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_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_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 test_botpt_24hr(self):
botpt_sk = StreamKey('RS03ECAL', 'MJ03E', '06-BOTPTA302', 'streamed', 'botpt_nano_sample')
botpt_24hr_sk = StreamKey('RS03ECAL', 'MJ03E', '06-BOTPTA302', 'streamed', 'botpt_nano_sample_24hr')
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_24hr_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_24hr_sk] = StreamDataset(botpt_24hr_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_24hr_sk].datasets[1]
self.assertIn('botsflu_time24h', result) # TODO - input is currently defined as TIME15S, should be TIME?
self.assertIn('botsflu_daydepth', result)
self.assertIn('botsflu_4wkrate', result)
self.assertIn('botsflu_8wkrate', result)
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_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 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_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_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_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_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()
self.assertIn('ctdgv_m_glider_instrument_recovered-sci_water_pressure_dbar', 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_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_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_metbk_hourly(self):
cals = {
'CC_lat': 40.13678333,
'CC_lon': -70.76978333,
'CC_depth_of_conductivity_and_temperature_measurements_m': 1.0668,
'CC_height_of_air_humidity_measurement_m': 4.2926,
'CC_height_of_air_temperature_measurement_m': 4.2926,
'CC_height_of_windspeed_sensor_above_sealevel_m': 4.7498,
'CC_jcool': 1,
'CC_jwarm': 1,
'CC_zinvpbl': 600,
}
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)
hourly_sk = StreamKey('GI01SUMO', 'SBD11', '06-METBKA000', 'recovered_host', 'metbk_hourly')
source_sk = StreamKey('GI01SUMO', 'SBD11', '06-METBKA000', 'recovered_host', 'metbk_a_dcl_instrument_recovered')
vel_sk = StreamKey('GI01SUMO', 'RID16', '04-VELPTA000', 'recovered_host', 'velpt_ab_dcl_instrument_recovered')
tr = TimeRange(metbk_ds.time.values[0], metbk_ds.time.values[-1])
coefficients = {k: [{'start': tr.start-1000, 'stop': tr.stop+1000, 'value': cals[k], 'deployment': 3}] for k in cals}
sr = StreamRequest(hourly_sk, [], coefficients, tr, {}, request_id='UNIT')
metbk_ds = metbk_ds[self.base_params + [p.name for p in sr.stream_parameters[source_sk]]]
vel_ds = vel_ds[self.base_params + [p.name for p in sr.stream_parameters[vel_sk]]]
sr.datasets[source_sk] = StreamDataset(source_sk, sr.coefficients, sr.uflags, [hourly_sk, vel_sk], sr.request_id)
sr.datasets[hourly_sk] = StreamDataset(hourly_sk, sr.coefficients, sr.uflags, [source_sk, vel_sk], sr.request_id)
sr.datasets[vel_sk] = StreamDataset(vel_sk, sr.coefficients, sr.uflags, [hourly_sk, vel_sk], sr.request_id)
sr.datasets[source_sk]._insert_dataset(metbk_ds)
sr.datasets[vel_sk]._insert_dataset(vel_ds)
sr.calculate_derived_products()
expected_params = [p.name for p in hourly_sk.stream.parameters] + ['obs', 'time', 'deployment', 'lat', 'lon']
self.assertListEqual(sorted(expected_params), sorted(sr.datasets[hourly_sk].datasets[3]))
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_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_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 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 test_metbk_hourly(self):
cals = {
'CC_lat': 40.13678333,
'CC_lon': -70.76978333,
'CC_depth_of_conductivity_and_temperature_measurements_m': 1.0668,
'CC_height_of_air_humidity_measurement_m': 4.2926,
'CC_height_of_air_temperature_measurement_m': 4.2926,
'CC_height_of_windspeed_sensor_above_sealevel_m': 4.7498,
'CC_jcool': 1,
'CC_jwarm': 1,
'CC_zinvpbl': 600,
}
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)
hourly_sk = StreamKey('GI01SUMO', 'SBD11', '06-METBKA000',
'recovered_host', 'metbk_hourly')
source_sk = StreamKey('GI01SUMO', 'SBD11', '06-METBKA000',
'recovered_host',
'metbk_a_dcl_instrument_recovered')
vel_sk = StreamKey('GI01SUMO', 'RID16', '04-VELPTA000',
'recovered_host',
'velpt_ab_dcl_instrument_recovered')
tr = TimeRange(metbk_ds.time.values[0], metbk_ds.time.values[-1])
coefficients = {
k: [{
'start': tr.start - 1000,
'stop': tr.stop + 1000,
'value': cals[k],
'deployment': 3
}]
for k in cals
}
sr = StreamRequest(hourly_sk, [],
coefficients,
tr, {},
request_id='UNIT')
metbk_ds = metbk_ds[self.base_params +
[p.name for p in sr.stream_parameters[source_sk]]]
vel_ds = vel_ds[self.base_params +
[p.name for p in sr.stream_parameters[vel_sk]]]
sr.datasets[source_sk] = StreamDataset(source_sk, sr.coefficients,
sr.uflags, [hourly_sk, vel_sk],
sr.request_id)
sr.datasets[hourly_sk] = StreamDataset(hourly_sk, sr.coefficients,
sr.uflags, [source_sk, vel_sk],
sr.request_id)
sr.datasets[vel_sk] = StreamDataset(vel_sk, sr.coefficients, sr.uflags,
[hourly_sk, vel_sk], sr.request_id)
sr.datasets[source_sk]._insert_dataset(metbk_ds)
sr.datasets[vel_sk]._insert_dataset(vel_ds)
sr.calculate_derived_products()
expected_params = [p.name for p in hourly_sk.stream.parameters
] + ['obs', 'time', 'deployment', 'lat', 'lon']
self.assertListEqual(sorted(expected_params),
sorted(sr.datasets[hourly_sk].datasets[3]))