def counter_example(): g = TransitionSystem() g.add_path([0, 1, 2, 3, 4]) g.add_path([5, 6, 7, 0]) g.add_edge(4, 5, formula="x") g.add_edge(4, 1, formula="!x") g.add_edge(1, 0) g.add_edge(3, 2) g.vars = dict(x='bool') g.env_vars.add('x') # g.dump('sys_graph_2.pdf') # aut_g = graph_to_logic(g, 'pc', ignore_initial=True) # aut = Automaton() aut.players = dict(alice=0, bob=1) aut.vars = dict( pc=dict(type='saturating', dom=(0, 7), owner='alice'), x=dict(type='bool', owner='bob'), _i=dict(type='saturating', dom=(0, 1), owner='alice')) aut.action['alice'] = [aut_g.action['sys'][0]] aut.win['alice: []<>'] = ['pc = 6'] aut.win['bob: []<>'] = ['True'] fill_blanks(aut) print(aut) aut = aut.build() make_assumptions(aut)
def counter_example(): g = TransitionSystem() g.add_path([0, 1, 2, 3, 4]) g.add_path([5, 6, 7, 0]) g.add_edge(4, 5, formula="x") g.add_edge(4, 1, formula="~ x") g.add_edge(1, 0) g.add_edge(3, 2) g.vars = dict(x='bool') g.env_vars.add('x') # g.dump('sys_graph_2.pdf') # aut_g = graph_to_logic(g, 'pc', ignore_initial=True) # aut = sym.Automaton() aut.players = dict(alice=0, bob=1) table = dict(pc=dict(type='saturating', dom=(0, 7), owner='alice'), x=dict(type='bool', owner='bob'), _i=dict(type='saturating', dom=(0, 1), owner=None)) aut.add_vars(table, flexible=True) aut.varlist = dict(alice=['pc'], bob=['x']) aut.init_expr = dict(alice='TRUE', bob='TRUE') aut.action_expr = dict(alice=aut_g.action['sys'][0], bob='TRUE') aut.win_expr = dict(alice={'[]<>': ['pc = 6']}, bob={'[]<>': ['True']}) # TODO: sym.fill_blanks(aut) print(aut) aut.build() make_assumptions(aut)
def test_ee_image(): g = TransitionSystem() g.vars = dict(x='bool') g.env_vars = {'x'} g.add_edge(0, 1, formula='x') g.add_edge(0, 1, formula=' ~ x') g.add_edge(0, 2, formula='x') aut = logicizer.graph_to_logic(g, 'pc', True) source = aut.add_expr('pc = 0') u = fx.ee_image(source, aut) u_ = aut.add_expr('(pc = 1) \/ (pc = 2)') assert u == u_, _to_expr(u, aut)
def test_ue_image_no_constrain(): g = TransitionSystem() g.vars = dict(x='bool') g.env_vars = {'x'} g.add_edge(0, 1, formula='x') g.add_edge(0, 2, formula=' ~ x') aut = logicizer.graph_to_logic(g, 'pc', True) # source constrained to x source = aut.add_expr('x /\ (pc = 0)') u = fx.ee_image(source, aut) assert u == aut.add_expr('pc = 1') # source contains both x and ~ x source = aut.add_expr('pc = 0') u = fx.ee_image(source, aut) assert u == aut.add_expr('(pc = 1) \/ (pc = 2)')
def semi_symbolic(): """Example using a semi-enumerated state machine. Instructive variants: - `formula = "x'"` - `self_loops = True` - `aut.moore = False` """ g = TransitionSystem() g.owner = 'sys' g.vars = dict(x='bool') g.env_vars.add('x') nx.add_path(g, range(11)) g.add_edge(10, 10) g.add_edge(10, 0, formula="x") # symbolic aut = logicizer.graph_to_logic(g, 'nd', ignore_initial=True, self_loops=False) aut.init['env'] = 'nd = 1' aut.win['<>[]'] = aut.bdds_from(' ~ x') aut.win['[]<>'] = aut.bdds_from('nd = 0') aut.qinit = '\A \A' aut.moore = True aut.plus_one = True print(aut) # compile to BDD z, yij, xijk = gr1.solve_streett_game(aut) gr1.make_streett_transducer(z, yij, xijk, aut) # print t.bdd.to_expr(t.action['sys'][0]) r = aut.action['sys'] # aut.bdd.dump('bdd.pdf', roots=[r]) g = enumerate_controller(aut) h, _ = sym_enum._format_nx(g) pd = nx.drawing.nx_pydot.to_pydot(h) pd.write_pdf('game_states.pdf') print('Enumerated strategy has {n} nodes.'.format(n=len(g))) print(('Winning set:', aut.bdd.to_expr(z))) print('{n} BDD nodes in total'.format(n=len(aut.bdd)))
def semi_symbolic(): """Example using a semi-enumerated state machine. Instructive variants: - `formula = "x'"` - `self_loops = True` - `aut.moore = False` """ g = TransitionSystem() g.owner = 'sys' g.vars = dict(x='bool') g.env_vars.add('x') g.add_path(range(11)) g.add_edge(10, 10) g.add_edge(10, 0, formula="x") # symbolic aut = logicizer.graph_to_logic( g, 'nd', ignore_initial=True, self_loops=False) aut.init['env'] = 'nd = 1' aut.win['<>[]'] = aut.bdds_from(' ~ x') aut.win['[]<>'] = aut.bdds_from('nd = 0') aut.qinit = '\A \A' aut.moore = True aut.plus_one = True print(aut) # compile to BDD z, yij, xijk = gr1.solve_streett_game(aut) gr1.make_streett_transducer(z, yij, xijk, aut) # print t.bdd.to_expr(t.action['sys'][0]) r = aut.action['sys'] # aut.bdd.dump('bdd.pdf', roots=[r]) g = enumerate_controller(aut) h, _ = sym_enum._format_nx(g) pd = nx.drawing.nx_pydot.to_pydot(h) pd.write_pdf('game_states.pdf') print('Enumerated strategy has {n} nodes.'.format( n=len(g))) print(('Winning set:', aut.bdd.to_expr(z))) print('{n} BDD nodes in total'.format( n=len(aut.bdd)))