davide
b663a89abd
- model.py: aggiunge termine sorgente Gaussiana (σ=0.02) nella PDE loss per approssimare δ(x − X_SRC); sostituisce BC Neumann a x=0 con Robin - engine.py: clustering collocation vicino X_SRC anziché x=0; downsample FDM su entrambi gli assi spaziale e temporale in evaluate_model() - visualizer.py: downsample FDM su entrambi gli assi prima del plot - app.py: aggiorna header con fisica corrente - CLAUDE.md: aggiorna PDE, BC e note architetturali Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
63 lines
1.4 KiB
Python
63 lines
1.4 KiB
Python
import sys
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import engine
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def print_header():
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print("=" * 55)
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print(" Heat Equation PINN — ∂T/∂t = α ∂²T/∂x²")
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print(" Robin BC (x=0, x=L) + point source @ X_SRC")
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print("=" * 55)
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def _ask_float(prompt, default):
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val = input(prompt).strip()
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try:
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return float(val)
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except ValueError:
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return default
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def _ask_int(prompt, default):
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val = input(prompt).strip()
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return int(val) if val.isdigit() else default
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def main_menu():
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print("\nInitializing collocation points...")
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data = engine.prepare_data()
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print(f"Ready — device: {data['device']}\n")
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while True:
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print("\n" + "-" * 30)
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print(" MAIN MENU")
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print("-" * 30)
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print("1. Train New Model")
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print("2. Evaluate Model (L2 vs analytical)")
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print("3. Visualize Temperature Field")
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print("0. Exit")
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print("-" * 30)
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choice = input("Select an option (0-3): ").strip()
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if choice == '1':
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epochs = _ask_int("Epochs (default 5000): ", 5000)
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engine.train_model(data, epochs=epochs)
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elif choice == '2':
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engine.evaluate_model(data)
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elif choice == '3':
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engine.generate_visualization(data)
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elif choice == '0':
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print("Exiting.")
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sys.exit(0)
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else:
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print("Invalid choice.")
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if __name__ == "__main__":
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print_header()
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main_menu()
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