rules.scale added and tested.

Author: amogorkon

fuzzy/rules.py

@@ -1,3 +1,16 @@
 
-def scale(x, *, IN_min=0, IN_max=1, OUT_min, OUT_max):
-    return (OUT_max - OUT_min)*(x - IN_min) / (IN_max - IN_min) + OUT_min
+from math import isinf
+
+def scale(OUT_min, OUT_max, *, IN_min=0, IN_max=1):
+    """Scale from one domain to another.
+    
+    Works best for [0,1] -> R. For R -> R additional testing is required.
+    """
+    assert IN_min < IN_max
+    # this is not arbitrary. lim x -> inf x*0+x -> inf
+    if isinf(OUT_max - OUT_min):
+        return lambda x: OUT_max
+    
+    def f(x):
+        return (OUT_max - OUT_min)*(x - IN_min) / (IN_max - IN_min) + OUT_min
+    return f

test_fuzzy_units.py

@@ -4,10 +4,11 @@
 from unittest import TestCase, skip
 import numpy as np
 
-from fuzzy.classes import Domain, Set, Rule
+from fuzzy.classes import Domain, Set
 from fuzzy import functions as fun
 from fuzzy import hedges
 from fuzzy import combinators as combi
+import fuzzy.rules as ru
 
 class Test_Functions(TestCase):
     @given(st.floats(allow_nan=False))
@@ -343,4 +344,18 @@ def test_complement(self):
         D = Domain("d", 0, 10, res=0.1)
         D.s1 = Set(fun.bounded_linear(3, 12))
         D.s2 = ~~D.s1
-        assert all(np.isclose(D.s1.array(), D.s2.array()))
+        assert all(np.isclose(D.s1.array(), D.s2.array()))
+        
+
+class Test_Rules(TestCase):
+    @given(st.floats(min_value=0, max_value=1),
+           st.floats(min_value=0, max_value=1),
+           st.floats(min_value=0, max_value=1),
+           st.floats(allow_infinity=False, allow_nan=False),
+          st.floats(allow_infinity=False, allow_nan=False))
+    def test_scaling(self, x, IN_min, IN_max, OUT_min, OUT_max):
+        assume(IN_min < IN_max)
+        assume(IN_min <= x <= IN_max)
+        assume(OUT_min < OUT_max)
+        f = ru.scale(OUT_min, OUT_max, IN_min=IN_min, IN_max=IN_max) 
+        assert (OUT_min <= f(x) <= OUT_max)