NetLSD
NetLSD is a family of spectral graph descriptros. Given a graph, NetLSD computes a low-dimensional vector representation that can be used for different tasks.
Quick start
import netlsd
import networkx as nx
g = nx.erdos_renyi_graph(100, 0.01) # create a random graph with 100 nodes
descriptor = netlsd.heat(g) # compute the signature
That’s it! Then, signatures of two graphs can be compared easily. NetLSD supports networkx, graph_tool, and igraph packages natively.
import netlsd
import numpy as np
distance = netlsd.compare(desc1, desc2) # compare the signatures using l2 distance
distance = np.linalg.norm(desc1 - desc2) # equivalent
For more advanced usage, check out online documentation.
Requirements
numpy
scipy
Installation
cd netlsd
pip install -r requirements.txt
python setup.py install
Or simply pip install netlsd
Citing
If you find NetLSD useful in your research, we ask that you cite the following paper:
@inproceedings{Tsitsulin:2018:KDD,
author={Tsitsulin, Anton and Mottin, Davide and Karras, Panagiotis and Bronstein, Alex and M{\"u}ller, Emmanuel},
title={NetLSD: Hearing the Shape of a Graph},
booktitle = {Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
series = {KDD '18},
year = {2018},
}
Misc
NetLSD - Hearing the shape of graphs.
MIT license
Documentation: http://netlsd.readthedocs.org
Metadata
Release files for NetLSD 1.0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| NetLSD-1.0.2.tar.gz | 6.0 kB | Without provenance | Details for NetLSD-1.0.2.tar.gz |
Release files / NetLSD-1.0.2.tar.gz
| Download URL | NetLSD-1.0.2.tar.gz |
|---|---|
| Size | 6.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2e407e5db5dbc54079f99537d7608079e2ee73f1415ce8fb0eab9497936c7349
|
|
BLAKE2b-256 checksum How to use checksums |
37059f479b6fd30275290bc2abdd15dc2364b6942758a3616cd9210bcb659952
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
Python-urllib/3.6
|
Security for NetLSD 1.0.2
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.