Radial Cantor Set

Cantor Set

This visualization renders the Cantor set as an L-System, expanding the initial symbol "A" through eight iterations into a hierarchical string representation. Each generation appears as a horizontal band of black rectangles corresponding to the symbol "A," while "B" symbols remain empty, creating the familiar fractal’s self-similar gaps. Built with React and D3 v5, it uses `scaleBand` for positioning and sizing along both axes, with the width scale dynamically redomained per row. The SVG output is generated declaratively, mapping each valid symbol to a `<rect>` element within the React component tree.

82% match

Radial Colors

This radial visualization generates a circular patchwork of colored arcs by iterating a Lindenmayer system 20 times, starting from a single symbol and expanding it through string-rewriting rules. Each iteration produces a ring of segments, with arc angles determined by d3.scaleBand and radii mapped from the iteration count. The SVG paths are rendered using d3.arc, while colors derive from d3.schemeAccent via d3.scaleOrdinal. The pseudorandom pattern emerges from the L-system rules defined in the code, with data generated procedurally rather than sourced externally.

Cantor Set

This visualization renders the Cantor set, a fractal generated by an L-system with production rules A→AB and B→A, iterated 80 times. It displays each iteration as a horizontal band of SVG rectangles, where only segments corresponding to symbol 'A' are drawn, revealing the characteristic recursive pattern of gaps. The implementation combines React for declarative SVG rendering with D3.js utilities, using `d3.range` for iteration generation, `d3.scaleBand` for positioning and sizing, and the `reduce` method to flatten nested data structures.

Cantor Set

This example visualizes the Cantor Set as a grid of thin horizontal bars, showing how the set’s structure emerges from repeated subdivision. It is computed using an L-System with production rules applied over ten iterations, and rendered as SVG rectangles via React. The code uses d3’s `scaleBand` for positioning and `range` for iteration, with each rectangle colored or filtered based on the symbol `A`. The visualization highlights the classic fractal pattern of removing middle thirds, generated entirely through string rewriting and geometric mapping.

Cantor Set

This visualization shows the Cantor set as a series of horizontal rows, with each row representing one iteration of the fractal’s construction. Black rectangles mark the remaining segments after repeatedly removing the middle third of each interval, while empty spaces show the removed portions. The code computes the set using an L-system with rules A→ABA and B→BBB, starting from the initial state "A" over eight iterations. D3 v4 scales (`d3.scaleBand`) position the rectangles in an SVG, and the rendering filters for the "A" symbols to draw the visible bars.

Cantor Set

The Cantor Set appears as a fractal ladder of horizontal black bars against a white background, with each successive row containing fewer and shorter segments. The visualization computes the set as an L-System using production rules (A→ABA, B→BBB), iterated eight times, and renders the result as SVG rectangles via React. D3’s `scaleBand` maps each symbol’s position and width, while a filter selects only A symbols for display. The code leverages React 16.10 and D3 v5, with ReactDOM rendering the final geometric pattern.

Sswvogt

79% match

Radial Chart

A radial bar chart displays the relative frequency of letters A through Z from a CSV dataset. Each letter occupies an equal angular segment, with the bar's outer radius proportional to its frequency value. The visualization uses D3 v3 to bind data to SVG path elements, computing arc geometry via `d3.svg.arc`. A linear scale maps data extents to bar lengths, while text labels are positioned along a circular path using `textPath` with a generated arc. The chart is rendered statically, with no animation or interaction implemented.

DDarienLiang

74% match