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luismarques

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If you want to check how this idea is taken to way more sophisticated levels than this, then check out D's ranges and algorithms. This article only covers the equivalent of input iterators / ranges. You can also find in D sophisticated ways to deal with the last part of the article, regarding how to ascertain the different capabilities of your range/type, in ways that go beyond the traditional type system and OOP concepts.

edit: (also, D's lazy keyword, which performs the transformation described in the article automatically)

I used to use D for larger tasks and Python for quicker ones, like processing some text file and so on. One day I realized that I prefered using D even for those smaller tasks, where quick and dirty solutions would do. One thing that helped was that the standard algorithms (from the std.algorithm module) are really useful and compose very well, once you get to know them, and allow solving those kinds of tasks both quickly and efficiently.

Try programming with (std.)ranges and (std.)algorithm's. It's something completely refreshing, replacing a mess of loopy code with a clean pipeline of algorithms. The lazy nature of the standard algorithms and the clean syntax you get with the UFCS feature produce some really neat results. Even if you end up not using D any further, it can change your view of programming.

Isn't this (just) dithering noise?

AFAIK, the reason it's so effective in the example is that adding the noise helps the quantization process in the posterization better represent the original color spectrum. Without the dithering the quantization error can keep adding up in a way that the posterization filter cannot control (but which the image author can engineer to be problematic, as surely was the case here). With the dithering you have a statistical guarantee that the quantization errors average out.

Thanks! What other items often go together with these aluminum extrusions? Is there a place or a book to learn about this topic, or is it something that people only learn through experimentation and mimicking?

Do you know what those cloverleaf shaped metal beams are called, and how you can learn more about building hardware prototypes with those kinds of products?

I know very little about mechanical engineering and hardware prototyping, but I saw those metal thingies about a year ago in a DYI tinkerer community (it was used in a DYI 3D printer), and I have been wondering about that topic ever since.

I've done this exact test in Kerbal Space Program, except that I put the parachutes symmetrically. Also, the parachutes deploy at 500 meters by default. Looking at this and seeing the exact same behaviour makes the game feel really natural. Like if this was just an offline rendering of my in-game launch :-)

Interesting. Belgium shows up so small in the map in that page that I didn't even notice it was bright green, and therefore didn't include it in the title.

I implemented sugarscape some years ago and my findings contradicted the thesis of the book; instead of having some robust emergent results (like a Pareto distribution of wealth, IIRC), the results presented in the book could only be produced by carefully tweaking some parameters of the simulation. Furthermore, when implementing sugarscape I realized that the book didn't even specify what values were used for those parameters. While that shouldn't matter if the effects were robust, they were not. Unfortunately I don't remember the exact results, but I hope to look into this again when I have more free time. In sum, I thought the book was very interesting, but was quite disappointed when I tried to replicate (and extend) the experiments. Such is science... :-)

Consider adding a Firewire 800 SATA enclosure. Then you can externally add an SSD or an HD for increased throughput (e.g. put the root on the internal drive, your home on the external one; or using OS X logical partitioning to combine both drives into a single volume)

Dont bother with a top of the line SSD, since the FW 800 can be saturated by mid-range SSDs.

Actually, unofficially, the older iMacs support 6 GB (4+2) since the first aluminium iMac (mid 2007, I think)

I bought a 4 GB DDR2 DIMM for my Dad's mid 2007 iMac, installed it together with a 2 GB DIMM and it has been running non-stop for almost a year now, without any problems. DDR2 is now a bit expensive, due to being old, the 4 GB DIMM cost me around 50$ on eBay.