Graphia
netgraph
| Graphia | netgraph | |
|---|---|---|
| 8 | 5 | |
| 220 | 642 | |
| 1.4% | - | |
| 9.7 | 7.4 | |
| 5 days ago | 2 months ago | |
| C++ | Python | |
| GPL3 | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Graphia
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NetworkX – Network Analysis in Python
Export the graph to GML or to GraphML or to GraphViz DOT or to some other Graph format. BTW I recommend 3D graph visualization over 2D when possible, that is when you're exploring interactively as opposed to printing figures. The Graphia tool is the only FOSS tool for this purpose that I know of:
https://graphia.app
https://github.com/graphia-app/graphia
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How to create a map showing the relationship between separate data points?
I may be biased. https://graphia.app
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Graphviz: Open-source graph visualization software
A fast 3D alternative for visualizing large graphs is Graphia: https://github.com/graphia-app/graphia https://graphia.app However, it's currently suffering from the Qt switch from 5 to 6.
Regarding Graphviz itself, I wonder why is there no special layout logic for planar graphs? They can be recognized and embedded on the plane in linear time without intersecting edges, so it would be very nice if some of the Graphviz tools actually did that.
A recent set of minimal graph coloring Graphviz visualizations of mine: https://gitlab.com/nsajko/example_optimally_colored_graphs
- Handbook of Graph Drawing and Visualization
- Rick and Morty’s Thanksploitation Deciduous Decision Tree
netgraph
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NetworkX – Network Analysis in Python
You may like my Netgraph library [1], which is a Python library that aims to complement networkx, igraph, and graph-tool with publication-quality visualisations.
Netgraph implements numerous node layout algorithms and several edge routing routines. Uniquely among Python alternatives, it handles networks with multiple components gracefully (which otherwise break most node layout routines), and it post-processes the output of the node layout and edge routing algorithms with several heuristics to increase the interpretability of the visualisation (reduction of overlaps between nodes, edges, and labels; edge crossing minimisation and edge unbundling where applicable). The highly customisable plots are created using Matplotlib, and the resulting Matplotlib objects are exposed in an easily queryable format such that they can be further manipulated and/or animated using standard Matplotlib syntax. Finally, Netgraph also supports interactive changes: with the InteractiveGraph class, nodes and edges can be positioned using the mouse, and the EditableGraph class additionally supports insertion and deletion of nodes and edges as well as their (re-)labelling through standard text-entry.
[1] https://github.com/paulbrodersen/netgraph
- Modeling project dependencies using direct graph
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Ask HN: With open source software, how do I find out where my users come from?
However, last weekend, there was a huge spike in downloads: instead of the 0-5 downloads that are typical for a normal weekend day, there were 2000 downloads, both on Saturday and Sunday [2]. I would love to know what happened here, or at least, I would like to be able to find out the next time something like this happens. Obviously, unlike a normal business, I don't control the distribution, so I can't measure the traffic with Google Analytics or similar tools.
I would love to hear how other people that have open source projects are getting their intel into their user base.
[1] https://github.com/paulbrodersen/netgraph
[2] https://pepy.tech/project/netgraph
- paulbrodersen/netgraph Python drawing utilities for publication quality plots of networks.
- Show HN: Netgraph, a Python library for visualizing networks
What are some alternatives?
AlphaPlot - :chart_with_upwards_trend: Application for statistical analysis and data visualization which can generate different types of publication quality 2D and 3D plots with extensive visual customization.
grand - Your favorite Python graph libraries, scalable and interoperable. Graph databases in memory, and familiar graph APIs for cloud databases.
matplotplusplus - Matplot++: A C++ Graphics Library for Data Visualization 📊🗾
algorithmx-python - A library for network visualization and algorithm simulation.
Gephi - Gephi - The Open Graph Viz Platform
chaos-theory - Playing around with chaos theory simulations. Creating equilibrium graphs and visualizing the logistic maps.
dtale - Visualizer for pandas data structures
pytransform3d - 3D transformations for Python.
sketchviz - A command line clone of https://sketchviz.com/
scapy - Scapy: the Python-based interactive packet manipulation program & library. Supports Python 2 & Python 3.
pygraphistry - PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer
nfstream - NFStream: a Flexible Network Data Analysis Framework.