def _pq_native_transform(xx: xr.Dataset) -> xr.Dataset:
"""
config:
bad_pixel_classes
cloud_classes
"""
valid = enum_to_bool(xx.SCL, bad_pixel_classes, invert=True, value_true=255, dtype='uint8')
clear = enum_to_bool(xx.SCL, bad_pixel_classes+cloud_classes, invert=True, value_true=255, dtype='uint8')
return xr.Dataset(dict(valid=valid, clear=clear))
def _native_op_data_band(self, xx):
from odc.algo import enum_to_bool, keep_good_only
if not self._mask_band in xx.data_vars:
return xx
# Erase Data Pixels for which mask == nodata
#
# xx[mask == nodata] = nodata
mask = xx[self._mask_band]
xx = xx.drop_vars([self._mask_band])
keeps = enum_to_bool(mask, self._nodata_classes, invert=True)
xx = keep_good_only(xx, keeps)
return xx
def _pq_native_transform(xx: xr.Dataset) -> xr.Dataset:
"""
config:
cloud_classes
.SCL -> .valid (anything but nodata)
.erased (cloud pixels only)
"""
scl = xx.SCL
valid = scl != scl.nodata
erased = enum_to_bool(scl, cloud_classes)
return xr.Dataset(
dict(valid=valid, erased=erased),
attrs={"native": True}, # <- native flag needed for fuser
)
def native_op(xx: xr.Dataset) -> xr.Dataset:
_xx = enum_to_bool(xx[band], categories)
return xr.Dataset(
{band: _xx},
attrs={"native": True}, # <- native flag needed for fuser
)