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# Natural Language Toolkit: Interface to the Mace4 Model Builder
#
# Author: Dan Garrette <dhgarrette@gmail.com>
# Ewan Klein <ewan@inf.ed.ac.uk>
# URL: <http://www.nltk.org/>
# For license information, see LICENSE.TXT
import os
import tempfile
from nltk.sem.logic import *
from nltk.sem import Valuation
from api import ModelBuilder, BaseModelBuilderCommand
from prover9 import *
"""
A model builder that makes use of the external 'Mace4' package.
"""
class MaceCommand(Prover9CommandParent, BaseModelBuilderCommand):
"""
A L{MaceCommand} specific to the L{Mace} model builder. It contains
the a print_assumptions() method that is used to print the list
of assumptions in multiple formats.
"""
_interpformat_bin = None
def __init__(self, goal=None, assumptions=None, timeout=60, model_builder=None):
"""
@param goal: Input expression to prove
@type goal: L{logic.Expression}
@param assumptions: Input expressions to use as assumptions in
the proof.
@type assumptions: C{list} of L{logic.Expression}
@param timeout: number of seconds before timeout; set to 0 for
no timeout.
@type timeout: C{int}
"""
if model_builder is not None:
assert isinstance(model_builder, Mace)
else:
model_builder = Mace(timeout)
BaseModelBuilderCommand.__init__(self, model_builder, goal, assumptions)
valuation = property(lambda mbc: mbc.model('valuation'))
def _convert2val(self, valuation_str):
"""
Transform the output file into an NLTK-style Valuation.
@return: A model if one is generated; None otherwise.
@rtype: L{nltk.sem.Valuation}
"""
valuation_standard_format = self._transform_output(valuation_str, 'standard')
val = []
for line in valuation_standard_format.splitlines(False):
l = line.strip()
if l.startswith('interpretation'):
# find the number of entities in the model
num_entities = int(l[l.index('(')+1:l.index(',')].strip())
elif l.startswith('function') and l.find('_') == -1:
# replace the integer identifier with a corresponding alphabetic character
name = l[l.index('(')+1:l.index(',')].strip()
if is_indvar(name):
name = name.upper()
value = int(l[l.index('[')+1:l.index(']')].strip())
val.append((name, MaceCommand._make_model_var(value)))
elif l.startswith('relation'):
l = l[l.index('(')+1:]
if '(' in l:
#relation is not nullary
name = l[:l.index('(')].strip()
values = [int(v.strip()) for v in l[l.index('[')+1:l.index(']')].split(',')]
val.append((name, MaceCommand._make_relation_set(num_entities, values)))
else:
#relation is nullary
name = l[:l.index(',')].strip()
value = int(l[l.index('[')+1:l.index(']')].strip())
val.append((name, value == 1))
return Valuation(val)
@staticmethod
def _make_relation_set(num_entities, values):
"""
Convert a Mace4-style relation table into a dictionary.
@parameter num_entities: the number of entities in the model; determines the row length in the table.
@type num_entities: C{int}
@parameter values: a list of 1's and 0's that represent whether a relation holds in a Mace4 model.
@type values: C{list} of C{int}
"""
r = set()
for position in [pos for (pos,v) in enumerate(values) if v == 1]:
r.add(tuple(MaceCommand._make_relation_tuple(position, values, num_entities)))
return r
@staticmethod
def _make_relation_tuple(position, values, num_entities):
if len(values) == 1:
return []
else:
sublist_size = len(values) / num_entities
sublist_start = position / sublist_size
sublist_position = position % sublist_size
sublist = values[sublist_start*sublist_size:(sublist_start+1)*sublist_size]
return [MaceCommand._make_model_var(sublist_start)] + \
MaceCommand._make_relation_tuple(sublist_position,
sublist,
num_entities)
@staticmethod
def _make_model_var(value):
"""
Pick an alphabetic character as identifier for an entity in the model.
@parameter value: where to index into the list of characters
@type value: C{int}
"""
letter = ['a','b','c','d','e','f','g','h','i','j','k','l','m','n',
'o','p','q','r','s','t','u','v','w','x','y','z'][value]
num = int(value) / 26
if num > 0:
return letter + str(num)
else:
return letter
def _decorate_model(self, valuation_str, format):
"""
Print out a Mace4 model using any Mace4 C{interpformat} format.
See U{http://www.cs.unm.edu/~mccune/mace4/manual/} for details.
@param valuation_str: C{str} with the model builder's output
@param format: C{str} indicating the format for displaying
models. Defaults to 'standard' format.
@return: C{str}
"""
if not format:
return valuation_str
elif format == 'valuation':
return self._convert2val(valuation_str)
else:
return self._transform_output(valuation_str, format)
def _transform_output(self, valuation_str, format):
"""
Transform the output file into any Mace4 C{interpformat} format.
@parameter format: Output format for displaying models.
@type format: C{str}
"""
if format in ['standard', 'standard2', 'portable', 'tabular',
'raw', 'cooked', 'xml', 'tex']:
return self._call_interpformat(valuation_str, [format])[0]
else:
raise LookupError("The specified format does not exist")
def _call_interpformat(self, input_str, args=[], verbose=False):
"""
Call the C{interpformat} binary with the given input.
@param input_str: A string whose contents are used as stdin.
@param args: A list of command-line arguments.
@return: A tuple (stdout, returncode)
@see: L{config_prover9}
"""
if self._interpformat_bin is None:
self._interpformat_bin = self._modelbuilder._find_binary(
'interpformat', verbose)
return self._modelbuilder._call(input_str, self._interpformat_bin,
args, verbose)
class Mace(Prover9Parent, ModelBuilder):
_mace4_bin = None
def _build_model(self, goal=None, assumptions=None, verbose=False):
"""
Use Mace4 to build a first order model.
@return: C{True} if a model was found (i.e. Mace returns value of 0),
else C{False}
"""
if not assumptions:
assumptions = []
stdout, returncode = self._call_mace4(self.prover9_input(goal, assumptions),
verbose=verbose)
return (returncode == 0, stdout)
def _call_mace4(self, input_str, args=[], verbose=False):
"""
Call the C{mace4} binary with the given input.
@param input_str: A string whose contents are used as stdin.
@param args: A list of command-line arguments.
@return: A tuple (stdout, returncode)
@see: L{config_prover9}
"""
if self._mace4_bin is None:
self._mace4_bin = self._find_binary('mace4', verbose)
return self._call(input_str, self._mace4_bin, args, verbose)
def spacer(num=30):
print '-' * num
def decode_result(found):
"""
Decode the result of model_found()
@parameter found: The output of model_found()
@type found: C{boolean}
"""
return {True: 'Countermodel found', False: 'No countermodel found', None: 'None'}[found]
def test_model_found(arguments):
"""
Try some proofs and exhibit the results.
"""
lp = LogicParser()
for (goal, assumptions) in arguments:
g = lp.parse(goal)
alist = [lp.parse(a) for a in assumptions]
m = MaceCommand(g, assumptions=alist, timeout=5)
found = m.build_model()
for a in alist:
print ' %s' % a
print '|- %s: %s\n' % (g, decode_result(found))
def test_build_model(arguments):
"""
Try to build a L{nltk.sem.Valuation}.
"""
lp = LogicParser()
g = lp.parse('all x.man(x)')
alist = [lp.parse(a) for a in ['man(John)',
'man(Socrates)',
'man(Bill)',
'some x.(-(x = John) & man(x) & sees(John,x))',
'some x.(-(x = Bill) & man(x))',
'all x.some y.(man(x) -> gives(Socrates,x,y))']]
m = MaceCommand(g, assumptions=alist)
m.build_model()
spacer()
print "Assumptions and Goal"
spacer()
for a in alist:
print ' %s' % a
print '|- %s: %s\n' % (g, decode_result(m.build_model()))
spacer()
#print m.model('standard')
#print m.model('cooked')
print "Valuation"
spacer()
print m.valuation, '\n'
def test_transform_output(argument_pair):
"""
Transform the model into various Mace4 C{interpformat} formats.
"""
lp = LogicParser()
g = lp.parse(argument_pair[0])
alist = [lp.parse(a) for a in argument_pair[1]]
m = MaceCommand(g, assumptions=alist)
m.build_model()
for a in alist:
print ' %s' % a
print '|- %s: %s\n' % (g, m.build_model())
for format in ['standard', 'portable', 'xml', 'cooked']:
spacer()
print "Using '%s' format" % format
spacer()
print m.model(format=format)
def test_make_relation_set():
print MaceCommand._make_relation_set(num_entities=3, values=[1,0,1]) == set([('c',), ('a',)])
print MaceCommand._make_relation_set(num_entities=3, values=[0,0,0,0,0,0,1,0,0]) == set([('c', 'a')])
print MaceCommand._make_relation_set(num_entities=2, values=[0,0,1,0,0,0,1,0]) == set([('a', 'b', 'a'), ('b', 'b', 'a')])
arguments = [
('mortal(Socrates)', ['all x.(man(x) -> mortal(x))', 'man(Socrates)']),
('(not mortal(Socrates))', ['all x.(man(x) -> mortal(x))', 'man(Socrates)'])
]
if __name__ == '__main__':
test_model_found(arguments)
test_build_model(arguments)
test_transform_output(arguments[1])
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