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GIve easy, high-level access to ome-zarr fileset

ez_zarr 최신버젼 다운로드

최종 버전 다운로드 (.zip)

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<br>

# ez_zarr

<br>

## 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](https://ngff.openmicroscopy.org/latest/)
specifications in OME-Zarr with additional metadata fields, for
example the ones generated by the [Fractal](https://fractal-analytics-platform.github.io/) 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.

In addition to the python package, we also provide an R package
that automatically generates and wraps a python environment with
`ez_zarr` and all dependencies, available at https://github.com/fmicompbio/ezzarr.

## Example
You can use `ez_zarr` from the command line to get information about an OME-Zarr fileset:
```
ez_zarr tests/example_data/plate_ones.zarr
```

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

## legacy objects from `hcs_wrappers`
from ez_zarr import hcs_wrappers

plate_3d = hcs_wrappers.FractalZarr('tests/example_data/plate_ones.zarr')
plate_3d
# FractalZarr plate_ones.zarr
#   path: tests/example_data/plate_ones.zarr
#   n_wells: 1
#   n_channels: 2 (some-label-1, some-label-2)
#   n_pyramid_levels: 3
#   pyramid_zyx_scalefactor: {'0': array([1. 2. 2.])}
#   full_resolution_zyx_spacing: [1.0, 0.1625, 0.1625]
#   segmentations: 
#   tables (measurements): FOV_ROI_table

```

A more extensive example is available from [here](https://fmicompbio.github.io/ez_zarr/getting_started_Image/), also available as an [ipynb notebook](https://fmicompbio.github.io/ez_zarr/getting_started_Image.ipynb).

## Install
`ez_zarr` is available for all major platforms (macOS, Linux and Windows) and modern versions of python. It can be installed using `pip` or `conda`:

### Using `pip`
[![PyPI - Version](https://img.shields.io/pypi/v/ez-zarr.svg?logo=pypi&label=PyPI&logoColor=gold)](https://pypi.org/project/ez-zarr/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/ez-zarr.svg?logo=python&label=Python&logoColor=gold)](https://pypi.org/project/ez-zarr/)
![PyPI - Downloads](https://img.shields.io/pypi/dm/ez-zarr)

The release version of `ez_zarr` can be installed using pip:
```
pip install ez-zarr
```

To install also the dependencies required for running unit tests or to download the example data and run the examples given in the documentation, install `ez_zarr` with the `dev` and `doc` extras, respectively:
```
pip install "ez-zarr[dev,doc]"
```

The current (development) `ez_zarr` can be installed from github.com using:
```
pip install git+ssh://git@github.com/fmicompbio/ez_zarr.git
```

### Using `conda`
[![Conda Version](https://img.shields.io/conda/vn/conda-forge/ez-zarr.svg)](https://anaconda.org/conda-forge/ez-zarr)
[![Conda Platforms](https://img.shields.io/conda/pn/conda-forge/ez-zarr.svg)](https://anaconda.org/conda-forge/ez-zarr)
[![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/ez-zarr.svg)](https://anaconda.org/conda-forge/ez-zarr)

Alternatively, you can install `ez-zarr` from the `conda-forge` channel using:
```
conda install -c conda-forge --override-channels ez-zarr
```

## Software status
[![unit-tests](https://github.com/fmicompbio/ez_zarr/actions/workflows/test_and_deploy.yaml/badge.svg)](https://github.com/fmicompbio/ez_zarr/actions/workflows/test_and_deploy.yaml)
[![codecov](https://codecov.io/gh/fmicompbio/ez_zarr/graph/badge.svg)](https://codecov.io/gh/fmicompbio/ez_zarr)

## Supported versions of `zarr`
`ez-zarr` currently supports OME-Zarr v0.4 and v0.5 (corresponding to version 2 and 3 of the `zarr` format, and thus version 2 and 3 of the `zarr` python package). OME-Zarr v0.5 support was introduced in `ez-zarr` v0.4.0.

## 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](https://github.com/fmicompbio/ez_zarr/blob/main/LICENSE)).

`ez_zarr` is being developed at the Friedrich Miescher Institute for
Biomedical Research by [@silvbarb](https://github.com/silvbarb), [@csoneson](https://github.com/csoneson) and [@mbstadler](https://github.com/mbstadler).

## Citing ez-zarr
[![DOI](https://joss.theoj.org/papers/10.21105/joss.07882/status.svg)](https://doi.org/10.21105/joss.07882)

If you are using ez-zarr in published research, please cite the paper:

Barbiero et al., (2025). ez-zarr: A Python package for easy access and visualisation of OME-Zarr filesets. Journal of Open Source Software, 10(109), 7882, https://doi.org/10.21105/joss.07882

## Need help? 
If you run into problems when using `ez_zarr`, please first check whether the 
answer is available in the [help pages for the individual functions underneath 'Documentation'](https://fmicompbio.github.io/ez_zarr/) or in 
the ['Getting started' vignette](https://fmicompbio.github.io/ez_zarr/getting_started_Image/).
If not, please [open an issue](https://github.com/fmicompbio/ez_zarr/issues/new) 
and explain your problem. Try to provide a reproducible example, and always 
include the code you used, that will make it much easier for us to help.

## Contributions
If you would like to contribute to `ez_zarr`, you can do so by sending a pull 
request to this repository. If the contribution involves changes in the 
functionality provided by `ez_zarr`, we encourage you to first open an issue 
to discuss the intended contribution.

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