| Name | ez-zarr JSON |
| Version |
0.3.5
JSON |
| download |
| home_page | None |
| Summary | Give easy, high-level access to ome-zarr filesets. |
| upload_time | 2024-12-19 16:36:11 |
| maintainer | None |
| docs_url | None |
| author | Silvia Barbiero, Charlotte Soneson, Michael Stadler |
| requires_python | >=3.9 |
| 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. |
| keywords |
ome_zarr
image analysis
fractal
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<img src="docs/ez_zarr.png" align="right" alt="ez-zarr" width="150"/>
<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
### Using `pip`
[](https://pypi.org/project/ez-zarr/)
[](https://pypi.org/project/ez-zarr/)
The release version of `ez_zarr` can be installed using pip:
```
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
```
### Using `conda`
[](https://anaconda.org/conda-forge/ez-zarr)
[](https://anaconda.org/conda-forge/ez-zarr)
[](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
[](https://github.com/fmicompbio/ez_zarr/actions/workflows/test_and_deploy.yaml)
[](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).
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"description": "<img src=\"docs/ez_zarr.png\" align=\"right\" alt=\"ez-zarr\" width=\"150\"/>\n\n<br>\n\n# ez_zarr\n\n<br>\n\n## Goals\nThe aim of `ez_zarr` is to provide easy, high-level access\nto OME-Zarr filesets (high content screening microscopy data, stored\naccording to the [NGFF](https://ngff.openmicroscopy.org/latest/)\nspecifications in OME-Zarr with additional metadata fields, for\nexample the ones generated by the [Fractal](https://fractal-analytics-platform.github.io/) platform).\n\nThe goal is that users can write simple scripts working with plates,\nwells and fields of view, without having to understand how these\nare represented within an OME-Zarr fileset.\n\nIn addition to the python package, we also provide an R package\nthat automatically generates and wraps a python environment with\n`ez_zarr` and all dependencies, available at https://github.com/fmicompbio/ezzarr.\n\n## Example\nYou can use `ez_zarr` from the command line to get information about an OME-Zarr fileset:\n```\nez_zarr tests/example_data/plate_ones.zarr\n```\n\nor from within python to get access to all its functionality:\n```\n## import module\nfrom ez_zarr import ome_zarr\n\n## open an Image\nimg = ome_zarr.Image('tests/example_data/plate_ones_mip.zarr/B/03/0')\nimg\n# Image 0\n# path: tests/example_data/plate_ones_mip.zarr/B/03/0\n# n_channels: 2 (some-label-1, some-label-2)\n# n_pyramid_levels: 3\n# pyramid_zyx_scalefactor: [1. 2. 2.]\n# full_resolution_zyx_spacing (micrometer): [1.0, 0.1625, 0.1625]\n# segmentations: organoids\n# tables (measurements): FOV_ROI_table\n\n## legacy objects from `hcs_wrappers`\nfrom ez_zarr import hcs_wrappers\n\nplate_3d = hcs_wrappers.FractalZarr('tests/example_data/plate_ones.zarr')\nplate_3d\n# FractalZarr plate_ones.zarr\n# path: tests/example_data/plate_ones.zarr\n# n_wells: 1\n# n_channels: 2 (some-label-1, some-label-2)\n# n_pyramid_levels: 3\n# pyramid_zyx_scalefactor: {'0': array([1. 2. 2.])}\n# full_resolution_zyx_spacing: [1.0, 0.1625, 0.1625]\n# segmentations: \n# tables (measurements): FOV_ROI_table\n\n```\n\nA 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).\n\n## Install\n### Using `pip`\n[](https://pypi.org/project/ez-zarr/)\n[](https://pypi.org/project/ez-zarr/)\n\n\nThe release version of `ez_zarr` can be installed using pip:\n```\npip install ez-zarr\n```\n\nThe current (development) `ez_zarr` can be installed from github.com using:\n```\npip install git+ssh://git@github.com/fmicompbio/ez_zarr.git\n```\n\n### Using `conda`\n[](https://anaconda.org/conda-forge/ez-zarr)\n[](https://anaconda.org/conda-forge/ez-zarr)\n[](https://anaconda.org/conda-forge/ez-zarr)\n\nAlternatively, you can install `ez-zarr` from the `conda-forge` channel using:\n```\nconda install -c conda-forge --override-channels ez-zarr\n```\n\n## Software status\n[](https://github.com/fmicompbio/ez_zarr/actions/workflows/test_and_deploy.yaml)\n[](https://codecov.io/gh/fmicompbio/ez_zarr)\n\n## Contributors and License\n`ez_zarr` is released under the MIT License, and the copyright\nis with the Friedrich Miescher Insitute for Biomedical Research\n(see [LICENSE](https://github.com/fmicompbio/ez_zarr/blob/main/LICENSE)).\n\n`ez_zarr` is being developed at the Friedrich Miescher Institute for\nBiomedical Research by [@silvbarb](https://github.com/silvbarb), [@csoneson](https://github.com/csoneson) and [@mbstadler](https://github.com/mbstadler).\n",
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