https://github.com/nvladimus/npy2bdv

Fast writing of numpy 3d-arrays into HDF5 Fiji/BigDataViewer files.
https://github.com/nvladimus/npy2bdv

bigdataviewer h5 hdf5 numpy

Last synced: 6 days ago
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Fast writing of numpy 3d-arrays into HDF5 Fiji/BigDataViewer files.

• Host: GitHub
• URL: https://github.com/nvladimus/npy2bdv
• Owner: nvladimus
• License: gpl-3.0
• Created: 2019-08-20T16:10:51.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-08-22T10:26:53.000Z (6 months ago)
• Last Synced: 2025-02-07T12:12:39.881Z (13 days ago)
• Topics: bigdataviewer, h5, hdf5, numpy
• Language: Python
• Homepage:
• Size: 4.13 MB
• Stars: 35
• Watchers: 6
• Forks: 12
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# npy2bdv

 A library for writing/reading HDF5/XML datasets of 

 Fiji BigDataViewer/BigStitcher format as numpy arrays. 

 

[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)

[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

 

 ## Installation

 Run `pip install npy2bdv` in the command line. Use `import npy2bdv` in the code.

 

 ## Documentation

For a quick start, see examples in the Jupyter 

[`notebook`](/docs/examples/examples_h5writing.ipynb).

API [documentation](https://nvladimus.github.io/npy2bdv/).

 ## Supported H5/XML writing options

 * compression methods `None`, `gzip`, `lzf` (`None` by default).

 * downsampling options: 

    - any number of mipmap levels

    - computed via averaging, compatible with BigDataViewer/BigStitcher convention.

 * user-defined block sizes for H5 storage (default `4,256,256`)

 * any number of time points, illuminations, channels, tiles, angles.

 * arbitrary affine transformation for each individual view (e.g. translation, rotation, shear).

 * arbitrary voxel calibration for each view, to account for spatial anisotropy.

 * individual views can differ in dimensions, voxel size, voxel units, exposure time, and exposure units.

 * missing views are labeled in XML automatically.

 * support of additional meta-information:

    - camera properties: `name`, `exposureTime`, `exposureUnits`

    - `microscope` (name and version), `user`

 * writing virtual stacks of arbitrary size, by plane or sub-stack. Handy when your stack is larger than your RAM.

    - virtual stacks can be written with multiple subsampling levels and compression.

    

 ## New features

 See [Recent changes](CHANGELOG.md)

 

 ## Writing speed

 Currently speeds betewen 150 - 320 MB/s were achieved with confidence. Speeds of up to 2300 MB/s reported in earlier versions are likely due to bugs in testing methods in notebook [`examples_h5writing.ipynb`](/docs/examples/examples_h5writing.ipynb). More tesing is underway.

 ## Acknowledgements

 This code was inspired by [Talley Lambert's](https://github.com/tlambert03/imarispy) code 

 and improved by generous input from Adam Glaser, [VolkerH](https://github.com/VolkerH), Doug Shepherd, 

 [Peter H](https://github.com/abred), [Mike Taormina](https://github.com/miketaormina) and [Pradeep Rajasekhar](https://github.com/pr4deepr).

 

 To report issues or bugs please use the [issues](https://github.com/nvladimus/npy2bdv/issues) tool.

 

 ## Citation

 You can cite it like so

 

 [![DOI](https://zenodo.org/badge/203410946.svg)](https://zenodo.org/badge/latestdoi/203410946)

## Support

If you find this library useful, send me some love :blush:



It will give me some dopamine and motivation to keep improving it :heart: