def get_crs_coordinates(dataset: gdal.Dataset, x_idx: float, y_idx: float) -> Coordinate2D:
geotransform = dataset.GetGeoTransform()
origin_x = geotransform[0] # origin_x/y is the CRS coordinate at the top left corner of the (0,0) pixel
origin_y = geotransform[3]
dx = geotransform[1]
dy = geotransform[5]
x = x_idx * dx + origin_x
y = y_idx * dy + origin_y
return Coordinate2D(x=x, y=y)
def create_index_dict(dataset: gdal.Dataset, tilesize_x: int, tilesize_y: int, ysize_pad: int, tile_bdr: int,
filename_digits: int, is_categorical: bool,
units: Optional[str]=None, description: Optional[str]=None,
strict_datum: bool=True) -> Tuple[Dict[str, Any], DatumMismatch, Optional[float], int, Optional[float]]:
'''
Returns a dictionary that can be used for writing a WPS Binary format index file.
If the given dataset has a CRS or data type unsupported by WRF then an error is raised.
See also :func:`write_index_file`.
'''
band = dataset.GetRasterBand(1) # type: gdal.Band
dtype = band.DataType
if dtype in DTYPE_INT:
no_data_value = band.GetNoDataValue() # type: Optional[float]
scale_factor = band.GetScale()
inv_scale_factor = None
if band.GetOffset() != 0:
raise UnsupportedError('Integer data with offset not supported')
elif dtype in DTYPE_FLOAT:
if is_categorical:
raise UserError('Categorical data must have integer-type data but is float')
assert band.GetOffset() == 0
assert band.GetScale() == 1
# WPS binary doesn't support floating point data.
# Floating point data must be converted to integers by scaling and rounding.
inv_scale_factor, min_max = compute_inv_scale_factor(read_blocks(band))
scale_factor = 1/inv_scale_factor
min_, max_ = min_max
min_scaled = round(min_ * inv_scale_factor)
max_scaled = round(max_ * inv_scale_factor)
dtype = get_optimal_dtype(min_scaled, max_scaled)
if band.GetNoDataValue() is None:
no_data_value = None
else:
# TODO may fail if value range equals dtype range
# adjusting the scaling factor slightly to make room for a no-data value may help
no_data_value = get_no_data_value(dtype, min_scaled, max_scaled)
#print('Scale factor: {}'.format(scale_factor))
#print('Min/max: {}'.format(min_max))
#print('Min/max scaled: {}'.format((min_scaled, max_scaled)))
#print('No data: {}'.format(no_data_value))
else:
assert False, "Unsupported data type: {}".format(gdal.GetDataTypeName(dtype))
signed = gdal_dtype_is_signed(dtype)
wordsize = gdal.GetDataTypeSize(dtype) // 8
wkt = dataset.GetProjection()
srs = osr.SpatialReference(wkt)
truelat1 = truelat2 = stand_lon = None
geotransform = dataset.GetGeoTransform()
dx = geotransform[1]
dy = geotransform[5]
assert dx > 0
# dy can be negative, see below
projection = None
datum_mismatch = None
if srs.IsGeographic():
if srs.EPSGTreatsAsLatLong():
raise UnsupportedError("Unsupported axis order: Lat/Lon, must be Lon/Lat")
if not CRS.is_wrf_sphere_datum(srs):
datum_mismatch = DatumMismatch(
expected='WRF Sphere (6370km)',
actual='a={}m b={}m'.format(srs.GetSemiMajor(), srs.GetSemiMinor()))
if datum_mismatch and strict_datum:
raise UnsupportedError("Unsupported datum, must be based on a sphere with " +
"radius {}m, but is an ellipsoid with a={}m b={}m".format(
WRF_EARTH_RADIUS, srs.GetSemiMajor(), srs.GetSemiMinor()))
projection = 'regular_ll'
elif srs.IsProjected():
proj = srs.GetAttrValue('projection')
datum = srs.GetAttrValue('datum')
if proj in ['Albers_Conic_Equal_Area', 'Lambert_Conformal_Conic_2SP', 'Mercator_2SP']:
truelat1 = srs.GetNormProjParm('standard_parallel_1')
if proj == 'Polar_Stereographic':
truelat1 = srs.GetNormProjParm('latitude_of_origin')
if proj in ['Albers_Conic_Equal_Area', 'Lambert_Conformal_Conic_2SP']:
truelat2 = srs.GetNormProjParm('standard_parallel_2')
if proj == 'Albers_Conic_Equal_Area':
stand_lon = srs.GetNormProjParm('longitude_of_center')
if proj in ['Lambert_Conformal_Conic_2SP', 'Mercator_2SP', 'Polar_Stereographic']:
stand_lon = srs.GetNormProjParm('central_meridian')
if proj == "Albers_Conic_Equal_Area":
if datum != "North_American_Datum_1983":
datum_mismatch = DatumMismatch(expected='NAD83', actual=datum)
projection = 'albers_nad83'
elif proj == "Lambert_Conformal_Conic_2SP":
if not CRS.is_wrf_sphere_datum(srs):
datum_mismatch = DatumMismatch(expected='WRF Sphere (6370km)', actual=datum)
projection = 'lambert'
elif proj == "Mercator_2SP":
if not CRS.is_wrf_sphere_datum(srs):
datum_mismatch = DatumMismatch(expected='WRF Sphere (6370km)', actual=datum)
projection = 'mercator'
# For polar stereographic we don't allow datum mismatch in non-strict mode
# as it would be ambiguous which WPS projection ID to choose.
elif proj == "Polar_Stereographic" and datum == 'WGS_1984':
projection = 'polar_wgs84'
elif proj == "Polar_Stereographic" and CRS.is_wrf_sphere_datum(srs):
projection = 'polar'
if projection is None or (datum_mismatch and strict_datum):
raise UnsupportedError("Unsupported projection/datum: {}; {}".format(proj, datum))
else:
raise UnsupportedError("Unsupported SRS type, must be geographic or projected")
if units is None and is_categorical:
units = 'category'
# gdal always uses system byte order when creating ENVI files
is_little_endian = sys.byteorder == 'little'
# WPS does not support the concept of negative dy and requires that
# the highest y coordinate corresponds to the highest y index.
# If row_order=top_bottom (which we use), then the highest y index corresponds to
# the row that is stored first in the file.
# If row_order=bottom_top, then the highest y index corresponds to
# the row that is stored last in the file.
# Index coordinates in WPS do not start from 0 but from 1 where (1,1)
# corresponds to the center of the cell. GDAL (0,0) corresponds to the corner of the cell.
# See also http://www2.mmm.ucar.edu/wrf/users/FAQ_files/FAQ_wps_intermediate_format.html.
half_cell = 0.5
# WPS index coordinates
known_x = known_y = 1.0
# GDAL index coordinates
x_idx = known_x - half_cell
if dy < 0:
y_idx = ysize_pad - known_y + half_cell
else:
y_idx = known_y - half_cell
known_lonlat = CRS(srs=srs).to_lonlat(get_crs_coordinates(dataset, x_idx, y_idx))
metadata = {
'type': 'categorical' if is_categorical else 'continuous',
'endian': 'little' if is_little_endian else 'big',
'signed': 'yes' if signed else 'no',
'wordsize': wordsize,
'row_order': 'top_bottom',
'projection': projection,
'dx': dx,
'dy': abs(dy),
'known_x': known_x,
'known_y': known_y,
'known_lat': known_lonlat.lat,
'known_lon': known_lonlat.lon,
'tile_x': tilesize_x,
'tile_y': tilesize_y,
'tile_z': 1,
'tile_bdr': tile_bdr
}
if filename_digits > 5:
metadata['filename_digits'] = filename_digits
if scale_factor != 1:
metadata['scale_factor'] = scale_factor
if no_data_value is not None:
metadata['missing_value'] = float(no_data_value)
if is_categorical:
# Note that ComputeRasterMinMax ignores pixels with no-data value.
band_min, band_max = band.ComputeRasterMinMax()
assert band_min == int(band_min)
assert band_max == int(band_max)
metadata['category_min'] = int(band_min)
metadata['category_max'] = int(band_max)
if truelat1 is not None:
metadata['truelat1'] = truelat1
if truelat2 is not None:
metadata['truelat2'] = truelat2
if stand_lon is not None:
metadata['stdlon'] = stand_lon
if units is not None:
metadata['units'] = units
if description is not None:
metadata['description'] = description
return metadata, datum_mismatch, inv_scale_factor, dtype, no_data_value