Project description
NAVis is a Python 3 library for Neuron Analysis and
Visualization with focus on hierarchical tree-like neuron data.
Features:
interactive 2D (matplotlib) and 3D (vispy or plotly) plotting of neurons
virtual neuron surgery: cutting, pruning, rerooting
clustering methods (e.g. by connectivity or synapse placement)
R bindings (e.g. for libraries nat, rcatmaid, elmr)
interfaces with Blender 3D and Cytoscape
Check out the Documentation.
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
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file navis-0.1.0.tar.gz.
File metadata
-
Download URL: navis-0.1.0.tar.gz
- Upload date:
-
Size: 1.4 MB
- Tags: Source
-
Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.4.2 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.8.0 tqdm/4.31.0 CPython/3.5.3
File hashes
Hashes for navis-0.1.0.tar.gz
| Algorithm |
Hash digest |
|
| SHA256 |
0c2c3c72e302db1160d2575bc7e5c8b4a2381268dfb32214868109f01c720dca
|
|
| MD5 |
74e6f568205dd6b9b2c06538c635a699
|
|
| BLAKE2b-256 |
e55045a6376a1197197bb6035cd0a030baf5d5bfba6e71bcd186e0d3f4a8ca1e
|
|
See more details on using hashes here.
File details
Details for the file navis-0.1.0-py3-none-any.whl.
File metadata
-
Download URL: navis-0.1.0-py3-none-any.whl
- Upload date:
-
Size: 1.4 MB
- Tags: Python 3
-
Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.4.2 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.8.0 tqdm/4.31.0 CPython/3.5.3
File hashes
Hashes for navis-0.1.0-py3-none-any.whl
| Algorithm |
Hash digest |
|
| SHA256 |
479e132f495b2f24495ad1c251224b427aa372a44662c199275dc7cfc175e01f
|
|
| MD5 |
1ee04ca5aa008ca65ed9de3247259b6d
|
|
| BLAKE2b-256 |
ef4e8a7733c38b58768d114bcfcfe921119384af614c62643626a4712f47c99e
|
|
See more details on using hashes here.