Integrate attr libraries
This commit is contained in:
Marcell Vazquez-Chanlatte
parent
fb2e79b807
commit
472fd45ce2
9 changed files with 200 additions and 265 deletions
305
mtl/ast.py
305
mtl/ast.py
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@ -1,7 +1,9 @@
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# -*- coding: utf-8 -*-
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from collections import deque, namedtuple
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from functools import lru_cache
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from typing import Union, NamedTuple
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import attr
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import funcy as fn
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from lenses import lens, bind
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@ -24,131 +26,161 @@ def flatten_binary(phi, op, dropT, shortT):
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return op(tuple(fn.mapcat(f, phi.args)))
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class AST(object):
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__slots__ = ()
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def __or__(self, other):
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return flatten_binary(Or((self, other)), Or, BOT, TOP)
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def __and__(self, other):
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return flatten_binary(And((self, other)), And, TOP, BOT)
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def __invert__(self):
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if isinstance(self, Neg):
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return self.arg
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return Neg(self)
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def __rshift__(self, t):
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if self in (BOT, TOP):
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return self
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phi = self
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for _ in range(t):
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phi = Next(phi)
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return phi
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def __call__(self, trace, time=0):
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return mtl.pointwise_sat(self)(trace, time)
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@property
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def children(self):
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return tuple()
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def walk(self):
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"""Walk of the AST."""
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pop = deque.pop
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children = deque([self])
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while len(children) > 0:
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node = pop(children)
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yield node
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children.extend(node.children)
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@property
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def params(self):
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def get_params(leaf):
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if isinstance(leaf, ModalOp):
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if isinstance(leaf.interval[0], Param):
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yield leaf.interval[0]
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if isinstance(leaf.interval[1], Param):
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yield leaf.interval[1]
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return set(fn.mapcat(get_params, self.walk()))
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def set_params(self, val):
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phi = param_lens(self)
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return phi.modify(lambda x: float(val.get(x, val.get(str(x), x))))
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@property
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def atomic_predicates(self):
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return set(AP_lens.collect()(self))
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def inline_context(self, context):
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phi, phi2 = self, None
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def update(ap):
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return context.get(ap, ap)
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while phi2 != phi:
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phi2, phi = phi, AP_lens.modify(update)(phi)
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return phi
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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def _or(exp1, exp2):
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return flatten_binary(Or((exp1, exp2)), Or, BOT, TOP)
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class _Top(AST):
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__slots__ = ()
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def _and(exp1, exp2):
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return flatten_binary(And((exp1, exp2)), And, TOP, BOT)
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def _neg(exp):
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if isinstance(exp, _Bot):
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return _Top()
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elif isinstance(exp, _Top):
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return _Bot()
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elif isinstance(exp, Neg):
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return exp.arg
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return Neg(exp)
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def _eval(exp, trace, time=0):
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return mtl.pointwise_sat(exp)(trace, time)
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def _timeshift(exp, t):
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if exp in (BOT, TOP):
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return exp
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for _ in range(t):
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exp = Next(exp)
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return exp
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def _walk(exp):
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"""Walk of the AST."""
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pop = deque.pop
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children = deque([exp])
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while len(children) > 0:
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node = pop(children)
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yield node
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children.extend(node.children)
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def _params(exp):
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def get_params(leaf):
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if isinstance(leaf, ModalOp):
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if isinstance(leaf.interval[0], Param):
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yield leaf.interval[0]
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if isinstance(leaf.interval[1], Param):
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yield leaf.interval[1]
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return set(fn.mapcat(get_params, exp.walk()))
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def _set_symbols(node, val):
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children = tuple(_set_symbols(c, val) for c in node.children)
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if hasattr(node, 'interval'):
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return node.evolve(
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arg=children[0],
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interval=_update_itvl(node.interval, val),
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)
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elif isinstance(node, AtomicPred):
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return val.get(node.id, node)
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elif hasattr(node, 'args'):
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return node.evolve(args=children)
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elif hasattr(node, 'arg'):
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return node.evolve(arg=children[0])
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return node
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def _inline_context(exp, context):
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phi, phi2 = exp, None
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while phi2 != phi:
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phi2, phi = phi, _set_symbols(phi, context)
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return phi
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def _atomic_predicates(exp):
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return set(bind(exp).Recur(AtomicPred).collect())
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class Param(NamedTuple):
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name: str
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def __repr__(self):
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return self.name
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def ast_class(cls):
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cls.__or__ = _or
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cls.__and__ = _and
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cls.__invert__ = _neg
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cls.__call__ = _eval
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cls.__rshift__ = _timeshift
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cls.__getitem__ = _inline_context
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cls.walk = _walk
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cls.params = property(_params)
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cls.atomic_predicates = property(_atomic_predicates)
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cls.evolve = attr.evolve
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if not hasattr(cls, "children"):
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cls.children = property(lambda _: ())
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return attr.s(frozen=True, auto_attribs=True, repr=False, slots=True)(cls)
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def _update_itvl(itvl, lookup):
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def _update_param(p):
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if not isinstance(p, Param) or p.name not in lookup:
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return p
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val = lookup[p.name]
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return val if isinstance(lookup, Param) else float(val)
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return Interval(*map(_update_param, itvl))
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@ast_class
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class _Top:
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def __repr__(self):
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return "TRUE"
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def __invert__(self):
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return BOT
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class _Bot(AST):
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__slots__ = ()
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@ast_class
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class _Bot:
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def __repr__(self):
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return "FALSE"
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def __invert__(self):
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return TOP
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TOP = _Top()
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BOT = _Bot()
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class AtomicPred(namedtuple("AP", ["id"]), AST):
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__slots__ = ()
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@ast_class
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class AtomicPred:
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id: str
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def __repr__(self):
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return f"{self.id}"
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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@property
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def children(self):
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return tuple()
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class Interval(namedtuple('I', ['lower', 'upper'])):
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__slots__ = ()
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class Interval(NamedTuple):
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lower: Union[float, Param]
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upper: Union[float, Param]
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def __repr__(self):
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return f"[{self.lower},{self.upper}]"
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class NaryOpMTL(namedtuple('NaryOp', ['args']), AST):
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__slots__ = ()
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@ast_class
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class NaryOpMTL:
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OP = "?"
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args: "Node" # TODO: when 3.7 is more common replace with type union.
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def __repr__(self):
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return "(" + f" {self.OP} ".join(f"{x}" for x in self.args) + ")"
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@ -159,28 +191,18 @@ class NaryOpMTL(namedtuple('NaryOp', ['args']), AST):
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class Or(NaryOpMTL):
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__slots__ = ()
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OP = "|"
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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class And(NaryOpMTL):
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__slots__ = ()
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OP = "&"
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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class ModalOp(namedtuple('ModalOp', ['interval', 'arg']), AST):
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__slots__ = ()
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@ast_class
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class ModalOp:
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OP = '?'
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interval: Interval
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arg: "Node"
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def __repr__(self):
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if self.interval.lower == 0 and self.interval.upper == float('inf'):
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@ -193,25 +215,17 @@ class ModalOp(namedtuple('ModalOp', ['interval', 'arg']), AST):
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class F(ModalOp):
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__slots__ = ()
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OP = "< >"
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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class G(ModalOp):
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__slots__ = ()
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OP = "[ ]"
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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class Until(namedtuple('ModalOp', ['arg1', 'arg2']), AST):
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__slots__ = ()
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@ast_class
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class Until:
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arg1: "Node"
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arg2: "Node"
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def __repr__(self):
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return f"({self.arg1} U {self.arg2})"
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@ -220,13 +234,10 @@ class Until(namedtuple('ModalOp', ['arg1', 'arg2']), AST):
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def children(self):
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return (self.arg1, self.arg2)
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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class Neg(namedtuple('Neg', ['arg']), AST):
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__slots__ = ()
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@ast_class
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class Neg:
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arg: "Node"
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def __repr__(self):
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return f"~{self.arg}"
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@ -235,13 +246,10 @@ class Neg(namedtuple('Neg', ['arg']), AST):
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def children(self):
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return (self.arg,)
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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class Next(namedtuple('Next', ['arg']), AST):
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__slots__ = ()
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@ast_class
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class Next:
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arg: "Node"
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def __repr__(self):
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return f"@{self.arg}"
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@ -250,30 +258,7 @@ class Next(namedtuple('Next', ['arg']), AST):
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def children(self):
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return (self.arg,)
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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class Param(namedtuple('Param', ['name']), AST):
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__slots__ = ()
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def __repr__(self):
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return self.name
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def __hash__(self):
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# TODO: compute hash based on contents
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return hash(repr(self))
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@lru_cache()
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def param_lens(phi, *, getter=False):
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return bind(phi).Recur(Param)
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def type_pred(*args):
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ast_types = set(args)
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return lambda x: type(x) in ast_types
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AP_lens = lens.Recur(AtomicPred)
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