Removes alpha/beta from weighted formula

papers/formulas/weighted.py

@@ -1,5 +1,5 @@
-def _weighted(temp, prob, s, u, alpha=1, beta=1):
-    weighted = (temp / 100) * s + ((100 - temp) / 100) * u 
+def _weighted(temp, prob, s, u):
+    weighted = (temp / 100) * s + ((100 - temp) / 100) * u
     return weighted
 
 def _weighted_inverse(temp, prob):
@@ -7,7 +7,7 @@ def _weighted_inverse(temp, prob):
     return _weighted(temp, prob, iprob, prob)
 
 # Uses .5 instead of 1-prob
-def _fifty_converge(temp, prob): 
+def _fifty_converge(temp, prob):
     return _weighted(temp, prob, .5, prob)
 
 # Curves to the average of the (1-p) and .5
@@ -15,14 +15,14 @@ def _soft_curve(temp, prob):
     return min(1, _weighted(temp, prob, (1.5-prob)/2, prob))
 
 # Curves to the weighted average of the (1-p) and .5
-def _weighted_soft_curve(temp, prob): 
+def _weighted_soft_curve(temp, prob):
     weight = 100
     gamma  = .5  # convergance value
     alpha  = 1   # gamma weight
     beta   = 3   # iprob weight
-    curved = min(1, 
-                 (temp / weight) * 
-                     ((alpha * gamma + beta * (1 - prob)) / 
-                         (alpha + beta)) + 
+    curved = min(1,
+                 (temp / weight) *
+                     ((alpha * gamma + beta * (1 - prob)) /
+                         (alpha + beta)) +
                  ((weight - temp) / weight) * prob)
     return curved