Fetch data from DVID server
Project description
dvidtools
Python tools to fetch data from DVID servers.
Find the documentation here.
Want to query a neuPrint server instead? Check out neuprint-python.
What can dvidtools
do for you?
- get/set user bookmarks
- get/set neuron annotations (names)
- download precomputed meshes, skeletons (SWCs) and ROIs
- get basic neuron info (# of voxels/synapses)
- get synapses
- get connectivity (adjacency matrix, connectivity table)
- retrieve labels (TODO, to split, etc)
- map positions to body IDs
- mesh or skeletonize sparsevols
- detect potential open ends (based on a script by Stephen Plaza)
Install
Make sure you have Python 3 (3.6 or later), pip. Then run this:
pip3 install dvidtools
To install the dev version straight from Github:
pip3 install git+https://github.com/flyconnectome/dvid_tools@master
Optional dependencies
Necessary dependencies will be installed automatically.
If you plan to use the tip detector with classifier-derived confidence, you will also need sciki-learn:
pip3 install scikit-learn
For from-scratch skeletonization you need to install skeletor
:
pip3 install skeletor
Examples
Please see the documentation for examples.
Testing
For testing you need to have two environment variables set: DVID_TEST_SERVER
and DVID_TEST_NODE
. These should point to a DVID server/node that contain
the Janelia hemibrain dataset. Then run:
$ pytest -v
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for dvidtools-0.4.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9a9b077bdeb35c91da101343fca7ed6bc2247092455a5d318798039b6aef6dbb |
|
MD5 | 9e644f1f9cb25c5aefe2376e12b1478b |
|
BLAKE2b-256 | 19f62847b02e57c5ef59ebb5a5c09c6dc062958e1d84e88609c4a5811166655d |