import numpy.ma as ma
import iris
import iris.exceptions
from iris.coord_systems import GeogCS, RotatedGeogCS, TransverseMercator
from iris.fileformats.grib import grib_phenom_translation as gptx
from iris.fileformats.grib._load_convert import (_STATISTIC_TYPE_NAMES,
_TIME_RANGE_UNITS)
from iris.util import is_regular, regular_step
# Invert code tables from :mod:`iris.fileformats.grib._load_convert`.
_STATISTIC_TYPE_NAMES = {
val: key
for key, val in _STATISTIC_TYPE_NAMES.items()
}
_TIME_RANGE_UNITS = {val: key for key, val in _TIME_RANGE_UNITS.items()}
def fixup_float32_as_int32(value):
"""
Workaround for use when the ECMWF GRIB API treats an IEEE 32-bit
floating-point value as a signed, 4-byte integer.
Returns the integer value which will result in the on-disk
representation corresponding to the IEEE 32-bit floating-point
value.
"""
value_as_float32 = np.array(value, dtype='f4')
value_as_uint32 = value_as_float32.view(dtype='u4')
if value_as_uint32 >= 0x80000000:
import numpy.ma as ma
import iris
import iris.exceptions
import iris.unit
from iris.coord_systems import GeogCS, RotatedGeogCS, TransverseMercator
from iris.fileformats.grib import grib_phenom_translation as gptx
from iris.fileformats.grib._load_convert import (_STATISTIC_TYPE_NAMES,
_TIME_RANGE_UNITS)
from iris.util import is_regular, regular_step
# Invert code tables from :mod:`iris.fileformats.grib._load_convert`.
_STATISTIC_TYPE_NAMES = {val: key for key, val in
_STATISTIC_TYPE_NAMES.items()}
_TIME_RANGE_UNITS = {val: key for key, val in _TIME_RANGE_UNITS.items()}
def fixup_float32_as_int32(value):
"""
Workaround for use when the ECMWF GRIB API treats an IEEE 32-bit
floating-point value as a signed, 4-byte integer.
Returns the integer value which will result in the on-disk
representation corresponding to the IEEE 32-bit floating-point
value.
"""
value_as_float32 = np.array(value, dtype='f4')
value_as_uint32 = value_as_float32.view(dtype='u4')
if value_as_uint32 >= 0x80000000: