nbvv 1.2.0

Interactive volumetric voxel viewing

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 jupyterlab, jupyter notebook and nbextensions installed (not necessary in every environment):

pip install jupyter_contrib_nbextensions && jupyter contrib nbextension install --user

Install nbvv in one of these ways:

• Option 1: Install from PyPi

  pip install nbvv
  jupyter nbextension install --py nbvv --sys-prefix
  jupyter nbextension enable nbvv --py --sys-prefix
  

• Option 2: Run build.sh from this repo
• Option 3: Step-by-step, from source:

  pip install -e .
  jupyter nbextension install --py --overwrite --symlink --sys-prefix nbvv
  jupyter nbextension enable --py --sys-prefix nbvv
  jupyter labextension develop . --overwrite
  

Documentation

Extended documentation is not available yet. When completed it will be made available at: allen-cell-animated.github.io/nbvv.

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), channel_names=my_list_of_channel_name_strings)

Development

See CONTRIBUTING.md for information related to developing the code.