part 2, Zoom and Panning with D3.js and canvas

part 3, Zoom and Panning with D3.js and canvas

This example demonstrates interactive zooming, panning, and brushing of a synthetic scatterplot containing 10,000 random data points, rendered with a hybrid SVG–Canvas approach. The D3.js v4 code overlays an SVG layer for axes and controls on top of a Canvas layer for efficient point drawing, using `d3.zoom` and `d3.brush` to handle transformations and selections. A toolbar offers Reset, Zoom, and Brush modes, where zooming rescales axes via `d3.scaleLinear` and redraws points with `Canvas` arc primitives, while brushing highlights the selected region on the SVG layer.

94% match

part 1, Zoom and Panning with D3.js and canvas,

This example shows a canvas-based scatter plot of 10,000 random data points, with the page built for future brushing interactions. It uses D3.js v4 to create SVG axes and labels, while rendering the points themselves on a separate HTML5 canvas element for performance. The code initializes linear scales for both x and y dimensions, draws the axes with `d3.axisBottom` and `d3.axisLeft`, and plots each point using the Canvas API’s `arc` and `fill` methods. The canvas is positioned over the SVG using CSS classes, demonstrating a hybrid rendering approach.

94% match

Canvas Geometric Zooming

This example demonstrates geometric zooming on a canvas, where a scatterplot of 2,000 normally distributed points scales and translates as a single unit. The code uses D3 v4’s `d3.zoom` to handle user input, applying the transform directly to the canvas context via `translate` and `scale`. Points are drawn with the Canvas 2D API’s `arc` method, and the zoom behavior redraws all points on each event. No semantic distortion occurs—the entire visualization scales uniformly.

86% match

Zoom + Pan

A D3.js line chart with grid-like axes supports interactive panning and zooming, controlled by dragging and mouse-wheel gestures. The view resets via a button, triggering a smooth animated transition back to the default domain using `d3.behavior.zoom`, `d3.scale.linear`, and `d3.transition().tween`. The SVG rendering showcases the axis updates, while the button click remaps the scales programmatically and rebinds them to the zoom behavior.

84% match

Canvas Chart Zoom

This example renders 10,000 random data points as a scatter plot on a Canvas surface, using d3fc’s `cartesianCanvasChart` and `seriesCanvasPoint` components. A d3-zoom handler enables pan and zoom interactions, re-rendering the chart on each transform by updating linear scales and invoking the chart’s render function. The code also includes SVG equivalents (`cartesianSvgChart`, `seriesSvgPoint`) to highlight the performance difference, with Canvas offering roughly 10x faster redraws.

CColinEberhardt

Pan & Zoom Axes

This example demonstrates a zoomable scatterplot where panning and zooming are controlled by the d3-zoom library. The visualization shows a colorful gradient rectangle as the data view, with axes that rescale dynamically through `transform.rescaleX` and `transform.rescaleY`. Users can drag to pan and scroll to zoom, with a button to reset the view via `d3.zoomIdentity`. The SVG rendering uses d3-scaleLinear for axes and a text gradient inspired by Nadieh Bremer.

Mmbostock

Canvas Semantic Zooming

This example demonstrates semantic zooming of a scatterplot containing 2,000 points rendered on a Canvas element. As the user zooms, the points are re-projected through the current transform, and the drawing is cleared and redrawn at each zoom event. The code uses D3’s `d3.zoom` and `d3.event` to manage the interactive transform, and the `d3.randomNormal` distribution positions the data in a Gaussian cluster centered on the canvas. All drawing occurs directly on the Canvas 2D context.

Mmbostock

Canvas Geometric Zooming

This example demonstrates geometric zooming on a canvas, where a scatterplot of 2,000 normally distributed points scales and translates as a unified image. The code uses d3.zoom with scaleExtent to handle user interaction, applying the transform directly to the canvas context via translate and scale methods. Points are drawn using the Canvas 2D API’s arc and fill operations, while the underlying data is generated with d3.randomNormal. Unlike semantic zooming, this approach redraws the entire visualization at the new scale, preserving the spatial relationships between all marks.

Mmbostock