Mental Meta 2: Every Day I’m Shuffling | Dojo Of Lies. Interesting article about the effectiveness of various card shuffling methods. Particularly interesting for me is that the "Ripple-Shuffle" and "Mash-Shuffle" don't fare so well compared to a randomized "Pile-Shuffle". In MTG circles, the Riffle-Shuffle is often considered the gold standard - but it seems that a mixed method is actually more correct (which I probably also achieve with my Overhand-Shuffle and Mash-Shuffle).
mathematik
The Julia Language. Had I already mentioned that? Doesn't matter, it's worth repeating, especially since there's now also a small compact IDE for Julia.
Un peu de math...: Installing and using Sage just got even easier.. - and that's it, just a git pull and a make. Ok, and large amounts of coffee while waiting for the build. Way cool. If you don't know Sage: a mathematics package with similar complexity and focus as Mathematica, which is entirely based on open source projects that are all integrated with Python as the "glue" language.
FriCAS - an advanced CAS. I've lost track of it a bit - FriCAS is formerly Axiom, a quite extensive mathematics package like Mathematica, written in Common Lisp. Available for various systems, somewhat rough in the interface (just a command line), but very powerful. And somewhat more modern than perhaps Maxima (whereas for Maxima there are GUI options, I have no idea what FriCAS has to offer). Like every decent open source project, it is of course only a fork of a fork - under Open Axiom there is another project and under Axiom the original code is continued. Although for me, since Sage (and actually even much more since Anaconda and IPython Notebooks), all of this has become less relevant - in general, my requirements are at a much lower level and are already covered by the libraries available via IPython and Python. Of course, Mathematica and similar are still interesting - but the motivation to start the packages and to enter the rather different syntax world is rather low. Python has long since achieved the good-enough status.
Falling Faster than the Speed of Sound « Wolfram Blog. Interesting analysis of Felix Baumgartner's jump with Mathematica. I'm still in the play phase with Mathematica, so such things are quite exciting to get a better feel for how to approach problems with Mathematica. Working with Mathematica is quite different from normal programming environments.
XKCD plots in d3. And this in JavaScript and directly in the browser. Would be something for the math fans out there who always think they have to post plots.
Depth of field. Good explanation of what depth of field really means mathematically. Quite interesting to read if you don't yet fully understand the relationships (Hint: the primary factor is the imaging ratio, everything else is just a function of it).
The Julia Manual. Hmm, not yet sure what to think of this language, but it does sound interesting - a kind of Matlab, but based on LLVM and linguistically significantly renovated, with some interesting ideas (e.g., Julia expressions are stored internally in a Julia-specific data structure, so that real macros can be implemented).
StatsModels: Statistics in Python — statsmodels v0.3.0 documentation. Not my focus at the moment, but with this module you can examine numbers for their statistical model.
pandas: powerful Python data analysis toolkit — pandas v0.4.1 documentation. I think I haven't had this before, but it's quite interesting for number crunchers and list comparers: a quite powerful toolkit for analyzing large datasets, especially with handling missing data and aligning data on a common basis. Overall, not entirely uninteresting for a project at work where I frequently deal with larger datasets from external sources.
Python, SymPy and Quantum Physics. So far, NumPy/Matplotlib and SymPy have been two separate worlds for me - this blog post shows how to connect these two, meaning to work out your function definitions symbolically with SymPy and then transfer them to NumPy to perform numerical investigations. This is particularly interesting in connection with the qtconsole of ipython, because it only displays matplotlib plots inline, while SymPy plots open in a separate window (as they run via pyglet), which is rather inconvenient for saving the results of your work.
Issue 438 - pyglet - pyglet 1.1.3 fails on Snow Leopard. Oh man, this is really annoying. Pyglet is used by Sympy to output mathematical expressions. Unfortunately, Pyglet uses Carbon on OSX - and that is only 32-bit. And all my attempts to force something to 32-bit were in vain - actually, this can be done via environment variable or alternatively with the arch tool, but for some reason (probably due to internal indirect program calls) this is not done in Python as documented. Annoying, because Sympy has been on the list of things to try out for a while (not just since the QT console).
Orange - Data Mining Fruitful & Fun. Wow, just stumbled upon this, I didn't know it, I think. A GUI interface with a node interface for defining data analyses and visualizations, where these nodes are programmed in Python. The entire interface is built with QT, so there is also an OSX version of it. If you need to sift through larger amounts of data, this is definitely worth a look, especially since it is open source and you don't lose anything there.
Sage: Open Source Mathematics Software. Simply because I've been thinking about worksheet interfaces lately and considering what options there are - Sage is not just a math package, but primarily a huge collection of Python modules and a worksheet interface for Python as well. Okay, you use a web browser against a locally running web server, but still, it's actually a nice thing. And meanwhile, version 4.7 with many changes is out. And you can repeat good things. It's definitely cheaper than mathematics and I also like Python much better as a programming language. Since I will probably eventually install my own server to access notebooks from anywhere, here's a blogmark on a guide on how to build your own Sage server with Ubuntu.
Multiplication is easier when it's complex - too early to read it all now, but it looks interesting.
John Graham-Cumming: Data Visualization Disease - "Averages are fun because any fool can calculate them, but pity the fool who averages without thinking.".
Mandelbulb: The Unravelling of the Real 3D Mandelbrot Fractal - Mathematics can simply be beautiful.
FractalMaker - nice Flash visualization of fractals.
Abramowitz and Stegun: Handbook of Mathematical Functions - certainly interesting for all number crunchers. And since it's online, sometimes faster than a dead-tree version.
3 awesome free Math programs - Short introductions to the major players in the open source environment.
wxMaxima - a GUI for Maxima. Should also compile on OS X.
The Pi-Search Page - search for numbers in Pi up to 200 million digits. Has been around for 10 years, this time waster.
Pi - in pixels. One pixel per digit, the digit as color. Cool. (and yes, I know, only a snippet of Pi)
PHI, the golden ratio - various definitions of the golden ratio.