Update app.py

app.py

@@ -678,13 +678,17 @@ with gr.Blocks(css="""
             # To use your preferred DeepMIMO scenarios for the custom dataset, please [clone the model](https://huggingface.co/wi-lab/lwm) and follow the instructions below:
             from input_preprocess import DeepMIMO_data_gen deepmimo_data_cleaning label_gen
             
-            scenario_names = ['city_19_oklahoma']
+            scenario_names = np.array([
+                "city_18_denver", "city_15_indianapolis", "city_19_oklahoma", 
+                "city_12_fortworth", "city_11_santaclara", "city_7_sandiego"
+            ])
+            scenario_name = scenario_names[0]
             
-            deepmimo_data = [DeepMIMO_data_gen(scenario_name) for scenario_name in scenario_names]
-            cleaned_deepmimo_data = [deepmimo_data_cleaning(deepmimo_data[scenario_idx]) for scenario_idx in range(len(scenario_names))]
+            deepmimo_data = DeepMIMO_data_gen(scenario_name)
+            cleaned_deepmimo_data = deepmimo_data_cleaning(deepmimo_data)
             
-            channels = np.squeeze(np.array(cleaned_deepmimo_data[0]), axis=1)
-            labels = label_gen('LoS/NLoS Classification', deepmimo_data[0], scenario_names, n_beams=64)
+            channels = np.squeeze(np.array(cleaned_deepmimo_data), axis=1)
+            labels = label_gen('LoS/NLoS Classification', deepmimo_data, scenario_name)
             ```
         """)