fix

app.py

@@ -1067,11 +1067,38 @@ def create_category_scaling_plot(
                     hovertemplate=build_fit_line_hovertemplate(fit_label, a, b, c, raw_rmse, log_rmse),
                 )
             )
-    else:
-        # 单独显示模式：为每个数据集创建散点图和拟合线
-        for idx, dataset in enumerate(selected_datasets):
-            if dataset not in new_df.columns:
-                continue
+    else:
+        # 单独显示模式：为每个数据集创建散点图和拟合线
+        fig.add_trace(
+            go.Scatter(
+                x=[None],
+                y=[None],
+                mode="markers",
+                name="Non-Pareto",
+                marker=dict(size=9, color="rgba(55,65,81,0.9)", symbol="circle"),
+                hoverinfo="skip",
+            )
+        )
+        if use_pareto:
+            fig.add_trace(
+                go.Scatter(
+                    x=[None],
+                    y=[None],
+                    mode="markers",
+                    name="Pareto",
+                    marker=dict(
+                        size=10,
+                        color="rgba(255,255,255,0.95)",
+                        symbol="diamond",
+                        line=dict(color="#263238", width=1.1),
+                    ),
+                    hoverinfo="skip",
+                )
+            )
+
+        for idx, dataset in enumerate(selected_datasets):
+            if dataset not in new_df.columns:
+                continue
 
             # 提取该数据集的数据
             x_values = new_df["Params (B)"].astype(float).tolist()
@@ -1138,8 +1165,9 @@ def create_category_scaling_plot(
                             + "<extra></extra>"
                         ),
                         legendgroup=dataset,
-                    )
-                )
+                        showlegend=False,
+                    )
+                )
 
             # 如果使用帕累托前沿，高亮显示帕累托前沿的点
             if use_pareto:
@@ -1168,9 +1196,10 @@ def create_category_scaling_plot(
                             + "<extra></extra>"
                         ),
                         legendgroup=dataset,
-                    )
-                )
-
+                        showlegend=False,
+                    )
+                )
+
             # 添加拟合曲线
             fit_type = "Pareto Fit" if use_pareto else "Fit"
             fit_label = f"{dataset} ({fit_type})"
@@ -1179,7 +1208,7 @@ def create_category_scaling_plot(
                     x=fit_x.tolist(),
                     y=fit_y.tolist(),
                     mode="lines",
-                    name=fit_label,
+                    name=dataset,
                     line=dict(color=color, width=2, dash="dash"),
                     hovertemplate=build_fit_line_hovertemplate(fit_label, a, b, c, raw_rmse, log_rmse),
                     legendgroup=dataset,
@@ -1208,13 +1237,13 @@ def create_category_scaling_plot(
     coloraxis = create_fit_delta_coloraxis(all_delta_values)
     coloraxis["colorbar"].update(
         dict(
-            x=1.01,
+            x=1.02,
             xanchor="left",
             y=0.5,
             yanchor="middle",
-            len=0.86,
-            thickness=42,
-            tickfont=dict(size=10),
+            len=0.72,
+            thickness=28,
+            tickfont=dict(size=9),
             title=dict(text="vs fit", side="top"),
         )
     )
@@ -1226,12 +1255,14 @@ def create_category_scaling_plot(
         showlegend=True,
         legend=dict(
             yanchor="top",
-            y=0.99,
+            y=0.98,
             xanchor="left",
-            x=1.18,
-            bgcolor="rgba(255,255,255,0.9)",
+            x=0.02,
+            bgcolor="rgba(255,255,255,0.78)",
+            bordercolor="rgba(15,23,42,0.08)",
+            borderwidth=1,
             font=dict(size=9),
-            tracegroupgap=6,
+            tracegroupgap=2,
         ),
         xaxis=dict(
             title="Parameters (B)",
@@ -1253,7 +1284,7 @@ def create_category_scaling_plot(
             autorange="reversed",
         ),
         coloraxis=coloraxis,
-        margin=dict(l=70, r=320, t=70, b=65),  # 为图例和颜色条预留空间
+        margin=dict(l=70, r=80, t=70, b=65),
     )
     return fig