':
+    if benchmark_type == 'Semantic Similarity Inference':
         # Show x and y metric selectors for similarity
         metric_names = benchmark_specific_metrics.get(benchmark_type, [])
         return (
@@ -309,7 +309,7 @@ def update_metric_choices(benchmark_type):
             gr.update(choices=metric_names, value=metric_names[1], visible=True),
             gr.update(visible=False), gr.update(visible=False),  gr.update(visible=False)
         )
-    elif benchmark_type == 'function':
+    elif benchmark_type == 'Ontology-based Function Prediction':
         # Show aspect and dataset type selectors for function
         aspect_types = benchmark_specific_metrics[benchmark_type]['aspect_types']
         metric_types = benchmark_specific_metrics[benchmark_type]['dataset_types']
@@ -319,7 +319,7 @@ def update_metric_choices(benchmark_type):
             gr.update(visible=False), 
             gr.update(choices=metric_types, value=metric_types[0], visible=True)
         )
-    elif benchmark_type == 'family':
+    elif benchmark_type == 'Drug Target Protein Family Classification':
         # Show dataset and metric selectors for family
         datasets = benchmark_specific_metrics[benchmark_type]['datasets']
         metrics = benchmark_specific_metrics[benchmark_type]['metrics']
@@ -328,7 +328,7 @@ def update_metric_choices(benchmark_type):
             gr.update(choices=datasets, value=datasets[0], visible=True),
             gr.update(visible=False)
         )
-    elif benchmark_type == 'affinity':
+    elif benchmark_type == 'Protein Protein Binding Affinity Estimation':
         # Show single metric selector for affinity
         metrics = benchmark_specific_metrics[benchmark_type]
         return (