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.
I came across a video on Youtube on Pi day. Coincidently it was about estimating the value of Pi produced by Matt Parker aka standupmaths. While I am not quite interested in knowing the best way to estimate Pi, I am quite interested in the algorithm he showed in the video however. Specifically, I am interested to find out how easy it is to implement in Python.
It is very much expected that there will be endless stream of new (and often times better) tools introduced to solve the same set of problems. While I am slowly resuming my programming work, and in the process of reviving my very much dead postgrad project, I found some alternative to the tools I had used in the past. I suppose I shall just jot them down here so that there’s a reference for later use.
Recently I am involved in developing some small modules for a enterprise class website using CodeIgniter (CI). There was no restriction given on which framework should I use for the development and I chose CI as I learned a bit on it (when I was considering whether to shift my personal development project). Of course there are other reasons why I chose to learn CI, for example the superior documentation and screencasts available.
I am not going to waste time telling stories that inspire this post, as most people would have already heard something similar constantly. This is not a mythbuster kinda post, so don’t expect a scientific proof to the answer of the question. Instead, through this post, I hope to break the impression that claims composing a HTML document is difficult.
Although my supervisor strongly recommend using JENA for RDF related work, but as I really don’t like Java (just personal preference), and wouldn’t want to install JRE/JVM (whatever it is called) at my shared server account, so I went to look for an alternative. After spending some time searching, I found this library called Redland and it provides binding for my current favorite language — PHP, so I decided to use this for my RDF work.