Update app.py

app.py

@@ -1,92 +1,92 @@
-import pyvista as pv
-import streamlit as st
+# app.py
 
-# Material properties (dummy data)
-materials = {
-    "Steel": {"Density": 7850, "Yield Strength": 250},
-    "Aluminum": {"Density": 2700, "Yield Strength": 50},
-    "Brass": {"Density": 8500, "Yield Strength": 200},
-}
+# Import libraries
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from sklearn.ensemble import RandomForestClassifier
+from sklearn.model_selection import train_test_split
+from sklearn.metrics import accuracy_score
+import gradio as gr
+import joblib
 
-# Function to create punch and die geometry
-def create_geometry(length, width, height, inner_width, inner_height, thickness):
-    punch = pv.Box(bounds=(0, length, 0, width, 0, height))
-    die = pv.Box(bounds=(-inner_width / 2, inner_width / 2,
-                         -inner_height / 2, inner_height / 2,
-                         -thickness, 0))
-    return punch, die
+# Step 1: Generate or Load Sample Data
+np.random.seed(42)
+data = pd.DataFrame({
+    "Pressure": np.random.randint(50, 200, 200),
+    "Temperature": np.random.randint(300, 700, 200),
+    "Material_Type": np.random.randint(1, 5, 200),
+    "Defect_Type": np.random.choice([0, 1, 2], 200, p=[0.6, 0.3, 0.1])
+})
 
-# Streamlit App
-st.title("Interactive Punch and Die Design Tool")
-st.sidebar.header("Input Parameters")
+# Splitting data
+X = data[["Pressure", "Temperature", "Material_Type"]]
+y = data["Defect_Type"]
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
 
-# User inputs for Punch Dimensions
-st.sidebar.subheader("Punch Dimensions")
-length = st.sidebar.slider("Length (mm)", 10, 200, 50)
-width = st.sidebar.slider("Width (mm)", 10, 200, 30)
-height = st.sidebar.slider("Height (mm)", 5, 100, 10)
+# Step 2: Train the Model
+model = RandomForestClassifier(n_estimators=100, random_state=42)
+model.fit(X_train, y_train)
 
-# User inputs for Die Dimensions
-st.sidebar.subheader("Die Dimensions")
-inner_width = st.sidebar.slider("Inner Width (mm)", 10, 150, 40)
-inner_height = st.sidebar.slider("Inner Height (mm)", 10, 150, 20)
-die_thickness = st.sidebar.slider("Die Thickness (mm)", 5, 50, 15)
+# Save the model
+joblib.dump(model, "defect_model.pkl")
 
-# Material Selection
-st.sidebar.subheader("Material Selection")
-material = st.sidebar.selectbox("Material", list(materials.keys()))
-mesh_size = st.sidebar.slider("Mesh Size (mm)", 1, 10, 5)
-force = st.sidebar.slider("Force Applied (kN)", 1, 1000, 200)
+# Test the Model
+y_pred = model.predict(X_test)
+print(f"Model Accuracy: {accuracy_score(y_test, y_pred):.2f}")
 
-# Display selected material properties
-st.sidebar.subheader("Material Properties")
-st.sidebar.write(f"Density: {materials[material]['Density']} kg/m³")
-st.sidebar.write(f"Yield Strength: {materials[material]['Yield Strength']} MPa")
+# Step 3: Define Helper Functions for Visualizations
+def plot_simulation(pressure, temperature, material_type):
+    # Simulate some stress/strain values for visualization
+    stress = np.linspace(pressure * 0.5, pressure * 1.5, 100)
+    strain = stress / (temperature * 0.01 * material_type)
+    
+    # Create the plot
+    plt.figure(figsize=(8, 5))
+    plt.plot(stress, strain, label="Stress-Strain Curve")
+    plt.xlabel("Stress (MPa)")
+    plt.ylabel("Strain (%)")
+    plt.title("Stress-Strain Simulation")
+    plt.legend()
+    plt.grid(True)
+    
+    # Save the plot to an image
+    plot_path = "simulation_plot.png"
+    plt.savefig(plot_path)
+    plt.close()
+    return plot_path
 
-# Generate Punch and Die Models
-punch, die = create_geometry(length, width, height, inner_width, inner_height, die_thickness)
+# Step 4: Prediction and Visualization Function
+def predict_and_visualize(pressure, temperature, material_type):
+    # Load the model
+    loaded_model = joblib.load("defect_model.pkl")
+    # Predict
+    input_data = np.array([[pressure, temperature, material_type]])
+    prediction = loaded_model.predict(input_data)[0]
+    defect_map = {0: "No Defect", 1: "Crack", 2: "Wrinkle"}
+    defect_prediction = defect_map[prediction]
+    
+    # Generate visualization
+    plot_path = plot_simulation(pressure, temperature, material_type)
+    
+    return f"Predicted Defect: {defect_prediction}", plot_path
 
-# 3D Visualization
-st.subheader("3D Visualization of Punch and Die")
-plotter = pv.Plotter(off_screen=True)  # Use off_screen for static visualization
-plotter.add_mesh(punch, color="blue", opacity=0.5, label="Punch")
-plotter.add_mesh(die, color="red", opacity=0.5, label="Die")
-plotter.add_axes()
-plotter.show_bounds()
-plotter.view_xy()
-
-# Save the visualization as an image
-image_path = "visualization.png"
-plotter.screenshot(image_path)
-
-# Display the image in Streamlit
-st.image(image_path, caption="3D Visualization of Punch and Die", use_column_width=True)
-
-# Generate APDL Script
-st.subheader("Generated APDL Script")
-apdl_script = f"""
-/PREP7
-! Define material properties
-MP,DENS,1,{materials[material]['Density']}
-MP,YIELD,1,{materials[material]['Yield Strength']}
-! Define punch geometry
-BLOCK,0,{length},0,{width},0,{height}
-! Define die geometry
-BLOCK,-{inner_width/2},{inner_width/2},-{inner_height/2},{inner_height/2},-{die_thickness},0
-! Mesh settings
-ESIZE,{mesh_size}
-! Apply force
-F,1,FZ,{force}
-/SOLU
-SOLVE
-/POST1
-"""
-
-# Display and Download APDL Script
-st.code(apdl_script)
-st.download_button("Download APDL Script", apdl_script, "generated_apdl_script.txt")
-
-# Placeholder for Validation Results
-st.subheader("Validation Feedback")
-st.write("Validation results and stress maps will be shown here.")
+# Step 5: Create Gradio Interface with Visualization
+interface = gr.Interface(
+    fn=predict_and_visualize,
+    inputs=[
+        gr.Slider(50, 200, step=1, label="Pressure"),
+        gr.Slider(300, 700, step=1, label="Temperature"),
+        gr.Dropdown(choices=["1", "2", "3", "4"], label="Material Type")
+    ],
+    outputs=[
+        gr.Textbox(label="Prediction"),
+        gr.Image(label="Stress-Strain Visualization")
+    ],
+    title="Defect Prediction & Simulation",
+    description="Predict defect type and visualize stress-strain simulation for input features: Pressure, Temperature, and Material Type."
+)
 
+# Step 6: Launch the Interface
+if __name__ == "__main__":
+    interface.launch()