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							43 lines
						
					
					
						
							1.3 KiB
						
					
					
				
			
		
		
		
			
			
			
				
					
				
				
					
				
			
		
		
	
	
							43 lines
						
					
					
						
							1.3 KiB
						
					
					
				| import stormpy | |
| import stormpy.core | |
| import stormpy.simulator | |
| 
 | |
| 
 | |
| import stormpy.shields | |
| 
 | |
| import stormpy.examples | |
| import stormpy.examples.files | |
| 
 | |
| 
 | |
| def optimal_shield_extraction(): | |
|     path = stormpy.examples.files.prism_smg_robot | |
|     formula_str = "<Optimal> <<sh>> R{\"travel_costs\"}min=? [ LRA ]" | |
| 
 | |
|     program = stormpy.parse_prism_program(path) | |
|     formulas = stormpy.parse_properties_for_prism_program(formula_str, program) | |
| 
 | |
|     options = stormpy.BuilderOptions([p.raw_formula for p in formulas]) | |
|     options.set_build_state_valuations(True) | |
|     options.set_build_choice_labels(True) | |
|     options.set_build_all_labels() | |
|     model = stormpy.build_sparse_model_with_options(program, options) | |
|     | |
|     shield_specification = stormpy.logic.ShieldExpression(stormpy.logic.ShieldingType.OPTIMAL)  | |
|     result = stormpy.model_checking(model, formulas[0], extract_scheduler=True, shield_expression=shield_specification) | |
|      | |
|     assert result.has_scheduler | |
|     assert result.has_shield | |
|     | |
|     shield = result.shield | |
| 
 | |
|     state_ids = [x for x in model.states] | |
|     scheduler = shield.construct() | |
| 
 | |
|     for state_id in state_ids[0:50]: | |
|         choices = scheduler.get_choice(state_id) | |
|         print(F"Corrections in state {state_id}, are {choices.choice_map} ") | |
|      | |
| 
 | |
| 
 | |
| if __name__ == '__main__': | |
|     optimal_shield_extraction() |