68 lines
1.5 KiB
Python
68 lines
1.5 KiB
Python
# 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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import numpy as np
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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, min(t + t2, x.index[-1]))
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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, min(t + t2, x.index[-1]))
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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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# TODO(lift interpolation much higher)
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return lambda term: term.coeff*np.interp(t, x.index, x[term.id.name])
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