sketch out tests for smooth robustness
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0261bb434f
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2 changed files with 31 additions and 2 deletions
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@ -1,5 +1,7 @@
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import stl
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import stl
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import stl.boolean_eval
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import stl.robustness
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import stl.robustness
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import stl.smooth_robustness
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import pandas as pd
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import pandas as pd
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from nose2.tools import params
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from nose2.tools import params
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import unittest
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import unittest
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@ -19,7 +21,34 @@ x = pd.DataFrame([[1,2], [1,4], [4,2]], index=[0,0.1,0.2],
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class TestSTLRobustness(unittest.TestCase):
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class TestSTLRobustness(unittest.TestCase):
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@params(ex1, ex2, ex3, ex4, ex5, ex6)
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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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def test_robustness_sign(self, phi_str, _):
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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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stl_eval2 = stl.robustness.pointwise_robustness(phi)
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r = stl_eval2(x, 0)
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assert (r == 0 or ((r > 0) == stl_eval(x, 0)))
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@params(ex1, ex2, ex3, ex4, ex5, ex6)
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def test_robustness_value(self, phi_str, r):
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phi = stl.parse(phi_str)
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phi = stl.parse(phi_str)
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stl_eval = stl.robustness.pointwise_robustness(phi)
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stl_eval = stl.robustness.pointwise_robustness(phi)
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self.assertEqual(stl_eval(x, 0), r)
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self.assertEqual(stl_eval(x, 0), r)
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@params(ex1, ex2, ex3, ex4, ex5, ex6)
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def test_eps_robustness(self, phi_str, r):
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phi = stl.parse(phi_str)
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r = stl.robustness.pointwise_robustness(phi)(x, 0)
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lo, hi = stl.smooth_robustness.smooth_robustness(phi, L=1, eps=0.1)
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# hi - lo <= eps
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# lo <= r <= hi
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raise NotImplementedError
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@params(ex1, ex2, ex3, ex4, ex5, ex6)
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def test_interval_polarity(self, phi_str, r):
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phi = stl.parse(phi_str)
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lo, hi = stl.smooth_robustness.smooth_robustness(phi, L=1, eps=0.1)
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# hi - lo > 0
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raise NotImplementedError
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@ -66,7 +66,7 @@ def terms_lens(phi:"STL", bind=True) -> lens:
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def param_lens(phi):
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def param_lens(phi):
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is_sym = lambda x: isinstance(x, sympy.Symbol)
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is_sym = lambda x: isinstance(x, sympy.Symbol)
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def focus_lens(leaf):
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def focus_lens(leaf):
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return [lens().const, lens().id] if isinstance(leaf, LinEq) else [lens().interval[0], lens().interval[1]]
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return [lens().const] if isinstance(leaf, LinEq) else [lens().interval[0], lens().interval[1]]
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return ast_lens(phi, pred=type_pred(LinEq, F, G),
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return ast_lens(phi, pred=type_pred(LinEq, F, G),
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focus_lens=focus_lens).filter_(is_sym)
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focus_lens=focus_lens).filter_(is_sym)
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