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graphistry avatar

graphistry/pygraphistry

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2,522 stele·231 fork-uri·Python·BSD-3-Clause·2 vizualizări

Pygraphistry

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

Features

  • Graph Learning - Tool for visual graph analysis and data exploration.
  • Python Network Analysis - Extracting and visually exploring large-scale graph data.

Istoric stele

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Întrebări frecvente

Ce face graphistry/pygraphistry?

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

Care sunt principalele funcționalități ale graphistry/pygraphistry?

Principalele funcționalități ale graphistry/pygraphistry sunt: Graph Learning, Python Network Analysis.

Care sunt câteva alternative open-source pentru graphistry/pygraphistry?

Alternativele open-source pentru graphistry/pygraphistry includ: benedekrozemberczki/karateclub — Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020). chszlab/chszlablib — Python Frontend to Algorithms of the Algorithm Engineering Group Heidelberg. dmlc/dgl — DGL is a Python library for building and training graph neural networks. It functions as a graph message passing… ericmjl/nxviz — Visualization Package for NetworkX. giuliorossetti/cdlib — Community Discovery Library. benedekrozemberczki/littleballoffur — Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020).

Alternative open-source pentru Pygraphistry

Proiecte open-source similare, clasificate după numărul de funcționalități comune cu Pygraphistry.
  • benedekrozemberczki/karateclubAvatar benedekrozemberczki

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    Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

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  • chszlab/chszlablibAvatar CHSZLab

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  • dmlc/dglAvatar dmlc

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    DGL is a Python library for building and training graph neural networks. It functions as a graph message passing framework and a geometric deep learning tool, enabling the development of models that analyze graph-structured data. The library is designed for large-scale graph processing, utilizing distributed training and neighbor sampling to handle datasets with billions of edges. It provides specialized support for heterogeneous graph modeling, allowing for the representation of complex real-world entities with multiple node and edge types. Its capabilities cover a wide range of graph tasks

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    Vezi pe GitHub↗14,283
  • benedekrozemberczki/littleballoffurAvatar benedekrozemberczki

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Vezi toate cele 17 alternative pentru Pygraphistry→