def main():
# Start from a given CNF and VTREE file
vtree = Vtree.from_file(bytes(here / "input" / "simple.vtree"))
sdd = SddManager.from_vtree(vtree)
print(f"Created an SDD with {sdd.var_count()} variables")
root = sdd.read_cnf_file(bytes(here / "input" / "simple.cnf"))
# For DNF functions use `read_dnf_file`
# If the vtree is not given, you can also use 'from_cnf_file`
# Model Counting
wmc = root.wmc(log_mode=True)
w = wmc.propagate()
print(f"Model count: {int(math.exp(w))}")
# Weighted Model Counting
lits = [None] + [sdd.literal(i) for i in range(1, sdd.var_count() + 1)]
# Positive literal weight
wmc.set_literal_weight(lits[1], math.log(0.5))
# Negative literal weight
wmc.set_literal_weight(-lits[1], math.log(0.5))
w = wmc.propagate()
print(f"Weighted model count: {math.exp(w)}")
# Visualize SDD and VTREE
print("saving sdd and vtree ... ", end="")
with open(here / "output" / "sdd.dot", "w") as out:
print(sdd.dot(), file=out)
with open(here / "output" / "vtree.dot", "w") as out:
print(vtree.dot(), file=out)
print("done")
def to_pysdd(self, varnums):
"""
Convert this Vtree into a Vtree from PySDD.
If len(varnums) == 0, a vtree with one variable is returned instead
"""
if len(varnums) == 0:
return PysddVtree.new_with_var_order(1, [1], "balanced")
# After skimming the documention of the PySDD library, there doesn't
# seem to be an easy way to manually 'build' a vtree.
# However, there is a save/load mechanism, so we'll use that instead.
# Inline documentation of such files:
# ids of vtree nodes start at 0
# ids of variables start at 1
# vtree nodes appear bottom-up, children before parents
#
# file syntax:
# vtree number-of-nodes-in-vtree
# L id-of-leaf-vtree-node id-of-variable
# I id-of-internal-vtree-node id-of-left-child id-of-right-child
for internal_id, node in enumerate(self.all_nodes()):
node._internal_id = internal_id
with tempfile.NamedTemporaryFile(mode="w+") as f:
f.write("c Generated by PyWMI\n")
f.write(f"vtree {self.count()}\n")
self._to_pysdd(f, varnums)
f.flush()
vtree = PysddVtree.from_file(f.name)
return vtree
def main():
# set up vtree and manager
vtree = Vtree.from_file("input/opt-swap.vtree".encode())
manager = SddManager.from_vtree(vtree)
print("reading sdd from file ...")
alpha = manager.read_sdd_file("input/opt-swap.sdd".encode())
print(f" sdd size = {alpha.size()}")
# ref, perform the minimization, and then de-ref
alpha.ref()
print("minimizing sdd size ... ", end="")
manager.minimize() # see also manager.minimize_limited()
print("done!")
print(f" sdd size = {alpha.size()}")
alpha.deref()
# augment the SDD
print("augmenting sdd ...")
beta = alpha * (manager.l(4) + manager.l(5))
print(f" sdd size = {beta.size()}")
# ref, perform the minimization again on new SDD, and then de-ref
beta.ref()
print("minimizing sdd ... ", end="")
manager.minimize()
print("done!")
print(f" sdd size = {beta.size()}")
beta.deref()
def main():
# set up vtree and manager
vtree = Vtree.from_file(bytes(here / "input" / "big-swap.vtree"))
manager = SddManager.from_vtree(vtree)
print("reading sdd from file ...")
alpha = manager.read_sdd_file("input/big-swap.sdd".encode())
print(f" sdd size = {alpha.size()}")
# to perform a swap, we need the manager's vtree
manager_vtree = manager.vtree()
# ref alpha (no dead nodes when swapping)
alpha.ref()
# using size of sdd normalized for manager_vtree as baseline for limit
manager.init_vtree_size_limit(manager_vtree)
limit = 2.0
manager.set_vtree_operation_size_limit(limit)
print(f"modifying vtree (swap node 7) (limit growth by {limit:.1f}x) ... ",
end="")
succeeded = manager_vtree.swap(manager, 1) # limited
print("succeeded!" if succeeded == 1 else "did not succeed!")
print(f" sdd size = {alpha.size()}")
print("modifying vtree (swap node 7) (no limit) ... ", end="")
succeeded = manager_vtree.swap(manager, 0) # not limited
print("succeeded!" if succeeded == 1 else "did not succeed!")
print(f" sdd size = {alpha.size()}")
print("updating baseline of size limit ...")
manager.update_vtree_size_limit()
left_vtree = manager_vtree.left()
limit = 1.2
manager.set_vtree_operation_size_limit(limit)
print(f"modifying vtree (swap node 5) (limit growth by {limit}x) ... ",
end="")
succeeded = left_vtree.swap(manager, 1) # limited
print("succeeded!" if succeeded == 1 else "did not succeed!")
print(f" sdd size = {alpha.size()}")
limit = 1.3
manager.set_vtree_operation_size_limit(limit)
print(f"modifying vtree (swap node 5) (limit growth by {limit}x) ... ",
end="")
succeeded = left_vtree.swap(manager, 1) # limited
print("succeeded!" if succeeded == 1 else "did not succeed!")
print(f" sdd size = {alpha.size()}")
# deref alpha, since ref's are no longer needed
alpha.deref()
def sddConstructorFromFile(self,sddFName):
self.sddfName = sddFName
if os.path.isfile(self.sddfName+".sdd") and os.path.isfile(self.sddfName+".vtree") and os.path.isfile(self.sddfName+".map") :
with open(self.sddfName + ".map", "r") as f:
self.nameMappingDic = json.load(f)
vtree = Vtree.from_file((self.sddfName+".vtree").encode())
self.sdd = SddManager.from_vtree(vtree)
self.formula = self.sdd.read_sdd_file((self.sddfName+".sdd").encode())
else:
print("Please provide correct files")
sys.exit()
def main():
# set up vtree and manager
vtree = Vtree.from_file(bytes(here / "input" / "rotate-left.vtree"))
manager = SddManager.from_vtree(vtree)
# construct the term X_1 ^ X_2 ^ X_3 ^ X_4
x = [None] + [manager.literal(i) for i in range(1, 5)]
alpha = x[1]*x[2]*x[3]*x[4]
# to perform a rotate, we need the manager's vtree
manager_vtree = manager.vtree()
manager_vtree_right = manager_vtree.right()
print("saving vtree & sdd ...")
if not Path("output").is_dir():
raise Exception(f"Directory 'output' does not exist")
manager_vtree.save_as_dot("output/before-rotate-vtree.dot".encode())
alpha.save_as_dot("output/before-rotate-sdd.dot".encode())
# ref alpha (so it is not gc'd)
alpha.ref()
# garbage collect (no dead nodes when performing vtree operations)
print(f"dead sdd nodes = {manager.dead_count()}")
print("garbage collection ...")
manager.garbage_collect()
print(f"dead sdd nodes = {manager.dead_count()}")
print("left rotating ... ", end="")
succeeded = manager_vtree_right.rotate_left(manager, 0)
print("succeeded!" if succeeded == 1 else "did not succeed!")
# deref alpha, since ref's are no longer needed
alpha.deref()
# the root changed after rotation, so get the manager's vtree again
# this time using root_location
manager_vtree = manager.vtree()
print("saving vtree & sdd ...")
if not Path("output").is_dir():
raise Exception(f"Directory 'output' does not exist")
manager_vtree.save_as_dot("output/after-rotate-vtree.dot".encode())
alpha.save_as_dot("output/after-rotate-sdd.dot".encode())
def do_model_count(self, filename):
# create vtree
vtree_path = CounterFactory.create("minic2d").create_vtree(filename)
vtree = Vtree.from_file(bytes(vtree_path.encode()))
sdd = SddManager.from_vtree(vtree)
# read CNF
root = sdd.read_cnf_file(bytes(filename.encode()))
# do model counting
wmc = root.wmc(log_mode=False)
# add weights
weights = get_weights_from_cnf_file(filename)
lits = [sdd.literal(i) for i in range(1, sdd.var_count() + 1)]
assert len(weights) == 2 * len(lits), \
"Unexpected len {} for weights, got {}. Weights:\n{}".format(len(weights), 2 * len(lits), weights)
for i in range(len(lits)):
wmc.set_literal_weight(lits[i], weights[2 * i])
wmc.set_literal_weight(-lits[i], weights[2 * i + 1])
# write visualisation of SDD and Vtree to files
sdd_file = os.path.abspath(
os.path.join(os.path.dirname(filename), "sdd."))
vtree_file = os.path.abspath(
os.path.join(os.path.dirname(filename), "vtree-sdd."))
with open(sdd_file + "dot", "w") as out:
out.write(sdd.dot())
with open(vtree_file + "dot", "w") as out:
out.write(vtree.dot())
# (graph,) = pydot.graph_from_dot_file(sdd_file + "dot")
# graph.write_png(sdd_file + "png")
# (graph,) = pydot.graph_from_dot_file(vtree_file + "dot")
# graph.write_png(vtree_file + "png")
return wmc.propagate()
def main():
arg_parser = argparse.ArgumentParser(description="problog pipeline")
arg_parser.add_argument("--bif-file",
"-b",
help="The input bayesian network")
arg_parser.add_argument("--pl-file", "-p", help="The input problog file")
arg_parser.add_argument("cnf_file", help="The output cnf file")
arg_parser.add_argument("--enc",
"-e",
default=1,
help="The enc type 1 or 2",
type=int)
arg_parser.add_argument(
"--cnf-type",
"-c",
default="c2d",
help="The type of cnf file to output (c2d for minic2d or cachet)")
arg_parser.add_argument("--verbose",
"-v",
default=False,
help="Verbose output",
type=bool,
nargs='?',
const=True)
args = arg_parser.parse_args()
if (args.bif_file is None and args.pl_file is None) or \
(args.bif_file is not None and args.pl_file is not None):
print("one input file required")
return -1
c2d = True
if args.cnf_type == "c2d":
c2d = True
elif args.cnf_type == "cachet":
c2d = False
else:
print("unknwon cnf type")
return -1
is_bif = args.bif_file is not None
file_name = args.bif_file if is_bif else args.pl_file
enc1 = args.enc == 1
verbose = args.verbose
contents = None
with open(file_name, 'r') as f:
contents = f.read()
variables = None
cnf = None
weights = None
evidence = None
queries = None
start_time = time.time()
if is_bif:
variables, cnf, weights, queries = parse_bif(contents, enc1, verbose)
else:
variables, cnf, weights, evidence, queries = parse_srl(
contents, verbose)
cnf_time = time.time()
# if verbose:
# print("cnf latex:")
# print(len(cnf.args))
# clauses = cnf.args
# for clause in clauses:
# print("$", latex_print(clause), "$")
# print()
ints = cnf_to_ints(cnf, variables)
if evidence is not None:
for ev_name, ev_val in evidence:
idx = variables.index(ev_name) + 1
if not ev_val:
idx = -idx
ints.append([idx])
save_cnf(args.cnf_file, ints, variables, weights, c2d)
vtree_time = None
if c2d:
vtree_name = args.cnf_file + ".vtree"
print("miniC2D:")
minic2d = subprocess.run(
[MINIC2D_PATH, '-c', args.cnf_file, '-o', vtree_name])
if minic2d.returncode != 0:
print("error creating vtree")
return -1
vtree_time = time.time()
print("calculating sdd")
vtree = Vtree.from_file(vtree_name.encode())
sdd = SddManager.from_vtree(vtree)
root = sdd.read_cnf_file(args.cnf_file.encode())
print("sdd node count:", sdd.count())
print("sdd size:", sdd.size())
if verbose:
sdd.print_stdout()
print()
wmc = root.wmc(log_mode=False)
w = wmc.propagate()
print("model count:", w)
nlits = sdd.var_count()
assert nlits == len(variables)
for idx in range(nlits):
i = idx + 1
w_pos = weights[variables[idx]][0]
w_neg = weights[variables[idx]][1]
wmc.set_literal_weight(sdd.literal(i), w_pos)
wmc.set_literal_weight(sdd.literal(-i), w_neg)
w = wmc.propagate()
print("weighted count:", w)
print()
print("queries:")
if queries is not None:
for query in queries:
idx = variables.index(query) + 1
pr = wmc.literal_pr(sdd.literal(idx))
print("P(", query, ") =\t", pr)
end_time = time.time()
print()
print("cnf variables:", len(variables), "clauses: ", len(ints))
print()
print("total time:\t", end_time - start_time)
print("cnf time:\t", cnf_time - start_time)
if vtree_time is not None:
print("vtree time:\t", vtree_time - cnf_time)
print("count time:\t", end_time - vtree_time)
return 0
