From 28f755edc503f2715ceffc80a9adf4be3962b2f1 Mon Sep 17 00:00:00 2001 From: Marcell Vazquez-Chanlatte Date: Sun, 9 Oct 2016 21:55:48 -0700 Subject: [PATCH] adding tests for lexicographic parameteric synth --- robustness.py | 3 --- test_synth.py | 30 ++++++++++++++++++++++++++++++ 2 files changed, 30 insertions(+), 3 deletions(-) create mode 100644 test_synth.py diff --git a/robustness.py b/robustness.py index e875ffb..09ddda2 100644 --- a/robustness.py +++ b/robustness.py @@ -79,7 +79,6 @@ def binsearch(stleval, *, tol=1e-3, lo, hi, polarity): while abs(r) > tol and hi - lo > tol: mid = lo + (hi - lo) / 2 r = stleval(mid) - print(lo, mid, hi, r) if polarity: # swap direction r *= -1 if r < 0: @@ -97,10 +96,8 @@ def lex_param_project(stl, x, *, order, polarity, ranges, tol=1e-3): def stleval_fact(var, val): l = lens(val)[var] return lambda p: pointwise_robustness(set_params(stl, l.set(p)))(x, 0) - for var in order: - print(val) stleval = stleval_fact(var, val) lo, hi = ranges[var] _, param = binsearch(stleval, lo=lo, hi=hi, tol=tol, polarity=polarity[var]) diff --git a/test_synth.py b/test_synth.py new file mode 100644 index 0000000..a5a7f80 --- /dev/null +++ b/test_synth.py @@ -0,0 +1,30 @@ +import stl +import stl.robustness +import pandas as pd +from nose2.tools import params +import unittest +from sympy import Symbol + +oo = float('inf') + +ex1 = ("A > a?", ("a?",), {"a?": (0, 10)}, {"a?": True}, {"a?": 1}) +ex1 = ("F[0, b?](A > a?)", ("a?", "b?"), {"a?": (0, 10), "b?": (0, 10)}, + {"a?": True, "b?": False}, {"a?": 4, "b?": 0.2}) +x = pd.DataFrame([[1,2], [1,4], [4,2]], index=[0,0.1,0.2], + columns=["A", "B"]) + + +class TestSTLRobustness(unittest.TestCase): + @params(ex1) + def test_lex_synth(self, phi_str, order, ranges, polarity, val): + phi = stl.parse(phi_str) + val2 = stl.robustness.lex_param_project( + phi, x, order=order, ranges=ranges, polarity=polarity) + + phi = stl.robustness.set_params(phi, val) + stl_eval = stl.robustness.pointwise_robustness(phi) + self.assertAlmostEqual(stl_eval(x, 0), 0) + + for var in order: + self.assertAlmostEqual(val2[var], val[var], delta=0.01) +