def updateValue(self):
self.rawImportance = self.__calculateRawImportance()
intraStringHappiness = self.__calculateIntraStringHappiness()
self.intraStringUnhappiness = 100.0 - intraStringHappiness
interStringHappiness = 0.0
if self.correspondence:
interStringHappiness = self.correspondence.totalStrength
self.interStringUnhappiness = 100.0 - interStringHappiness
averageHappiness = (intraStringHappiness + interStringHappiness) / 2
self.totalUnhappiness = 100.0 - averageHappiness
if self.clampSalience:
self.intraStringSalience = 100.0
self.interStringSalience = 100.0
else:
from formulas import weightedAverage
self.intraStringSalience = weightedAverage(
((self.relativeImportance, 0.2), (self.intraStringUnhappiness,
0.8)))
self.interStringSalience = weightedAverage(
((self.relativeImportance, 0.8), (self.interStringUnhappiness,
0.2)))
self.totalSalience = (self.intraStringSalience +
self.interStringSalience) / 2.0
logging.info('Set salience of %s to %f = (%f + %f)/2', self.__str__(),
self.totalSalience, self.intraStringSalience,
self.interStringSalience)
def updateValue(self):
self.rawImportance = self.__calculateRawImportance()
intraStringHappiness = self.__calculateIntraStringHappiness()
self.intraStringUnhappiness = 100.0 - intraStringHappiness
interStringHappiness = 0.0
if self.correspondence:
interStringHappiness = self.correspondence.totalStrength
self.interStringUnhappiness = 100.0 - interStringHappiness
averageHappiness = (intraStringHappiness + interStringHappiness) / 2
self.totalUnhappiness = 100.0 - averageHappiness
if self.clampSalience:
self.intraStringSalience = 100.0
self.interStringSalience = 100.0
else:
from formulas import weightedAverage
self.intraStringSalience = weightedAverage((
(self.relativeImportance, 0.2),
(self.intraStringUnhappiness, 0.8)))
self.interStringSalience = weightedAverage((
(self.relativeImportance, 0.8),
(self.interStringUnhappiness, 0.2)))
self.totalSalience = (self.intraStringSalience +
self.interStringSalience) / 2.0
logging.info('Set salience of %s to %f = (%f + %f)/2',
self.__str__(), self.totalSalience,
self.intraStringSalience, self.interStringSalience)
def updateInternalStrength(self):
if not (self.descriptor and self.relation):
self.internalStrength = 0.0
return
averageDepth = (self.descriptor.conceptualDepth +
self.relation.conceptualDepth) / 2.0
averageDepth **= 1.1
# see if the object corresponds to an object
# if so, see if the descriptor is present (modulo slippages) in the
# corresponding object
changedObjects = [o for o in workspace.initial.objects if o.changed]
changed = changedObjects[0]
sharedDescriptorTerm = 0.0
if changed and changed.correspondence:
targetObject = changed.correspondence.objectFromTarget
slippages = workspace.slippages()
slipnode = self.descriptor.applySlippages(slippages)
if not targetObject.described(slipnode):
self.internalStrength = 0.0
return
sharedDescriptorTerm = 100.0
conceptual_height = (100.0 - self.descriptor.conceptualDepth) / 10.0
sharedDescriptorWeight = conceptual_height ** 1.4
depthDifference = 100.0 - abs(self.descriptor.conceptualDepth -
self.relation.conceptualDepth)
weights = ((depthDifference, 12),
(averageDepth, 18),
(sharedDescriptorTerm, sharedDescriptorWeight))
self.internalStrength = weightedAverage(weights)
if self.internalStrength > 100.0:
self.internalStrength = 100.0
def updateInternalStrength(self):
if not (self.descriptor and self.relation):
self.internalStrength = 0.0
return
averageDepth = (self.descriptor.conceptualDepth +
self.relation.conceptualDepth) / 2.0
averageDepth **= 1.1
# see if the object corresponds to an object
# if so, see if the descriptor is present (modulo slippages) in the
# corresponding object
changedObjects = [o for o in workspace.initial.objects if o.changed]
changed = changedObjects[0]
sharedDescriptorTerm = 0.0
if changed and changed.correspondence:
targetObject = changed.correspondence.objectFromTarget
slippages = workspace.slippages()
slipnode = self.descriptor.applySlippages(slippages)
if not targetObject.described(slipnode):
self.internalStrength = 0.0
return
sharedDescriptorTerm = 100.0
conceptual_height = (100.0 - self.descriptor.conceptualDepth) / 10.0
sharedDescriptorWeight = conceptual_height**1.4
depthDifference = 100.0 - abs(self.descriptor.conceptualDepth -
self.relation.conceptualDepth)
weights = ((depthDifference, 12), (averageDepth, 18),
(sharedDescriptorTerm, sharedDescriptorWeight))
self.internalStrength = weightedAverage(weights)
if self.internalStrength > 100.0:
self.internalStrength = 100.0
def updateInternalStrength(self):
relatedBondAssociation = self.groupCategory.getRelatedNode(slipnet.bondCategory).degreeOfAssociation()
bondWeight = relatedBondAssociation ** 0.98
length = len(self.objectList)
if length == 1:
lengthFactor = 5.0
elif length == 2:
lengthFactor = 20.0
elif length == 3:
lengthFactor = 60.0
else:
lengthFactor = 90.0
lengthWeight = 100.0 - bondWeight
weightList = ((relatedBondAssociation, bondWeight), (lengthFactor, lengthWeight))
self.internalStrength = formulas.weightedAverage(weightList)
def updateInternalStrength(self):
relatedBondAssociation = self.groupCategory.getRelatedNode(
slipnet.bondCategory).degreeOfAssociation()
bondWeight = relatedBondAssociation**0.98
length = len(self.objectList)
if length == 1:
lengthFactor = 5.0
elif length == 2:
lengthFactor = 20.0
elif length == 3:
lengthFactor = 60.0
else:
lengthFactor = 90.0
lengthWeight = 100.0 - bondWeight
weightList = ((relatedBondAssociation, bondWeight), (lengthFactor,
lengthWeight))
self.internalStrength = formulas.weightedAverage(weightList)
def updateTemperature(self):
logging.debug('updateTemperature')
workspace.assessTemperature()
ruleWeakness = 100.0
if workspace.rule:
workspace.rule.update_strength()
ruleWeakness = 100.0 - workspace.rule.total_strength
values = ((workspace.totalUnhappiness, 0.8), (ruleWeakness, 0.2))
slightly_above_actual_temperature = formulas.actualTemperature + 0.001
logging.info('actualTemperature: %f' % slightly_above_actual_temperature)
formulas.actualTemperature = formulas.weightedAverage(values)
logging.info('unhappiness: %f, weakness: %f, actualTemperature: %f' % (
workspace.totalUnhappiness + 0.001, ruleWeakness + 0.001, formulas.actualTemperature + 0.001))
if temperature.clamped:
formulas.actualTemperature = 100.0
logging.info('actualTemperature: %f' % (formulas.actualTemperature + 0.001))
temperature.update(formulas.actualTemperature)
if not self.clampTemperature:
formulas.Temperature = formulas.actualTemperature
temperature.update(formulas.Temperature)
def updateTemperature(self):
logging.debug('updateTemperature')
workspace.assessTemperature()
ruleWeakness = 100.0
if workspace.rule:
workspace.rule.updateStrength()
ruleWeakness = 100.0 - workspace.rule.totalStrength
values = ((workspace.totalUnhappiness, 0.8), (ruleWeakness, 0.2))
above_actual_temperature = formulas.actualTemperature + 0.001
logging.info('actualTemperature: %f', above_actual_temperature)
formulas.actualTemperature = formulas.weightedAverage(values)
logging.info('unhappiness: %f, weakness: %f, actualTemperature: %f',
workspace.totalUnhappiness + 0.001, ruleWeakness + 0.001,
formulas.actualTemperature + 0.001)
if temperature.clamped:
formulas.actualTemperature = 100.0
logging.info('actualTemperature: %f',
formulas.actualTemperature + 0.001)
temperature.update(formulas.actualTemperature)
if not self.clampTemperature:
formulas.Temperature = formulas.actualTemperature
temperature.update(formulas.Temperature)
def updateTotalStrength(self):
"""Recalculate the total strength based on internal and external strengths"""
weights = ((self.internalStrength, self.internalStrength),
(self.externalStrength, 100 - self.internalStrength))
strength = formulas.weightedAverage(weights)
self.totalStrength = strength
def updateTotalStrength(self):
"""Recalculate the total strength based on internal and external strengths"""
weights = ((self.internalStrength, self.internalStrength), (self.externalStrength, 100 - self.internalStrength))
strength = formulas.weightedAverage(weights)
self.totalStrength = strength
