def _write_thumbnail(task: AlchemistTask, dataset_assembler: DatasetAssembler):
if task.settings.output.preview_image is not None:
dataset_assembler.write_thumbnail(*task.settings.output.preview_image)
elif task.settings.output.preview_image_singleband is not None:
dataset_assembler.write_thumbnail_singleband(
**task.settings.output.preview_image_singleband
)
def _unpack_products(p: DatasetAssembler, product_list: Iterable[str],
h5group: h5py.Group) -> None:
"""
Unpack and package the NBAR and NBART products.
"""
# listing of all datasets of IMAGE CLASS type
img_paths = _find_h5_paths(h5group, "IMAGE")
for product in product_list:
with do(f"Starting {product}", heading=True):
for pathname in [
p for p in img_paths if "/{}/".format(product.upper()) in p
]:
with do(f"Path {pathname!r}"):
dataset = h5group[pathname]
band_name = utils.normalise_band_name(
dataset.attrs["alias"])
write_measurement_h5(
p,
f"{product}:{band_name}",
dataset,
overview_resampling=Resampling.average,
file_id=_file_id(dataset),
)
if (p.platform, product) in _THUMBNAILS:
red, green, blue = _THUMBNAILS[(p.platform, product)]
with do(f"Thumbnailing {product}"):
p.write_thumbnail(red,
green,
blue,
kind=product,
static_stretch=(1, 3000))
def _unpack_products(p: DatasetAssembler, product_list: Iterable[str],
h5group: h5py.Group) -> None:
"""
Unpack and package the NBAR and NBART products.
"""
# listing of all datasets of IMAGE CLASS type
img_paths = _find_h5_paths(h5group, "IMAGE")
for product in product_list:
with sub_product(product, p):
for pathname in [
p for p in img_paths if f"/{product.upper()}/" in p
]:
with do(f"Path {pathname!r}"):
dataset = h5group[pathname]
band_name = utils.normalise_band_name(
dataset.attrs["alias"])
write_measurement_h5(
p,
f"{product}:{band_name}",
dataset,
overview_resampling=Resampling.average,
file_id=_file_id(dataset),
)
if product in _THUMBNAILS:
red, green, blue = _THUMBNAILS[product]
with do(f"Thumbnailing {product}"):
p.write_thumbnail(
red,
green,
blue,
static_stretch=(1, 3000),
# Because of our strange sub-products and filename standards, we want the
# 'kind' to be included in the recorded thumbnail accessory metadata,
# but not in the filename.
# So we manually calculate a filename without the 'kind' field included.
kind=product,
path=p.names.thumbnail_filename(),
)