def regenerate(self, markov_model_id):
""" Regenerate the markvov chain """
try:
markov_model = self.get_markov_model(int(markov_model_id))
except KeyError:
print_error('No such markov model id')
return False
label = __group_of_labels__.get_label_by_id(
markov_model.get_label_id())
connections = label.get_connections_complete()
# Get all the group of models and connections names
state = ""
for group_of_model_id in connections:
# Get all the connections
for conn in connections[group_of_model_id]:
# Get the model group
group = __groupofgroupofmodels__.get_group(group_of_model_id)
# Get the model
model = group.get_model(conn)
# Get each state
state += model.get_state() + '#'
# Delete the last #
state = state[:-1]
# Store the state
markov_model.set_state(state)
# Store the connections
markov_model.set_connections(connections)
# Create the MM itself
markov_model.create(markov_model.get_state())
print_info('Markov model {} regenerated.'.format(markov_model_id))
def regenerate(self, markov_model_id):
""" Regenerate the markvov chain """
try:
markov_model = self.get_markov_model(int(markov_model_id))
except KeyError:
print_error('No such markov model id')
return False
label = __group_of_labels__.get_label_by_id(markov_model.get_label_id())
connections = label.get_connections_complete()
# Get all the group of models and connections names
state = ""
for group_of_model_id in connections:
# Get all the connections
for conn in connections[group_of_model_id]:
# Get the model group
group = __groupofgroupofmodels__.get_group(group_of_model_id)
# Get the model
model = group.get_model(conn)
# Get each state
state += model.get_state() + '#'
# Delete the last #
state = state[:-1]
# Store the state
markov_model.set_state(state)
# Store the connections
markov_model.set_connections(connections)
# Create the MM itself
markov_model.create(markov_model.get_state())
print_info('Markov model {} regenerated.'.format(markov_model_id))
def add_label(self, group_of_model_id, connection_id):
""" Add a label """
if __datasets__.current:
dataset_id_standing = __datasets__.current.get_id()
dataset_id = group_of_model_id.split('-')[0]
if str(dataset_id_standing) != dataset_id:
print_error(
'You should select the dataset you are going to work in. Not another'
)
return False
if not __groupofgroupofmodels__.get_group(group_of_model_id):
print_error('That group of models does not exist.')
return False
has_label = self.check_label_existance(group_of_model_id,
connection_id)
if has_label:
print_error(
'This connection from this dataset was already assigned the label id {}'
.format(has_label))
else:
print_warning(
'Remember that a label should represent a unique behavioral model!'
)
try:
label_id = self.labels[list(
self.labels.keys())[-1]].get_id() + 1
except (KeyError, IndexError):
label_id = 1
name = self.decide_a_label_name(connection_id)
if name:
previous_label = self.search_label_name(name,
verbose=False,
exact=1)
if previous_label:
label = self.get_label(name)
label.add_connection(group_of_model_id, connection_id)
else:
label = Label(label_id)
label.set_name(name)
label.add_connection(group_of_model_id, connection_id)
self.labels[label_id] = label
# Add label id to the model
self.add_label_to_model(group_of_model_id, connection_id,
name)
# add auto note with the label to the model
self.add_auto_label_for_connection(group_of_model_id,
connection_id, name)
else:
# This is not necesary, but is a precaution
print_error('Aborting the assignment of the label.')
return False
else:
print_error('There is no dataset selected.')
def get_the_model_of_a_connection(self, group_of_model_id, connection_id):
""" Given a connection_id and group of model id, get the model """
# Get the note id, group_id and group
dataset_id = int(group_of_model_id.split('-')[0])
dataset = __datasets__.get_dataset(dataset_id)
group = __groupofgroupofmodels__.get_group(group_of_model_id)
try:
if group.has_model(connection_id):
model = group.get_model(connection_id)
return model
except AttributeError:
print_error('The connection does not have a model. Probably deleted.')
return False
def get_the_model_of_a_connection(self, connection_id):
""" Given a connection_id and current dataset, get the model """
if __datasets__.current:
# Get the note id, group_id and group
dataset = __datasets__.get_dataset(__datasets__.current.get_id())
group_of_models = dataset.get_group_of_models()
for group_id in group_of_models: # Usually is only one group...
group = __groupofgroupofmodels__.get_group(group_id)
if group.has_model(connection_id):
model = group.get_model(connection_id)
return model
else:
print_error('There is no dataset selected.')
def get_the_model_of_a_connection(self, group_of_model_id, connection_id):
""" Given a connection_id and group of model id, get the model """
# Get the note id, group_id and group
dataset_id = int(group_of_model_id.split('-')[0])
dataset = __datasets__.get_dataset(dataset_id)
group = __groupofgroupofmodels__.get_group(group_of_model_id)
try:
if group.has_model(connection_id):
model = group.get_model(connection_id)
return model
except AttributeError:
print_error(
'The connection does not have a model. Probably deleted.')
return False
def create_new_model(self, label_name, number_of_flows):
""" Given a label name create a new markov chain object"""
# Get the label object
label_to_model = __group_of_labels__.get_label(label_name)
if label_to_model:
# Create a new markov chain object
## Get the new id
try:
mm_id = self.markov_models[list(
self.markov_models.keys())[-1]].get_id() + 1
except (KeyError, IndexError):
mm_id = 1
markov_model = Markov_Model(mm_id)
# Store the label id
markov_model.set_label_id(label_to_model.get_id())
state = ""
# Get all the connections in the label
connections = label_to_model.get_connections_complete()
# Get all the group of models and connections names
for group_of_model_id in connections:
# Get all the connections
for conn in connections[group_of_model_id]:
# Get the model group
group = __groupofgroupofmodels__.get_group(
group_of_model_id)
# Get the model
model = group.get_model(conn)
# Get each state
state += model.get_state() + '#'
# Delete the last #
state = state[:-1]
# Store the state
markov_model.set_state(state)
# Store the connections
markov_model.set_connections(connections)
# Create the MM itself
markov_model.create(markov_model.get_state())
# Generate the self probability
prob = markov_model.compute_probability(markov_model.get_state())
markov_model.set_self_probability(prob)
# Store
self.markov_models[mm_id] = markov_model
print_info('New model created with id {}'.format(
markov_model.get_id()))
else:
print_error('No label with that name')
def create_new_model(self, label_name, number_of_flows):
""" Given a label name create a new markov chain object"""
# Get the label object
label_to_model = __group_of_labels__.get_label(label_name)
if label_to_model:
# Create a new markov chain object
## Get the new id
try:
mm_id = self.markov_models[list(self.markov_models.keys())[-1]].get_id() + 1
except (KeyError, IndexError):
mm_id = 1
markov_model = Markov_Model(mm_id)
# Store the label id
markov_model.set_label_id(label_to_model.get_id())
state = ""
# Get all the connections in the label
connections = label_to_model.get_connections_complete()
# Get all the group of models and connections names
for group_of_model_id in connections:
# Get all the connections
for conn in connections[group_of_model_id]:
# Get the model group
group = __groupofgroupofmodels__.get_group(group_of_model_id)
# Get the model
model = group.get_model(conn)
# Get each state
#state += model.get_state() + '#'
state += model.get_state()
# Delete the last #
#state = state[:-1]
# Store the state
markov_model.set_state(state)
# Store the connections
markov_model.set_connections(connections)
# Create the MM itself
markov_model.create(markov_model.get_state())
# Generate the self probability
prob = markov_model.compute_probability(markov_model.get_state())
markov_model.set_self_probability(prob)
# Store
self.markov_models[mm_id] = markov_model
print_info('New model created with id {}'.format(markov_model.get_id()))
else:
print_error('No label with that name')
def add_label(self, group_of_model_id, connection_id):
""" Add a label """
if __datasets__.current:
dataset_id_standing = __datasets__.current.get_id()
dataset_id = group_of_model_id.split('-')[0]
if str(dataset_id_standing) != dataset_id:
print_error('You should select the dataset you are going to work in. Not another')
return False
if not __groupofgroupofmodels__.get_group(group_of_model_id):
print_error('That group of models does not exist.')
return False
has_label = self.check_label_existance(group_of_model_id, connection_id)
if has_label:
print_error('This connection from this dataset was already assigned the label id {}'.format(has_label))
else:
print_warning('Remember that a label should represent a unique behavioral model!')
try:
label_id = self.labels[list(self.labels.keys())[-1]].get_id() + 1
except (KeyError, IndexError):
label_id = 1
name = self.decide_a_label_name(connection_id)
if name:
previous_label = self.search_label_name(name, verbose=False, exact=1)
if previous_label:
label = self.get_label(name)
label.add_connection(group_of_model_id, connection_id)
else:
label = Label(label_id)
label.set_name(name)
label.add_connection(group_of_model_id, connection_id)
self.labels[label_id] = label
# Add label id to the model
self.add_label_to_model(group_of_model_id, connection_id, name)
# add auto note with the label to the model
self.add_auto_label_for_connection(group_of_model_id, connection_id, name)
else:
# This is not necesary, but is a precaution
print_error('Aborting the assignment of the label.')
return False
else:
print_error('There is no dataset selected.')
def add_label_with_filter(self, group_of_model_id, filter):
""" Add a label using the filters to a group of connection ids"""
if __datasets__.current:
dataset_id_standing = __datasets__.current.get_id()
dataset_id = group_of_model_id.split('-')[0]
if str(dataset_id_standing) != dataset_id:
print_error('You should select the dataset you are going to work in. Not another')
return False
if not __groupofgroupofmodels__.get_group(group_of_model_id):
print_error('That group of models does not exist.')
return False
print_warning('Remember that a label should represent a unique behavioral model!')
# Get the base name of the labels
temp_general_name = self.decide_a_label_name("") # Connection id is empty because we are not checking the protos. This is used because we need to assign a label to multiple connections id.
if temp_general_name:
# The general name of the label is the one every connection will share except the final number that will change.
# The general_name_id is the final number that will keep changing
general_name = '-'.join(temp_general_name.split('-')[0:-1])
general_name_id = int(temp_general_name.split('-')[-1])
# Get all the connections from the connection model
group_of_connections_id = int(group_of_model_id.split('-')[0])
group_of_connections = __group_of_group_of_connections__.get_group(group_of_connections_id)
connections = group_of_connections.get_connections()
# Construct the filter
self.construct_filter(filter)
# Check we are using the correct filters
for temp_filter in self.filter:
if temp_filter[0] != "connid" :
print_error('Adding labels with a filter only supports the type of filter connid= and connid!=')
return False
elif temp_filter[1] != "=" and temp_filter[1] != "!=":
print_error('Adding labels with a filter only supports the type of filter connid= and connid!=')
return False
for connection in connections:
connection_id = connection.get_id()
has_label = self.check_label_existance(group_of_model_id, connection_id)
# Get next label id
try:
label_id = self.labels[list(self.labels.keys())[-1]].get_id() + 1
except (KeyError, IndexError):
label_id = 1
# Obtain the name
name = general_name + '-' + str(general_name_id)
proto = general_name.split('-')[2]
label = Label(label_id)
label.set_name(name)
label.add_connection(group_of_model_id, connection_id)
if self.apply_filter(label):
if has_label:
#print_error('This connection from this dataset was already assigned the label id {}. We did not change it.'.format(has_label))
continue
# Add label id to the model
self.add_label_to_model(group_of_model_id, connection_id, name)
# add auto note with the label to the model
self.add_auto_label_for_connection(group_of_model_id, connection_id, name)
self.labels[label_id] = label
general_name_id += 1
else:
del label
else:
# This is not necesary, but is a precaution
print_error('Aborting the assignment of the label.')
return False
else:
print_error('There is no dataset selected.')
def add_label_with_filter(self, group_of_model_id, filter):
""" Add a label using the filters to a group of connection ids"""
if __datasets__.current:
dataset_id_standing = __datasets__.current.get_id()
dataset_id = group_of_model_id.split('-')[0]
if str(dataset_id_standing) != dataset_id:
print_error(
'You should select the dataset you are going to work in. Not another'
)
return False
if not __groupofgroupofmodels__.get_group(group_of_model_id):
print_error('That group of models does not exist.')
return False
print_warning(
'Remember that a label should represent a unique behavioral model!'
)
# Get the base name of the labels
temp_general_name = self.decide_a_label_name(
""
) # Connection id is empty because we are not checking the protos. This is used because we need to assign a label to multiple connections id.
if temp_general_name:
# The general name of the label is the one every connection will share except the final number that will change.
# The general_name_id is the final number that will keep changing
general_name = '-'.join(temp_general_name.split('-')[0:-1])
general_name_id = int(temp_general_name.split('-')[-1])
# Get all the connections from the connection model
group_of_connections_id = int(group_of_model_id.split('-')[0])
group_of_connections = __group_of_group_of_connections__.get_group(
group_of_connections_id)
connections = group_of_connections.get_connections()
# Construct the filter
self.construct_filter(filter)
for connection in connections:
connection_id = connection.get_id()
has_label = self.check_label_existance(
group_of_model_id, connection_id)
# Get next label id
try:
label_id = self.labels[list(
self.labels.keys())[-1]].get_id() + 1
except (KeyError, IndexError):
label_id = 1
# Obtain the name of this connection
name = general_name + '-' + str(general_name_id)
proto = general_name.split('-')[2]
label = Label(label_id)
label.set_name(name)
label.add_connection(group_of_model_id, connection_id)
if self.apply_filter(label,
groupofmodelid=group_of_model_id,
connectionid=connection_id):
if has_label:
# his connection from this dataset was already assigned this id. We did not change it
continue
# Add the label id to the model
self.add_label_to_model(group_of_model_id,
connection_id, name)
# add auto note with the label to the model
self.add_auto_label_for_connection(
group_of_model_id, connection_id, name)
# Update the label list
self.labels[label_id] = label
general_name_id += 1
else:
del label
else:
# This is not necesary, but is a precaution
print_error('Aborting the assignment of the label.')
return False
else:
print_error('There is no dataset selected.')
