def create_nut_sr(self):
nutnr_fn = 'nutnr_a_sample.nc'
ctdpf_fn = 'ctdpf_sbe43_sample.nc'
qc = json.load(open(os.path.join(DATA_DIR, 'qc.json')))
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
sr = StreamRequest(self.nut_sk, [18],
tr, {},
qc_parameters=qc,
request_id='UNIT')
nutnr_ds = xr.open_dataset(os.path.join(DATA_DIR, nutnr_fn),
decode_times=False)
ctdpf_ds = xr.open_dataset(os.path.join(DATA_DIR, ctdpf_fn),
decode_times=False)
nutnr_ds = nutnr_ds[
self.base_params +
[p.name for p in sr.stream_parameters[self.nut_sk]]]
ctdpf_ds = ctdpf_ds[
self.base_params +
[p.name for p in sr.stream_parameters[self.ctd_sk]]]
sr.datasets[self.ctd_sk] = StreamDataset(self.ctd_sk, sr.uflags,
[self.nut_sk], sr.request_id)
sr.datasets[self.nut_sk] = StreamDataset(self.nut_sk, sr.uflags,
[self.ctd_sk], sr.request_id)
sr.datasets[self.ctd_sk].events = self.ctd_events
sr.datasets[self.nut_sk].events = self.nut_events
sr.datasets[self.ctd_sk]._insert_dataset(ctdpf_ds)
sr.datasets[self.nut_sk]._insert_dataset(nutnr_ds)
return sr
def test_calculate(self):
nutnr_sk = StreamKey('CE04OSPS', 'SF01B', '4A-NUTNRA102', 'streamed',
'nutnr_a_sample')
ctdpf_sk = StreamKey('CE04OSPS', 'SF01B', '2A-CTDPFA107', 'streamed',
'ctdpf_sbe43_sample')
nutnr_fn = 'nutnr_a_sample.nc'
ctdpf_fn = 'ctdpf_sbe43_sample.nc'
cals = json.load(open(os.path.join(DATA_DIR, 'cals.json')))
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
coefficients = {
k: [{
'start': tr.start - 1,
'stop': tr.stop + 1,
'value': cals[k],
'deployment': 1
}]
for k in cals
}
sr = StreamRequest(nutnr_sk, [2443],
coefficients,
tr, {},
request_id='UNIT')
nutnr_ds = xr.open_dataset(os.path.join(DATA_DIR, nutnr_fn),
decode_times=False)
ctdpf_ds = xr.open_dataset(os.path.join(DATA_DIR, ctdpf_fn),
decode_times=False)
nutnr_ds = nutnr_ds[self.base_params +
[p.name for p in sr.stream_parameters[nutnr_sk]]]
ctdpf_ds = ctdpf_ds[self.base_params +
[p.name for p in sr.stream_parameters[ctdpf_sk]]]
sr.datasets[ctdpf_sk] = StreamDataset(ctdpf_sk, sr.coefficients,
sr.uflags, [nutnr_sk],
sr.request_id)
sr.datasets[nutnr_sk] = StreamDataset(nutnr_sk, sr.coefficients,
sr.uflags, [ctdpf_sk],
sr.request_id)
sr.datasets[ctdpf_sk]._insert_dataset(ctdpf_ds)
sr.datasets[nutnr_sk]._insert_dataset(nutnr_ds)
sr.calculate_derived_products()
ds = sr.datasets[ctdpf_sk]
tempwat = ctd_sbe16plus_tempwat(ds.datasets[0].temperature,
cals['CC_a0'], cals['CC_a1'],
cals['CC_a2'], cals['CC_a3'])
np.testing.assert_array_equal(ds.datasets[0].seawater_temperature,
tempwat)
pracsal = ctd_pracsal(ds.datasets[0].seawater_conductivity,
ds.datasets[0].seawater_temperature,
ds.datasets[0].seawater_pressure)
np.testing.assert_array_equal(ds.datasets[0].practical_salinity,
pracsal)
response = json.loads(JsonResponse(sr).json())
self.assertEqual(len(response), len(nutnr_ds.time.values))
def create_metbk_hourly_sr(self):
metbk_fn = 'metbk_a_dcl_instrument_recovered.nc'
metbk_ds = xr.open_dataset(os.path.join(DATA_DIR, metbk_fn), decode_times=False)
vel_fn = 'velpt_ab_dcl_instrument_recovered.nc'
vel_ds = xr.open_dataset(os.path.join(DATA_DIR, vel_fn), decode_times=False)
# both of these datasets are labeled deployment 3 but the times are squarely in deployment 1. Fix.
metbk_ds.deployment.values[:] = 1
vel_ds.deployment.values[:] = 1
tr = TimeRange(metbk_ds.time.values[0], metbk_ds.time.values[-1])
sr = StreamRequest(self.hourly_sk, [], tr, {}, request_id='UNIT')
metbk_ds = metbk_ds[self.base_params + [p.name for p in sr.stream_parameters[self.met_sk]]]
vel_ds = vel_ds[self.base_params + [p.name for p in sr.stream_parameters[self.vel_sk]]]
sr.datasets[self.met_sk] = StreamDataset(self.met_sk, sr.uflags, [self.hourly_sk, self.vel_sk], sr.request_id)
sr.datasets[self.hourly_sk] = StreamDataset(self.hourly_sk, sr.uflags, [self.met_sk, self.vel_sk], sr.request_id)
sr.datasets[self.vel_sk] = StreamDataset(self.vel_sk, sr.uflags, [self.hourly_sk, self.met_sk], sr.request_id)
sr.datasets[self.hourly_sk].events = self.met_events
sr.datasets[self.met_sk].events = self.met_events
sr.datasets[self.vel_sk].events = self.vel_events
sr.datasets[self.met_sk]._insert_dataset(metbk_ds)
sr.datasets[self.vel_sk]._insert_dataset(vel_ds)
return sr
def test_exclude_data(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
times = ctd_ds.time.values
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.exclude_flagged_data()
np.testing.assert_array_equal(times, ctd_stream_dataset.datasets[2].time.values)
# exclude a bit
start = ntplib.ntp_to_system_time(times[0]) * 1000
stop = ntplib.ntp_to_system_time(times[100]) * 1000
anno = self._create_exclusion_anno(start, stop)
ctd_stream_dataset.annotation_store.add_annotations([anno])
ctd_stream_dataset.exclude_flagged_data()
np.testing.assert_array_equal(times[101:], ctd_stream_dataset.datasets[2].time.values)
# exclude everything
start = ntplib.ntp_to_system_time(times[0]) * 1000
stop = ntplib.ntp_to_system_time(times[-1]) * 1000
anno = self._create_exclusion_anno(start, stop)
ctd_stream_dataset.annotation_store.add_annotations([anno])
ctd_stream_dataset.exclude_flagged_data()
self.assertNotIn(2, ctd_stream_dataset.datasets)
def test_cspp_nutnr_uses_ctd_pressure(self):
nut_fn = 'nutnr_j_cspp_instrument_recovered.nc'
ctd_fn = 'ctdpf_j_cspp_instrument_recovered.nc'
nut_ds = xr.open_dataset(os.path.join(DATA_DIR, nut_fn),
decode_times=False)
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, ctd_fn),
decode_times=False)
tr = TimeRange(nut_ds.time.values[0], nut_ds.time.values[-1])
sr = StreamRequest(self.nut_sk2, [], tr, {}, request_id='UNIT')
nut_ds = nut_ds[self.base_params +
[p.name for p in sr.stream_parameters[self.nut_sk2]]]
sr.datasets[self.ctd_sk2] = StreamDataset(self.ctd_sk2, sr.uflags,
[self.nut_sk2],
sr.request_id)
sr.datasets[self.nut_sk2] = StreamDataset(self.nut_sk2, sr.uflags,
[self.ctd_sk2],
sr.request_id)
sr.datasets[self.ctd_sk2]._insert_dataset(ctd_ds)
sr.datasets[self.nut_sk2]._insert_dataset(nut_ds)
sr.calculate_derived_products()
sr.import_extra_externals()
sr.rename_parameters()
self.assertIn('int_ctd_pressure',
sr.datasets[self.nut_sk2].datasets[1])
data = json.loads(JsonResponse(sr).json())
for each in data:
self.assertIn('int_ctd_pressure', each)
def fetch_raw_data(self):
"""
Fetch the source data for this request
:return:
"""
for stream_key, stream_parameters in self.stream_parameters.iteritems():
other_streams = set(self.stream_parameters)
other_streams.remove(stream_key)
should_pad = stream_key != self.stream_key
if not stream_key.is_virtual:
log.debug('<%s> Fetching raw data for %s', self.request_id, stream_key.as_refdes())
sd = StreamDataset(stream_key, self.coefficients, self.uflags, other_streams, self.request_id)
try:
sd.fetch_raw_data(self.time_range, self.limit, should_pad)
self.datasets[stream_key] = sd
except MissingDataException as e:
if stream_key == self.stream_key:
raise MissingDataException("Query returned no results for primary stream")
elif stream_key in self.stream_key.stream.source_streams:
raise MissingDataException("Query returned no results for source stream")
else:
log.error('<%s> %s', self.request_id, e.message)
else:
log.debug('<%s> Creating empty dataset for virtual stream: %s',
self.request_id, stream_key.as_refdes())
sd = StreamDataset(stream_key, self.coefficients, self.uflags, other_streams, self.request_id)
self.datasets[stream_key] = sd
def test_insert_valid_scalar_data(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
data = np.zeros_like(ctd_ds.time.values)
param = Parameter.query.get(3777)
StreamDataset._insert_data(ctd_ds, param, data)
self.assertIn('corrected_dissolved_oxygen', ctd_ds)
def test_insert_valid_scalar_data(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
data = np.zeros_like(ctd_ds.time.values)
param = Parameter.query.get(3777)
StreamDataset._insert_data(ctd_ds, param, data)
self.assertIn('corrected_dissolved_oxygen', ctd_ds)
def test_insert_valid_array_data(self):
adcp_fn = 'deployment0000_RS03AXBS-LJ03A-10-ADCPTE301-streamed-adcp_velocity_beam.nc'
adcp_ds = xr.open_dataset(os.path.join(DATA_DIR, adcp_fn), decode_times=False)
data = np.zeros_like(adcp_ds.velocity_beam1)
param = Parameter.query.get(2769)
StreamDataset._insert_data(adcp_ds, param, data)
self.assertIn('corrected_echo_intensity_beam1', adcp_ds)
self.assertEqual(set(adcp_ds.corrected_echo_intensity_beam1.dims), {'obs', 'bin'})
def test_insert_valid_array_data(self):
adcp_fn = 'deployment0000_RS03AXBS-LJ03A-10-ADCPTE301-streamed-adcp_velocity_beam.nc'
adcp_ds = xr.open_dataset(os.path.join(DATA_DIR, adcp_fn), decode_times=False)
data = np.zeros_like(adcp_ds.velocity_beam1)
param = Parameter.query.get(2769)
StreamDataset._insert_data(adcp_ds, param, data)
self.assertIn('corrected_echo_intensity_beam1', adcp_ds)
self.assertEqual(set(adcp_ds.corrected_echo_intensity_beam1.dims), {'obs', 'bin'})
def test_insert_bad_shape_array_data(self):
adcp_fn = 'deployment0000_RS03AXBS-LJ03A-10-ADCPTE301-streamed-adcp_velocity_beam.nc'
adcp_ds = xr.open_dataset(os.path.join(DATA_DIR, adcp_fn), decode_times=False)
data = np.zeros_like(adcp_ds.time)
param = Parameter.query.get(2769)
with self.assertRaises(ValueError):
StreamDataset._insert_data(adcp_ds, param, data)
self.assertNotIn('corrected_echo_intensity_beam1', adcp_ds)
def test_add_externals(self):
nutnr_sk = StreamKey('CE04OSPS', 'SF01B', '4A-NUTNRA102', 'streamed',
'nutnr_a_sample')
ctdpf_sk = StreamKey('CE04OSPS', 'SF01B', '2A-CTDPFA107', 'streamed',
'ctdpf_sbe43_sample')
nutnr_fn = 'nutnr_a_sample.nc'
ctdpf_fn = 'ctdpf_sbe43_sample.nc'
cals = json.load(open(os.path.join(DATA_DIR, 'cals.json')))
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
coefficients = {
k: [{
'start': tr.start - 1,
'stop': tr.stop + 1,
'value': cals[k],
'deployment': 1
}]
for k in cals
}
sr = StreamRequest(nutnr_sk, [2443],
coefficients,
tr, {},
request_id='UNIT')
nutnr_ds = xr.open_dataset(os.path.join(DATA_DIR, nutnr_fn),
decode_times=False)
ctdpf_ds = xr.open_dataset(os.path.join(DATA_DIR, ctdpf_fn),
decode_times=False)
ctdpf_ds = ctdpf_ds[self.base_params +
[p.name for p in sr.stream_parameters[ctdpf_sk]]]
nutnr_ds = nutnr_ds[self.base_params +
[p.name for p in sr.stream_parameters[nutnr_sk]]]
sr.datasets[ctdpf_sk] = StreamDataset(ctdpf_sk, sr.coefficients,
sr.uflags, [nutnr_sk],
sr.request_id)
sr.datasets[nutnr_sk] = StreamDataset(nutnr_sk, sr.coefficients,
sr.uflags, [ctdpf_sk],
sr.request_id)
sr.datasets[ctdpf_sk]._insert_dataset(ctdpf_ds)
sr.datasets[nutnr_sk]._insert_dataset(nutnr_ds)
sr.calculate_derived_products()
sr.import_extra_externals()
self.assertIn('ctdpf_sbe43_sample-seawater_pressure',
sr.datasets[nutnr_sk].datasets[0])
self.assertNotIn('ctdpf_sbe43_sample-seawater_pressure',
sr.datasets[ctdpf_sk].datasets[0])
data = json.loads(JsonResponse(sr).json())
for each in data:
self.assertIn('int_ctd_pressure', each)
def test_insert_bad_shape_array_data(self):
adcp_fn = 'deployment0000_RS03AXBS-LJ03A-10-ADCPTE301-streamed-adcp_velocity_beam.nc'
adcp_ds = xr.open_dataset(os.path.join(DATA_DIR, adcp_fn), decode_times=False)
data = np.zeros_like(adcp_ds.time)
param = Parameter.query.get(2769)
with self.assertRaises(ValueError):
StreamDataset._insert_data(adcp_ds, param, data)
self.assertNotIn('corrected_echo_intensity_beam1', adcp_ds)
def test_qc(self):
nutnr_sk = StreamKey('CE04OSPS', 'SF01B', '4A-NUTNRA102', 'streamed',
'nutnr_a_sample')
ctdpf_sk = StreamKey('CE04OSPS', 'SF01B', '2A-CTDPFA107', 'streamed',
'ctdpf_sbe43_sample')
nutnr_fn = 'nutnr_a_sample.nc'
ctdpf_fn = 'ctdpf_sbe43_sample.nc'
cals = json.load(open(os.path.join(DATA_DIR, 'cals.json')))
qc = json.load(open(os.path.join(DATA_DIR, 'qc.json')))
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
coefficients = {
k: [{
'start': tr.start - 1,
'stop': tr.stop + 1,
'value': cals[k],
'deployment': 1
}]
for k in cals
}
sr = StreamRequest(nutnr_sk, [2443],
coefficients,
tr, {},
qc_parameters=qc,
request_id='UNIT')
nutnr_ds = xr.open_dataset(os.path.join(DATA_DIR, nutnr_fn),
decode_times=False)
ctdpf_ds = xr.open_dataset(os.path.join(DATA_DIR, ctdpf_fn),
decode_times=False)
ctdpf_ds = ctdpf_ds[self.base_params +
[p.name for p in sr.stream_parameters[ctdpf_sk]]]
nutnr_ds = nutnr_ds[self.base_params +
[p.name for p in sr.stream_parameters[nutnr_sk]]]
sr.datasets[ctdpf_sk] = StreamDataset(ctdpf_sk, sr.coefficients,
sr.uflags, [nutnr_sk],
sr.request_id)
sr.datasets[nutnr_sk] = StreamDataset(nutnr_sk, sr.coefficients,
sr.uflags, [ctdpf_sk],
sr.request_id)
sr.datasets[ctdpf_sk]._insert_dataset(ctdpf_ds)
sr.datasets[nutnr_sk]._insert_dataset(nutnr_ds)
sr.calculate_derived_products()
expected_parameters = [
'temp_sal_corrected_nitrate_qc_executed',
'temp_sal_corrected_nitrate_qc_results'
]
self.assert_parameters_in_datasets(sr.datasets[nutnr_sk].datasets,
expected_parameters)
def test_insert_bad_length_data(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
data = np.arange(0, 100)
param = Parameter.query.get(3777)
with self.assertRaises(ValueError):
StreamDataset._insert_data(ctd_ds, param, data)
self.assertNotIn('corrected_dissolved_oxygen', ctd_ds)
def test_insert_bad_length_data(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
data = np.arange(0, 100)
param = Parameter.query.get(3777)
with self.assertRaises(ValueError):
StreamDataset._insert_data(ctd_ds, param, data)
self.assertNotIn('corrected_dissolved_oxygen', ctd_ds)
def mock_fetch_raw_data(self):
if StreamRequestTest.call_cnt % 2 == 0:
self.datasets[self.stream_key] = StreamDataset(self.stream_key, self.uflags, [], self.request_id)
self.datasets[self.stream_key]._insert_dataset(ctd_ds)
self.datasets[self.stream_key].events = AssetEvents('test', [])
else:
self.datasets[self.stream_key] = StreamDataset(self.stream_key, self.uflags, [], self.request_id)
self.datasets[self.stream_key]._insert_dataset(echo_ds)
self.datasets[self.stream_key].events = AssetEvents('test', [])
StreamRequestTest.call_cnt += 1
def test_add_externals_glider(self):
gps_fn = 'deployment0003_CE05MOAS-GL319-00-ENG000000-recovered_host-glider_gps_position.nc'
par_fn = 'deployment0003_CE05MOAS-GL319-01-PARADM000-recovered_host-parad_m_glider_recovered.nc'
ctd_fn = 'deployment0003_CE05MOAS-GL319-05-CTDGVM000-recovered_host-ctdgv_m_glider_instrument_recovered.nc'
gps_sk = StreamKey('CE05MOAS', 'GL319', '00-ENG000000', 'recovered_host', 'glider_gps_position')
par_sk = StreamKey('CE05MOAS', 'GL319', '01-PARADM000', 'recovered_host', 'parad_m_glider_recovered')
ctd_sk = StreamKey('CE05MOAS', 'GL319', '05-CTDGVM000', 'recovered_host', 'ctdgv_m_glider_instrument_recovered')
# Fetch the source data
gps_ds = xr.open_dataset(os.path.join(DATA_DIR, gps_fn), decode_times=False)
par_ds = xr.open_dataset(os.path.join(DATA_DIR, par_fn), decode_times=False)
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, ctd_fn), decode_times=False)
# Create the stream request
tr = TimeRange(par_ds.time.values[0], par_ds.time.values[-1])
sr = StreamRequest(par_sk, [], tr, {}, request_id='UNIT')
# Filter the source data to just the data the stream request says we need
gps_ds = gps_ds[self.base_params + [p.name for p in sr.stream_parameters[gps_sk]]]
par_ds = par_ds[self.base_params + [p.name for p in sr.stream_parameters[par_sk]]]
ctd_ds = ctd_ds[self.base_params + [p.name for p in sr.stream_parameters[ctd_sk]]]
# Create the StreamDataset objects
sr.datasets[gps_sk] = StreamDataset(gps_sk, sr.uflags, [par_sk, ctd_sk], sr.request_id)
sr.datasets[par_sk] = StreamDataset(par_sk, sr.uflags, [gps_sk, ctd_sk], sr.request_id)
sr.datasets[ctd_sk] = StreamDataset(ctd_sk, sr.uflags, [par_sk, gps_sk], sr.request_id)
sr.datasets[gps_sk].events = self.get_events(gps_sk)
sr.datasets[par_sk].events = self.get_events(par_sk)
sr.datasets[ctd_sk].events = self.get_events(ctd_sk)
# Insert the source data
sr.datasets[gps_sk]._insert_dataset(gps_ds)
sr.datasets[par_sk]._insert_dataset(par_ds)
sr.datasets[ctd_sk]._insert_dataset(ctd_ds)
sr.calculate_derived_products()
sr.import_extra_externals()
# Ticket 9328: int_ctd_pressure is now set in stream_request.import_extra_externals()
self.assertNotIn('ctdgv_m_glider_instrument_recovered-sci_water_pressure_dbar', sr.datasets[par_sk].datasets[3])
self.assertIn('int_ctd_pressure', sr.datasets[par_sk].datasets[3])
self.assertNotIn('ctdgv_m_glider_instrument_recovered-sci_water_pressure_dbar', sr.datasets[ctd_sk].datasets[3])
data = json.loads(JsonResponse(sr).json())
for each in data:
self.assertIn('int_ctd_pressure', each)
self.assertIn('lat', each)
self.assertIn('lon', each)
def test_csv(self):
nutnr_sk = StreamKey('CE04OSPS', 'SF01B', '4A-NUTNRA102', 'streamed',
'nutnr_a_sample')
ctdpf_sk = StreamKey('CE04OSPS', 'SF01B', '2A-CTDPFA107', 'streamed',
'ctdpf_sbe43_sample')
nutnr_fn = 'nutnr_a_sample.nc'
ctdpf_fn = 'ctdpf_sbe43_sample.nc'
cals = json.load(open(os.path.join(DATA_DIR, 'cals.json')))
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
coefficients = {
k: [{
'start': tr.start - 1,
'stop': tr.stop + 1,
'value': cals[k],
'deployment': 1
}]
for k in cals
}
sr = StreamRequest(nutnr_sk, [2443],
coefficients,
tr, {},
request_id='UNIT')
nutnr_ds = xr.open_dataset(os.path.join(DATA_DIR, nutnr_fn),
decode_times=False)
ctdpf_ds = xr.open_dataset(os.path.join(DATA_DIR, ctdpf_fn),
decode_times=False)
nutnr_ds = nutnr_ds[self.base_params +
[p.name for p in sr.stream_parameters[nutnr_sk]]]
ctdpf_ds = ctdpf_ds[self.base_params +
[p.name for p in sr.stream_parameters[ctdpf_sk]]]
sr.datasets[ctdpf_sk] = StreamDataset(ctdpf_sk, sr.coefficients,
sr.uflags, [nutnr_sk],
sr.request_id)
sr.datasets[nutnr_sk] = StreamDataset(nutnr_sk, sr.coefficients,
sr.uflags, [ctdpf_sk],
sr.request_id)
sr.datasets[ctdpf_sk]._insert_dataset(ctdpf_ds)
sr.datasets[nutnr_sk]._insert_dataset(nutnr_ds)
sr.calculate_derived_products()
csv = CsvGenerator(sr, ',').to_csv()
self.assertTrue(csv)
def test_log_algorithm_inputs_no_result(self):
def mock_write(self):
return json.dumps(self.m_qdata, default=jdefault)
uflags = {'advancedStreamEngineLogging': True, 'userName': '******'}
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, uflags, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
parameter = Parameter.query.get(13)
with mock.patch('util.stream_dataset.ParameterReport.write', new=mock_write):
result = ctd_stream_dataset._log_algorithm_inputs(parameter, {}, None, self.ctdpf_sk, ctd_ds)
self.assertIsNotNone(result)
def test_calculate_internal_single_deployment(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn),
decode_times=False)
ctd_ds = ctd_ds[[
'obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0'
]]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_all()
for deployment in ctd_stream_dataset.datasets:
ds = ctd_stream_dataset.datasets[deployment]
tempwat = ctd_sbe16plus_tempwat(
ds.temperature,
ctd_stream_dataset.events.get_cal('CC_a0', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a1', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a2', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a3', deployment)[0][2])
np.testing.assert_array_equal(ds.seawater_temperature, tempwat)
pracsal = ctd_pracsal(ds.seawater_conductivity,
ds.seawater_temperature,
ds.seawater_pressure)
np.testing.assert_array_equal(ds.practical_salinity, pracsal)
def test_botpt_15s(self):
botpt_sk = StreamKey('RS03ECAL', 'MJ03E', '06-BOTPTA302', 'streamed',
'botpt_nano_sample')
botpt_15s_sk = StreamKey('RS03ECAL', 'MJ03E', '06-BOTPTA302',
'streamed', 'botpt_nano_sample_15s')
botpt_fn = 'deployment0001_RS03ECAL-MJ03E-06-BOTPTA302-streamed-botpt_nano_sample.nc'
cals = json.load(open(os.path.join(DATA_DIR, 'cals.json')))
tr = TimeRange(3674160000.0, 3674181600.1)
coefficients = {
k: [{
'start': tr.start - 1,
'stop': tr.stop + 1,
'value': cals[k],
'deployment': 1
}]
for k in cals
}
sr = StreamRequest(botpt_15s_sk, [],
coefficients,
tr, {},
request_id='UNIT')
botps_ds = xr.open_dataset(os.path.join(DATA_DIR, botpt_fn),
decode_times=False)
botps_ds = botps_ds[self.base_params +
[p.name for p in sr.stream_parameters[botpt_sk]]]
sr.datasets[botpt_sk] = StreamDataset(botpt_sk, sr.coefficients,
sr.uflags, [], sr.request_id)
sr.datasets[botpt_15s_sk] = StreamDataset(botpt_15s_sk,
sr.coefficients, sr.uflags,
[botpt_sk], sr.request_id)
sr.datasets[botpt_sk]._insert_dataset(botps_ds)
sr.calculate_derived_products()
result = sr.datasets[botpt_15s_sk].datasets[1]
self.assertIn('botsflu_time15s', result)
self.assertIn('botsflu_meanpres', result)
self.assertIn('botsflu_meandepth', result)
self.assertIn('botsflu_5minrate', result)
self.assertIn('botsflu_10minrate', result)
self.assertIn('botsflu_predtide', result)
def test_calculate_internal_multiple_deployments(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn),
decode_times=False)
ctd_ds = ctd_ds[[
'obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0'
]]
# remap times to make this two separate deployments
dep1_start = self.ctd_events.deps[1].ntp_start
dep2_stop = self.ctd_events.deps[2].ntp_start + 864000
ctd_ds.time.values = np.linspace(dep1_start + 1,
dep2_stop - 1,
num=ctd_ds.time.shape[0])
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_all()
for deployment in ctd_stream_dataset.datasets:
ds = ctd_stream_dataset.datasets[deployment]
tempwat = ctd_sbe16plus_tempwat(
ds.temperature,
ctd_stream_dataset.events.get_cal('CC_a0', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a1', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a2', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a3', deployment)[0][2])
np.testing.assert_array_equal(ds.seawater_temperature, tempwat)
pracsal = ctd_pracsal(ds.seawater_conductivity,
ds.seawater_temperature,
ds.seawater_pressure)
np.testing.assert_array_equal(ds.practical_salinity, pracsal)
def test_provenance_as_netcdf_attribute_missing(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = copy.deepcopy(self.ctd_events)
ctd_stream_dataset.events.deps = {}
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.insert_instrument_attributes()
def test_log_algorithm_inputs_no_result(self):
def mock_write(self):
return json.dumps(self.m_qdata, default=jdefault)
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
coefficients = {k: [{'start': tr.start - 1, 'stop': tr.stop + 1, 'value': v, 'deployment': 1}]
for k, v in self.ctd_nutnr_cals.iteritems()}
coefficients = CalibrationCoefficientStore(coefficients, 'UNIT')
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
uflags = {'advancedStreamEngineLogging': True, 'userName': '******'}
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, coefficients, uflags, [], 'UNIT')
ctd_stream_dataset._insert_dataset(ctd_ds)
parameter = Parameter.query.get(911)
with mock.patch('util.stream_dataset.ParameterReport.write', new=mock_write):
result = ctd_stream_dataset._log_algorithm_inputs(parameter, {}, None, self.ctdpf_sk, ctd_ds)
self.assertIsNotNone(result)
def fetch_raw_data(self):
"""
Fetch the source data for this request
:return:
"""
for stream_key, stream_parameters in self.stream_parameters.iteritems(
):
other_streams = set(self.stream_parameters)
other_streams.remove(stream_key)
should_pad = stream_key != self.stream_key
if not stream_key.is_virtual:
log.debug('<%s> Fetching raw data for %s', self.request_id,
stream_key.as_refdes())
sd = StreamDataset(stream_key, self.coefficients, self.uflags,
other_streams, self.request_id)
try:
sd.fetch_raw_data(self.time_range, self.limit, should_pad)
self.datasets[stream_key] = sd
except MissingDataException as e:
if stream_key == self.stream_key:
raise MissingDataException(
"Query returned no results for primary stream")
elif stream_key in self.stream_key.stream.source_streams:
raise MissingDataException(
"Query returned no results for source stream")
else:
log.error('<%s> %s', self.request_id, e.message)
else:
log.debug('<%s> Creating empty dataset for virtual stream: %s',
self.request_id, stream_key.as_refdes())
sd = StreamDataset(stream_key, self.coefficients, self.uflags,
other_streams, self.request_id)
self.datasets[stream_key] = sd
def test_calculate_internal_multiple_deployments(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
# remap times to make this two separate deployments
dep1_start = self.ctd_events.deps[1].ntp_start
dep2_stop = self.ctd_events.deps[2].ntp_start + 864000
ctd_ds.time.values = np.linspace(dep1_start+1, dep2_stop-1, num=ctd_ds.time.shape[0])
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_all()
for deployment in ctd_stream_dataset.datasets:
ds = ctd_stream_dataset.datasets[deployment]
tempwat = ctd_sbe16plus_tempwat(ds.temperature,
ctd_stream_dataset.events.get_cal('CC_a0', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a1', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a2', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a3', deployment)[0][2])
np.testing.assert_array_equal(ds.seawater_temperature, tempwat)
pracsal = ctd_pracsal(ds.seawater_conductivity,
ds.seawater_temperature,
ds.seawater_pressure)
np.testing.assert_array_equal(ds.practical_salinity, pracsal)
def test_calculate_internal_multiple_deployments(self):
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
coefficients = {k: [{'start': tr.start-1, 'stop': tr.stop+1, 'value': v, 'deployment': 1},
{'start': tr.start-1, 'stop': tr.stop+1, 'value': v, 'deployment': 2}]
for k, v in self.ctd_nutnr_cals.iteritems()}
coefficients = CalibrationCoefficientStore(coefficients, 'UNIT')
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
ctd_ds.deployment.values[:100000] = 1
ctd_ds.deployment.values[100000:] = 2
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, coefficients, {}, [], 'UNIT')
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_internal()
for ds in ctd_stream_dataset.datasets.itervalues():
tempwat = ctd_sbe16plus_tempwat(ds.temperature,
self.ctd_nutnr_cals['CC_a0'], self.ctd_nutnr_cals['CC_a1'],
self.ctd_nutnr_cals['CC_a2'], self.ctd_nutnr_cals['CC_a3'])
np.testing.assert_array_equal(ds.seawater_temperature, tempwat)
pracsal = ctd_pracsal(ds.seawater_conductivity,
ds.seawater_temperature,
ds.seawater_pressure)
np.testing.assert_array_equal(ds.practical_salinity, pracsal)
def test_pressure_depth_renamed(self):
dosta_fn = 'dosta_abcdjm_cspp_instrument_recovered.nc'
ctd_fn = 'ctdpf_j_cspp_instrument_recovered.nc'
dosta_ds = xr.open_dataset(os.path.join(DATA_DIR, dosta_fn),
decode_times=False)
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, ctd_fn),
decode_times=False)
tr = TimeRange(dosta_ds.time.values[0], dosta_ds.time.values[-1])
sr = StreamRequest(self.dosta_sk, [], tr, {}, request_id='UNIT')
dosta_ds = dosta_ds[
self.base_params +
[p.name for p in sr.stream_parameters[self.dosta_sk]]]
sr.datasets[self.dosta_sk] = StreamDataset(self.dosta_sk, sr.uflags,
[self.ctd_sk2],
sr.request_id)
sr.datasets[self.ctd_sk2] = StreamDataset(self.ctd_sk2, sr.uflags,
[self.dosta_sk],
sr.request_id)
sr.datasets[self.dosta_sk]._insert_dataset(dosta_ds)
sr.datasets[self.ctd_sk2]._insert_dataset(ctd_ds)
sr.calculate_derived_products()
sr.import_extra_externals()
sr.rename_parameters()
self.assertNotIn('pressure_depth',
sr.datasets[self.dosta_sk].datasets[1])
self.assertIn('pressure', sr.datasets[self.dosta_sk].datasets[1])
data = json.loads(JsonResponse(sr).json())
for each in data:
self.assertNotIn('pressure_depth', each)
self.assertIn('pressure', each)
def create_echo_sounding_sr(self, parameters=None):
parameters = [] if parameters is None else parameters
echo_fn = 'echo_sounding.nc'
echo_ds = xr.open_dataset(os.path.join(DATA_DIR, echo_fn), decode_times=False)
# somehow the times in this dataset are corrupted. Remap to valid times spanning both deployments
dep1_start = self.hpies_events.deps[1].ntp_start
dep2_end = self.hpies_events.deps[2].ntp_start + 864000
echo_ds.time.values = np.linspace(dep1_start + 1, dep2_end - 1, num=echo_ds.time.shape[0])
tr = TimeRange(dep1_start, dep2_end)
sr = StreamRequest(self.echo_sk, parameters, tr, {}, request_id='UNIT')
sr.datasets[self.echo_sk] = StreamDataset(self.echo_sk, sr.uflags, [], sr.request_id)
sr.datasets[self.echo_sk].events = self.hpies_events
sr.datasets[self.echo_sk]._insert_dataset(echo_ds)
return sr
def test_provenance_as_netcdf_attribute_missing(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = copy.deepcopy(self.ctd_events)
ctd_stream_dataset.events.deps = {}
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.insert_instrument_attributes()
def test_fill_missing(self):
velpt_ds = xr.open_dataset(os.path.join(DATA_DIR, self.velpt_fn), decode_times=False)
velpt_ds = velpt_ds[['obs', 'time', 'deployment', 'velocity_beam1', 'velocity_beam2', 'velocity_beam3',
'amplitude_beam1', 'amplitude_beam2', 'amplitude_beam3']]
velpt_stream_dataset = StreamDataset(self.velpt_sk, {}, [], 'UNIT')
velpt_stream_dataset.events = self.velpt_events
velpt_stream_dataset._insert_dataset(velpt_ds)
velpt_stream_dataset.fill_missing()
expected_params = ['eastward_velocity']
self.assert_parameters_in_datasets(velpt_stream_dataset.datasets, expected_params, expect_fill=True)
def test_fill_missing(self):
velpt_ds = xr.open_dataset(os.path.join(DATA_DIR, self.velpt_fn), decode_times=False)
velpt_ds = velpt_ds[['obs', 'time', 'deployment', 'velocity_beam1', 'velocity_beam2', 'velocity_beam3',
'amplitude_beam1', 'amplitude_beam2', 'amplitude_beam3']]
velpt_stream_dataset = StreamDataset(self.velpt_sk, {}, [], 'UNIT')
velpt_stream_dataset.events = self.velpt_events
velpt_stream_dataset._insert_dataset(velpt_ds)
velpt_stream_dataset.fill_missing()
expected_params = ['eastward_velocity']
self.assert_parameters_in_datasets(velpt_stream_dataset.datasets, expected_params, expect_fill=True)
def test_provenance_as_netcdf_attribute(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn),
decode_times=False)
ctd_ds = ctd_ds[[
'obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0'
]]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.insert_instrument_attributes()
for ds in ctd_stream_dataset.datasets.itervalues():
self.assertIn('Manufacturer', ds.attrs)
self.assertIn('ModelNumber', ds.attrs)
self.assertIn('SerialNumber', ds.attrs)
self.assertIn('Description', ds.attrs)
self.assertIn('FirmwareVersion', ds.attrs)
self.assertIn('SoftwareVersion', ds.attrs)
self.assertIn('AssetUniqueID', ds.attrs)
self.assertIn('Notes', ds.attrs)
self.assertIn('Owner', ds.attrs)
self.assertIn('RemoteResources', ds.attrs)
self.assertIn('ShelfLifeExpirationDate', ds.attrs)
self.assertIn('Mobile', ds.attrs)
self.assertIn('AssetManagementRecordLastModified', ds.attrs)
self.assertEqual(ds.attrs['Manufacturer'], 'Sea-Bird Electronics')
self.assertEqual(ds.attrs['ModelNumber'], 'SBE 16plus V2')
self.assertEqual(ds.attrs['SerialNumber'], '16-50112')
self.assertEqual(ds.attrs['Description'],
'CTD Profiler: CTDPF Series A')
self.assertEqual(ds.attrs['AssetUniqueID'], 'ATOSU-66662-00013')
self.assertEqual(ds.attrs['Mobile'], 'False')
self.assertEqual(ds.attrs['AssetManagementRecordLastModified'],
'2017-04-03T23:48:25.650000')
self.assertEqual(ds.attrs['FirmwareVersion'], 'Not specified.')
self.assertEqual(ds.attrs['SoftwareVersion'], 'Not specified.')
self.assertEqual(ds.attrs['Notes'], 'Not specified.')
self.assertEqual(ds.attrs['Owner'], 'Not specified.')
self.assertEqual(ds.attrs['RemoteResources'], '[]')
self.assertEqual(ds.attrs['ShelfLifeExpirationDate'],
'Not specified.')
def test_function_map_scalar(self):
echo_fn = 'echo_sounding.nc'
echo_ds = xr.open_dataset(os.path.join(DATA_DIR, echo_fn),
decode_times=False)
echo_sk = StreamKey('RS01SLBS', 'LJ01A', '05-HPIESA101', 'streamed',
'echo_sounding')
tr = TimeRange(0, 99999999)
sr = StreamRequest(echo_sk, [], {}, tr, {}, request_id='UNIT')
sr.datasets[echo_sk] = StreamDataset(echo_sk, sr.coefficients,
sr.uflags, [], sr.request_id)
sr.datasets[echo_sk]._insert_dataset(echo_ds)
sr.calculate_derived_products()
sr._add_location()
expected = {
'hpies_travel_time1_L1', 'hpies_travel_time2_L1',
'hpies_travel_time3_L1', 'hpies_travel_time4_L1',
'hpies_bliley_temperature_L1', 'hpies_pressure_L1'
}
missing = expected.difference(sr.datasets[echo_sk].datasets[0])
self.assertSetEqual(missing, set())
def test_log_algorithm_inputs_no_result(self):
def mock_write(self):
return json.dumps(self.m_qdata, default=jdefault)
uflags = {'advancedStreamEngineLogging': True, 'userName': '******'}
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, uflags, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
parameter = Parameter.query.get(13)
with mock.patch('util.stream_dataset.ParameterReport.write', new=mock_write):
result = ctd_stream_dataset._log_algorithm_inputs(parameter, {}, None, self.ctdpf_sk, ctd_ds)
self.assertIsNotNone(result)
def test_add_location(self):
echo_fn = 'echo_sounding.nc'
echo_ds = xr.open_dataset(os.path.join(DATA_DIR, echo_fn),
decode_times=False)
echo_ds.deployment.values[:20] = 1
echo_ds.deployment.values[20:] = 2
echo_sk = StreamKey('RS01SLBS', 'LJ01A', '05-HPIESA101', 'streamed',
'echo_sounding')
location_info = {
echo_sk.as_three_part_refdes(): [{
'deployment': 1,
'lat': 1,
'lon': 5
}, {
'deployment': 2,
'lat': 2,
'lon': 6
}]
}
tr = TimeRange(0, 99999999)
sr = StreamRequest(echo_sk, [], {},
tr, {},
location_information=location_info,
request_id='UNIT')
sr.datasets[echo_sk] = StreamDataset(echo_sk, sr.coefficients,
sr.uflags, [], sr.request_id)
sr.datasets[echo_sk]._insert_dataset(echo_ds)
sr.calculate_derived_products()
sr._add_location()
ds = sr.datasets[echo_sk]
for deployment, lat, lon in [(1, 1.0, 5.0), (2, 2.0, 6.0)]:
lats = set(np.unique(ds.datasets[deployment].lat.values))
lons = set(np.unique(ds.datasets[deployment].lon.values))
self.assertSetEqual(lats, {lat})
self.assertSetEqual(lons, {lon})
def test_provenance_as_netcdf_attribute(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.insert_instrument_attributes()
for ds in ctd_stream_dataset.datasets.itervalues():
self.assertIn('Manufacturer', ds.attrs)
self.assertIn('ModelNumber', ds.attrs)
self.assertIn('SerialNumber', ds.attrs)
self.assertIn('Description', ds.attrs)
self.assertIn('FirmwareVersion', ds.attrs)
self.assertIn('SoftwareVersion', ds.attrs)
self.assertIn('AssetUniqueID', ds.attrs)
self.assertIn('Notes', ds.attrs)
self.assertIn('Owner', ds.attrs)
self.assertIn('RemoteResources', ds.attrs)
self.assertIn('ShelfLifeExpirationDate', ds.attrs)
self.assertIn('Mobile', ds.attrs)
self.assertIn('AssetManagementRecordLastModified', ds.attrs)
self.assertEqual(ds.attrs['Manufacturer'], 'Sea-Bird Electronics')
self.assertEqual(ds.attrs['ModelNumber'], 'SBE 16plus V2')
self.assertEqual(ds.attrs['SerialNumber'], '16-50112')
self.assertEqual(ds.attrs['Description'], 'CTD Profiler: CTDPF Series A')
self.assertEqual(ds.attrs['AssetUniqueID'], 'ATOSU-66662-00013')
self.assertEqual(ds.attrs['Mobile'], 'False')
self.assertEqual(ds.attrs['AssetManagementRecordLastModified'], '2017-04-03T23:48:25.650000')
self.assertEqual(ds.attrs['FirmwareVersion'], 'Not specified.')
self.assertEqual(ds.attrs['SoftwareVersion'], 'Not specified.')
self.assertEqual(ds.attrs['Notes'], 'Not specified.')
self.assertEqual(ds.attrs['Owner'], 'Not specified.')
self.assertEqual(ds.attrs['RemoteResources'], '[]')
self.assertEqual(ds.attrs['ShelfLifeExpirationDate'], 'Not specified.')
def test_calculate_internal_single_deployment(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_all()
for deployment in ctd_stream_dataset.datasets:
ds = ctd_stream_dataset.datasets[deployment]
tempwat = ctd_sbe16plus_tempwat(ds.temperature,
ctd_stream_dataset.events.get_cal('CC_a0', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a1', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a2', deployment)[0][2],
ctd_stream_dataset.events.get_cal('CC_a3', deployment)[0][2])
np.testing.assert_array_equal(ds.seawater_temperature, tempwat)
pracsal = ctd_pracsal(ds.seawater_conductivity,
ds.seawater_temperature,
ds.seawater_pressure)
np.testing.assert_array_equal(ds.practical_salinity, pracsal)
def test_calculate_external_single_deployment(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
nut_ds = xr.open_dataset(os.path.join(DATA_DIR, self.nutnr_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
nut_ds = nut_ds[['obs', 'time', 'deployment', 'spectral_channels',
'frame_type', 'nutnr_dark_value_used_for_fit']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_all()
nut_stream_dataset = StreamDataset(self.nutnr_sk, {}, [self.ctdpf_sk], 'UNIT')
nut_stream_dataset.events = self.nut_events
nut_stream_dataset._insert_dataset(nut_ds)
nut_stream_dataset.calculate_all()
nut_stream_dataset.interpolate_needed({self.ctdpf_sk: ctd_stream_dataset})
nut_stream_dataset.calculate_all()
expected_params = ['ctdpf_sbe43_sample-seawater_temperature',
'ctdpf_sbe43_sample-practical_salinity',
'salinity_corrected_nitrate']
self.assert_parameters_in_datasets(nut_stream_dataset.datasets, expected_params)
def test_calculate_external_12035(self):
velpt_ds = xr.open_dataset(os.path.join(DATA_DIR, self.velpt_fn), decode_times=False)
metbk_ds = xr.open_dataset(os.path.join(DATA_DIR, self.metbk_fn), decode_times=False)
velpt_ds = velpt_ds[['obs', 'time', 'deployment', 'velocity_beam1', 'velocity_beam2', 'velocity_beam3',
'amplitude_beam1', 'amplitude_beam2', 'amplitude_beam3']]
metbk_ds = metbk_ds[['obs', 'time', 'deployment', 'barometric_pressure', 'relative_humidity',
'air_temperature', 'longwave_irradiance', 'precipitation', 'sea_surface_temperature',
'sea_surface_conductivity', 'shortwave_irradiance', 'eastward_wind_velocity',
'northward_wind_velocity']]
velpt_stream_dataset = StreamDataset(self.velpt_sk, {}, [], 'UNIT')
velpt_stream_dataset.events = self.velpt_events
velpt_stream_dataset._insert_dataset(velpt_ds)
velpt_stream_dataset.calculate_all()
metbk_stream_dataset = StreamDataset(self.metbk_sk, {}, [self.velpt_sk], 'UNIT')
metbk_stream_dataset.events = self.metbk_events
metbk_stream_dataset._insert_dataset(metbk_ds)
metbk_stream_dataset.calculate_all()
metbk_stream_dataset.interpolate_needed({self.velpt_sk: velpt_stream_dataset})
metbk_stream_dataset.calculate_all()
expected_params = ['met_barpres',
'met_windavg_mag_corr_east',
'met_windavg_mag_corr_north',
'met_current_direction',
'met_current_speed',
'met_relwind_direction',
'met_relwind_speed',
'met_netsirr',
'met_salsurf',
'met_spechum',
'met_heatflx_minute',
'met_latnflx_minute',
'met_netlirr_minute',
'met_sensflx_minute',
]
self.assert_parameters_in_datasets(metbk_stream_dataset.datasets, expected_params)
def test_exclude_data(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn),
decode_times=False)
ctd_ds = ctd_ds[[
'obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0'
]]
times = ctd_ds.time.values
store = AnnotationStore()
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.exclude_flagged_data(store)
np.testing.assert_array_equal(
times, ctd_stream_dataset.datasets[2].time.values)
# exclude a bit
start = ntplib.ntp_to_system_time(times[0]) * 1000
stop = ntplib.ntp_to_system_time(times[100]) * 1000
anno = self._create_exclusion_anno(self.ctdpf_sk, start, stop)
store.add_annotations([anno])
ctd_stream_dataset.exclude_flagged_data(store)
np.testing.assert_array_equal(
times[101:], ctd_stream_dataset.datasets[2].time.values)
# exclude everything
start = ntplib.ntp_to_system_time(times[0]) * 1000
stop = ntplib.ntp_to_system_time(times[-1]) * 1000
anno = self._create_exclusion_anno(self.ctdpf_sk, start, stop)
store.add_annotations([anno])
ctd_stream_dataset.exclude_flagged_data(store)
self.assertNotIn(2, ctd_stream_dataset.datasets)
def test_calculate_external_multiple_deployments(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn),
decode_times=False)
nut_ds = xr.open_dataset(os.path.join(DATA_DIR, self.nutnr_fn),
decode_times=False)
ctd_ds = ctd_ds[[
'obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0'
]]
nut_ds = nut_ds[[
'obs', 'time', 'deployment', 'spectral_channels', 'frame_type',
'nutnr_dark_value_used_for_fit'
]]
# remap times to make this two separate deployments
dep1_start = self.ctd_events.deps[1].ntp_start
dep2_stop = self.ctd_events.deps[2].ntp_start + 864000
ctd_ds.time.values = np.linspace(dep1_start + 1,
dep2_stop - 1,
num=ctd_ds.time.shape[0])
nut_ds.time.values = np.linspace(dep1_start + 1,
dep2_stop - 1,
num=nut_ds.time.shape[0])
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_all()
nut_stream_dataset = StreamDataset(self.nutnr_sk, {}, [self.ctdpf_sk],
'UNIT')
nut_stream_dataset.events = self.nut_events
nut_stream_dataset._insert_dataset(nut_ds)
nut_stream_dataset.calculate_all()
nut_stream_dataset.interpolate_needed(
{self.ctdpf_sk: ctd_stream_dataset})
nut_stream_dataset.calculate_all()
expected_params = [
'ctdpf_sbe43_sample-seawater_temperature',
'ctdpf_sbe43_sample-practical_salinity',
'salinity_corrected_nitrate'
]
self.assert_parameters_in_datasets(nut_stream_dataset.datasets,
expected_params)
def test_calculate_external_12035(self):
velpt_ds = xr.open_dataset(os.path.join(DATA_DIR, self.velpt_fn),
decode_times=False)
metbk_ds = xr.open_dataset(os.path.join(DATA_DIR, self.metbk_fn),
decode_times=False)
velpt_ds = velpt_ds[[
'obs', 'time', 'deployment', 'velocity_beam1', 'velocity_beam2',
'velocity_beam3', 'amplitude_beam1', 'amplitude_beam2',
'amplitude_beam3'
]]
metbk_ds = metbk_ds[[
'obs', 'time', 'deployment', 'barometric_pressure',
'relative_humidity', 'air_temperature', 'longwave_irradiance',
'precipitation', 'sea_surface_temperature',
'sea_surface_conductivity', 'shortwave_irradiance',
'eastward_wind_velocity', 'northward_wind_velocity'
]]
velpt_stream_dataset = StreamDataset(self.velpt_sk, {}, [], 'UNIT')
velpt_stream_dataset.events = self.velpt_events
velpt_stream_dataset._insert_dataset(velpt_ds)
velpt_stream_dataset.calculate_all()
metbk_stream_dataset = StreamDataset(self.metbk_sk, {},
[self.velpt_sk], 'UNIT')
metbk_stream_dataset.events = self.metbk_events
metbk_stream_dataset._insert_dataset(metbk_ds)
metbk_stream_dataset.calculate_all()
metbk_stream_dataset.interpolate_needed(
{self.velpt_sk: velpt_stream_dataset})
metbk_stream_dataset.calculate_all()
expected_params = [
'met_barpres',
'met_windavg_mag_corr_east',
'met_windavg_mag_corr_north',
'met_current_direction',
'met_current_speed',
'met_relwind_direction',
'met_relwind_speed',
'met_netsirr',
'met_salsurf',
'met_spechum',
'met_heatflx_minute',
'met_latnflx_minute',
'met_netlirr_minute',
'met_sensflx_minute',
]
self.assert_parameters_in_datasets(metbk_stream_dataset.datasets,
expected_params)
def test_calculate_external_multiple_deployments(self):
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
nut_ds = xr.open_dataset(os.path.join(DATA_DIR, self.nutnr_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
nut_ds = nut_ds[['obs', 'time', 'deployment', 'spectral_channels',
'frame_type', 'nutnr_dark_value_used_for_fit']]
# remap times to make this two separate deployments
dep1_start = self.ctd_events.deps[1].ntp_start
dep2_stop = self.ctd_events.deps[2].ntp_start + 864000
ctd_ds.time.values = np.linspace(dep1_start + 1, dep2_stop - 1, num=ctd_ds.time.shape[0])
nut_ds.time.values = np.linspace(dep1_start + 1, dep2_stop - 1, num=nut_ds.time.shape[0])
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, {}, [], 'UNIT')
ctd_stream_dataset.events = self.ctd_events
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_all()
nut_stream_dataset = StreamDataset(self.nutnr_sk, {}, [self.ctdpf_sk], 'UNIT')
nut_stream_dataset.events = self.nut_events
nut_stream_dataset._insert_dataset(nut_ds)
nut_stream_dataset.calculate_all()
nut_stream_dataset.interpolate_needed({self.ctdpf_sk: ctd_stream_dataset})
nut_stream_dataset.calculate_all()
expected_params = ['ctdpf_sbe43_sample-seawater_temperature',
'ctdpf_sbe43_sample-practical_salinity',
'salinity_corrected_nitrate']
self.assert_parameters_in_datasets(nut_stream_dataset.datasets, expected_params)
def fetch_raw_data(self):
"""
Fetch the source data for this request
:return:
"""
# Start fetching calibration data from Asset Management
am_events = {}
am_futures = {}
for stream_key in self.stream_parameters:
refdes = '-'.join((stream_key.subsite, stream_key.node, stream_key.sensor))
am_futures[stream_key] = self.asset_management.get_events_async(refdes)
# Resolve calibration data futures and attach to instrument data
for stream_key in am_futures:
events = am_futures[stream_key].result()
am_events[stream_key] = events
# Start fetching instrument data
for stream_key, stream_parameters in self.stream_parameters.iteritems():
other_streams = set(self.stream_parameters)
other_streams.remove(stream_key)
should_pad = stream_key != self.stream_key
if not stream_key.is_virtual:
log.debug('<%s> Fetching raw data for %s', self.request_id, stream_key.as_refdes())
sd = StreamDataset(stream_key, self.uflags, other_streams, self.request_id)
sd.events = am_events[stream_key]
try:
sd.fetch_raw_data(self.time_range, self.limit, should_pad)
self.datasets[stream_key] = sd
except MissingDataException as e:
if stream_key == self.stream_key:
raise MissingDataException("Query returned no results for primary stream")
elif stream_key.stream in self.stream_key.stream.source_streams:
raise MissingDataException("Query returned no results for source stream")
else:
log.error('<%s> %s', self.request_id, e.message)
else:
log.debug('<%s> Creating empty dataset for virtual stream: %s',
self.request_id, stream_key.as_refdes())
sd = StreamDataset(stream_key, self.uflags, other_streams, self.request_id)
sd.events = am_events[stream_key]
self.datasets[stream_key] = sd
# Fetch annotations
self._insert_annotations()
self._exclude_flagged_data()
self._exclude_nondeployed_data()
# Verify data still exists after masking virtual
message = 'Query returned no results for %s stream (due to deployment or annotation mask)'
if self.stream_key.is_virtual:
found_streams = [stream.stream for stream in self.datasets
if self.datasets[stream]]
if not any(stream in self.stream_key.stream.source_streams for stream in found_streams):
raise MissingDataException(message % 'source')
# real
else:
primary_stream_dataset = self.datasets[self.stream_key]
if not primary_stream_dataset.datasets:
raise MissingDataException(message % 'primary')
# Remove any empty, non-virtual supporting datasets
for stream_key in list(self.datasets):
if not stream_key.is_virtual:
if not self.datasets[stream_key].datasets:
del self.datasets[stream_key]
def test_calculate_external_single_deployment(self):
tr = TimeRange(3.65342400e+09, 3.65351040e+09)
coefficients = {k: [{'start': tr.start-1, 'stop': tr.stop+1, 'value': v, 'deployment': 1}]
for k, v in self.ctd_nutnr_cals.iteritems()}
coefficients = CalibrationCoefficientStore(coefficients, 'UNIT')
ctd_ds = xr.open_dataset(os.path.join(DATA_DIR, self.ctdpf_fn), decode_times=False)
nut_ds = xr.open_dataset(os.path.join(DATA_DIR, self.nutnr_fn), decode_times=False)
ctd_ds = ctd_ds[['obs', 'time', 'deployment', 'temperature', 'pressure',
'pressure_temp', 'conductivity', 'ext_volt0']]
nut_ds = nut_ds[['obs', 'time', 'deployment', 'spectral_channels',
'frame_type', 'nutnr_dark_value_used_for_fit']]
ctd_stream_dataset = StreamDataset(self.ctdpf_sk, coefficients, {}, [], 'UNIT')
ctd_stream_dataset._insert_dataset(ctd_ds)
ctd_stream_dataset.calculate_internal()
nut_stream_dataset = StreamDataset(self.nutnr_sk, coefficients, {}, [self.ctdpf_sk], 'UNIT')
nut_stream_dataset._insert_dataset(nut_ds)
nut_stream_dataset.calculate_internal()
nut_stream_dataset.interpolate_needed({self.ctdpf_sk: ctd_stream_dataset})
nut_stream_dataset.calculate_external()
expected_params = ['ctdpf_sbe43_sample-seawater_temperature',
'ctdpf_sbe43_sample-practical_salinity',
'temp_sal_corrected_nitrate']
self.assert_parameters_in_datasets(nut_stream_dataset.datasets, expected_params)