add boolean semantics

boolean_eval.py

@@ -0,0 +1,66 @@
+# TODO: figure out how to deduplicate this with robustness
+# - Abstract as working on distributive lattice
+
+from functools import singledispatch
+import operator as op
+
+from lenses import lens
+
+import stl.ast
+
+@singledispatch
+def pointwise_sat(stl):
+    raise NotImplementedError
+
+
+@pointwise_sat.register(stl.Or)
+def _(stl):
+    return lambda x, t: any(pointwise_sat(arg)(x, t) for arg in stl.args)
+
+
+@pointwise_sat.register(stl.And)
+def _(stl):
+    return lambda x, t: all(pointwise_sat(arg)(x, t) for arg in stl.args)
+
+
+@pointwise_sat.register(stl.F)
+def _(stl):
+    lo, hi = stl.interval
+    return lambda x, t: any((pointwise_sat(stl.arg)(x, t + t2) 
+                             for t2 in x[lo:hi].index))
+
+
+@pointwise_sat.register(stl.G)
+def _(stl):
+    lo, hi = stl.interval
+    return lambda x, t: all((pointwise_sat(stl.arg)(x, t + t2) 
+                             for t2 in x[lo:hi].index))
+
+
+@pointwise_sat.register(stl.Neg)
+def _(stl):
+    return lambda x, t: not pointwise_sat(arg)(x, t)
+
+
+op_lookup = {
+    ">": op.gt,
+    ">=": op.ge,
+    "<": op.lt,
+    "<=": op.le,
+    "=": op.eq,
+}
+
+
+@pointwise_sat.register(stl.LinEq)
+def _(stl):
+    op = op_lookup[stl.op]
+    return lambda x, t: op(eval_terms(stl, x, t), stl.const)
+
+
+def eval_terms(lineq, x, t):
+    psi = lens(lineq).terms.each_().modify(eval_term(x, t))
+    return sum(psi.terms)
+
+
+def eval_term(x, t):
+    return lambda term: term.coeff*x[term.id.name][t]