Example #1
0
    def _setup_resources(self):
        # TODO: some or all of this (or some variation) should move to DAMS'

        # Build the test resources for the dataset
        dms_cli = DatasetManagementServiceClient()
        dams_cli = DataAcquisitionManagementServiceClient()
        dpms_cli = DataProductManagementServiceClient()
        rr_cli = ResourceRegistryServiceClient()
        pubsub_cli = PubsubManagementServiceClient()

        eda = ExternalDatasetAgent(name='example eda',handler_module=self.DVR_CONFIG['dvr_mod'],
            handler_class=self.DVR_CONFIG['dvr_cls'])
        eda_id = dams_cli.create_external_dataset_agent(eda)

        eda_inst = ExternalDatasetAgentInstance(name='example eda instance')
        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(name='example data provider', institution=Institution(),
            contact=ContactInformation())
        dprov.contact.individual_names_given = 'Christopher Mueller'
        dprov.contact.email = '*****@*****.**'

        # Create DataSource
        dsrc = DataSource(name='example datasource', protocol_type='DAP', institution=Institution(),
            contact=ContactInformation())
        dsrc.connection_params['base_data_url'] = ''
        dsrc.contact.individual_names_given = '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)

        #create temp streamdef so the data product can create the stream
        pc_list = []

        #Get 'time' parameter context
        pc_list.append(dms_cli.read_parameter_context_by_name('time', id_only=True))

        for pc_k, pc in self._create_parameter_dictionary().iteritems():
            pc_list.append(dms_cli.create_parameter_context(pc_k, pc[1].dump()))

        pdict_id = dms_cli.create_parameter_dictionary('netcdf_param_dict', pc_list)

        #create temp streamdef so the data product can create the stream
        streamdef_id = pubsub_cli.create_stream_definition(name="netcdf", description="netcdf", parameter_dictionary_id=pdict_id)

        tdom, sdom = time_series_domain()
        tdom, sdom = tdom.dump(), sdom.dump()

        dprod = IonObject(RT.DataProduct,
            name='usgs_parsed_product',
            description='parsed usgs product',
            temporal_domain=tdom,
            spatial_domain=sdom)

        # Generate the data product and associate it to the ExternalDataset
        dproduct_id = dpms_cli.create_data_product(data_product=dprod,
            stream_definition_id=streamdef_id)

        dams_cli.assign_data_product(input_resource_id=ds_id, data_product_id=dproduct_id)

        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}))

        # Create the logger for receiving publications
        _, stream_route, _ = 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,
            'stream_route': stream_route,
            'stream_def': streamdef_id,
            'data_producer_id': dproducer_id,  # CBM: Should this be put in the main body of the config - with mod & cls?
            'max_records': 1,
            }
    def _setup_resources(self):
        # TODO: some or all of this (or some variation) should move to DAMS'

        # Build the test resources for the dataset
        dms_cli = DatasetManagementServiceClient()
        dams_cli = DataAcquisitionManagementServiceClient()
        dpms_cli = DataProductManagementServiceClient()
        rr_cli = ResourceRegistryServiceClient()
        pubsub_cli = PubsubManagementServiceClient()

        eda = ExternalDatasetAgent(handler_module=self.DVR_CONFIG['dvr_mod'],
            handler_class=self.DVR_CONFIG['dvr_cls'])
        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.individual_names_given = 'Christopher Mueller'
        dprov.contact.email = '*****@*****.**'

        # Create DataSource
        dsrc = DataSource(protocol_type='FILE', institution=Institution(), contact=ContactInformation())
        dsrc.connection_params['base_data_url'] = ''
        dsrc.contact.individual_names_given = '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['base_url'] = 'test_data/slocum/'
        dset.dataset_description.parameters['list_pattern'] = 'ru05-2012-021-0-0-sbd.dat'
        dset.dataset_description.parameters['date_pattern'] = '%Y %j'
        dset.dataset_description.parameters['date_extraction_pattern'] = 'ru05-([\d]{4})-([\d]{3})-\d-\d-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)

        #create temp streamdef so the data product can create the stream
        pc_list = []
        for pc_k, pc in self._create_parameter_dictionary().iteritems():
            pc_list.append(dms_cli.create_parameter_context(pc_k, pc[1].dump()))

        pdict_id = dms_cli.create_parameter_dictionary('slocum_param_dict', pc_list)

        streamdef_id = pubsub_cli.create_stream_definition(name="slocum_stream_def", description="stream def for slocum testing", parameter_dictionary_id=pdict_id)

        #        dpms_cli.create_data_product()

        # Generate the data product and associate it to the ExternalDataset

        tdom, sdom = time_series_domain()
        tdom, sdom = tdom.dump(), sdom.dump()

        dprod = IonObject(RT.DataProduct,
            name='slocum_parsed_product',
            description='parsed slocum product',
            temporal_domain=tdom,
            spatial_domain=sdom)

        dproduct_id = dpms_cli.create_data_product(data_product=dprod,
            stream_definition_id=streamdef_id)

        dams_cli.assign_data_product(input_resource_id=ds_id, data_product_id=dproduct_id)

        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}))

        # Create the logger for receiving publications
        _, stream_route, _ = 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,
            'stream_route': stream_route,
            'stream_def': streamdef_id,
            'external_dataset_res': dset,
            'data_producer_id': dproducer_id,  # CBM: Should this be put in the main body of the config - with mod & cls?
            'max_records': 20,
            }
    def _setup_resources(self):
        # TODO: some or all of this (or some variation) should move to DAMS'

        # Build the test resources for the dataset
        dms_cli = DatasetManagementServiceClient()
        dams_cli = DataAcquisitionManagementServiceClient()
        dpms_cli = DataProductManagementServiceClient()
        rr_cli = ResourceRegistryServiceClient()
        pubsub_cli = PubsubManagementServiceClient()

        eda = ExternalDatasetAgent(name='example data agent',
                                   handler_module=self.DVR_CONFIG['dvr_mod'],
                                   handler_class=self.DVR_CONFIG['dvr_cls'])
        eda_id = dams_cli.create_external_dataset_agent(eda)

        eda_inst = ExternalDatasetAgentInstance(
            name='example dataset agent instance')
        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(name='example data provider',
                                     institution=Institution(),
                                     contact=ContactInformation())
        dprov.contact.individual_names_given = 'Christopher Mueller'
        dprov.contact.email = '*****@*****.**'

        # Create DataSource
        dsrc = DataSource(name='example datasource',
                          protocol_type='FILE',
                          institution=Institution(),
                          contact=ContactInformation())
        dsrc.connection_params['base_data_url'] = ''
        dsrc.contact.individual_names_given = 'Tim Giguere'
        dsrc.contact.email = '*****@*****.**'

        # Create ExternalDataset
        ds_name = 'ruv_test_dataset'
        dset = ExternalDataset(name=ds_name,
                               dataset_description=DatasetDescription(),
                               update_description=UpdateDescription(),
                               contact=ContactInformation())

        dset.dataset_description.parameters['base_url'] = 'test_data/ruv/'
        dset.dataset_description.parameters[
            'list_pattern'] = 'RDLi_SEAB_2011_08_24_1600.ruv'
        dset.dataset_description.parameters['date_pattern'] = '%Y %m %d %H %M'
        dset.dataset_description.parameters[
            'date_extraction_pattern'] = 'RDLi_SEAB_([\d]{4})_([\d]{2})_([\d]{2})_([\d]{2})([\d]{2}).ruv'
        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'] = []

        # Create DataSourceModel
        dsrc_model = DataSourceModel(name='ruv_model')
        #dsrc_model.model = 'RUV'
        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)

        pdict = ParameterDictionary()

        t_ctxt = ParameterContext(
            'data',
            param_type=QuantityType(value_encoding=numpy.dtype('int64')))
        t_ctxt.axis = AxisTypeEnum.TIME
        t_ctxt.uom = 'seconds since 01-01-1970'
        pdict.add_context(t_ctxt)

        #create temp streamdef so the data product can create the stream
        pc_list = []
        for pc_k, pc in pdict.iteritems():
            pc_list.append(dms_cli.create_parameter_context(
                pc_k, pc[1].dump()))

        pdict_id = dms_cli.create_parameter_dictionary('ruv_param_dict',
                                                       pc_list)

        streamdef_id = pubsub_cli.create_stream_definition(
            name="ruv",
            description="stream def for ruv testing",
            parameter_dictionary_id=pdict_id)

        dprod = IonObject(RT.DataProduct,
                          name='ruv_parsed_product',
                          description='parsed ruv product')

        # Generate the data product and associate it to the ExternalDataset
        dproduct_id = dpms_cli.create_data_product(
            data_product=dprod, stream_definition_id=streamdef_id)

        dams_cli.assign_data_product(input_resource_id=ds_id,
                                     data_product_id=dproduct_id)

        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: Eventually, probably want to group this crap somehow - not sure how yet...

        # Create the logger for receiving publications
        _, stream_route, _ = self.create_stream_and_logger(name='ruv',
                                                           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,
            'stream_route': stream_route,
            'external_dataset_res': dset,
            'param_dictionary': pdict.dump(),
            'data_producer_id':
            dproducer_id,  # CBM: Should this be put in the main body of the config - with mod & cls?
            'max_records': 20,
        }
    def _setup_hfr(self):
        # TODO: some or all of this (or some variation) should move to DAMS

        # Create and register the necessary resources/objects

        eda = ExternalDatasetAgent()
        eda_id = self.dams_cli.create_external_dataset_agent(eda)

        eda_inst = ExternalDatasetAgentInstance()
        eda_inst_id = self.dams_cli.create_external_dataset_agent_instance(
            eda_inst, external_dataset_agent_id=eda_id)

        # Create DataProvider
        dprov = ExternalDataProvider(institution=Institution(),
                                     contact=ContactInformation())
        #        dprov.institution.name = "HFR UCSD"

        # Create DataSource
        dsrc = DataSource(protocol_type="DAP",
                          institution=Institution(),
                          contact=ContactInformation())
        dsrc.connection_params[
            "base_data_url"] = "http://hfrnet.ucsd.edu:8080/thredds/dodsC/"

        # Create ExternalDataset
        dset = ExternalDataset(name="UCSD HFR",
                               dataset_description=DatasetDescription(),
                               update_description=UpdateDescription(),
                               contact=ContactInformation())
        dset.dataset_description.parameters[
            "dataset_path"] = "HFRNet/USEGC/6km/hourly/RTV"
        #        dset.dataset_description.parameters["dataset_path"] = "test_data/hfr.nc"
        dset.dataset_description.parameters["temporal_dimension"] = "time"
        dset.dataset_description.parameters["zonal_dimension"] = "lon"
        dset.dataset_description.parameters["meridional_dimension"] = "lat"

        # Create DataSourceModel
        dsrc_model = DataSourceModel(name="dap_model")
        dsrc_model.model = "DAP"
        dsrc_model.data_handler_module = "eoi.agent.handler.dap_external_data_handler"
        dsrc_model.data_handler_class = "DapExternalDataHandler"

        ## Run everything through DAMS
        ds_id = self.hfr_ds_id = self.dams_cli.create_external_dataset(
            external_dataset=dset)
        ext_dprov_id = self.dams_cli.create_external_data_provider(
            external_data_provider=dprov)
        ext_dsrc_id = self.dams_cli.create_data_source(data_source=dsrc)
        ext_dsrc_model_id = self.dams_cli.create_data_source_model(dsrc_model)

        # Register the ExternalDataset
        dproducer_id = self.dams_cli.register_external_data_set(
            external_dataset_id=ds_id)

        ## Associate everything
        # Convenience method
        #        self.dams_cli.assign_eoi_resources(external_data_provider_id=ext_dprov_id, data_source_id=ext_dsrc_id, data_source_model_id=ext_dsrc_model_id, external_dataset_id=ds_id, external_data_agent_id=eda_id, agent_instance_id=eda_inst_id)

        # Or using each method
        self.dams_cli.assign_data_source_to_external_data_provider(
            data_source_id=ext_dsrc_id, external_data_provider_id=ext_dprov_id)
        self.dams_cli.assign_data_source_to_data_model(
            data_source_id=ext_dsrc_id, data_source_model_id=ext_dsrc_model_id)
        self.dams_cli.assign_external_dataset_to_data_source(
            external_dataset_id=ds_id, data_source_id=ext_dsrc_id)
        self.dams_cli.assign_external_dataset_to_agent_instance(
            external_dataset_id=ds_id, agent_instance_id=eda_inst_id)
        #        self.dams_cli.assign_external_dataset_agent_to_data_model(external_data_agent_id=eda_id, data_source_model_id=ext_dsrc_model_id)
        #        self.dams_cli.assign_external_data_agent_to_agent_instance(external_data_agent_id=eda_id, agent_instance_id=eda_inst_id)

        # Generate the data product and associate it to the ExternalDataset
        dprod = DataProduct(name='hfr_product', description='raw hfr product')
        dproduct_id = self.dpms_cli.create_data_product(data_product=dprod)

        self.dams_cli.assign_data_product(input_resource_id=ds_id,
                                          data_product_id=dproduct_id,
                                          create_stream=True)
    def _setup_ncom(self):
        # TODO: some or all of this (or some variation) should move to DAMS

        # Create and register the necessary resources/objects

        eda = ExternalDatasetAgent()
        eda_id = self.dams_cli.create_external_dataset_agent(eda)

        eda_inst = ExternalDatasetAgentInstance()
        eda_inst_id = self.dams_cli.create_external_dataset_agent_instance(
            eda_inst, external_dataset_agent_id=eda_id)

        # Create DataProvider
        dprov = ExternalDataProvider(institution=Institution(),
                                     contact=ContactInformation())
        #        dprov.institution.name = "OOI CGSN"
        dprov.contact.name = "Robert Weller"
        dprov.contact.email = "*****@*****.**"

        # Create DataSource
        dsrc = DataSource(protocol_type="DAP",
                          institution=Institution(),
                          contact=ContactInformation())
        #        dsrc.connection_params["base_data_url"] = "http://ooi.whoi.edu/thredds/dodsC/"
        dsrc.connection_params["base_data_url"] = ""
        dsrc.contact.name = "Rich Signell"
        dsrc.contact.email = "*****@*****.**"

        # Create ExternalDataset
        dset = ExternalDataset(name="test",
                               dataset_description=DatasetDescription(),
                               update_description=UpdateDescription(),
                               contact=ContactInformation())

        #        dset.dataset_description.parameters["dataset_path"] = "ooi/AS02CPSM_R_M.nc"
        dset.dataset_description.parameters[
            "dataset_path"] = "test_data/ncom.nc"
        dset.dataset_description.parameters["temporal_dimension"] = "time"
        dset.dataset_description.parameters["zonal_dimension"] = "lon"
        dset.dataset_description.parameters["meridional_dimension"] = "lat"

        # Create DataSourceModel
        dsrc_model = DataSourceModel(name="dap_model")
        dsrc_model.model = "DAP"
        dsrc_model.data_handler_module = "eoi.agent.handler.dap_external_data_handler"
        dsrc_model.data_handler_class = "DapExternalDataHandler"

        ## Run everything through DAMS
        ds_id = self.ncom_ds_id = self.dams_cli.create_external_dataset(
            external_dataset=dset)
        ext_dprov_id = self.dams_cli.create_external_data_provider(
            external_data_provider=dprov)
        ext_dsrc_id = self.dams_cli.create_data_source(data_source=dsrc)
        ext_dsrc_model_id = self.dams_cli.create_data_source_model(dsrc_model)

        # Register the ExternalDataset
        dproducer_id = self.dams_cli.register_external_data_set(
            external_dataset_id=ds_id)

        ## Associate everything
        # Convenience method
        #        self.dams_cli.assign_eoi_resources(external_data_provider_id=ext_dprov_id, data_source_id=ext_dsrc_id, data_source_model_id=ext_dsrc_model_id, external_dataset_id=ds_id, external_data_agent_id=eda_id, agent_instance_id=eda_inst_id)

        # Or using each method
        self.dams_cli.assign_data_source_to_external_data_provider(
            data_source_id=ext_dsrc_id, external_data_provider_id=ext_dprov_id)
        self.dams_cli.assign_data_source_to_data_model(
            data_source_id=ext_dsrc_id, data_source_model_id=ext_dsrc_model_id)
        self.dams_cli.assign_external_dataset_to_data_source(
            external_dataset_id=ds_id, data_source_id=ext_dsrc_id)
        self.dams_cli.assign_external_dataset_to_agent_instance(
            external_dataset_id=ds_id, agent_instance_id=eda_inst_id)
        #        self.dams_cli.assign_external_dataset_agent_to_data_model(external_data_agent_id=eda_id, data_source_model_id=ext_dsrc_model_id)
        #        self.dams_cli.assign_external_data_agent_to_agent_instance(external_data_agent_id=eda_id, agent_instance_id=eda_inst_id)

        # Generate the data product and associate it to the ExternalDataset
        dprod = DataProduct(name='ncom_product',
                            description='raw ncom product')
        dproduct_id = self.dpms_cli.create_data_product(data_product=dprod)

        self.dams_cli.assign_data_product(input_resource_id=ds_id,
                                          data_product_id=dproduct_id,
                                          create_stream=True)
Example #6
0
    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,
        }
    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,
        }