Free Interactive Voronoi Treemap Polygon Visualization Tool—
gemini-3.0-flash
gemini-3.0-flashVisualize hierarchical data effortlessly with this free Voronoi Treemap generator. Create weighted polygon distributions for analytics and design in the browser.
What This App Does
Visualize hierarchical data effortlessly with this free Voronoi Treemap generator. Create weighted polygon distributions for analytics and design in the browser. — generated by gemini-3.0-flash and published by @Akhenaten on Slopstore. Categorized under Utility, this app is part of Slopstore's curated collection of AI-generated tools and experiments. Run it free in your browser. No installation needed.
AI Generation Prompt
Technical Specification: Interactive Voronoi Treemap Generator
Overview
A high-performance, single-file browser utility designed to generate weighted Voronoi Treemaps from user-provided hierarchical datasets. The tool focuses on clean aesthetics, real-time rendering, and high-quality SVG exports.
Constraints & Architecture
- Single File: All HTML, CSS (Tailwind via CDN), and JS (D3.js via CDN) contained within one file.
- No Persistent Storage: Absolutely no usage of
localStorage,sessionStorage, or cookies. The state is volatile and exists only during the tab lifecycle. - Sandbox Compliant: No reliance on external browser APIs that may be restricted in sandboxed iframes.
- Aesthetic: High-contrast, light-mode only design with professional typography (Inter/system-ui) and smooth transitions.
Feature List
- Data Input: A syntax-highlighted textarea for JSON/CSV input with real-time validation.
- Configuration Panel:
- Weight normalization toggles.
- Color palette selection (preset professional schemes).
- Stroke weight and opacity sliders.
- Toggleable labels for polygon nodes.
- Rendering Engine: Utilizes D3.js for calculating weighted Voronoi polygons.
- Export: One-click SVG download functionality for the generated canvas.
- Responsive UI: The layout switches from a side-by-side view on desktops to a stacked view on smaller devices.
UI Layout
- Header: Simple, clean application title with a descriptive tagline.
- Primary Split-View:
- Left Sidebar (300px): Configuration inputs, data paste area, and action buttons (Generate/Reset/Download).
- Main Canvas (Flexible): Full-screen interactive visualization area with subtle background grid.
- Modals: Custom HTML/CSS modal popups for errors (e.g., malformed data) or download confirmations.
Design System & Palette
- Background:
#ffffff(Base),#f8fafc(Sidebar/Controls). - Primary Accent:
#3b82f6(Buttons, active states). - Text:
#1e293b(Primary),#64748b(Secondary). - Borders:
#e2e8f0(Separator lines). - Transitions: All UI interactive elements use 200ms
ease-in-outtransitions.
Interaction Logic
- Data Parsing: On input, the app parses the JSON/CSV into an internal weighted object array.
- Computation: Trigger D3
voronoiMapalgorithm upon user click. Show a subtle progress spinner during compute. - Visual Update: Smooth fade-in of the polygons on the canvas after generation.
- Tooltips: Hovering over a polygon displays the label and weight in a custom tooltip box floating above the canvas.
Developer Instructions
- Use the
d3andd3-voronoi-mapCDNs. - Use
Tailwindfor all layout and component styling to ensure a modern, SaaS-like look. - Implement a clean 'Copy to Clipboard' or 'Download SVG' trigger using
Blobobjects for file generation. - Ensure all buttons have a consistent
hoverandactivestate styling. - Do not use any external tracking, analytics, or external API calls.
Spread the word
gemini-3.0-flashFiles being used
Frequently Asked Questions
Everything you need to know about using this application.
What is a Voronoi Treemap visualization?
A Voronoi Treemap is a sophisticated data visualization technique that uses Voronoi tessellation to represent hierarchical data structures. Unlike standard rectangular treemaps, this method uses organic, weighted polygon shapes to fill a defined area, making it an excellent choice for aesthetically pleasing and unique data representations. This tool allows users to input weighted data sets and automatically computes the optimal polygon layout. It is widely used in information design, financial reporting, and scientific mapping to illustrate the relative proportions of various categories in a non-traditional, visually engaging format.
How do I format data for the Voronoi generator?
The application supports raw data input via a dedicated side panel, accepting standard JSON arrays or CSV formats. For JSON, you should provide an object structure with key-value pairs representing the entity name and its associated weight or numerical value. Once the data is submitted, the algorithm dynamically calculates the area of each cell based on its weight relative to the total input. The tool processes this data entirely in your browser's memory, ensuring that your sensitive information remains private and is never transmitted to an external server or stored in local browser caches.
Can I export or save my generated visualizations?
Yes, you can export your completed Voronoi Treemap directly from the browser as a high-quality SVG (Scalable Vector Graphics) file. This format is ideal for inclusion in reports, websites, or design projects, as it maintains resolution quality at any scale. Because this application is strictly sandboxed and does not use local storage or cookies, your visualization state is kept only in the active session. If you refresh the page, the state is cleared, so please be sure to download your generated graphics before navigating away from the page.
Does this tool require external software or plugins?
This is a purely client-side, browser-based utility. It requires no installation, plugin, or account creation to use. All calculations and rendering are performed in real-time using high-performance JavaScript libraries, ensuring that the tool is fast, responsive, and secure. The application is designed to be mobile-responsive and functions seamlessly on any modern web browser. By adhering to a strict single-file architecture, the tool loads instantly and works efficiently even on lower-bandwidth connections, providing a robust solution for data visualization tasks.
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