def prepare_input(self, fname):
input = CnfReader.from_file(fname)
self.num_vars = input.num_vars
self.num_clauses = input.num_clauses
self.clauses = input.clauses
self.var_clause_dict = defaultdict(set)
return cnf2primal(input.num_vars, input.clauses, self.var_clause_dict)
def prepare_input(self, fname):
input = CnfReader.from_file(fname)
self.num_vars = input.num_vars
self.num_clauses = input.num_clauses
self.clauses = input.clauses
self.projected = list(input.projected)
self.var_clause_dict = defaultdict(set)
#logger.debug("{} vars, {}={} clauses", input.num_vars, input.num_clauses, len(input.clauses))
num_vars, edges, adj = cnf2primal(input.num_vars, input.clauses, self.var_clause_dict, True)
return self.abstr.abstract(num_vars,edges,adj,self.projected)
def prepare_input(self, fname):
input = CnfReader.from_file(fname)
self.num_vars = input.num_vars
self.num_clauses = input.num_clauses
self.clauses = input.clauses
self.projected = input.projected
self.var_clause_dict = defaultdict(set)
num_vars, edges = cnf2primal(input.num_vars, input.clauses, self.var_clause_dict)
# Create clique over projected variables
for a in self.projected:
for b in self.projected:
if a < b:
edges.add((a,b))
return (num_vars, edges)
def preprocess(self):
global cfg
if "preprocessor" not in cfg["nesthdb"]:
return # True, num_vars, vars, len(clauses), clauses, None
cfg_prep = cfg["nesthdb"]["preprocessor"]
preprocessor = [cfg_prep["path"]]
if "args" in cfg_prep:
preprocessor.extend(cfg_prep["args"].split(' '))
self.active_process = ppmc = subprocess.Popen(preprocessor,stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.DEVNULL)
clauses,proj_vars,num_vars,mapping,rev_mapping = normalize_cnf(self.formula.clauses, self.projected, True)
StreamWriter(ppmc.stdin).write_cnf(self.formula.num_vars,clauses,normalize=False)
ppmc.stdin.close()
input = CnfReader.from_stream(ppmc.stdout,silent=True)
ppmc.wait()
ppmc.stdout.close()
self.active_process = None
if not input.error:
self.maybe_sat = input.maybe_sat
if not input.done:
# fix corner case, where input.vars contains not all of range(1,input.max_vars+1)
clauses, vars, proj_vars = denormalize_cnf(input.clauses,input.vars,proj_vars,rev_mapping)
self.formula = Formula(vars,clauses)
self.projected = proj_vars.intersection(vars)
# remove single_clause_proj_vars, they are not needed/relevant and only waste resources!
# consequently, these variables are treated as if they were never there, no 2 ** correction!
_, singles, _ = denormalize_cnf((),input.single_vars,(),rev_mapping)
self.projected_orig = self.projected_orig.difference(singles)
else:
# set models to 1 if instance was sat
if len(self.projected) == 0:
self.models = 1
# use result if instance was #sat
elif self.projected.intersection(self.formula.vars) == self.formula.vars:
self.models = input.models
# dont use result if instance was pmc
else:
pass
else:
logger.debug("Pre-processor failed... ignoring result")
def read_input(fname):
input = CnfReader.from_file(fname)
return input.num_vars, input.vars, input.num_clauses, input.clauses, input.projected
def from_file(cls, fname):
input = CnfReader.from_file(fname)
# uncomment the following line for sharpsat solving
#input.projected = set(range(1,input.num_vars+1)) - input.single_vars #sharpsat!
return cls(input.vars, input.clauses, input.projected)
def sharpsat_from_file(cls, fname):
input = CnfReader.from_file(fname)
return cls(input.vars, input.clauses, set(range(1,input.num_vars+1)) - input.single_vars)
def from_file(cls, fname):
input = CnfReader.from_file(fname)
return cls(input.vars, input.clauses, input.projected)