One of the cool new features of the JavaFX 2.2 developer preview release is a new Canvas node that allows you to do free drawing within an area on the JavaFX scene similar to the HTML 5 Canvas. You can download this release for Windows, Mac, and Linux from JavaFX Developer Preview.

Being adventurous, I decided to take the JavaFX Canvas for a spin around the block. In doing some searching for cool HTML 5 Canvas examples, I came across Dirk Weber's blog comparing performance of HTML5 Canvas, SVG and  Adobe Flash,An experiment: Canvas vs. SVG vs. Flash. This looked interesting for a Canvas beginner as I am, so I decided to copy his implementation and see how it runs in JavaFX.

This turned out to be pretty straight forward. Dirk's original JavaScript application for the HTML 5 Canvas contained a spirograph drawn at the top of the screen with 4 sliders beneath it for changing the number of rotations and particles  and the inner and outer radius for the spirograph. Also, at the top is a text display showing the frames-per-second after the image is drawn. By manipulating the slider properties, the spirograph is drawn differently and each time the performance is shown in frames per second. 

To do the same thing in JavaFX,  I first created a JavaFX Application class, with a Stage and Scene and placed the Canvas at the top of the scene with 4 sliders below it followed by a Label to report the frames per second as defined in Dirk's original JavaScript implementation. One change I made to Dirk's implementation was instead of using Arrays of doubles for points, I used the JavaFX Point2D class. 

My original goal was just to become familiar with the JavaFX Canvas object, but as I played around I noticed something about the performance. When I ran Dirk's HTML 5 and Flash version I would get a consistent frame-per-second rate of 50-70 fps when I adjusted the sliders (Mac OS X 10.7.4, 2.6 GHz Intel Core 2 Duo, 4 GB ram). However, when I ran my JavaFX version, the first time after starting, it drew the spirograph in the low 40s fps. But I noticed that when I adjusted the sliders, the performance got better. First adjustment, low 80s fps; fifth adjustment, mid 120s; a few more and I was getting 1000 fps, and eventually Infinity fps. I didn't believe the Infinity reading, so I debugged to the code, only to find out that it took less than a millisecond to calculate and draw the spirograph.

I assume that this behavior reflects the Hotspot compiler kicking in after a few iterations of the Spirograph calculation. But, it sure is fast. 

The JavaFX source can be downloaded from here: 

SpiroGraph.java

SpiroCanvas.java

Views: 3911

Comment

You need to be a member of Codetown to add comments!

Join Codetown

Happy 10th year, JCertif!

Notes

Welcome to Codetown!

Codetown is a social network. It's got blogs, forums, groups, personal pages and more! You might think of Codetown as a funky camper van with lots of compartments for your stuff and a great multimedia system, too! Best of all, Codetown has room for all of your friends.

When you create a profile for yourself you get a personal page automatically. That's where you can be creative and do your own thing. People who want to get to know you will click on your name or picture and…
Continue

Created by Michael Levin Dec 18, 2008 at 6:56pm. Last updated by Michael Levin May 4, 2018.

Looking for Jobs or Staff?

Check out the Codetown Jobs group.

 

Enjoy the site? Support Codetown with your donation.



InfoQ Reading List

How Agoda Unified Multiple Data Pipelines Into a Single Source of Truth

Agoda recently described how it consolidated multiple independent data pipelines into a centralized Apache Spark-based platform to eliminate inconsistencies in financial data. The company implemented a multi-layered quality framework that combines automated validations, machine-learning-based anomaly detection, and data contracts, while processing millions of daily booking transactions.

By Eran Stiller

AI-Powered Code Editor Cursor Introduces Dynamic Context Discovery to Improve Token-Efficiency

Cursor has introduces a new approach to minimize the context size of requests sent to large language models. Called dynamic context discovery, this method moves away from including large amounts of static context upfront, allowing the agent to dynamically retrieve only the information it needs. This reduces token usage and limits the inclusion of potentially confusing or irrelevant details.

By Sergio De Simone

Vercel Open-Sources Bash Tool for Context Retrieval Using Local Filesystems

Vercel has open-sourced bash-tool that provides a Bash execution engine for AI agents, enabling them to run filesystem-based commands to retrieve context for model prompts.

By Daniel Dominguez

Article: Platform-as-a-Product: Declarative Infrastructure for Developer Velocity

Declarative infrastructure config hides complexity, enabling developers to focus on application code. Unified YAML per service allows early cost validation, while independent CI with centralized CD balances team autonomy and deployment consistency. This standardized approach scales across organizations, making infrastructure invisible and operations automatic.

By Avinash Sabat

QCon London 2026: Practitioner-Led Tracks on Connectivity & Production AI Engineering

QCon London 2026 returns March 16–19 with 15 tracks for senior leads. Key sessions cover system integration via MCP, AI engineering, and debugging distributed systems. Explore modern security, Staff+ insights, and performance optimization with peer-led and practical discussions.

By Artenisa Chatziou

© 2026   Created by Michael Levin.   Powered by

Badges  |  Report an Issue  |  Terms of Service