Update app.py

app.py

@@ -3,7 +3,6 @@ import pandas as pd
 import xgboost as xgb
 from sklearn.model_selection import train_test_split
 import gradio as gr
-import shap
 
 # 加载数据
 df_strength = pd.read_excel("Dataset1.xlsx")
@@ -34,38 +33,40 @@ clf.fit(x_train, y_train)
 def CirConStr(Temperature, CO2_Pressure, Time, CO2_Concentration, Particle_Size, CaO, MgO, SiO2, Al2O3, Fe2O3, MnO, L_S):
     x = np.array([Temperature, CO2_Pressure, Time, CO2_Concentration, Particle_Size, CaO, MgO, SiO2, Al2O3, Fe2O3, MnO, L_S])
     prediction = clf.predict(x.reshape(1, -1))
-    return prediction[0]
+    return prediction
 
-# 绘制 SHAP waterfall plot 的函数
-def plot_waterfall(Temperature, CO2_Pressure, Time, CO2_Concentration, Particle_Size, CaO, MgO, SiO2, Al2O3, Fe2O3, MnO, L_S):
-    x = np.array([Temperature, CO2_Pressure, Time, CO2_Concentration, Particle_Size, CaO, MgO, SiO2, Al2O3, Fe2O3, MnO, L_S])
-    explainer = shap.Explainer(clf, x_train)
-    shap_values = explainer(x)
+# 创建界面
+with gr.Blocks() as app:
+    gr.Markdown("### Rapid estimation of CO2 sequestration capacity of SS")
+
+    with gr.Row():
+        with gr.Column():
+            Temperature = gr.Number(label="Temperature (unit: ℃)")
+            CO2_Pressure = gr.Number(label="CO2_Pressure (unit: Bar)")
+            Time = gr.Number(label="Time (unit: h)")
+            CO2_Concentration = gr.Number(label="CO2_Concentration(unit: %)")
+        
+        with gr.Column():
+            Particle_Size = gr.Number(label="Particle_Size (unit: μm)")
+            CaO = gr.Number(label="CaO (fc, unit: %)")
+            MgO = gr.Number(label="MgO (fc, unit: %)")
+            SiO2 = gr.Number(label="SiO2 (fc, unit: %)")
+        
+        with gr.Column():
+            Al2O3 = gr.Number(label="Al2O3 (fc, unit: %)")
+            Fe2O3 = gr.Number(label="Fe2O3 (fc, unit: %)")
+            MnO = gr.Number(label="MnO (unit: %)")
+            L_S = gr.Number(label="L_S(L/S, unit: &)")
     
-    # 绘制 SHAP waterfall plot 并返回 HTML
-    shap.initjs()
-    waterfall_plot_html = shap.waterfall_plot(explainer.expected_value, shap_values[0], feature_names=df_strength.columns[:-1], show=False)
-    return waterfall_plot_html.html
+    # 输出组件
+    output = gr.Textbox(label="Estimated CO2 sequestration capacity of SS (fcc, unit: %)")
+    
+    # 添加按钮和功能
+    calculate_btn = gr.Button("Calculate")
+    calculate_btn.click(
+        CirConStr,
+        inputs=[Temperature, CO2_Pressure, Time, CO2_Concentration, Particle_Size, CaO, MgO, SiO2, Al2O3, Fe2O3, MnO, L_S],
+        outputs=output
+    )
 
-# 创建界面
-with gr.Interface(fn=CirConStr, inputs=[
-        gr.inputs.Number(label="Temperature (unit: ℃)"),
-        gr.inputs.Number(label="CO2_Pressure (unit: Bar)"),
-        gr.inputs.Number(label="Time (unit: h)"),
-        gr.inputs.Number(label="CO2_Concentration(unit: %)"),
-        gr.inputs.Number(label="Particle_Size (unit: μm)"),
-        gr.inputs.Number(label="CaO (fc, unit: %)"),
-        gr.inputs.Number(label="MgO (fc, unit: %)"),
-        gr.inputs.Number(label="SiO2 (fc, unit: %)"),
-        gr.inputs.Number(label="Al2O3 (fc, unit: %)"),
-        gr.inputs.Number(label="Fe2O3 (fc, unit: %)"),
-        gr.inputs.Number(label="MnO (unit: %)"),
-        gr.inputs.Number(label="L_S(L/S, unit: &)"),
-    ], 
-    outputs=[
-        gr.outputs.Textbox(label="Estimated CO2 sequestration capacity of SS (fcc, unit: %)"),
-        gr.outputs.HTML(label="SHAP Waterfall Plot")
-    ],
-    title="Rapid estimation of CO2 sequestration capacity of SS"
-) as app:
-    app.launch()
+app.launch()