spot/wrap/python/spot.py
Alexandre Duret-Lutz 2362b9ab68 python: improve handling of formulas
* src/misc/escape.hh, src/misc/escape.cc (escape_latex): New function.
* src/ltlvisit/tostring.cc: Escape atomic proposition in LaTeX output.
* wrap/python/spot.py: Make it easy to output formulas in different
syntaxes.  Also allow the AST to be shown.
* wrap/python/spot_impl.i: Catch std::runtime_error.
* wrap/python/tests/formulas.ipynb: New file.
* wrap/python/tests/Makefile.am: Add it.
2015-03-11 21:09:12 +01:00

264 lines
9.7 KiB
Python

# -*- coding: utf-8 -*-
# Copyright (C) 2014, 2015 Laboratoire de
# Recherche et Développement de l'Epita (LRDE).
#
# This file is part of Spot, a model checking library.
#
# Spot is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later version.
#
# Spot is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
# or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public
# License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from spot_impl import *
import subprocess
import sys
_bdd_dict = make_bdd_dict()
def _ostream_to_svg(ostr):
dotty = subprocess.Popen(['dot', '-Tsvg'],
stdin=subprocess.PIPE,
stdout=subprocess.PIPE)
dotty.stdin.write(ostr.str().encode('utf-8'))
res = dotty.communicate()
return res[0].decode('utf-8')
def _render_automaton_as_svg(a):
ostr = ostringstream()
dotty_reachable(ostr, a)
return _ostream_to_svg(ostr)
tgba._repr_svg_ = _render_automaton_as_svg
def _render_formula_as_svg(a):
# Load the SVG function only if we need it. This way the bindings
# can still be used outside of IPython if IPython is not
# installed.
from IPython.display import SVG
ostr = ostringstream()
dotty(ostr, a)
return SVG(_ostream_to_svg(ostr))
def _formula_str_ctor(self, str):
self.this = parse_formula(str)
def _formula_to_str(self, format = 'spot'):
if format == 'spot':
return to_string(self)
elif format == 'spin':
return to_spin_string(self)
elif format == 'utf8':
return to_utf8_string(self)
elif format == 'lbt':
return to_lbt_string(self)
elif format == 'wring':
return to_wring_string(self)
elif format == 'latex':
return to_latex_string(self)
elif format == 'sclatex':
return to_sclatex_string(self)
else:
raise ValueError("unknown string format: " + format)
formula.__init__ = _formula_str_ctor
formula.to_str = _formula_to_str
formula.show_ast = _render_formula_as_svg
def _tgba_str_ctor(self, str):
self.this = ltl_to_tgba_fm(parse_formula(str), _bdd_dict)
tgba.__init__ = _tgba_str_ctor
# Wrapper around a formula iterator to which we add some methods of formula
# (using _addfilter and _addmap), so that we can write things like
# formulas.simplify().is_X_free().
class formulaiterator:
def __init__(self, formulas):
self._formulas = formulas
def __iter__(self):
return self
def __next__(self):
return next(self._formulas)
# fun shoud be a predicate and should be a method of formula.
# _addfilter adds this predicate as a filter whith the same name in
# formulaiterator.
def _addfilter(fun):
def filtf(self, *args, **kwargs):
it = filter(lambda f: getattr(f, fun)(*args, **kwargs), self)
return formulaiterator(it)
def nfiltf(self, *args, **kwargs):
it = filter(lambda f: not getattr(f, fun)(*args, **kwargs), self)
return formulaiterator(it)
setattr(formulaiterator, fun, filtf)
if fun[:3] == 'is_':
notfun = fun[:3] + 'not_' + fun[3:]
elif fun[:4] == 'has_':
notfun = fun[:4] + 'no_' + fun[4:]
else:
notfun = 'not_' + fun
setattr(formulaiterator, fun, filtf)
setattr(formulaiterator, notfun, nfiltf)
# fun should be a function taking a formula as its first parameter and returning
# a formula.
# _addmap adds this function as a method of formula and formulaiterator.
def _addmap(fun):
def mapf(self, *args, **kwargs):
return formulaiterator(map(lambda f: getattr(f, fun)(*args, **kwargs),
self))
setattr(formula, fun, lambda self, *args, **kwargs: globals()[fun](self,
*args, **kwargs))
setattr(formulaiterator, fun, mapf)
def randltl(ap, n = -1, **kwargs):
"""Generate random formulas.
Returns a random formula iterator.
ap: the number of atomic propositions used to generate random formulas.
n: number of formulas to generate, or unbounded if n < 0.
**kwargs:
seed: seed for the random number generator (0).
output: can be 'ltl', 'psl', 'bool' or 'sere' ('ltl').
allow_dups: allow duplicate formulas (False).
tree_size: tree size of the formulas generated, before mandatory
simplifications (15)
boolean_priorities: set priorities for Boolean formulas.
ltl_priorities: set priorities for LTL formulas.
sere_priorities: set priorities for SERE formulas.
dump_priorities: show current priorities, do not generate any formula.
simplify:
0 No rewriting
1 basic rewritings and eventual/universal rules
2 additional syntactic implication rules
3 (default) better implications using containment
"""
opts = option_map()
output_map = {
"ltl" : OUTPUTLTL,
"psl" : OUTPUTPSL,
"bool" : OUTPUTBOOL,
"sere" : OUTPUTSERE
}
if isinstance(ap, list):
aprops = atomic_prop_set()
e = default_environment.instance()
for elt in ap:
aprops.insert(is_atomic_prop(e.require(elt)))
ap = aprops
ltl_priorities = kwargs.get("ltl_priorities", None)
sere_priorities = kwargs.get("sere_priorities", None)
boolean_priorities = kwargs.get("boolean_priorities", None)
output = output_map[kwargs.get("output", "ltl")]
opts.set("output", output)
opts.set("seed", kwargs.get("seed", 0))
tree_size = kwargs.get("tree_size", 15)
if isinstance(tree_size, tuple):
tree_size_min, tree_size_max = tree_size
else:
tree_size_min = tree_size_max = tree_size
opts.set("tree_size_min", tree_size_min)
opts.set("tree_size_max", tree_size_max)
opts.set("unique", not kwargs.get("allow_dups", False))
opts.set("wf", kwargs.get("weak_fairness", False))
simpl_level = kwargs.get("simplify", 0)
if simpl_level > 3 or simpl_level < 0:
sys.stderr.write('invalid simplification level: ' + simpl_level)
return
opts.set("simplification_level", simpl_level)
rg = randltlgenerator(ap, opts, ltl_priorities, sere_priorities,
boolean_priorities)
dump_priorities = kwargs.get("dump_priorities", False)
if dump_priorities:
dumpstream = ostringstream()
if output == OUTPUTLTL:
print('Use argument ltl_priorities=STRING to set the following ' \
'LTL priorities:\n')
rg.dump_ltl_priorities(dumpstream)
print(dumpstream.str())
elif output == OUTPUTBOOL:
print('Use argument boolean_priorities=STRING to set the ' \
'following Boolean formula priorities:\n')
rg.dump_bool_priorities(dumpstream)
print(dumpstream.str())
elif output == OUTPUTPSL or output == OUTPUTSERE:
if output != OUTPUTSERE:
print('Use argument ltl_priorities=STRING to set the following ' \
'LTL priorities:\n')
rg.dump_psl_priorities(dumpstream)
print(dumpstream.str())
print('Use argument sere_priorities=STRING to set the following ' \
'SERE priorities:\n')
rg.dump_sere_priorities(dumpstream)
print(dumpstream.str())
print('Use argument boolean_priorities=STRING to set the ' \
'following Boolean formula priorities:\n')
rg.dump_sere_bool_priorities(dumpstream)
print(dumpstream.str())
else:
sys.stderr.write("internal error: unknown type of output")
return
def _randltlgenerator(rg):
i = 0
while i != n:
f = rg.next()
if f is None:
sys.stderr.write("Warning: could not generate a new unique formula " \
"after " + str(MAX_TRIALS) + " trials.\n")
yield None
else:
yield f
i += 1
return formulaiterator(_randltlgenerator(rg))
def simplify(f, **kwargs):
level = kwargs.get('level', None)
if level is not None:
return ltl_simplifier(ltl_simplifier_options(level)).simplify(f)
basics = kwargs.get('basics', True)
synt_impl = kwargs.get('synt_impl', True)
event_univ = kwargs.get('event_univ', True)
containment_checks = kwargs.get('containment_checks', False)
containment_checks_stronger = kwargs.get('containment_checks_stronger', False)
nenoform_stop_on_boolean = kwargs.get('nenoform_stop_on_boolean', False)
reduce_size_strictly = kwargs.get('reduce_size_strictly', False)
boolean_to_isop = kwargs.get('boolean_to_isop', False)
favor_event_univ = kwargs.get('favor_event_univ', False)
simp_opts = ltl_simplifier_options(basics,
synt_impl,
event_univ,
containment_checks,
containment_checks_stronger,
nenoform_stop_on_boolean,
reduce_size_strictly,
boolean_to_isop,
favor_event_univ)
return ltl_simplifier(simp_opts).simplify(f)
for fun in dir(formula):
if (callable(getattr(formula, fun)) and
(fun[:3] == 'is_' or fun[:4] == 'has_')):
_addfilter(fun)
for fun in ['remove_x', 'get_literal', 'relabel', 'relabel_bse',
'simplify', 'unabbreviate_ltl']:
_addmap(fun)