add boolean semantics
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66
boolean_eval.py
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66
boolean_eval.py
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# TODO: figure out how to deduplicate this with robustness
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# - Abstract as working on distributive lattice
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from functools import singledispatch
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import operator as op
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from lenses import lens
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import stl.ast
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@singledispatch
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def pointwise_sat(stl):
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raise NotImplementedError
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@pointwise_sat.register(stl.Or)
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def _(stl):
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return lambda x, t: any(pointwise_sat(arg)(x, t) for arg in stl.args)
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@pointwise_sat.register(stl.And)
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def _(stl):
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return lambda x, t: all(pointwise_sat(arg)(x, t) for arg in stl.args)
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@pointwise_sat.register(stl.F)
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def _(stl):
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lo, hi = stl.interval
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return lambda x, t: any((pointwise_sat(stl.arg)(x, t + t2)
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for t2 in x[lo:hi].index))
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@pointwise_sat.register(stl.G)
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def _(stl):
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lo, hi = stl.interval
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return lambda x, t: all((pointwise_sat(stl.arg)(x, t + t2)
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for t2 in x[lo:hi].index))
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@pointwise_sat.register(stl.Neg)
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def _(stl):
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return lambda x, t: not pointwise_sat(arg)(x, t)
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op_lookup = {
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">": op.gt,
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">=": op.ge,
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"<": op.lt,
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"<=": op.le,
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"=": op.eq,
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}
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@pointwise_sat.register(stl.LinEq)
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def _(stl):
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op = op_lookup[stl.op]
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return lambda x, t: op(eval_terms(stl, x, t), stl.const)
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def eval_terms(lineq, x, t):
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psi = lens(lineq).terms.each_().modify(eval_term(x, t))
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return sum(psi.terms)
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def eval_term(x, t):
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return lambda term: term.coeff*x[term.id.name][t]
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22
test_boolean_eval.py
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22
test_boolean_eval.py
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import stl
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import stl.boolean_eval
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import pandas as pd
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from nose2.tools import params
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import unittest
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from sympy import Symbol
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ex1 = ("2*A > 3", False)
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ex2 = ("F[0, 1](2*A > 3)", True)
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ex3 = ("F[1, 0](2*A > 3)", False)
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ex4 = ("G[1, 0](2*A > 3)", True)
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ex5 = ("(A < 0)", False)
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ex6 = ("G[0, 0.1](A < 0)", False)
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x = pd.DataFrame([[1,2], [1,4], [4,2]], index=[0,0.1,0.2],
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columns=["A", "B"])
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class TestSTLRobustness(unittest.TestCase):
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@params(ex1, ex2, ex3, ex4, ex5, ex6)
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def test_stl(self, phi_str, r):
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phi = stl.parse(phi_str)
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stl_eval = stl.boolean_eval.pointwise_sat(phi)
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self.assertEqual(stl_eval(x, 0), r)
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