def test_from_dict(self):
d = dict(standard_name='lwe_thickness_of_precipitation_amount')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount'
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
vertical_datum='NAVD88')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#vertical_datum=navd88'
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
vertical_datum='NAVD88',
discriminant='2')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount:2#vertical_datum=navd88'
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
cell_methods='time: sum (interval: PT24H) time: mean')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:mean,time:sum;interval=pt24h'
# Interval as a dict key (not inline with cell_methods)
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
cell_methods='time: sum time: mean',
interval='pt24h')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:mean,time:sum;interval=pt24h'
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
cell_methods='time: minimum within years time: mean over years')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:mean_over_years,time:minimum_within_years'
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
cell_methods='time: variance (interval: PT1H comment: sampled instantaneously)')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:variance;interval=pt1h'
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
cell_methods='time: variance time: mean (interval: PT1H comment: sampled instantaneously)')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:mean,time:variance;interval=pt1h'
# Interval specified twice
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
cell_methods='time: variance time: mean (interval: PT1H comment: sampled instantaneously)',
interval='PT1H')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:mean,time:variance;interval=pt1h'
# Interval specified twice
d = dict(standard_name='lwe_thickness_of_precipitation_amount',
cell_methods='time: variance time: mean (interval: PT1H comment: sampled instantaneously)',
interval='PT1H',
discriminant='2')
urn = IoosUrn.from_dict('axiom', 'foo', d)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount:2#cell_methods=time:mean,time:variance;interval=pt1h'
def test_from_variable(self):
with netCDF4.Dataset(
os.path.join(
os.path.dirname(__file__),
'resources',
'test_urn_from_variable.nc'
)
) as nc:
urn = IoosUrn.from_dict('axiom', 'foo', nc.variables['temperature'].__dict__)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#vertical_datum=navd88'
urn = IoosUrn.from_dict('axiom', 'foo', nc.variables['temperature2'].__dict__)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:variance;interval=pt1h'
urn = IoosUrn.from_dict('axiom', 'foo', nc.variables['temperature3'].__dict__)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount#cell_methods=time:mean,time:variance;interval=pt1h'
urn = IoosUrn.from_dict('axiom', 'foo', nc.variables['temperature4'].__dict__)
assert urn.urn == 'urn:ioos:sensor:axiom:foo:lwe_thickness_of_precipitation_amount:2#cell_methods=time:mean,time:variance;interval=pt1h'