Actionscript3, Flash, Java, C#, C++, Algorithms & Imageprocessing
The full source code of Apparat is now available at GoogleCode. It is the whole framework behind TDSI and Reducer.
Apparat is released under the GNU Lesser General Public License. Please contact me if you want to contribute to this project. Maybe someone is interested in writing an Ant task for Reducer? I am also happy to receive feedback if you have used the framework to build something cool with it.
Please join the Apparat Discussion Group if you are interested in collaboration.
Another spinoff from my current library to optimize SWF/SWC files. Reducer is a tool that will make SWF and SWC files significantly smaller. There is currently a huge problem with filesizes. If you use the [Embed] tag with PNG images they are not compressed at all. For the Hobnox AudioTool we have been using the Flash IDE to export all graphics so that they are smaller which was a pain.
Now with Reducer you are safe to use [Embed] and then run the tool afterwards. It will compress all lossless images and make them lossy. But usually a PNG can be compressed at 100% JPEG quality and you will still safe a lot of data.
Note: You will not loose alpha transparency when using Reducer. The SWF file format allows us to use a special compression where a PNG gets split up into its color and alpha channels. The color channels are encoded using the traditional JPEG algorithm with adjustable quality while the alpha channel is handled seperately. Transparency is always stored in a lossless fashion which means even with a low JPEG quality you will not get any compression artifacts for the alpha channel.
Update: Reducer is now open source!
First of all I think I have to clarify at least one thing. I have criticised Adobe in the past for a lof of reasons. Not because I do not like them or the technologies they produce but because I want to improve the Flash Platform. This is of course pure self-interest since Flash is a key technology for the Hobnox AudioTool.
Continue reading ‘This is an outrage!’
Everyone likes examples. So here are three examples using TDSI. The archive includes a ready-to-go FDT project with post-compile ANT tasks configured.
This is the old code of the already optimized attractor using the Memory API instead of a Vector.<uint>.
In this case there exists no Particle class at all and no linked list. The particle information is stored inside the memory as well. Particles are extended to a fourth value so indexing a particle can be done with a simple bitshift which is very fast.
The last example uses float instead of double values for the particles. The framerate stays the same which is really cool because the memory usage drops. Before a particle consisted of four doubles which is a total of 4 * 8b = 32b. In this example each particle takes up only 16b. There the memory difference is 0x4B0000b which is about 4.7mb in total.
And also the first version needs about 20mb on my machine which means about 12mb of RAM are not wasted. Pretty cool when thinking about devices with less memory.
By the way I just stumpled across a bug when using [Embed]. Hopefully it will be easy to fix.
I am definitly not good at choosing names for software projects. However TurboDieselSportInjection is a release of my experiments from yesterday. It is a spinoff from the whole framework and allows you to inline __bytecode and of course to use the new Memory API.
Hopefully you are kind enough to provide me with some feedback. I am especially interested in Exceptions that occur when reading or writing ABC files. Have fun!
Update: TDSI is now open source!
