def ExecuteReasoner(self):
onto = World()
try:
onto.get_ontology("file://" + self.input).load()
sync_reasoner_pellet(onto, infer_property_values=True)
onto.save(file=self.output)
return True
except:
return False
def convert_worker(self, filename):
db_path = os.path.join(
self.db_dir, '.'.join(
(os.path.splitext(os.path.basename(filename))[0], "sqlite3")))
if not os.path.isfile(db_path):
self.Print(cDebug.LEVEL_DEVELOPMENT, 'Convert: ' + db_path)
my_world = World()
my_world.set_backend(filename=db_path)
my_world.get_ontology('file://' + filename).load()
my_world.save()
if self.remove_source:
os.remove(filename)
return db_path
def _read_from_source(filename: str) -> Ontology:
name = os.path.basename(filename)
_, ext = os.path.splitext(name)
if ext == ".json":
with open(filename) as json_file:
data = json.load(json_file)
elif ext == ".pkl":
with open(filename, "rb") as f:
data = pickle.load(f)
elif ext == ".owl":
world = World()
try:
ontology = world.get_ontology(filename)
onto = ontology.load()
except OwlReadyOntologyParsingError as ex:
return Ontology(name, {}, filename=filename, error_msg=ex.args[0])
with onto:
data = _onto_to_tree(Thing, world)
else:
raise NotImplementedError(f"No readers for file {name}")
assert isinstance(data, dict)
return Ontology(name, data, filename=filename)
def find_candidate_instances(w2v_vectors, tagged_words, input_onto, topn):
candidate_instances = defaultdict(list)
world = World()
onto = world.get_ontology(input_onto).load()
onto_classes = onto.classes()
for onto_class in onto_classes:
instances = [
nlp.get_name_from_IRI(inst)
for inst in onto.get_instances_of(onto_class)
]
for inst in instances:
if inst not in w2v_vectors.vocab.keys():
instances.remove(inst)
similar = find_by_cos_similarity(w2v_vectors, instances, onto_class,
topn)
similar = filter_by_pos(similar, instances, tagged_words)
for s in similar[:]:
if s[1] <= 0.42:
similar.remove(s)
candidate_instances[onto_class] = similar
return candidate_instances
def onto_get_var_limits():
da_vars = {}
mec_vars = {}
# creating a new world to isolate the reasoning results
new_world = World()
# Loading our ontologia
onto = new_world.get_ontology(onto_dir_path).load()
variables = onto.search(type=onto.Variable)
for var in variables:
try:
if 'DA' in var.esVariableDe[0].get_name():
da_vars[django_names[var.get_name()]] = {
'min': var.tieneValorMinimo,
'max': var.tieneValorMaximo
}
# print(var.esVariableDe[0].get_name())
if 'MEC' in var.esVariableDe[0].get_name():
mec_vars[django_names[var.get_name()]] = {
'min': var.tieneValorMinimo,
'max': var.tieneValorMaximo
}
# print(var.esVariableDe[0].get_name())
except Exception as e:
print("None", e)
return da_vars, mec_vars
def sparql_query_owlready(self, query):
"""
""SELECT ?p WHERE {
<http://www.semanticweb.org/jiba/ontologies/2017/0/test#ma_pizza> <http://www.semanticweb.org/jiba/ontologies/2017/0/test#price> ?p .
}""
"""
my_world = World()
onto = my_world.get_ontology(
join(self._onto.path, self._onto.owl_file + ".owl")).load()
graph = my_world.as_rdflib_graph()
return list(graph.query_owlready(query))
def populate_ontology(candidate_instances, input_onto, output_onto):
world = World()
onto = world.get_ontology(input_onto).load()
for onto_class, instances in candidate_instances.items():
print_class_and_similar(onto_class, instances)
for inst in instances:
_save_instance(onto, onto_class, inst)
onto.save(file=output_onto)
def get_ontology_from_local_file(filename: str = '',
db_dir: str = '',
db_dir_name: str = '',
use_owl_world: bool = True) -> Ontology:
filename_with_prefix = 'file://' + filename
if use_owl_world:
if not os.path.isdir(db_dir):
ret = FL.CreateDir(db_dir)
my_world = World()
my_world.set_backend(filename=db_dir_name)
return my_world.get_ontology(filename_with_prefix).load()
else:
return get_ontology(filename_with_prefix).load()
def __iter__(self) -> Iterator[Optional[Tuple[Ontology, Scene]]]:
for index, scene in enumerate(self.variation_dimensions):
self.iterations += 1
if scene is not None:
world = World(backend='sqlite', filename=':memory:', dbname=f"scene_db_{index:04}")
with world.get_ontology(self.base_iri) as onto:
self.domain_factory(onto)
self.instantiate_scene(scene, onto)
try:
sync_reasoner_pellet(x=world,
infer_data_property_values=True,
infer_property_values=True,
debug=self.debug)
except Exception as e:
onto.save("error.rdf.xml")
raise e
yield onto, scene
else:
yield None
if self.max_tries is not None and self.iterations >= self.max_tries:
break
def reasoner(data):
# print(data.shape)
# print("Inside OntoParser-Reasoner")
# creating a new world to isolate the reasoning results
# ontos = {n: World().get_ontology(onto_dir_path).load()
# for n in range(data.shape[0])}
new_world = World()
# Loading the ontology
onto = new_world.get_ontology(onto_dir_path).load()
# Creating individuals of Lectura that will be used by the rules
onto.Variable_Dil1_Entrada.tieneValorPropuesto = float(data[0])
onto.Lectura_AGV_Entrada.tieneValorCensado = float(data[1])
onto.Lectura_DQO_Entrada.tieneValorCensado = float(data[2])
onto.Lectura_Biomasa_Salida.tieneValorCensado = float(data[3])
onto.Lectura_DQO_Salida.tieneValorCensado = float(data[4])
onto.Lectura_AGV_Salida.tieneValorCensado = float(data[5])
onto.Variable_Dil2_Entrada.tieneValorPropuesto = float(data[7])
onto.Lectura_Ace_Salida.tieneValorCensado = float(data[9])
onto.Lectura_xa_Salida.tieneValorCensado = float(data[10])
onto.Lectura_xm_Salida.tieneValorCensado = float(data[11])
onto.Lectura_xh_Salida.tieneValorCensado = float(data[12])
onto.Lectura_mox_Salida.tieneValorCensado = float(data[13])
onto.Lectura_imec_Salida.tieneValorCensado = float(data[14])
onto.Lectura_QH2_Salida.tieneValorCensado = float(data[15])
# Apply the rules using pellet reasoner
sync_reasoner_pellet(onto,
infer_data_property_values=True,
infer_property_values=True,
debug=0)
# Get new states for each process
infered_states = get_infered_states(onto)
return json.dumps(infered_states), onto
class OntologyManager:
def __init__(self, iri="http://www.example.org/onto.owl"):
self.typical_facts_list = list()
self.a_box_members_list = list()
self.scenarios_list = list()
self.typical_members_list = list()
self.cost_dict = dict()
self.symptoms_dict = dict()
self.my_world = World()
self.big_world = World()
self.onto = self.my_world.get_ontology(iri)
def create_complementary_class(self, class_identifier):
with self.onto:
complementary_class = Not(class_identifier)
return complementary_class
def create_class(self, class_name):
if not self.is_class_present(class_name):
with self.onto:
new_class = types.new_class(class_name, (Thing,))
return new_class
else:
return self.get_class(class_name)
def create_property(self, property_name):
with self.onto:
new_property = types.new_class(property_name, (ObjectProperty,))
return new_property
def add_sub_class(self, sub_class_identifier, super_class_identifier):
with self.onto:
sub_class_identifier.is_a.append(super_class_identifier)
def add_member_to_class(self, member_name, class_identifier, symp: bool = False):
self.a_box_members_list.append(AboxMember(class_identifier, member_name, symp))
return class_identifier(member_name)
def add_member_to_multiple_classes(self, member_identifier, class_list, symp: bool = False):
for c in class_list:
member_identifier.is_a.append(c)
self.a_box_members_list.append(AboxMember(c, member_identifier.name, symp))
# & operatore logico di owlready di intersezione.
# r1 proprietà di owlready
# only per ogni
# some invece significa esiste
# noinspection PyUnresolvedReferences
def add_typical_fact(self, t_class_identifier, class_identifier, probability="No probability"):
with self.onto:
t_class_identifier_1 = self.create_class(t_class_identifier.name + "1")
t_class_intersection = self.create_class(
"Intersection" + t_class_identifier.name + t_class_identifier_1.name)
t_class_intersection.equivalent_to = [t_class_identifier & t_class_identifier_1]
self.add_sub_class(t_class_intersection, class_identifier)
r1 = self.create_property("r1")
t_class_identifier_1.is_a.append(r1.only(Not(t_class_identifier) & t_class_identifier_1))
not_t_class_identifier_1 = self.create_class("Not" + t_class_identifier_1.name)
not_t_class_identifier_1.is_a.append(r1.some(t_class_identifier & t_class_identifier_1))
self.typical_facts_list.append(TypicalFact(t_class_identifier, class_identifier, probability))
# C e C1
# Interesezione serve per esplicitare il concetto della doppia appartenenza
def set_as_typical_member(self, member_name, t_class_identifier, t_class_identifier_1):
with self.onto:
print("Membro tipico:")
t_class_identifier(member_name)
t_class_identifier_1(member_name)
t_class_intersection = self.get_class("Intersection" + t_class_identifier.name + t_class_identifier_1.name)
t_class_intersection(member_name)
print(member_name + " is_a " + t_class_identifier.name)
print(member_name + " is_a " + t_class_identifier_1.name)
print(member_name + " is_a " + t_class_intersection.name)
def is_class_present(self, class_name):
if self.get_class(class_name) is not None:
return True
return False
def get_class(self, class_name):
return self.onto[class_name]
def consistency(self, condition: bool = False):
try:
with self.onto:
if condition:
sync_reasoner(self.my_world)
classi_incosistenti = list(self.my_world.inconsistent_classes())
if not len(classi_incosistenti) == 0:
return classi_incosistenti
else:
sync_reasoner(self.big_world)
return "The ontology is consistent"
except OwlReadyInconsistentOntologyError:
return "The ontology is inconsistent"
def store_for_reasoning(self, member_name: str, class_id: object):
self.symptoms_dict.update({class_id: member_name})
def add_symptoms_to_kb(self):
for class_sy, pname, in self.symptoms_dict.items():
class_c = self.create_class(class_sy.name)
not_class_c = self.create_class("Not(" + class_sy.name + ")")
class_c.equivalent_to = [Not(not_class_c)]
self.add_member_to_class(pname, not_class_c, symp=True)
print("Sintomo aggiunto: " + pname + ": " + not_class_c.name)
def save_base_world(self):
self.onto.save("ontoBase.owl", format="ntriples")
def create_new_world(self):
self.onto.destroy()
self.big_world = World()
self.onto = self.big_world.get_ontology(
"file://" + PATH_TO_ONTO + "//ontoBase.owl").load() # .load(True, None, True)
def show_classes_iri(self):
for c in self.big_world.classes():
print(str(c.name) + " is_a " + str(c.is_a))
def show_members_in_classes(self):
for c in self.big_world.classes():
for m in c.instances():
print(m.name + " member_of " + c.name)
def show_classes_iri_my(self):
for c in self.my_world.classes():
print(str(c.name) + " is_a " + str(c.is_a))
def show_members_in_classes_my(self):
for c in self.my_world.classes():
for m in c.instances():
print(m.name + " member_of " + c.name)
def show_scenarios(self):
num_scenario = 1
for s in self.scenarios_list:
print("INIZIO SCENARIO " + str(num_scenario))
record = ""
if len(s.list_of_typical_members) == 0:
print("Scenario vuoto" + "\n" + "Probabilità scenario: " + str(s.probability))
else:
for tm in s.list_of_typical_members:
record = record + "Typical(" + tm.t_class_identifier.name + ")" + "," + tm.member_name + "," \
+ str(tm.probability) + "\n"
record = record + "Probabilità scenario: " + str(s.probability)
print(record)
print("FINE SCENARIO " + str(num_scenario))
print("\n")
num_scenario = num_scenario + 1
@staticmethod
def show_a_specific_scenario(scenario):
print("INIZIO SCENARIO")
record = ""
if len(scenario.list_of_typical_members) == 0:
print("Scenario vuoto;" + "\nProbabilità scenario: " + str(scenario.probability))
else:
for tm in scenario.list_of_typical_members:
record = record + tm.t_class_identifier.name + "," + tm.member_name + "," + str(tm.probability) + "; "
record = record + "\nProbabilità scenario: " + str(scenario.probability)
print(record)
print("FINE SCENARIO")
# TODO Metodi mai utilizzati decidere cosa farne
@staticmethod
def destroy_class(class_identifier):
destroy_entity(class_identifier)
@staticmethod
def set_classes_as_disjoint(classes_identifier_list):
AllDisjoint(classes_identifier_list)
@staticmethod
def remove_onto_file():
if os.path.exists("ontoBase.owl"):
os.remove("ontoBase.owl")
else:
print("The file does not exist")
class OntologyInspector(object):
def __init__(self, owl_file, path, endpoint=None, inspector=None):
self.owl_file = owl_file.replace(".owl", "")
self.path = path
self._onto = GenericOntology(join(self.path, self.owl_file))
self.world = World()
self.world.get_ontology(join(self.path, self.owl_file + ".owl")).load()
self.endpoint = endpoint
self.inspector = inspector or SPARQLQueries(endpoint, self)
self.list_labels = set() # An unique list of ontology labels
self.superclass_for_class = {}
self.__load_subclasses__()
self.__nsmap = {} ##mapping of namespaces
@property
def ontology(self):
""" owlready2 ontology format """
return self._onto.onto
def reload_ontology(self):
""" reload from disk """
self._onto = GenericOntology(join(self.path, self.owl_file))
def update_ontology(self, onto):
""" owlready2 ontology format """
self._onto.onto = onto
def __get_owl_root_node__(self):
try:
from lxml import etree
except:
import xml.etree.cElementTree as etree
owl_file = self.path + '/' + self.owl_file + ".owl"
owl_root = etree.parse(owl_file).getroot()
self.nsmap = owl_root.nsmap.copy()
self.nsmap['xmlns'] = self.nsmap.pop(None)
return owl_root
def __load_subclasses__(self):
owl_root = self.__get_owl_root_node__()
for class_obj in owl_root.findall('{%s}Class' % owl_root.nsmap['owl']):
onto_label = class_obj.get('{%s}about' % owl_root.nsmap['rdf'])
self.list_labels.add(onto_label)
subclass_of_obj = class_obj.find('{%s}subClassOf' %
owl_root.nsmap['rdfs'])
if subclass_of_obj is not None:
superclass_label = subclass_of_obj.get('{%s}resource' %
owl_root.nsmap['rdf'])
self.superclass_for_class[onto_label] = superclass_label
def is_leaf_class(self, onto_label):
"""
Checks if the ontology label provided (for instance http://dbpedia.org/ontology/SportsTeam) is a leaf in the DBpedia ontology tree or not
It is a leaf if it is not super-class of any other class in the ontology
@param onto_label: the ontology label
@type onto_label: string
@return: whether it is a leaf or not
@rtype: bool
"""
is_super_class = False
for subclass, superclass in list(self.superclass_for_class.items()):
if superclass == onto_label:
is_super_class = True
break
if not is_super_class and onto_label not in self.list_labels:
return None
return not is_super_class
def get_ontology_path(self, onto_label):
'''
Returns the path of ontology classes for the given ontology label (is-a relations)
@param onto_label: the ontology label (could be http://dbpedia.org/ontology/SportsTeam or just SportsTeam)
@type onto_label: str
@return: list of ontology labels
@rtype: list
'''
thing_label = '%sThing' % self.nsmap['owl']
if onto_label == thing_label:
return [thing_label]
else:
if self.nsmap[
'xmlns'] not in onto_label: # To allow things like "SportsTeam instead of http://dbpedia.org/ontology/SportsTeam
onto_label = self.nsmap['xmlns'] + onto_label
if onto_label not in self.superclass_for_class:
return []
else:
super_path = self.get_ontology_path(
self.superclass_for_class[onto_label])
super_path.insert(0, onto_label)
return super_path
def get_depth(self, onto_label):
'''
Returns the depth in the ontology hierarchy for the given ontology label (is-a relations)
@param onto_label: the ontology label (could be http://dbpedia.org/ontology/SportsTeam or just SportsTeam)
@type onto_label: str
@return: depth
@rtype: int
'''
path = self.get_ontology_path(onto_label)
return len(path)
def search(self, *args, **kwargs):
return self.ontology.search(*args, **kwargs)
def search_one(self, *args, **kwargs):
return self.ontology.search_one(*args, **kwargs)
def search_by_iri(self, iri):
return self.ontology.search(iri=iri)
def search_by_type(self, typ):
return self.ontology.search(type=typ)
def search_by_subclass_of(self, subclass_of):
return self.ontology.search(subclass_of=subclass_of)
def search_by_is_a(self, is_a):
return self.ontology.search(is_a=is_a)
def as_sql(self, query, name=None, path=None):
""" search triples and export result in sql db"""
name = name or query
with GenericSQLDatabase(name, path) as db:
triples = self.inspector.triples(query)
for triple in triples:
thing = triple["subject"]["value"]
prop = triple["predicate"]["value"]
value = triple["object"]["value"]
t = db.add_thing(thing)
p = db.add_property(prop, value=value)
t.properties.append(p)
return db
def from_sql(self, path):
return self
def hermit_reason(self):
""" load from disk, reason and return owlready2 ontology format"""
self.world = World()
onto = self.world.get_ontology(join(self.path,
self.owl_file + ".owl")).load()
sync_reasoner_hermit(self.world)
return onto
def pellet_reason(self):
""" load from disk, reason and return owlready2 ontology format"""
self.world = World()
onto = self.world.get_ontology(join(self.path,
self.owl_file + ".owl")).load()
sync_reasoner_pellet(self.world)
return onto
def EYE_reason(self, data, rules):
'''
data = """
@prefix ppl: <http://example.org/people#>.
@prefix foaf: <http://xmlns.com/foaf/0.1/>.
ppl:Cindy foaf:knows ppl:John.
ppl:Cindy foaf:knows ppl:Eliza.
ppl:Cindy foaf:knows ppl:Kate.
ppl:Eliza foaf:knows ppl:John.
ppl:Peter foaf:knows ppl:John.
"""
rules = """
@prefix foaf: <http://xmlns.com/foaf/0.1/>.
{
?personA foaf:knows ?personB.
}
=>
{
?personB foaf:knows ?personA.
}.
"""
output = """
PREFIX ppl: <http://example.org/people#>
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
ppl:Cindy foaf:knows ppl:John.
ppl:Cindy foaf:knows ppl:Eliza.
ppl:Cindy foaf:knows ppl:Kate.
ppl:Eliza foaf:knows ppl:John.
ppl:Peter foaf:knows ppl:John.
ppl:John foaf:knows ppl:Cindy.
ppl:Eliza foaf:knows ppl:Cindy.
ppl:Kate foaf:knows ppl:Cindy.
ppl:John foaf:knows ppl:Eliza.
ppl:John foaf:knows ppl:Peter. """
'''
return EYE_rest(data, rules)
class KnowledgeBase(AbstractKnowledgeBase):
""" Knowledge Base Class representing Tbox and Abox along with the concept hierarchy """
def __init__(self, path):
super().__init__()
self.path = path
self.world = World()
self.onto = self.world.get_ontology('file://' +
self.path).load(reload=True)
self.property_hierarchy = PropertyHierarchy(self.onto)
self.name = self.onto.name
self.parse()
self._concept_generator = ConceptGenerator(
concepts=self.uri_to_concept,
thing=self.thing,
nothing=self.nothing,
onto=self.onto)
self.describe()
def instance_retrieval(self, c: Concept):
if c.instances is None:
return self._concept_generator.instance_retrieval(c)
return c.instances
def instance_retrieval_from_iterable(self, nodes: Iterable):
return [self.instance_retrieval(n.concept) for n in nodes]
def instance_retrieval_parallel_from_iterable(self, nodes: Iterable):
"""
with multiprocessing.Pool(processes=4) as executor:
instances = executor.map(self.concept_generator.instance_retrieval_node, nodes)
return instances
with concurrent.futures.ThreadPoolExecutor() as executor:
instances = executor.map(self.concept_generator.instance_retrieval_node, nodes)
return instances
=> The least efficient.
with concurrent.futures.ProcessPoolExecutor() as executor:
instances = executor.map(self.concept_generator.instance_retrieval_node, nodes)
return instances
"""
with multiprocessing.Pool(processes=4) as executor:
instances = executor.map(
self._concept_generator.instance_retrieval_node, nodes)
return instances
def clean(self):
"""
Clearn all stored values if there is any.
@return:
"""
def __concept_hierarchy_fill(self, owl_concept, our_concept):
"""
our_concept can not be Nothing or Thing
"""
has_sub_concept = False
# 3. Get all sub concepts of input concept.
for owlready_subclass_concept_A in owl_concept.descendants(
include_self=False):
if owlready_subclass_concept_A.name in [
'Nothing', 'Thing', 'T', '⊥'
]:
raise ValueError
has_sub_concept = True
# 3.2 Map them into the corresponding our Concept objects.
subclass_concept_A = self.uri_to_concept[
owlready_subclass_concept_A.iri]
# 3.3. Add all our sub concepts into the concept the top down concept hierarchy.
self.top_down_concept_hierarchy[our_concept].add(
subclass_concept_A)
self.down_top_concept_hierarchy[subclass_concept_A].add(
our_concept)
# 4. Get all super concepts of input concept.
for owlready_superclass_concept_A in owl_concept.ancestors(
include_self=False):
if owlready_superclass_concept_A.name == 'Thing' and len(
[i for i in owl_concept.ancestors(include_self=False)]) == 1:
self.top_down_direct_concept_hierarchy[self.thing].add(
our_concept)
self.down_top_direct_concept_hierarchy[our_concept].add(
self.thing)
else:
# 3.2 Map them into the corresponding our Concept objects.
superclass_concept_A = self.uri_to_concept[
owlready_superclass_concept_A.iri]
# 3.3. Add all our super concepts into the concept the down to concept concept hierarchy.
self.down_top_concept_hierarchy[our_concept].add(
superclass_concept_A)
self.top_down_concept_hierarchy[superclass_concept_A].add(
our_concept)
# 4. If concept does not have any sub concept, then concept is a leaf concept.
# Every leaf concept is directly related to Nothing.
if has_sub_concept is False:
self.top_down_direct_concept_hierarchy[our_concept].add(
self.nothing)
self.down_top_direct_concept_hierarchy[self.nothing].add(
our_concept)
def __direct_concept_hierarchy_fill(self, owlready_concept_A, concept_A,
onto):
for owlready_direct_subclass_concept_A in owlready_concept_A.subclasses(
world=onto.world): # returns direct subclasses
if owlready_concept_A == owlready_direct_subclass_concept_A:
print(owlready_concept_A)
print(owlready_direct_subclass_concept_A)
raise ValueError
direct_subclass_concept_A = self.uri_to_concept[
owlready_direct_subclass_concept_A.iri]
self.top_down_direct_concept_hierarchy[concept_A].add(
direct_subclass_concept_A)
self.down_top_direct_concept_hierarchy[
direct_subclass_concept_A].add(concept_A)
def __build_hierarchy(self, onto: Ontology) -> None:
"""
Builds concept sub and super classes hierarchies.
1) self.top_down_concept_hierarchy is a mapping from Concept objects to a set of Concept objects that are
direct subclasses of given Concept object.
2) self.down_top_concept_hierarchy is a mapping from Concept objects to set of Concept objects that are
direct superclasses of given Concept object.
"""
# 1. (Mapping from string URI to Class Expressions, Thing Concept, Nothing Concept
self.uri_to_concept, self.thing, self.nothing = parse_tbox_into_concepts(
onto)
assert len(self.uri_to_concept) > 2
assert self.thing.iri == 'http://www.w3.org/2002/07/owl#Thing'
assert self.thing.name == '⊤'
assert self.nothing.iri == 'http://www.w3.org/2002/07/owl#Nothing'
assert self.nothing.name == '⊥'
self.individuals = self.thing.instances
self.down_top_concept_hierarchy[self.thing] = set()
for IRI, concept_A in self.uri_to_concept.items(
): # second loop over concepts in the execution,
assert IRI == concept_A.iri
try:
assert len(onto.search(iri=IRI)) == 1
except AssertionError:
# Thing and Nothing is not added into hierarchy
assert IRI in [
'http://www.w3.org/2002/07/owl#Thing',
'http://www.w3.org/2002/07/owl#Nothing'
]
assert concept_A.name in ['⊤', '⊥']
continue
owlready_concept_A = onto.search(iri=concept_A.iri)[0]
assert owlready_concept_A.iri == concept_A.iri
self.__concept_hierarchy_fill(owlready_concept_A, concept_A)
self.__direct_concept_hierarchy_fill(owlready_concept_A, concept_A,
onto)
# All concepts are subsumed by Thing.
self.top_down_concept_hierarchy[self.thing].add(concept_A)
self.down_top_concept_hierarchy[concept_A].add(self.thing)
# All concepts subsume Nothing.
self.top_down_concept_hierarchy[concept_A].add(self.nothing)
self.down_top_concept_hierarchy[self.nothing].add(concept_A)
self.top_down_concept_hierarchy[self.thing].add(self.nothing)
self.down_top_concept_hierarchy[self.nothing].add(self.thing)
################################################################################################################
# Sanity checking
# 1. Did we parse classes correctly ?
owlready2_classes = {i.iri for i in onto.classes()}
our_classes = {k for k, v in self.uri_to_concept.items()}
try:
assert our_classes.issuperset(owlready2_classes) and (
our_classes.difference(owlready2_classes) == {
'http://www.w3.org/2002/07/owl#Thing',
'http://www.w3.org/2002/07/owl#Nothing'
})
except AssertionError:
raise AssertionError('Assertion error => at superset checking.')
try:
# Thing subsumes all parsed concept except itself.
assert len(self.top_down_concept_hierarchy[self.thing]) == (
len(our_classes) - 1)
assert len(self.down_top_concept_hierarchy[self.nothing]) == (
len(our_classes) - 1)
except AssertionError:
raise AssertionError(
'Assertion error => at concept hierarchy checking.')
# start from here
try:
assert len(self.down_top_concept_hierarchy[self.nothing]) == (
len(our_classes) - 1)
assert len(self.top_down_direct_concept_hierarchy[self.thing]) >= 1
except AssertionError:
raise AssertionError(
'Assertion error => total number of parsed concept checking')
# 2. Did we create top down direct concept hierarchy correctly ?
for concept, direct_sub_concepts in self.top_down_direct_concept_hierarchy.items(
):
for dsc in direct_sub_concepts:
assert concept.instances.issuperset(dsc.instances)
# 3. Did we create top down concept hierarchy correctly ?
for concept, direct_sub_concepts in self.top_down_concept_hierarchy.items(
):
for dsc in direct_sub_concepts:
assert concept.instances.issuperset(dsc.instances)
# 3. Did we create down top direct concept hierarchy correctly ?
for concept, direct_super_concepts in self.down_top_direct_concept_hierarchy.items(
):
for dsc in direct_super_concepts:
assert concept.instances.issubset(dsc.instances)
# 4. Did we create down top concept hierarchy correctly ?
for concept, direct_super_concepts in self.down_top_concept_hierarchy.items(
):
for dsc in direct_super_concepts:
try:
assert concept.instances.issubset(dsc.instances)
except AssertionError:
raise AssertionError('Subset error')
def parse(self):
"""
Top-down and bottom up hierarchies are constructed from from owlready2.Ontology
"""
self.__build_hierarchy(self.onto)
# OPERATIONS
def negation(self, concept: Concept) -> Concept:
""" Return a Concept object that is a negation of given concept."""
return self._concept_generator.negation(concept)
def union(self, conceptA: Concept, conceptB: Concept) -> Concept:
"""Return a concept c == (conceptA OR conceptA)"""
return self._concept_generator.union(conceptA, conceptB)
def intersection(self, conceptA: Concept, conceptB: Concept) -> Concept:
"""Return a concept c == (conceptA AND conceptA)"""
return self._concept_generator.intersection(conceptA, conceptB)
def existential_restriction(self, concept: Concept, property_) -> Concept:
"""Return a concept c == (\exists R.C)"""
return self._concept_generator.existential_restriction(
concept, property_)
def universal_restriction(self, concept: Concept, property_) -> Concept:
"""Return a concept c == (\forall R.C)"""
return self._concept_generator.universal_restriction(
concept, property_)
@staticmethod
def is_atomic(c: owlready2.entity.ThingClass):
"""
Check whether input owlready2 concept object is atomic concept.
This is a workaround
@param c:
@return:
"""
assert isinstance(c, owlready2.entity.ThingClass)
if '¬' in c.name and not (' ' in c.name):
return False
elif ' ' in c.name or '∃' in c.name or '∀' in c.name:
return False
else:
return True
def get_leaf_concepts(self, concept: Concept) -> Generator:
""" Return : { x | (x subClassOf concept) AND not exist y: y subClassOf x )} """
assert isinstance(concept, Concept)
for leaf in self.concepts_to_leafs[concept]:
yield leaf
@parametrized_performance_debugger()
def negation_from_iterables(self, s: Iterable) -> Generator:
""" Return : { x | ( x \equiv not s} """
assert isinstance(s, Iterable)
for item in s:
yield self._concept_generator.negation(item)
# @parametrized_performance_debugger()
def get_direct_sub_concepts(self, concept: Concept) -> Generator:
""" Return : { x | ( x subClassOf concept )} """
assert isinstance(concept, Concept)
yield from self.top_down_direct_concept_hierarchy[concept]
def get_all_sub_concepts(self, concept: Concept):
""" Return : { x | ( x subClassOf concept ) OR ..."""
assert isinstance(concept, Concept)
yield from self.top_down_concept_hierarchy[concept]
def get_direct_parents(self, concept: Concept) -> Generator:
""" Return : { x | (concept subClassOf x)} """
assert isinstance(concept, Concept)
yield from self.down_top_direct_concept_hierarchy[concept]
def get_parents(self, concept: Concept) -> Generator:
""" Return : { x | (concept subClassOf x)} """
yield from self.down_top_concept_hierarchy[concept]
def most_general_existential_restrictions(self,
concept: Concept) -> Generator:
""" Return : { \exist.r.x | r \in MostGeneral r} """
assert isinstance(concept, Concept)
for prob in self.property_hierarchy.get_most_general_property():
yield self._concept_generator.existential_restriction(
concept, prob)
def union_from_iterables(self, concept_a: Iterable, concept_b: Iterable):
temp = set()
seen = set()
for i in concept_a:
for j in concept_b:
if (i.name, j.name) in seen:
continue
u = self._concept_generator.union(i, j)
seen.add((i.name, j.name))
seen.add((j.name, i.name))
temp.add(u)
return temp
def intersect_from_iterables(self, concept_a, concept_b):
temp = set()
seen = set()
for i in concept_a:
for j in concept_b:
if (i.name, j.name) in seen:
continue
and_ = self._concept_generator.intersection(i, j)
seen.add((i.name, j.name))
seen.add((j.name, i.name))
temp.add(and_)
return temp
def most_general_universal_restrictions(self,
concept: Concept) -> Generator:
""" Return : { \forall.r.x | r \in MostGeneral r} """
assert isinstance(concept, Concept)
for prob in self.property_hierarchy.get_most_general_property():
yield self._concept_generator.universal_restriction(concept, prob)
def __init__(self, data_dir_path):
my_world = World()
# path to the owl file is given here
my_world.get_ontology("file://%s" % data_dir_path).load()
sync_reasoner(my_world) # reasoner is started and synchronized here
self.graph = my_world.as_rdflib_graph()
def update_onto_limits(var_boundaries):
# print("Updating boundaries")
# print(var_boundaries)
# creating a new world to isolate the reasoning results
new_world = World()
# Loading our ontologia
onto = new_world.get_ontology(onto_dir_path).load()
# Updating DA variables
onto.Variable_Dil1_Entrada.tieneValorMinimo = float(
var_boundaries.loc['min']['da_dil1'])
onto.Variable_AGV_Entrada.tieneValorMinimo = float(
var_boundaries.loc['min']['da_agv_in'])
onto.Variable_DQO_Entrada.tieneValorMinimo = float(
var_boundaries.loc['min']['da_dqo_in'])
onto.Variable_Biomasa_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['da_biomasa_x'])
onto.Variable_DQO_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['da_dqo_out'])
onto.Variable_AGV_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['da_agv_out'])
onto.Variable_Dil1_Entrada.tieneValorMaximo = float(
var_boundaries.loc['max']['da_dil1'])
onto.Variable_AGV_Entrada.tieneValorMaximo = float(
var_boundaries.loc['max']['da_agv_in'])
onto.Variable_DQO_Entrada.tieneValorMaximo = float(
var_boundaries.loc['max']['da_dqo_in'])
onto.Variable_Biomasa_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['da_biomasa_x'])
onto.Variable_DQO_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['da_dqo_out'])
onto.Variable_AGV_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['da_agv_out'])
# Updating MEC variables
onto.Variable_Dil2_Entrada.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_dil2'])
onto.Variable_Eapp_Entrada.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_eapp'])
onto.Variable_Ace_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_ace'])
onto.Variable_xa_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_xa'])
onto.Variable_xm_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_xm'])
onto.Variable_xh_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_xh'])
onto.Variable_mox_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_mox'])
onto.Variable_imec_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_imec'])
onto.Variable_QH2_Salida.tieneValorMinimo = float(
var_boundaries.loc['min']['mec_qh2'])
onto.Variable_Dil2_Entrada.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_dil2'])
onto.Variable_Eapp_Entrada.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_eapp'])
onto.Variable_Ace_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_ace'])
onto.Variable_xa_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_xa'])
onto.Variable_xm_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_xm'])
onto.Variable_xh_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_xh'])
onto.Variable_mox_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_mox'])
onto.Variable_imec_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_imec'])
onto.Variable_QH2_Salida.tieneValorMaximo = float(
var_boundaries.loc['max']['mec_qh2'])
onto.save(onto_dir_path, format="rdfxml")
print("limits updated")
print()
def get_ontology_from_database(iri, db_dir_name, exclusive=True) -> Ontology:
my_world = World()
my_world.set_backend(filename=db_dir_name, exclusive=exclusive)
return my_world.get_ontology(iri).load()