def reify_batchcentroid(self, resource_id):
""" Extracts the REST API arguments from the batch centroid
JSON structure:
cluster, dataset and args
"""
child = self.get_resource(resource_id)
# batch resources have 2 different origins as arguments
[(_, parent1), (_, parent2)] = u.get_origin_info(child)
parent1 = self.get_resource(parent1)
parent2 = self.get_resource(parent2)
opts = {"create": {}, "update": {}}
# common create options for batch resources
u.common_batch_options(child, parent1, parent2, opts)
if child.get('header', True):
opts['create'].update(
u.default_setting(child, 'distance_name', [None, '']))
# name, exclude automatic naming alternatives
u.non_automatic_name(child, opts)
calls = u.build_calls(resource_id,
[parent1['resource'], parent2['resource']], opts)
self.add(resource_id, calls)
def reify_batchanomalyscore(self, resource_id):
""" Extracts the REST API arguments from the batch anomaly score
JSON structure:
anomaly detector, dataset and args
"""
child = self.get_resource(resource_id)
# batch resources have 2 different origins as arguments
[(_, parent1),
(_, parent2)] = u.get_origin_info(child)
parent1 = self.get_resource(parent1)
parent2 = self.get_resource(parent2)
opts = {"create": {}, "update": {}}
# common create options for batch resources
u.common_batch_options(child, parent1, parent2, opts)
# name, exclude automatic naming alternatives
u.non_automatic_name(
child, opts)
calls = u.build_calls(
resource_id, [parent1['resource'], parent2['resource']], opts)
self.add(resource_id, calls)
def reify_batchcentroid(self, resource_id):
""" Extracts the REST API arguments from the batch centroid
JSON structure:
cluster, dataset and args
"""
child = self.get_resource(resource_id)
# batch resources have 2 different origins as arguments
[(_, parent1),
(_, parent2)] = u.get_origin_info(child)
parent1 = self.get_resource(parent1)
parent2 = self.get_resource(parent2)
opts = {"create": {}, "update": {}}
# common create options for batch resources
u.common_batch_options(child, parent1, parent2, opts)
if child.get('header', True):
opts['create'].update(
u.default_setting(child, 'distance_name', [None, '']))
# name, exclude automatic naming alternatives
u.non_automatic_name(
child, opts)
calls = u.build_calls(
resource_id, [parent1['resource'], parent2['resource']], opts)
self.add(resource_id, calls)
def reify_batchprediction(self, resource_id):
""" Extracts the REST API arguments from the batch prediction
JSON structure:
model/ensemble, dataset and args
"""
child = self.get_resource(resource_id)
# evalutations have 2 different origins as arguments
[(_, parent1),
(_, parent2)] = u.get_origin_info(child)
parent1 = self.get_resource(parent1)
parent2 = self.get_resource(parent2)
opts = {"create": {}, "update": {}}
# common create options for batch resources
u.common_batch_options(child, parent1, parent2, opts)
if child.get('header', True):
opts['create'].update(
u.default_setting(child, 'prediction_name', [None, '']))
opts['create'].update(
u.default_setting(child, 'centroid_name', [None, '']))
# name, exclude automatic naming alternatives
u.non_automatic_name(
child, opts,
autoname=u'Batch Prediction of %s with %s' % \
(parent1.get('name', ''),
parent2.get('name', '')))
calls = u.build_calls(
resource_id, [parent1['resource'], parent2['resource']], opts)
self.add(resource_id, calls)
def reify_batchanomalyscore(self, resource_id):
""" Extracts the REST API arguments from the batch anomaly score
JSON structure:
anomaly detector, dataset and args
"""
child = self.get_resource(resource_id)
# batch resources have 2 different origins as arguments
[(_, parent1),
(_, parent2)] = u.get_origin_info(child)
parent1 = self.get_resource(parent1)
parent2 = self.get_resource(parent2)
opts = {"create": {}, "update": {}}
# common create options for batch resources
u.common_batch_options(child, parent1, parent2, opts)
# name, exclude automatic naming alternatives
u.non_automatic_name(
child, opts,
autoname=u'Batch Anomaly Score of %s with %s' % \
(parent1.get('name', ''),
parent2.get('name', '')))
calls = u.build_calls(
resource_id, [parent1['resource'], parent2['resource']], opts)
self.add(resource_id, calls)
def reify_batchprediction(self, resource_id):
""" Extracts the REST API arguments from the batch prediction
JSON structure:
model/ensemble, dataset and args
"""
child = self.get_resource(resource_id)
# evalutations have 2 different origins as arguments
[(_, parent1),
(_, parent2)] = u.get_origin_info(child)
parent1 = self.get_resource(parent1)
parent2 = self.get_resource(parent2)
opts = {"create": {}, "update": {}}
# common create options for batch resources
u.common_batch_options(child, parent1, parent2, opts)
if child.get('header', True):
opts['create'].update(
u.default_setting(child, 'prediction_name', [None, '']))
opts['create'].update(
u.default_setting(child, 'centroid_name', [None, '']))
# name, exclude automatic naming alternatives
u.non_automatic_name(
child, opts,
autoname=u'Batch Prediction of %s with %s' % \
(parent1.get('name', ''),
parent2.get('name', '')))
calls = u.build_calls(
resource_id, [parent1['resource'], parent2['resource']], opts)
self.add(resource_id, calls)
