From 765323c3cd539ab1ec7aacdcbd4d7279445273af Mon Sep 17 00:00:00 2001
From: lsaldyt <lsaldyt@localhost.localdomain>
Date: Mon, 16 Oct 2017 13:21:19 -0700
Subject: [PATCH] Updates adjustment formula to a satisfactory formula

Out of all of the formulas I've tried, I believe this formula to be a more elegant alternative to Mitchell's formula.
However, like Mitchell's original formula, it still provides weird answers in some cases, but I believe these to source from elsewhere,
not from the adjustment formula.

For more information, please see:

https://docs.google.com/spreadsheets/d/1JT2yCBUAsFzMcbKsQUcH1DhcBbuWDKTgPvUwD9EqyTY/edit?usp=sharing
wq
---
 copycat/copycat.py     | 3 ++-
 copycat/temperature.py | 9 ++++++++-
 2 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/copycat/copycat.py b/copycat/copycat.py
index 1f16cd9..e66a738 100644
--- a/copycat/copycat.py
+++ b/copycat/copycat.py
@@ -68,7 +68,7 @@ class Copycat(object):
     def run(self, initial, modified, target, iterations):
         self.workspace.resetWithStrings(initial, modified, target)
 
-        self.temperature.useAdj('original')
+        #self.temperature.useAdj('original')
         #self.temperature.useAdj('entropy')
         #self.temperature.useAdj('inverse') # 100 weight
         #self.temperature.useAdj('fifty_converge') 
@@ -76,6 +76,7 @@ class Copycat(object):
         #self.temperature.useAdj('weighted_soft') 
         #self.temperature.useAdj('alt_fifty')
         #self.temperature.useAdj('average_alt')
+        self.temperature.useAdj('best')
 
         answers = {}
         for i in range(iterations):
diff --git a/copycat/temperature.py b/copycat/temperature.py
index 20aca17..e62f0a8 100644
--- a/copycat/temperature.py
+++ b/copycat/temperature.py
@@ -56,6 +56,12 @@ def _averaged_alt(temp, prob):
     u = prob ** 2 if prob < .5 else math.sqrt(prob)
     return _weighted(temp, prob, s, u)
 
+def _working_best(temp, prob):
+    s = .5   # convergence
+    r = 1.05 # power
+    u = prob ** r if prob < .5 else prob ** (1/r)
+    return _weighted(temp, prob, s, u)
+
 class Temperature(object):
     def __init__(self):
         self.reset()
@@ -68,7 +74,8 @@ class Temperature(object):
                 'soft'           : _soft_curve,
                 'weighted_soft'  : _weighted_soft_curve,
                 'alt_fifty'      : _alt_fifty,
-                'average_alt'    : _averaged_alt}
+                'average_alt'    : _averaged_alt,
+                'best'           : _working_best}
 
     def reset(self):
         self.actual_value = 100.0