added / renamed shield examples

examples/shields/01_pre_shield_extraction.py

@@ -0,0 +1,46 @@
+import stormpy
+import stormpy.core
+import stormpy.simulator
+
+
+import stormpy.shields
+
+import stormpy.examples
+import stormpy.examples.files
+
+"""
+
+Example for the extraction of a Pre Safety Shield 
+from a model checking result and querying the shield 
+for allowed choices in a state.
+
+"""
+
+def pre_shield_extraction():
+    path = stormpy.examples.files.prism_mdp_lava_simple
+    formula_str = "<ShieldFileName, PreSafety, gamma=0.9> Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
+
+    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)
+
+    initial_state = model.initial_states[0]
+    assert initial_state == 0
+    result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
+    assert result.has_scheduler
+    assert result.has_shield
+    
+    shield = result.shield
+    
+    for state_id in model.states:
+        choices = shield.construct().get_choice(state_id)
+        print(F"Allowed choices in state {state_id}, are {choices.choice_map} ")
+
+
+if __name__ == '__main__':
+    pre_shield_extraction()

examples/shields/02_post_shield_extraction.py

@@ -0,0 +1,49 @@
+import stormpy
+import stormpy.core
+import stormpy.simulator
+
+
+import stormpy.shields
+
+import stormpy.examples
+import stormpy.examples.files
+
+
+"""
+
+Example for the extraction of a Post Safety Shield 
+from a model checking result and querying the shield 
+for allowed actions.
+
+"""
+
+
+def post_shield_extraction():
+    path = stormpy.examples.files.prism_mdp_lava_simple
+    formula_str = "<ShieldFileName, PostSafety, gamma=0.9> Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
+
+    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)
+
+    initial_state = model.initial_states[0]
+    assert initial_state == 0
+    result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
+    assert result.has_scheduler
+    assert result.has_shield
+    
+    shield = result.shield
+  
+    for state_id in model.states:
+        choices = shield.construct().get_choice(state_id)
+        print(F"Allowed choices in state {state_id}, are {choices.choice_map} ")
+
+
+
+if __name__ == '__main__':
+    post_shield_extraction()

examples/shields/04_optimal_shield.py → examples/shields/03_optimal_shield_extraction.py

@@ -7,10 +7,9 @@ import stormpy.shields
 
 import stormpy.examples
 import stormpy.examples.files
-import random
 
 
-def optimal_shield_03():
+def optimal_shield_extraction():
     path = stormpy.examples.files.prism_smg_robot
     formula_str = "<path_correction, Optimal> <<sh>> R{\"travel_costs\"}min=? [ LRA ]"
 
@@ -24,35 +23,17 @@ def optimal_shield_03():
     model = stormpy.build_sparse_model_with_options(program, options)
    
     result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
-    assert result.has_scheduler
-    print(F"Check Scheduler: {result.has_scheduler}")
-    print(F"Check Shield: {result.has_schield}")
 
-    print(type(result))
+    assert result.has_scheduler
+    assert result.has_shield
    
     shield = result.shield
-    scheduler = result.scheduler
-    
-    print(type(shield))
-
-    assert scheduler.memoryless
-    assert scheduler.deterministic
 
-    constructed_shield = shield.construct()
-
-    print(type(constructed_shield))
-    
-    stormpy.shields.export_shieldDouble(model, shield)
+    for state_id in model.states:
+        choices = shield.construct().get_choice(state_id)
+        print(F"Allowed choices in state {state_id}, are {choices.choice_map} ")
     
-    # for state in model.states:
-    #     choice = scheduler.get_choice(state)
-    #     action = choice.get_deterministic_choice()
-    #     print("In state {} choose action {}".format(state, action))
-
-    # dtmc = model.apply_scheduler(scheduler)
-    # print(dtmc)
-
 
 
 if __name__ == '__main__':
-    optimal_shield_03()
+    optimal_shield_extraction()

examples/shields/02_post_shield.py → examples/shields/04_pre_shield_export.py

@@ -7,12 +7,17 @@ import stormpy.shields
 
 import stormpy.examples
 import stormpy.examples.files
-import random
 
+"""
 
-def post_shield_02():
+Example of exporting a Pre Safety Shield
+to a file
+
+"""
+
+def pre_schield():
     path = stormpy.examples.files.prism_mdp_lava_simple
-    formula_str = "<ShieldFileName, PostSafety, gamma=0.9> Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
+    formula_str = "<pre, PreSafety, gamma=0.2> Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
 
     program = stormpy.parse_prism_program(path)
     formulas = stormpy.parse_properties_for_prism_program(formula_str, program)
@@ -27,17 +32,13 @@ def post_shield_02():
     assert initial_state == 0
     result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
     assert result.has_scheduler
-    assert result.has_schield
+    assert result.has_shield
     
     shield = result.shield
 
-    lookup = stormpy.shields.create_shield_action_lookup(model, shield)
-    query = list(lookup.keys())[0]
+    stormpy.shields.export_shieldDouble(model, shield)
     
-    print(query)
-    print(lookup[query])
-
 
 
 if __name__ == '__main__':
-    post_shield_02()
+    pre_schield()

examples/shields/01_pre_shield.py → examples/shields/05_post_shield_export.py

@@ -7,12 +7,17 @@ import stormpy.shields
 
 import stormpy.examples
 import stormpy.examples.files
-import random
 
+"""
 
-def pre_schield_01():
+Example of exporting a Pre Safety Shield
+to a file
+
+"""
+
+def pre_schield():
     path = stormpy.examples.files.prism_mdp_lava_simple
-    formula_str = "<ShieldFileName, PreSafety, gamma=0.9> Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
+    formula_str = "<post, PostSafety, gamma=1> Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
 
     program = stormpy.parse_prism_program(path)
     formulas = stormpy.parse_properties_for_prism_program(formula_str, program)
@@ -27,16 +32,13 @@ def pre_schield_01():
     assert initial_state == 0
     result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
     assert result.has_scheduler
-    assert result.has_schield
+    assert result.has_shield
     
     shield = result.shield
+
+    stormpy.shields.export_shieldDouble(model, shield)
     
-    lookup = stormpy.shields.create_shield_action_lookup(model, shield)
-    query = list(lookup.keys())[0]
-    
-    print(query)
-    print(lookup[query])
 
 
 if __name__ == '__main__':
-    pre_schield_01()
+    pre_schield()

examples/shields/03_optimal_shield.py → examples/shields/06_optimal_shield_export.py

@@ -7,10 +7,14 @@ import stormpy.shields
 
 import stormpy.examples
 import stormpy.examples.files
-import random
 
 
-def optimal_shield_03():
+"""
+Example of exporting a Optimal Shield
+to a file
+"""
+
+def optimal_shield_export():
     path = stormpy.examples.files.prism_smg_lights
     formula_str = "<tlsShield, Optimal> <<shield>> R{\"differenceWithInterferenceCost\"}min=? [ LRA ]"
 
@@ -25,34 +29,12 @@ def optimal_shield_03():
    
     result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
     assert result.has_scheduler
-    print(F"Check Scheduler: {result.has_scheduler}")
-    print(F"Check Shield: {result.has_schield}")
+    assert result.has_shield
 
-    print(type(result))
-   
     shield = result.shield
-    scheduler = result.scheduler
-    
-    print(type(shield))
-
-    assert scheduler.memoryless
-    assert scheduler.deterministic
-
-    constructed_shield = shield.construct()
-
-    print(type(constructed_shield))
     
     stormpy.shields.export_shieldDouble(model, shield)
-    
-    # for state in model.states:
-    #     choice = scheduler.get_choice(state)
-    #     action = choice.get_deterministic_choice()
-    #     print("In state {} choose action {}".format(state, action))
-
-    # dtmc = model.apply_scheduler(scheduler)
-    # print(dtmc)
-
 
 
 if __name__ == '__main__':
-    optimal_shield_03()
+    optimal_shield_export()

examples/shields/07_pre_shield_simulator.py

@@ -0,0 +1,59 @@
+import stormpy
+import stormpy.core
+import stormpy.simulator
+
+import stormpy.shields
+
+import stormpy.examples
+import stormpy.examples.files
+
+import random
+
+"""
+Simulating a model with the usage of a pre shield
+"""
+
+def example_pre_shield_simulator():
+    path = stormpy.examples.files.prism_mdp_lava_simple
+    formula_str = "<ShieldFileName, PreSafety, gamma=0.9> Pmax=? [G !\"AgentIsInLavaAndNotDone\"]"
+
+    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)
+
+    initial_state = model.initial_states[0]
+    assert initial_state == 0
+    result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
+    assert result.has_scheduler
+    assert result.has_shield
+    
+    shield = result.shield
+
+    pre_scheduler = shield.construct()
+
+    simulator = stormpy.simulator.create_simulator(model, seed=42)
+    final_outcomes = dict()
+    for n in range(1000):
+        while not simulator.is_done():
+            current_state = simulator.get_current_state()
+            choices = pre_scheduler.get_choice(current_state).choice_map
+            index = random.randint(0, len(choices) - 1)
+            selected_action = choices[index]
+            state_string = model.state_valuations.get_string(current_state)
+            print(F"Simulator is in state {state_string}. Allowed Choices are {choices}. Selected Action: {selected_action}")
+            observation, reward = simulator.step(selected_action[1])
+        if observation not in final_outcomes:
+            final_outcomes[observation] = 1
+        else:
+            final_outcomes[observation] += 1
+        simulator.restart()
+
+
+
+if __name__ == '__main__':
+    example_pre_shield_simulator()

examples/shields/10_optimal_controller.py

@@ -0,0 +1,9 @@
+import stormpy
+import stormpy.core
+import stormpy.simulator
+
+
+import stormpy.shields
+
+import stormpy.examples
+import stormpy.examples.files