Fork from AI: Rainbow Colors

A fork of an earlier Sankey experiment, this visualization maps a simplified five-node flow from Sector to Industry to Stock, then splits into Buy and Sell actions. The diagram uses the custom d3.sankey plugin to calculate node positions and link paths, rendered as SVG with D3 v3. The example hand-codes its data in a sankeydata.json file rather than loading it externally. Styling applies crisp node rectangles, bold text labels, and semi-transparent black links that darken on hover to show the proportional flow of values between each stage.

MMuhammadAaqib137

65% match

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Fork of Fork of Sankey Particles

An interactive Sankey diagram visualizes energy flows between sources and consumers, with animated particles traveling along links to represent the magnitude of each transfer. The SVG renders nodes and link paths using D3.js and the sankey layout plugin, while a separate Canvas layer draws moving particles computed from each link's path geometry. Particles are generated based on a frequency scale derived from link values and fade over time, creating a dynamic sense of flow intensity across the network.

DDonald Bagwell

64% match

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Fork of SANKEY Experiment

A directed-flow diagram maps notification counts from a total source through matched and scrap categories into downstream targets. The visualization uses a custom `d3.sankey` layout with SVG rendering, featuring draggable nodes and hoverable links with adjustable stroke opacity. Node heights encode link values, and the layout algorithm iteratively optimizes node positions to reduce collisions. Data comes from a static JSON file, with node labels styled in bold Verdana text and the chart embedded in a React application shell.

PPeter S

63% match

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Fork of SANKEY Experiment

A fork of a Sankey experiment visualizes the flow of notifications from "Total Notifications" through "Matched" or "Scrap" categories, using a custom D3.js plugin. The SVG diagram renders rectangular nodes connected by curved links, with colors and opacity indicating flow volume. It employs the `d3.sankey` layout function to compute node positions and link depths, while `d3.nest` organizes nodes by breadth for collision resolution. The code leverages D3's `d3.interpolateNumber` for link curvature and reads data from a static `sankeydata.json` file.

Ggongxinya

63% match

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test of Fork of SANKEY Experiment

A Sankey diagram shows the flow of notifications from a total pool into matched and scraped categories, then onward to specific systems like XRM, Prodc, PN OTD, and CRB. The visualization uses D3.js (v3.5.17) with a custom `d3.sankey` layout algorithm that computes node positions and link curvatures. Data comes from a JSON file containing node names and link values, rendered as SVG elements with styled rectangles and cubic Bézier curves. Hovering a link increases its stroke opacity to highlight the path.

SSenserva

62% match

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Fork of Sankey Particles

This fork of the Sankey diagram animates particle flow along links to show energy transfer magnitudes. The visualization combines SVG for static nodes and links with a Canvas overlay for the moving particles, using d3.timer to update particle positions via path.getPointAtLength. It adapts Mike Bostock's d3.sankey layout, applying it to the energy.json dataset, with particle frequency and size scaled by link value.

Ggongxinya

62% match

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Fork from AI: Implement Idea 5 List

Prototype of idea #5 from VIZ_IDEAS.md: Sankey diagram of episode → source → target interaction weight flow.

TTest

61% match