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mixtank-new     (Miscellaneous Networks)

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This network is in the collection of Miscellaneous Networks





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Metadata

Tags
AuthorJ. Marchal
Date2005
Edge weightsWeighted
Metadatacomputational fluid dynamics problem
DescriptionPOLYFLOW mixing tank (new version to avoid underflow)

Citing the repository in published materials

If you find Network Repository useful for your research, please consider citing the following paper:

@inproceedings{nr,
     title={The Network Data Repository with Interactive Graph Analytics and Visualization},
     author={Ryan A. Rossi and Nesreen K. Ahmed},
     booktitle={Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence},
     url={http://networkrepository.com},
     year={2015}
}

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Network Statistics

Nodes30K
Edges2M
Density0.00437954
Maximum degree306
Minimum degree20
Average degree131
Assortativity0.0209445
Number of triangles147.3M
Average number of triangles4.9K
Maximum number of triangles13.7K
Average clustering coefficient0.625705
Fraction of closed triangles0.42836
Maximum k-core89
Lower bound of Maximum Clique31

Data Preview

Interactive visualization of mixtank_new's graph structure

Interactively explore the networks graph structure!

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Interactive Visualization of Node-level Properties and Statistics

Tools for Interactive Exploration of Node-level Statistics

Visualize and interactively explore mixtank-new and its important node-level statistics!

  • Each point represents a node (vertex) in the graph.
  • A subset of interesting nodes may be selected and their properties may be visualized across all node-level statistics. To select a subset of nodes, hold down the left mouse button while dragging the mouse in any direction until the nodes of interest are highlighted.This feature allows users to explore and analyze various subsets of nodes and their important interesting statistics and properties to gain insights into the graph data
  • Zoom in/out on the visualization you created at any point by using the buttons below on the left.
  • Once a subset of interesting nodes are selected, the user may further analyze by selecting and drilling down on any of the interesting properties using the left menu below.
  • We also have tools for interactively visualizing, comparing, and exploring the graph-level properties and statistics.
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Interactive Visualization of Node-level Feature Distributions

Node-level Feature Distributions

degree distribution

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degree CDF

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degree CCDF

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kcore distribution

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kcore CDF

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kcore CCDF

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triangle distribution

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triangle CDF

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triangle CCDF

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All visualizations and analytics are interactive and flexible for exploratory analysis and data mining in real-time and include the following features:

  • Degree, k-core, triangles, and triangle-core distributions. We include plots for each of the fundamental graph features and counts of the number with a particular property (i.e., number of nodes that form k triangles or have degree k, etc.)
  • We also include the CDF and CCDF distributions for each graph in the collection.
  • All visualizations and plots are zoomable. One may zoom-in or out on the data visualization using scrolling.
  • Panning. Users may also click anywhere on the plot and move the mouse in any direction to pan.
  • Adjust scale and other application dependent-parameters. All interactive visualizations may adjust the scale which is particularly important in certain types of graph data that contain highly skewed graph properties (power-lawed graphs and/or networks) such as degree distribution.

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