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184 | @validate_call
def projection(
*,
# Fractal parameters
zarr_url: str,
init_args: InitArgsMIP,
) -> dict[str, Any]:
"""
Perform intensity projection along Z axis with a chosen method.
Note: this task stores the output in a new zarr file.
Args:
zarr_url: Path or url to the individual OME-Zarr image to be processed.
(standard argument for Fractal tasks, managed by Fractal server).
init_args: Intialization arguments provided by
`create_cellvoyager_ome_zarr_init`.
"""
method = DaskProjectionMethod(init_args.method)
logger.info(f"{init_args.origin_url=}")
logger.info(f"{zarr_url=}")
logger.info(f"{method=}")
# Read image metadata
ngff_image = load_NgffImageMeta(init_args.origin_url)
# Currently not using the validation models due to wavelength_id issue
# See #681 for discussion
# new_attrs = ngff_image.model_dump(exclude_none=True)
# Current way to get the necessary metadata for MIP
group = zarr.open_group(init_args.origin_url, mode="r")
new_attrs = group.attrs.asdict()
# Create the zarr image with correct
new_image_group = zarr.group(zarr_url)
new_image_group.attrs.put(new_attrs)
# Load 0-th level
data_czyx = da.from_zarr(init_args.origin_url + "/0")
num_channels = data_czyx.shape[0]
chunksize_y = data_czyx.chunksize[-2]
chunksize_x = data_czyx.chunksize[-1]
logger.info(f"{num_channels=}")
logger.info(f"{chunksize_y=}")
logger.info(f"{chunksize_x=}")
# Loop over channels
accumulate_chl = []
for ind_ch in range(num_channels):
# Perform MIP for each channel of level 0
project_yx = da.stack(
[method.apply(data_czyx[ind_ch], axis=0)], axis=0
)
accumulate_chl.append(project_yx)
accumulated_array = da.stack(accumulate_chl, axis=0)
# Write to disk (triggering execution)
try:
accumulated_array.to_zarr(
f"{zarr_url}/0",
overwrite=init_args.overwrite,
dimension_separator="/",
write_empty_chunks=False,
)
except ContainsArrayError as e:
error_msg = (
f"Cannot write array to zarr group at '{zarr_url}/0', "
f"with {init_args.overwrite=} (original error: {str(e)}).\n"
"Hint: try setting overwrite=True."
)
logger.error(error_msg)
raise OverwriteNotAllowedError(error_msg)
# Starting from on-disk highest-resolution data, build and write to disk a
# pyramid of coarser levels
build_pyramid(
zarrurl=zarr_url,
overwrite=init_args.overwrite,
num_levels=ngff_image.num_levels,
coarsening_xy=ngff_image.coarsening_xy,
chunksize=(1, 1, chunksize_y, chunksize_x),
)
# Copy over any tables from the original zarr
# Generate the list of tables:
tables = get_tables_list_v1(init_args.origin_url)
roi_tables = get_tables_list_v1(init_args.origin_url, table_type="ROIs")
non_roi_tables = [table for table in tables if table not in roi_tables]
for table in roi_tables:
logger.info(
f"Reading {table} from "
f"{init_args.origin_url=}, convert it to 2D, and "
"write it back to the new zarr file."
)
new_ROI_table = ad.read_zarr(f"{init_args.origin_url}/tables/{table}")
old_ROI_table_attrs = zarr.open_group(
f"{init_args.origin_url}/tables/{table}"
).attrs.asdict()
# Convert 3D ROIs to 2D
pxl_sizes_zyx = ngff_image.get_pixel_sizes_zyx(level=0)
new_ROI_table = convert_ROIs_from_3D_to_2D(
new_ROI_table, pixel_size_z=pxl_sizes_zyx[0]
)
# Write new table
write_table(
new_image_group,
table,
new_ROI_table,
table_attrs=old_ROI_table_attrs,
overwrite=init_args.overwrite,
)
for table in non_roi_tables:
logger.info(
f"Reading {table} from "
f"{init_args.origin_url=}, and "
"write it back to the new zarr file."
)
new_non_ROI_table = ad.read_zarr(
f"{init_args.origin_url}/tables/{table}"
)
old_non_ROI_table_attrs = zarr.open_group(
f"{init_args.origin_url}/tables/{table}"
).attrs.asdict()
# Write new table
write_table(
new_image_group,
table,
new_non_ROI_table,
table_attrs=old_non_ROI_table_attrs,
overwrite=init_args.overwrite,
)
# Generate image_list_updates
image_list_update_dict = dict(
image_list_updates=[
dict(
zarr_url=zarr_url,
origin=init_args.origin_url,
types=dict(is_3D=False),
)
]
)
return image_list_update_dict
|