Sunflower

Posted on May 20, 2025

My last mandala moved the data structure that defines the mandala from client side javascript to server side python. Here, the text (this text) and the title are also in serverside python. This keeps all the post specific changes in one place (e.g. mandala17.py), standardizes the html for a post, and is a step towards moving the post text and data into a database.

Python generated data

Posted on May 11, 2025

I'm still making mandalas that are fun for me. But this mandala is the first one that is built from a dataset that was generated in Python on the server. This is a big milestone towards making them into data visualizations that describe datasets.

Interesting white space, interactivity and data driven(ness)

Posted on May 3, 2025

Making mandalas that I like

For this mandala I played around a little with the white space. In the center the white space makes a flower, or sun shape, and around the curved droplets some white leaf or petal shapes emerge.

Moving towards mandala inspired data visualizations

The interactions are working pretty well now. Using the zoom buttons you can zoom in much further than the browser alone will let you. And, introducing dragging! You can now move the image around by grabbing and dragging it.
Finally, this is the first of my mandalas that is data driven. The mandala is generated from a JSON data structure instead of being defined with lines of software. Notice that every shape now has it's own description. Those descriptions are in the data, not written in lines of software. The data structure for this mandala is defined in javascript, on the client side. So the next step is to send the json data structure from the server, created in python and representative of a dataset.

Images for performance

Posted on April 22, 2025

This mandala looks similar to the last one. But, to draw that one, the browser uses html that describes 3,720 elements. To draw this one, the browser uses html that describes 16 elements. The software now draws the mandala into an image, then uses that image 16 times. This will help performance in the future when we want to represent a large amount of data. The software will be able to zoom in and out of mandalas that represent clusters of data.