Update src/streamlit_app.py

src/streamlit_app.py

@@ -179,17 +179,9 @@ def create_bar_chart(df, view_type):
             xaxis_title_text="Model",
             yaxis_title_text="Score (Lower is better)",
             title_text="",
-            font=dict(size=15, color="black"),
             xaxis_tickangle=-45,
             bargap=0.2, # Increase gap for slimmer bars
             height=500, # Set the height of the plot
-            margin=dict(
-                l=0,   # Left
-                r=0,   # Right
-                b=0,   # Bottom
-                t=5,   # Top
-                pad=0  # Padding
-            ),
         )
         
         # Remove the color legend from the chart.
@@ -222,48 +214,48 @@ def create_bar_chart(df, view_type):
         # )
     
     elif view_type == "Per Embodiment":
-        embodiment_cols = [col for col in df.columns if col.startswith('Embodiment-')]
+        # embodiment_cols = [col for col in df.columns if col.startswith('Embodiment-')]
         fig = go.Figure()
-        for col in embodiment_cols:
-            fig.add_trace(go.Bar(
-                name=col.replace('Embodiment-', ''),
-                x=df['Model'],
-                y=df[col],
-                orientation='v',
-                marker_color=px.colors.qualitative.Plotly,
-                text=df[col].round(1),
-                textposition='outside',
-            ))
-        fig.update_layout(
-            title="Model Performance - Per Embodiment",
-            xaxis_title="Model",
-            yaxis_title="Score",
-            yaxis_range=[0, 100],
-            barmode='group',
-            height=500,
-        )
+        # for col in embodiment_cols:
+        #     fig.add_trace(go.Bar(
+        #         name=col.replace('Embodiment-', ''),
+        #         x=df['Model'],
+        #         y=df[col],
+        #         orientation='v',
+        #         marker_color=px.colors.qualitative.Plotly,
+        #         text=df[col].round(1),
+        #         textposition='outside',
+        #     ))
+        # fig.update_layout(
+        #     title="Model Performance - Per Embodiment",
+        #     xaxis_title="Model",
+        #     yaxis_title="Score",
+        #     yaxis_range=[0, 100],
+        #     barmode='group',
+        #     height=500,
+        # )
     
     else:  # Per Category
-        category_cols = [col for col in df.columns if col.startswith('Category-')]
+        # category_cols = [col for col in df.columns if col.startswith('Category-')]
         fig = go.Figure()
-        for col in category_cols:
-            fig.add_trace(go.Bar(
-                name=col.replace('Category-', ''),
-                x=df['Model'],
-                y=df[col],
-                orientation='v',
-                marker_color=px.colors.qualitative.Plotly,
-                text=df[col].round(1),
-                textposition='outside',
-            ))
-        fig.update_layout(
-            title="Model Performance - Per Category",
-            xaxis_title="Model",
-            yaxis_title="Score",
-            yaxis_range=[0, 100],
-            barmode='group',
-            height=500,
-        )
+        # for col in category_cols:
+        #     fig.add_trace(go.Bar(
+        #         name=col.replace('Category-', ''),
+        #         x=df['Model'],
+        #         y=df[col],
+        #         orientation='v',
+        #         marker_color=px.colors.qualitative.Plotly,
+        #         text=df[col].round(1),
+        #         textposition='outside',
+        #     ))
+        # fig.update_layout(
+        #     title="Model Performance - Per Category",
+        #     xaxis_title="Model",
+        #     yaxis_title="Score",
+        #     yaxis_range=[0, 100],
+        #     barmode='group',
+        #     height=500,
+        # )
     
     # Common styling
     fig.update_layout(