More goodness from Dan Kaminsky: he's gone gold on "Paketto Keiretsu 1.0," a suite of TCP hacking tools, including this wild-ass visualizer.
Phentropy plots an arbitrarily large data source (of arbitrary data) onto a three dimensional volumetric matrix, which may then be parsed by OpenQVIS. Data mapping is accomplished by interpreting the file as a one dimensional stream of integers and progressively mapping quads in phase space. This process is reasonably straightforward: Take four numbers. Make X equal to the second number minus the first number. Make Y equal to the third number minus the second number. Then make Z equal to the last number minus the third number. Given the XYZ coordinate, draw a point. It turns out that many, many non-random datasets will have extraordinarily apparent regions in 3-space with increased density, reflecting common rates of change of the apparently random dataset. These regions are referred to as Strange Attractors, and can be used to predict future values from an otherwise random system.
