def test_load_aut_json():
g = gr1c.load_aut_json(REFERENCE_AUTJSON_smallbool)
assert g.env_vars == dict(x='boolean'), (g.env_vars)
assert g.sys_vars == dict(y='boolean'), (g.sys_vars)
# `REFERENCE_AUTJSON_smallbool` defined above
h = nx.DiGraph()
nodes = {0: '0x1E8FA40', 1: '0x1E8FA00', 2: '0x1E8F990'}
h.add_node(nodes[0], state=dict(x=0, y=0),
mode=0, rgrad=1, initial=False)
h.add_node(nodes[1], state=dict(x=1, y=1),
mode=1, rgrad=1, initial=False)
h.add_node(nodes[2], state=dict(x=0, y=1),
mode=0, rgrad=1, initial=True)
edges = [(nodes[0], nodes[1]),
(nodes[1], nodes[0]),
(nodes[2], nodes[1])]
h.add_edges_from(edges)
# compare
for u, d in h.nodes_iter(data=True):
assert u in g, (u, g.nodes())
d_ = g.node[u]
for k, v in d.iteritems():
v_ = d_.get(k)
assert v_ == v, (k, v, v_, d, d_)
h_edges = set(h.edges_iter())
g_edges = set(g.edges_iter())
assert h_edges == g_edges, (h_edges, g_edges)
def synthesize(spec, init_option="ALL_ENV_EXIST_SYS_INIT"):
"""Synthesize strategy realizing the given specification.
cf. L{tulip.interfaces.gr1c.synthesize}
"""
tsys, exprtab = _spec_to_gr1py(spec)
strategy = gr1py.solve.synthesize(tsys, exprtab)
if strategy is None:
return None
s = gr1py.output.dump_json(tsys.symtab, strategy)
return load_aut_json(s)
def synthesize(spec):
"""Synthesize strategy realizing the given specification.
cf. L{tulip.interfaces.gr1c.synthesize}
"""
init_option = select_options(spec)
tsys, exprtab = _spec_to_gr1py(spec)
strategy = gr1py.solve.synthesize(tsys, exprtab, init_flags=init_option)
if strategy is None:
return None
s = gr1py.output.dump_json(tsys.symtab, strategy)
return load_aut_json(s)
