Hi there! I have been messing around with a snake game written in
If you are interested, you can check the results here.
Today I’d like to drop some photos of my recent holidays to Nepal here. All of these were taken using a Canon
40D with the
Canon 28-105 USM II f3.5-4.5. I decided to leave my other two lenses home (the wide angle lens
Sigma 10-20 1:4-5.6 EX DC HSM and the standard
Canon EF 50mm f/1.8 Mk II) because of the philosophy of the travel. We were mostly a backpacker group and we’d be moving around quite a lot, trekking the Himalayas and going to the jungle, so I figured the extra weight wasn’t worth it. Looking backwards, I regret not taking the wide angle lens, for some of the landscapes we could behold were truly amazing.
A couple of posts ago I mentioned I would write a few lines about my experience with the migration of my RTS engine from Slick to libgdx and that’s what I’ll do in this post. I’ll be talking very lightly on some issues such as the code structure, the rendering process, the camera, etc. If you need a starting tutorial please refer to the official documentation, this is not what you are looking for. I’m just trying to give my impressions in the migration process I had to undertake. But first I want to back up a little and give a quick overview of both libraries.
As you may have noted, I updated the look and feel of the website to a more sober, greenish and polished design. The moon in the header has been replaced by a jumping monkey, which is always likeable. Regarding performance, this new site has less and smaller CSS files and less images and therefore it loads faster. Additionally, it uses HTML5, which is good. I also took the opportunity to update to the latest version of drupal and make use of the newer ZEN base theme. Here there’s a side-by-side comparison between the old and the new styles.
Today I want to introduce a very different piece of software I have been putting together lately. It is a RTS (real time strategy) engine. I started playing with the idea as a time killer some years ago, kicking off the development with a fast version of the A* pathfinding algorithm backed not by a grid (as usual) but by a quadtree. Quadtrees make pathfinding super-fast because of their hierarchical division of space and their adaptive partition sizes. Even though I used visibility graphs to store the navigable nodes from one given point, quadtrees are also fast for checking the properties/elements of a position’s surroundings, for child nodes are always spatially contained in parent nodes.