adding tests for lexicographic parameteric synth

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:
@@ -98,9 +97,7 @@ def lex_param_project(stl, x, *, order, polarity, ranges, tol=1e-3):
         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])

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)
+