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Adds notes to temperature.py

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LSaldyt
2017-09-29 13:47:03 -06:00
parent 60a5274066
commit 665bf1f778
3 changed files with 42 additions and 240 deletions
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61
copycat/temperature.py
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@ -212,6 +212,44 @@ class Temperature(object):
Need to play with this more... and WTF is f anyways?
LSaldyt:
Recall self.value():
def value(self):
return 100.0 if self.clamped else self.actual_value
f in terms of value() and value only
f = ((10 - sqrt(100 - self.value()))/100 + 1) * value
For the original LISP program:
; This function is a filter: it inputs a value (from 0 to 100) and returns
; a probability (from 0 - 1) based on that value and the temperature. When
; the temperature is 0, the result is (/ value 100), but at higher
; temperatures, values below 50 get raised and values above 50 get lowered
; as a function of temperature.
; I think this whole formula could probably be simplified.
(setq result
(cond ((= prob 0) 0)
((<= prob .5)
(setq low-prob-factor (max 1 (truncate (abs (log prob 10)))))
(min (+ prob
(* (/ (- 10 (sqrt (fake-reciprocal *temperature*)))
100)
(- (expt 10 (- (1- low-prob-factor))) prob)))
.5))
((= prob .5) .5)
((> prob .5)
(max (- 1
(+ (- 1 prob)
(* (/ (- 10 (sqrt (fake-reciprocal *temperature*)))
100)
(- 1 (- 1 prob)))))
.5))))
result)
"""
if value == 0 or value == 0.5 or self.value() == 0:
return value
@ -221,22 +259,7 @@ class Temperature(object):
a = math.sqrt(coldness)
c = (10 - a) / 100
f = (c + 1) * value
return (0 + (-f * math.log2(f))) # max(f, 0.0000)
def getAdjustedProbability(self, value):
# Recall self.value():
# def value(self):
# return 100.0 if self.clamped else self.actual_value
#
# f in terms of value() and value only
# f = ((10 - sqrt(100 - self.value()))/100 + 1) * value
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 max(f, 0.5)
# return max(f, 0.5)
# return max(f, 0.0)
# return (0 + (-f * math.log2(f)))
return -f * math.log2(f)