Added documentation for MA scheduler extraction

doc/source/doc/schedulers.rst

@@ -7,8 +7,8 @@ The scheduler determines which action to take at each state.
 
 For a given reachability property, Storm can return the scheduler realizing the resulting probability.
 
-Examining Schedulers
-====================
+Examining Schedulers for MDPs
+=============================
 
 .. seealso:: `01-schedulers.py <https://github.com/moves-rwth/stormpy/blob/master/examples/schedulers/01-schedulers.py>`_
 
@@ -30,6 +30,7 @@ Next we check the model and make sure to extract the scheduler:
     >>> result = stormpy.model_checking(model, formulas[0], extract_scheduler=True)
 
 The result then contains the scheduler we want:
+
     >>> assert result.has_scheduler
     >>> scheduler = result.scheduler
     >>> assert scheduler.memoryless
@@ -58,3 +59,41 @@ To get the information which action the scheduler chooses in which state, we can
     In state 5 choose action 0
     -etc-
 
+
+Examining Schedulers for Markov automata
+========================================
+
+.. seealso:: `02-schedulers.py <https://github.com/moves-rwth/stormpy/blob/master/examples/schedulers/02-schedulers.py>`_
+
+Currently there is no support yet for scheduler extraction on MAs.
+However, if the timing information is not relevant for the property, we can circumvent this lack by first transforming the MA to an MDP.
+
+We build the model as before:
+
+    >>> path = stormpy.examples.files.prism_ma_simple
+    >>> formula_str = "Tmin=? [ F s=4 ]"
+
+    >>> program = stormpy.parse_prism_program(path, False, True)
+    >>> formulas = stormpy.parse_properties_for_prism_program(formula_str, program)
+    >>> ma = stormpy.build_model(program, formulas)
+
+Next we transform the continuous-time model into a discrete-time model.
+Note that all timing information is lost at this point.
+
+    >>> mdp, mdp_formulas = stormpy.transform_to_discrete_time_model(ma, formulas)
+    >>> assert mdp.model_type == stormpy.ModelType.MDP
+
+After the transformation we have obtained an MDP where we can extract the scheduler as shown before:
+
+    >>> result = stormpy.model_checking(mdp, mdp_formulas[0], extract_scheduler=True)
+    >>> scheduler = result.scheduler
+    >>> print(scheduler)
+    ___________________________________________________________________
+    Fully defined memoryless deterministic scheduler:
+    model state:    choice(s)
+               0    1
+               1    0
+               2    0
+               3    0
+               4    0
+    -etc-

examples/schedulers/01-schedulers.py

@@ -7,7 +7,6 @@ import stormpy.examples.files
 
 def example_schedulers_01():
     path = stormpy.examples.files.prism_mdp_coin_2_2
-
     formula_str = "Pmin=? [F \"finished\" & \"all_coins_equal_1\"]"
 
     program = stormpy.parse_prism_program(path)

examples/schedulers/02-schedulers.py

@@ -0,0 +1,37 @@
+import stormpy
+import stormpy.core
+
+import stormpy.examples
+import stormpy.examples.files
+
+
+def example_schedulers_02():
+    path = stormpy.examples.files.prism_ma_simple
+    formula_str = "Tmin=? [ F s=4 ]"
+
+    program = stormpy.parse_prism_program(path, False, True)
+    formulas = stormpy.parse_properties_for_prism_program(formula_str, program)
+    ma = stormpy.build_model(program, formulas)
+    assert ma.model_type == stormpy.ModelType.MA
+
+    # Convert MA to MDP
+    mdp, mdp_formulas = stormpy.transform_to_discrete_time_model(ma, formulas)
+    assert mdp.model_type == stormpy.ModelType.MDP
+    initial_state = mdp.initial_states[0]
+    assert initial_state == 0
+
+    result = stormpy.model_checking(mdp, mdp_formulas[0], extract_scheduler=True)
+    assert result.has_scheduler
+    scheduler = result.scheduler
+    print(scheduler)
+    assert scheduler.memoryless
+    assert scheduler.deterministic
+
+    for state in mdp.states:
+        choice = scheduler.get_choice(state)
+        action = choice.get_deterministic_choice()
+        print("In state {} choose action {}".format(state, action))
+
+
+if __name__ == '__main__':
+    example_schedulers_02()

lib/stormpy/examples/files.py

@@ -19,6 +19,8 @@ prism_pdtmc_die = _path("pdtmc", "parametric_die.pm")
 """Knuth Yao Die -- 2 unfair coins Example"""
 prism_dtmc_brp = _path("dtmc", "brp-16-2.pm")
 """Bounded Retransmission Protocol"""
+prism_ma_simple = _path("ma", "simple.ma")
+"""Prism file for a simple Markov automaton"""
 drn_ctmc_dft = _path("ctmc", "dft.drn")
 """DRN format for a CTMC from a DFT"""
 drn_pdtmc_die = _path("pdtmc", "die.drn")