1.H. Driven IFS and Data Analysis

Driven IFS Rules

The difficulty with Stewart's experiment is that departures from uniform randomness in selecting the order of application of the rules are expressed in some non-uniform fill of the gasket.
We see some parts of the gasket filled more darkly, or some parts left empty. While it is possible to learn to parse these figures, it is much simpler to read the images generated by this IFS
T3(x, y) = (x/2, y/2) + (0, 1/2) T4(x, y) = (x/2, y/2) + (1/2, 1/2)
T1(x, y) = (x/2, y/2) T2(x, y) = (x/2, y/2) + (1/2, 0)
This IFS generates the filled-in unit square. Consequently, any departure from uniform randomness will be visible through departures from uniform fill of the square.
Here are some examples, all with 10000 points.
 
uniform random sequence   p1 = p4 = 0.1; p2 = p3 = 0.4
 
p1 = 0.1; p2 = p3 = p4 = 0.3   p1 = p3 = 0.1; p2 = p4 = 0.4

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