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_save_rules.py
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# Copyright iris-grib contributors
#
# This file is part of iris-grib and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.
"""
Grib save implementation.
:mod:`iris_grib._save_rules` is a private module with no public API.
It is invoked from :meth:`iris_grib.save_grib2`.
"""
import warnings
import cf_units
import gribapi
import numpy as np
import numpy.ma as ma
import cartopy.crs as ccrs
import iris
from iris.aux_factory import HybridHeightFactory, HybridPressureFactory
from iris.coord_systems import (GeogCS, RotatedGeogCS, Mercator,
TransverseMercator, LambertConformal)
from iris.exceptions import TranslationError
from ._iris_mercator_support import confirm_extended_mercator_supported
from . import grib_phenom_translation as gptx
from ._load_convert import (_STATISTIC_TYPE_NAMES, _TIME_RANGE_UNITS,
_SPATIAL_PROCESSING_TYPES)
from .grib_phenom_translation import GRIBCode
from iris.util import is_regular, regular_step
# Invert code tables from :mod:`iris_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:
# Convert from two's-complement to sign-and-magnitude.
# NB. Because of the silly representation of negative
# integers in GRIB2, there is no value we can pass to
# grib_set that will result in the bit pattern 0x80000000.
# But since that bit pattern corresponds to a floating
# point value of negative-zero, we can safely treat it as
# positive-zero instead.
value_as_grib_int = 0x80000000 - int(value_as_uint32)
else:
value_as_grib_int = int(value_as_uint32)
return value_as_grib_int
def fixup_int32_as_uint32(value):
"""
Workaround for use when the ECMWF GRIB API treats a signed, 4-byte
integer value as an unsigned, 4-byte integer.
Returns the unsigned integer value which will result in the on-disk
representation corresponding to the signed, 4-byte integer value.
"""
value = int(value)
if -0x7fffffff <= value <= 0x7fffffff:
if value < 0:
# Convert from two's-complement to sign-and-magnitude.
value = 0x80000000 - value
else:
msg = '{} out of range -2147483647 to 2147483647.'.format(value)
raise ValueError(msg)
return value
def ensure_set_int32_value(grib, key, value):
"""
Ensure the workaround function :func:`fixup_int32_as_uint32` is applied as
necessary to problem keys.
"""
try:
gribapi.grib_set(grib, key, value)
except gribapi.GribInternalError:
value = fixup_int32_as_uint32(value)
gribapi.grib_set(grib, key, value)
###############################################################################
#
# Constants
#
###############################################################################
# Reference Flag Table 3.3
_RESOLUTION_AND_COMPONENTS_GRID_WINDS_BIT = 3 # NB "bit5", from MSB=1.
# Reference Regulation 92.1.6
_DEFAULT_DEGREES_UNITS = 1.0e-6
###############################################################################
#
# Identification Section 1
#
###############################################################################
def centre(cube, grib):
# TODO: read centre from cube
gribapi.grib_set_long(grib, "centre", 74) # UKMO
gribapi.grib_set_long(grib, "subCentre", 0) # exeter is not in the spec
def reference_time(cube, grib):
# Set the reference time.
# (analysis, forecast start, verify time, obs time, etc)
try:
fp_coord = cube.coord("forecast_period")
except iris.exceptions.CoordinateNotFoundError:
fp_coord = None
if fp_coord is not None:
rt, rt_meaning, _, _ = _non_missing_forecast_period(cube)
else:
rt, rt_meaning, _, _ = _missing_forecast_period(cube)
gribapi.grib_set_long(grib, "significanceOfReferenceTime", rt_meaning)
gribapi.grib_set_long(
grib, "dataDate", "%04d%02d%02d" % (rt.year, rt.month, rt.day))
gribapi.grib_set_long(
grib, "dataTime", "%02d%02d" % (rt.hour, rt.minute))
# TODO: Set the calendar, when we find out what happened to the proposal!
# http://tinyurl.com/oefqgv6
# I was sure it was approved for pre-operational use but it's not there.
def identification(cube, grib):
centre(cube, grib)
reference_time(cube, grib)
# operational product, operational test, research product, etc
# (missing for now)
gribapi.grib_set_long(grib, "productionStatusOfProcessedData", 255)
# Code table 1.4
# analysis, forecast, processed satellite, processed radar,
if cube.coords('realization'):
# assume realization will always have 1 and only 1 point
# as cubes saving to GRIB2 a 2D horizontal slices
if cube.coord('realization').points[0] != 0:
gribapi.grib_set_long(grib, "typeOfProcessedData", 4)
else:
gribapi.grib_set_long(grib, "typeOfProcessedData", 3)
else:
gribapi.grib_set_long(grib, "typeOfProcessedData", 2)
###############################################################################
#
# Grid Definition Section 3
#
###############################################################################
def shape_of_the_earth(cube, grib):
# assume latlon
cs = cube.coord(dimensions=[0]).coord_system
# Initially set shape_of_earth keys to missing (255 for byte, -1 for long).
gribapi.grib_set_long(grib, "scaleFactorOfRadiusOfSphericalEarth", 255)
gribapi.grib_set_long(grib, "scaledValueOfRadiusOfSphericalEarth", -1)
gribapi.grib_set_long(grib, "scaleFactorOfEarthMajorAxis", 255)
gribapi.grib_set_long(grib, "scaledValueOfEarthMajorAxis", -1)
gribapi.grib_set_long(grib, "scaleFactorOfEarthMinorAxis", 255)
gribapi.grib_set_long(grib, "scaledValueOfEarthMinorAxis", -1)
if isinstance(cs, GeogCS):
ellipsoid = cs
else:
ellipsoid = cs.ellipsoid
if ellipsoid is None:
msg = "Could not determine shape of the earth from coord system "\
"of horizontal grid."
raise TranslationError(msg)
# Spherical earth.
if ellipsoid.inverse_flattening == 0.0:
gribapi.grib_set_long(grib, "shapeOfTheEarth", 1)
gribapi.grib_set_long(grib, "scaleFactorOfRadiusOfSphericalEarth", 0)
gribapi.grib_set_long(grib, "scaledValueOfRadiusOfSphericalEarth",
ellipsoid.semi_major_axis)
gribapi.grib_set_long(grib, "scaleFactorOfEarthMajorAxis", 0)
gribapi.grib_set_long(grib, "scaledValueOfEarthMajorAxis", 0)
gribapi.grib_set_long(grib, "scaleFactorOfEarthMinorAxis", 0)
gribapi.grib_set_long(grib, "scaledValueOfEarthMinorAxis", 0)
# Oblate spheroid earth.
else:
gribapi.grib_set_long(grib, "shapeOfTheEarth", 7)
gribapi.grib_set_long(grib, "scaleFactorOfEarthMajorAxis", 0)
gribapi.grib_set_long(grib, "scaledValueOfEarthMajorAxis",
ellipsoid.semi_major_axis)
gribapi.grib_set_long(grib, "scaleFactorOfEarthMinorAxis", 0)
gribapi.grib_set_long(grib, "scaledValueOfEarthMinorAxis",
ellipsoid.semi_minor_axis)
def grid_dims(x_coord, y_coord, grib, x_str, y_str):
gribapi.grib_set_long(grib, x_str, x_coord.shape[0])
gribapi.grib_set_long(grib, y_str, y_coord.shape[0])
def latlon_first_last(x_coord, y_coord, grib):
if x_coord.has_bounds() or y_coord.has_bounds():
warnings.warn("Ignoring xy bounds")
# XXX Pending #1125
# gribapi.grib_set_double(grib, "latitudeOfFirstGridPointInDegrees",
# float(y_coord.points[0]))
# gribapi.grib_set_double(grib, "latitudeOfLastGridPointInDegrees",
# float(y_coord.points[-1]))
# gribapi.grib_set_double(grib, "longitudeOfFirstGridPointInDegrees",
# float(x_coord.points[0]))
# gribapi.grib_set_double(grib, "longitudeOfLastGridPointInDegrees",
# float(x_coord.points[-1]))
# WORKAROUND
gribapi.grib_set_long(grib, "latitudeOfFirstGridPoint",
int(y_coord.points[0]*1000000))
gribapi.grib_set_long(grib, "latitudeOfLastGridPoint",
int(y_coord.points[-1]*1000000))
gribapi.grib_set_long(grib, "longitudeOfFirstGridPoint",
int((x_coord.points[0] % 360)*1000000))
gribapi.grib_set_long(grib, "longitudeOfLastGridPoint",
int((x_coord.points[-1] % 360)*1000000))
def dx_dy(x_coord, y_coord, grib):
x_step = regular_step(x_coord)
y_step = regular_step(y_coord)
# Set x and y step. For degrees, this is encoded as an integer:
# 1 * 10^6 * floating point value.
# WMO Manual on Codes regulation 92.1.6
if x_coord.units == 'degrees':
gribapi.grib_set(grib, "iDirectionIncrement",
round(1e6 * float(abs(x_step))))
else:
raise ValueError('X coordinate must be in degrees, not {}'
'.'.format(x_coord.units))
if y_coord.units == 'degrees':
gribapi.grib_set(grib, "jDirectionIncrement",
round(1e6 * float(abs(y_step))))
else:
raise ValueError('Y coordinate must be in degrees, not {}'
'.'.format(y_coord.units))
def scanning_mode_flags(x_coord, y_coord, grib):
gribapi.grib_set_long(grib, "iScansPositively",
int(x_coord.points[1] - x_coord.points[0] > 0))
gribapi.grib_set_long(grib, "jScansPositively",
int(y_coord.points[1] - y_coord.points[0] > 0))
def horizontal_grid_common(cube, grib, xy=False):
nx_str, ny_str = ("Nx", "Ny") if xy else ("Ni", "Nj")
# Grib encoding of the sequences of X and Y points.
y_coord = cube.coord(dimensions=[0])
x_coord = cube.coord(dimensions=[1])
shape_of_the_earth(cube, grib)
grid_dims(x_coord, y_coord, grib, nx_str, ny_str)
scanning_mode_flags(x_coord, y_coord, grib)
def latlon_points_regular(cube, grib):
y_coord = cube.coord(dimensions=[0])
x_coord = cube.coord(dimensions=[1])
latlon_first_last(x_coord, y_coord, grib)
dx_dy(x_coord, y_coord, grib)
def latlon_points_irregular(cube, grib):
y_coord = cube.coord(dimensions=[0])
x_coord = cube.coord(dimensions=[1])
# Distinguish between true-north and grid-oriented vectors.
is_grid_wind = cube.name() in ('x_wind', 'y_wind', 'grid_eastward_wind',
'grid_northward_wind')
# Encode in bit "5" of 'resolutionAndComponentFlags' (other bits unused).
component_flags = 0
if is_grid_wind:
component_flags |= 2 ** _RESOLUTION_AND_COMPONENTS_GRID_WINDS_BIT
gribapi.grib_set(grib, 'resolutionAndComponentFlags', component_flags)
# Record the X and Y coordinate values.
# NOTE: there is currently a bug in the gribapi which means that the size
# of the longitudes array does not equal 'Nj', as it should.
# See : https://software.ecmwf.int/issues/browse/SUP-1096
# So, this only works at present if the x and y dimensions are **equal**.
lon_values = x_coord.points / _DEFAULT_DEGREES_UNITS
lat_values = y_coord.points / _DEFAULT_DEGREES_UNITS
gribapi.grib_set_array(grib, 'longitudes',
np.array(np.round(lon_values), dtype=np.int64))
gribapi.grib_set_array(grib, 'latitudes',
np.array(np.round(lat_values), dtype=np.int64))
def rotated_pole(cube, grib):
# Grib encoding of a rotated pole coordinate system.
cs = cube.coord(dimensions=[0]).coord_system
if cs.north_pole_grid_longitude != 0.0:
raise TranslationError(
'Grib save does not yet support Rotated-pole coordinates with '
'a rotated prime meridian.')
# XXX Pending #1125
# gribapi.grib_set_double(grib, "latitudeOfSouthernPoleInDegrees",
# float(cs.n_pole.latitude))
# gribapi.grib_set_double(grib, "longitudeOfSouthernPoleInDegrees",
# float(cs.n_pole.longitude))
# gribapi.grib_set_double(grib, "angleOfRotationInDegrees", 0)
# WORKAROUND
latitude = cs.grid_north_pole_latitude / _DEFAULT_DEGREES_UNITS
longitude = (((cs.grid_north_pole_longitude + 180) % 360) /
_DEFAULT_DEGREES_UNITS)
gribapi.grib_set(grib, "latitudeOfSouthernPole", - int(round(latitude)))
gribapi.grib_set(grib, "longitudeOfSouthernPole", int(round(longitude)))
gribapi.grib_set(grib, "angleOfRotation", 0)
def points_in_unit(coord, unit):
points = coord.units.convert(coord.points, unit)
points = np.around(points).astype(int)
return points
def step(points, atol):
diffs = points[1:] - points[:-1]
mean_diff = np.mean(diffs).astype(points.dtype)
if not np.allclose(diffs, mean_diff, atol=atol):
raise ValueError()
return int(mean_diff)
def grid_definition_template_0(cube, grib):
"""
Set keys within the provided grib message based on
Grid Definition Template 3.0.
Template 3.0 is used to represent "latitude/longitude (or equidistant
cylindrical, or Plate Carree)".
The coordinates are regularly spaced, true latitudes and longitudes.
"""
# Constant resolution, aka 'regular' true lat-lon grid.
gribapi.grib_set_long(grib, "gridDefinitionTemplateNumber", 0)
horizontal_grid_common(cube, grib)
latlon_points_regular(cube, grib)
def grid_definition_template_1(cube, grib):
"""
Set keys within the provided grib message based on
Grid Definition Template 3.1.
Template 3.1 is used to represent "rotated latitude/longitude (or
equidistant cylindrical, or Plate Carree)".
The coordinates are regularly spaced, rotated latitudes and longitudes.
"""
# Constant resolution, aka 'regular' rotated lat-lon grid.
gribapi.grib_set_long(grib, "gridDefinitionTemplateNumber", 1)
# Record details of the rotated coordinate system.
rotated_pole(cube, grib)
# Encode the lat/lon points.
horizontal_grid_common(cube, grib)
latlon_points_regular(cube, grib)
def grid_definition_template_4(cube, grib):
"""
Set keys within the provided grib message based on
Grid Definition Template 3.4.
Template 3.4 is used to represent "variable resolution latitude/longitude".
The coordinates are irregularly spaced latitudes and longitudes.
"""
# XXX: will we need to set `Ni` and `Nj`?
gribapi.grib_set(grib, "gridDefinitionTemplateNumber", 4)
horizontal_grid_common(cube, grib)
latlon_points_irregular(cube, grib)
def grid_definition_template_5(cube, grib):
"""
Set keys within the provided grib message based on
Grid Definition Template 3.5.
Template 3.5 is used to represent "variable resolution rotated
latitude/longitude".
The coordinates are irregularly spaced, rotated latitudes and longitudes.
"""
# NOTE: we must set Ni=Nj=1 before establishing the template.
# Without this, setting "gridDefinitionTemplateNumber" = 5 causes an
# immediate error.
# See: https://software.ecmwf.int/issues/browse/SUP-1095
# This is acceptable, as the subsequent call to 'horizontal_grid_common'
# will set these to the correct horizontal dimensions
# (by calling 'grid_dims').
gribapi.grib_set(grib, "Ni", 1)
gribapi.grib_set(grib, "Nj", 1)
gribapi.grib_set(grib, "gridDefinitionTemplateNumber", 5)
# Record details of the rotated coordinate system.
rotated_pole(cube, grib)
# Encode the lat/lon points.
horizontal_grid_common(cube, grib)
latlon_points_irregular(cube, grib)
def grid_definition_template_10(cube, grib):
"""
Set keys within the provided grib message based on
Grid Definition Template 3.10.
Template 3.10 is used to represent a Mercator grid.
"""
gribapi.grib_set(grib, "gridDefinitionTemplateNumber", 10)
# Retrieve some information from the cube.
y_coord = cube.coord(dimensions=[0])
x_coord = cube.coord(dimensions=[1])
cs = y_coord.coord_system
# Normalise the coordinate values to millimetres - the resolution
# used in the GRIB message.
y_mm = points_in_unit(y_coord, 'mm')
x_mm = points_in_unit(x_coord, 'mm')
# Encode the horizontal points.
# NB. Since we're already in millimetres, our tolerance for
# discrepancy in the differences is 1.
try:
x_step = step(x_mm, atol=1)
y_step = step(y_mm, atol=1)
except ValueError:
msg = 'Irregular coordinates not supported for Mercator.'
raise TranslationError(msg)
gribapi.grib_set(grib, 'Di', abs(x_step))
gribapi.grib_set(grib, 'Dj', abs(y_step))
horizontal_grid_common(cube, grib)
# Transform first and last points into geographic CS.
geog = cs.ellipsoid if cs.ellipsoid is not None else GeogCS(1)
first_x, first_y, = geog.as_cartopy_crs().transform_point(
x_coord.points[0],
y_coord.points[0],
cs.as_cartopy_crs())
last_x, last_y = geog.as_cartopy_crs().transform_point(
x_coord.points[-1],
y_coord.points[-1],
cs.as_cartopy_crs())
first_x = first_x % 360
last_x = last_x % 360
gribapi.grib_set(grib, "latitudeOfFirstGridPoint",
int(np.round(first_y / _DEFAULT_DEGREES_UNITS)))
gribapi.grib_set(grib, "longitudeOfFirstGridPoint",
int(np.round(first_x / _DEFAULT_DEGREES_UNITS)))
gribapi.grib_set(grib, "latitudeOfLastGridPoint",
int(np.round(last_y / _DEFAULT_DEGREES_UNITS)))
gribapi.grib_set(grib, "longitudeOfLastGridPoint",
int(np.round(last_x / _DEFAULT_DEGREES_UNITS)))
# Check and raise a more intelligible error, if the Iris version is too old
# to support the Mercator 'standard_parallel' property.
confirm_extended_mercator_supported()
# Encode the latitude at which the projection intersects the Earth.
gribapi.grib_set(grib, 'LaD',
cs.standard_parallel / _DEFAULT_DEGREES_UNITS)
# Encode resolution and component flags
gribapi.grib_set(grib, 'resolutionAndComponentFlags',
0x1 << _RESOLUTION_AND_COMPONENTS_GRID_WINDS_BIT)
def grid_definition_template_12(cube, grib):
"""
Set keys within the provided grib message based on
Grid Definition Template 3.12.
Template 3.12 is used to represent a Transverse Mercator grid.
"""
gribapi.grib_set(grib, "gridDefinitionTemplateNumber", 12)
# Retrieve some information from the cube.
y_coord = cube.coord(dimensions=[0])
x_coord = cube.coord(dimensions=[1])
cs = y_coord.coord_system
# Normalise the coordinate values to centimetres - the resolution
# used in the GRIB message.
y_cm = points_in_unit(y_coord, 'cm')
x_cm = points_in_unit(x_coord, 'cm')
# Set some keys specific to GDT12.
# Encode the horizontal points.
# NB. Since we're already in centimetres, our tolerance for
# discrepancy in the differences is 1.
try:
x_step = step(x_cm, atol=1)
y_step = step(y_cm, atol=1)
except ValueError:
msg = ('Irregular coordinates not supported for Transverse '
'Mercator.')
raise TranslationError(msg)
gribapi.grib_set(grib, 'Di', abs(x_step))
gribapi.grib_set(grib, 'Dj', abs(y_step))
horizontal_grid_common(cube, grib)
# GRIBAPI expects unsigned ints in X1, X2, Y1, Y2 but it should accept
# signed ints, so work around this.
# See https://software.ecmwf.int/issues/browse/SUP-1101
ensure_set_int32_value(grib, 'Y1', int(y_cm[0]))
ensure_set_int32_value(grib, 'Y2', int(y_cm[-1]))
ensure_set_int32_value(grib, 'X1', int(x_cm[0]))
ensure_set_int32_value(grib, 'X2', int(x_cm[-1]))
# Lat and lon of reference point are measured in millionths of a degree.
gribapi.grib_set(grib, "latitudeOfReferencePoint",
cs.latitude_of_projection_origin / _DEFAULT_DEGREES_UNITS)
gribapi.grib_set(grib, "longitudeOfReferencePoint",
cs.longitude_of_central_meridian / _DEFAULT_DEGREES_UNITS)
# Convert a value in metres into the closest integer number of
# centimetres.
def m_to_cm(value):
return int(round(value * 100))
# False easting and false northing are measured in units of (10^-2)m.
gribapi.grib_set(grib, 'XR', m_to_cm(cs.false_easting))
gribapi.grib_set(grib, 'YR', m_to_cm(cs.false_northing))
# GRIBAPI expects a signed int for scaleFactorAtReferencePoint
# but it should accept a float, so work around this.
# See https://software.ecmwf.int/issues/browse/SUP-1100
value = cs.scale_factor_at_central_meridian
key_type = gribapi.grib_get_native_type(grib,
"scaleFactorAtReferencePoint")
if key_type is not float:
value = fixup_float32_as_int32(value)
gribapi.grib_set(grib, "scaleFactorAtReferencePoint", value)
def grid_definition_template_30(cube, grib):
"""
Set keys within the provided grib message based on
Grid Definition Template 3.30.
Template 3.30 is used to represent a Lambert Conformal grid.
"""
gribapi.grib_set(grib, "gridDefinitionTemplateNumber", 30)
# Retrieve some information from the cube.
y_coord = cube.coord(dimensions=[0])
x_coord = cube.coord(dimensions=[1])
cs = y_coord.coord_system
# Normalise the coordinate values to millimetres - the resolution
# used in the GRIB message.
y_mm = points_in_unit(y_coord, 'mm')
x_mm = points_in_unit(x_coord, 'mm')
# Encode the horizontal points.
# NB. Since we're already in millimetres, our tolerance for
# discrepancy in the differences is 1.
try:
x_step = step(x_mm, atol=1)
y_step = step(y_mm, atol=1)
except ValueError:
msg = ('Irregular coordinates not supported for Lambert '
'Conformal.')
raise TranslationError(msg)
gribapi.grib_set(grib, 'Dx', abs(x_step))
gribapi.grib_set(grib, 'Dy', abs(y_step))
horizontal_grid_common(cube, grib, xy=True)
# Transform first point into geographic CS
geog = cs.ellipsoid if cs.ellipsoid is not None else GeogCS(1)
first_x, first_y = geog.as_cartopy_crs().transform_point(
x_coord.points[0],
y_coord.points[0],
cs.as_cartopy_crs())
first_x = first_x % 360
central_lon = cs.central_lon % 360
gribapi.grib_set(grib, "latitudeOfFirstGridPoint",
int(np.round(first_y / _DEFAULT_DEGREES_UNITS)))
gribapi.grib_set(grib, "longitudeOfFirstGridPoint",
int(np.round(first_x / _DEFAULT_DEGREES_UNITS)))
gribapi.grib_set(grib, "LaD", cs.central_lat / _DEFAULT_DEGREES_UNITS)
gribapi.grib_set(grib, "LoV", central_lon / _DEFAULT_DEGREES_UNITS)
latin1, latin2 = cs.secant_latitudes
gribapi.grib_set(grib, "Latin1", latin1 / _DEFAULT_DEGREES_UNITS)
gribapi.grib_set(grib, "Latin2", latin2 / _DEFAULT_DEGREES_UNITS)
gribapi.grib_set(grib, 'resolutionAndComponentFlags',
0x1 << _RESOLUTION_AND_COMPONENTS_GRID_WINDS_BIT)
# Which pole are the parallels closest to? That is the direction
# that the cone converges.
poliest_sec = latin1 if abs(latin1) > abs(latin2) else latin2
centre_flag = 0x0 if poliest_sec > 0 else 0x1
gribapi.grib_set(grib, 'projectionCentreFlag', centre_flag)
gribapi.grib_set(grib, "latitudeOfSouthernPole", 0)
gribapi.grib_set(grib, "longitudeOfSouthernPole", 0)
def grid_definition_section(cube, grib):
"""
Set keys within the grid definition section of the provided grib message,
based on the properties of the cube.
"""
x_coord = cube.coord(dimensions=[1])
y_coord = cube.coord(dimensions=[0])
cs = x_coord.coord_system # N.B. already checked same cs for x and y.
regular_x_and_y = is_regular(x_coord) and is_regular(y_coord)
if isinstance(cs, GeogCS):
if regular_x_and_y:
grid_definition_template_0(cube, grib)
else:
grid_definition_template_4(cube, grib)
elif isinstance(cs, RotatedGeogCS):
# Rotated coordinate system cases.
# Choose between GDT 3.1 and 3.5 according to coordinate regularity.
if regular_x_and_y:
grid_definition_template_1(cube, grib)
else:
grid_definition_template_5(cube, grib)
elif isinstance(cs, Mercator):
# Mercator coordinate system (template 3.10)
grid_definition_template_10(cube, grib)
elif isinstance(cs, TransverseMercator):
# Transverse Mercator coordinate system (template 3.12).
grid_definition_template_12(cube, grib)
elif isinstance(cs, LambertConformal):
# Lambert Conformal coordinate system (template 3.30).
grid_definition_template_30(cube, grib)
else:
name = cs.grid_mapping_name.replace('_', ' ').title()
emsg = 'Grib saving is not supported for coordinate system {!r}'
raise ValueError(emsg.format(name))
###############################################################################
#
# Product Definition Section 4
#
###############################################################################
def set_discipline_and_parameter(cube, grib):
# Default values for parameter identity keys = effectively "MISSING".
discipline, category, number = 255, 255, 255
identity_found = False
# First, see if we can find and interpret a 'GRIB_PARAM' attribute.
attr = cube.attributes.get('GRIB_PARAM', None)
if attr:
try:
# Convert to standard tuple-derived form.
gc = GRIBCode(attr)
if gc.edition == 2:
discipline = gc.discipline
category = gc.category
number = gc.number
identity_found = True
except:
pass
if not identity_found:
# Else, translate a cube phenomenon, if possible.
# NOTE: for now, can match by *either* standard_name or long_name.
# This allows workarounds for data with no identified standard_name.
grib2_info = gptx.cf_phenom_to_grib2_info(cube.standard_name,
cube.long_name)
if grib2_info is not None:
discipline = grib2_info.discipline
category = grib2_info.category
number = grib2_info.number
identity_found = True
if not identity_found:
warnings.warn('Unable to determine Grib2 parameter code for cube.\n'
'discipline, parameterCategory and parameterNumber '
'have been set to "missing".')
gribapi.grib_set(grib, "discipline", discipline)
gribapi.grib_set(grib, "parameterCategory", category)
gribapi.grib_set(grib, "parameterNumber", number)
def _non_missing_forecast_period(cube):
# Calculate "model start time" to use as the reference time.
fp_coord = cube.coord("forecast_period")
# Convert fp and t to hours so we can subtract to calculate R.
cf_fp_hrs = fp_coord.units.convert(fp_coord.points[0], 'hours')
t_coord = cube.coord("time").copy()
hours_since = cf_units.Unit("hours since epoch",
calendar=t_coord.units.calendar)
t_coord.convert_units(hours_since)
rt_num = t_coord.points[0] - cf_fp_hrs
rt = hours_since.num2date(rt_num)
rt_meaning = 1 # "start of forecast"
# Forecast period
if fp_coord.units == cf_units.Unit("hours"):
grib_time_code = 1
elif fp_coord.units == cf_units.Unit("minutes"):
grib_time_code = 0
elif fp_coord.units == cf_units.Unit("seconds"):
grib_time_code = 13
else:
raise TranslationError(
"Unexpected units for 'forecast_period' : %s" % fp_coord.units)
if not t_coord.has_bounds():
fp = fp_coord.points[0]
else:
if not fp_coord.has_bounds():
raise TranslationError(
"bounds on 'time' coordinate requires bounds on"
" 'forecast_period'.")
fp = fp_coord.bounds[0][0]
if fp - int(fp):
warnings.warn("forecast_period encoding problem: "
"scaling required.")
fp = int(fp)
return rt, rt_meaning, fp, grib_time_code
def _missing_forecast_period(cube):
"""
Returns a reference time and significance code together with a forecast
period and corresponding units type code.
"""
t_coord = cube.coord("time")
if cube.coords('forecast_reference_time'):
# Make copies and convert them to common "hours since" units.
hours_since = cf_units.Unit('hours since epoch',
calendar=t_coord.units.calendar)
frt_coord = cube.coord('forecast_reference_time').copy()
frt_coord.convert_units(hours_since)
t_coord = t_coord.copy()
t_coord.convert_units(hours_since)
# Extract values.
t = t_coord.bounds[0, 0] if t_coord.has_bounds() else t_coord.points[0]
frt = frt_coord.points[0]
# Calculate GRIB parameters.
rt = frt_coord.units.num2date(frt)
rt_meaning = 1 # Forecast reference time.
fp = t - frt
integer_fp = int(fp)
if integer_fp != fp:
msg = 'Truncating floating point forecast period {} to ' \
'integer value {}'
warnings.warn(msg.format(fp, integer_fp))
fp = integer_fp
fp_meaning = 1 # Hours
else:
# With no forecast period or forecast reference time set assume a
# reference time significance of "Observation time" and set the
# forecast period to 0h.
t = t_coord.bounds[0, 0] if t_coord.has_bounds() else t_coord.points[0]
rt = t_coord.units.num2date(t)
rt_meaning = 3 # Observation time
fp = 0
fp_meaning = 1 # Hours
return rt, rt_meaning, fp, fp_meaning
def set_forecast_time(cube, grib):
"""
Set the forecast time keys based on the forecast_period coordinate. In
the absence of a forecast_period and forecast_reference_time,
the forecast time is set to zero.
"""
try:
fp_coord = cube.coord("forecast_period")
except iris.exceptions.CoordinateNotFoundError:
fp_coord = None
if fp_coord is not None:
_, _, fp, grib_time_code = _non_missing_forecast_period(cube)
else:
_, _, fp, grib_time_code = _missing_forecast_period(cube)
gribapi.grib_set(grib, "indicatorOfUnitOfTimeRange", grib_time_code)
gribapi.grib_set(grib, "forecastTime", fp)
def set_fixed_surfaces(cube, grib, full3d_cube=None):
# Look for something we can export
v_coord = grib_v_code = output_unit = None
# Detect factories for hybrid vertical coordinates.
hybrid_factories = [
factory for factory in cube.aux_factories
if isinstance(factory, (HybridHeightFactory, HybridPressureFactory))]
if not hybrid_factories:
hybrid_factory = None
elif len(hybrid_factories) > 1:
msg = 'Data contains >1 vertical coordinate factory : {}'
raise ValueError(msg.format(hybrid_factories))
else:
factory = hybrid_factories[0]
# Fetch the matching 'complete' factory from the *full* 3d cube, so we
# have all the level information.
hybrid_factory = full3d_cube.aux_factory(factory.name())
# Handle various different styles of vertical coordinate.
# hybrid height / pressure
if hybrid_factory is not None:
# N.B. in this case, there are additional operations, besides just
# encoding v_coord : see below at end ..
v_coord = cube.coord('model_level_number')
output_unit = cf_units.Unit("1")
if isinstance(hybrid_factory, HybridHeightFactory):
grib_v_code = 118
elif isinstance(hybrid_factory, HybridPressureFactory):
grib_v_code = 119
else:
msg = 'Unrecognised factory type : {}'
raise ValueError(msg.format(hybrid_factory))
# pressure
elif cube.coords("air_pressure") or cube.coords("pressure"):
grib_v_code = 100
output_unit = cf_units.Unit("Pa")
v_coord = (cube.coords("air_pressure") or cube.coords("pressure"))[0]
# altitude
elif cube.coords("altitude"):
grib_v_code = 102
output_unit = cf_units.Unit("m")
v_coord = cube.coord("altitude")
# height
elif cube.coords("height"):
grib_v_code = 103
output_unit = cf_units.Unit("m")
v_coord = cube.coord("height")
# depth
elif cube.coords("depth"):
grib_v_code = 106
output_unit = cf_units.Unit('m')
v_coord = cube.coord("depth")
elif cube.coords("air_potential_temperature"):
grib_v_code = 107
output_unit = cf_units.Unit('K')
v_coord = cube.coord("air_potential_temperature")
# unknown / absent
else:
# check for *ANY* height coords at all...
v_coords = cube.coords(axis='z')
if v_coords:
# There are vertical coordinate(s), but we don't understand them...
v_coords_str = ' ,'.join(["'{}'".format(c.name())
for c in v_coords])
raise TranslationError(
'The vertical-axis coordinate(s) ({}) '
'are not recognised or handled.'.format(v_coords_str))
# What did we find?
if v_coord is None:
# No vertical coordinate: record as 'surface' level (levelType=1).
# NOTE: may *not* be truly correct, but seems to be common practice.
# Still under investigation :
# See https://github.com/SciTools/iris/issues/519
gribapi.grib_set(grib, "typeOfFirstFixedSurface", 1)
gribapi.grib_set(grib, "scaleFactorOfFirstFixedSurface", 0)
gribapi.grib_set(grib, "scaledValueOfFirstFixedSurface", 0)
# Set secondary surface = 'missing'.
gribapi.grib_set(grib, "typeOfSecondFixedSurface", -1)
gribapi.grib_set(grib, "scaleFactorOfSecondFixedSurface", 255)
gribapi.grib_set(grib, "scaledValueOfSecondFixedSurface", -1)
elif not v_coord.has_bounds():
# No second surface
output_v = v_coord.units.convert(v_coord.points[0], output_unit)
if output_v - abs(output_v):
warnings.warn("Vertical level encoding problem: scaling required.")
output_v = int(output_v)
gribapi.grib_set(grib, "typeOfFirstFixedSurface", grib_v_code)
gribapi.grib_set(grib, "scaleFactorOfFirstFixedSurface", 0)
gribapi.grib_set(grib, "scaledValueOfFirstFixedSurface", output_v)
gribapi.grib_set(grib, "typeOfSecondFixedSurface", -1)
gribapi.grib_set(grib, "scaleFactorOfSecondFixedSurface", 255)
gribapi.grib_set(grib, "scaledValueOfSecondFixedSurface", -1)
else:
# bounded : set lower+upper surfaces
output_v = v_coord.units.convert(v_coord.bounds[0], output_unit)
if output_v[0] - abs(output_v[0]) or output_v[1] - abs(output_v[1]):
warnings.warn("Vertical level encoding problem: scaling required.")
gribapi.grib_set(grib, "typeOfFirstFixedSurface", grib_v_code)
gribapi.grib_set(grib, "typeOfSecondFixedSurface", grib_v_code)
gribapi.grib_set(grib, "scaleFactorOfFirstFixedSurface", 0)
gribapi.grib_set(grib, "scaleFactorOfSecondFixedSurface", 0)
gribapi.grib_set(grib, "scaledValueOfFirstFixedSurface",
int(output_v[0]))
gribapi.grib_set(grib, "scaledValueOfSecondFixedSurface",
int(output_v[1]))
if hybrid_factory is not None:
# Need to record ALL the level coefficents in a 'PV' vector.
level_delta_coord = hybrid_factory.delta
sigma_coord = hybrid_factory.sigma
model_levels = full3d_cube.coord('model_level_number').points
# Just check these make some kind of sense (!)
if model_levels.dtype.kind not in 'iu':
msg = 'model_level_number is not an integer: dtype={}.'
raise ValueError(msg.format(model_levels.dtype))
if np.min(model_levels) < 1:
msg = 'model_level_number must be > 0: mininum value = {}.'
raise ValueError(msg.format(np.min(model_levels)))
# Need to save enough levels for indexes up to [max(model_levels)]
n_levels = np.max(model_levels)
max_valid_nlevels = 9999
if n_levels > max_valid_nlevels:
msg = ('model_level_number values are > {} : '
'maximum value = {}.')
raise ValueError(msg.format(max_valid_nlevels, n_levels))
# In sample data we have seen, there seems to be an extra missing data
# value *before* each set of n-levels coefficients.
# Note: values are indexed according to model_level_number,
# I.E. sigma, delta = PV[i], PV[NV/2+i] : where i=1..n_levels
n_coeffs = n_levels + 1
coeffs_array = np.zeros(n_coeffs * 2, dtype=np.float32)
for n_lev, height, sigma in zip(model_levels,
level_delta_coord.points,
sigma_coord.points):
# Record all the level coefficients coming from the 'full' cube.
# Note: if some model levels are missing, we must still have the
# coeffs at the correct index according to the model_level_number
# value, i.e. at [level] and [NV // 2 + level].
# Thus, we can *not* paste the values in a block: each one needs to
# go in the index corresponding to its 'model_level_number' value.
coeffs_array[n_lev] = height
coeffs_array[n_coeffs + n_lev] = sigma
pv_values = [float(el) for el in coeffs_array]
# eccodes does not support writing numpy.int64, cast to python int
gribapi.grib_set(grib, "NV", int(n_coeffs * 2))
gribapi.grib_set_array(grib, "pv", pv_values)
def set_time_range(time_coord, grib):
"""