Update app.py

app.py

@@ -10,62 +10,64 @@ subgroup_select1 = pn.widgets.Select(name='Layers', options=["conv2d5", "conv2d6
 subgroup_select2 = pn.widgets.Select(name='Layers', options=["conv2d5", "conv2d6", "conv2d7", "conv2d8", "conv2d9", "linear1", "linear2"])
 
 # Bind the widgets to the create_plot function
-@pn.depends(subgroup_select.param.value)
-def create_plot(layers):
-    df_train_umap = pd.read_csv(f"https://raw.githubusercontent.com/jeonghin/si649_project2_sparcs/main/data/classifier_1_Test_Data/UMAP_data/Raw_data_UMAP_{layers}.csv").sample(n=5000, random_state=19)
-    color_dict = {
-        "ClassifierA_Cr203_C6": "#B3262A",
-        "ClassifierA_test_stim": "#2f559a",
-        "ClassifierA_test_unstim": "#5AADC5",
-    }
-
-    # Define a selection for zooming and panning (interval)
-    zoom = alt.selection_interval(bind='scales')
-
-    # Define a selection for the legend
-    legend_selection = alt.selection_multi(fields=['class_label'], bind='legend')
-
-
-    # Create the Altair chart object
-    chart = alt.Chart(df_train_umap).mark_circle(size=4, opacity=1).encode(
-        x=alt.X("UMAP_1:Q", scale=alt.Scale(zero=False)),
-        y=alt.Y("UMAP_2:Q", scale=alt.Scale(zero=False)),
-        color=alt.Color("class_label:N", scale=alt.Scale(domain=list(color_dict.keys()), range=list(color_dict.values()))),
-        tooltip=['UMAP_1', 'UMAP_2', 'class_label'],
-        opacity=alt.condition(legend_selection, alt.value(1), alt.value(0))  # Use the selection here to control opacity
-    ).properties(
-        title=f"UMAP Test Data Labels - {layers}",
-    ).add_selection(
-        legend_selection,  # Add the selection to the chart
+def create_plot(subgroup_select):
+    @pn.depends(subgroup_select.param.value)
+    def _plot(layers):
+        df_train_umap = pd.read_csv(f"https://raw.githubusercontent.com/jeonghin/si649_project2_sparcs/main/data/classifier_1_Test_Data/UMAP_data/Raw_data_UMAP_{layers}.csv").sample(n=5000, random_state=19)
+        color_dict = {
+            "ClassifierA_Cr203_C6": "#B3262A",
+            "ClassifierA_test_stim": "#2f559a",
+            "ClassifierA_test_unstim": "#5AADC5",
+        }
     
-        zoom
-    ).configure_axis(
-        grid=False
-    ).configure_view(
-        strokeWidth=0
-    )
-
-    return chart
-
-# # Combine everything in a Panel Column to create an app
-# app = pn.Column("# UMAP Data Interactive Visualization", subgroup_select, pn.panel(create_plot, reactive=True))
-
-# # Set the app to be servable
-# app.servable()
-
-# Create two instances of the main layout
-# Main layout 1
+        # Define a selection for zooming and panning (interval)
+        zoom = alt.selection_interval(bind='scales')
+    
+        # Define a selection for the legend
+        legend_selection = alt.selection_multi(fields=['class_label'], bind='legend')
+    
+    
+        # Create the Altair chart object
+        chart = alt.Chart(df_train_umap).mark_circle(size=4, opacity=1).encode(
+            x=alt.X("UMAP_1:Q", scale=alt.Scale(zero=False)),
+            y=alt.Y("UMAP_2:Q", scale=alt.Scale(zero=False)),
+            color=alt.Color("class_label:N", scale=alt.Scale(domain=list(color_dict.keys()), range=list(color_dict.values()))),
+            tooltip=['UMAP_1', 'UMAP_2', 'class_label'],
+            opacity=alt.condition(legend_selection, alt.value(1), alt.value(0))  # Use the selection here to control opacity
+        ).properties(
+            title=f"UMAP Test Data Labels - {layers}",
+        ).add_selection(
+            legend_selection,  # Add the selection to the chart
+        
+            zoom
+        ).configure_axis(
+            grid=False
+        ).configure_view(
+            strokeWidth=0
+        )
+    
+        return chart
+    return _plot
+    
+    # # Combine everything in a Panel Column to create an app
+    # app = pn.Column("# UMAP Data Interactive Visualization", subgroup_select, pn.panel(create_plot, reactive=True))
+    
+    # # Set the app to be servable
+    # app.servable()
+    
+    # Create two instances of the main layout
+    # Main layout 1
 main_layout1 = pn.Column(
     "# Data Interactive Visualization (SPARCS)",
     subgroup_select1,
-    pn.panel(create_plot, reactive=True),
+    pn.panel(create_plot(subgroup_select1), reactive=True),
 )
 
 # Main layout 2
 main_layout2 = pn.Column(
     "# Data Interactive Visualization (SPARCS)",
     subgroup_select2,
-    pn.panel(create_plot, reactive=True),
+    pn.panel(create_plot(subgroup_select2), reactive=True),
 )
 
 # Place layouts side by side using pn.Row