alex/copycat
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Major overhaul of temperature logic. Behavioral change.

Browse Source 
I think the reason the temperature logic was so confused in the old code
is because the Java code has a class `Temperature` that is used for
graphical display *and* two variables in `formulas` that are used for
most of the actual math. But somewhere along the line, some of the code
in `formulas.java` started reading from `Temperature.value` as well.
So the Python code was just faithfully copying that confusion.

The actual abstraction here is a very simple "temperature" object
with a stored value. It can be "clamped" to 100.0 for a given period.
The only complication is that one of the codelets (the rule-transformer
codelet) wants to get access to the "actual value" of the temperature
even when it is clamped.

The Python rule-transformer codelet also had a bug: it was accidentally
setting `temperature.value` on the `temperature` module instead of on
the `temperature.temperature` object! This turned some of its behavior
into a no-op, for whatever that's worth.

Lastly, the calculation of `finalTemperature` in the main program can
now report 100.0 if the answer is found while the temperature is clamped.
I don't fully understand why this didn't happen in the old code.
I've hacked around it with `temperature.last_unclamped_value` for now,
but I should TODO FIXME.
This commit is contained in:
Arthur O'Dwyer
2017-04-17 01:29:16 -07:00
parent 6a56fdd898
commit cc288161a4
7 changed files with 34 additions and 40 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
copycat/formulas.py
View File

@ -4,8 +4,6 @@ import random
from temperature import temperature
actualTemperature = Temperature = 100.0
def selectListPosition(probabilities):
total = sum(probabilities)
@ -35,23 +33,18 @@ def weightedAverage(values):
def temperatureAdjustedValue(value):
#logging.info('Temperature: %s' % Temperature)
#logging.info('actualTemperature: %s' % actualTemperature)
return value ** (((100.0 - Temperature) / 30.0) + 0.5)
return value ** (((100.0 - temperature.value()) / 30.0) + 0.5)
def temperatureAdjustedProbability(value):
if not value or value == 0.5 or not temperature.value:
if value == 0 or value == 0.5 or temperature.value() == 0:
return value
if value < 0.5:
return 1.0 - temperatureAdjustedProbability(1.0 - value)
coldness = 100.0 - temperature.value
coldness = 100.0 - temperature.value()
a = math.sqrt(coldness)
b = 10.0 - a
c = b / 100
d = c * (1.0 - (1.0 - value)) # as said the java
e = (1.0 - value) + d
f = 1.0 - e
c = (10 - a) / 100
f = (c + 1) * value
return max(f, 0.5)