Welcome to ez_zarr
Goals
The aim of ez_zarr
is to provide easy, high-level access
to OME-Zarr filesets (high content screening microscopy data, stored
according to the NGFF
specifications in OME-Zarr with additional metadata fields, for
example the ones generated by the Fractal platform).
The goal is that users can write simple scripts working with plates, wells and fields of view, without having to understand how these are represented within an OME-Zarr fileset.
Example
You can use ez_zarr
from the command line to get information about an OME-Zarr fileset:
or from within python to get access to all its functionality:
## import module
from ez_zarr import ome_zarr
## open an Image
img = ome_zarr.Image('tests/example_data/plate_ones_mip.zarr/B/03/0')
img
# Image 0
# path: tests/example_data/plate_ones_mip.zarr/B/03/0
# n_channels: 2 (some-label-1, some-label-2)
# n_pyramid_levels: 3
# pyramid_zyx_scalefactor: [1. 2. 2.]
# full_resolution_zyx_spacing (micrometer): [1.0, 0.1625, 0.1625]
# segmentations: organoids
# tables (measurements): FOV_ROI_table
A more extensive example is available from here, also available as an ipynb notebook.
Install
ez_zarr
is hosted on GitHub at github.com/fmicompbio/ez_zarr and the documentation can be found at fmicompbio.github.io/ez_zarr.
The release version of ez_zarr
can be installed using pip:
The current (development) version of ez_zarr
can be installed from github.com using:
Alternatively, you can install ez_zarr
using conda from the conda-forge
channel by:
Software status
Contributors and License
ez_zarr
is released under the MIT License, and the copyright
is with the Friedrich Miescher Insitute for Biomedical Research
(see LICENSE).
ez_zarr
is being developed at the Friedrich Miescher Institute for
Biomedical Research by @silvbarb, @csoneson and @mbstadler.