ome-zarr-py

Save an array as OME-Zarr using the ome-zarr-py library.

Create a directory named saved_omezarrs in your home directory, and browse into it.

cd /path/to/data/saved_omezarrs

Access Python:

python

Do the relevant imports

import zarr, os
import numcodecs
from ome_zarr import writer, scale
from ome_zarr.io import parse_url
from skimage.data import astronaut

Create fake data

data = astronaut().swapaxes(0, 2).swapaxes(1, 2)

Specify a scaler

In order to create an image pyramid, one has to instantiate a scaler. This scaler requires the parameters: scale factor, number of resolution layers and downscaling method.

scaler = scale.Scaler(downscale=2, # Downscaling factor for x and y axes
                      max_layer=4, # Number of downscalings = 5
                      method = 'nearest' # downscaling method
                      )

Specify the axis identities and the corresponding units

This dictionary will impose the axis order and the units corresponding to each axis.

axes = [
    dict(name = 'c', type = 'channel'),
    dict(name = 'y', type = 'space', unit = 'micrometer'),
    dict(name = 'x', type = 'space', unit = 'micrometer'),
]

Specify the voxel sizes for each resolution level

This is a list of list, where the length of the outer list must match the number of resolution levels. The inner lists contain dictionaries for different types of coordinate transforms. Each inner list must contain a scaling transform, a dictionary that takes scale as key and an iterable of voxel sizes as value.

coordinate_transforms = [
    [{'scale': [1, 0.2, 0.2], 'type': 'scale'}],
    [{'scale': [1, 0.4, 0.4], 'type': 'scale'}],
    [{'scale': [1, 0.8, 0.8], 'type': 'scale'}],
    [{'scale': [1, 1.6, 1.6], 'type': 'scale'}],
    [{'scale': [1, 3.2, 3.2], 'type': 'scale'}]
]

Create a zarr store to write

For the sake of simplicity, here we demonstrate how to write to a local store. It is also possible to write to a remote location by simply specifying a remote url as input to the parse_url function.

# Specify the path where you want to write
output_path = "./saved_omezarrs/astronaut.zarr"
# Parse the url as a zarr store. Note that "mode = 'w'" enables writing to this store.
store = parse_url(output_path, mode = 'w').store 
root = zarr.open_group(store)

Specify zarr storage options

The most important zarr storage options are the chunks and the compression parameters. The chunks parameter is simply a tuple of integers corresponding to each axis. The compression parameter requires compressor object from the Numcodecs package, which is a dependency of zarr-python.

storage_options=dict(
                    chunks=(1, 64, 64),  # Output chunk shape
                    compression = numcodecs.Zlib(), # Compressor to be used, defaults to numcodecs.Blosc()
                    overwrite = True # Overwrite the output path
                )

Save the array

Here we use the ome_zarr.writer.write_image function to save the array. This function takes the parameters specified above as input, downscales the array accordingly and writes the resulting pyramid to the specified zarr group.

writer.write_image(image = data, # In this case, a numpy array
                   group = root,
                   axes = axes, # Dimensionality order
                   scaler=scaler,
                   coordinate_transformations = coordinate_transforms,
                   storage_options = storage_options
                   )