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Visualization can help explore the patterns of Euclidean rhythms. Here are some generated .png images using Python and pillow.

Let’s start by visualising one pattern at a time (pulses in light pink).

visualize_it(4, 2)

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visualize_it(6, 3)

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visualize_it(7, 3)

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visualize_it(8, 3)

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visualize_it(9, 4)

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Stacking patterns

Stacking patterns on top of one another can help us get a feel for how pulses get distributed into beats. When patterns with the same beats are stacked in a mirrored way, interesting geometric patterns are generated:

stacked_same_beat = [
    (16, 2),
    (16, 4),
    (16, 6),
    (16, 16),
    (16, 6),
    (16, 4),
    (16, 2)
]

visualize_many(stacked_same_beat, 600, 600, 'er_stacked_same_beats')

er_stacked_same_beats

How about rhythms with different beats? The results are more chaotic, but still patternish. This is what stacked Carnatic music might look like, you get different subdivisions of a time interval simultaneously

rhythms = [randpair(randint(3, 23)) for _ in range(20)]
visualize_many(rhythms, 600, 600, 'er_visualize_many')

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