Interactive volumetric voxel viewing
Project description
# Volume Viewer Jupyter Notebook Extension
Embeds the Allen Institute web-based 3d viewer in Jupyter notebooks
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## Description
Most 3D viewers are far too heavyweight to use for quick visualization tasks when experimenting with tractably-sized (analyzing, checking, …) 3D volumetric datasets. nbvv is a multichannel volume viewer for interactive data exploration in jupyter. This is a jupyter widget that provides volumetric rendering given a multiple channel zstack as a numpy array.
Envisioned user group is anyone who wants a robust and quick way to interactively interrogate volumetric data as part of their workflows; domain which motivated development is multi-channel volumetric light/fluorescence microscopy datasets. The viewer is optimized for volume data that has finer xy resolution than z resolution.
## Installation
To install from source: You will need to make sure nodejs and npm are installed on your system. One way to do this is using nvm, for example: ` nvm install 14.17.0 nvm use 14.17.0 `
Make sure you have jupyter notebook and nbextensions installed (not necessary in every environment): ` pip install jupyter_contrib_nbextensions && jupyter contrib nbextension install --user ` Then you can run build.sh from this repo, or: ` pip install . `
To install from pypi install the package: ` pip install nbvv ` and then enable the extension in jupyter: ` jupyter nbextension install --py nbvv --sys-prefix jupyter nbextension enable nbvv --py --sys-prefix `
## Documentation
If you have more extensive technical documentation (whether generated or not), ensure they are published to the following address: For full package documentation please visit [allen-cell-animated.github.io/nbvv](https://allen-cell-animated.github.io/nbvv/index.html).
## Quick Start
try the demo notebook: ` jupyter notebook examples/demo.ipynb `
In a Jupyter notebook, load or create volume data in a numpy array. The data should be of shape (Z,Y,X) or (C,Z,Y,X) for multi-channel data. Display the numpy data using ` import nbvv nbvv.volshow(mynumpydata, spacing=(1.0, 1.0, 4.0)) `
## Development
See [CONTRIBUTING.md](CONTRIBUTING.md) for information related to developing the code.
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