Notes on codes, projects and everything
Traversing a tree structure often involves writing a recursive function. However, Python isn’t the best language for this purpose. Therefore I started flattening the tree into a key-value dictonary structure. Logically it is still a tree, but it is physically stored as a dictionary. Therefore it is now easier to write a simple loop to traverse it.
In the previous post, I re-implemented Annoy in 2D with some linear algebra maths. Then I spent some time going through some tutorial on vectors, and expanded the script to handle data in 3D and more. So instead of finding gradient, the perpendicular line in the middle of two points, I construct a plane, and find the distance between it and points to construct the tree.
Recently I switched my search code to Annoy because the input dataset is huge (7.5mil records with 20k dictionary count). It wasn’t without issues though, however I would probably talk about it next time. In order to figure out what each parameters meant, I spent some time watching through the talk given by the author @fulhack.
Implementing a Information Retrieval system is a fun thing to do. However, doing it efficiently is not (at least to me). So my first few attempts didn’t really end well (mostly uses just Go/golang with some bash tricks here and there, with or without a database). Then I jumped back to Python, which I am more familiar with and was very surprised with all the options available. So I started with Pandas and Scikit-learn combo.
This is basically a small incremental update to my script published here. For some reason, the previous version of the script didn’t really work, so this release should fix the problem. Besides fixing the problem where the daemon did not actually launched at start up, I have added a settings applet for this script as well.
The Nand2Tetris part I at coursera is very much my first completed course. It was so fun to actually work through the material and it feels amazing to know how simple it is to actually build a computer from scratch. While it is simple, it doesn’t mean the course itself is easy though. I was struggling to get the CPU wired up properly that I spent two to three days just to get it working.
Another half a day spent on figuring out how to package my daemon properly, fortunately with help from friends over at #harmattan IRC channel as well as cckwes, I finally get the deb package generated properly. So just a quick reminder on what my daemon does, it is just a quick hack that toggles the ‘allow background connections’ on and off depending which kind of data network a user is connected to. Apparently I am not the only one who are looking for this, as a feature request was filed long long time ago.
I like how Kohana 3 organizes the classes, and I thought the same thing may be applied to my Zend Framework experimental project. Basically what this means is that I can name the controller class according to PEAR naming convention, and deduce the location of the file by just parsing the class name.
I was invited to try Go (the programming language, not that board game) a few months ago, however I didn’t complete back then. The main reason was because it felt raw, compared to other languages that I know a fair bit better (for example Ruby). There was no much syntatic sugar around, and getting some work done with it feels “dirty”.