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Adds base temp formula

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LSaldyt
2017-09-29 17:55:24 -06:00
parent 6b1c4634fe
commit 430e2b3750
1 changed files with 76 additions and 5 deletions
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81
copycat/temperature.py
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@ -221,6 +221,10 @@ class Temperature(object):
f in terms of value() and value only
f = ((10 - sqrt(100 - self.value()))/100 + 1) * value
so, the function: (10 - sqrt(100 - temp)) / 100
produces a scalar from the current temperature,
ranging from 1.0 when the temp is 0 to 1.1 when the temp is 100.
This is used to scale probablities in their inverse directions
For the original LISP program:
; This function is a filter: it inputs a value (from 0 to 100) and returns
@ -277,23 +281,89 @@ class Temperature(object):
It looks like the function below preserves most of the functionality of the original lisp.
However, the comments themselves agree that the formula is overly complicated.
"""
prob = value # Slightly more descriptive (and less ambiguous), will change argument
# Temperature, potentially clamped
temp = self.value()
temp = self.value()
iprob = 1 - prob
# This function does precisely what I think the original lisp comment describes, but provides crappy results
# return (temp / 200) * iprob + ((200 - temp) / 200) * prob
# However, this version preforms much better:
# Some statistical analysis is needed of course
return (temp / 100) * iprob + ((100 - temp) / 100) * prob
'''
lucas@infinity:~/projects/personal/copycat$ ./main.py abc abd xyz --iterations 10 --plot
Answered wyz (time 3865, final temperature 13.9)
Answered wyz (time 8462, final temperature 10.8)
Answered wyz (time 6062, final temperature 11.7)
Answered yyz (time 4022, final temperature 15.6)
Answered yyz (time 2349, final temperature 59.8)
Answered xyd (time 17977, final temperature 14.9)
Answered xyd (time 1550, final temperature 14.7)
Answered xyd (time 11755, final temperature 16.8)
Answered wyz (time 2251, final temperature 13.7)
Answered yyz (time 13007, final temperature 11.7)
wyz: 4 (avg time 5160.0, avg temp 12.5)
xyd: 3 (avg time 10427.3, avg temp 15.5)
yyz: 3 (avg time 6459.3, avg temp 29.0)
However, it generally does worse on abc:abd::ijjkk:_
lucas@infinity:~/projects/personal/copycat$ ./main.py abc abd ijjkkk --iterations 10 --plot
Answered ijjlll (time 7127, final temperature 17.6)
Answered ijjlll (time 968, final temperature 17.5)
Answered ijjkkl (time 1471, final temperature 19.8)
Answered ijjlll (time 1058, final temperature 13.2)
Answered ijjkkl (time 489, final temperature 83.9)
Answered ijjkkl (time 1576, final temperature 18.7)
Answered ijjkkl (time 1143, final temperature 65.2)
Answered ijjkkl (time 3067, final temperature 19.6)
Answered ijjkkl (time 1973, final temperature 40.4)
Answered ijjkkl (time 1064, final temperature 50.6)
ijjlll: 3 (avg time 3051.0, avg temp 16.1)
ijjkkl: 7 (avg time 1540.4, avg temp 42.6)
'''
# unparameterized version
#curvedProb = (temp / 100) * iprob + (cold / 100) * prob
#if prob < .5:
# # Curving small (<.5) probabilities to .5, but not over
# return max(curvedProb, .5)
#else:
# # Curving large (>.5) probabilities to .5, but not under
# return min(curvedProb, .5)
# parameterized version : weights towards or away from probabilities
# alpha = 1.0
# beta = 1.0
# return ((alpha + temp / 100) * iprob + (beta + cold / 100) * prob) / (alpha + beta)
'''
# A scaling factor (between 0 and infinity), based on temperature (i.e. 100/coldness)
if temp == 100: # Avoid dividing by zero
factor = float('inf')
else:
factor = 100 / (100 - temp)
# My factor:
# factor = 100 / (100 - temp)
# SQRT:
# factor = math.sqrt(100 / (100 - temp))
# Original factor:
# factor = (110 - math.sqrt(100 - temp)) / 100
# Factor ^ 10:
# factor = ((110 - math.sqrt(100 - temp)) / 100) ** 10.
# Factor ^ 20
# factor = ((110 - math.sqrt(100 - temp)) / 100) ** 20.
# No factor:
# factor = 1
if prob == .5:
return .5
elif prob > .5:
prob = prob / factor
elif prob < .5:
prob = prob * factor
return max(min(prob, 0), 1) # Normalize between 0 and 1. TODO: make scaling factor more reasonable
"""
return min(max(prob, 0), 1) # Normalize between 0 and 1.
if value == 0 or value == 0.5 or self.value() == 0:
return value
@ -307,3 +377,4 @@ class Temperature(object):
# return max(f, 0.0)
# return (0 + (-f * math.log2(f)))
return -f * math.log2(f)
'''