Gist ed756303e2cbb63f5fc8

100%

Gist ed756303e2cbb63f5fc8

✓ Published0🌍 Public

Last edited Nov 7, 2015

Created on Nov 6, 2015

This visualization uses a force-directed layout to show relationships between terms and facets, with each term linked to a facet (binding or year). The graph is rendered using D3’s `d3.forceSimulation`, with nodes and links drawn as SVG elements. The code reads from an XML file (`facets.xml`) via `d3.xml` and parses `<term>` elements to build the network. It applies a force simulation with charge and link forces, and updates node positions on each tick using `d3.drag` for interactivity. The visualization clearly distinguishes term nodes from facet nodes, revealing clustering by year and binding type.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 7f84369bd0c0b467d6b0

This visualization uses a force-directed graph layout implemented with D3’s `d3.forceSimulation` to position nodes connected by links, representing a network of relationships from an underlying dataset. The scene renders on an HTML5 Canvas, with the simulation’s tick events redrawing the nodes as colored circles and the edges as lines. A zoom interaction is added via `d3.zoom`, applying a transform to the canvas context to allow panning and scaling of the graph. The example demonstrates a typical static network diagram without additional interactivity beyond zoom and drag, relying on the force simulation to settle the layout.

MMbrownshoes

78% match

Loading thumbnail…

Gist 05ff2219cb2cc463ad1612e8a501c400

This visualization uses a force-directed simulation to show a network of interconnected nodes, with each node represented as a colored circle and links drawn between related points. The code relies on `d3.forceSimulation` and `d3.forceLink` to compute the layout, while `d3.drag` enables user interaction to move nodes. A canvas element renders the graph, with the simulation updating positions each tick. The data appears to be a small custom-generated dataset of nodes and edges, with node colors mapping to distinct groups, and the visualization does not include any external data source or geographic rendering.

MMistyBlunch

76% match

Loading thumbnail…

Gist f52706b726949be61205fcf8133a66e7

This example visualizes a dynamic network of interconnected nodes, showing how forces shape a cluster’s layout over time. It uses a force-directed simulation via `d3.forceSimulation` with charge, link, and collision forces to position nodes, while links are drawn as straight lines. The rendering relies on SVG paths updated each tick, and the code includes a custom drag interaction using `d3.drag` to let viewers manually reposition nodes. The underlying data structure is a small JavaScript array of objects representing nodes and links, likely sourced from a static inline dataset. The visualization emphasizes real-time interaction rather than geographic or spatial data, focusing on emergent clustering behavior.

11wheel

75% match

Loading thumbnail…

Gist a7d5ced57721ac3f7075bbbbaee32a49

This interactive visualization uses a force-directed simulation to animate a network of nodes and links, showing how connected elements cluster and repel. The code relies on D3’s `d3.forceSimulation` with custom forces for charge, centering, and collision, while link positions update via the simulation’s tick handler. Node rendering uses SVG circles, and the visualization reads its data from an embedded array of node and link objects, with no external data source. The interaction includes drag-and-drop support via D3’s drag behavior, letting viewers move nodes while the simulation continuously recalculates positions.

11wheel

75% match

Loading thumbnail…

Gist 1328c48d7adc70f7a23d190cdf877f7d

This visualization uses D3.js to render a dynamic network graph of interconnected nodes and links. The code employs `d3.forceSimulation` with forces such as charge, link, and centering to position the nodes, while links and nodes are drawn using SVG lines and circles. The simulation updates positions on each tick, and the graph responds to drag and zoom interactions. Node sizes and link thicknesses are determined by degree and connection counts, offering a clear view of the network’s structure and clustering.

MMbrownshoes

75% match

Loading thumbnail…

Gist 3e83522b4fd1d103c56977dac9442a3e

This example visualizes a force-directed network graph, showing nodes and edges arranged in a cluster layout. It uses D3’s `d3.forceSimulation` to compute node positions and `d3.forceLink` for edge constraints, rendering the result as an SVG. The graph data is generated locally in the code via a helper function that builds node and link arrays, with node colors reflecting a categorical scale. The visualization updates positions on each simulation tick, producing an interactive, animated network layout.

MMistyBlunch

75% match

Loading thumbnail…

Gist 8a97689739c217f28474d80c89013628

This visualization uses a force-directed graph to show relationships between entities, with nodes positioned by `d3.forceSimulation` and links drawn as curved paths. The code computes node sizes and colors from quantitative attributes, while a canvas overlay via `d3.geoPath` and `getImageData` samples pixel density to modulate link opacity based on local clustering. It employs a custom `transition.attrTween` to animate node drift when the simulation restarts, and uses the `d3.hierarchy` API to flatten nested data from a JSON file. The visualization reads credentials from an `env.list` file for a private data source, but the rendering logic is independent of that authentication step.

CConorAspell

75% match

Loading thumbnail…

Gist db32a113f546aa03b43c0e1f84f80d28

The visualization shows a force-directed network graph of GitHub gist data, with nodes representing individual gists and links showing relationships between them. It uses d3.forceSimulation to compute the layout, with node size encoding gist size and color indicating file type or language. The rendering relies on SVG elements updated per tick via the simulation’s tick event. The code loads a static JSON file containing preprocessed gist metadata, and does not use canvas or WebGL. The visualization highlights clustering patterns among related gists, revealing emergent communities in the dataset.

335degrees

75% match