Experiments to refer to Lucas

copycat/temperature.py

@@ -33,6 +33,7 @@ class Temperature(object):
     def getAdjustedValue(self, value):
         return value ** (((100.0 - self.value()) / 30.0) + 0.5)
 
+    """
     def getAdjustedProbability(self, value):
         if value == 0 or value == 0.5 or self.value() == 0:
             return value
@@ -43,3 +44,84 @@ class Temperature(object):
         c = (10 - a) / 100
         f = (c + 1) * value
         return max(f, 0.5)
+    """
+
+    def getAdjustedProbability(self, value):
+        """
+        This function returns the probability for a decision.
+        Copied above.
+
+        Please look at the last line of it.  Strangely, it was
+        return max(f, 0.5).  Does that make sense? Let's compare
+        some results.  Where it was (0.5), we obtained, for example:
+
+        iiijjjlll: 670 (avg time 1108.5, avg temp 23.6)
+        iiijjjd: 2 (avg time 1156.0, avg temp 35.0)
+        iiijjjkkl: 315 (avg time 1194.4, avg temp 35.5)
+        iiijjjkll: 8 (avg time 2096.8, avg temp 44.1)
+        iiijjjkkd: 5 (avg time 837.2, avg temp 48.0)
+
+        wyz: 5 (avg time 2275.2, avg temp 14.9)
+        xyd: 982 (avg time 2794.4, avg temp 17.5)
+        yyz: 7 (avg time 2731.9, avg temp 25.1)
+        dyz: 2 (avg time 3320.0, avg temp 27.1)
+        xyy: 2 (avg time 4084.5, avg temp 31.1)
+        xyz: 2 (avg time 1873.5, avg temp 52.1)
+
+        Now, let's see what return max(f, 0.0000) does:
+
+        wyz: 7 (avg time 3192.9, avg temp 13.1)
+        xyd: 985 (avg time 2849.1, avg temp 17.5)
+        yyz: 6 (avg time 3836.7, avg temp 18.6)
+        xyy: 1 (avg time 1421.0, avg temp 19.5)
+        xyz: 1 (avg time 7350.0, avg temp 48.3)
+
+        They *seem* better (in the strict sense that we've obtained both
+        lower T and more times of wyz.)  But they're *not* statistically
+        significant (for 1000 runs).
+
+        Now... looking at the code... it seems to be a mess... what does
+        function f() even mean in intuitive terms?
+
+        Work it does, but dude... quite a hack.
+
+        Another run, with return f @line89:
+
+        wyz: 8 (avg time 4140.5, avg temp 13.3)
+        yyz: 6 (avg time 2905.2, avg temp 14.5)
+        xyd: 982 (avg time 3025.4, avg temp 17.6)
+        dyz: 4 (avg time 4265.0, avg temp 17.7)
+
+        Does it even matter? Another (quick) run, I think with return (0.5):
+
+        dyz: 1 (avg time 5198.0, avg temp 15.3)
+        wyz: 3 (avg time 4043.7, avg temp 17.1)
+        yyz: 9 (avg time 3373.6, avg temp 21.0)
+        xyd: 84 (avg time 5011.1, avg temp 23.3)
+        xyy: 3 (avg time 4752.0, avg temp 27.9)
+
+        Compared to return(0.99):
+
+        xyd: 1000 (avg time 1625.2, avg temp 17.3)
+
+        Comparing to return f --> Statistically significant.
+        Comparing to return(0.5) --> same, so this return value does something.
+
+        Now running return(0.0):
+
+        xyz: 3 (avg time 3996.7, avg temp 81.1)
+        dyz: 46 (avg time 5931.7, avg temp 82.6)
+        xd: 17 (avg time 6090.3, avg temp 83.8)
+        xyd: 934 (avg time 7699.8, avg temp 88.1)
+
+        It's bad overall, but at least it's statistically significant!
+        """
+        if value == 0 or value == 0.5 or self.value() == 0:
+            return value
+        if value < 0.5:
+            return 1.0 - self.getAdjustedProbability(1.0 - value)
+        coldness = 100.0 - self.value()
+        a = math.sqrt(coldness)
+        c = (10 - a) / 100
+        f = (c + 1) * value
+        return (0.0)  # f  # max(f, 0.0000)

main.py

@@ -9,10 +9,10 @@ To run it, type at the terminal:
 The script takes three to five arguments. The first two are a pair of strings
 with some change, for example "abc" and "abd". The third is a string which the
 script should try to change analogously. The fourth (which defaults to "1") is
-a number of iterations. One can also specify a defined seed falue for the
+a number of iterations. One can also specify a defined seed value for the
 random number generator.
 
-The above might produce output such as these runs:
+This instruction produces output such as:
 
     iiijjjlll: 670 (avg time 1108.5, avg temp 23.6)
     iiijjjd: 2 (avg time 1156.0, avg temp 35.0)