March 2014
Beginner to intermediate
222 pages
4h 7m
English
So far, we have assumed that we have uniformly sampled 2D data; our data is sampled with a grid pattern. However, nonuniformly sampled data is very common. For instance, we might want to visualize measurements from weather stations. Weather stations are built wherever it is possible; they are laid out into a perfect grid. When sampling functions, we might use a sophisticated sampling process (adaptive sampling, quasi-random sampling, and so on) which does not produce grid layouts. Here, we show a simple way to deal with such 2D data.
The script draws the Mandelbrot set sampled from the same square as in the previous recipes. However, instead of using a regular grid sampling, we randomly sample the Mandelbrot ...
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