def create_lookup_rdt(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsub_management.create_stream_definition('lookup', parameter_dictionary_id=pdict_id, stream_configuration={'reference_designator':"GA03FLMA-RI001-13-CTDMOG999"})
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
return rdt
def create_lookup_rdt(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsub_management.create_stream_definition('lookup', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
return rdt
def test_lookup_values_ingest_replay(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsub_management.create_stream_definition('lookups', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition, stream_def_id)
stream_id, route = self.pubsub_management.create_stream('example', exchange_point=self.exchange_point_name, stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
ingestion_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
config = DotDict()
config.process.lookup_docs = ['test1', 'test2']
self.ingestion_management.persist_data_stream(stream_id=stream_id, ingestion_configuration_id=ingestion_config_id, dataset_id=dataset_id, config=config)
self.addCleanup(self.ingestion_management.unpersist_data_stream, stream_id, ingestion_config_id)
stored_value_manager = StoredValueManager(self.container)
stored_value_manager.stored_value_cas('test1',{'offset_a':10.0, 'offset_b':13.1})
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = [20.0] * 20
granule = rdt.to_granule()
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(30))
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], np.arange(20))
np.testing.assert_array_almost_equal(rdt_out['temp'], np.array([20.] * 20))
np.testing.assert_array_almost_equal(rdt_out['calibrated'], np.array([30.]*20))
np.testing.assert_array_equal(rdt_out['offset_b'], np.array([rdt_out.fill_value('offset_b')] * 20))
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(20,40)
rdt['temp'] = [20.0] * 20
granule = rdt.to_granule()
dataset_monitor.event.clear()
stored_value_manager.stored_value_cas('test1',{'offset_a':20.0})
stored_value_manager.stored_value_cas('coefficient_document',{'offset_b':10.0})
gevent.sleep(2)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(30))
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], np.arange(40))
np.testing.assert_array_almost_equal(rdt_out['temp'], np.array([20.] * 20 + [20.] * 20))
np.testing.assert_array_equal(rdt_out['offset_b'], np.array([10.] * 40))
np.testing.assert_array_almost_equal(rdt_out['calibrated'], np.array([30.]*20 + [40.]*20))
np.testing.assert_array_almost_equal(rdt_out['calibrated_b'], np.array([40.] * 20 + [50.] * 20))
def test_lookup_values(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsubcli.create_stream_definition('lookup', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsubcli.delete_stream_definition, stream_def_id)
data_product = DataProduct(name='lookup data product')
tdom, sdom = time_series_domain()
data_product.temporal_domain = tdom.dump()
data_product.spatial_domain = sdom.dump()
data_product_id = self.dpsc_cli.create_data_product(data_product, stream_definition_id=stream_def_id)
self.addCleanup(self.dpsc_cli.delete_data_product, data_product_id)
data_producer = DataProducer(name='producer')
data_producer.producer_context = DataProcessProducerContext()
data_producer.producer_context.configuration['qc_keys'] = ['offset_document']
data_producer_id, _ = self.rrclient.create(data_producer)
self.addCleanup(self.rrclient.delete, data_producer_id)
assoc,_ = self.rrclient.create_association(subject=data_product_id, object=data_producer_id, predicate=PRED.hasDataProducer)
self.addCleanup(self.rrclient.delete_association, assoc)
document_keys = self.damsclient.list_qc_references(data_product_id)
self.assertEquals(document_keys, ['offset_document'])
svm = StoredValueManager(self.container)
svm.stored_value_cas('offset_document', {'offset_a':2.0})
self.dpsc_cli.activate_data_product_persistence(data_product_id)
dataset_ids, _ = self.rrclient.find_objects(subject=data_product_id, predicate=PRED.hasDataset, id_only=True)
dataset_id = dataset_ids[0]
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [0]
rdt['temp'] = [20.]
granule = rdt.to_granule()
stream_ids, _ = self.rrclient.find_objects(subject=data_product_id, predicate=PRED.hasStream, id_only=True)
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
publisher = StandaloneStreamPublisher(stream_id, route)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(10))
granule = self.data_retriever.retrieve(dataset_id)
rdt2 = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt['temp'], rdt2['temp'])
np.testing.assert_array_almost_equal(rdt2['calibrated'], np.array([22.0]))
svm.stored_value_cas('updated_document', {'offset_a':3.0})
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ep = EventPublisher(event_type=OT.ExternalReferencesUpdatedEvent)
ep.publish_event(origin=data_product_id, reference_keys=['updated_document'])
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [1]
rdt['temp'] = [20.]
granule = rdt.to_granule()
gevent.sleep(2) # Yield so that the event goes through
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(10))
granule = self.data_retriever.retrieve(dataset_id)
rdt2 = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt2['temp'],np.array([20.,20.]))
np.testing.assert_array_almost_equal(rdt2['calibrated'], np.array([22.0,23.0]))
def test_lookup_values_ingest_replay(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsub_management.create_stream_definition(
'lookups', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsub_management.delete_stream_definition,
stream_def_id)
stream_id, route = self.pubsub_management.create_stream(
'example',
exchange_point=self.exchange_point_name,
stream_definition_id=stream_def_id)
self.addCleanup(self.pubsub_management.delete_stream, stream_id)
ingestion_config_id = self.get_ingestion_config()
dataset_id = self.create_dataset(pdict_id)
config = DotDict()
config.process.lookup_docs = ['test1', 'test2']
self.ingestion_management.persist_data_stream(
stream_id=stream_id,
ingestion_configuration_id=ingestion_config_id,
dataset_id=dataset_id,
config=config)
self.addCleanup(self.ingestion_management.unpersist_data_stream,
stream_id, ingestion_config_id)
stored_value_manager = StoredValueManager(self.container)
stored_value_manager.stored_value_cas('test1', {
'offset_a': 10.0,
'offset_b': 13.1
})
publisher = StandaloneStreamPublisher(stream_id, route)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(20)
rdt['temp'] = [20.0] * 20
granule = rdt.to_granule()
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(30))
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], np.arange(20))
np.testing.assert_array_almost_equal(rdt_out['temp'],
np.array([20.] * 20))
np.testing.assert_array_almost_equal(rdt_out['calibrated'],
np.array([30.] * 20))
np.testing.assert_array_equal(
rdt_out['offset_b'],
np.array([rdt_out.fill_value('offset_b')] * 20))
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = np.arange(20, 40)
rdt['temp'] = [20.0] * 20
granule = rdt.to_granule()
dataset_monitor.event.clear()
stored_value_manager.stored_value_cas('test1', {'offset_a': 20.0})
stored_value_manager.stored_value_cas('coefficient_document',
{'offset_b': 10.0})
gevent.sleep(2)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(30))
replay_granule = self.data_retriever.retrieve(dataset_id)
rdt_out = RecordDictionaryTool.load_from_granule(replay_granule)
np.testing.assert_array_almost_equal(rdt_out['time'], np.arange(40))
np.testing.assert_array_almost_equal(rdt_out['temp'],
np.array([20.] * 20 + [20.] * 20))
np.testing.assert_array_equal(rdt_out['offset_b'],
np.array([10.] * 40))
np.testing.assert_array_almost_equal(rdt_out['calibrated'],
np.array([30.] * 20 + [40.] * 20))
np.testing.assert_array_almost_equal(rdt_out['calibrated_b'],
np.array([40.] * 20 + [50.] * 20))
def test_lookup_values(self):
ph = ParameterHelper(self.dataset_management, self.addCleanup)
pdict_id = ph.create_lookups()
stream_def_id = self.pubsubcli.create_stream_definition(
'lookup', parameter_dictionary_id=pdict_id)
self.addCleanup(self.pubsubcli.delete_stream_definition, stream_def_id)
data_product = DataProduct(name='lookup data product')
tdom, sdom = time_series_domain()
data_product.temporal_domain = tdom.dump()
data_product.spatial_domain = sdom.dump()
data_product_id = self.dpsc_cli.create_data_product(
data_product, stream_definition_id=stream_def_id)
self.addCleanup(self.dpsc_cli.delete_data_product, data_product_id)
data_producer = DataProducer(name='producer')
data_producer.producer_context = DataProcessProducerContext()
data_producer.producer_context.configuration['qc_keys'] = [
'offset_document'
]
data_producer_id, _ = self.rrclient.create(data_producer)
self.addCleanup(self.rrclient.delete, data_producer_id)
assoc, _ = self.rrclient.create_association(
subject=data_product_id,
object=data_producer_id,
predicate=PRED.hasDataProducer)
self.addCleanup(self.rrclient.delete_association, assoc)
document_keys = self.damsclient.list_qc_references(data_product_id)
self.assertEquals(document_keys, ['offset_document'])
svm = StoredValueManager(self.container)
svm.stored_value_cas('offset_document', {'offset_a': 2.0})
self.dpsc_cli.activate_data_product_persistence(data_product_id)
dataset_ids, _ = self.rrclient.find_objects(subject=data_product_id,
predicate=PRED.hasDataset,
id_only=True)
dataset_id = dataset_ids[0]
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [0]
rdt['temp'] = [20.]
granule = rdt.to_granule()
stream_ids, _ = self.rrclient.find_objects(subject=data_product_id,
predicate=PRED.hasStream,
id_only=True)
stream_id = stream_ids[0]
route = self.pubsubcli.read_stream_route(stream_id=stream_id)
publisher = StandaloneStreamPublisher(stream_id, route)
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(10))
granule = self.data_retriever.retrieve(dataset_id)
rdt2 = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt['temp'], rdt2['temp'])
np.testing.assert_array_almost_equal(rdt2['calibrated'],
np.array([22.0]))
svm.stored_value_cas('updated_document', {'offset_a': 3.0})
dataset_monitor = DatasetMonitor(dataset_id)
self.addCleanup(dataset_monitor.stop)
ep = EventPublisher(event_type=OT.ExternalReferencesUpdatedEvent)
ep.publish_event(origin=data_product_id,
reference_keys=['updated_document'])
rdt = RecordDictionaryTool(stream_definition_id=stream_def_id)
rdt['time'] = [1]
rdt['temp'] = [20.]
granule = rdt.to_granule()
gevent.sleep(2) # Yield so that the event goes through
publisher.publish(granule)
self.assertTrue(dataset_monitor.event.wait(10))
granule = self.data_retriever.retrieve(dataset_id)
rdt2 = RecordDictionaryTool.load_from_granule(granule)
np.testing.assert_array_equal(rdt2['temp'], np.array([20., 20.]))
np.testing.assert_array_almost_equal(rdt2['calibrated'],
np.array([22.0, 23.0]))
