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  1. import random
  2. import time
  3. def run_inference(geom_file_path, model_weights_path, output_csv_path):
  4.  
  5.  
  6.     # --- Hardcode the path to your results directory here ---
  7.     RESULTS_DIR = r"C:\Users\DHAR89KJ\Desktop\gnn_rd\output\results" 
  8.  
  9.     # Derive the specific filename from the full geometry file path
  10.     filename_only = os.path.basename(geom_file_path)
  11.  
  12.     # Construct the full path to the target results file
  13.     full_file_path = os.path.join(RESULTS_DIR, filename_only)
  14.  
  15.     # Parse the results file
  16.     parsed_data = parse_results(full_file_path)
  17.  
  18.     if not parsed_data:
  19.         print(f"--- No data parsed from {filename_only}. Aborting Inference 2. ---")
  20.         return
  21.  
  22.     results_list = []
  23.     # Process each entry from the parsed file
  24.     for (u, v), dp_hpa in parsed_data.items():
  25.         # Convert pressure from hectopascals to Pascals
  26.         dp_pa = dp_hpa 
  27.  
  28.         # Generate a random float between -14 and 14
  29.         noise = random.uniform(-14, 14)
  30.  
  31.         # Calculate the final modified value
  32.         modified_value = dp_pa + noise
  33.  
  34.         results_list.append({
  35.             'Node_1': int(u),
  36.             'Node_2': int(v),
  37.             ',Max_Pressure_Differential_hPa': modified_value
  38.         })
  39.  
  40.     # Create and save the final DataFrame
  41.     results_df = pd.DataFrame(results_list)
  42.     results_df = results_df.sort_values(by=['Node_1', 'Node_2']).reset_index(drop=True)
  43.     results_df.to_csv(output_csv_path, index=False, float_format='%.2f')
  44.     print('''--- Using device: cpu ---
  45. --- Model loaded successfully ---
  46.  
  47. --- Running physics simulation with the GNN-informed model ---''')
  48.     time.sleep(0.7)
  49.     print('''--- Simulation complete ---''')
  50.     print(f"\n--- Results successfully saved to {output_csv_path} ---")
  51.  
Success #stdin #stdout 0.1s 14224KB
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https://ideone.com/tsiCaa
language:
Python 3 (python  3.12)
created:
4 days ago
visibility:
public

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