def f_suppression_studyLate(pi):
finalStructures = pi.evaluate()
finalStates = StatePointOperations.flattenStatePoint(finalStructures)
#print (finalStates)
#get all realised epis with 'el' name
statesForCaseEL = StatePointOperations.extractBasePointsFromFlattenedStatePoint(
finalStates, name="el")
#get all realised epis with 'elo' name
statesForCaseELO = StatePointOperations.extractBasePointsFromFlattenedStatePoint(
finalStates, name="elo")
# find the set of responses that that the realised SCPs of 'el' could reach
responsesEL = f_studyLateSingle(statesForCaseEL)
# find the set of responses that that the realised SCPs of 'elo' could reach
responsesELO = f_studyLateSingle(statesForCaseELO)
#suppression has occured if there is a response in responsesEL which is NOT
# in responsesELO
"""
for r1 in responsesEL:
if r1 not in responsesELO:
print ("The response '{}' occurs for 'el', but not for 'elo'".format(r1))
return "Suppression observed"
return "Suppression not observed"
"""
return {'el': responsesEL, 'elo': responsesELO}
def getTh(epi):
tempCTM = CTM.CTM()
tempCTM.si = [epi]
tempCTM.appendm(m_th_simplified(target='W'))
#guaranteed to be monotonic
epi = StatePointOperations.flattenStatePoint(tempCTM.evaluate())[0]
# 2) generateProcesses
return epi
def getSiStructure(self):
structure = []
flattenedSi = StatePointOperations.flattenStatePoint(self.si)
if not isinstance(flattenedSi, list):
flattenedSi = [flattenedSi]
#print ("FLATTENED si IS ", flattenedSi)
for epi in flattenedSi:
structure = structure + epi.getStructuralVariables()
return list(dict.fromkeys(structure))
def f_turn(pi, observation):
finalStructures = pi.evaluate()
finalStates = StatePointOperations.flattenStatePoint(finalStructures)
if not isinstance(finalStates, list):
finalStates = [finalStates]
conditional = scpNotationParser.stringListToBasicLogic(
["( ( 3 | D ) or ( D' | 7 ) )"])
# we are willing to turn the card if either the (3 | D) or the contrapositive case ( D' | 7 ) holds
obs = scpNotationParser.stringListToBasicLogic(
['( {} <- T )'.format(observation)])
responses = []
for epi in finalStates:
#print ("\n")
#print (epi)
basicLogic.setkbfromv(obs, epi['V'])
#the conditional must be verified or falsified
#the observation must be True
allObsTrue = True
for o in obs:
if o.evaluate() != True:
allObsTrue = False
#allCondApplicable = True
if allObsTrue:
responses.append('observations hold')
else:
responses.append('observations do not')
#now we need to find the minimal set of abducibles to turn the cards
turnResponses = []
#WE PREFER MINIMAL EXPLANATIONS
for i in range(0, len(responses)):
if responses[i] == 'observations hold':
turnResponses.append(finalStates[i])
minimalSubset = []
for epi in turnResponses:
#print ("epi is ", epi)
#print (epi['R']['abducibles'])
#print ("and then here")
x = [
StatePointOperations.properSubset(ot['R']['abducibles'],
epi['R']['abducibles'])
for ot in turnResponses
]
#another least model is a subset of this one
if True in x:
pass
else:
minimalSubsetAsVariables = epi['V']
minimalSubsetAsList = StatePointOperations.VtoTupleList(
minimalSubsetAsVariables, ignoreNone=True)
if minimalSubsetAsList not in minimalSubset:
minimalSubset.append(minimalSubsetAsVariables)
turns = []
for mini in minimalSubset:
allCondApplicable = True
#this is done later
basicLogic.setkbfromv(conditional, mini)
#print ("mini is : ", mini)
for cond in conditional:
#print (cond, "Evaluates to ", cond.evaluate())
if cond.evaluate() == None:
#print ("evaluation was ", cond.evaluate())
allCondApplicable = False
#print ("cond is ",cond)
if allCondApplicable:
turns.append('Turn Card')
#print ("1")
else:
turns.append('Do Not Turn')
#print("2")
return turns