def assertComponentAddition(self, componentAdditionJSON, initiatingClauseHash=None):
if 'stem' in componentAdditionJSON['component_addition']['target']['component']['stem']:
stems = self.retrieveComponent(componentAdditionJSON['component_addition']['target']['component']['stem']['stem'], componentAdditionJSON['component_addition']['target']['component']['stem']['branch'], assertBranches=True, initiatingClauseHash=initiatingClauseHash)
if isinstance(stems, set):
stem = self.context.findLastReferenced(stems)
#raise Exception('assertComponentAssignment: Too many potential stems')
else:
stem = stems
elif 'concept' in componentAdditionJSON['component_addition']['target']['component']['stem']:
stem = self.assertConcept(componentAdditionJSON['component_addition']['target']['component']['stem'], initiatingClauseHash)
else:
raise Exception('assertComponentAddition: Unknown component structure')
branchPhrase = utilities.camelCase(componentAdditionJSON['component_addition']['target']['component']['branch'])
branches = self.retrieveComponent(componentAdditionJSON['component_addition']['target']['component']['stem'], componentAdditionJSON['component_addition']['target']['component']['branch'], assertBranches=True, initiatingClauseHash=initiatingClauseHash)
def checkIfNegativeAssignment(concept):
if re.match('^!', concept['concept']):
affirmativeConcept = concept['concept'][1:]
self.removeComponentAssignment(stem, branchPhrase, branches, affirmativeConcept, initiatingClauseHash)
return True
else:
return False
if isinstance(componentAdditionJSON['component_addition']['addition'], list):
componentAdditionJSON['component_addition']['addition'][:] = [x for x in componentAdditionJSON['component_addition']['addition'] if not checkIfNegativeAssignment(x)]
else:
if checkIfNegativeAssignment(componentAdditionJSON['component_addition']['addition']): return
unspecifiedBranches = []
if branches:
if isinstance(branches, set):
for branch in branches:
if branch.name == branchPhrase: unspecifiedBranches.append(branch)
else:
if branch.name == branchPhrase: unspecifiedBranches.append(branches)
assignments = list()
uninstantiatedAssignments = list()
if isinstance(componentAdditionJSON['component_addition']['addition'], list):
for concept in componentAdditionJSON['component_addition']['addition']:
x = self.context.queryNounPhrases(concept['concept'])
if x:
assignments.extend(x)
else:
uninstantiatedAssignments.append(concept['concept'])
else:
x = self.context.queryNounPhrases(componentAdditionJSON['component_addition']['addition']['concept'])
if x:
assignments.extend(x)
else:
uninstantiatedAssignments.append(componentAdditionJSON['component_addition']['addition']['concept'])
for uninstantiatedAssignment in uninstantiatedAssignments:
assignment = self.context.newNounPhrase(uninstantiatedAssignment, initiatingClauseHash)
#assignment.classify(utilities.sanitize(branchPhrase).split()[-1])
assignments.append(assignment)
for assignment in assignments:
if len(unspecifiedBranches) > 0:
unspecifiedBranch = unspecifiedBranches.pop()
unspecifiedBranch.name = 'unspecified' + unspecifiedBranch.name[0].upper() + unspecifiedBranch.name[1:]
self.context.mergeConcepts(assignment, unspecifiedBranch, initiatingClauseHash)
else:
self.context.setComponent(stem, branchPhrase, assignment, initiatingClauseHash)
def __init__(self, name=None, type=None, bootstrapVocabulary=None):
if name:
if getattr(self, "isQuantity", False):
self.name = str(name)
else:
self.name = utilities.camelCase(name)
else:
self.name = None
if type:
self.classify(utilities.sanitize(type))
if bootstrapVocabulary == True:
Concept.bootstrapVocabulary = True
Concept.wordnetClassifier = WordNetClassifier()
Concept.taxonomy.classifiers.append(Concept.wordnetClassifier)
elif bootstrapVocabulary == False:
Concept.bootstrapVocabulary = False
def synonyms(self, phrase=None):
if not phrase:
if not self.name:
return None
else:
phrase = self.name
phrase = utilities.camelCase(phrase)
listOfSetsWithPhrase = []
for key in self.thesaurus:
if phrase in self.thesaurus[key]:
if self.thesaurus[key] not in listOfSetsWithPhrase:
listOfSetsWithPhrase.append(self.thesaurus[key])
if len(listOfSetsWithPhrase) == 0:
self.thesaurus[phrase] = {phrase}
elif len(listOfSetsWithPhrase) > 1:
mergedSet = set.union(*listOfSetsWithPhrase)
for element in mergedSet:
self.thesaurus[element] = mergedSet
elif phrase not in self.thesaurus:
self.thesaurus[phrase] = listOfSetsWithPhrase[0]
return self.thesaurus[phrase]
def __init__(self, concept, context):
self.name = concept.name
self.hashcode = None
for hash in context.conceptHashTable:
if context.conceptHashTable[hash] is concept:
self.hashcode = hash
self.synonyms = concept.synonyms().copy()
self.parents = concept.parents()
self.ancestors = concept.ancestors()
self.descendants = concept.descendants()
if utilities.camelCase(concept.name) in self.synonyms: self.synonyms.remove(utilities.camelCase(concept.name))
self.states = list()
if concept in context.stateGraph:
descriptors = context.stateGraph.successors(concept)
for descriptor in descriptors:
self.states.append((descriptor.name, 100))
if concept in context.potentialActionGraph:
potentialDescriptorEdges = context.potentialStateGraph.out_edges(concept, data=True) if concept in context.potentialStateGraph else []
for potentialDescriptorEdge in potentialDescriptorEdges:
self.states.append((potentialDescriptorEdge[1].name, int(potentialDescriptorEdge[2]['weight'])))
def combineStates(stateTuples):
evidence = dict()
for stateTuple in stateTuples:
if not stateTuple[0] in evidence:
evidence[stateTuple[0]] = int(stateTuple[1])
else:
if evidence[stateTuple[0]] < 100:
evidence[stateTuple[0]] = evidence[stateTuple[0]] + int(stateTuple[1])
else:
evidence[stateTuple[0]] = 100
states = list()
for state in evidence:
states.append((state, evidence[state]))
return states
self.states = combineStates(self.states)
self.components = list()
if concept in context.componentGraph:
for componentEdge in context.componentGraph.out_edges(concept, data=True):
self.components.append((componentEdge[2]['label'], componentEdge[1].name, 100))
if concept in context.potentialComponentGraph:
potentialComponentEdges = context.potentialComponentGraph.out_edges(concept, data=True) if concept in context.potentialComponentGraph else []
for potentialComponentEdge in potentialComponentEdges:
self.components.append((potentialComponentEdge[2]['label'], potentialComponentEdge[1].name, potentialComponentEdge[2]['weight']))
def combineComponents(componentTuples):
evidence = dict()
for componentTuple in componentTuples:
if not componentTuple[0] in evidence:
evidence[componentTuple[0]] = dict()
if not componentTuple[1] in evidence[componentTuple[0]]:
evidence[componentTuple[0]][componentTuple[1]] = int(componentTuple[2])
else:
if evidence[componentTuple[0]][componentTuple[1]] < 100:
evidence[componentTuple[0]][componentTuple[1]] = evidence[componentTuple[0]][componentTuple[1]] + int(componentTuple[2])
else:
evidence[componentTuple[0]][componentTuple[1]] = 100
components = list()
for branchPhrase in evidence:
for component in evidence[branchPhrase]:
components.append((branchPhrase, component, evidence[branchPhrase][component]))
return components
self.components = combineComponents(self.components)
self.componentOf = list()
if concept in context.componentGraph:
for componentEdge in context.componentGraph.in_edges(concept, data=True):
self.componentOf.append((componentEdge[2]['label'], componentEdge[0].name, 100))
if concept in context.potentialComponentGraph:
potentialComponentOfEdges = context.potentialComponentGraph.in_edges(concept, data=True) if concept in context.potentialComponentGraph else []
for potentialComponentOfEdge in potentialComponentOfEdges:
self.componentOf.append((potentialComponentOfEdge[2]['label'], potentialComponentOfEdge[0].name, potentialComponentOfEdge[2]['weight']))
self.componentOf = combineComponents(self.componentOf)
self.actions = list()
if concept in context.actionGraph:
acts = set(context.actionGraph.neighbors(concept))
for actor_act in context.actionGraph.out_edges(concept):
for act_target in context.actionGraph.out_edges(actor_act[1]):
self.actions.append((act_target[0].name, act_target[1].name, 100))
acts.remove(act_target[0])
for act in acts:
self.actions.append((act.name, 'None', 100))
if concept in context.potentialActionGraph:
potentialActs = set(map(lambda x: x.name, context.potentialActionGraph.neighbors(concept)))
for potential_actor_act in context.potentialActionGraph.out_edges(concept):
for potential_act_target in context.potentialActionGraph.out_edges(potential_actor_act[1], data=True):
self.actions.append((potential_act_target[0].name, potential_act_target[1].name, potential_act_target[2]['weight']))
if potential_act_target[0].name in potentialActs:
potentialActs.remove(potential_act_target[0].name)
for potentialAct in potentialActs:
weight = context.potentialActionGraph.in_edges(potentialAct, data=True)[0][2]['weight']
self.actions.append((potentialAct.name, 'None', weight))
def combineActions(actionTuples):
evidence = dict()
for actionTuple in actionTuples:
if not actionTuple[0] in evidence:
evidence[actionTuple[0]] = dict()
if not actionTuple[1] in evidence[actionTuple[0]]:
evidence[actionTuple[0]][actionTuple[1]] = int(actionTuple[2])
else:
if evidence[actionTuple[0]][actionTuple[1]] < 100:
evidence[actionTuple[0]][actionTuple[1]] = evidence[actionTuple[0]][actionTuple[1]] + int(actionTuple[2])
else:
evidence[actionTuple[0]][actionTuple[1]] = 100
actions = list()
for act in evidence:
for target in evidence[act]:
actions.append((act, target, evidence[act][target]))
return actions
self.actions = combineActions(self.actions)
self.actedOnBy = list()
if concept in context.actionGraph:
for act_target in context.actionGraph.in_edges(concept):
for actor_act in context.actionGraph.in_edges(act_target[0]):
self.actedOnBy.append((act_target[0].name, actor_act[0].name, 100))
if concept in context.potentialActionGraph:
for potential_act_target in context.potentialActionGraph.in_edges(concept):
for potential_actor_act in context.potentialActionGraph.in_edges(potential_act_target[0], data=True):
self.actedOnBy.append((potential_act_target[0].name, potential_actor_act[0].name, potential_actor_act[2]['weight']))
self.actedOnBy = combineActions(self.actedOnBy)
