Metadata-Version: 2.1
Name: ez_zarr
Version: 0.2.2
Summary: Give easy, high-level access to ome-zarr filesets.
Author: Silvia Barbiero, Charlotte Soneson, Michael Stadler
Maintainer-email: Michael Stadler <michael.stadler@fmi.ch>
License: MIT License
        
        Copyright (c) 2023 Friedrich Miescher Institute for Biomedical Research
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/fmicompbio/ez_zarr
Project-URL: Issues, https://github.com/fmicompbio/ez_zarr/issues
Project-URL: Documentation, https://fmicompbio.github.io/ez_zarr/
Project-URL: Sources, https://github.com/fmicompbio/ez_zarr
Keywords: ome_zarr,image analysis,Fractal
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: anndata
Requires-Dist: dask
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: zarr
Requires-Dist: matplotlib
Requires-Dist: scikit-image
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"

# 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](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/fractal-tasks-core/) 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:
```
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 hcs_wrappers

# create `plate_3d` object representing an OME-Zarr fileset
plate_3d = hcs_wrappers.FractalZarr('tests/example_data/plate_ones.zarr')

# print fileset summary
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

from ez_zarr import ome_zarr
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](https://fmicompbio.github.io/ez_zarr/getting_started_hcs_wrappers/), also available as an [ipynb notebook](https://fmicompbio.github.io/ez_zarr/getting_started_hcs_wrappers.ipynb).

## Install
[![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 install ez-zarr
```

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

## 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?token=GEBLX8ENJ1)](https://codecov.io/gh/fmicompbio/ez_zarr)

## 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).
