Initial leaderboard setup

.ipynb_checkpoints/app-checkpoint.py

@@ -181,40 +181,35 @@ with tab2:
             default=st.session_state.combined_df['Model'].unique()
         )
     
+    # Create a consistent color mapping for all models
+    plotly_colors = ['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880', '#FF97FF', '#FECB52']
+    model_colors = {model: plotly_colors[i % len(plotly_colors)] for i, model in enumerate(sorted(st.session_state.combined_df['Model'].unique()))}
+    
     class_data = st.session_state.combined_df[
         (st.session_state.combined_df['Category'] == selected_category) &
         (~st.session_state.combined_df['Class'].str.contains('Overall')) &
         (st.session_state.combined_df['Model'].isin(selected_models))
     ]
     
-    # Bar chart
+    # Bar chart with consistent colors
     fig = px.bar(
         class_data,
         x='Class',
         y=selected_metric,
         color='Model',
         barmode='group',
-        title=f'{selected_metric} by Class for {selected_category}'
+        title=f'{selected_metric} by Class for {selected_category}',
+        color_discrete_map=model_colors
     )
     st.plotly_chart(fig, use_container_width=True)
     
-    # Create a shared legend container
-    legend_data = []
-    for i, model in enumerate(selected_models):
-        legend_data.append({
-            'Model': model,
-            'Visible': True,
-            'Index': i
-        })
-    legend_df = pd.DataFrame(legend_data)
-    
-    # Create toggles for models using st.columns
-    st.markdown("### Select Models to Display:")
-    
     # Calculate how many columns we need (aim for about 4-5 models per row)
     models_per_row = 4
     num_rows = (len(selected_models) + models_per_row - 1) // models_per_row
     
+    st.markdown("### Select Models to Display:")
+    
+    # Create toggles for models using st.columns
     for row in range(num_rows):
         cols = st.columns(models_per_row)
         for col_idx in range(models_per_row):
@@ -223,9 +218,8 @@ with tab2:
                 model = selected_models[model_idx]
                 container = cols[col_idx].container()
                 
-                # Get Plotly's default color for this model index
-                plotly_colors = ['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880', '#FF97FF', '#FECB52']
-                color = plotly_colors[model_idx % len(plotly_colors)]
+                # Get the consistent color for this model
+                color = model_colors[model]
                 
                 # Store toggle state in session state with unique key
                 toggle_key = f"toggle_{model}"
@@ -234,12 +228,12 @@ with tab2:
 
                 # Create the checkbox with colored text
                 st.session_state[toggle_key] = container.checkbox(
-                    f"⬤ {model}",  # Add a colored circle before the model name
+                    f"⬤ {model}",
                     value=st.session_state[toggle_key],
                     key=f"model_toggle_{model}"
                 )
                 
-                # Add colored style to the label
+                # Add colored style to the checkbox
                 container.markdown(
                     f"""
                     <style>
@@ -282,7 +276,8 @@ with tab2:
                     y='Recall',
                     color='Model',
                     title=f'Precision vs Recall: {current_class}',
-                    height=300
+                    height=300,
+                    color_discrete_map=model_colors  # Use consistent colors
                 )
                 
                 # Update layout for better visibility

app.py

@@ -181,40 +181,35 @@ with tab2:
             default=st.session_state.combined_df['Model'].unique()
         )
     
+    # Create a consistent color mapping for all models
+    plotly_colors = ['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880', '#FF97FF', '#FECB52']
+    model_colors = {model: plotly_colors[i % len(plotly_colors)] for i, model in enumerate(sorted(st.session_state.combined_df['Model'].unique()))}
+    
     class_data = st.session_state.combined_df[
         (st.session_state.combined_df['Category'] == selected_category) &
         (~st.session_state.combined_df['Class'].str.contains('Overall')) &
         (st.session_state.combined_df['Model'].isin(selected_models))
     ]
     
-    # Bar chart
+    # Bar chart with consistent colors
     fig = px.bar(
         class_data,
         x='Class',
         y=selected_metric,
         color='Model',
         barmode='group',
-        title=f'{selected_metric} by Class for {selected_category}'
+        title=f'{selected_metric} by Class for {selected_category}',
+        color_discrete_map=model_colors
     )
     st.plotly_chart(fig, use_container_width=True)
     
-    # Create a shared legend container
-    legend_data = []
-    for i, model in enumerate(selected_models):
-        legend_data.append({
-            'Model': model,
-            'Visible': True,
-            'Index': i
-        })
-    legend_df = pd.DataFrame(legend_data)
-    
-    # Create toggles for models using st.columns
-    st.markdown("### Select Models to Display:")
-    
     # Calculate how many columns we need (aim for about 4-5 models per row)
     models_per_row = 4
     num_rows = (len(selected_models) + models_per_row - 1) // models_per_row
     
+    st.markdown("### Select Models to Display:")
+    
+    # Create toggles for models using st.columns
     for row in range(num_rows):
         cols = st.columns(models_per_row)
         for col_idx in range(models_per_row):
@@ -223,9 +218,8 @@ with tab2:
                 model = selected_models[model_idx]
                 container = cols[col_idx].container()
                 
-                # Get Plotly's default color for this model index
-                plotly_colors = ['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880', '#FF97FF', '#FECB52']
-                color = plotly_colors[model_idx % len(plotly_colors)]
+                # Get the consistent color for this model
+                color = model_colors[model]
                 
                 # Store toggle state in session state with unique key
                 toggle_key = f"toggle_{model}"
@@ -234,12 +228,12 @@ with tab2:
 
                 # Create the checkbox with colored text
                 st.session_state[toggle_key] = container.checkbox(
-                    f"⬤ {model}",  # Add a colored circle before the model name
+                    f"⬤ {model}",
                     value=st.session_state[toggle_key],
                     key=f"model_toggle_{model}"
                 )
                 
-                # Add colored style to the label
+                # Add colored style to the checkbox
                 container.markdown(
                     f"""
                     <style>
@@ -282,7 +276,8 @@ with tab2:
                     y='Recall',
                     color='Model',
                     title=f'Precision vs Recall: {current_class}',
-                    height=300
+                    height=300,
+                    color_discrete_map=model_colors  # Use consistent colors
                 )
                 
                 # Update layout for better visibility