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)
visualize_it(6, 3)
visualize_it(7, 3)
visualize_it(8, 3)
visualize_it(9, 4)
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')
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')