def __init__(self, taxonomy, shape=None):
"""
@brief Initialize a new instance of Record Dictionary Tool with a taxonomy and an optional fixed length
@param taxonomy is an instance of a TaxonomyTool or Taxonomy (IonObject) used in this record dictionary
@param length is an optional fixed length for the value sequences of this record dictionary
"""
if not isinstance(shape, (_NoneType, int, tuple)):
raise TypeError(
'Invalid shape argument, received type "%s"; should be None or int or tuple'
% type(shape))
self._rd = {}
self._shp = shape
if isinstance(self._shp, int):
self._shp = (self._shp, )
# hold onto the taxonomy - we need it to build the granule...
if isinstance(taxonomy, TaxyTool):
self._tx = taxonomy
elif isinstance(taxonomy, Taxonomy):
self._tx = TaxyTool(taxonomy)
else:
raise TypeError(
'Invalid taxonomy argument, received type "%s"; should be Taxonomy or TaxyTool'
% type(taxonomy))
def load_from_granule(cls, g):
"""
@brief return an instance of Record Dictionary Tool from a granule. Used when a granule is received in a message
"""
result = cls(TaxyTool(g.taxonomy))
result._rd = g.record_dictionary
return result
def test_extend_names(self):
tc = TaxyTool()
tc.add_taxonomy_set('1', 'a')
tc.add_taxonomy_set('2', 'a')
self.assertEquals(tc.get_handles('1'), {
0,
})
self.assertEquals(tc.get_handles('2'), {
1,
})
self.assertEquals(tc.get_names_by_handle(0), {
'1',
'a',
})
self.assertEquals(tc.get_names_by_handle(1), {
'2',
'a',
})
tc.extend_names_by_nick_name('1', 'c', 'e')
tc.extend_names_by_nick_name('2', 'z', 'x')
tc.extend_names_by_nick_name('1', 'd', 'f')
self.assertEquals(tc.get_handles('a'), {0, 1})
self.assertEquals(tc.get_handles('z'), {
1,
})
self.assertEquals(tc.get_handles('c'), {
0,
})
#Test for a name that isn't in the taxonomy
self.assertEquals(tc.get_handles('b'), {
-1,
})
self.assertEquals(tc.get_names_by_handle(0), {
'1',
'a',
'c',
'e',
'd',
'f',
})
self.assertEquals(tc.get_names_by_handle(1), {
'2',
'a',
'z',
'x',
})
tc.extend_names_by_anyname('a', 'extend')
self.assertEquals(tc.get_handles('extend'), {
0,
1,
})
def test_get_nick_names(self):
tc = TaxyTool()
tc.add_taxonomy_set('1', 'a')
tc.add_taxonomy_set('2', 'a')
self.assertEquals(tc.get_nick_name(0), '1')
self.assertEquals(tc.get_nick_names('a'), ['1', '2'])
self.assertEquals(tc.get_handle('1'), 0)
self.assertEquals(tc.get_handles('a'), {0, 1})
def test_build_granule_and_load_from_granule(self):
#Define a taxonomy and add sets. add_taxonomy_set takes one or more names and assigns them to one handle
tx = TaxyTool()
tx.add_taxonomy_set('temp', 'long_temp_name')
tx.add_taxonomy_set('cond', 'long_cond_name')
tx.add_taxonomy_set('pres', 'long_pres_name')
tx.add_taxonomy_set('rdt')
# map is {<local name>: <granule name or path>}
#Use RecordDictionaryTool to create a record dictionary. Send in the taxonomy so the Tool knows what to expect
rdt = RecordDictionaryTool(taxonomy=tx)
#Create some arrays and fill them with random values
temp_array = numpy.random.standard_normal(100)
cond_array = numpy.random.standard_normal(100)
pres_array = numpy.random.standard_normal(100)
#Use the RecordDictionaryTool to add the values. This also would work if you used long_temp_name, etc.
rdt['temp'] = temp_array
rdt['cond'] = cond_array
rdt['pres'] = pres_array
#You can also add in another RecordDictionaryTool, providing the taxonomies are the same.
rdt2 = RecordDictionaryTool(taxonomy=tx)
rdt2['temp'] = temp_array
rdt['rdt'] = rdt2
g = build_granule(data_producer_id='john',
taxonomy=tx,
record_dictionary=rdt)
l_tx = TaxyTool.load_from_granule(g)
l_rd = RecordDictionaryTool.load_from_granule(g)
# Make sure we got back the same Taxonomy Object
self.assertEquals(l_tx._t, tx._t)
self.assertEquals(l_tx.get_handles('temp'), tx.get_handles('temp'))
self.assertEquals(l_tx.get_handles('testing_2'),
tx.get_handles('testing_2'))
# Now test the record dictionary object
self.assertEquals(l_rd._rd, rdt._rd)
self.assertEquals(l_rd._tx._t, rdt._tx._t)
for k, v in l_rd.iteritems():
self.assertIn(k, rdt)
if isinstance(v, numpy.ndarray):
self.assertTrue((v == rdt[k]).all())
else:
self.assertEquals(v._rd, rdt[k]._rd)
def test_init(self):
"""
test initialization of the TaxyCab
"""
tc = TaxyTool()
self.assertRaises(KeyError, tc.get_handle, 'nick_name')
self.assertRaises(KeyError, tc.get_names_by_handle, 0)
tx = Taxonomy(map={1: ('nick_name', {'nick_name', 'a'})})
tc2 = TaxyTool(taxonomy=tx)
self.assertEquals(tc2._cnt, 1)
self.assertEquals(tc2.get_handles('a'), {
1,
})
self.assertEquals(tc2.get_handle('nick_name'), 1)
tc3 = TaxyTool(tx)
self.assertEquals(tc3.get_names_by_handle(1), {'nick_name', 'a'})
def _setup_resources(self):
stream_id = self.create_stream_and_logger(name='fibonacci_stream')
tx = TaxyTool()
tx.add_taxonomy_set('data', 'external_data')
#TG: Build TaxonomyTool & add to dh_cfg.taxonomy
self.DVR_CONFIG['dh_cfg'] = {
'TESTING': True,
'stream_id': stream_id,
'data_producer_id': 'fibonacci_data_producer_id',
'taxonomy': tx.dump(),
'max_records': 4,
}
def _setup_resources(self):
stream_id = self.create_stream_and_logger(name='dummydata_stream')
tx = TaxyTool()
tx.add_taxonomy_set('data', 'external_data')
self.DVR_CONFIG['dh_cfg'] = {
'TESTING': True,
'stream_id':
stream_id, #TODO: This should probably be a 'stream_config' dict with stream_name:stream_id members
'data_producer_id': 'dummy_data_producer_id',
'taxonomy': tx.dump(),
'max_records': 4,
}
def launch_benchmark(transform_number=1, primer=1, message_length=4):
import gevent
from gevent.greenlet import Greenlet
from pyon.util.containers import DotDict
from pyon.net.transport import NameTrio
from pyon.net.endpoint import Publisher
import numpy
from pyon.ion.granule.record_dictionary import RecordDictionaryTool
from pyon.ion.granule.taxonomy import TaxyTool
from pyon.ion.granule.granule import build_granule
tt = TaxyTool()
tt.add_taxonomy_set('a')
import uuid
num = transform_number
msg_len = message_length
transforms = list()
pids = 1
TransformBenchTesting.message_length = message_length
cc = Container.instance
pub = Publisher(to_name=NameTrio(get_sys_name(),
str(uuid.uuid4())[0:6]))
for i in xrange(num):
tbt = cc.proc_manager._create_service_instance(
str(pids), 'tbt', 'prototype.transforms.linear',
'TransformInPlaceNewGranule',
DotDict({
'process': {
'name': 'tbt%d' % pids,
'transform_id': pids
}
}))
tbt.init()
tbt.start()
gevent.sleep(0.2)
for i in xrange(primer):
rd = RecordDictionaryTool(tt, message_length)
rd['a'] = numpy.arange(message_length)
gran = build_granule(data_producer_id='dp_id',
taxonomy=tt,
record_dictionary=rd)
pub.publish(gran)
g = Greenlet(tbt.perf)
g.start()
transforms.append(tbt)
pids += 1
def test_combine_granule(self):
tt = TaxyTool()
tt.add_taxonomy_set('a')
rdt = RecordDictionaryTool(tt)
rdt['a'] = numpy.array([1, 2, 3])
granule1 = build_granule('test', tt, rdt)
rdt = RecordDictionaryTool(tt)
rdt['a'] = numpy.array([4, 5, 6])
granule2 = build_granule('test', tt, rdt)
granule3 = combine_granules(granule1, granule2)
rdt = RecordDictionaryTool.load_from_granule(granule3)
self.assertTrue(
numpy.allclose(rdt['a'], numpy.array([1, 2, 3, 4, 5, 6])))
def test_yamlize(self):
tc = TaxyTool()
tc.add_taxonomy_set('1', 'a')
tc.add_taxonomy_set('2', 'b')
tc.extend_names_by_nick_name('1', 'x')
tc.extend_names_by_anyname('a', 'z')
tc.extend_names_by_anyname('b', 'c')
s = tc.dump()
tc2 = TaxyTool.load(s)
#@todo - a list is not a set and the yaml dump/ion serialization can not handle sets...
self.assertEquals(tc2._cnt, 1)
self.assertEquals(tc2.get_names_by_handle(0), {
'1',
'x',
'a',
'z',
})
self.assertEquals(tc2.get_names_by_handle(1), {
'2',
'b',
'c',
})
self.assertEquals(tc._cnt, 1)
self.assertEquals(tc.get_names_by_handle(0), {
'1',
'x',
'a',
'z',
})
self.assertEquals(tc.get_names_by_handle(1), {
'2',
'b',
'c',
})
def _setup_resources(self):
# TODO: some or all of this (or some variation) should move to DAMS'
# Build the test resources for the dataset
dams_cli = DataAcquisitionManagementServiceClient()
dpms_cli = DataProductManagementServiceClient()
rr_cli = ResourceRegistryServiceClient()
eda = ExternalDatasetAgent()
eda_id = dams_cli.create_external_dataset_agent(eda)
eda_inst = ExternalDatasetAgentInstance()
eda_inst_id = dams_cli.create_external_dataset_agent_instance(
eda_inst, external_dataset_agent_id=eda_id)
# Create and register the necessary resources/objects
# Create DataProvider
dprov = ExternalDataProvider(institution=Institution(),
contact=ContactInformation())
dprov.contact.name = 'Christopher Mueller'
dprov.contact.email = '*****@*****.**'
# Create DataSource
dsrc = DataSource(protocol_type='DAP',
institution=Institution(),
contact=ContactInformation())
dsrc.connection_params['base_data_url'] = ''
dsrc.contact.name = 'Tim Giguere'
dsrc.contact.email = '*****@*****.**'
# Create ExternalDataset
ds_name = 'usgs_test_dataset'
dset = ExternalDataset(name=ds_name,
dataset_description=DatasetDescription(),
update_description=UpdateDescription(),
contact=ContactInformation())
# The usgs.nc test dataset is a download of the R1 dataset found here:
# http://thredds-test.oceanobservatories.org/thredds/dodsC/ooiciData/E66B1A74-A684-454A-9ADE-8388C2C634E5.ncml
dset.dataset_description.parameters[
'dataset_path'] = 'test_data/usgs.nc'
dset.dataset_description.parameters['temporal_dimension'] = 'time'
dset.dataset_description.parameters['zonal_dimension'] = 'lon'
dset.dataset_description.parameters['meridional_dimension'] = 'lat'
dset.dataset_description.parameters['vertical_dimension'] = 'z'
dset.dataset_description.parameters['variables'] = [
'water_temperature',
'streamflow',
'water_temperature_bottom',
'water_temperature_middle',
'specific_conductance',
'data_qualifier',
]
# Create DataSourceModel
dsrc_model = DataSourceModel(name='dap_model')
dsrc_model.model = 'DAP'
dsrc_model.data_handler_module = 'N/A'
dsrc_model.data_handler_class = 'N/A'
## Run everything through DAMS
ds_id = dams_cli.create_external_dataset(external_dataset=dset)
ext_dprov_id = dams_cli.create_external_data_provider(
external_data_provider=dprov)
ext_dsrc_id = dams_cli.create_data_source(data_source=dsrc)
ext_dsrc_model_id = dams_cli.create_data_source_model(dsrc_model)
# Register the ExternalDataset
dproducer_id = dams_cli.register_external_data_set(
external_dataset_id=ds_id)
# Or using each method
dams_cli.assign_data_source_to_external_data_provider(
data_source_id=ext_dsrc_id, external_data_provider_id=ext_dprov_id)
dams_cli.assign_data_source_to_data_model(
data_source_id=ext_dsrc_id, data_source_model_id=ext_dsrc_model_id)
dams_cli.assign_external_dataset_to_data_source(
external_dataset_id=ds_id, data_source_id=ext_dsrc_id)
dams_cli.assign_external_dataset_to_agent_instance(
external_dataset_id=ds_id, agent_instance_id=eda_inst_id)
# dams_cli.assign_external_data_agent_to_agent_instance(external_data_agent_id=self.eda_id, agent_instance_id=self.eda_inst_id)
# Generate the data product and associate it to the ExternalDataset
dprod = DataProduct(name='usgs_parsed_product',
description='parsed usgs product')
dproduct_id = dpms_cli.create_data_product(data_product=dprod)
dams_cli.assign_data_product(input_resource_id=ds_id,
data_product_id=dproduct_id,
create_stream=True)
stream_id, assn = rr_cli.find_objects(subject=dproduct_id,
predicate=PRED.hasStream,
object_type=RT.Stream,
id_only=True)
stream_id = stream_id[0]
log.info('Created resources: {0}'.format({
'ExternalDataset': ds_id,
'ExternalDataProvider': ext_dprov_id,
'DataSource': ext_dsrc_id,
'DataSourceModel': ext_dsrc_model_id,
'DataProducer': dproducer_id,
'DataProduct': dproduct_id,
'Stream': stream_id
}))
#CBM: Use CF standard_names
ttool = TaxyTool()
ttool.add_taxonomy_set('time', 'time')
ttool.add_taxonomy_set('lon', 'longitude')
ttool.add_taxonomy_set('lat', 'latitude')
ttool.add_taxonomy_set('z', 'water depth')
ttool.add_taxonomy_set('water_temperature',
'average water temperature')
ttool.add_taxonomy_set('water_temperature_bottom',
'water temperature at bottom of water column')
ttool.add_taxonomy_set('water_temperature_middle',
'water temperature at middle of water column')
ttool.add_taxonomy_set('streamflow', 'flow velocity of stream')
ttool.add_taxonomy_set('specific_conductance',
'specific conductance of water')
ttool.add_taxonomy_set('data_qualifier', 'data qualifier flag')
ttool.add_taxonomy_set('coords',
'This group contains coordinate parameters')
ttool.add_taxonomy_set('data', 'This group contains data parameters')
# Create the logger for receiving publications
self.create_stream_and_logger(name='usgs', stream_id=stream_id)
self.EDA_RESOURCE_ID = ds_id
self.EDA_NAME = ds_name
self.DVR_CONFIG['dh_cfg'] = {
'TESTING': True,
'stream_id': stream_id,
'taxonomy': ttool.dump(),
'data_producer_id':
dproducer_id, #CBM: Should this be put in the main body of the config - with mod & cls?
'max_records': 4,
}
def test_eq(self):
tx1 = Taxonomy(
map={
1: ('nick_name', {'nick_name', 'a'}),
2: ('nick2', {'nick2', 'a', 'b', 'cc'})
})
# pass with tt1._t.map "is"
tt1 = TaxyTool(tx1)
tt2 = TaxyTool(tx1)
self.assertEquals(tt1, tt2)
# after changes - thy are still the same
tt2.add_taxonomy_set('new_name', 'p', 'q', 'r')
self.assertEquals(tt2, tt1)
# pass with 'is'
tt3 = tt1
self.assertEquals(tt3, tt1)
# after changes - thy are still the same
tt3.add_taxonomy_set('new_name', 'p', 'q', 'r')
self.assertEquals(tt1, tt3)
# pass with tt1._t.map '=='
tx1 = Taxonomy(
map={
1: ('nick_name', {'nick_name', 'a'}),
2: ('nick2', {'nick2', 'a', 'b', 'cc'})
})
tx2 = Taxonomy(
map={
1: ('nick_name', {'nick_name', 'a'}),
2: ('nick2', {'nick2', 'a', 'b', 'cc'})
})
self.assertNotEquals(tx1, tx2)
self.assertEquals(tx1.map, tx2.map)
tt1 = TaxyTool(tx1)
tt2 = TaxyTool(tx2)
self.assertEquals(tt1, tt2)
# fail with tt1._t.map '=='
tx2 = Taxonomy(
map={
1: ('nick_name', {'nick_name', 'as'}),
2: ('nick2', {'nick2', 'a', 'b', 'cc'})
})
tt1 = TaxyTool(tx1)
tt2 = TaxyTool(tx2)
self.assertNotEquals(tt1, tt2)
# Use the interface to build a complex one and test equality as they go in and out of sync...
tt1 = TaxyTool()
tt2 = TaxyTool()
tt1.add_taxonomy_set('a name', 'junk', '1', '2')
tt2.add_taxonomy_set('a name', 'junk', '1', '2')
self.assertEquals(tt1, tt2)
tt2.add_taxonomy_set('new_name', '1')
self.assertNotEquals(tt1, tt2)
tt1.extend_names_by_nick_name('a name', '3')
tt2.extend_names_by_nick_name('a name', '3')
tt1.add_taxonomy_set('new_name', '1')
self.assertEquals(tt1, tt2)
def test_taxonomy_set(self):
nick_name = 'nick_name'
a = 'a'
b = 'b'
c = 'c'
tc = TaxyTool()
tc.add_taxonomy_set(nick_name=nick_name)
self.assertEquals(tc.get_handles('a name'), {
-1,
})
self.assertRaises(KeyError, tc.get_names_by_handle, 5)
self.assertEquals(tc.get_names_by_handle(0), {
nick_name,
})
tc = TaxyTool()
tc.add_taxonomy_set(a)
self.assertEquals(tc.get_handle(a), 0)
self.assertEquals(tc.get_names_by_handle(0), {
a,
})
self.assertEquals(tc.get_names_by_nick_name(a), {
a,
})
tc = TaxyTool()
tc.add_taxonomy_set(a)
tc.add_taxonomy_set(b)
self.assertEquals(tc.get_handle(a), 0)
self.assertEquals(tc.get_names_by_handle(0), {
a,
})
self.assertEquals(tc.get_handle(b), 1)
self.assertEquals(tc.get_names_by_handle(1), {
b,
})
tc = TaxyTool()
tc.add_taxonomy_set(nick_name, a, b, c)
self.assertEquals(tc.get_handle(nick_name), 0)
self.assertEquals(tc.get_handles(a), {
0,
})
self.assertEquals(tc.get_handles(b), {
0,
})
self.assertEquals(tc.get_handles(c), {
0,
})
self.assertEquals(tc.get_names_by_handle(0), {
nick_name,
a,
b,
c,
})
self.assertEquals(tc.get_names_by_nick_name(nick_name), {
nick_name,
a,
b,
c,
})
def _setup_resources(self):
# TODO: some or all of this (or some variation) should move to DAMS'
# Build the test resources for the dataset
dams_cli = DataAcquisitionManagementServiceClient()
dpms_cli = DataProductManagementServiceClient()
rr_cli = ResourceRegistryServiceClient()
eda = ExternalDatasetAgent()
eda_id = dams_cli.create_external_dataset_agent(eda)
eda_inst = ExternalDatasetAgentInstance()
eda_inst_id = dams_cli.create_external_dataset_agent_instance(eda_inst, external_dataset_agent_id=eda_id)
# Create and register the necessary resources/objects
# Create DataProvider
dprov = ExternalDataProvider(institution=Institution(), contact=ContactInformation())
dprov.contact.name = 'Christopher Mueller'
dprov.contact.email = '*****@*****.**'
# Create DataSource
dsrc = DataSource(protocol_type='FILE', institution=Institution(), contact=ContactInformation())
dsrc.connection_params['base_data_url'] = ''
dsrc.contact.name='Tim Giguere'
dsrc.contact.email = '*****@*****.**'
# Create ExternalDataset
ds_name = 'slocum_test_dataset'
dset = ExternalDataset(name=ds_name, dataset_description=DatasetDescription(), update_description=UpdateDescription(), contact=ContactInformation())
dset.dataset_description.parameters['dataset_path'] = 'test_data/ru05-2012-021-0-0-sbd.dat'
dset.dataset_description.parameters['temporal_dimension'] = None
dset.dataset_description.parameters['zonal_dimension'] = None
dset.dataset_description.parameters['meridional_dimension'] = None
dset.dataset_description.parameters['vertical_dimension'] = None
dset.dataset_description.parameters['variables'] = [
'c_wpt_y_lmc',
'sci_water_cond',
'm_y_lmc',
'u_hd_fin_ap_inflection_holdoff',
'sci_m_present_time',
'm_leakdetect_voltage_forward',
'sci_bb3slo_b660_scaled',
'c_science_send_all',
'm_gps_status',
'm_water_vx',
'm_water_vy',
'c_heading',
'sci_fl3slo_chlor_units',
'u_hd_fin_ap_gain',
'm_vacuum',
'u_min_water_depth',
'm_gps_lat',
'm_veh_temp',
'f_fin_offset',
'u_hd_fin_ap_hardover_holdoff',
'c_alt_time',
'm_present_time',
'm_heading',
'sci_bb3slo_b532_scaled',
'sci_fl3slo_cdom_units',
'm_fin',
'x_cycle_overrun_in_ms',
'sci_water_pressure',
'u_hd_fin_ap_igain',
'sci_fl3slo_phyco_units',
'm_battpos',
'sci_bb3slo_b470_scaled',
'm_lat',
'm_gps_lon',
'sci_ctd41cp_timestamp',
'm_pressure',
'c_wpt_x_lmc',
'c_ballast_pumped',
'x_lmc_xy_source',
'm_lon',
'm_avg_speed',
'sci_water_temp',
'u_pitch_ap_gain',
'm_roll',
'm_tot_num_inflections',
'm_x_lmc',
'u_pitch_ap_deadband',
'm_final_water_vy',
'm_final_water_vx',
'm_water_depth',
'm_leakdetect_voltage',
'u_pitch_max_delta_battpos',
'm_coulomb_amphr',
'm_pitch',
]
# Create DataSourceModel
dsrc_model = DataSourceModel(name='slocum_model')
dsrc_model.model = 'SLOCUM'
dsrc_model.data_handler_module = 'N/A'
dsrc_model.data_handler_class = 'N/A'
## Run everything through DAMS
ds_id = dams_cli.create_external_dataset(external_dataset=dset)
ext_dprov_id = dams_cli.create_external_data_provider(external_data_provider=dprov)
ext_dsrc_id = dams_cli.create_data_source(data_source=dsrc)
ext_dsrc_model_id = dams_cli.create_data_source_model(dsrc_model)
# Register the ExternalDataset
dproducer_id = dams_cli.register_external_data_set(external_dataset_id=ds_id)
# Or using each method
dams_cli.assign_data_source_to_external_data_provider(data_source_id=ext_dsrc_id, external_data_provider_id=ext_dprov_id)
dams_cli.assign_data_source_to_data_model(data_source_id=ext_dsrc_id, data_source_model_id=ext_dsrc_model_id)
dams_cli.assign_external_dataset_to_data_source(external_dataset_id=ds_id, data_source_id=ext_dsrc_id)
dams_cli.assign_external_dataset_to_agent_instance(external_dataset_id=ds_id, agent_instance_id=eda_inst_id)
# dams_cli.assign_external_data_agent_to_agent_instance(external_data_agent_id=self.eda_id, agent_instance_id=self.eda_inst_id)
# Generate the data product and associate it to the ExternalDataset
dprod = DataProduct(name='slocum_parsed_product', description='parsed slocum product')
dproduct_id = dpms_cli.create_data_product(data_product=dprod)
dams_cli.assign_data_product(input_resource_id=ds_id, data_product_id=dproduct_id, create_stream=True)
stream_id, assn = rr_cli.find_objects(subject=dproduct_id, predicate=PRED.hasStream, object_type=RT.Stream, id_only=True)
stream_id = stream_id[0]
log.info('Created resources: {0}'.format({'ExternalDataset':ds_id, 'ExternalDataProvider':ext_dprov_id, 'DataSource':ext_dsrc_id, 'DataSourceModel':ext_dsrc_model_id, 'DataProducer':dproducer_id, 'DataProduct':dproduct_id, 'Stream':stream_id}))
#CBM: Use CF standard_names
ttool = TaxyTool()
ttool.add_taxonomy_set('c_wpt_y_lmc'),
ttool.add_taxonomy_set('sci_water_cond'),
ttool.add_taxonomy_set('m_y_lmc'),
ttool.add_taxonomy_set('u_hd_fin_ap_inflection_holdoff'),
ttool.add_taxonomy_set('sci_m_present_time'),
ttool.add_taxonomy_set('m_leakdetect_voltage_forward'),
ttool.add_taxonomy_set('sci_bb3slo_b660_scaled'),
ttool.add_taxonomy_set('c_science_send_all'),
ttool.add_taxonomy_set('m_gps_status'),
ttool.add_taxonomy_set('m_water_vx'),
ttool.add_taxonomy_set('m_water_vy'),
ttool.add_taxonomy_set('c_heading'),
ttool.add_taxonomy_set('sci_fl3slo_chlor_units'),
ttool.add_taxonomy_set('u_hd_fin_ap_gain'),
ttool.add_taxonomy_set('m_vacuum'),
ttool.add_taxonomy_set('u_min_water_depth'),
ttool.add_taxonomy_set('m_gps_lat'),
ttool.add_taxonomy_set('m_veh_temp'),
ttool.add_taxonomy_set('f_fin_offset'),
ttool.add_taxonomy_set('u_hd_fin_ap_hardover_holdoff'),
ttool.add_taxonomy_set('c_alt_time'),
ttool.add_taxonomy_set('m_present_time'),
ttool.add_taxonomy_set('m_heading'),
ttool.add_taxonomy_set('sci_bb3slo_b532_scaled'),
ttool.add_taxonomy_set('sci_fl3slo_cdom_units'),
ttool.add_taxonomy_set('m_fin'),
ttool.add_taxonomy_set('x_cycle_overrun_in_ms'),
ttool.add_taxonomy_set('sci_water_pressure'),
ttool.add_taxonomy_set('u_hd_fin_ap_igain'),
ttool.add_taxonomy_set('sci_fl3slo_phyco_units'),
ttool.add_taxonomy_set('m_battpos'),
ttool.add_taxonomy_set('sci_bb3slo_b470_scaled'),
ttool.add_taxonomy_set('m_lat'),
ttool.add_taxonomy_set('m_gps_lon'),
ttool.add_taxonomy_set('sci_ctd41cp_timestamp'),
ttool.add_taxonomy_set('m_pressure'),
ttool.add_taxonomy_set('c_wpt_x_lmc'),
ttool.add_taxonomy_set('c_ballast_pumped'),
ttool.add_taxonomy_set('x_lmc_xy_source'),
ttool.add_taxonomy_set('m_lon'),
ttool.add_taxonomy_set('m_avg_speed'),
ttool.add_taxonomy_set('sci_water_temp'),
ttool.add_taxonomy_set('u_pitch_ap_gain'),
ttool.add_taxonomy_set('m_roll'),
ttool.add_taxonomy_set('m_tot_num_inflections'),
ttool.add_taxonomy_set('m_x_lmc'),
ttool.add_taxonomy_set('u_pitch_ap_deadband'),
ttool.add_taxonomy_set('m_final_water_vy'),
ttool.add_taxonomy_set('m_final_water_vx'),
ttool.add_taxonomy_set('m_water_depth'),
ttool.add_taxonomy_set('m_leakdetect_voltage'),
ttool.add_taxonomy_set('u_pitch_max_delta_battpos'),
ttool.add_taxonomy_set('m_coulomb_amphr'),
ttool.add_taxonomy_set('m_pitch'),
#CBM: Eventually, probably want to group this crap somehow - not sure how yet...
# Create the logger for receiving publications
self.create_stream_and_logger(name='slocum',stream_id=stream_id)
self.EDA_RESOURCE_ID = ds_id
self.EDA_NAME = ds_name
self.DVR_CONFIG['dh_cfg'] = {
'TESTING':True,
'stream_id':stream_id,
'external_dataset_res':dset,
'taxonomy':ttool.dump(),
'data_producer_id':dproducer_id,#CBM: Should this be put in the main body of the config - with mod & cls?
'max_records':20,
}
# Inherit some old machinery for this example
from ion.processes.data.ctd_stream_publisher import SimpleCtdPublisher
### For new granule and stream interface
from pyon.ion.granule.record_dictionary import RecordDictionaryTool
from pyon.ion.granule.taxonomy import TaxyTool
from pyon.ion.granule.granule import build_granule
from pyon.public import log
import numpy
import random
import time
### Taxonomies are defined before hand out of band... somehow.
tx = TaxyTool()
tx.add_taxonomy_set('temp','long name for temp')
tx.add_taxonomy_set('cond','long name for cond')
tx.add_taxonomy_set('lat','long name for latitude')
tx.add_taxonomy_set('lon','long name for longitude')
tx.add_taxonomy_set('pres','long name for pres')
tx.add_taxonomy_set('time','long name for time')
# This is an example of using groups it is not a normative statement about how to use groups
tx.add_taxonomy_set('group1','This group contains coordinates...')
tx.add_taxonomy_set('group0','This group contains data...')
tx.add_taxonomy_set('raw_fixed','Fixed length bytes in an array of records')
tx.add_taxonomy_set('raw_blob','Unlimited length bytes in an array')
class ExampleDataProducer(SimpleCtdPublisher):
def test_activateDatasetAgent(self):
# Create ExternalDatasetModel
datsetModel_obj = IonObject(RT.ExternalDatasetModel,
name='ExampleDatasetModel',
description="ExampleDatasetModel",
datset_type="FibSeries")
try:
datasetModel_id = self.damsclient.create_external_dataset_model(
datsetModel_obj)
except BadRequest as ex:
self.fail("failed to create new ExternalDatasetModel: %s" % ex)
log.debug(
"TestExternalDatasetAgentMgmt: new ExternalDatasetModel id = %s",
str(datasetModel_id))
# Create ExternalDatasetAgent
datasetAgent_obj = IonObject(RT.ExternalDatasetAgent,
name='datasetagent007',
description="datasetagent007",
handler_module=EDA_MOD,
handler_class=EDA_CLS)
try:
datasetAgent_id = self.damsclient.create_external_dataset_agent(
datasetAgent_obj, datasetModel_id)
except BadRequest as ex:
self.fail("failed to create new ExternalDatasetAgent: %s" % ex)
log.debug(
"TestExternalDatasetAgentMgmt: new ExternalDatasetAgent id = %s",
str(datasetAgent_id))
# Create ExternalDataset
log.debug(
'TestExternalDatasetAgentMgmt: Create external dataset resource ')
extDataset_obj = IonObject(RT.ExternalDataset,
name='ExtDataset',
description="ExtDataset")
try:
extDataset_id = self.damsclient.create_external_dataset(
extDataset_obj, datasetModel_id)
except BadRequest as ex:
self.fail("failed to create new external dataset resource: %s" %
ex)
log.debug(
"TestExternalDatasetAgentMgmt: new ExternalDataset id = %s ",
str(extDataset_id))
#register the dataset as a data producer
dproducer_id = self.damsclient.register_external_data_set(
extDataset_id)
# create a stream definition for the data from the ctd simulator
ctd_stream_def = SBE37_CDM_stream_definition()
ctd_stream_def_id = self.pubsubcli.create_stream_definition(
container=ctd_stream_def)
log.debug(
"TestExternalDatasetAgentMgmt: new Stream Definition id = %s",
str(ctd_stream_def_id))
log.debug(
"TestExternalDatasetAgentMgmt: Creating new data product with a stream definition"
)
dp_obj = IonObject(RT.DataProduct,
name='eoi dataset data',
description=' stream test')
try:
data_product_id1 = self.dpclient.create_data_product(
dp_obj, ctd_stream_def_id)
except BadRequest as ex:
self.fail("failed to create new data product: %s" % ex)
log.debug("TestExternalDatasetAgentMgmt: new dp_id = %s",
str(data_product_id1))
self.damsclient.assign_data_product(input_resource_id=extDataset_id,
data_product_id=data_product_id1)
self.dpclient.activate_data_product_persistence(
data_product_id=data_product_id1,
persist_data=True,
persist_metadata=True)
# Retrieve the id of the OUTPUT stream from the out Data Product
stream_ids, _ = self.rrclient.find_objects(data_product_id1,
PRED.hasStream, None, True)
log.debug("TestExternalDatasetAgentMgmt: Data product streams1 = %s",
str(stream_ids))
stream_id = stream_ids[0]
# Build a taxonomy for the dataset
tx = TaxyTool()
tx.add_taxonomy_set('data', 'external_data')
# Augment the DVR_CONFIG with the necessary pieces
self.DVR_CONFIG['dh_cfg'] = {
'TESTING': True,
'stream_id':
stream_id, #TODO: This should probably be a 'stream_config' dict with stream_name:stream_id members
'data_producer_id': dproducer_id,
# 'external_dataset_res':extDataset_obj, # Not needed - retrieved by EDA based on resource_id
'taxonomy': tx.dump(), #TODO: Currently does not support sets
'max_records': 4,
}
# Create agent config.
self._stream_config = {}
agent_config = {
'driver_config': self.DVR_CONFIG,
'stream_config': self._stream_config,
'agent': {
'resource_id': EDA_RESOURCE_ID
},
'test_mode': True
}
extDatasetAgentInstance_obj = IonObject(
RT.ExternalDatasetAgentInstance,
name='DatasetAgentInstance',
description="DatasetAgentInstance",
dataset_driver_config=self.DVR_CONFIG,
dataset_agent_config=agent_config)
extDatasetAgentInstance_id = self.damsclient.create_external_dataset_agent_instance(
external_dataset_agent_instance=extDatasetAgentInstance_obj,
external_dataset_agent_id=datasetAgent_id,
external_dataset_id=extDataset_id)
log.debug(
"TestExternalDatasetAgentMgmt: Dataset agent instance obj: = %s",
str(extDatasetAgentInstance_obj))
log.debug(
"TestExternalDatasetAgentMgmt: Dataset agent instance id: = %s",
str(extDatasetAgentInstance_id))
#Check that the instance is currently not active
id, active = self.damsclient.retrieve_external_dataset_agent_instance(
extDataset_id)
log.debug(
"TestExternalDatasetAgentMgmt: Dataset agent instance id: = %s active 1 = %s ",
str(id), str(active))
self.damsclient.start_external_dataset_agent_instance(
extDatasetAgentInstance_id)
dataset_agent_instance_obj = self.damsclient.read_external_dataset_agent_instance(
extDatasetAgentInstance_id)
log.debug(
"TestExternalDatasetAgentMgmt: Dataset agent instance obj: = %s",
str(dataset_agent_instance_obj))
# now the instance process should be active
id, active = self.damsclient.retrieve_external_dataset_agent_instance(
extDataset_id)
log.debug(
"TestExternalDatasetAgentMgmt: Dataset agent instance id: = %s active 2 = %s ",
str(id), str(active))
# Start a resource agent client to talk with the instrument agent.
self._dsa_client = ResourceAgentClient(extDataset_id,
process=FakeProcess())
print 'TestExternalDatasetAgentMgmt: got ia client %s', self._dsa_client
log.debug("TestExternalDatasetAgentMgmt: got dataset client %s",
str(self._dsa_client))
# cmd=AgentCommand(command='initialize')
# _ = self._dsa_client.execute_agent(cmd)
#
# cmd = AgentCommand(command='go_active')
# _ = self._dsa_client.execute_agent(cmd)
#
# cmd = AgentCommand(command='run')
# _ = self._dsa_client.execute_agent(cmd)
#
# log.info('Send an unconstrained request for data (\'new data\')')
# cmd = AgentCommand(command='acquire_data')
# self._dsa_client.execute(cmd)
#
# log.info('Send a second unconstrained request for data (\'new data\'), should be rejected')
# cmd = AgentCommand(command='acquire_data')
# self._dsa_client.execute(cmd)
#
# cmd = AgentCommand(command='reset')
# _ = self._dsa_client.execute_agent(cmd)
# cmd = AgentCommand(command='get_current_state')
# retval = self._dsa_client.execute_agent(cmd)
# state = retval.result
# TODO: Think about what we really should be testing at this point
# The following is taken from ion.agents.data.test.test_external_dataset_agent.ExternalDatasetAgentTestBase.test_states()
# TODO: Do we also need to show data retrieval?
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.UNINITIALIZED)
cmd = AgentCommand(command='initialize')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.INACTIVE)
cmd = AgentCommand(command='go_active')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.IDLE)
cmd = AgentCommand(command='run')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.OBSERVATORY)
cmd = AgentCommand(command='pause')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.STOPPED)
cmd = AgentCommand(command='resume')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.OBSERVATORY)
cmd = AgentCommand(command='clear')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.IDLE)
cmd = AgentCommand(command='run')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.OBSERVATORY)
cmd = AgentCommand(command='pause')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.STOPPED)
cmd = AgentCommand(command='clear')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.IDLE)
cmd = AgentCommand(command='run')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.OBSERVATORY)
cmd = AgentCommand(command='reset')
retval = self._dsa_client.execute_agent(cmd)
cmd = AgentCommand(command='get_current_state')
retval = self._dsa_client.execute_agent(cmd)
state = retval.result
self.assertEqual(state, InstrumentAgentState.UNINITIALIZED)
#-------------------------------
# Deactivate InstrumentAgentInstance
#-------------------------------
self.damsclient.stop_external_dataset_agent_instance(
extDatasetAgentInstance_id)
