fix bug in robustness calculation + move synth for it's on module

robustness.py

@@ -4,7 +4,6 @@ from operator import sub, add
 from lenses import lens
 
 import stl.ast
-from stl.utils import set_params, param_lens
 
 oo = float('inf')
 
@@ -45,8 +44,8 @@ def _(stl):
 op_lookup = {
     ">": sub,
     ">=": sub,
-    "<": add,
+    "<": lambda x, y: sub(y, x),
-    "<=": add,
+    "<=": lambda x, y: sub(y, x),
     "=": lambda a, b: -abs(a - b),
 }
 
@@ -64,45 +63,3 @@ def eval_terms(lineq, x, t):
 
 def eval_term(x, t):
     return lambda term: term.coeff*x[term.id.name][t]
-
-
-def binsearch(stleval, *, tol=1e-3, lo, hi, polarity):
-    """Only run search if tightest robustness was positive."""
-    # Only check low since hi taken care of by precondition.
-    # TODO: allow for different polarities
-    rL, rH = stleval(lo), stleval(hi)
-    # Early termination via bounds checks
-    posL, posH = rL > 0, rH > 0
-    if polarity and posL:
-        return lo
-    elif not polarity and posH:
-        return hi
-
-    while hi - lo > tol:
-        mid = lo + (hi - lo) / 2
-        r = stleval(mid)
-        if not polarity: # swap direction
-            r *= -1
-        if r < 0:
-            lo, hi = mid, hi
-        else:
-            lo, hi = lo, mid
-    
-    # Want satisifiable formula
-    return hi if polarity else lo
-
-
-def lex_param_project(stl, x, *, order, polarity, ranges, tol=1e-3):
-    val = {var: (ranges[var][0] if not polarity[var] else ranges[var][1]) for var in order}
-    p_lens = param_lens(stl)
-    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:
-        stleval = stleval_fact(var, val)
-        lo, hi = ranges[var]
-        param = binsearch(stleval, lo=lo, hi=hi, tol=tol, polarity=polarity[var])
-        val[var] = param
-
-    return val

synth.py

@@ -0,0 +1,45 @@
+from stl.utils import set_params, param_lens
+from stl.robustness import pointwise_robustness
+
+from lenses import lens
+
+def binsearch(stleval, *, tol=1e-3, lo, hi, polarity):
+    """Only run search if tightest robustness was positive."""
+    # Only check low since hi taken care of by precondition.
+    # TODO: allow for different polarities
+    rL, rH = stleval(lo), stleval(hi)
+    # Early termination via bounds checks
+    posL, posH = rL > 0, rH > 0
+    if polarity and posL:
+        return lo
+    elif not polarity and posH:
+        return hi
+
+    while hi - lo > tol:
+        mid = lo + (hi - lo) / 2
+        r = stleval(mid)
+        if not polarity: # swap direction
+            r *= -1
+        if r < 0:
+            lo, hi = mid, hi
+        else:
+            lo, hi = lo, mid
+    
+    # Want satisifiable formula
+    return hi if polarity else lo
+
+
+def lex_param_project(stl, x, *, order, polarity, ranges, tol=1e-3):
+    val = {var: (ranges[var][0] if not polarity[var] else ranges[var][1]) for var in order}
+    p_lens = param_lens(stl)
+    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:
+        stleval = stleval_fact(var, val)
+        lo, hi = ranges[var]
+        param = binsearch(stleval, lo=lo, hi=hi, tol=tol, polarity=polarity[var])
+        val[var] = param
+
+    return val

test_robustness.py

@@ -11,13 +11,15 @@ ex1 = ("2*A > 3", -1)
 ex2 = ("F[0, 1](2*A > 3)", 5)
 ex3 = ("F[1, 0](2*A > 3)", -oo)
 ex4 = ("G[1, 0](2*A > 3)", oo)
+ex5 = ("(A < 0)", -1)
+ex6 = ("G[0, 0.1](A < 0)", -1)
 x = pd.DataFrame([[1,2], [1,4], [4,2]], index=[0,0.1,0.2], 
                  columns=["A", "B"])
 
 
 
 class TestSTLRobustness(unittest.TestCase):
-    @params(ex1, ex2, ex3, ex4)
+    @params(ex1, ex2, ex3, ex4, ex5, ex6)
     def test_stl(self, phi_str, r):
         phi = stl.parse(phi_str)
         stl_eval = stl.robustness.pointwise_robustness(phi)

test_synth.py

@@ -1,5 +1,6 @@
 import stl
 import stl.robustness
+import stl.synth
 import pandas as pd
 from nose2.tools import params
 import unittest
@@ -13,9 +14,10 @@ ex2 = ("F[0, b?](A > a?)", ("a?", "b?"), {"a?": (0, 10), "b?": (0, 5)},
 ex3 = ("F[0, b?](A < 0)", ("b?",), {"b?": (0, 5)},
        {"b?": True}, {"b?": 5})
 ex4 = ("G[0, b?](A < 0)", ("b?",), {"b?": (0.1, 5)},
-       {"b?": True}, {"b?": 0.1})
+       {"b?": False}, {"b?": 0.1})
 ex5 = ("F[0, b?](A > 0)", ("b?",), {"b?": (0.1, 5)},
        {"b?": True}, {"b?": 0.1})
+
 x = pd.DataFrame([[1,2], [1,4], [4,2]], index=[0,0.1,0.2], 
                  columns=["A", "B"])
 
@@ -24,14 +26,14 @@ class TestSTLRobustness(unittest.TestCase):
     @params(ex1, ex2, ex3, ex4, ex5)
     def test_lex_synth(self, phi_str, order, ranges, polarity, val):
         phi = stl.parse(phi_str)
-        val2 = stl.robustness.lex_param_project(
+        val2 = stl.synth.lex_param_project(
             phi, x, order=order, ranges=ranges, polarity=polarity)
 
-        phi = stl.robustness.set_params(phi, val2)
+        phi2 = stl.utils.set_params(phi, val2)
-        phi2 = stl.robustness.set_params(phi, val)
+        phi3 = stl.utils.set_params(phi, val)
 
-        stl_eval = stl.robustness.pointwise_robustness(phi)
+        stl_eval = stl.robustness.pointwise_robustness(phi2)
-        stl_eval2 = stl.robustness.pointwise_robustness(phi2)
+        stl_eval2 = stl.robustness.pointwise_robustness(phi3)
 
         # check that the robustnesses are almost the same
         self.assertAlmostEqual(stl_eval(x, 0), stl_eval2(x, 0), delta=0.01)