https://github.com/Open-Science-Tools/nd2reader
Pure Python library for reading NIS Elements ND2 images and metadata
https://github.com/Open-Science-Tools/nd2reader
microscopy microscopy-images nd2 nikon nis-elements pims
Last synced: about 1 year ago
JSON representation
Pure Python library for reading NIS Elements ND2 images and metadata
- Host: GitHub
- URL: https://github.com/Open-Science-Tools/nd2reader
- Owner: Open-Science-Tools
- License: gpl-3.0
- Created: 2017-02-14T15:47:40.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2025-01-15T10:15:32.000Z (over 1 year ago)
- Last Synced: 2025-04-17T13:06:57.046Z (about 1 year ago)
- Topics: microscopy, microscopy-images, nd2, nikon, nis-elements, pims
- Language: Python
- Homepage: https://open-science-tools.github.io/nd2reader/
- Size: 27.1 MB
- Stars: 47
- Watchers: 4
- Forks: 30
- Open Issues: 29
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: COPYING
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-biological-image-analysis - Nd2reader - A pure-Python package that reads images produced by NIS Elements 4.0+. (Other)
README
# nd2reader
**This package is no longer actively developed because I'm no longer working in this field and can't properly maintain it. If you'd like to help, please see the [contributing](https://github.com/rbnvrw/nd2reader/blob/master/CONTRIBUTING.md) page
for more information.**
[](https://anaconda.org/conda-forge/nd2reader)
[](https://anaconda.org/conda-forge/nd2reader)
[](https://github.com/rbnvrw/nd2reader/actions/workflows/python-package.yml)
### About
`nd2reader` is a pure-Python package that reads images produced by NIS Elements 4.0+. It has only been definitively tested on NIS Elements 4.30.02 Build 1053. Support for older versions is being actively worked on.
The reader is written in the [pims](https://github.com/soft-matter/pims) framework, enabling easy access to multidimensional files, lazy slicing, and nice display in IPython.
### Alternatives
- [nd2](https://pypi.org/project/nd2/)
- Open a PR if you'd like to be listed here.
### Documentation
The documentation is available [here](https://open-science-tools.github.io/nd2reader/).
### Installation
The package is available on PyPi. Install it using:
```
pip install nd2reader
```
If you don't already have the packages `numpy`, `pims`, `six` and `xmltodict`, they will be installed automatically if you use the `setup.py` script.
Python >= 3.5 are supported.
#### Installation via Conda Forge
Installing `nd2reader` from the `conda-forge` channel can be achieved by adding `conda-forge` to your channels with:
```
conda config --add channels conda-forge
```
Once the `conda-forge` channel has been enabled, `nd2reader` can be installed with:
```
conda install nd2reader
```
It is possible to list all of the versions of `nd2reader` available on your platform with:
```
conda search nd2reader --channel conda-forge
```
### ND2s
`nd2reader` follows the [pims](https://github.com/soft-matter/pims) framework. To open a file and show the first frame:
```python
from nd2reader import ND2Reader
import matplotlib.pyplot as plt
with ND2Reader('my_directory/example.nd2') as images:
plt.imshow(images[0])
```
After opening the file, all `pims` features are supported. Please refer to the [pims documentation](http://soft-matter.github.io/pims/).
#### Backwards compatibility
Older versions of `nd2reader` do not use the `pims` framework. To provide backwards compatibility, a legacy [Nd2](https://open-science-tools.github.io/nd2reader/nd2reader.html#module-nd2reader.legacy) class is provided.
### Contributing
If you'd like to help with the development of nd2reader or just have an idea for improvement, please see the [contributing](https://github.com/rbnvrw/nd2reader/blob/master/CONTRIBUTING.md) page
for more information.
### Bug Reports and Features
If this fails to work exactly as expected, please open an [issue](https://github.com/rbnvrw/nd2reader/issues).
If you get an unhandled exception, please paste the entire stack trace into the issue as well.
### Acknowledgments
PIMS modified version by Ruben Verweij.
Original version by Jim Rybarski. Support for the development of this package was partially provided by the [Finkelstein Laboratory](http://finkelsteinlab.org/).