def test_load_probability_forecast(self):
# Test GribWrapper interpretation of PDT 4.9 data.
# NOTE:
# Currently Iris has only partial support for PDT 4.9.
# Though it can load the data, key metadata (thresholds) is lost.
# At present, we are not testing for this.
# Make a testing grib message in memory, with gribapi.
grib_message = gribapi.grib_new_from_samples('GRIB2')
gribapi.grib_set_long(grib_message, 'productDefinitionTemplateNumber',
9)
gribapi.grib_set_string(grib_message, 'stepRange', '10-55')
grib_wrapper = iris.fileformats.grib.GribWrapper(grib_message)
# Define two expected datetimes for _periodEndDateTime as
# gribapi v1.9.16 mis-calculates this.
# See https://software.ecmwf.int/wiki/display/GRIB/\
# GRIB+API+version+1.9.18+released
try:
# gribapi v1.9.16 has no __version__ attribute.
gribapi_ver = gribapi.__version__
except AttributeError:
gribapi_ver = gribapi.grib_get_api_version()
if StrictVersion(gribapi_ver) < StrictVersion('1.9.18'):
exp_end_date = datetime.datetime(year=2007,
month=3,
day=25,
hour=12,
minute=0,
second=0)
else:
exp_end_date = datetime.datetime(year=2007,
month=3,
day=25,
hour=19,
minute=0,
second=0)
# Check that it captures the statistics time period info.
# (And for now, nothing else)
self.assertEqual(
grib_wrapper._referenceDateTime,
datetime.datetime(year=2007,
month=3,
day=23,
hour=12,
minute=0,
second=0))
self.assertEqual(
grib_wrapper._periodStartDateTime,
datetime.datetime(year=2007,
month=3,
day=23,
hour=22,
minute=0,
second=0))
self.assertEqual(grib_wrapper._periodEndDateTime, exp_end_date)
def test_load_probability_forecast(self):
# Test GribWrapper interpretation of PDT 4.9 data.
# NOTE:
# Currently iris-grib has only partial support for PDT 4.9.
# Though it can load the data, key metadata (thresholds) is lost.
# At present, we are not testing for this.
# Make a testing grib message in memory, with gribapi.
grib_message = gribapi.grib_new_from_samples('GRIB2')
gribapi.grib_set_long(grib_message, 'productDefinitionTemplateNumber',
9)
gribapi.grib_set_string(grib_message, 'stepRange', '10-55')
grib_wrapper = iris.fileformats.grib.GribWrapper(grib_message)
# Define two expected datetimes for _periodEndDateTime as
# gribapi v1.9.16 mis-calculates this.
# See https://software.ecmwf.int/wiki/display/GRIB/\
# GRIB+API+version+1.9.18+released
try:
# gribapi v1.9.16 has no __version__ attribute.
gribapi_ver = gribapi.__version__
except AttributeError:
gribapi_ver = gribapi.grib_get_api_version()
if StrictVersion(gribapi_ver) < StrictVersion('1.9.18'):
exp_end_date = datetime.datetime(year=2007, month=3, day=25,
hour=12, minute=0, second=0)
else:
exp_end_date = datetime.datetime(year=2007, month=3, day=25,
hour=19, minute=0, second=0)
# Check that it captures the statistics time period info.
# (And for now, nothing else)
self.assertEqual(
grib_wrapper._referenceDateTime,
datetime.datetime(year=2007, month=3, day=23,
hour=12, minute=0, second=0)
)
self.assertEqual(
grib_wrapper._periodStartDateTime,
datetime.datetime(year=2007, month=3, day=23,
hour=22, minute=0, second=0)
)
self.assertEqual(grib_wrapper._periodEndDateTime, exp_end_date)
def test_load_probability_forecast(self):
# Test GribWrapper interpretation of PDT 4.9 data.
# NOTE:
# Currently Iris has only partial support for PDT 4.9.
# Though it can load the data, key metadata (thresholds) is lost.
# At present, we are not testing for this.
# Make a testing grib message in memory, with gribapi.
grib_message = gribapi.grib_new_from_samples('GRIB2')
gribapi.grib_set_long(grib_message, 'productDefinitionTemplateNumber', 9)
gribapi.grib_set_string(grib_message, 'stepRange', '10-55')
grib_wrapper = iris.fileformats.grib.GribWrapper(grib_message)
# Check that it captures the statistics time period info.
# (And for now, nothing else)
self.assertEqual(
grib_wrapper._referenceDateTime,
datetime.datetime(year=2007, month=03, day=23,
hour=12, minute=0, second=0)
)
def test_load_probability_forecast(self):
# Test GribWrapper interpretation of PDT 4.9 data.
# NOTE:
# Currently Iris has only partial support for PDT 4.9.
# Though it can load the data, key metadata (thresholds) is lost.
# At present, we are not testing for this.
# Make a testing grib message in memory, with gribapi.
grib_message = gribapi.grib_new_from_samples('GRIB2')
gribapi.grib_set_long(grib_message, 'productDefinitionTemplateNumber',
9)
gribapi.grib_set_string(grib_message, 'stepRange', '10-55')
grib_wrapper = iris.fileformats.grib.GribWrapper(grib_message)
# Check that it captures the statistics time period info.
# (And for now, nothing else)
self.assertEqual(
grib_wrapper._referenceDateTime,
datetime.datetime(year=2007, month=03, day=23,
hour=12, minute=0, second=0)
)
